diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/LICENSE.txt b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2ee057eeb0bc419bc18d1c5bd9a0683d4b1a6815
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/LICENSE.txt
@@ -0,0 +1,914 @@
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diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/include/numpy/libdivide/LICENSE.txt b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/include/numpy/libdivide/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..375a7faa07019536b6b9aad67949fbfa5b4c12db
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/include/numpy/libdivide/LICENSE.txt
@@ -0,0 +1,21 @@
+  zlib License
+  ------------
+
+  Copyright (C) 2010 - 2019 ridiculous_fish, <libdivide@ridiculousfish.com>
+  Copyright (C) 2016 - 2019 Kim Walisch, <kim.walisch@gmail.com>
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/common/pythoncapi-compat/COPYING b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/common/pythoncapi-compat/COPYING
new file mode 100644
index 0000000000000000000000000000000000000000..6a223f9f6b2d351e52b2112af654c49cdcd742df
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/common/pythoncapi-compat/COPYING
@@ -0,0 +1,14 @@
+BSD Zero Clause License
+
+Copyright Contributors to the pythoncapi_compat project.
+
+Permission to use, copy, modify, and/or distribute this software for any
+purpose with or without fee is hereby granted.
+
+THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
+INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
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diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/highway/LICENSE b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/highway/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..70cc735458ff85838fb08a61148eb8c9fe4ef8ad
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/highway/LICENSE
@@ -0,0 +1,371 @@
+This project is primarily dual-licensed under your choice of either the Apache
+License 2.0 or the BSD 3-Clause License.
+
+The following files are licensed under different terms:
+*   hwy/contrib/random/random-inl.h: CC0 1.0 Universal
+
+The full texts of all applicable licenses are included below, separated by
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+    this list of conditions and the following disclaimer in the documentation
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+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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+
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+    surrendered, licensed or otherwise affected by this document.
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+ c. Affirmer disclaims responsibility for clearing rights of other persons
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\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/multiarray/dragon4_LICENSE.txt b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/multiarray/dragon4_LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cb24e976e19f1146d0ca8ae8ad7f64d125b71e34
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/multiarray/dragon4_LICENSE.txt
@@ -0,0 +1,27 @@
+Copyright (c) 2014 Ryan Juckett
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to
+deal in the Software without restriction, including without limitation the
+rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+sell copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+IN THE SOFTWARE.
+
+dragon4.c|h h contains a modified version of Ryan Juckett's Dragon4
+implementation, obtained from https://www.ryanjuckett.com,
+which has been ported from C++ to C and which has
+modifications specific to printing floats in numpy.
+
+Ryan Juckett's original code was under the Zlib license; he gave numpy
+permission to include it under the MIT license instead.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/npysort/x86-simd-sort/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/npysort/x86-simd-sort/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..99399cd4ec783c1c2af00c6e38357fb518d7b250
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/npysort/x86-simd-sort/LICENSE.md
@@ -0,0 +1,28 @@
+BSD 3-Clause License
+
+Copyright (c) 2022, Intel. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/umath/svml/LICENSE b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/umath/svml/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..51b8406fa98999f72f20a5cc72d321188b660eb0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/_core/src/umath/svml/LICENSE
@@ -0,0 +1,30 @@
+Copyright (c) 2005-2021, NumPy Developers.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+       notice, this list of conditions and the following disclaimer.
+
+    * Redistributions in binary form must reproduce the above
+       copyright notice, this list of conditions and the following
+       disclaimer in the documentation and/or other materials provided
+       with the distribution.
+
+    * Neither the name of the NumPy Developers nor the names of any
+       contributors may be used to endorse or promote products derived
+       from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/fft/pocketfft/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/fft/pocketfft/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..79b818c5e05787714dfea4bb234c8b2b0ef0b064
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/fft/pocketfft/LICENSE.md
@@ -0,0 +1,25 @@
+Copyright (C) 2010-2018 Max-Planck-Society
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+* Redistributions in binary form must reproduce the above copyright notice, this
+  list of conditions and the following disclaimer in the documentation and/or
+  other materials provided with the distribution.
+* Neither the name of the copyright holder nor the names of its contributors may
+  be used to endorse or promote products derived from this software without
+  specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/linalg/lapack_lite/LICENSE.txt b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/linalg/lapack_lite/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4d23316b6739404951c27f97b9098612931d4247
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/linalg/lapack_lite/LICENSE.txt
@@ -0,0 +1,48 @@
+Copyright (c) 1992-2013 The University of Tennessee and The University
+                        of Tennessee Research Foundation.  All rights
+                        reserved.
+Copyright (c) 2000-2013 The University of California Berkeley. All
+                        rights reserved.
+Copyright (c) 2006-2013 The University of Colorado Denver.  All rights
+                        reserved.
+
+$COPYRIGHT$
+
+Additional copyrights may follow
+
+$HEADER$
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+- Redistributions of source code must retain the above copyright
+  notice, this list of conditions and the following disclaimer.
+
+- Redistributions in binary form must reproduce the above copyright
+  notice, this list of conditions and the following disclaimer listed
+  in this license in the documentation and/or other materials
+  provided with the distribution.
+
+- Neither the name of the copyright holders nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+The copyright holders provide no reassurances that the source code
+provided does not infringe any patent, copyright, or any other
+intellectual property rights of third parties.  The copyright holders
+disclaim any liability to any recipient for claims brought against
+recipient by any third party for infringement of that parties
+intellectual property rights.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/ma/LICENSE b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/ma/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..f165a0f6dbf57b89e2f6e23b9f042750dde3caab
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/ma/LICENSE
@@ -0,0 +1,24 @@
+* Copyright (c) 2006, University of Georgia and Pierre G.F. Gerard-Marchant
+* All rights reserved.
+* Redistribution and use in source and binary forms, with or without
+* modification, are permitted provided that the following conditions are met:
+*
+*     * Redistributions of source code must retain the above copyright
+*       notice, this list of conditions and the following disclaimer.
+*     * Redistributions in binary form must reproduce the above copyright
+*       notice, this list of conditions and the following disclaimer in the
+*       documentation and/or other materials provided with the distribution.
+*     * Neither the name of the University of Georgia nor the
+*       names of its contributors may be used to endorse or promote products
+*       derived from this software without specific prior written permission.
+*
+* THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+* DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY
+* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..4f9513f1eddbc5aba61a8a1ef8f64869b2b4a917
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/LICENSE.md
@@ -0,0 +1,71 @@
+**This software is dual-licensed under the The University of Illinois/NCSA
+Open Source License (NCSA) and The 3-Clause BSD License**
+
+# NCSA Open Source License
+**Copyright (c) 2019 Kevin Sheppard. All rights reserved.**
+
+Developed by: Kevin Sheppard (<kevin.sheppard@economics.ox.ac.uk>,
+<kevin.k.sheppard@gmail.com>)
+[http://www.kevinsheppard.com](http://www.kevinsheppard.com)
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal with
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+Redistributions of source code must retain the above copyright notice, this
+list of conditions and the following disclaimers.
+
+Redistributions in binary form must reproduce the above copyright notice, this
+list of conditions and the following disclaimers in the documentation and/or
+other materials provided with the distribution.
+
+Neither the names of Kevin Sheppard, nor the names of any contributors may be
+used to endorse or promote products derived from this Software without specific
+prior written permission.
+
+**THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH
+THE SOFTWARE.**
+
+
+# 3-Clause BSD License
+**Copyright (c) 2019 Kevin Sheppard. All rights reserved.**
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice,
+   this list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its contributors
+   may be used to endorse or promote products derived from this software
+   without specific prior written permission.
+
+**THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+THE POSSIBILITY OF SUCH DAMAGE.**
+
+# Components
+
+Many parts of this module have been derived from original sources, 
+often the algorithm's designer. Component licenses are located with 
+the component code.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/distributions/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/distributions/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..3d693b8e9c756567fa50cc8b9ec2f6590396c0d6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/distributions/LICENSE.md
@@ -0,0 +1,61 @@
+## NumPy
+
+Copyright (c) 2005-2017, NumPy Developers.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+* Redistributions of source code must retain the above copyright
+   notice, this list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above
+   copyright notice, this list of conditions and the following
+   disclaimer in the documentation and/or other materials provided
+   with the distribution.
+
+* Neither the name of the NumPy Developers nor the names of any
+   contributors may be used to endorse or promote products derived
+   from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+## Julia
+
+The ziggurat methods were derived from Julia.
+
+Copyright (c) 2009-2019: Jeff Bezanson, Stefan Karpinski, Viral B. Shah,
+and other contributors:
+
+https://github.com/JuliaLang/julia/contributors
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be
+included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
+LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/mt19937/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/mt19937/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..364e728d996d5cf4ca5251560050f6246a435601
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/mt19937/LICENSE.md
@@ -0,0 +1,61 @@
+# MT19937
+
+Copyright (c) 2003-2005, Jean-Sebastien Roy (js@jeannot.org)
+
+The rk_random and rk_seed functions algorithms and the original design of
+the Mersenne Twister RNG:
+
+  Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
+  All rights reserved.
+
+  Redistribution and use in source and binary forms, with or without
+  modification, are permitted provided that the following conditions
+  are met:
+
+  1. Redistributions of source code must retain the above copyright
+  notice, this list of conditions and the following disclaimer.
+
+  2. Redistributions in binary form must reproduce the above copyright
+  notice, this list of conditions and the following disclaimer in the
+  documentation and/or other materials provided with the distribution.
+
+  3. The names of its contributors may not be used to endorse or promote
+  products derived from this software without specific prior written
+  permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER
+OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+Original algorithm for the implementation of rk_interval function from
+Richard J. Wagner's implementation of the Mersenne Twister RNG, optimised by
+Magnus Jonsson.
+
+Constants used in the rk_double implementation by Isaku Wada.
+
+Permission is hereby granted, free of charge, to any person obtaining a
+copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be included
+in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/pcg64/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/pcg64/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..da7487a3110780bd9bc1e682d2a0c4f8b5f1e9e1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/pcg64/LICENSE.md
@@ -0,0 +1,22 @@
+# PCG64
+
+## The MIT License
+
+PCG Random Number Generation for C.
+
+Copyright 2014 Melissa O'Neill <oneill@pcg-random.org>
+
+Permission is hereby granted, free of charge, to any person obtaining 
+a copy of this software and associated documentation files (the "Software"), 
+to deal in the Software without restriction, including without limitation 
+the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in 
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS 
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR 
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER 
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN 
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/philox/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/philox/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..c815ae29364457c0bdccf417d170c2dd8696e09a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/philox/LICENSE.md
@@ -0,0 +1,31 @@
+# PHILOX
+
+Copyright 2010-2012, D. E. Shaw Research.
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+* Redistributions of source code must retain the above copyright
+  notice, this list of conditions, and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright
+  notice, this list of conditions, and the following disclaimer in the
+  documentation and/or other materials provided with the distribution.
+
+* Neither the name of D. E. Shaw Research nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/sfc64/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/sfc64/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..84707451a9f5c6432ef3a959f6c60d401327b981
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/sfc64/LICENSE.md
@@ -0,0 +1,27 @@
+# SFC64
+
+## The MIT License
+
+Adapted from a C++ implementation of Chris Doty-Humphrey's SFC PRNG.
+
+https://gist.github.com/imneme/f1f7821f07cf76504a97f6537c818083
+
+Copyright (c) 2018 Melissa E. O'Neill
+
+Permission is hereby granted, free of charge, to any person obtaining a
+copy of this software and associated documentation files (the "Software"),
+to deal in the Software without restriction, including without limitation
+the rights to use, copy, modify, merge, publish, distribute, sublicense,
+and/or sell copies of the Software, and to permit persons to whom the
+Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+DEALINGS IN THE SOFTWARE.
diff --git a/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/splitmix64/LICENSE.md b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/splitmix64/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..fb75aa5b380f24d69518397ed93da5317c9da113
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy-2.4.4.dist-info/licenses/numpy/random/src/splitmix64/LICENSE.md
@@ -0,0 +1,9 @@
+# SPLITMIX64
+
+Written in 2015 by Sebastiano Vigna (vigna@acm.org)
+
+To the extent possible under law, the author has dedicated all copyright
+and related and neighboring rights to this software to the public domain
+worldwide. This software is distributed without any warranty.
+
+See <http://creativecommons.org/publicdomain/zero/1.0/>.
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy/char/__init__.py b/python/user_packages/Python313/site-packages/numpy/char/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a360f7f74cd0c9ce96997d659353af7fa2b1555
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/char/__init__.py
@@ -0,0 +1,2 @@
+from numpy._core.defchararray import *
+from numpy._core.defchararray import __all__, __doc__
diff --git a/python/user_packages/Python313/site-packages/numpy/char/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/char/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..c736eb28b5638e9db16c58c466c5ec45fa081dca
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/char/__init__.pyi
@@ -0,0 +1,111 @@
+from numpy._core.defchararray import (
+    add,
+    array,
+    asarray,
+    capitalize,
+    center,
+    chararray,
+    compare_chararrays,
+    count,
+    decode,
+    encode,
+    endswith,
+    equal,
+    expandtabs,
+    find,
+    greater,
+    greater_equal,
+    index,
+    isalnum,
+    isalpha,
+    isdecimal,
+    isdigit,
+    islower,
+    isnumeric,
+    isspace,
+    istitle,
+    isupper,
+    join,
+    less,
+    less_equal,
+    ljust,
+    lower,
+    lstrip,
+    mod,
+    multiply,
+    not_equal,
+    partition,
+    replace,
+    rfind,
+    rindex,
+    rjust,
+    rpartition,
+    rsplit,
+    rstrip,
+    split,
+    splitlines,
+    startswith,
+    str_len,
+    strip,
+    swapcase,
+    title,
+    translate,
+    upper,
+    zfill,
+)
+
+__all__ = [
+    "equal",
+    "not_equal",
+    "greater_equal",
+    "less_equal",
+    "greater",
+    "less",
+    "str_len",
+    "add",
+    "multiply",
+    "mod",
+    "capitalize",
+    "center",
+    "count",
+    "decode",
+    "encode",
+    "endswith",
+    "expandtabs",
+    "find",
+    "index",
+    "isalnum",
+    "isalpha",
+    "isdigit",
+    "islower",
+    "isspace",
+    "istitle",
+    "isupper",
+    "join",
+    "ljust",
+    "lower",
+    "lstrip",
+    "partition",
+    "replace",
+    "rfind",
+    "rindex",
+    "rjust",
+    "rpartition",
+    "rsplit",
+    "rstrip",
+    "split",
+    "splitlines",
+    "startswith",
+    "strip",
+    "swapcase",
+    "title",
+    "translate",
+    "upper",
+    "zfill",
+    "isnumeric",
+    "isdecimal",
+    "array",
+    "asarray",
+    "compare_chararrays",
+    "chararray",
+]
diff --git a/python/user_packages/Python313/site-packages/numpy/core/__init__.py b/python/user_packages/Python313/site-packages/numpy/core/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5bd55086d0f0e6d4b605a1217421d5a29ccf10b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/__init__.py
@@ -0,0 +1,33 @@
+"""
+The `numpy.core` submodule exists solely for backward compatibility
+purposes. The original `core` was renamed to `_core` and made private.
+`numpy.core` will be removed in the future.
+"""
+from numpy import _core
+
+from ._utils import _raise_warning
+
+
+# We used to use `np.core._ufunc_reconstruct` to unpickle.
+# This is unnecessary, but old pickles saved before 1.20 will be using it,
+# and there is no reason to break loading them.
+def _ufunc_reconstruct(module, name):
+    # The `fromlist` kwarg is required to ensure that `mod` points to the
+    # inner-most module rather than the parent package when module name is
+    # nested. This makes it possible to pickle non-toplevel ufuncs such as
+    # scipy.special.expit for instance.
+    mod = __import__(module, fromlist=[name])
+    return getattr(mod, name)
+
+
+# force lazy-loading of submodules to ensure a warning is printed
+
+__all__ = ["arrayprint", "defchararray", "_dtype_ctypes", "_dtype",  # noqa: F822
+           "einsumfunc", "fromnumeric", "function_base", "getlimits",
+           "_internal", "multiarray", "_multiarray_umath", "numeric",
+           "numerictypes", "overrides", "records", "shape_base", "umath"]
+
+def __getattr__(attr_name):
+    attr = getattr(_core, attr_name)
+    _raise_warning(attr_name)
+    return attr
diff --git a/python/user_packages/Python313/site-packages/numpy/core/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/core/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_dtype.py b/python/user_packages/Python313/site-packages/numpy/core/_dtype.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bda9108c55c3e34d06dc41ed6631848070655c0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/_dtype.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import _dtype
+
+    from ._utils import _raise_warning
+    ret = getattr(_dtype, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core._dtype' has no attribute {attr_name}")
+    _raise_warning(attr_name, "_dtype")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_dtype.pyi b/python/user_packages/Python313/site-packages/numpy/core/_dtype.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_dtype_ctypes.py b/python/user_packages/Python313/site-packages/numpy/core/_dtype_ctypes.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e82bed72241bc37b0744907036071ffe073172e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/_dtype_ctypes.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import _dtype_ctypes
+
+    from ._utils import _raise_warning
+    ret = getattr(_dtype_ctypes, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core._dtype_ctypes' has no attribute {attr_name}")
+    _raise_warning(attr_name, "_dtype_ctypes")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_dtype_ctypes.pyi b/python/user_packages/Python313/site-packages/numpy/core/_dtype_ctypes.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_internal.py b/python/user_packages/Python313/site-packages/numpy/core/_internal.py
new file mode 100644
index 0000000000000000000000000000000000000000..f9c3d211d4344ac20f202f257f8b45ef5b009253
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/_internal.py
@@ -0,0 +1,27 @@
+from numpy._core import _internal
+
+
+# Build a new array from the information in a pickle.
+# Note that the name numpy.core._internal._reconstruct is embedded in
+# pickles of ndarrays made with NumPy before release 1.0
+# so don't remove the name here, or you'll
+# break backward compatibility.
+def _reconstruct(subtype, shape, dtype):
+    from numpy import ndarray
+    return ndarray.__new__(subtype, shape, dtype)
+
+
+# Pybind11 (in versions <= 2.11.1) imports _dtype_from_pep3118 from the
+# _internal submodule, therefore it must be importable without a warning.
+_dtype_from_pep3118 = _internal._dtype_from_pep3118
+
+def __getattr__(attr_name):
+    from numpy._core import _internal
+
+    from ._utils import _raise_warning
+    ret = getattr(_internal, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core._internal' has no attribute {attr_name}")
+    _raise_warning(attr_name, "_internal")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_multiarray_umath.py b/python/user_packages/Python313/site-packages/numpy/core/_multiarray_umath.py
new file mode 100644
index 0000000000000000000000000000000000000000..7c188fd9158e88eae0dcf8b555c9364f8d4ccbd1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/_multiarray_umath.py
@@ -0,0 +1,57 @@
+from numpy import ufunc
+from numpy._core import _multiarray_umath
+
+for item in _multiarray_umath.__dir__():
+    # ufuncs appear in pickles with a path in numpy.core._multiarray_umath
+    # and so must import from this namespace without warning or error
+    attr = getattr(_multiarray_umath, item)
+    if isinstance(attr, ufunc):
+        globals()[item] = attr
+
+
+def __getattr__(attr_name):
+    from numpy._core import _multiarray_umath
+
+    from ._utils import _raise_warning
+
+    if attr_name in {"_ARRAY_API", "_UFUNC_API"}:
+        import sys
+        import textwrap
+        import traceback
+
+        from numpy.version import short_version
+
+        msg = textwrap.dedent(f"""
+            A module that was compiled using NumPy 1.x cannot be run in
+            NumPy {short_version} as it may crash. To support both 1.x and 2.x
+            versions of NumPy, modules must be compiled with NumPy 2.0.
+            Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
+
+            If you are a user of the module, the easiest solution will be to
+            downgrade to 'numpy<2' or try to upgrade the affected module.
+            We expect that some modules will need time to support NumPy 2.
+
+            """)
+        tb_msg = "Traceback (most recent call last):"
+        for line in traceback.format_stack()[:-1]:
+            if "frozen importlib" in line:
+                continue
+            tb_msg += line
+
+        # Also print the message (with traceback).  This is because old versions
+        # of NumPy unfortunately set up the import to replace (and hide) the
+        # error.  The traceback shouldn't be needed, but e.g. pytest plugins
+        # seem to swallow it and we should be failing anyway...
+        sys.stderr.write(msg + tb_msg)
+        raise ImportError(msg)
+
+    ret = getattr(_multiarray_umath, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            "module 'numpy.core._multiarray_umath' has no attribute "
+            f"{attr_name}")
+    _raise_warning(attr_name, "_multiarray_umath")
+    return ret
+
+
+del _multiarray_umath, ufunc
diff --git a/python/user_packages/Python313/site-packages/numpy/core/_utils.py b/python/user_packages/Python313/site-packages/numpy/core/_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..d94f39bcb3cc155ce6534c8c81d06ef0e1ccf63e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/_utils.py
@@ -0,0 +1,21 @@
+import warnings
+
+
+def _raise_warning(attr: str, submodule: str | None = None) -> None:
+    new_module = "numpy._core"
+    old_module = "numpy.core"
+    if submodule is not None:
+        new_module = f"{new_module}.{submodule}"
+        old_module = f"{old_module}.{submodule}"
+    warnings.warn(
+        f"{old_module} is deprecated and has been renamed to {new_module}. "
+        "The numpy._core namespace contains private NumPy internals and its "
+        "use is discouraged, as NumPy internals can change without warning in "
+        "any release. In practice, most real-world usage of numpy.core is to "
+        "access functionality in the public NumPy API. If that is the case, "
+        "use the public NumPy API. If not, you are using NumPy internals. "
+        "If you would still like to access an internal attribute, "
+        f"use {new_module}.{attr}.",
+        DeprecationWarning,
+        stacklevel=3
+    )
diff --git a/python/user_packages/Python313/site-packages/numpy/core/arrayprint.py b/python/user_packages/Python313/site-packages/numpy/core/arrayprint.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f3bcf8acb1f10bf3c595e3ab7a886ac16ba31a1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/arrayprint.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import arrayprint
+
+    from ._utils import _raise_warning
+    ret = getattr(arrayprint, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.arrayprint' has no attribute {attr_name}")
+    _raise_warning(attr_name, "arrayprint")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/defchararray.py b/python/user_packages/Python313/site-packages/numpy/core/defchararray.py
new file mode 100644
index 0000000000000000000000000000000000000000..da288809e79a14a83709774404eec5281b05c9aa
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/defchararray.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import defchararray
+
+    from ._utils import _raise_warning
+    ret = getattr(defchararray, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.defchararray' has no attribute {attr_name}")
+    _raise_warning(attr_name, "defchararray")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/einsumfunc.py b/python/user_packages/Python313/site-packages/numpy/core/einsumfunc.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1e974e0b977a695423bcf2c469553b70b13f497
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/einsumfunc.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import einsumfunc
+
+    from ._utils import _raise_warning
+    ret = getattr(einsumfunc, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.einsumfunc' has no attribute {attr_name}")
+    _raise_warning(attr_name, "einsumfunc")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/fromnumeric.py b/python/user_packages/Python313/site-packages/numpy/core/fromnumeric.py
new file mode 100644
index 0000000000000000000000000000000000000000..e50084f7f8cd5cc1be1bb49de57f9d189fcc7fe8
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/fromnumeric.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import fromnumeric
+
+    from ._utils import _raise_warning
+    ret = getattr(fromnumeric, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.fromnumeric' has no attribute {attr_name}")
+    _raise_warning(attr_name, "fromnumeric")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/function_base.py b/python/user_packages/Python313/site-packages/numpy/core/function_base.py
new file mode 100644
index 0000000000000000000000000000000000000000..88fc2268b66064714fdd87efa17c1b2137c75c1b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/function_base.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import function_base
+
+    from ._utils import _raise_warning
+    ret = getattr(function_base, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.function_base' has no attribute {attr_name}")
+    _raise_warning(attr_name, "function_base")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/getlimits.py b/python/user_packages/Python313/site-packages/numpy/core/getlimits.py
new file mode 100644
index 0000000000000000000000000000000000000000..65c1107a349064278717f15f25206286d0645ef9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/getlimits.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import getlimits
+
+    from ._utils import _raise_warning
+    ret = getattr(getlimits, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.getlimits' has no attribute {attr_name}")
+    _raise_warning(attr_name, "getlimits")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/multiarray.py b/python/user_packages/Python313/site-packages/numpy/core/multiarray.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb604a89dd0096040bf77e02302ce86a118e1082
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/multiarray.py
@@ -0,0 +1,25 @@
+from numpy._core import multiarray
+
+# these must import without warning or error from numpy.core.multiarray to
+# support old pickle files
+for item in ["_reconstruct", "scalar"]:
+    globals()[item] = getattr(multiarray, item)
+
+# Pybind11 (in versions <= 2.11.1) imports _ARRAY_API from the multiarray
+# submodule as a part of NumPy initialization, therefore it must be importable
+# without a warning.
+_ARRAY_API = multiarray._ARRAY_API
+
+def __getattr__(attr_name):
+    from numpy._core import multiarray
+
+    from ._utils import _raise_warning
+    ret = getattr(multiarray, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.multiarray' has no attribute {attr_name}")
+    _raise_warning(attr_name, "multiarray")
+    return ret
+
+
+del multiarray
diff --git a/python/user_packages/Python313/site-packages/numpy/core/numeric.py b/python/user_packages/Python313/site-packages/numpy/core/numeric.py
new file mode 100644
index 0000000000000000000000000000000000000000..dcf0fd1696dd2e021cd9c196e3cef75fb69a4ef0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/numeric.py
@@ -0,0 +1,12 @@
+def __getattr__(attr_name):
+    from numpy._core import numeric
+
+    from ._utils import _raise_warning
+
+    sentinel = object()
+    ret = getattr(numeric, attr_name, sentinel)
+    if ret is sentinel:
+        raise AttributeError(
+            f"module 'numpy.core.numeric' has no attribute {attr_name}")
+    _raise_warning(attr_name, "numeric")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/numerictypes.py b/python/user_packages/Python313/site-packages/numpy/core/numerictypes.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ed72d613dfb362e2274f3222d7649715d206a4f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/numerictypes.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import numerictypes
+
+    from ._utils import _raise_warning
+    ret = getattr(numerictypes, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.numerictypes' has no attribute {attr_name}")
+    _raise_warning(attr_name, "numerictypes")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/overrides.py b/python/user_packages/Python313/site-packages/numpy/core/overrides.py
new file mode 100644
index 0000000000000000000000000000000000000000..eac0bb408b90aaf69fadd2fde2d432e733a851e8
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/overrides.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import overrides
+
+    from ._utils import _raise_warning
+    ret = getattr(overrides, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.overrides' has no attribute {attr_name}")
+    _raise_warning(attr_name, "overrides")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/overrides.pyi b/python/user_packages/Python313/site-packages/numpy/core/overrides.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..0d44e772b9f027a7dcfb6eab5274bd41a5fe8b1b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/overrides.pyi
@@ -0,0 +1,7 @@
+# NOTE: At runtime, this submodule dynamically re-exports any `numpy._core.overrides`
+# member, and issues a `DeprecationWarning` when accessed. But since there is no
+# `__dir__` or `__all__` present, these annotations would be unverifiable. Because
+# this module is also deprecated in favor of `numpy._core`, and therefore not part of
+# the public API, we omit the "re-exports", which in practice would require literal
+# duplication of the stubs in order for the `@deprecated` decorator to be understood
+# by type-checkers.
diff --git a/python/user_packages/Python313/site-packages/numpy/core/records.py b/python/user_packages/Python313/site-packages/numpy/core/records.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3c84dd1fa86c11f92d56bc0ddcf23173f597624
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/records.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import records
+
+    from ._utils import _raise_warning
+    ret = getattr(records, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.records' has no attribute {attr_name}")
+    _raise_warning(attr_name, "records")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/shape_base.py b/python/user_packages/Python313/site-packages/numpy/core/shape_base.py
new file mode 100644
index 0000000000000000000000000000000000000000..2372a66599c4033aa25eb21358f3c6201a3abf0a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/shape_base.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import shape_base
+
+    from ._utils import _raise_warning
+    ret = getattr(shape_base, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.shape_base' has no attribute {attr_name}")
+    _raise_warning(attr_name, "shape_base")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/core/umath.py b/python/user_packages/Python313/site-packages/numpy/core/umath.py
new file mode 100644
index 0000000000000000000000000000000000000000..836c0b3a81c9bc9c9feb187458f0ee624cc13106
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/core/umath.py
@@ -0,0 +1,10 @@
+def __getattr__(attr_name):
+    from numpy._core import umath
+
+    from ._utils import _raise_warning
+    ret = getattr(umath, attr_name, None)
+    if ret is None:
+        raise AttributeError(
+            f"module 'numpy.core.umath' has no attribute {attr_name}")
+    _raise_warning(attr_name, "umath")
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.py b/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..35d2e3190715dea110ff2642d87bb307ee160b95
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.py
@@ -0,0 +1,13 @@
+from ._ctypeslib import (
+    __all__,
+    __doc__,
+    _concrete_ndptr,
+    _ndptr,
+    as_array,
+    as_ctypes,
+    as_ctypes_type,
+    c_intp,
+    ctypes,
+    load_library,
+    ndpointer,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..e9efaa421d0c40063bfbdf17ba4bc5647f218b43
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ctypeslib/__init__.pyi
@@ -0,0 +1,15 @@
+import ctypes
+from ctypes import c_int64 as _c_intp
+
+from ._ctypeslib import (
+    __all__ as __all__,
+    __doc__ as __doc__,
+    _concrete_ndptr as _concrete_ndptr,
+    _ndptr as _ndptr,
+    as_array as as_array,
+    as_ctypes as as_ctypes,
+    as_ctypes_type as as_ctypes_type,
+    c_intp as c_intp,
+    load_library as load_library,
+    ndpointer as ndpointer,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.py b/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.py
new file mode 100644
index 0000000000000000000000000000000000000000..92a3c789bb7a4a43d444d2c243dd675a2d029982
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.py
@@ -0,0 +1,603 @@
+"""
+============================
+``ctypes`` Utility Functions
+============================
+
+See Also
+--------
+load_library : Load a C library.
+ndpointer : Array restype/argtype with verification.
+as_ctypes : Create a ctypes array from an ndarray.
+as_array : Create an ndarray from a ctypes array.
+
+References
+----------
+.. [1] "SciPy Cookbook: ctypes", https://scipy-cookbook.readthedocs.io/items/Ctypes.html
+
+Examples
+--------
+Load the C library:
+
+>>> _lib = np.ctypeslib.load_library('libmystuff', '.')     #doctest: +SKIP
+
+Our result type, an ndarray that must be of type double, be 1-dimensional
+and is C-contiguous in memory:
+
+>>> array_1d_double = np.ctypeslib.ndpointer(
+...                          dtype=np.double,
+...                          ndim=1, flags='CONTIGUOUS')    #doctest: +SKIP
+
+Our C-function typically takes an array and updates its values
+in-place.  For example::
+
+    void foo_func(double* x, int length)
+    {
+        int i;
+        for (i = 0; i < length; i++) {
+            x[i] = i*i;
+        }
+    }
+
+We wrap it using:
+
+>>> _lib.foo_func.restype = None                      #doctest: +SKIP
+>>> _lib.foo_func.argtypes = [array_1d_double, c_int] #doctest: +SKIP
+
+Then, we're ready to call ``foo_func``:
+
+>>> out = np.empty(15, dtype=np.double)
+>>> _lib.foo_func(out, len(out))                #doctest: +SKIP
+
+"""
+__all__ = ['load_library', 'ndpointer', 'c_intp', 'as_ctypes', 'as_array',
+           'as_ctypes_type']
+
+import os
+
+import numpy as np
+import numpy._core.multiarray as mu
+from numpy._utils import set_module
+
+try:
+    import ctypes
+except ImportError:
+    ctypes = None
+
+if ctypes is None:
+    @set_module("numpy.ctypeslib")
+    def _dummy(*args, **kwds):
+        """
+        Dummy object that raises an ImportError if ctypes is not available.
+
+        Raises
+        ------
+        ImportError
+            If ctypes is not available.
+
+        """
+        raise ImportError("ctypes is not available.")
+    load_library = _dummy
+    as_ctypes = _dummy
+    as_ctypes_type = _dummy
+    as_array = _dummy
+    ndpointer = _dummy
+    from numpy import intp as c_intp
+    _ndptr_base = object
+else:
+    import numpy._core._internal as nic
+    c_intp = nic._getintp_ctype()
+    del nic
+    _ndptr_base = ctypes.c_void_p
+
+    # Adapted from Albert Strasheim
+    @set_module("numpy.ctypeslib")
+    def load_library(libname, loader_path):
+        """
+        It is possible to load a library using
+
+        >>> lib = ctypes.cdll[<full_path_name>] # doctest: +SKIP
+
+        But there are cross-platform considerations, such as library file extensions,
+        plus the fact Windows will just load the first library it finds with that name.
+        NumPy supplies the load_library function as a convenience.
+
+        .. versionchanged:: 1.20.0
+            Allow libname and loader_path to take any
+            :term:`python:path-like object`.
+
+        Parameters
+        ----------
+        libname : path-like
+            Name of the library, which can have 'lib' as a prefix,
+            but without an extension.
+        loader_path : path-like
+            Where the library can be found.
+
+        Returns
+        -------
+        ctypes.cdll[libpath] : library object
+           A ctypes library object
+
+        Raises
+        ------
+        OSError
+            If there is no library with the expected extension, or the
+            library is defective and cannot be loaded.
+        """
+        # Convert path-like objects into strings
+        libname = os.fsdecode(libname)
+        loader_path = os.fsdecode(loader_path)
+
+        ext = os.path.splitext(libname)[1]
+        if not ext:
+            import sys
+            import sysconfig
+            # Try to load library with platform-specific name, otherwise
+            # default to libname.[so|dll|dylib].  Sometimes, these files are
+            # built erroneously on non-linux platforms.
+            base_ext = ".so"
+            if sys.platform.startswith("darwin"):
+                base_ext = ".dylib"
+            elif sys.platform.startswith("win"):
+                base_ext = ".dll"
+            libname_ext = [libname + base_ext]
+            so_ext = sysconfig.get_config_var("EXT_SUFFIX")
+            if not so_ext == base_ext:
+                libname_ext.insert(0, libname + so_ext)
+        else:
+            libname_ext = [libname]
+
+        loader_path = os.path.abspath(loader_path)
+        if not os.path.isdir(loader_path):
+            libdir = os.path.dirname(loader_path)
+        else:
+            libdir = loader_path
+
+        for ln in libname_ext:
+            libpath = os.path.join(libdir, ln)
+            if os.path.exists(libpath):
+                try:
+                    return ctypes.cdll[libpath]
+                except OSError:
+                    # defective lib file
+                    raise
+        # if no successful return in the libname_ext loop:
+        raise OSError("no file with expected extension")
+
+
+def _num_fromflags(flaglist):
+    num = 0
+    for val in flaglist:
+        num += mu._flagdict[val]
+    return num
+
+
+_flagnames = ['C_CONTIGUOUS', 'F_CONTIGUOUS', 'ALIGNED', 'WRITEABLE',
+              'OWNDATA', 'WRITEBACKIFCOPY']
+def _flags_fromnum(num):
+    res = []
+    for key in _flagnames:
+        value = mu._flagdict[key]
+        if (num & value):
+            res.append(key)
+    return res
+
+
+class _ndptr(_ndptr_base):
+    @classmethod
+    def from_param(cls, obj):
+        if not isinstance(obj, np.ndarray):
+            raise TypeError("argument must be an ndarray")
+        if cls._dtype_ is not None \
+               and obj.dtype != cls._dtype_:
+            raise TypeError(f"array must have data type {cls._dtype_}")
+        if cls._ndim_ is not None \
+               and obj.ndim != cls._ndim_:
+            raise TypeError("array must have %d dimension(s)" % cls._ndim_)
+        if cls._shape_ is not None \
+               and obj.shape != cls._shape_:
+            raise TypeError(f"array must have shape {str(cls._shape_)}")
+        if cls._flags_ is not None \
+               and ((obj.flags.num & cls._flags_) != cls._flags_):
+            raise TypeError(f"array must have flags {_flags_fromnum(cls._flags_)}")
+        return obj.ctypes
+
+
+class _concrete_ndptr(_ndptr):
+    """
+    Like _ndptr, but with `_shape_` and `_dtype_` specified.
+
+    Notably, this means the pointer has enough information to reconstruct
+    the array, which is not generally true.
+    """
+    def _check_retval_(self):
+        """
+        This method is called when this class is used as the .restype
+        attribute for a shared-library function, to automatically wrap the
+        pointer into an array.
+        """
+        return self.contents
+
+    @property
+    def contents(self):
+        """
+        Get an ndarray viewing the data pointed to by this pointer.
+
+        This mirrors the `contents` attribute of a normal ctypes pointer
+        """
+        full_dtype = np.dtype((self._dtype_, self._shape_))
+        full_ctype = ctypes.c_char * full_dtype.itemsize
+        buffer = ctypes.cast(self, ctypes.POINTER(full_ctype)).contents
+        return np.frombuffer(buffer, dtype=full_dtype).squeeze(axis=0)
+
+
+# Factory for an array-checking class with from_param defined for
+# use with ctypes argtypes mechanism
+_pointer_type_cache = {}
+
+@set_module("numpy.ctypeslib")
+def ndpointer(dtype=None, ndim=None, shape=None, flags=None):
+    """
+    Array-checking restype/argtypes.
+
+    An ndpointer instance is used to describe an ndarray in restypes
+    and argtypes specifications.  This approach is more flexible than
+    using, for example, ``POINTER(c_double)``, since several restrictions
+    can be specified, which are verified upon calling the ctypes function.
+    These include data type, number of dimensions, shape and flags.  If a
+    given array does not satisfy the specified restrictions,
+    a ``TypeError`` is raised.
+
+    Parameters
+    ----------
+    dtype : data-type, optional
+        Array data-type.
+    ndim : int, optional
+        Number of array dimensions.
+    shape : tuple of ints, optional
+        Array shape.
+    flags : str or tuple of str
+        Array flags; may be one or more of:
+
+        - C_CONTIGUOUS / C / CONTIGUOUS
+        - F_CONTIGUOUS / F / FORTRAN
+        - OWNDATA / O
+        - WRITEABLE / W
+        - ALIGNED / A
+        - WRITEBACKIFCOPY / X
+
+    Returns
+    -------
+    klass : ndpointer type object
+        A type object, which is an ``_ndtpr`` instance containing
+        dtype, ndim, shape and flags information.
+
+    Raises
+    ------
+    TypeError
+        If a given array does not satisfy the specified restrictions.
+
+    Examples
+    --------
+    >>> clib.somefunc.argtypes = [np.ctypeslib.ndpointer(dtype=np.float64,
+    ...                                                  ndim=1,
+    ...                                                  flags='C_CONTIGUOUS')]
+    ... #doctest: +SKIP
+    >>> clib.somefunc(np.array([1, 2, 3], dtype=np.float64))
+    ... #doctest: +SKIP
+
+    """
+
+    # normalize dtype to dtype | None
+    if dtype is not None:
+        dtype = np.dtype(dtype)
+
+    # normalize flags to int | None
+    num = None
+    if flags is not None:
+        if isinstance(flags, str):
+            flags = flags.split(',')
+        elif isinstance(flags, (int, np.integer)):
+            num = flags
+            flags = _flags_fromnum(num)
+        elif isinstance(flags, mu.flagsobj):
+            num = flags.num
+            flags = _flags_fromnum(num)
+        if num is None:
+            try:
+                flags = [x.strip().upper() for x in flags]
+            except Exception as e:
+                raise TypeError("invalid flags specification") from e
+            num = _num_fromflags(flags)
+
+    # normalize shape to tuple | None
+    if shape is not None:
+        try:
+            shape = tuple(shape)
+        except TypeError:
+            # single integer -> 1-tuple
+            shape = (shape,)
+
+    cache_key = (dtype, ndim, shape, num)
+
+    try:
+        return _pointer_type_cache[cache_key]
+    except KeyError:
+        pass
+
+    # produce a name for the new type
+    if dtype is None:
+        name = 'any'
+    elif dtype.names is not None:
+        name = str(id(dtype))
+    else:
+        name = dtype.str
+    if ndim is not None:
+        name += "_%dd" % ndim
+    if shape is not None:
+        name += "_" + "x".join(str(x) for x in shape)
+    if flags is not None:
+        name += "_" + "_".join(flags)
+
+    if dtype is not None and shape is not None:
+        base = _concrete_ndptr
+    else:
+        base = _ndptr
+
+    klass = type(f"ndpointer_{name}", (base,),
+                 {"_dtype_": dtype,
+                  "_shape_": shape,
+                  "_ndim_": ndim,
+                  "_flags_": num})
+    _pointer_type_cache[cache_key] = klass
+    return klass
+
+
+if ctypes is not None:
+    def _ctype_ndarray(element_type, shape):
+        """ Create an ndarray of the given element type and shape """
+        for dim in shape[::-1]:
+            element_type = dim * element_type
+            # prevent the type name include np.ctypeslib
+            element_type.__module__ = None
+        return element_type
+
+    def _get_scalar_type_map():
+        """
+        Return a dictionary mapping native endian scalar dtype to ctypes types
+        """
+        ct = ctypes
+        simple_types = [
+            ct.c_byte, ct.c_short, ct.c_int, ct.c_long, ct.c_longlong,
+            ct.c_ubyte, ct.c_ushort, ct.c_uint, ct.c_ulong, ct.c_ulonglong,
+            ct.c_float, ct.c_double,
+            ct.c_bool,
+        ]
+        return {np.dtype(ctype): ctype for ctype in simple_types}
+
+    _scalar_type_map = _get_scalar_type_map()
+
+    def _ctype_from_dtype_scalar(dtype):
+        # swapping twice ensure that `=` is promoted to <, >, or |
+        dtype_with_endian = dtype.newbyteorder('S').newbyteorder('S')
+        dtype_native = dtype.newbyteorder('=')
+        try:
+            ctype = _scalar_type_map[dtype_native]
+        except KeyError as e:
+            raise NotImplementedError(
+                f"Converting {dtype!r} to a ctypes type"
+            ) from None
+
+        if dtype_with_endian.byteorder == '>':
+            ctype = ctype.__ctype_be__
+        elif dtype_with_endian.byteorder == '<':
+            ctype = ctype.__ctype_le__
+
+        return ctype
+
+    def _ctype_from_dtype_subarray(dtype):
+        element_dtype, shape = dtype.subdtype
+        ctype = _ctype_from_dtype(element_dtype)
+        return _ctype_ndarray(ctype, shape)
+
+    def _ctype_from_dtype_structured(dtype):
+        # extract offsets of each field
+        field_data = []
+        for name in dtype.names:
+            field_dtype, offset = dtype.fields[name][:2]
+            field_data.append((offset, name, _ctype_from_dtype(field_dtype)))
+
+        # ctypes doesn't care about field order
+        field_data = sorted(field_data, key=lambda f: f[0])
+
+        if len(field_data) > 1 and all(offset == 0 for offset, _, _ in field_data):
+            # union, if multiple fields all at address 0
+            size = 0
+            _fields_ = []
+            for offset, name, ctype in field_data:
+                _fields_.append((name, ctype))
+                size = max(size, ctypes.sizeof(ctype))
+
+            # pad to the right size
+            if dtype.itemsize != size:
+                _fields_.append(('', ctypes.c_char * dtype.itemsize))
+
+            # we inserted manual padding, so always `_pack_`
+            return type('union', (ctypes.Union,), {
+                '_fields_': _fields_,
+                '_pack_': 1,
+                '__module__': None,
+            })
+        else:
+            last_offset = 0
+            _fields_ = []
+            for offset, name, ctype in field_data:
+                padding = offset - last_offset
+                if padding < 0:
+                    raise NotImplementedError("Overlapping fields")
+                if padding > 0:
+                    _fields_.append(('', ctypes.c_char * padding))
+
+                _fields_.append((name, ctype))
+                last_offset = offset + ctypes.sizeof(ctype)
+
+            padding = dtype.itemsize - last_offset
+            if padding > 0:
+                _fields_.append(('', ctypes.c_char * padding))
+
+            # we inserted manual padding, so always `_pack_`
+            return type('struct', (ctypes.Structure,), {
+                '_fields_': _fields_,
+                '_pack_': 1,
+                '__module__': None,
+            })
+
+    def _ctype_from_dtype(dtype):
+        if dtype.fields is not None:
+            return _ctype_from_dtype_structured(dtype)
+        elif dtype.subdtype is not None:
+            return _ctype_from_dtype_subarray(dtype)
+        else:
+            return _ctype_from_dtype_scalar(dtype)
+
+    @set_module("numpy.ctypeslib")
+    def as_ctypes_type(dtype):
+        r"""
+        Convert a dtype into a ctypes type.
+
+        Parameters
+        ----------
+        dtype : dtype
+            The dtype to convert
+
+        Returns
+        -------
+        ctype
+            A ctype scalar, union, array, or struct
+
+        Raises
+        ------
+        NotImplementedError
+            If the conversion is not possible
+
+        Notes
+        -----
+        This function does not losslessly round-trip in either direction.
+
+        ``np.dtype(as_ctypes_type(dt))`` will:
+
+        - insert padding fields
+        - reorder fields to be sorted by offset
+        - discard field titles
+
+        ``as_ctypes_type(np.dtype(ctype))`` will:
+
+        - discard the class names of `ctypes.Structure`\ s and
+          `ctypes.Union`\ s
+        - convert single-element `ctypes.Union`\ s into single-element
+          `ctypes.Structure`\ s
+        - insert padding fields
+
+        Examples
+        --------
+        Converting a simple dtype:
+
+        >>> dt = np.dtype('int8')
+        >>> ctype = np.ctypeslib.as_ctypes_type(dt)
+        >>> ctype
+        <class 'ctypes.c_byte'>
+
+        Converting a structured dtype:
+
+        >>> dt = np.dtype([('x', 'i4'), ('y', 'f4')])
+        >>> ctype = np.ctypeslib.as_ctypes_type(dt)
+        >>> ctype
+        <class 'struct'>
+
+        """
+        return _ctype_from_dtype(np.dtype(dtype))
+
+    @set_module("numpy.ctypeslib")
+    def as_array(obj, shape=None):
+        """
+        Create a numpy array from a ctypes array or POINTER.
+
+        The numpy array shares the memory with the ctypes object.
+
+        The shape parameter must be given if converting from a ctypes POINTER.
+        The shape parameter is ignored if converting from a ctypes array
+
+        Examples
+        --------
+        Converting a ctypes integer array:
+
+        >>> import ctypes
+        >>> ctypes_array = (ctypes.c_int * 5)(0, 1, 2, 3, 4)
+        >>> np_array = np.ctypeslib.as_array(ctypes_array)
+        >>> np_array
+        array([0, 1, 2, 3, 4], dtype=int32)
+
+        Converting a ctypes POINTER:
+
+        >>> import ctypes
+        >>> buffer = (ctypes.c_int * 5)(0, 1, 2, 3, 4)
+        >>> pointer = ctypes.cast(buffer, ctypes.POINTER(ctypes.c_int))
+        >>> np_array = np.ctypeslib.as_array(pointer, (5,))
+        >>> np_array
+        array([0, 1, 2, 3, 4], dtype=int32)
+
+        """
+        if isinstance(obj, ctypes._Pointer):
+            # convert pointers to an array of the desired shape
+            if shape is None:
+                raise TypeError(
+                    'as_array() requires a shape argument when called on a '
+                    'pointer')
+            p_arr_type = ctypes.POINTER(_ctype_ndarray(obj._type_, shape))
+            obj = ctypes.cast(obj, p_arr_type).contents
+
+        return np.asarray(obj)
+
+    @set_module("numpy.ctypeslib")
+    def as_ctypes(obj):
+        """
+        Create and return a ctypes object from a numpy array.  Actually
+        anything that exposes the __array_interface__ is accepted.
+
+        Examples
+        --------
+        Create ctypes object from inferred int ``np.array``:
+
+        >>> inferred_int_array = np.array([1, 2, 3])
+        >>> c_int_array = np.ctypeslib.as_ctypes(inferred_int_array)
+        >>> type(c_int_array)
+        <class 'c_long_Array_3'>
+        >>> c_int_array[:]
+        [1, 2, 3]
+
+        Create ctypes object from explicit 8 bit unsigned int ``np.array`` :
+
+        >>> exp_int_array = np.array([1, 2, 3], dtype=np.uint8)
+        >>> c_int_array = np.ctypeslib.as_ctypes(exp_int_array)
+        >>> type(c_int_array)
+        <class 'c_ubyte_Array_3'>
+        >>> c_int_array[:]
+        [1, 2, 3]
+
+        """
+        ai = obj.__array_interface__
+        if ai["strides"]:
+            raise TypeError("strided arrays not supported")
+        if ai["version"] != 3:
+            raise TypeError("only __array_interface__ version 3 supported")
+        addr, readonly = ai["data"]
+        if readonly:
+            raise TypeError("readonly arrays unsupported")
+
+        # can't use `_dtype((ai["typestr"], ai["shape"]))` here, as it overflows
+        # dtype.itemsize (gh-14214)
+        ctype_scalar = as_ctypes_type(ai["typestr"])
+        result_type = _ctype_ndarray(ctype_scalar, ai["shape"])
+        result = result_type.from_address(addr)
+        result.__keep = obj
+        return result
diff --git a/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.pyi b/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..90627278fd6fbaf680a858718126f94d9aff3d83
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ctypeslib/_ctypeslib.pyi
@@ -0,0 +1,236 @@
+# NOTE: Numpy's mypy plugin is used for importing the correct
+# platform-specific `ctypes._SimpleCData[int]` sub-type
+import ctypes
+from _typeshed import StrOrBytesPath
+from collections.abc import Iterable, Sequence
+from ctypes import c_int64 as _c_intp
+from typing import Any, ClassVar, Generic, Literal as L, TypeAlias, TypeVar, overload
+
+import numpy as np
+from numpy import (
+    byte,
+    double,
+    dtype,
+    generic,
+    intc,
+    long,
+    longdouble,
+    longlong,
+    ndarray,
+    short,
+    single,
+    ubyte,
+    uintc,
+    ulong,
+    ulonglong,
+    ushort,
+    void,
+)
+from numpy._core._internal import _ctypes
+from numpy._core.multiarray import flagsobj
+from numpy._typing import (
+    DTypeLike,
+    NDArray,
+    _AnyShape,
+    _ArrayLike,
+    _BoolCodes,
+    _ByteCodes,
+    _DoubleCodes,
+    _DTypeLike,
+    _IntCCodes,
+    _LongCodes,
+    _LongDoubleCodes,
+    _LongLongCodes,
+    _ShapeLike,
+    _ShortCodes,
+    _SingleCodes,
+    _UByteCodes,
+    _UIntCCodes,
+    _ULongCodes,
+    _ULongLongCodes,
+    _UShortCodes,
+    _VoidDTypeLike,
+)
+
+__all__ = ["load_library", "ndpointer", "c_intp", "as_ctypes", "as_array", "as_ctypes_type"]
+
+# TODO: Add a proper `_Shape` bound once we've got variadic typevars
+_DTypeT = TypeVar("_DTypeT", bound=dtype)
+_DTypeOptionalT = TypeVar("_DTypeOptionalT", bound=dtype | None)
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+
+_FlagsKind: TypeAlias = L[
+    "C_CONTIGUOUS", "CONTIGUOUS", "C",
+    "F_CONTIGUOUS", "FORTRAN", "F",
+    "ALIGNED", "A",
+    "WRITEABLE", "W",
+    "OWNDATA", "O",
+    "WRITEBACKIFCOPY", "X",
+]
+
+# TODO: Add a shape typevar once we have variadic typevars (PEP 646)
+class _ndptr(ctypes.c_void_p, Generic[_DTypeOptionalT]):
+    # In practice these 4 classvars are defined in the dynamic class
+    # returned by `ndpointer`
+    _dtype_: ClassVar[_DTypeOptionalT]
+    _shape_: ClassVar[_AnyShape | None]
+    _ndim_: ClassVar[int | None]
+    _flags_: ClassVar[list[_FlagsKind] | None]
+
+    @overload  # type: ignore[override]
+    @classmethod
+    def from_param(cls: type[_ndptr[None]], obj: NDArray[Any]) -> _ctypes[Any]: ...
+    @overload
+    @classmethod
+    def from_param(cls: type[_ndptr[_DTypeT]], obj: ndarray[Any, _DTypeT]) -> _ctypes[Any]: ...
+
+class _concrete_ndptr(_ndptr[_DTypeT]):
+    _dtype_: ClassVar[_DTypeT]
+    _shape_: ClassVar[_AnyShape]
+    @property
+    def contents(self) -> ndarray[_AnyShape, _DTypeT]: ...
+
+def load_library(libname: StrOrBytesPath, loader_path: StrOrBytesPath) -> ctypes.CDLL: ...
+
+c_intp = _c_intp
+
+@overload
+def ndpointer(
+    dtype: None = None,
+    ndim: int | None = None,
+    shape: _ShapeLike | None = None,
+    flags: _FlagsKind | Iterable[_FlagsKind] | int | flagsobj | None = None,
+) -> type[_ndptr[None]]: ...
+@overload
+def ndpointer(
+    dtype: _DTypeLike[_ScalarT],
+    ndim: int | None = None,
+    *,
+    shape: _ShapeLike,
+    flags: _FlagsKind | Iterable[_FlagsKind] | int | flagsobj | None = None,
+) -> type[_concrete_ndptr[dtype[_ScalarT]]]: ...
+@overload
+def ndpointer(
+    dtype: DTypeLike | None,
+    ndim: int | None = None,
+    *,
+    shape: _ShapeLike,
+    flags: _FlagsKind | Iterable[_FlagsKind] | int | flagsobj | None = None,
+) -> type[_concrete_ndptr[dtype]]: ...
+@overload
+def ndpointer(
+    dtype: _DTypeLike[_ScalarT],
+    ndim: int | None = None,
+    shape: None = None,
+    flags: _FlagsKind | Iterable[_FlagsKind] | int | flagsobj | None = None,
+) -> type[_ndptr[dtype[_ScalarT]]]: ...
+@overload
+def ndpointer(
+    dtype: DTypeLike | None,
+    ndim: int | None = None,
+    shape: None = None,
+    flags: _FlagsKind | Iterable[_FlagsKind] | int | flagsobj | None = None,
+) -> type[_ndptr[dtype]]: ...
+
+@overload
+def as_ctypes_type(dtype: _BoolCodes | _DTypeLike[np.bool] | type[ctypes.c_bool]) -> type[ctypes.c_bool]: ...
+@overload
+def as_ctypes_type(dtype: _ByteCodes | _DTypeLike[byte] | type[ctypes.c_byte]) -> type[ctypes.c_byte]: ...
+@overload
+def as_ctypes_type(dtype: _ShortCodes | _DTypeLike[short] | type[ctypes.c_short]) -> type[ctypes.c_short]: ...
+@overload
+def as_ctypes_type(dtype: _IntCCodes | _DTypeLike[intc] | type[ctypes.c_int]) -> type[ctypes.c_int]: ...
+@overload
+def as_ctypes_type(dtype: _LongCodes | _DTypeLike[long] | type[ctypes.c_long]) -> type[ctypes.c_long]: ...
+@overload
+def as_ctypes_type(dtype: type[int]) -> type[c_intp]: ...
+@overload
+def as_ctypes_type(dtype: _LongLongCodes | _DTypeLike[longlong] | type[ctypes.c_longlong]) -> type[ctypes.c_longlong]: ...
+@overload
+def as_ctypes_type(dtype: _UByteCodes | _DTypeLike[ubyte] | type[ctypes.c_ubyte]) -> type[ctypes.c_ubyte]: ...
+@overload
+def as_ctypes_type(dtype: _UShortCodes | _DTypeLike[ushort] | type[ctypes.c_ushort]) -> type[ctypes.c_ushort]: ...
+@overload
+def as_ctypes_type(dtype: _UIntCCodes | _DTypeLike[uintc] | type[ctypes.c_uint]) -> type[ctypes.c_uint]: ...
+@overload
+def as_ctypes_type(dtype: _ULongCodes | _DTypeLike[ulong] | type[ctypes.c_ulong]) -> type[ctypes.c_ulong]: ...
+@overload
+def as_ctypes_type(dtype: _ULongLongCodes | _DTypeLike[ulonglong] | type[ctypes.c_ulonglong]) -> type[ctypes.c_ulonglong]: ...
+@overload
+def as_ctypes_type(dtype: _SingleCodes | _DTypeLike[single] | type[ctypes.c_float]) -> type[ctypes.c_float]: ...
+@overload
+def as_ctypes_type(dtype: _DoubleCodes | _DTypeLike[double] | type[float | ctypes.c_double]) -> type[ctypes.c_double]: ...
+@overload
+def as_ctypes_type(dtype: _LongDoubleCodes | _DTypeLike[longdouble] | type[ctypes.c_longdouble]) -> type[ctypes.c_longdouble]: ...
+@overload
+def as_ctypes_type(dtype: _VoidDTypeLike) -> type[Any]: ...  # `ctypes.Union` or `ctypes.Structure`
+@overload
+def as_ctypes_type(dtype: str) -> type[Any]: ...
+
+@overload
+def as_array(obj: ctypes._PointerLike, shape: Sequence[int]) -> NDArray[Any]: ...
+@overload
+def as_array(obj: _ArrayLike[_ScalarT], shape: _ShapeLike | None = None) -> NDArray[_ScalarT]: ...
+@overload
+def as_array(obj: object, shape: _ShapeLike | None = None) -> NDArray[Any]: ...
+
+@overload
+def as_ctypes(obj: np.bool) -> ctypes.c_bool: ...
+@overload
+def as_ctypes(obj: byte) -> ctypes.c_byte: ...
+@overload
+def as_ctypes(obj: short) -> ctypes.c_short: ...
+@overload
+def as_ctypes(obj: intc) -> ctypes.c_int: ...
+@overload
+def as_ctypes(obj: long) -> ctypes.c_long: ...
+@overload
+def as_ctypes(obj: longlong) -> ctypes.c_longlong: ...  # type: ignore[overload-cannot-match]
+@overload
+def as_ctypes(obj: ubyte) -> ctypes.c_ubyte: ...
+@overload
+def as_ctypes(obj: ushort) -> ctypes.c_ushort: ...
+@overload
+def as_ctypes(obj: uintc) -> ctypes.c_uint: ...
+@overload
+def as_ctypes(obj: ulong) -> ctypes.c_ulong: ...
+@overload
+def as_ctypes(obj: ulonglong) -> ctypes.c_ulonglong: ...  # type: ignore[overload-cannot-match]
+@overload
+def as_ctypes(obj: single) -> ctypes.c_float: ...
+@overload
+def as_ctypes(obj: double) -> ctypes.c_double: ...
+@overload
+def as_ctypes(obj: longdouble) -> ctypes.c_longdouble: ...
+@overload
+def as_ctypes(obj: void) -> Any: ...  # `ctypes.Union` or `ctypes.Structure`
+@overload
+def as_ctypes(obj: NDArray[np.bool]) -> ctypes.Array[ctypes.c_bool]: ...
+@overload
+def as_ctypes(obj: NDArray[byte]) -> ctypes.Array[ctypes.c_byte]: ...
+@overload
+def as_ctypes(obj: NDArray[short]) -> ctypes.Array[ctypes.c_short]: ...
+@overload
+def as_ctypes(obj: NDArray[intc]) -> ctypes.Array[ctypes.c_int]: ...
+@overload
+def as_ctypes(obj: NDArray[long]) -> ctypes.Array[ctypes.c_long]: ...
+@overload
+def as_ctypes(obj: NDArray[longlong]) -> ctypes.Array[ctypes.c_longlong]: ...  # type: ignore[overload-cannot-match]
+@overload
+def as_ctypes(obj: NDArray[ubyte]) -> ctypes.Array[ctypes.c_ubyte]: ...
+@overload
+def as_ctypes(obj: NDArray[ushort]) -> ctypes.Array[ctypes.c_ushort]: ...
+@overload
+def as_ctypes(obj: NDArray[uintc]) -> ctypes.Array[ctypes.c_uint]: ...
+@overload
+def as_ctypes(obj: NDArray[ulong]) -> ctypes.Array[ctypes.c_ulong]: ...
+@overload
+def as_ctypes(obj: NDArray[ulonglong]) -> ctypes.Array[ctypes.c_ulonglong]: ...  # type: ignore[overload-cannot-match]
+@overload
+def as_ctypes(obj: NDArray[single]) -> ctypes.Array[ctypes.c_float]: ...
+@overload
+def as_ctypes(obj: NDArray[double]) -> ctypes.Array[ctypes.c_double]: ...
+@overload
+def as_ctypes(obj: NDArray[longdouble]) -> ctypes.Array[ctypes.c_longdouble]: ...
+@overload
+def as_ctypes(obj: NDArray[void]) -> ctypes.Array[Any]: ...  # `ctypes.Union` or `ctypes.Structure`
diff --git a/python/user_packages/Python313/site-packages/numpy/doc/ufuncs.py b/python/user_packages/Python313/site-packages/numpy/doc/ufuncs.py
new file mode 100644
index 0000000000000000000000000000000000000000..398e5e7975e0a27e6a2eae5444404b8bdec20571
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/doc/ufuncs.py
@@ -0,0 +1,138 @@
+"""
+===================
+Universal Functions
+===================
+
+Ufuncs are, generally speaking, mathematical functions or operations that are
+applied element-by-element to the contents of an array. That is, the result
+in each output array element only depends on the value in the corresponding
+input array (or arrays) and on no other array elements. NumPy comes with a
+large suite of ufuncs, and scipy extends that suite substantially. The simplest
+example is the addition operator: ::
+
+ >>> np.array([0,2,3,4]) + np.array([1,1,-1,2])
+ array([1, 3, 2, 6])
+
+The ufunc module lists all the available ufuncs in numpy. Documentation on
+the specific ufuncs may be found in those modules. This documentation is
+intended to address the more general aspects of ufuncs common to most of
+them. All of the ufuncs that make use of Python operators (e.g., +, -, etc.)
+have equivalent functions defined (e.g. add() for +)
+
+Type coercion
+=============
+
+What happens when a binary operator (e.g., +,-,\\*,/, etc) deals with arrays of
+two different types? What is the type of the result? Typically, the result is
+the higher of the two types. For example: ::
+
+ float32 + float64 -> float64
+ int8 + int32 -> int32
+ int16 + float32 -> float32
+ float32 + complex64 -> complex64
+
+There are some less obvious cases generally involving mixes of types
+(e.g. uints, ints and floats) where equal bit sizes for each are not
+capable of saving all the information in a different type of equivalent
+bit size. Some examples are int32 vs float32 or uint32 vs int32.
+Generally, the result is the higher type of larger size than both
+(if available). So: ::
+
+ int32 + float32 -> float64
+ uint32 + int32 -> int64
+
+Finally, the type coercion behavior when expressions involve Python
+scalars is different than that seen for arrays. Since Python has a
+limited number of types, combining a Python int with a dtype=np.int8
+array does not coerce to the higher type but instead, the type of the
+array prevails. So the rules for Python scalars combined with arrays is
+that the result will be that of the array equivalent the Python scalar
+if the Python scalar is of a higher 'kind' than the array (e.g., float
+vs. int), otherwise the resultant type will be that of the array.
+For example: ::
+
+  Python int + int8 -> int8
+  Python float + int8 -> float64
+
+ufunc methods
+=============
+
+Binary ufuncs support 4 methods.
+
+**.reduce(arr)** applies the binary operator to elements of the array in
+  sequence. For example: ::
+
+ >>> np.add.reduce(np.arange(10))  # adds all elements of array
+ 45
+
+For multidimensional arrays, the first dimension is reduced by default: ::
+
+ >>> np.add.reduce(np.arange(10).reshape(2,5))
+     array([ 5,  7,  9, 11, 13])
+
+The axis keyword can be used to specify different axes to reduce: ::
+
+ >>> np.add.reduce(np.arange(10).reshape(2,5),axis=1)
+ array([10, 35])
+
+**.accumulate(arr)** applies the binary operator and generates an
+equivalently shaped array that includes the accumulated amount for each
+element of the array. A couple examples: ::
+
+ >>> np.add.accumulate(np.arange(10))
+ array([ 0,  1,  3,  6, 10, 15, 21, 28, 36, 45])
+ >>> np.multiply.accumulate(np.arange(1,9))
+ array([    1,     2,     6,    24,   120,   720,  5040, 40320])
+
+The behavior for multidimensional arrays is the same as for .reduce(),
+as is the use of the axis keyword).
+
+**.reduceat(arr,indices)** allows one to apply reduce to selected parts
+  of an array. It is a difficult method to understand. See the documentation
+  at:
+
+**.outer(arr1,arr2)** generates an outer operation on the two arrays arr1 and
+  arr2. It will work on multidimensional arrays (the shape of the result is
+  the concatenation of the two input shapes.: ::
+
+ >>> np.multiply.outer(np.arange(3),np.arange(4))
+ array([[0, 0, 0, 0],
+        [0, 1, 2, 3],
+        [0, 2, 4, 6]])
+
+Output arguments
+================
+
+All ufuncs accept an optional output array. The array must be of the expected
+output shape. Beware that if the type of the output array is of a different
+(and lower) type than the output result, the results may be silently truncated
+or otherwise corrupted in the downcast to the lower type. This usage is useful
+when one wants to avoid creating large temporary arrays and instead allows one
+to reuse the same array memory repeatedly (at the expense of not being able to
+use more convenient operator notation in expressions). Note that when the
+output argument is used, the ufunc still returns a reference to the result.
+
+ >>> x = np.arange(2)
+ >>> np.add(np.arange(2, dtype=float), np.arange(2, dtype=float), x,
+ ...        casting='unsafe')
+ array([0, 2])
+ >>> x
+ array([0, 2])
+
+and & or as ufuncs
+==================
+
+Invariably people try to use the python 'and' and 'or' as logical operators
+(and quite understandably). But these operators do not behave as normal
+operators since Python treats these quite differently. They cannot be
+overloaded with array equivalents. Thus using 'and' or 'or' with an array
+results in an error. There are two alternatives:
+
+ 1) use the ufunc functions logical_and() and logical_or().
+ 2) use the bitwise operators & and \\|. The drawback of these is that if
+    the arguments to these operators are not boolean arrays, the result is
+    likely incorrect. On the other hand, most usages of logical_and and
+    logical_or are with boolean arrays. As long as one is careful, this is
+    a convenient way to apply these operators.
+
+"""
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/__init__.py b/python/user_packages/Python313/site-packages/numpy/f2py/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..151193af21b0c4587c9c5c785ff5bc8c7d605e8d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/__init__.py
@@ -0,0 +1,86 @@
+"""Fortran to Python Interface Generator.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the terms
+of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+__all__ = ['run_main', 'get_include']
+
+import os
+import subprocess
+import sys
+import warnings
+
+from numpy.exceptions import VisibleDeprecationWarning
+
+from . import diagnose, f2py2e
+
+run_main = f2py2e.run_main
+main = f2py2e.main
+
+
+def get_include():
+    """
+    Return the directory that contains the ``fortranobject.c`` and ``.h`` files.
+
+    .. note::
+
+        This function is not needed when building an extension with
+        `numpy.distutils` directly from ``.f`` and/or ``.pyf`` files
+        in one go.
+
+    Python extension modules built with f2py-generated code need to use
+    ``fortranobject.c`` as a source file, and include the ``fortranobject.h``
+    header. This function can be used to obtain the directory containing
+    both of these files.
+
+    Returns
+    -------
+    include_path : str
+        Absolute path to the directory containing ``fortranobject.c`` and
+        ``fortranobject.h``.
+
+    Notes
+    -----
+    .. versionadded:: 1.21.1
+
+    Unless the build system you are using has specific support for f2py,
+    building a Python extension using a ``.pyf`` signature file is a two-step
+    process. For a module ``mymod``:
+
+    * Step 1: run ``python -m numpy.f2py mymod.pyf --quiet``. This
+      generates ``mymodmodule.c`` and (if needed)
+      ``mymod-f2pywrappers.f`` files next to ``mymod.pyf``.
+    * Step 2: build your Python extension module. This requires the
+      following source files:
+
+      * ``mymodmodule.c``
+      * ``mymod-f2pywrappers.f`` (if it was generated in Step 1)
+      * ``fortranobject.c``
+
+    See Also
+    --------
+    numpy.get_include : function that returns the numpy include directory
+
+    """
+    return os.path.join(os.path.dirname(__file__), 'src')
+
+
+def __getattr__(attr):
+
+    # Avoid importing things that aren't needed for building
+    # which might import the main numpy module
+    if attr == "test":
+        from numpy._pytesttester import PytestTester
+        test = PytestTester(__name__)
+        return test
+
+    else:
+        raise AttributeError(f"module {__name__!r} has no attribute {attr!r}")
+
+
+def __dir__():
+    return list(globals().keys() | {"test"})
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..64540d3f4034c4e77bc24aaa6b29173977f033b3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/__init__.pyi
@@ -0,0 +1,5 @@
+from .f2py2e import main as main, run_main
+
+__all__ = ["get_include", "run_main"]
+
+def get_include() -> str: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/__main__.py b/python/user_packages/Python313/site-packages/numpy/f2py/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..19ced88500139d62fc99f027bc467b07ee59bb26
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/__main__.py
@@ -0,0 +1,5 @@
+# See:
+# https://web.archive.org/web/20140822061353/http://cens.ioc.ee/projects/f2py2e
+from numpy.f2py.f2py2e import main
+
+main()
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/__version__.py b/python/user_packages/Python313/site-packages/numpy/f2py/__version__.py
new file mode 100644
index 0000000000000000000000000000000000000000..3cf646f74e56c68a2f781b76bae9f145fc0ea4b9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/__version__.py
@@ -0,0 +1 @@
+from numpy.version import version  # noqa: F401
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/__version__.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/__version__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..6fd876a2e48078e05b8ad8b06ed19018d6cb5e1b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/__version__.pyi
@@ -0,0 +1 @@
+from numpy.version import version as version
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.py b/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a1399588bc9386219acff9ad7a483e27ea153f9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.py
@@ -0,0 +1,62 @@
+"""
+ISO_C_BINDING maps for f2py2e.
+Only required declarations/macros/functions will be used.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+# These map to keys in c2py_map, via forced casting for now, see gh-25229
+iso_c_binding_map = {
+    'integer': {
+        'c_int': 'int',
+        'c_short': 'short',  # 'short' <=> 'int' for now
+        'c_long': 'long',  # 'long' <=> 'int' for now
+        'c_long_long': 'long_long',
+        'c_signed_char': 'signed_char',
+        'c_size_t': 'unsigned',  # size_t <=> 'unsigned' for now
+        'c_int8_t': 'signed_char',  # int8_t <=> 'signed_char' for now
+        'c_int16_t': 'short',  # int16_t <=> 'short' for now
+        'c_int32_t': 'int',  # int32_t <=> 'int' for now
+        'c_int64_t': 'long_long',
+        'c_int_least8_t': 'signed_char',  # int_least8_t <=> 'signed_char' for now
+        'c_int_least16_t': 'short',  # int_least16_t <=> 'short' for now
+        'c_int_least32_t': 'int',  # int_least32_t <=> 'int' for now
+        'c_int_least64_t': 'long_long',
+        'c_int_fast8_t': 'signed_char',  # int_fast8_t <=> 'signed_char' for now
+        'c_int_fast16_t': 'short',  # int_fast16_t <=> 'short' for now
+        'c_int_fast32_t': 'int',  # int_fast32_t <=> 'int' for now
+        'c_int_fast64_t': 'long_long',
+        'c_intmax_t': 'long_long',  # intmax_t <=> 'long_long' for now
+        'c_intptr_t': 'long',  # intptr_t <=> 'long' for now
+        'c_ptrdiff_t': 'long',  # ptrdiff_t <=> 'long' for now
+    },
+    'real': {
+        'c_float': 'float',
+        'c_double': 'double',
+        'c_long_double': 'long_double'
+    },
+    'complex': {
+        'c_float_complex': 'complex_float',
+        'c_double_complex': 'complex_double',
+        'c_long_double_complex': 'complex_long_double'
+    },
+    'logical': {
+        'c_bool': 'unsigned_char'  # _Bool <=> 'unsigned_char' for now
+    },
+    'character': {
+        'c_char': 'char'
+    }
+}
+
+# TODO: See gh-25229
+isoc_c2pycode_map = {}
+iso_c2py_map = {}
+
+isoc_kindmap = {}
+for fortran_type, c_type_dict in iso_c_binding_map.items():
+    for c_type in c_type_dict.keys():
+        isoc_kindmap[c_type] = fortran_type
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..4a4b2ce2b633c3ad2bba4d78ce873fcc4b29bbbb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/_isocbind.pyi
@@ -0,0 +1,13 @@
+from typing import Any, Final
+
+iso_c_binding_map: Final[dict[str, dict[str, str]]] = ...
+
+isoc_c2pycode_map: Final[dict[str, Any]] = {}  # not implemented
+iso_c2py_map: Final[dict[str, Any]] = {}  # not implemented
+
+isoc_kindmap: Final[dict[str, str]] = ...
+
+# namespace pollution
+c_type: str
+c_type_dict: dict[str, str]
+fortran_type: str
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.py b/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f270807b350e2322481f153e52a53fd305e6111
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.py
@@ -0,0 +1,247 @@
+import os
+import re
+
+# START OF CODE VENDORED FROM `numpy.distutils.from_template`
+#############################################################
+"""
+process_file(filename)
+
+  takes templated file .xxx.src and produces .xxx file where .xxx
+  is .pyf .f90 or .f using the following template rules:
+
+  '<..>' denotes a template.
+
+  All function and subroutine blocks in a source file with names that
+  contain '<..>' will be replicated according to the rules in '<..>'.
+
+  The number of comma-separated words in '<..>' will determine the number of
+  replicates.
+
+  '<..>' may have two different forms, named and short. For example,
+
+  named:
+   <p=d,s,z,c> where anywhere inside a block '<p>' will be replaced with
+   'd', 's', 'z', and 'c' for each replicate of the block.
+
+   <_c>  is already defined: <_c=s,d,c,z>
+   <_t>  is already defined: <_t=real,double precision,complex,double complex>
+
+  short:
+   <s,d,c,z>, a short form of the named, useful when no <p> appears inside
+   a block.
+
+  In general, '<..>' contains a comma separated list of arbitrary
+  expressions. If these expression must contain a comma|leftarrow|rightarrow,
+  then prepend the comma|leftarrow|rightarrow with a backslash.
+
+  If an expression matches '\\<index>' then it will be replaced
+  by <index>-th expression.
+
+  Note that all '<..>' forms in a block must have the same number of
+  comma-separated entries.
+
+ Predefined named template rules:
+  <prefix=s,d,c,z>
+  <ftype=real,double precision,complex,double complex>
+  <ftypereal=real,double precision,\\0,\\1>
+  <ctype=float,double,complex_float,complex_double>
+  <ctypereal=float,double,\\0,\\1>
+"""
+
+routine_start_re = re.compile(r'(\n|\A)((     (\$|\*))|)\s*(subroutine|function)\b', re.I)
+routine_end_re = re.compile(r'\n\s*end\s*(subroutine|function)\b.*(\n|\Z)', re.I)
+function_start_re = re.compile(r'\n     (\$|\*)\s*function\b', re.I)
+
+def parse_structure(astr):
+    """ Return a list of tuples for each function or subroutine each
+    tuple is the start and end of a subroutine or function to be
+    expanded.
+    """
+
+    spanlist = []
+    ind = 0
+    while True:
+        m = routine_start_re.search(astr, ind)
+        if m is None:
+            break
+        start = m.start()
+        if function_start_re.match(astr, start, m.end()):
+            while True:
+                i = astr.rfind('\n', ind, start)
+                if i == -1:
+                    break
+                start = i
+                if astr[i:i + 7] != '\n     $':
+                    break
+        start += 1
+        m = routine_end_re.search(astr, m.end())
+        ind = end = (m and m.end() - 1) or len(astr)
+        spanlist.append((start, end))
+    return spanlist
+
+
+template_re = re.compile(r"<\s*(\w[\w\d]*)\s*>")
+named_re = re.compile(r"<\s*(\w[\w\d]*)\s*=\s*(.*?)\s*>")
+list_re = re.compile(r"<\s*((.*?))\s*>")
+
+def find_repl_patterns(astr):
+    reps = named_re.findall(astr)
+    names = {}
+    for rep in reps:
+        name = rep[0].strip() or unique_key(names)
+        repl = rep[1].replace(r'\,', '@comma@')
+        thelist = conv(repl)
+        names[name] = thelist
+    return names
+
+def find_and_remove_repl_patterns(astr):
+    names = find_repl_patterns(astr)
+    astr = re.subn(named_re, '', astr)[0]
+    return astr, names
+
+
+item_re = re.compile(r"\A\\(?P<index>\d+)\Z")
+def conv(astr):
+    b = astr.split(',')
+    l = [x.strip() for x in b]
+    for i in range(len(l)):
+        m = item_re.match(l[i])
+        if m:
+            j = int(m.group('index'))
+            l[i] = l[j]
+    return ','.join(l)
+
+def unique_key(adict):
+    """ Obtain a unique key given a dictionary."""
+    allkeys = list(adict.keys())
+    done = False
+    n = 1
+    while not done:
+        newkey = f'__l{n}'
+        if newkey in allkeys:
+            n += 1
+        else:
+            done = True
+    return newkey
+
+
+template_name_re = re.compile(r'\A\s*(\w[\w\d]*)\s*\Z')
+def expand_sub(substr, names):
+    substr = substr.replace(r'\>', '@rightarrow@')
+    substr = substr.replace(r'\<', '@leftarrow@')
+    lnames = find_repl_patterns(substr)
+    substr = named_re.sub(r"<\1>", substr)  # get rid of definition templates
+
+    def listrepl(mobj):
+        thelist = conv(mobj.group(1).replace(r'\,', '@comma@'))
+        if template_name_re.match(thelist):
+            return f"<{thelist}>"
+        name = None
+        for key in lnames.keys():    # see if list is already in dictionary
+            if lnames[key] == thelist:
+                name = key
+        if name is None:      # this list is not in the dictionary yet
+            name = unique_key(lnames)
+            lnames[name] = thelist
+        return f"<{name}>"
+
+    # convert all lists to named templates
+    # new names are constructed as needed
+    substr = list_re.sub(listrepl, substr)
+
+    numsubs = None
+    base_rule = None
+    rules = {}
+    for r in template_re.findall(substr):
+        if r not in rules:
+            thelist = lnames.get(r, names.get(r, None))
+            if thelist is None:
+                raise ValueError(f'No replicates found for <{r}>')
+            if r not in names and not thelist.startswith('_'):
+                names[r] = thelist
+            rule = [i.replace('@comma@', ',') for i in thelist.split(',')]
+            num = len(rule)
+
+            if numsubs is None:
+                numsubs = num
+                rules[r] = rule
+                base_rule = r
+            elif num == numsubs:
+                rules[r] = rule
+            else:
+                rules_base_rule = ','.join(rules[base_rule])
+                print("Mismatch in number of replacements "
+                      f"(base <{base_rule}={rules_base_rule}>) "
+                      f"for <{r}={thelist}>. Ignoring.")
+    if not rules:
+        return substr
+
+    def namerepl(mobj):
+        name = mobj.group(1)
+        return rules.get(name, (k + 1) * [name])[k]
+
+    newstr = ''
+    for k in range(numsubs):
+        newstr += template_re.sub(namerepl, substr) + '\n\n'
+
+    newstr = newstr.replace('@rightarrow@', '>')
+    newstr = newstr.replace('@leftarrow@', '<')
+    return newstr
+
+def process_str(allstr):
+    newstr = allstr
+    writestr = ''
+
+    struct = parse_structure(newstr)
+
+    oldend = 0
+    names = {}
+    names.update(_special_names)
+    for sub in struct:
+        cleanedstr, defs = find_and_remove_repl_patterns(newstr[oldend:sub[0]])
+        writestr += cleanedstr
+        names.update(defs)
+        writestr += expand_sub(newstr[sub[0]:sub[1]], names)
+        oldend = sub[1]
+    writestr += newstr[oldend:]
+
+    return writestr
+
+
+include_src_re = re.compile(r"(\n|\A)\s*include\s*['\"](?P<name>[\w\d./\\]+\.src)['\"]", re.I)
+
+def resolve_includes(source):
+    d = os.path.dirname(source)
+    with open(source) as fid:
+        lines = []
+        for line in fid:
+            m = include_src_re.match(line)
+            if m:
+                fn = m.group('name')
+                if not os.path.isabs(fn):
+                    fn = os.path.join(d, fn)
+                if os.path.isfile(fn):
+                    lines.extend(resolve_includes(fn))
+                else:
+                    lines.append(line)
+            else:
+                lines.append(line)
+    return lines
+
+def process_file(source):
+    lines = resolve_includes(source)
+    return process_str(''.join(lines))
+
+
+_special_names = find_repl_patterns('''
+<_c=s,d,c,z>
+<_t=real,double precision,complex,double complex>
+<prefix=s,d,c,z>
+<ftype=real,double precision,complex,double complex>
+<ctype=float,double,complex_float,complex_double>
+<ftypereal=real,double precision,\\0,\\1>
+<ctypereal=float,double,\\0,\\1>
+''')
+
+# END OF CODE VENDORED FROM `numpy.distutils.from_template`
+###########################################################
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..99e84604c82efa71f19cb146a4c8c215ac44bf64
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/_src_pyf.pyi
@@ -0,0 +1,28 @@
+import re
+from _typeshed import StrOrBytesPath
+from collections.abc import Mapping
+from typing import Final
+
+routine_start_re: Final[re.Pattern[str]] = ...
+routine_end_re: Final[re.Pattern[str]] = ...
+function_start_re: Final[re.Pattern[str]] = ...
+template_re: Final[re.Pattern[str]] = ...
+named_re: Final[re.Pattern[str]] = ...
+list_re: Final[re.Pattern[str]] = ...
+item_re: Final[re.Pattern[str]] = ...
+template_name_re: Final[re.Pattern[str]] = ...
+include_src_re: Final[re.Pattern[str]] = ...
+
+def parse_structure(astr: str) -> list[tuple[int, int]]: ...
+def find_repl_patterns(astr: str) -> dict[str, str]: ...
+def find_and_remove_repl_patterns(astr: str) -> tuple[str, dict[str, str]]: ...
+def conv(astr: str) -> str: ...
+
+#
+def unique_key(adict: Mapping[str, object]) -> str: ...
+def expand_sub(substr: str, names: dict[str, str]) -> str: ...
+def process_str(allstr: str) -> str: ...
+
+#
+def resolve_includes(source: StrOrBytesPath) -> list[str]: ...
+def process_file(source: StrOrBytesPath) -> str: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.py b/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e9fae4c08ff8db62659fe4423d7be23a9cc7b82
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.py
@@ -0,0 +1,1004 @@
+"""
+Auxiliary functions for f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy (BSD style) LICENSE.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+import pprint
+import re
+import sys
+import types
+from functools import reduce
+
+from . import __version__, cfuncs
+from .cfuncs import errmess
+
+__all__ = [
+    'applyrules', 'debugcapi', 'dictappend', 'errmess', 'gentitle',
+    'getargs2', 'getcallprotoargument', 'getcallstatement',
+    'getfortranname', 'getpymethoddef', 'getrestdoc', 'getusercode',
+    'getusercode1', 'getdimension', 'hasbody', 'hascallstatement', 'hascommon',
+    'hasexternals', 'hasinitvalue', 'hasnote', 'hasresultnote',
+    'isallocatable', 'isarray', 'isarrayofstrings',
+    'ischaracter', 'ischaracterarray', 'ischaracter_or_characterarray',
+    'iscomplex', 'iscstyledirective',
+    'iscomplexarray', 'iscomplexfunction', 'iscomplexfunction_warn',
+    'isdouble', 'isdummyroutine', 'isexternal', 'isfunction',
+    'isfunction_wrap', 'isint1', 'isint1array', 'isinteger', 'isintent_aux',
+    'isintent_c', 'isintent_callback', 'isintent_copy', 'isintent_dict',
+    'isintent_hide', 'isintent_in', 'isintent_inout', 'isintent_inplace',
+    'isintent_nothide', 'isintent_out', 'isintent_overwrite', 'islogical',
+    'islogicalfunction', 'islong_complex', 'islong_double',
+    'islong_doublefunction', 'islong_long', 'islong_longfunction',
+    'ismodule', 'ismoduleroutine', 'isoptional', 'isprivate', 'isvariable',
+    'isrequired', 'isroutine', 'isscalar', 'issigned_long_longarray',
+    'isstring', 'isstringarray', 'isstring_or_stringarray', 'isstringfunction',
+    'issubroutine', 'get_f2py_modulename', 'issubroutine_wrap', 'isthreadsafe',
+    'isunsigned', 'isunsigned_char', 'isunsigned_chararray',
+    'isunsigned_long_long', 'isunsigned_long_longarray', 'isunsigned_short',
+    'isunsigned_shortarray', 'l_and', 'l_not', 'l_or', 'outmess', 'replace',
+    'show', 'stripcomma', 'throw_error', 'isattr_value', 'getuseblocks',
+    'process_f2cmap_dict', 'containscommon', 'containsderivedtypes'
+]
+
+
+f2py_version = __version__.version
+
+
+show = pprint.pprint
+
+options = {}
+debugoptions = []
+wrapfuncs = 1
+
+
+def outmess(t):
+    if options.get('verbose', 1):
+        sys.stdout.write(t)
+
+
+def debugcapi(var):
+    return 'capi' in debugoptions
+
+
+def _ischaracter(var):
+    return 'typespec' in var and var['typespec'] == 'character' and \
+           not isexternal(var)
+
+
+def _isstring(var):
+    return 'typespec' in var and var['typespec'] == 'character' and \
+           not isexternal(var)
+
+
+def ischaracter_or_characterarray(var):
+    return _ischaracter(var) and 'charselector' not in var
+
+
+def ischaracter(var):
+    return ischaracter_or_characterarray(var) and not isarray(var)
+
+
+def ischaracterarray(var):
+    return ischaracter_or_characterarray(var) and isarray(var)
+
+
+def isstring_or_stringarray(var):
+    return _ischaracter(var) and 'charselector' in var
+
+
+def isstring(var):
+    return isstring_or_stringarray(var) and not isarray(var)
+
+
+def isstringarray(var):
+    return isstring_or_stringarray(var) and isarray(var)
+
+
+def isarrayofstrings(var):  # obsolete?
+    # leaving out '*' for now so that `character*(*) a(m)` and `character
+    # a(m,*)` are treated differently. Luckily `character**` is illegal.
+    return isstringarray(var) and var['dimension'][-1] == '(*)'
+
+
+def isarray(var):
+    return 'dimension' in var and not isexternal(var)
+
+
+def isscalar(var):
+    return not (isarray(var) or isstring(var) or isexternal(var))
+
+
+def iscomplex(var):
+    return isscalar(var) and \
+           var.get('typespec') in ['complex', 'double complex']
+
+
+def islogical(var):
+    return isscalar(var) and var.get('typespec') == 'logical'
+
+
+def isinteger(var):
+    return isscalar(var) and var.get('typespec') == 'integer'
+
+
+def isreal(var):
+    return isscalar(var) and var.get('typespec') == 'real'
+
+
+def get_kind(var):
+    try:
+        return var['kindselector']['*']
+    except KeyError:
+        try:
+            return var['kindselector']['kind']
+        except KeyError:
+            pass
+
+
+def isint1(var):
+    return var.get('typespec') == 'integer' \
+        and get_kind(var) == '1' and not isarray(var)
+
+
+def islong_long(var):
+    if not isscalar(var):
+        return 0
+    if var.get('typespec') not in ['integer', 'logical']:
+        return 0
+    return get_kind(var) == '8'
+
+
+def isunsigned_char(var):
+    if not isscalar(var):
+        return 0
+    if var.get('typespec') != 'integer':
+        return 0
+    return get_kind(var) == '-1'
+
+
+def isunsigned_short(var):
+    if not isscalar(var):
+        return 0
+    if var.get('typespec') != 'integer':
+        return 0
+    return get_kind(var) == '-2'
+
+
+def isunsigned(var):
+    if not isscalar(var):
+        return 0
+    if var.get('typespec') != 'integer':
+        return 0
+    return get_kind(var) == '-4'
+
+
+def isunsigned_long_long(var):
+    if not isscalar(var):
+        return 0
+    if var.get('typespec') != 'integer':
+        return 0
+    return get_kind(var) == '-8'
+
+
+def isdouble(var):
+    if not isscalar(var):
+        return 0
+    if not var.get('typespec') == 'real':
+        return 0
+    return get_kind(var) == '8'
+
+
+def islong_double(var):
+    if not isscalar(var):
+        return 0
+    if not var.get('typespec') == 'real':
+        return 0
+    return get_kind(var) == '16'
+
+
+def islong_complex(var):
+    if not iscomplex(var):
+        return 0
+    return get_kind(var) == '32'
+
+
+def iscomplexarray(var):
+    return isarray(var) and \
+           var.get('typespec') in ['complex', 'double complex']
+
+
+def isint1array(var):
+    return isarray(var) and var.get('typespec') == 'integer' \
+        and get_kind(var) == '1'
+
+
+def isunsigned_chararray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '-1'
+
+
+def isunsigned_shortarray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '-2'
+
+
+def isunsignedarray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '-4'
+
+
+def isunsigned_long_longarray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '-8'
+
+
+def issigned_chararray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '1'
+
+
+def issigned_shortarray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '2'
+
+
+def issigned_array(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '4'
+
+
+def issigned_long_longarray(var):
+    return isarray(var) and var.get('typespec') in ['integer', 'logical']\
+        and get_kind(var) == '8'
+
+
+def isallocatable(var):
+    return 'attrspec' in var and 'allocatable' in var['attrspec']
+
+
+def ismutable(var):
+    return not ('dimension' not in var or isstring(var))
+
+
+def ismoduleroutine(rout):
+    return 'modulename' in rout
+
+
+def ismodule(rout):
+    return 'block' in rout and 'module' == rout['block']
+
+
+def isfunction(rout):
+    return 'block' in rout and 'function' == rout['block']
+
+
+def isfunction_wrap(rout):
+    if isintent_c(rout):
+        return 0
+    return wrapfuncs and isfunction(rout) and (not isexternal(rout))
+
+
+def issubroutine(rout):
+    return 'block' in rout and 'subroutine' == rout['block']
+
+
+def issubroutine_wrap(rout):
+    if isintent_c(rout):
+        return 0
+    return issubroutine(rout) and hasassumedshape(rout)
+
+def isattr_value(var):
+    return 'value' in var.get('attrspec', [])
+
+
+def hasassumedshape(rout):
+    if rout.get('hasassumedshape'):
+        return True
+    for a in rout['args']:
+        for d in rout['vars'].get(a, {}).get('dimension', []):
+            if d == ':':
+                rout['hasassumedshape'] = True
+                return True
+    return False
+
+
+def requiresf90wrapper(rout):
+    return ismoduleroutine(rout) or hasassumedshape(rout)
+
+
+def isroutine(rout):
+    return isfunction(rout) or issubroutine(rout)
+
+
+def islogicalfunction(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return islogical(rout['vars'][a])
+    return 0
+
+
+def islong_longfunction(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return islong_long(rout['vars'][a])
+    return 0
+
+
+def islong_doublefunction(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return islong_double(rout['vars'][a])
+    return 0
+
+
+def iscomplexfunction(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return iscomplex(rout['vars'][a])
+    return 0
+
+
+def iscomplexfunction_warn(rout):
+    if iscomplexfunction(rout):
+        outmess("""\
+    **************************************************************
+        Warning: code with a function returning complex value
+        may not work correctly with your Fortran compiler.
+        When using GNU gcc/g77 compilers, codes should work
+        correctly for callbacks with:
+        f2py -c -DF2PY_CB_RETURNCOMPLEX
+    **************************************************************\n""")
+        return 1
+    return 0
+
+
+def isstringfunction(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return isstring(rout['vars'][a])
+    return 0
+
+
+def hasexternals(rout):
+    return 'externals' in rout and rout['externals']
+
+
+def isthreadsafe(rout):
+    return 'f2pyenhancements' in rout and \
+           'threadsafe' in rout['f2pyenhancements']
+
+
+def hasvariables(rout):
+    return 'vars' in rout and rout['vars']
+
+
+def isoptional(var):
+    return ('attrspec' in var and 'optional' in var['attrspec'] and
+            'required' not in var['attrspec']) and isintent_nothide(var)
+
+
+def isexternal(var):
+    return 'attrspec' in var and 'external' in var['attrspec']
+
+
+def getdimension(var):
+    dimpattern = r"\((.*?)\)"
+    if 'attrspec' in var.keys():
+        if any('dimension' in s for s in var['attrspec']):
+            return next(re.findall(dimpattern, v) for v in var['attrspec'])
+
+
+def isrequired(var):
+    return not isoptional(var) and isintent_nothide(var)
+
+
+def iscstyledirective(f2py_line):
+    directives = {"callstatement", "callprotoargument", "pymethoddef"}
+    return any(directive in f2py_line.lower() for directive in directives)
+
+
+def isintent_in(var):
+    if 'intent' not in var:
+        return 1
+    if 'hide' in var['intent']:
+        return 0
+    if 'inplace' in var['intent']:
+        return 0
+    if 'in' in var['intent']:
+        return 1
+    if 'out' in var['intent']:
+        return 0
+    if 'inout' in var['intent']:
+        return 0
+    if 'outin' in var['intent']:
+        return 0
+    return 1
+
+
+def isintent_inout(var):
+    return ('intent' in var and ('inout' in var['intent'] or
+            'outin' in var['intent']) and 'in' not in var['intent'] and
+            'hide' not in var['intent'] and 'inplace' not in var['intent'])
+
+
+def isintent_out(var):
+    return 'out' in var.get('intent', [])
+
+
+def isintent_hide(var):
+    return ('intent' in var and ('hide' in var['intent'] or
+            ('out' in var['intent'] and 'in' not in var['intent'] and
+                (not l_or(isintent_inout, isintent_inplace)(var)))))
+
+
+def isintent_nothide(var):
+    return not isintent_hide(var)
+
+
+def isintent_c(var):
+    return 'c' in var.get('intent', [])
+
+
+def isintent_cache(var):
+    return 'cache' in var.get('intent', [])
+
+
+def isintent_copy(var):
+    return 'copy' in var.get('intent', [])
+
+
+def isintent_overwrite(var):
+    return 'overwrite' in var.get('intent', [])
+
+
+def isintent_callback(var):
+    return 'callback' in var.get('intent', [])
+
+
+def isintent_inplace(var):
+    return 'inplace' in var.get('intent', [])
+
+
+def isintent_aux(var):
+    return 'aux' in var.get('intent', [])
+
+
+def isintent_aligned4(var):
+    return 'aligned4' in var.get('intent', [])
+
+
+def isintent_aligned8(var):
+    return 'aligned8' in var.get('intent', [])
+
+
+def isintent_aligned16(var):
+    return 'aligned16' in var.get('intent', [])
+
+
+isintent_dict = {isintent_in: 'INTENT_IN', isintent_inout: 'INTENT_INOUT',
+                 isintent_out: 'INTENT_OUT', isintent_hide: 'INTENT_HIDE',
+                 isintent_cache: 'INTENT_CACHE',
+                 isintent_c: 'INTENT_C', isoptional: 'OPTIONAL',
+                 isintent_inplace: 'INTENT_INPLACE',
+                 isintent_aligned4: 'INTENT_ALIGNED4',
+                 isintent_aligned8: 'INTENT_ALIGNED8',
+                 isintent_aligned16: 'INTENT_ALIGNED16',
+                 }
+
+
+def isprivate(var):
+    return 'attrspec' in var and 'private' in var['attrspec']
+
+
+def isvariable(var):
+    # heuristic to find public/private declarations of filtered subroutines
+    if len(var) == 1 and 'attrspec' in var and \
+            var['attrspec'][0] in ('public', 'private'):
+        is_var = False
+    else:
+        is_var = True
+    return is_var
+
+def hasinitvalue(var):
+    return '=' in var
+
+
+def hasinitvalueasstring(var):
+    if not hasinitvalue(var):
+        return 0
+    return var['='][0] in ['"', "'"]
+
+
+def hasnote(var):
+    return 'note' in var
+
+
+def hasresultnote(rout):
+    if not isfunction(rout):
+        return 0
+    if 'result' in rout:
+        a = rout['result']
+    else:
+        a = rout['name']
+    if a in rout['vars']:
+        return hasnote(rout['vars'][a])
+    return 0
+
+
+def hascommon(rout):
+    return 'common' in rout
+
+
+def containscommon(rout):
+    if hascommon(rout):
+        return 1
+    if hasbody(rout):
+        for b in rout['body']:
+            if containscommon(b):
+                return 1
+    return 0
+
+
+def hasderivedtypes(rout):
+    return ('block' in rout) and rout['block'] == 'type'
+
+
+def containsderivedtypes(rout):
+    if hasderivedtypes(rout):
+        return 1
+    if hasbody(rout):
+        for b in rout['body']:
+            if hasderivedtypes(b):
+                return 1
+    return 0
+
+
+def containsmodule(block):
+    if ismodule(block):
+        return 1
+    if not hasbody(block):
+        return 0
+    for b in block['body']:
+        if containsmodule(b):
+            return 1
+    return 0
+
+
+def hasbody(rout):
+    return 'body' in rout
+
+
+def hascallstatement(rout):
+    return getcallstatement(rout) is not None
+
+
+def istrue(var):
+    return 1
+
+
+def isfalse(var):
+    return 0
+
+
+class F2PYError(Exception):
+    pass
+
+
+class throw_error:
+
+    def __init__(self, mess):
+        self.mess = mess
+
+    def __call__(self, var):
+        mess = f'\n\n  var = {var}\n  Message: {self.mess}\n'
+        raise F2PYError(mess)
+
+
+def l_and(*f):
+    l1, l2 = 'lambda v', []
+    for i in range(len(f)):
+        l1 = '%s,f%d=f[%d]' % (l1, i, i)
+        l2.append('f%d(v)' % (i))
+    return eval(f"{l1}:{' and '.join(l2)}")
+
+
+def l_or(*f):
+    l1, l2 = 'lambda v', []
+    for i in range(len(f)):
+        l1 = '%s,f%d=f[%d]' % (l1, i, i)
+        l2.append('f%d(v)' % (i))
+    return eval(f"{l1}:{' or '.join(l2)}")
+
+
+def l_not(f):
+    return eval('lambda v,f=f:not f(v)')
+
+
+def isdummyroutine(rout):
+    try:
+        return rout['f2pyenhancements']['fortranname'] == ''
+    except KeyError:
+        return 0
+
+
+def getfortranname(rout):
+    try:
+        name = rout['f2pyenhancements']['fortranname']
+        if name == '':
+            raise KeyError
+        if not name:
+            errmess(f"Failed to use fortranname from {rout['f2pyenhancements']}\n")
+            raise KeyError
+    except KeyError:
+        name = rout['name']
+    return name
+
+
+def getmultilineblock(rout, blockname, comment=1, counter=0):
+    try:
+        r = rout['f2pyenhancements'].get(blockname)
+    except KeyError:
+        return
+    if not r:
+        return
+    if counter > 0 and isinstance(r, str):
+        return
+    if isinstance(r, list):
+        if counter >= len(r):
+            return
+        r = r[counter]
+    if r[:3] == "'''":
+        if comment:
+            r = '\t/* start ' + blockname + \
+                ' multiline (' + repr(counter) + ') */\n' + r[3:]
+        else:
+            r = r[3:]
+        if r[-3:] == "'''":
+            if comment:
+                r = r[:-3] + '\n\t/* end multiline (' + repr(counter) + ')*/'
+            else:
+                r = r[:-3]
+        else:
+            errmess(f"{blockname} multiline block should end with `'''`: {repr(r)}\n")
+    return r
+
+
+def getcallstatement(rout):
+    return getmultilineblock(rout, 'callstatement')
+
+
+def getcallprotoargument(rout, cb_map={}):
+    r = getmultilineblock(rout, 'callprotoargument', comment=0)
+    if r:
+        return r
+    if hascallstatement(rout):
+        outmess(
+            'warning: callstatement is defined without callprotoargument\n')
+        return
+    from .capi_maps import getctype
+    arg_types, arg_types2 = [], []
+    if l_and(isstringfunction, l_not(isfunction_wrap))(rout):
+        arg_types.extend(['char*', 'size_t'])
+    for n in rout['args']:
+        var = rout['vars'][n]
+        if isintent_callback(var):
+            continue
+        if n in cb_map:
+            ctype = cb_map[n] + '_typedef'
+        else:
+            ctype = getctype(var)
+            if l_and(isintent_c, l_or(isscalar, iscomplex))(var):
+                pass
+            elif isstring(var):
+                pass
+            elif not isattr_value(var):
+                ctype = ctype + '*'
+            if (isstring(var)
+                 or isarrayofstrings(var)  # obsolete?
+                 or isstringarray(var)):
+                arg_types2.append('size_t')
+        arg_types.append(ctype)
+
+    proto_args = ','.join(arg_types + arg_types2)
+    if not proto_args:
+        proto_args = 'void'
+    return proto_args
+
+
+def getusercode(rout):
+    return getmultilineblock(rout, 'usercode')
+
+
+def getusercode1(rout):
+    return getmultilineblock(rout, 'usercode', counter=1)
+
+
+def getpymethoddef(rout):
+    return getmultilineblock(rout, 'pymethoddef')
+
+
+def getargs(rout):
+    sortargs, args = [], []
+    if 'args' in rout:
+        args = rout['args']
+        if 'sortvars' in rout:
+            for a in rout['sortvars']:
+                if a in args:
+                    sortargs.append(a)
+            for a in args:
+                if a not in sortargs:
+                    sortargs.append(a)
+        else:
+            sortargs = rout['args']
+    return args, sortargs
+
+
+def getargs2(rout):
+    sortargs, args = [], rout.get('args', [])
+    auxvars = [a for a in rout['vars'].keys() if isintent_aux(rout['vars'][a])
+               and a not in args]
+    args = auxvars + args
+    if 'sortvars' in rout:
+        for a in rout['sortvars']:
+            if a in args:
+                sortargs.append(a)
+        for a in args:
+            if a not in sortargs:
+                sortargs.append(a)
+    else:
+        sortargs = auxvars + rout['args']
+    return args, sortargs
+
+
+def getrestdoc(rout):
+    if 'f2pymultilines' not in rout:
+        return None
+    k = None
+    if rout['block'] == 'python module':
+        k = rout['block'], rout['name']
+    return rout['f2pymultilines'].get(k, None)
+
+
+def gentitle(name):
+    ln = (80 - len(name) - 6) // 2
+    return f"/*{ln * '*'} {name} {ln * '*'}*/"
+
+
+def flatlist(lst):
+    if isinstance(lst, list):
+        return reduce(lambda x, y, f=flatlist: x + f(y), lst, [])
+    return [lst]
+
+
+def stripcomma(s):
+    if s and s[-1] == ',':
+        return s[:-1]
+    return s
+
+
+def replace(str, d, defaultsep=''):
+    if isinstance(d, list):
+        return [replace(str, _m, defaultsep) for _m in d]
+    if isinstance(str, list):
+        return [replace(_m, d, defaultsep) for _m in str]
+    for k in 2 * list(d.keys()):
+        if k == 'separatorsfor':
+            continue
+        if 'separatorsfor' in d and k in d['separatorsfor']:
+            sep = d['separatorsfor'][k]
+        else:
+            sep = defaultsep
+        if isinstance(d[k], list):
+            str = str.replace(f'#{k}#', sep.join(flatlist(d[k])))
+        else:
+            str = str.replace(f'#{k}#', d[k])
+    return str
+
+
+def dictappend(rd, ar):
+    if isinstance(ar, list):
+        for a in ar:
+            rd = dictappend(rd, a)
+        return rd
+    for k in ar.keys():
+        if k[0] == '_':
+            continue
+        if k in rd:
+            if isinstance(rd[k], str):
+                rd[k] = [rd[k]]
+            if isinstance(rd[k], list):
+                if isinstance(ar[k], list):
+                    rd[k] = rd[k] + ar[k]
+                else:
+                    rd[k].append(ar[k])
+            elif isinstance(rd[k], dict):
+                if isinstance(ar[k], dict):
+                    if k == 'separatorsfor':
+                        for k1 in ar[k].keys():
+                            if k1 not in rd[k]:
+                                rd[k][k1] = ar[k][k1]
+                    else:
+                        rd[k] = dictappend(rd[k], ar[k])
+        else:
+            rd[k] = ar[k]
+    return rd
+
+
+def applyrules(rules, d, var={}):
+    ret = {}
+    if isinstance(rules, list):
+        for r in rules:
+            rr = applyrules(r, d, var)
+            ret = dictappend(ret, rr)
+            if '_break' in rr:
+                break
+        return ret
+    if '_check' in rules and (not rules['_check'](var)):
+        return ret
+    if 'need' in rules:
+        res = applyrules({'needs': rules['need']}, d, var)
+        if 'needs' in res:
+            cfuncs.append_needs(res['needs'])
+
+    for k in rules.keys():
+        if k == 'separatorsfor':
+            ret[k] = rules[k]
+            continue
+        if isinstance(rules[k], str):
+            ret[k] = replace(rules[k], d)
+        elif isinstance(rules[k], list):
+            ret[k] = []
+            for i in rules[k]:
+                ar = applyrules({k: i}, d, var)
+                if k in ar:
+                    ret[k].append(ar[k])
+        elif k[0] == '_':
+            continue
+        elif isinstance(rules[k], dict):
+            ret[k] = []
+            for k1 in rules[k].keys():
+                if isinstance(k1, types.FunctionType) and k1(var):
+                    if isinstance(rules[k][k1], list):
+                        for i in rules[k][k1]:
+                            if isinstance(i, dict):
+                                res = applyrules({'supertext': i}, d, var)
+                                i = res.get('supertext', '')
+                            ret[k].append(replace(i, d))
+                    else:
+                        i = rules[k][k1]
+                        if isinstance(i, dict):
+                            res = applyrules({'supertext': i}, d)
+                            i = res.get('supertext', '')
+                        ret[k].append(replace(i, d))
+        else:
+            errmess(f'applyrules: ignoring rule {repr(rules[k])}.\n')
+        if isinstance(ret[k], list):
+            if len(ret[k]) == 1:
+                ret[k] = ret[k][0]
+            if ret[k] == []:
+                del ret[k]
+    return ret
+
+
+_f2py_module_name_match = re.compile(r'\s*python\s*module\s*(?P<name>[\w_]+)',
+                                     re.I).match
+_f2py_user_module_name_match = re.compile(r'\s*python\s*module\s*(?P<name>[\w_]*?'
+                                          r'__user__[\w_]*)', re.I).match
+
+def get_f2py_modulename(source):
+    name = None
+    with open(source) as f:
+        for line in f:
+            m = _f2py_module_name_match(line)
+            if m:
+                if _f2py_user_module_name_match(line):  # skip *__user__* names
+                    continue
+                name = m.group('name')
+                break
+    return name
+
+def getuseblocks(pymod):
+    all_uses = []
+    for inner in pymod['body']:
+        for modblock in inner['body']:
+            if modblock.get('use'):
+                all_uses.extend([x for x in modblock.get("use").keys() if "__" not in x])
+    return all_uses
+
+def process_f2cmap_dict(f2cmap_all, new_map, c2py_map, verbose=False):
+    """
+    Update the Fortran-to-C type mapping dictionary with new mappings and
+    return a list of successfully mapped C types.
+
+    This function integrates a new mapping dictionary into an existing
+    Fortran-to-C type mapping dictionary. It ensures that all keys are in
+    lowercase and validates new entries against a given C-to-Python mapping
+    dictionary. Redefinitions and invalid entries are reported with a warning.
+
+    Parameters
+    ----------
+    f2cmap_all : dict
+        The existing Fortran-to-C type mapping dictionary that will be updated.
+        It should be a dictionary of dictionaries where the main keys represent
+        Fortran types and the nested dictionaries map Fortran type specifiers
+        to corresponding C types.
+
+    new_map : dict
+        A dictionary containing new type mappings to be added to `f2cmap_all`.
+        The structure should be similar to `f2cmap_all`, with keys representing
+        Fortran types and values being dictionaries of type specifiers and their
+        C type equivalents.
+
+    c2py_map : dict
+        A dictionary used for validating the C types in `new_map`. It maps C
+        types to corresponding Python types and is used to ensure that the C
+        types specified in `new_map` are valid.
+
+    verbose : boolean
+        A flag used to provide information about the types mapped
+
+    Returns
+    -------
+    tuple of (dict, list)
+        The updated Fortran-to-C type mapping dictionary and a list of
+        successfully mapped C types.
+    """
+    f2cmap_mapped = []
+
+    new_map_lower = {}
+    for k, d1 in new_map.items():
+        d1_lower = {k1.lower(): v1 for k1, v1 in d1.items()}
+        new_map_lower[k.lower()] = d1_lower
+
+    for k, d1 in new_map_lower.items():
+        if k not in f2cmap_all:
+            f2cmap_all[k] = {}
+
+        for k1, v1 in d1.items():
+            if v1 in c2py_map:
+                if k1 in f2cmap_all[k]:
+                    outmess(
+                        "\tWarning: redefinition of {'%s':{'%s':'%s'->'%s'}}\n"
+                        % (k, k1, f2cmap_all[k][k1], v1)
+                    )
+                f2cmap_all[k][k1] = v1
+                if verbose:
+                    outmess(f'\tMapping "{k}(kind={k1})" to "{v1}\"\n')
+                f2cmap_mapped.append(v1)
+            elif verbose:
+                errmess(
+                    "\tIgnoring map {'%s':{'%s':'%s'}}: '%s' must be in %s\n"
+                    % (k, k1, v1, v1, list(c2py_map.keys()))
+                )
+
+    return f2cmap_all, f2cmap_mapped
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..174556a91222b9343fe45b48482e5d4270cd8c04
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/auxfuncs.pyi
@@ -0,0 +1,262 @@
+from _typeshed import FileDescriptorOrPath
+from collections.abc import Callable, Mapping
+from pprint import pprint as show
+from typing import Any, Final, Literal as L, Never, TypeAlias, TypeVar, overload
+
+from .cfuncs import errmess
+
+__all__ = [
+    "applyrules",
+    "containscommon",
+    "containsderivedtypes",
+    "debugcapi",
+    "dictappend",
+    "errmess",
+    "gentitle",
+    "get_f2py_modulename",
+    "getargs2",
+    "getcallprotoargument",
+    "getcallstatement",
+    "getdimension",
+    "getfortranname",
+    "getpymethoddef",
+    "getrestdoc",
+    "getuseblocks",
+    "getusercode",
+    "getusercode1",
+    "hasbody",
+    "hascallstatement",
+    "hascommon",
+    "hasexternals",
+    "hasinitvalue",
+    "hasnote",
+    "hasresultnote",
+    "isallocatable",
+    "isarray",
+    "isarrayofstrings",
+    "isattr_value",
+    "ischaracter",
+    "ischaracter_or_characterarray",
+    "ischaracterarray",
+    "iscomplex",
+    "iscomplexarray",
+    "iscomplexfunction",
+    "iscomplexfunction_warn",
+    "iscstyledirective",
+    "isdouble",
+    "isdummyroutine",
+    "isexternal",
+    "isfunction",
+    "isfunction_wrap",
+    "isint1",
+    "isint1array",
+    "isinteger",
+    "isintent_aux",
+    "isintent_c",
+    "isintent_callback",
+    "isintent_copy",
+    "isintent_dict",
+    "isintent_hide",
+    "isintent_in",
+    "isintent_inout",
+    "isintent_inplace",
+    "isintent_nothide",
+    "isintent_out",
+    "isintent_overwrite",
+    "islogical",
+    "islogicalfunction",
+    "islong_complex",
+    "islong_double",
+    "islong_doublefunction",
+    "islong_long",
+    "islong_longfunction",
+    "ismodule",
+    "ismoduleroutine",
+    "isoptional",
+    "isprivate",
+    "isrequired",
+    "isroutine",
+    "isscalar",
+    "issigned_long_longarray",
+    "isstring",
+    "isstring_or_stringarray",
+    "isstringarray",
+    "isstringfunction",
+    "issubroutine",
+    "issubroutine_wrap",
+    "isthreadsafe",
+    "isunsigned",
+    "isunsigned_char",
+    "isunsigned_chararray",
+    "isunsigned_long_long",
+    "isunsigned_long_longarray",
+    "isunsigned_short",
+    "isunsigned_shortarray",
+    "isvariable",
+    "l_and",
+    "l_not",
+    "l_or",
+    "outmess",
+    "process_f2cmap_dict",
+    "replace",
+    "show",
+    "stripcomma",
+    "throw_error",
+]
+
+###
+
+_VT = TypeVar("_VT")
+_RT = TypeVar("_RT")
+
+_Var: TypeAlias = Mapping[str, list[str]]
+_ROut: TypeAlias = Mapping[str, str]
+_F2CMap: TypeAlias = Mapping[str, Mapping[str, str]]
+
+_Bool: TypeAlias = bool | L[0, 1]
+_Intent: TypeAlias = L[
+    "INTENT_IN",
+    "INTENT_OUT",
+    "INTENT_INOUT",
+    "INTENT_C",
+    "INTENT_CACHE",
+    "INTENT_HIDE",
+    "INTENT_INPLACE",
+    "INTENT_ALIGNED4",
+    "INTENT_ALIGNED8",
+    "INTENT_ALIGNED16",
+    "OPTIONAL",
+]
+
+###
+
+isintent_dict: dict[Callable[[_Var], _Bool], _Intent]
+
+class F2PYError(Exception): ...
+
+class throw_error:
+    mess: Final[str]
+    def __init__(self, /, mess: str) -> None: ...
+    def __call__(self, /, var: _Var) -> Never: ...  # raises F2PYError
+
+#
+def l_and(*f: tuple[str, Callable[[_VT], _RT]]) -> Callable[[_VT], _RT]: ...
+def l_or(*f: tuple[str, Callable[[_VT], _RT]]) -> Callable[[_VT], _RT]: ...
+def l_not(f: tuple[str, Callable[[_VT], _RT]]) -> Callable[[_VT], _RT]: ...
+
+#
+def outmess(t: str) -> None: ...
+def debugcapi(var: _Var) -> bool: ...
+
+#
+def hasinitvalue(var: _Var | str) -> bool: ...
+def hasnote(var: _Var | str) -> bool: ...
+def ischaracter(var: _Var) -> bool: ...
+def ischaracterarray(var: _Var) -> bool: ...
+def ischaracter_or_characterarray(var: _Var) -> bool: ...
+def isstring(var: _Var) -> bool: ...
+def isstringarray(var: _Var) -> bool: ...
+def isstring_or_stringarray(var: _Var) -> bool: ...
+def isarray(var: _Var) -> bool: ...
+def isarrayofstrings(var: _Var) -> bool: ...
+def isscalar(var: _Var) -> bool: ...
+def iscomplex(var: _Var) -> bool: ...
+def islogical(var: _Var) -> bool: ...
+def isinteger(var: _Var) -> bool: ...
+def isint1(var: _Var) -> bool: ...
+def isint1array(var: _Var) -> bool: ...
+def islong_long(var: _Var) -> _Bool: ...
+def isunsigned(var: _Var) -> _Bool: ...
+def isunsigned_char(var: _Var) -> _Bool: ...
+def isunsigned_chararray(var: _Var) -> bool: ...
+def isunsigned_short(var: _Var) -> _Bool: ...
+def isunsigned_shortarray(var: _Var) -> bool: ...
+def isunsigned_long_long(var: _Var) -> _Bool: ...
+def isunsigned_long_longarray(var: _Var) -> bool: ...
+def issigned_long_longarray(var: _Var) -> bool: ...
+def isdouble(var: _Var) -> _Bool: ...
+def islong_double(var: _Var) -> _Bool: ...
+def islong_complex(var: _Var) -> _Bool: ...
+def iscomplexarray(var: _Var) -> bool: ...
+def isallocatable(var: _Var) -> bool: ...
+def isattr_value(var: _Var) -> bool: ...
+def isoptional(var: _Var) -> bool: ...
+def isexternal(var: _Var) -> bool: ...
+def isrequired(var: _Var) -> bool: ...
+def isprivate(var: _Var) -> bool: ...
+def isvariable(var: _Var) -> bool: ...
+def isintent_in(var: _Var) -> _Bool: ...
+def isintent_inout(var: _Var) -> bool: ...
+def isintent_out(var: _Var) -> bool: ...
+def isintent_hide(var: _Var) -> bool: ...
+def isintent_nothide(var: _Var) -> bool: ...
+def isintent_c(var: _Var) -> bool: ...
+def isintent_cache(var: _Var) -> bool: ...
+def isintent_copy(var: _Var) -> bool: ...
+def isintent_overwrite(var: _Var) -> bool: ...
+def isintent_callback(var: _Var) -> bool: ...
+def isintent_inplace(var: _Var) -> bool: ...
+def isintent_aux(var: _Var) -> bool: ...
+
+#
+def containsderivedtypes(rout: _ROut) -> L[0, 1]: ...
+def containscommon(rout: _ROut) -> _Bool: ...
+def hasexternals(rout: _ROut) -> bool: ...
+def hasresultnote(rout: _ROut) -> _Bool: ...
+def hasbody(rout: _ROut) -> _Bool: ...
+def hascommon(rout: _ROut) -> bool: ...
+def hasderivedtypes(rout: _ROut) -> bool: ...
+def hascallstatement(rout: _ROut) -> bool: ...
+def isroutine(rout: _ROut) -> bool: ...
+def ismodule(rout: _ROut) -> bool: ...
+def ismoduleroutine(rout: _ROut) -> bool: ...
+def issubroutine(rout: _ROut) -> bool: ...
+def issubroutine_wrap(rout: _ROut) -> _Bool: ...
+def isfunction(rout: _ROut) -> bool: ...
+def isfunction_wrap(rout: _ROut) -> _Bool: ...
+def islogicalfunction(rout: _ROut) -> _Bool: ...
+def islong_longfunction(rout: _ROut) -> _Bool: ...
+def islong_doublefunction(rout: _ROut) -> _Bool: ...
+def iscomplexfunction(rout: _ROut) -> _Bool: ...
+def iscomplexfunction_warn(rout: _ROut) -> _Bool: ...
+def isstringfunction(rout: _ROut) -> _Bool: ...
+def isthreadsafe(rout: _ROut) -> bool: ...
+def isdummyroutine(rout: _ROut) -> _Bool: ...
+def iscstyledirective(f2py_line: str) -> bool: ...
+
+# .
+def getdimension(var: _Var) -> list[Any] | None: ...
+def getfortranname(rout: _ROut) -> str: ...
+def getmultilineblock(rout: _ROut, blockname: str, comment: _Bool = 1, counter: int = 0) -> str | None: ...
+def getcallstatement(rout: _ROut) -> str | None: ...
+def getcallprotoargument(rout: _ROut, cb_map: dict[str, str] = {}) -> str: ...
+def getusercode(rout: _ROut) -> str | None: ...
+def getusercode1(rout: _ROut) -> str | None: ...
+def getpymethoddef(rout: _ROut) -> str | None: ...
+def getargs(rout: _ROut) -> tuple[list[str], list[str]]: ...
+def getargs2(rout: _ROut) -> tuple[list[str], list[str]]: ...
+def getrestdoc(rout: _ROut) -> str | None: ...
+
+#
+def gentitle(name: str) -> str: ...
+def stripcomma(s: str) -> str: ...
+@overload
+def replace(str: str, d: list[str], defaultsep: str = "") -> list[str]: ...
+@overload
+def replace(str: list[str], d: str, defaultsep: str = "") -> list[str]: ...
+@overload
+def replace(str: str, d: str, defaultsep: str = "") -> str: ...
+
+#
+def dictappend(rd: Mapping[str, object], ar: Mapping[str, object] | list[Mapping[str, object]]) -> dict[str, Any]: ...
+def applyrules(rules: Mapping[str, object], d: Mapping[str, object], var: _Var = {}) -> dict[str, Any]: ...
+
+#
+def get_f2py_modulename(source: FileDescriptorOrPath) -> str: ...
+def getuseblocks(pymod: Mapping[str, Mapping[str, Mapping[str, str]]]) -> list[str]: ...
+def process_f2cmap_dict(
+    f2cmap_all: _F2CMap,
+    new_map: _F2CMap,
+    c2py_map: _F2CMap,
+    verbose: bool = False,
+) -> tuple[dict[str, dict[str, str]], list[str]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.py b/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ab9e4067b7d5d016823545399060569414c5331
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.py
@@ -0,0 +1,811 @@
+"""
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+from . import __version__
+
+f2py_version = __version__.version
+
+import copy
+import os
+import re
+
+from . import cb_rules
+from ._isocbind import iso_c2py_map, iso_c_binding_map, isoc_c2pycode_map
+
+# The environment provided by auxfuncs.py is needed for some calls to eval.
+# As the needed functions cannot be determined by static inspection of the
+# code, it is safest to use import * pending a major refactoring of f2py.
+from .auxfuncs import *
+from .crackfortran import markoutercomma
+
+__all__ = [
+    'getctype', 'getstrlength', 'getarrdims', 'getpydocsign',
+    'getarrdocsign', 'getinit', 'sign2map', 'routsign2map', 'modsign2map',
+    'cb_sign2map', 'cb_routsign2map', 'common_sign2map', 'process_f2cmap_dict'
+]
+
+
+depargs = []
+lcb_map = {}
+lcb2_map = {}
+# forced casting: mainly caused by the fact that Python or Numeric
+#                 C/APIs do not support the corresponding C types.
+c2py_map = {'double': 'float',
+            'float': 'float',                          # forced casting
+            'long_double': 'float',                    # forced casting
+            'char': 'int',                             # forced casting
+            'signed_char': 'int',                      # forced casting
+            'unsigned_char': 'int',                    # forced casting
+            'short': 'int',                            # forced casting
+            'unsigned_short': 'int',                   # forced casting
+            'int': 'int',                              # forced casting
+            'long': 'int',
+            'long_long': 'long',
+            'unsigned': 'int',                         # forced casting
+            'complex_float': 'complex',                # forced casting
+            'complex_double': 'complex',
+            'complex_long_double': 'complex',          # forced casting
+            'string': 'string',
+            'character': 'bytes',
+            }
+
+c2capi_map = {'double': 'NPY_DOUBLE',
+                'float': 'NPY_FLOAT',
+                'long_double': 'NPY_LONGDOUBLE',
+                'char': 'NPY_BYTE',
+                'unsigned_char': 'NPY_UBYTE',
+                'signed_char': 'NPY_BYTE',
+                'short': 'NPY_SHORT',
+                'unsigned_short': 'NPY_USHORT',
+                'int': 'NPY_INT',
+                'unsigned': 'NPY_UINT',
+                'long': 'NPY_LONG',
+                'unsigned_long': 'NPY_ULONG',
+                'long_long': 'NPY_LONGLONG',
+                'unsigned_long_long': 'NPY_ULONGLONG',
+                'complex_float': 'NPY_CFLOAT',
+                'complex_double': 'NPY_CDOUBLE',
+                'complex_long_double': 'NPY_CDOUBLE',
+                'string': 'NPY_STRING',
+                'character': 'NPY_STRING'}
+
+c2pycode_map = {'double': 'd',
+                'float': 'f',
+                'long_double': 'g',
+                'char': 'b',
+                'unsigned_char': 'B',
+                'signed_char': 'b',
+                'short': 'h',
+                'unsigned_short': 'H',
+                'int': 'i',
+                'unsigned': 'I',
+                'long': 'l',
+                'unsigned_long': 'L',
+                'long_long': 'q',
+                'unsigned_long_long': 'Q',
+                'complex_float': 'F',
+                'complex_double': 'D',
+                'complex_long_double': 'G',
+                'string': 'S',
+                'character': 'c'}
+
+# https://docs.python.org/3/c-api/arg.html#building-values
+c2buildvalue_map = {'double': 'd',
+                    'float': 'f',
+                    'char': 'b',
+                    'signed_char': 'b',
+                    'short': 'h',
+                    'int': 'i',
+                    'long': 'l',
+                    'long_long': 'L',
+                    'complex_float': 'N',
+                    'complex_double': 'N',
+                    'complex_long_double': 'N',
+                    'string': 'y',
+                    'character': 'c'}
+
+f2cmap_all = {'real': {'': 'float', '4': 'float', '8': 'double',
+                       '12': 'long_double', '16': 'long_double'},
+              'integer': {'': 'int', '1': 'signed_char', '2': 'short',
+                          '4': 'int', '8': 'long_long',
+                          '-1': 'unsigned_char', '-2': 'unsigned_short',
+                          '-4': 'unsigned', '-8': 'unsigned_long_long'},
+              'complex': {'': 'complex_float', '8': 'complex_float',
+                          '16': 'complex_double', '24': 'complex_long_double',
+                          '32': 'complex_long_double'},
+              'complexkind': {'': 'complex_float', '4': 'complex_float',
+                              '8': 'complex_double', '12': 'complex_long_double',
+                              '16': 'complex_long_double'},
+              'logical': {'': 'int', '1': 'char', '2': 'short', '4': 'int',
+                          '8': 'long_long'},
+              'double complex': {'': 'complex_double'},
+              'double precision': {'': 'double'},
+              'byte': {'': 'char'},
+              }
+
+# Add ISO_C handling
+c2pycode_map.update(isoc_c2pycode_map)
+c2py_map.update(iso_c2py_map)
+f2cmap_all, _ = process_f2cmap_dict(f2cmap_all, iso_c_binding_map, c2py_map)
+# End ISO_C handling
+f2cmap_default = copy.deepcopy(f2cmap_all)
+
+f2cmap_mapped = []
+
+def load_f2cmap_file(f2cmap_file):
+    global f2cmap_all, f2cmap_mapped
+
+    f2cmap_all = copy.deepcopy(f2cmap_default)
+
+    if f2cmap_file is None:
+        # Default value
+        f2cmap_file = '.f2py_f2cmap'
+        if not os.path.isfile(f2cmap_file):
+            return
+
+    # User defined additions to f2cmap_all.
+    # f2cmap_file must contain a dictionary of dictionaries, only. For
+    # example, {'real':{'low':'float'}} means that Fortran 'real(low)' is
+    # interpreted as C 'float'. This feature is useful for F90/95 users if
+    # they use PARAMETERS in type specifications.
+    try:
+        outmess(f'Reading f2cmap from {f2cmap_file!r} ...\n')
+        with open(f2cmap_file) as f:
+            d = eval(f.read().lower(), {}, {})
+        f2cmap_all, f2cmap_mapped = process_f2cmap_dict(f2cmap_all, d, c2py_map, True)
+        outmess('Successfully applied user defined f2cmap changes\n')
+    except Exception as msg:
+        errmess(f'Failed to apply user defined f2cmap changes: {msg}. Skipping.\n')
+
+
+cformat_map = {'double': '%g',
+               'float': '%g',
+               'long_double': '%Lg',
+               'char': '%d',
+               'signed_char': '%d',
+               'unsigned_char': '%hhu',
+               'short': '%hd',
+               'unsigned_short': '%hu',
+               'int': '%d',
+               'unsigned': '%u',
+               'long': '%ld',
+               'unsigned_long': '%lu',
+               'long_long': '%ld',
+               'complex_float': '(%g,%g)',
+               'complex_double': '(%g,%g)',
+               'complex_long_double': '(%Lg,%Lg)',
+               'string': '\\"%s\\"',
+               'character': "'%c'",
+               }
+
+# Auxiliary functions
+
+
+def getctype(var):
+    """
+    Determines C type
+    """
+    ctype = 'void'
+    if isfunction(var):
+        if 'result' in var:
+            a = var['result']
+        else:
+            a = var['name']
+        if a in var['vars']:
+            return getctype(var['vars'][a])
+        else:
+            errmess(f'getctype: function {a} has no return value?!\n')
+    elif issubroutine(var):
+        return ctype
+    elif ischaracter_or_characterarray(var):
+        return 'character'
+    elif isstring_or_stringarray(var):
+        return 'string'
+    elif 'typespec' in var and var['typespec'].lower() in f2cmap_all:
+        typespec = var['typespec'].lower()
+        f2cmap = f2cmap_all[typespec]
+        ctype = f2cmap['']  # default type
+        if 'kindselector' in var:
+            if '*' in var['kindselector']:
+                try:
+                    ctype = f2cmap[var['kindselector']['*']]
+                except KeyError:
+                    errmess('getctype: "%s %s %s" not supported.\n' %
+                            (var['typespec'], '*', var['kindselector']['*']))
+            elif 'kind' in var['kindselector']:
+                if typespec + 'kind' in f2cmap_all:
+                    f2cmap = f2cmap_all[typespec + 'kind']
+                try:
+                    ctype = f2cmap[var['kindselector']['kind']]
+                except KeyError:
+                    if typespec in f2cmap_all:
+                        f2cmap = f2cmap_all[typespec]
+                    try:
+                        ctype = f2cmap[str(var['kindselector']['kind'])]
+                    except KeyError:
+                        errmess('getctype: "%s(kind=%s)" is mapped to C "%s" (to override define dict(%s = dict(%s="<C typespec>")) in %s/.f2py_f2cmap file).\n'
+                                % (typespec, var['kindselector']['kind'], ctype,
+                                   typespec, var['kindselector']['kind'], os.getcwd()))
+    elif not isexternal(var):
+        errmess(f'getctype: No C-type found in "{var}", assuming void.\n')
+    return ctype
+
+
+def f2cexpr(expr):
+    """Rewrite Fortran expression as f2py supported C expression.
+
+    Due to the lack of a proper expression parser in f2py, this
+    function uses a heuristic approach that assumes that Fortran
+    arithmetic expressions are valid C arithmetic expressions when
+    mapping Fortran function calls to the corresponding C function/CPP
+    macros calls.
+
+    """
+    # TODO: support Fortran `len` function with optional kind parameter
+    expr = re.sub(r'\blen\b', 'f2py_slen', expr)
+    return expr
+
+
+def getstrlength(var):
+    if isstringfunction(var):
+        if 'result' in var:
+            a = var['result']
+        else:
+            a = var['name']
+        if a in var['vars']:
+            return getstrlength(var['vars'][a])
+        else:
+            errmess(f'getstrlength: function {a} has no return value?!\n')
+    if not isstring(var):
+        errmess(
+            f'getstrlength: expected a signature of a string but got: {repr(var)}\n')
+    len = '1'
+    if 'charselector' in var:
+        a = var['charselector']
+        if '*' in a:
+            len = a['*']
+        elif 'len' in a:
+            len = f2cexpr(a['len'])
+    if re.match(r'\(\s*(\*|:)\s*\)', len) or re.match(r'(\*|:)', len):
+        if isintent_hide(var):
+            errmess('getstrlength:intent(hide): expected a string with defined length but got: %s\n' % (
+                repr(var)))
+        len = '-1'
+    return len
+
+
+def getarrdims(a, var, verbose=0):
+    ret = {}
+    if isstring(var) and not isarray(var):
+        ret['size'] = getstrlength(var)
+        ret['rank'] = '0'
+        ret['dims'] = ''
+    elif isscalar(var):
+        ret['size'] = '1'
+        ret['rank'] = '0'
+        ret['dims'] = ''
+    elif isarray(var):
+        dim = copy.copy(var['dimension'])
+        ret['size'] = '*'.join(dim)
+        try:
+            ret['size'] = repr(eval(ret['size']))
+        except Exception:
+            pass
+        ret['dims'] = ','.join(dim)
+        ret['rank'] = repr(len(dim))
+        ret['rank*[-1]'] = repr(len(dim) * [-1])[1:-1]
+        for i in range(len(dim)):  # solve dim for dependencies
+            v = []
+            if dim[i] in depargs:
+                v = [dim[i]]
+            else:
+                for va in depargs:
+                    if re.match(r'.*?\b%s\b.*' % va, dim[i]):
+                        v.append(va)
+            for va in v:
+                if depargs.index(va) > depargs.index(a):
+                    dim[i] = '*'
+                    break
+        ret['setdims'], i = '', -1
+        for d in dim:
+            i = i + 1
+            if d not in ['*', ':', '(*)', '(:)']:
+                ret['setdims'] = '%s#varname#_Dims[%d]=%s,' % (
+                    ret['setdims'], i, d)
+        if ret['setdims']:
+            ret['setdims'] = ret['setdims'][:-1]
+        ret['cbsetdims'], i = '', -1
+        for d in var['dimension']:
+            i = i + 1
+            if d not in ['*', ':', '(*)', '(:)']:
+                ret['cbsetdims'] = '%s#varname#_Dims[%d]=%s,' % (
+                    ret['cbsetdims'], i, d)
+            elif isintent_in(var):
+                outmess('getarrdims:warning: assumed shape array, using 0 instead of %r\n'
+                        % (d))
+                ret['cbsetdims'] = '%s#varname#_Dims[%d]=%s,' % (
+                    ret['cbsetdims'], i, 0)
+            elif verbose:
+                errmess(
+                    f'getarrdims: If in call-back function: array argument {repr(a)} must have bounded dimensions: got {repr(d)}\n')
+        if ret['cbsetdims']:
+            ret['cbsetdims'] = ret['cbsetdims'][:-1]
+#         if not isintent_c(var):
+#             var['dimension'].reverse()
+    return ret
+
+
+def getpydocsign(a, var):
+    global lcb_map
+    if isfunction(var):
+        if 'result' in var:
+            af = var['result']
+        else:
+            af = var['name']
+        if af in var['vars']:
+            return getpydocsign(af, var['vars'][af])
+        else:
+            errmess(f'getctype: function {af} has no return value?!\n')
+        return '', ''
+    sig, sigout = a, a
+    opt = ''
+    if isintent_in(var):
+        opt = 'input'
+    elif isintent_inout(var):
+        opt = 'in/output'
+    out_a = a
+    if isintent_out(var):
+        for k in var['intent']:
+            if k[:4] == 'out=':
+                out_a = k[4:]
+                break
+    init = ''
+    ctype = getctype(var)
+
+    if hasinitvalue(var):
+        init, showinit = getinit(a, var)
+        init = f', optional\\n    Default: {showinit}'
+    if isscalar(var):
+        if isintent_inout(var):
+            sig = '%s : %s rank-0 array(%s,\'%s\')%s' % (a, opt, c2py_map[ctype],
+                                                         c2pycode_map[ctype], init)
+        else:
+            sig = f'{a} : {opt} {c2py_map[ctype]}{init}'
+        sigout = f'{out_a} : {c2py_map[ctype]}'
+    elif isstring(var):
+        if isintent_inout(var):
+            sig = '%s : %s rank-0 array(string(len=%s),\'c\')%s' % (
+                a, opt, getstrlength(var), init)
+        else:
+            sig = f'{a} : {opt} string(len={getstrlength(var)}){init}'
+        sigout = f'{out_a} : string(len={getstrlength(var)})'
+    elif isarray(var):
+        dim = var['dimension']
+        rank = repr(len(dim))
+        sig = '%s : %s rank-%s array(\'%s\') with bounds (%s)%s' % (a, opt, rank,
+                                                                    c2pycode_map[
+                                                                        ctype],
+                                                                    ','.join(dim), init)
+        if a == out_a:
+            sigout = '%s : rank-%s array(\'%s\') with bounds (%s)'\
+                % (a, rank, c2pycode_map[ctype], ','.join(dim))
+        else:
+            sigout = '%s : rank-%s array(\'%s\') with bounds (%s) and %s storage'\
+                % (out_a, rank, c2pycode_map[ctype], ','.join(dim), a)
+    elif isexternal(var):
+        ua = ''
+        if a in lcb_map and lcb_map[a] in lcb2_map and 'argname' in lcb2_map[lcb_map[a]]:
+            ua = lcb2_map[lcb_map[a]]['argname']
+            if not ua == a:
+                ua = f' => {ua}'
+            else:
+                ua = ''
+        sig = f'{a} : call-back function{ua}'
+        sigout = sig
+    else:
+        errmess(
+            f'getpydocsign: Could not resolve docsignature for "{a}".\n')
+    return sig, sigout
+
+
+def getarrdocsign(a, var):
+    ctype = getctype(var)
+    if isstring(var) and (not isarray(var)):
+        sig = f'{a} : rank-0 array(string(len={getstrlength(var)}),\'c\')'
+    elif isscalar(var):
+        sig = f'{a} : rank-0 array({c2py_map[ctype]},\'{c2pycode_map[ctype]}\')'
+    elif isarray(var):
+        dim = var['dimension']
+        rank = repr(len(dim))
+        sig = '%s : rank-%s array(\'%s\') with bounds (%s)' % (a, rank,
+                                                               c2pycode_map[
+                                                                   ctype],
+                                                               ','.join(dim))
+    return sig
+
+
+def getinit(a, var):
+    if isstring(var):
+        init, showinit = '""', "''"
+    else:
+        init, showinit = '', ''
+    if hasinitvalue(var):
+        init = var['=']
+        showinit = init
+        if iscomplex(var) or iscomplexarray(var):
+            ret = {}
+
+            try:
+                v = var["="]
+                if ',' in v:
+                    ret['init.r'], ret['init.i'] = markoutercomma(
+                        v[1:-1]).split('@,@')
+                else:
+                    v = eval(v, {}, {})
+                    ret['init.r'], ret['init.i'] = str(v.real), str(v.imag)
+            except Exception:
+                raise ValueError(
+                    f'getinit: expected complex number `(r,i)\' but got `{init}\' as initial value of {a!r}.')
+            if isarray(var):
+                init = f"(capi_c.r={ret['init.r']},capi_c.i={ret['init.i']},capi_c)"
+        elif isstring(var):
+            if not init:
+                init, showinit = '""', "''"
+            if init[0] == "'":
+                init = '"%s"' % (init[1:-1].replace('"', '\\"'))
+            if init[0] == '"':
+                showinit = f"'{init[1:-1]}'"
+    return init, showinit
+
+
+def get_elsize(var):
+    if isstring(var) or isstringarray(var):
+        elsize = getstrlength(var)
+        # override with user-specified length when available:
+        elsize = var['charselector'].get('f2py_len', elsize)
+        return elsize
+    if ischaracter(var) or ischaracterarray(var):
+        return '1'
+    # for numerical types, PyArray_New* functions ignore specified
+    # elsize, so we just return 1 and let elsize be determined at
+    # runtime, see fortranobject.c
+    return '1'
+
+
+def sign2map(a, var):
+    """
+    varname,ctype,atype
+    init,init.r,init.i,pytype
+    vardebuginfo,vardebugshowvalue,varshowvalue
+    varrformat
+
+    intent
+    """
+    out_a = a
+    if isintent_out(var):
+        for k in var['intent']:
+            if k[:4] == 'out=':
+                out_a = k[4:]
+                break
+    ret = {'varname': a, 'outvarname': out_a, 'ctype': getctype(var)}
+    intent_flags = []
+    for f, s in isintent_dict.items():
+        if f(var):
+            intent_flags.append(f'F2PY_{s}')
+    if intent_flags:
+        # TODO: Evaluate intent_flags here.
+        ret['intent'] = '|'.join(intent_flags)
+    else:
+        ret['intent'] = 'F2PY_INTENT_IN'
+    if isarray(var):
+        ret['varrformat'] = 'N'
+    elif ret['ctype'] in c2buildvalue_map:
+        ret['varrformat'] = c2buildvalue_map[ret['ctype']]
+    else:
+        ret['varrformat'] = 'O'
+    ret['init'], ret['showinit'] = getinit(a, var)
+    if hasinitvalue(var) and iscomplex(var) and not isarray(var):
+        ret['init.r'], ret['init.i'] = markoutercomma(
+            ret['init'][1:-1]).split('@,@')
+    if isexternal(var):
+        ret['cbnamekey'] = a
+        if a in lcb_map:
+            ret['cbname'] = lcb_map[a]
+            ret['maxnofargs'] = lcb2_map[lcb_map[a]]['maxnofargs']
+            ret['nofoptargs'] = lcb2_map[lcb_map[a]]['nofoptargs']
+            ret['cbdocstr'] = lcb2_map[lcb_map[a]]['docstr']
+            ret['cblatexdocstr'] = lcb2_map[lcb_map[a]]['latexdocstr']
+        else:
+            ret['cbname'] = a
+            errmess('sign2map: Confused: external %s is not in lcb_map%s.\n' % (
+                a, list(lcb_map.keys())))
+    if isstring(var):
+        ret['length'] = getstrlength(var)
+    if isarray(var):
+        ret = dictappend(ret, getarrdims(a, var))
+        dim = copy.copy(var['dimension'])
+    if ret['ctype'] in c2capi_map:
+        ret['atype'] = c2capi_map[ret['ctype']]
+        ret['elsize'] = get_elsize(var)
+    # Debug info
+    if debugcapi(var):
+        il = [isintent_in, 'input', isintent_out, 'output',
+              isintent_inout, 'inoutput', isrequired, 'required',
+              isoptional, 'optional', isintent_hide, 'hidden',
+              iscomplex, 'complex scalar',
+              l_and(isscalar, l_not(iscomplex)), 'scalar',
+              isstring, 'string', isarray, 'array',
+              iscomplexarray, 'complex array', isstringarray, 'string array',
+              iscomplexfunction, 'complex function',
+              l_and(isfunction, l_not(iscomplexfunction)), 'function',
+              isexternal, 'callback',
+              isintent_callback, 'callback',
+              isintent_aux, 'auxiliary',
+              ]
+        rl = []
+        for i in range(0, len(il), 2):
+            if il[i](var):
+                rl.append(il[i + 1])
+        if isstring(var):
+            rl.append(f"slen({a})={ret['length']}")
+        if isarray(var):
+            ddim = ','.join(
+                map(lambda x, y: f'{x}|{y}', var['dimension'], dim))
+            rl.append(f'dims({ddim})')
+        if isexternal(var):
+            ret['vardebuginfo'] = f"debug-capi:{a}=>{ret['cbname']}:{','.join(rl)}"
+        else:
+            ret['vardebuginfo'] = 'debug-capi:%s %s=%s:%s' % (
+                ret['ctype'], a, ret['showinit'], ','.join(rl))
+        if isscalar(var):
+            if ret['ctype'] in cformat_map:
+                ret['vardebugshowvalue'] = f"debug-capi:{a}={cformat_map[ret['ctype']]}"
+        if isstring(var):
+            ret['vardebugshowvalue'] = 'debug-capi:slen(%s)=%%d %s=\\"%%s\\"' % (
+                a, a)
+        if isexternal(var):
+            ret['vardebugshowvalue'] = f'debug-capi:{a}=%p'
+    if ret['ctype'] in cformat_map:
+        ret['varshowvalue'] = f"#name#:{a}={cformat_map[ret['ctype']]}"
+        ret['showvalueformat'] = f"{cformat_map[ret['ctype']]}"
+    if isstring(var):
+        ret['varshowvalue'] = '#name#:slen(%s)=%%d %s=\\"%%s\\"' % (a, a)
+    ret['pydocsign'], ret['pydocsignout'] = getpydocsign(a, var)
+    if hasnote(var):
+        ret['note'] = var['note']
+    return ret
+
+
+def routsign2map(rout):
+    """
+    name,NAME,begintitle,endtitle
+    rname,ctype,rformat
+    routdebugshowvalue
+    """
+    global lcb_map
+    name = rout['name']
+    fname = getfortranname(rout)
+    ret = {'name': name,
+           'texname': name.replace('_', '\\_'),
+           'name_lower': name.lower(),
+           'NAME': name.upper(),
+           'begintitle': gentitle(name),
+           'endtitle': gentitle(f'end of {name}'),
+           'fortranname': fname,
+           'FORTRANNAME': fname.upper(),
+           'callstatement': getcallstatement(rout) or '',
+           'usercode': getusercode(rout) or '',
+           'usercode1': getusercode1(rout) or '',
+           }
+    if '_' in fname:
+        ret['F_FUNC'] = 'F_FUNC_US'
+    else:
+        ret['F_FUNC'] = 'F_FUNC'
+    if '_' in name:
+        ret['F_WRAPPEDFUNC'] = 'F_WRAPPEDFUNC_US'
+    else:
+        ret['F_WRAPPEDFUNC'] = 'F_WRAPPEDFUNC'
+    lcb_map = {}
+    if 'use' in rout:
+        for u in rout['use'].keys():
+            if u in cb_rules.cb_map:
+                for un in cb_rules.cb_map[u]:
+                    ln = un[0]
+                    if 'map' in rout['use'][u]:
+                        for k in rout['use'][u]['map'].keys():
+                            if rout['use'][u]['map'][k] == un[0]:
+                                ln = k
+                                break
+                    lcb_map[ln] = un[1]
+    elif rout.get('externals'):
+        errmess('routsign2map: Confused: function %s has externals %s but no "use" statement.\n' % (
+            ret['name'], repr(rout['externals'])))
+    ret['callprotoargument'] = getcallprotoargument(rout, lcb_map) or ''
+    if isfunction(rout):
+        if 'result' in rout:
+            a = rout['result']
+        else:
+            a = rout['name']
+        ret['rname'] = a
+        ret['pydocsign'], ret['pydocsignout'] = getpydocsign(a, rout)
+        ret['ctype'] = getctype(rout['vars'][a])
+        if hasresultnote(rout):
+            ret['resultnote'] = rout['vars'][a]['note']
+            rout['vars'][a]['note'] = ['See elsewhere.']
+        if ret['ctype'] in c2buildvalue_map:
+            ret['rformat'] = c2buildvalue_map[ret['ctype']]
+        else:
+            ret['rformat'] = 'O'
+            errmess('routsign2map: no c2buildvalue key for type %s\n' %
+                    (repr(ret['ctype'])))
+        if debugcapi(rout):
+            if ret['ctype'] in cformat_map:
+                ret['routdebugshowvalue'] = 'debug-capi:%s=%s' % (
+                    a, cformat_map[ret['ctype']])
+            if isstringfunction(rout):
+                ret['routdebugshowvalue'] = 'debug-capi:slen(%s)=%%d %s=\\"%%s\\"' % (
+                    a, a)
+        if isstringfunction(rout):
+            ret['rlength'] = getstrlength(rout['vars'][a])
+            if ret['rlength'] == '-1':
+                errmess('routsign2map: expected explicit specification of the length of the string returned by the fortran function %s; taking 10.\n' % (
+                    repr(rout['name'])))
+                ret['rlength'] = '10'
+    if hasnote(rout):
+        ret['note'] = rout['note']
+        rout['note'] = ['See elsewhere.']
+    return ret
+
+
+def modsign2map(m):
+    """
+    modulename
+    """
+    if ismodule(m):
+        ret = {'f90modulename': m['name'],
+               'F90MODULENAME': m['name'].upper(),
+               'texf90modulename': m['name'].replace('_', '\\_')}
+    else:
+        ret = {'modulename': m['name'],
+               'MODULENAME': m['name'].upper(),
+               'texmodulename': m['name'].replace('_', '\\_')}
+    ret['restdoc'] = getrestdoc(m) or []
+    if hasnote(m):
+        ret['note'] = m['note']
+    ret['usercode'] = getusercode(m) or ''
+    ret['usercode1'] = getusercode1(m) or ''
+    if m['body']:
+        ret['interface_usercode'] = getusercode(m['body'][0]) or ''
+    else:
+        ret['interface_usercode'] = ''
+    ret['pymethoddef'] = getpymethoddef(m) or ''
+    if 'gil_used' in m:
+        ret['gil_used'] = m['gil_used']
+    if 'coutput' in m:
+        ret['coutput'] = m['coutput']
+    if 'f2py_wrapper_output' in m:
+        ret['f2py_wrapper_output'] = m['f2py_wrapper_output']
+    return ret
+
+
+def cb_sign2map(a, var, index=None):
+    ret = {'varname': a}
+    ret['varname_i'] = ret['varname']
+    ret['ctype'] = getctype(var)
+    if ret['ctype'] in c2capi_map:
+        ret['atype'] = c2capi_map[ret['ctype']]
+        ret['elsize'] = get_elsize(var)
+    if ret['ctype'] in cformat_map:
+        ret['showvalueformat'] = f"{cformat_map[ret['ctype']]}"
+    if isarray(var):
+        ret = dictappend(ret, getarrdims(a, var))
+    ret['pydocsign'], ret['pydocsignout'] = getpydocsign(a, var)
+    if hasnote(var):
+        ret['note'] = var['note']
+        var['note'] = ['See elsewhere.']
+    return ret
+
+
+def cb_routsign2map(rout, um):
+    """
+    name,begintitle,endtitle,argname
+    ctype,rctype,maxnofargs,nofoptargs,returncptr
+    """
+    ret = {'name': f"cb_{rout['name']}_in_{um}",
+           'returncptr': ''}
+    if isintent_callback(rout):
+        if '_' in rout['name']:
+            F_FUNC = 'F_FUNC_US'
+        else:
+            F_FUNC = 'F_FUNC'
+        ret['callbackname'] = f"{F_FUNC}({rout['name'].lower()},{rout['name'].upper()})"
+        ret['static'] = 'extern'
+    else:
+        ret['callbackname'] = ret['name']
+        ret['static'] = 'static'
+    ret['argname'] = rout['name']
+    ret['begintitle'] = gentitle(ret['name'])
+    ret['endtitle'] = gentitle(f"end of {ret['name']}")
+    ret['ctype'] = getctype(rout)
+    ret['rctype'] = 'void'
+    if ret['ctype'] == 'string':
+        ret['rctype'] = 'void'
+    else:
+        ret['rctype'] = ret['ctype']
+    if ret['rctype'] != 'void':
+        if iscomplexfunction(rout):
+            ret['returncptr'] = """
+#ifdef F2PY_CB_RETURNCOMPLEX
+return_value=
+#endif
+"""
+        else:
+            ret['returncptr'] = 'return_value='
+    if ret['ctype'] in cformat_map:
+        ret['showvalueformat'] = f"{cformat_map[ret['ctype']]}"
+    if isstringfunction(rout):
+        ret['strlength'] = getstrlength(rout)
+    if isfunction(rout):
+        if 'result' in rout:
+            a = rout['result']
+        else:
+            a = rout['name']
+        if hasnote(rout['vars'][a]):
+            ret['note'] = rout['vars'][a]['note']
+            rout['vars'][a]['note'] = ['See elsewhere.']
+        ret['rname'] = a
+        ret['pydocsign'], ret['pydocsignout'] = getpydocsign(a, rout)
+        if iscomplexfunction(rout):
+            ret['rctype'] = """
+#ifdef F2PY_CB_RETURNCOMPLEX
+#ctype#
+#else
+void
+#endif
+"""
+    elif hasnote(rout):
+        ret['note'] = rout['note']
+        rout['note'] = ['See elsewhere.']
+    nofargs = 0
+    nofoptargs = 0
+    if 'args' in rout and 'vars' in rout:
+        for a in rout['args']:
+            var = rout['vars'][a]
+            if l_or(isintent_in, isintent_inout)(var):
+                nofargs = nofargs + 1
+                if isoptional(var):
+                    nofoptargs = nofoptargs + 1
+    ret['maxnofargs'] = repr(nofargs)
+    ret['nofoptargs'] = repr(nofoptargs)
+    if hasnote(rout) and isfunction(rout) and 'result' in rout:
+        ret['routnote'] = rout['note']
+        rout['note'] = ['See elsewhere.']
+    return ret
+
+
+def common_sign2map(a, var):  # obsolete
+    ret = {'varname': a, 'ctype': getctype(var)}
+    if isstringarray(var):
+        ret['ctype'] = 'char'
+    if ret['ctype'] in c2capi_map:
+        ret['atype'] = c2capi_map[ret['ctype']]
+        ret['elsize'] = get_elsize(var)
+    if ret['ctype'] in cformat_map:
+        ret['showvalueformat'] = f"{cformat_map[ret['ctype']]}"
+    if isarray(var):
+        ret = dictappend(ret, getarrdims(a, var))
+    elif isstring(var):
+        ret['size'] = getstrlength(var)
+        ret['rank'] = '1'
+    ret['pydocsign'], ret['pydocsignout'] = getpydocsign(a, var)
+    if hasnote(var):
+        ret['note'] = var['note']
+        var['note'] = ['See elsewhere.']
+    # for strings this returns 0-rank but actually is 1-rank
+    ret['arrdocstr'] = getarrdocsign(a, var)
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..b01d64c861fa7d4c564dddae37da38838faf6576
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/capi_maps.pyi
@@ -0,0 +1,33 @@
+from .auxfuncs import _ROut, _Var, process_f2cmap_dict
+
+__all__ = [
+    "cb_routsign2map",
+    "cb_sign2map",
+    "common_sign2map",
+    "getarrdims",
+    "getarrdocsign",
+    "getctype",
+    "getinit",
+    "getpydocsign",
+    "getstrlength",
+    "modsign2map",
+    "process_f2cmap_dict",
+    "routsign2map",
+    "sign2map",
+]
+
+###
+
+def getctype(var: _Var) -> str: ...
+def f2cexpr(expr: str) -> str: ...
+def getstrlength(var: _Var) -> str: ...
+def getarrdims(a: str, var: _Var, verbose: int = 0) -> dict[str, str]: ...
+def getpydocsign(a: str, var: _Var) -> tuple[str, str]: ...
+def getarrdocsign(a: str, var: _Var) -> str: ...
+def getinit(a: str, var: _Var) -> tuple[str, str]: ...
+def sign2map(a: str, var: _Var) -> dict[str, str]: ...
+def routsign2map(rout: _ROut) -> dict[str, str]: ...
+def modsign2map(m: _ROut) -> dict[str, str]: ...
+def cb_sign2map(a: str, var: _Var, index: object | None = None) -> dict[str, str]: ...
+def cb_routsign2map(rout: _ROut, um: str) -> dict[str, str]: ...
+def common_sign2map(a: str, var: _Var) -> dict[str, str]: ...  # obsolete
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.py b/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.py
new file mode 100644
index 0000000000000000000000000000000000000000..9803e68ea16ca21d818c1d13ae4bb1e5bdbbcedd
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.py
@@ -0,0 +1,665 @@
+"""
+Build call-back mechanism for f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+from . import __version__, cfuncs
+from .auxfuncs import (
+    applyrules,
+    debugcapi,
+    dictappend,
+    errmess,
+    getargs,
+    hasnote,
+    isarray,
+    iscomplex,
+    iscomplexarray,
+    iscomplexfunction,
+    isfunction,
+    isintent_c,
+    isintent_hide,
+    isintent_in,
+    isintent_inout,
+    isintent_nothide,
+    isintent_out,
+    isoptional,
+    isrequired,
+    isscalar,
+    isstring,
+    isstringfunction,
+    issubroutine,
+    l_and,
+    l_not,
+    l_or,
+    outmess,
+    replace,
+    stripcomma,
+    throw_error,
+)
+
+f2py_version = __version__.version
+
+
+################## Rules for callback function ##############
+
+cb_routine_rules = {
+    'cbtypedefs': 'typedef #rctype#(*#name#_typedef)(#optargs_td##args_td##strarglens_td##noargs#);',
+    'body': """
+#begintitle#
+typedef struct {
+    PyObject *capi;
+    PyTupleObject *args_capi;
+    int nofargs;
+    jmp_buf jmpbuf;
+} #name#_t;
+
+#if defined(F2PY_THREAD_LOCAL_DECL) && !defined(F2PY_USE_PYTHON_TLS)
+
+static F2PY_THREAD_LOCAL_DECL #name#_t *_active_#name# = NULL;
+
+static #name#_t *swap_active_#name#(#name#_t *ptr) {
+    #name#_t *prev = _active_#name#;
+    _active_#name# = ptr;
+    return prev;
+}
+
+static #name#_t *get_active_#name#(void) {
+    return _active_#name#;
+}
+
+#else
+
+static #name#_t *swap_active_#name#(#name#_t *ptr) {
+    char *key = "__f2py_cb_#name#";
+    return (#name#_t *)F2PySwapThreadLocalCallbackPtr(key, ptr);
+}
+
+static #name#_t *get_active_#name#(void) {
+    char *key = "__f2py_cb_#name#";
+    return (#name#_t *)F2PyGetThreadLocalCallbackPtr(key);
+}
+
+#endif
+
+/*typedef #rctype#(*#name#_typedef)(#optargs_td##args_td##strarglens_td##noargs#);*/
+#static# #rctype# #callbackname# (#optargs##args##strarglens##noargs#) {
+    #name#_t cb_local = { NULL, NULL, 0 };
+    #name#_t *cb = NULL;
+    PyTupleObject *capi_arglist = NULL;
+    PyObject *capi_return = NULL;
+    PyObject *capi_tmp = NULL;
+    PyObject *capi_arglist_list = NULL;
+    int capi_j,capi_i = 0;
+    int capi_longjmp_ok = 1;
+#decl#
+#ifdef F2PY_REPORT_ATEXIT
+f2py_cb_start_clock();
+#endif
+    cb = get_active_#name#();
+    if (cb == NULL) {
+        capi_longjmp_ok = 0;
+        cb = &cb_local;
+    }
+    capi_arglist = cb->args_capi;
+    CFUNCSMESS(\"cb:Call-back function #name# (maxnofargs=#maxnofargs#(-#nofoptargs#))\\n\");
+    CFUNCSMESSPY(\"cb:#name#_capi=\",cb->capi);
+    if (cb->capi==NULL) {
+        capi_longjmp_ok = 0;
+        cb->capi = PyObject_GetAttrString(#modulename#_module,\"#argname#\");
+        CFUNCSMESSPY(\"cb:#name#_capi=\",cb->capi);
+    }
+    if (cb->capi==NULL) {
+        PyErr_SetString(#modulename#_error,\"cb: Callback #argname# not defined (as an argument or module #modulename# attribute).\\n\");
+        goto capi_fail;
+    }
+    if (F2PyCapsule_Check(cb->capi)) {
+    #name#_typedef #name#_cptr;
+    #name#_cptr = F2PyCapsule_AsVoidPtr(cb->capi);
+    #returncptr#(*#name#_cptr)(#optargs_nm##args_nm##strarglens_nm#);
+    #return#
+    }
+    if (capi_arglist==NULL) {
+        capi_longjmp_ok = 0;
+        capi_tmp = PyObject_GetAttrString(#modulename#_module,\"#argname#_extra_args\");
+        if (capi_tmp) {
+            capi_arglist = (PyTupleObject *)PySequence_Tuple(capi_tmp);
+            Py_DECREF(capi_tmp);
+            if (capi_arglist==NULL) {
+                PyErr_SetString(#modulename#_error,\"Failed to convert #modulename#.#argname#_extra_args to tuple.\\n\");
+                goto capi_fail;
+            }
+        } else {
+            PyErr_Clear();
+            capi_arglist = (PyTupleObject *)Py_BuildValue(\"()\");
+        }
+    }
+    if (capi_arglist == NULL) {
+        PyErr_SetString(#modulename#_error,\"Callback #argname# argument list is not set.\\n\");
+        goto capi_fail;
+    }
+#setdims#
+#ifdef PYPY_VERSION
+#define CAPI_ARGLIST_SETITEM(idx, value) PyList_SetItem((PyObject *)capi_arglist_list, idx, value)
+    capi_arglist_list = PySequence_List((PyObject *)capi_arglist);
+    if (capi_arglist_list == NULL) goto capi_fail;
+#else
+#define CAPI_ARGLIST_SETITEM(idx, value) PyTuple_SetItem((PyObject *)capi_arglist, idx, value)
+#endif
+#pyobjfrom#
+#undef CAPI_ARGLIST_SETITEM
+#ifdef PYPY_VERSION
+    CFUNCSMESSPY(\"cb:capi_arglist=\",capi_arglist_list);
+#else
+    CFUNCSMESSPY(\"cb:capi_arglist=\",capi_arglist);
+#endif
+    CFUNCSMESS(\"cb:Call-back calling Python function #argname#.\\n\");
+#ifdef F2PY_REPORT_ATEXIT
+f2py_cb_start_call_clock();
+#endif
+#ifdef PYPY_VERSION
+    capi_return = PyObject_CallObject(cb->capi,(PyObject *)capi_arglist_list);
+    Py_DECREF(capi_arglist_list);
+    capi_arglist_list = NULL;
+#else
+    capi_return = PyObject_CallObject(cb->capi,(PyObject *)capi_arglist);
+#endif
+#ifdef F2PY_REPORT_ATEXIT
+f2py_cb_stop_call_clock();
+#endif
+    CFUNCSMESSPY(\"cb:capi_return=\",capi_return);
+    if (capi_return == NULL) {
+        fprintf(stderr,\"capi_return is NULL\\n\");
+        goto capi_fail;
+    }
+    if (capi_return == Py_None) {
+        Py_DECREF(capi_return);
+        capi_return = Py_BuildValue(\"()\");
+    }
+    else if (!PyTuple_Check(capi_return)) {
+        capi_return = Py_BuildValue(\"(N)\",capi_return);
+    }
+    capi_j = PyTuple_Size(capi_return);
+    capi_i = 0;
+#frompyobj#
+    CFUNCSMESS(\"cb:#name#:successful\\n\");
+    Py_DECREF(capi_return);
+#ifdef F2PY_REPORT_ATEXIT
+f2py_cb_stop_clock();
+#endif
+    goto capi_return_pt;
+capi_fail:
+    fprintf(stderr,\"Call-back #name# failed.\\n\");
+    Py_XDECREF(capi_return);
+    Py_XDECREF(capi_arglist_list);
+    if (capi_longjmp_ok) {
+        longjmp(cb->jmpbuf,-1);
+    }
+capi_return_pt:
+    ;
+#return#
+}
+#endtitle#
+""",
+    'need': ['setjmp.h', 'CFUNCSMESS', 'F2PY_THREAD_LOCAL_DECL'],
+    'maxnofargs': '#maxnofargs#',
+    'nofoptargs': '#nofoptargs#',
+    'docstr': """\
+    def #argname#(#docsignature#): return #docreturn#\\n\\
+#docstrsigns#""",
+    'latexdocstr': """
+{{}\\verb@def #argname#(#latexdocsignature#): return #docreturn#@{}}
+#routnote#
+
+#latexdocstrsigns#""",
+    'docstrshort': 'def #argname#(#docsignature#): return #docreturn#'
+}
+cb_rout_rules = [
+    {  # Init
+        'separatorsfor': {'decl': '\n',
+                          'args': ',', 'optargs': '', 'pyobjfrom': '\n', 'freemem': '\n',
+                          'args_td': ',', 'optargs_td': '',
+                          'args_nm': ',', 'optargs_nm': '',
+                          'frompyobj': '\n', 'setdims': '\n',
+                          'docstrsigns': '\\n"\n"',
+                          'latexdocstrsigns': '\n',
+                          'latexdocstrreq': '\n', 'latexdocstropt': '\n',
+                          'latexdocstrout': '\n', 'latexdocstrcbs': '\n',
+                          },
+        'decl': '/*decl*/', 'pyobjfrom': '/*pyobjfrom*/', 'frompyobj': '/*frompyobj*/',
+        'args': [], 'optargs': '', 'return': '', 'strarglens': '', 'freemem': '/*freemem*/',
+        'args_td': [], 'optargs_td': '', 'strarglens_td': '',
+        'args_nm': [], 'optargs_nm': '', 'strarglens_nm': '',
+        'noargs': '',
+        'setdims': '/*setdims*/',
+        'docstrsigns': '', 'latexdocstrsigns': '',
+        'docstrreq': '    Required arguments:',
+        'docstropt': '    Optional arguments:',
+        'docstrout': '    Return objects:',
+        'docstrcbs': '    Call-back functions:',
+        'docreturn': '', 'docsign': '', 'docsignopt': '',
+        'latexdocstrreq': '\\noindent Required arguments:',
+        'latexdocstropt': '\\noindent Optional arguments:',
+        'latexdocstrout': '\\noindent Return objects:',
+        'latexdocstrcbs': '\\noindent Call-back functions:',
+        'routnote': {hasnote: '--- #note#', l_not(hasnote): ''},
+    }, {  # Function
+        'decl': '    #ctype# return_value = 0;',
+        'frompyobj': [
+            {debugcapi: '    CFUNCSMESS("cb:Getting return_value->");'},
+            '''\
+    if (capi_j>capi_i) {
+        GETSCALARFROMPYTUPLE(capi_return,capi_i++,&return_value,#ctype#,
+          "#ctype#_from_pyobj failed in converting return_value of"
+          " call-back function #name# to C #ctype#\\n");
+    } else {
+        fprintf(stderr,"Warning: call-back function #name# did not provide"
+                       " return value (index=%d, type=#ctype#)\\n",capi_i);
+    }''',
+            {debugcapi:
+             '    fprintf(stderr,"#showvalueformat#.\\n",return_value);'}
+        ],
+        'need': ['#ctype#_from_pyobj', {debugcapi: 'CFUNCSMESS'}, 'GETSCALARFROMPYTUPLE'],
+        'return': '    return return_value;',
+        '_check': l_and(isfunction, l_not(isstringfunction), l_not(iscomplexfunction))
+    },
+    {  # String function
+        'pyobjfrom': {debugcapi: '    fprintf(stderr,"debug-capi:cb:#name#:%d:\\n",return_value_len);'},
+        'args': '#ctype# return_value,int return_value_len',
+        'args_nm': 'return_value,&return_value_len',
+        'args_td': '#ctype# ,int',
+        'frompyobj': [
+            {debugcapi: '    CFUNCSMESS("cb:Getting return_value->\\"");'},
+            """\
+    if (capi_j>capi_i) {
+        GETSTRFROMPYTUPLE(capi_return,capi_i++,return_value,return_value_len);
+    } else {
+        fprintf(stderr,"Warning: call-back function #name# did not provide"
+                       " return value (index=%d, type=#ctype#)\\n",capi_i);
+    }""",
+            {debugcapi:
+             '    fprintf(stderr,"#showvalueformat#\\".\\n",return_value);'}
+        ],
+        'need': ['#ctype#_from_pyobj', {debugcapi: 'CFUNCSMESS'},
+                 'string.h', 'GETSTRFROMPYTUPLE'],
+        'return': 'return;',
+        '_check': isstringfunction
+    },
+    {  # Complex function
+        'optargs': """
+#ifndef F2PY_CB_RETURNCOMPLEX
+#ctype# *return_value
+#endif
+""",
+        'optargs_nm': """
+#ifndef F2PY_CB_RETURNCOMPLEX
+return_value
+#endif
+""",
+        'optargs_td': """
+#ifndef F2PY_CB_RETURNCOMPLEX
+#ctype# *
+#endif
+""",
+        'decl': """
+#ifdef F2PY_CB_RETURNCOMPLEX
+    #ctype# return_value = {0, 0};
+#endif
+""",
+        'frompyobj': [
+            {debugcapi: '    CFUNCSMESS("cb:Getting return_value->");'},
+            """\
+    if (capi_j>capi_i) {
+#ifdef F2PY_CB_RETURNCOMPLEX
+        GETSCALARFROMPYTUPLE(capi_return,capi_i++,&return_value,#ctype#,
+          \"#ctype#_from_pyobj failed in converting return_value of call-back\"
+          \" function #name# to C #ctype#\\n\");
+#else
+        GETSCALARFROMPYTUPLE(capi_return,capi_i++,return_value,#ctype#,
+          \"#ctype#_from_pyobj failed in converting return_value of call-back\"
+          \" function #name# to C #ctype#\\n\");
+#endif
+    } else {
+        fprintf(stderr,
+                \"Warning: call-back function #name# did not provide\"
+                \" return value (index=%d, type=#ctype#)\\n\",capi_i);
+    }""",
+            {debugcapi: """\
+#ifdef F2PY_CB_RETURNCOMPLEX
+    fprintf(stderr,\"#showvalueformat#.\\n\",(return_value).r,(return_value).i);
+#else
+    fprintf(stderr,\"#showvalueformat#.\\n\",(*return_value).r,(*return_value).i);
+#endif
+"""}
+        ],
+        'return': """
+#ifdef F2PY_CB_RETURNCOMPLEX
+    return return_value;
+#else
+    return;
+#endif
+""",
+        'need': ['#ctype#_from_pyobj', {debugcapi: 'CFUNCSMESS'},
+                 'string.h', 'GETSCALARFROMPYTUPLE', '#ctype#'],
+        '_check': iscomplexfunction
+    },
+    {'docstrout': '        #pydocsignout#',
+     'latexdocstrout': ['\\item[]{{}\\verb@#pydocsignout#@{}}',
+                        {hasnote: '--- #note#'}],
+     'docreturn': '#rname#,',
+     '_check': isfunction},
+    {'_check': issubroutine, 'return': 'return;'}
+]
+
+cb_arg_rules = [
+    {  # Doc
+        'docstropt': {l_and(isoptional, isintent_nothide): '        #pydocsign#'},
+        'docstrreq': {l_and(isrequired, isintent_nothide): '        #pydocsign#'},
+        'docstrout': {isintent_out: '        #pydocsignout#'},
+        'latexdocstropt': {l_and(isoptional, isintent_nothide): ['\\item[]{{}\\verb@#pydocsign#@{}}',
+                                                                 {hasnote: '--- #note#'}]},
+        'latexdocstrreq': {l_and(isrequired, isintent_nothide): ['\\item[]{{}\\verb@#pydocsign#@{}}',
+                                                                 {hasnote: '--- #note#'}]},
+        'latexdocstrout': {isintent_out: ['\\item[]{{}\\verb@#pydocsignout#@{}}',
+                                          {l_and(hasnote, isintent_hide): '--- #note#',
+                                           l_and(hasnote, isintent_nothide): '--- See above.'}]},
+        'docsign': {l_and(isrequired, isintent_nothide): '#varname#,'},
+        'docsignopt': {l_and(isoptional, isintent_nothide): '#varname#,'},
+        'depend': ''
+    },
+    {
+        'args': {
+            l_and(isscalar, isintent_c): '#ctype# #varname_i#',
+            l_and(isscalar, l_not(isintent_c)): '#ctype# *#varname_i#_cb_capi',
+            isarray: '#ctype# *#varname_i#',
+            isstring: '#ctype# #varname_i#'
+        },
+        'args_nm': {
+            l_and(isscalar, isintent_c): '#varname_i#',
+            l_and(isscalar, l_not(isintent_c)): '#varname_i#_cb_capi',
+            isarray: '#varname_i#',
+            isstring: '#varname_i#'
+        },
+        'args_td': {
+            l_and(isscalar, isintent_c): '#ctype#',
+            l_and(isscalar, l_not(isintent_c)): '#ctype# *',
+            isarray: '#ctype# *',
+            isstring: '#ctype#'
+        },
+        'need': {l_or(isscalar, isarray, isstring): '#ctype#'},
+        # untested with multiple args
+        'strarglens': {isstring: ',int #varname_i#_cb_len'},
+        'strarglens_td': {isstring: ',int'},  # untested with multiple args
+        # untested with multiple args
+        'strarglens_nm': {isstring: ',#varname_i#_cb_len'},
+    },
+    {  # Scalars
+        'decl': {l_not(isintent_c): '    #ctype# #varname_i#=(*#varname_i#_cb_capi);'},
+        'error': {l_and(isintent_c, isintent_out,
+                        throw_error('intent(c,out) is forbidden for callback scalar arguments')):
+                  ''},
+        'frompyobj': [{debugcapi: '    CFUNCSMESS("cb:Getting #varname#->");'},
+                      {isintent_out:
+                       '    if (capi_j>capi_i)\n        GETSCALARFROMPYTUPLE(capi_return,capi_i++,#varname_i#_cb_capi,#ctype#,"#ctype#_from_pyobj failed in converting argument #varname# of call-back function #name# to C #ctype#\\n");'},
+                      {l_and(debugcapi, l_and(l_not(iscomplex), isintent_c)):
+                          '    fprintf(stderr,"#showvalueformat#.\\n",#varname_i#);'},
+                      {l_and(debugcapi, l_and(l_not(iscomplex), l_not(isintent_c))):
+                          '    fprintf(stderr,"#showvalueformat#.\\n",*#varname_i#_cb_capi);'},
+                      {l_and(debugcapi, l_and(iscomplex, isintent_c)):
+                          '    fprintf(stderr,"#showvalueformat#.\\n",(#varname_i#).r,(#varname_i#).i);'},
+                      {l_and(debugcapi, l_and(iscomplex, l_not(isintent_c))):
+                          '    fprintf(stderr,"#showvalueformat#.\\n",(*#varname_i#_cb_capi).r,(*#varname_i#_cb_capi).i);'},
+                      ],
+        'need': [{isintent_out: ['#ctype#_from_pyobj', 'GETSCALARFROMPYTUPLE']},
+                 {debugcapi: 'CFUNCSMESS'}],
+        '_check': isscalar
+    }, {
+        'pyobjfrom': [{isintent_in: """\
+    if (cb->nofargs>capi_i)
+        if (CAPI_ARGLIST_SETITEM(capi_i++,pyobj_from_#ctype#1(#varname_i#)))
+            goto capi_fail;"""},
+                      {isintent_inout: """\
+    if (cb->nofargs>capi_i)
+        if (CAPI_ARGLIST_SETITEM(capi_i++,pyarr_from_p_#ctype#1(#varname_i#_cb_capi)))
+            goto capi_fail;"""}],
+        'need': [{isintent_in: 'pyobj_from_#ctype#1'},
+                 {isintent_inout: 'pyarr_from_p_#ctype#1'},
+                 {iscomplex: '#ctype#'}],
+        '_check': l_and(isscalar, isintent_nothide),
+        '_optional': ''
+    }, {  # String
+        'frompyobj': [{debugcapi: '    CFUNCSMESS("cb:Getting #varname#->\\"");'},
+                      """    if (capi_j>capi_i)
+        GETSTRFROMPYTUPLE(capi_return,capi_i++,#varname_i#,#varname_i#_cb_len);""",
+                      {debugcapi:
+                       '    fprintf(stderr,"#showvalueformat#\\":%d:.\\n",#varname_i#,#varname_i#_cb_len);'},
+                      ],
+        'need': ['#ctype#', 'GETSTRFROMPYTUPLE',
+                 {debugcapi: 'CFUNCSMESS'}, 'string.h'],
+        '_check': l_and(isstring, isintent_out)
+    }, {
+        'pyobjfrom': [
+            {debugcapi:
+             ('    fprintf(stderr,"debug-capi:cb:#varname#=#showvalueformat#:'
+              '%d:\\n",#varname_i#,#varname_i#_cb_len);')},
+            {isintent_in: """\
+    if (cb->nofargs>capi_i)
+        if (CAPI_ARGLIST_SETITEM(capi_i++,pyobj_from_#ctype#1size(#varname_i#,#varname_i#_cb_len)))
+            goto capi_fail;"""},
+                      {isintent_inout: """\
+    if (cb->nofargs>capi_i) {
+        int #varname_i#_cb_dims[] = {#varname_i#_cb_len};
+        if (CAPI_ARGLIST_SETITEM(capi_i++,pyarr_from_p_#ctype#1(#varname_i#,#varname_i#_cb_dims)))
+            goto capi_fail;
+    }"""}],
+        'need': [{isintent_in: 'pyobj_from_#ctype#1size'},
+                 {isintent_inout: 'pyarr_from_p_#ctype#1'}],
+        '_check': l_and(isstring, isintent_nothide),
+        '_optional': ''
+    },
+    # Array ...
+    {
+        'decl': '    npy_intp #varname_i#_Dims[#rank#] = {#rank*[-1]#};',
+        'setdims': '    #cbsetdims#;',
+        '_check': isarray,
+        '_depend': ''
+    },
+    {
+        'pyobjfrom': [{debugcapi: '    fprintf(stderr,"debug-capi:cb:#varname#\\n");'},
+                      {isintent_c: """\
+    if (cb->nofargs>capi_i) {
+        /* tmp_arr will be inserted to capi_arglist_list that will be
+           destroyed when leaving callback function wrapper together
+           with tmp_arr. */
+        PyArrayObject *tmp_arr = (PyArrayObject *)PyArray_New(&PyArray_Type,
+          #rank#,#varname_i#_Dims,#atype#,NULL,(char*)#varname_i#,#elsize#,
+          NPY_ARRAY_CARRAY,NULL);
+""",
+                       l_not(isintent_c): """\
+    if (cb->nofargs>capi_i) {
+        /* tmp_arr will be inserted to capi_arglist_list that will be
+           destroyed when leaving callback function wrapper together
+           with tmp_arr. */
+        PyArrayObject *tmp_arr = (PyArrayObject *)PyArray_New(&PyArray_Type,
+          #rank#,#varname_i#_Dims,#atype#,NULL,(char*)#varname_i#,#elsize#,
+          NPY_ARRAY_FARRAY,NULL);
+""",
+                       },
+                      """
+        if (tmp_arr==NULL)
+            goto capi_fail;
+        if (CAPI_ARGLIST_SETITEM(capi_i++,(PyObject *)tmp_arr))
+            goto capi_fail;
+}"""],
+        '_check': l_and(isarray, isintent_nothide, l_or(isintent_in, isintent_inout)),
+        '_optional': '',
+    }, {
+        'frompyobj': [{debugcapi: '    CFUNCSMESS("cb:Getting #varname#->");'},
+                      """    if (capi_j>capi_i) {
+        PyArrayObject *rv_cb_arr = NULL;
+        if ((capi_tmp = PyTuple_GetItem(capi_return,capi_i++))==NULL) goto capi_fail;
+        rv_cb_arr =  array_from_pyobj(#atype#,#varname_i#_Dims,#rank#,F2PY_INTENT_IN""",
+                      {isintent_c: '|F2PY_INTENT_C'},
+                      """,capi_tmp);
+        if (rv_cb_arr == NULL) {
+            fprintf(stderr,\"rv_cb_arr is NULL\\n\");
+            goto capi_fail;
+        }
+        MEMCOPY(#varname_i#,PyArray_DATA(rv_cb_arr),PyArray_NBYTES(rv_cb_arr));
+        if (capi_tmp != (PyObject *)rv_cb_arr) {
+            Py_DECREF(rv_cb_arr);
+        }
+    }""",
+                      {debugcapi: '    fprintf(stderr,"<-.\\n");'},
+                      ],
+        'need': ['MEMCOPY', {iscomplexarray: '#ctype#'}],
+        '_check': l_and(isarray, isintent_out)
+    }, {
+        'docreturn': '#varname#,',
+        '_check': isintent_out
+    }
+]
+
+################## Build call-back module #############
+cb_map = {}
+
+
+def buildcallbacks(m):
+    cb_map[m['name']] = []
+    for bi in m['body']:
+        if bi['block'] == 'interface':
+            for b in bi['body']:
+                if b:
+                    buildcallback(b, m['name'])
+                else:
+                    errmess(f"warning: empty body for {m['name']}\n")
+
+
+def buildcallback(rout, um):
+    from . import capi_maps
+
+    outmess(f"    Constructing call-back function \"cb_{rout['name']}_in_{um}\"\n")
+    args, depargs = getargs(rout)
+    capi_maps.depargs = depargs
+    var = rout['vars']
+    vrd = capi_maps.cb_routsign2map(rout, um)
+    rd = dictappend({}, vrd)
+    cb_map[um].append([rout['name'], rd['name']])
+    for r in cb_rout_rules:
+        if ('_check' in r and r['_check'](rout)) or ('_check' not in r):
+            ar = applyrules(r, vrd, rout)
+            rd = dictappend(rd, ar)
+    savevrd = {}
+    for i, a in enumerate(args):
+        vrd = capi_maps.cb_sign2map(a, var[a], index=i)
+        savevrd[a] = vrd
+        for r in cb_arg_rules:
+            if '_depend' in r:
+                continue
+            if '_optional' in r and isoptional(var[a]):
+                continue
+            if ('_check' in r and r['_check'](var[a])) or ('_check' not in r):
+                ar = applyrules(r, vrd, var[a])
+                rd = dictappend(rd, ar)
+                if '_break' in r:
+                    break
+    for a in args:
+        vrd = savevrd[a]
+        for r in cb_arg_rules:
+            if '_depend' in r:
+                continue
+            if ('_optional' not in r) or ('_optional' in r and isrequired(var[a])):
+                continue
+            if ('_check' in r and r['_check'](var[a])) or ('_check' not in r):
+                ar = applyrules(r, vrd, var[a])
+                rd = dictappend(rd, ar)
+                if '_break' in r:
+                    break
+    for a in depargs:
+        vrd = savevrd[a]
+        for r in cb_arg_rules:
+            if '_depend' not in r:
+                continue
+            if '_optional' in r:
+                continue
+            if ('_check' in r and r['_check'](var[a])) or ('_check' not in r):
+                ar = applyrules(r, vrd, var[a])
+                rd = dictappend(rd, ar)
+                if '_break' in r:
+                    break
+    if 'args' in rd and 'optargs' in rd:
+        if isinstance(rd['optargs'], list):
+            rd['optargs'] = rd['optargs'] + ["""
+#ifndef F2PY_CB_RETURNCOMPLEX
+,
+#endif
+"""]
+            rd['optargs_nm'] = rd['optargs_nm'] + ["""
+#ifndef F2PY_CB_RETURNCOMPLEX
+,
+#endif
+"""]
+            rd['optargs_td'] = rd['optargs_td'] + ["""
+#ifndef F2PY_CB_RETURNCOMPLEX
+,
+#endif
+"""]
+    if isinstance(rd['docreturn'], list):
+        rd['docreturn'] = stripcomma(
+            replace('#docreturn#', {'docreturn': rd['docreturn']}))
+    optargs = stripcomma(replace('#docsignopt#',
+                                 {'docsignopt': rd['docsignopt']}
+                                 ))
+    if optargs == '':
+        rd['docsignature'] = stripcomma(
+            replace('#docsign#', {'docsign': rd['docsign']}))
+    else:
+        rd['docsignature'] = replace('#docsign#[#docsignopt#]',
+                                     {'docsign': rd['docsign'],
+                                      'docsignopt': optargs,
+                                      })
+    rd['latexdocsignature'] = rd['docsignature'].replace('_', '\\_')
+    rd['latexdocsignature'] = rd['latexdocsignature'].replace(',', ', ')
+    rd['docstrsigns'] = []
+    rd['latexdocstrsigns'] = []
+    for k in ['docstrreq', 'docstropt', 'docstrout', 'docstrcbs']:
+        if k in rd and isinstance(rd[k], list):
+            rd['docstrsigns'] = rd['docstrsigns'] + rd[k]
+        k = 'latex' + k
+        if k in rd and isinstance(rd[k], list):
+            rd['latexdocstrsigns'] = rd['latexdocstrsigns'] + rd[k][0:1] +\
+                ['\\begin{description}'] + rd[k][1:] +\
+                ['\\end{description}']
+    if 'args' not in rd:
+        rd['args'] = ''
+        rd['args_td'] = ''
+        rd['args_nm'] = ''
+    if not (rd.get('args') or rd.get('optargs') or rd.get('strarglens')):
+        rd['noargs'] = 'void'
+
+    ar = applyrules(cb_routine_rules, rd)
+    cfuncs.callbacks[rd['name']] = ar['body']
+    if isinstance(ar['need'], str):
+        ar['need'] = [ar['need']]
+
+    if 'need' in rd:
+        for t in cfuncs.typedefs.keys():
+            if t in rd['need']:
+                ar['need'].append(t)
+
+    cfuncs.typedefs_generated[rd['name'] + '_typedef'] = ar['cbtypedefs']
+    ar['need'].append(rd['name'] + '_typedef')
+    cfuncs.needs[rd['name']] = ar['need']
+
+    capi_maps.lcb2_map[rd['name']] = {'maxnofargs': ar['maxnofargs'],
+                                      'nofoptargs': ar['nofoptargs'],
+                                      'docstr': ar['docstr'],
+                                      'latexdocstr': ar['latexdocstr'],
+                                      'argname': rd['argname']
+                                      }
+    outmess(f"      {ar['docstrshort']}\n")
+################## Build call-back function #############
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..67d3fd9b4e1b18cd5890da6fbfe51300c0806344
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/cb_rules.pyi
@@ -0,0 +1,17 @@
+from collections.abc import Mapping
+from typing import Any, Final
+
+from .__version__ import version
+
+##
+
+f2py_version: Final = version
+
+cb_routine_rules: Final[dict[str, str | list[str]]] = ...
+cb_rout_rules: Final[list[dict[str, str | Any]]] = ...
+cb_arg_rules: Final[list[dict[str, str | Any]]] = ...
+
+cb_map: Final[dict[str, list[list[str]]]] = ...
+
+def buildcallbacks(m: Mapping[str, object]) -> None: ...
+def buildcallback(rout: Mapping[str, object], um: Mapping[str, object]) -> None: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.py b/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.py
new file mode 100644
index 0000000000000000000000000000000000000000..c33a0d9ecbd825fd3bc4bffe64fc14c78e6f2343
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.py
@@ -0,0 +1,1563 @@
+"""
+C declarations, CPP macros, and C functions for f2py2e.
+Only required declarations/macros/functions will be used.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+import copy
+import sys
+
+from . import __version__
+
+f2py_version = __version__.version
+
+
+def errmess(s: str) -> None:
+    """
+    Write an error message to stderr.
+
+    This indirection is needed because sys.stderr might not always be available (see #26862).
+    """
+    if sys.stderr is not None:
+        sys.stderr.write(s)
+
+##################### Definitions ##################
+
+
+outneeds = {'includes0': [], 'includes': [], 'typedefs': [], 'typedefs_generated': [],
+            'userincludes': [],
+            'cppmacros': [], 'cfuncs': [], 'callbacks': [], 'f90modhooks': [],
+            'commonhooks': []}
+needs = {}
+includes0 = {'includes0': '/*need_includes0*/'}
+includes = {'includes': '/*need_includes*/'}
+userincludes = {'userincludes': '/*need_userincludes*/'}
+typedefs = {'typedefs': '/*need_typedefs*/'}
+typedefs_generated = {'typedefs_generated': '/*need_typedefs_generated*/'}
+cppmacros = {'cppmacros': '/*need_cppmacros*/'}
+cfuncs = {'cfuncs': '/*need_cfuncs*/'}
+callbacks = {'callbacks': '/*need_callbacks*/'}
+f90modhooks = {'f90modhooks': '/*need_f90modhooks*/',
+               'initf90modhooksstatic': '/*initf90modhooksstatic*/',
+               'initf90modhooksdynamic': '/*initf90modhooksdynamic*/',
+               }
+commonhooks = {'commonhooks': '/*need_commonhooks*/',
+               'initcommonhooks': '/*need_initcommonhooks*/',
+               }
+
+############ Includes ###################
+
+includes0['math.h'] = '#include <math.h>'
+includes0['string.h'] = '#include <string.h>'
+includes0['setjmp.h'] = '#include <setjmp.h>'
+
+includes['arrayobject.h'] = '''#define PY_ARRAY_UNIQUE_SYMBOL PyArray_API
+#include "arrayobject.h"'''
+includes['npy_math.h'] = '#include "numpy/npy_math.h"'
+
+includes['arrayobject.h'] = '#include "fortranobject.h"'
+includes['stdarg.h'] = '#include <stdarg.h>'
+
+############# Type definitions ###############
+
+typedefs['unsigned_char'] = 'typedef unsigned char unsigned_char;'
+typedefs['unsigned_short'] = 'typedef unsigned short unsigned_short;'
+typedefs['unsigned_long'] = 'typedef unsigned long unsigned_long;'
+typedefs['signed_char'] = 'typedef signed char signed_char;'
+typedefs['long_long'] = """
+#if defined(NPY_OS_WIN32)
+typedef __int64 long_long;
+#else
+typedef long long long_long;
+typedef unsigned long long unsigned_long_long;
+#endif
+"""
+typedefs['unsigned_long_long'] = """
+#if defined(NPY_OS_WIN32)
+typedef __uint64 long_long;
+#else
+typedef unsigned long long unsigned_long_long;
+#endif
+"""
+typedefs['long_double'] = """
+#ifndef _LONG_DOUBLE
+typedef long double long_double;
+#endif
+"""
+typedefs[
+    'complex_long_double'] = 'typedef struct {long double r,i;} complex_long_double;'
+typedefs['complex_float'] = 'typedef struct {float r,i;} complex_float;'
+typedefs['complex_double'] = 'typedef struct {double r,i;} complex_double;'
+typedefs['string'] = """typedef char * string;"""
+typedefs['character'] = """typedef char character;"""
+
+
+############### CPP macros ####################
+cppmacros['CFUNCSMESS'] = """
+#ifdef DEBUGCFUNCS
+#define CFUNCSMESS(mess) fprintf(stderr,\"debug-capi:\"mess);
+#define CFUNCSMESSPY(mess,obj) CFUNCSMESS(mess) \\
+    PyObject_Print((PyObject *)obj,stderr,Py_PRINT_RAW);\\
+    fprintf(stderr,\"\\n\");
+#else
+#define CFUNCSMESS(mess)
+#define CFUNCSMESSPY(mess,obj)
+#endif
+"""
+cppmacros['F_FUNC'] = """
+#if defined(PREPEND_FORTRAN)
+#if defined(NO_APPEND_FORTRAN)
+#if defined(UPPERCASE_FORTRAN)
+#define F_FUNC(f,F) _##F
+#else
+#define F_FUNC(f,F) _##f
+#endif
+#else
+#if defined(UPPERCASE_FORTRAN)
+#define F_FUNC(f,F) _##F##_
+#else
+#define F_FUNC(f,F) _##f##_
+#endif
+#endif
+#else
+#if defined(NO_APPEND_FORTRAN)
+#if defined(UPPERCASE_FORTRAN)
+#define F_FUNC(f,F) F
+#else
+#define F_FUNC(f,F) f
+#endif
+#else
+#if defined(UPPERCASE_FORTRAN)
+#define F_FUNC(f,F) F##_
+#else
+#define F_FUNC(f,F) f##_
+#endif
+#endif
+#endif
+#if defined(UNDERSCORE_G77)
+#define F_FUNC_US(f,F) F_FUNC(f##_,F##_)
+#else
+#define F_FUNC_US(f,F) F_FUNC(f,F)
+#endif
+"""
+cppmacros['F_WRAPPEDFUNC'] = """
+#if defined(PREPEND_FORTRAN)
+#if defined(NO_APPEND_FORTRAN)
+#if defined(UPPERCASE_FORTRAN)
+#define F_WRAPPEDFUNC(f,F) _F2PYWRAP##F
+#else
+#define F_WRAPPEDFUNC(f,F) _f2pywrap##f
+#endif
+#else
+#if defined(UPPERCASE_FORTRAN)
+#define F_WRAPPEDFUNC(f,F) _F2PYWRAP##F##_
+#else
+#define F_WRAPPEDFUNC(f,F) _f2pywrap##f##_
+#endif
+#endif
+#else
+#if defined(NO_APPEND_FORTRAN)
+#if defined(UPPERCASE_FORTRAN)
+#define F_WRAPPEDFUNC(f,F) F2PYWRAP##F
+#else
+#define F_WRAPPEDFUNC(f,F) f2pywrap##f
+#endif
+#else
+#if defined(UPPERCASE_FORTRAN)
+#define F_WRAPPEDFUNC(f,F) F2PYWRAP##F##_
+#else
+#define F_WRAPPEDFUNC(f,F) f2pywrap##f##_
+#endif
+#endif
+#endif
+#if defined(UNDERSCORE_G77)
+#define F_WRAPPEDFUNC_US(f,F) F_WRAPPEDFUNC(f##_,F##_)
+#else
+#define F_WRAPPEDFUNC_US(f,F) F_WRAPPEDFUNC(f,F)
+#endif
+"""
+cppmacros['F_MODFUNC'] = """
+#if defined(F90MOD2CCONV1) /*E.g. Compaq Fortran */
+#if defined(NO_APPEND_FORTRAN)
+#define F_MODFUNCNAME(m,f) $ ## m ## $ ## f
+#else
+#define F_MODFUNCNAME(m,f) $ ## m ## $ ## f ## _
+#endif
+#endif
+
+#if defined(F90MOD2CCONV2) /*E.g. IBM XL Fortran, not tested though */
+#if defined(NO_APPEND_FORTRAN)
+#define F_MODFUNCNAME(m,f)  __ ## m ## _MOD_ ## f
+#else
+#define F_MODFUNCNAME(m,f)  __ ## m ## _MOD_ ## f ## _
+#endif
+#endif
+
+#if defined(F90MOD2CCONV3) /*E.g. MIPSPro Compilers */
+#if defined(NO_APPEND_FORTRAN)
+#define F_MODFUNCNAME(m,f)  f ## .in. ## m
+#else
+#define F_MODFUNCNAME(m,f)  f ## .in. ## m ## _
+#endif
+#endif
+/*
+#if defined(UPPERCASE_FORTRAN)
+#define F_MODFUNC(m,M,f,F) F_MODFUNCNAME(M,F)
+#else
+#define F_MODFUNC(m,M,f,F) F_MODFUNCNAME(m,f)
+#endif
+*/
+
+#define F_MODFUNC(m,f) (*(f2pymodstruct##m##.##f))
+"""
+cppmacros['SWAPUNSAFE'] = """
+#define SWAP(a,b) (size_t)(a) = ((size_t)(a) ^ (size_t)(b));\\
+ (size_t)(b) = ((size_t)(a) ^ (size_t)(b));\\
+ (size_t)(a) = ((size_t)(a) ^ (size_t)(b))
+"""
+cppmacros['SWAP'] = """
+#define SWAP(a,b,t) {\\
+    t *c;\\
+    c = a;\\
+    a = b;\\
+    b = c;}
+"""
+# cppmacros['ISCONTIGUOUS']='#define ISCONTIGUOUS(m) (PyArray_FLAGS(m) &
+# NPY_ARRAY_C_CONTIGUOUS)'
+cppmacros['PRINTPYOBJERR'] = """
+#define PRINTPYOBJERR(obj)\\
+    fprintf(stderr,\"#modulename#.error is related to \");\\
+    PyObject_Print((PyObject *)obj,stderr,Py_PRINT_RAW);\\
+    fprintf(stderr,\"\\n\");
+"""
+cppmacros['MINMAX'] = """
+#ifndef max
+#define max(a,b) ((a > b) ? (a) : (b))
+#endif
+#ifndef min
+#define min(a,b) ((a < b) ? (a) : (b))
+#endif
+#ifndef MAX
+#define MAX(a,b) ((a > b) ? (a) : (b))
+#endif
+#ifndef MIN
+#define MIN(a,b) ((a < b) ? (a) : (b))
+#endif
+"""
+cppmacros['len..'] = """
+/* See fortranobject.h for definitions. The macros here are provided for BC. */
+#define rank f2py_rank
+#define shape f2py_shape
+#define fshape f2py_shape
+#define len f2py_len
+#define flen f2py_flen
+#define slen f2py_slen
+#define size f2py_size
+"""
+cppmacros['pyobj_from_char1'] = r"""
+#define pyobj_from_char1(v) (PyLong_FromLong(v))
+"""
+cppmacros['pyobj_from_short1'] = r"""
+#define pyobj_from_short1(v) (PyLong_FromLong(v))
+"""
+needs['pyobj_from_int1'] = ['signed_char']
+cppmacros['pyobj_from_int1'] = r"""
+#define pyobj_from_int1(v) (PyLong_FromLong(v))
+"""
+cppmacros['pyobj_from_long1'] = r"""
+#define pyobj_from_long1(v) (PyLong_FromLong(v))
+"""
+needs['pyobj_from_long_long1'] = ['long_long']
+cppmacros['pyobj_from_long_long1'] = """
+#ifdef HAVE_LONG_LONG
+#define pyobj_from_long_long1(v) (PyLong_FromLongLong(v))
+#else
+#warning HAVE_LONG_LONG is not available. Redefining pyobj_from_long_long.
+#define pyobj_from_long_long1(v) (PyLong_FromLong(v))
+#endif
+"""
+needs['pyobj_from_long_double1'] = ['long_double']
+cppmacros['pyobj_from_long_double1'] = """
+#define pyobj_from_long_double1(v) (PyFloat_FromDouble(v))"""
+cppmacros['pyobj_from_double1'] = """
+#define pyobj_from_double1(v) (PyFloat_FromDouble(v))"""
+cppmacros['pyobj_from_float1'] = """
+#define pyobj_from_float1(v) (PyFloat_FromDouble(v))"""
+needs['pyobj_from_complex_long_double1'] = ['complex_long_double']
+cppmacros['pyobj_from_complex_long_double1'] = """
+#define pyobj_from_complex_long_double1(v) (PyComplex_FromDoubles(v.r,v.i))"""
+needs['pyobj_from_complex_double1'] = ['complex_double']
+cppmacros['pyobj_from_complex_double1'] = """
+#define pyobj_from_complex_double1(v) (PyComplex_FromDoubles(v.r,v.i))"""
+needs['pyobj_from_complex_float1'] = ['complex_float']
+cppmacros['pyobj_from_complex_float1'] = """
+#define pyobj_from_complex_float1(v) (PyComplex_FromDoubles(v.r,v.i))"""
+needs['pyobj_from_string1'] = ['string']
+cppmacros['pyobj_from_string1'] = """
+#define pyobj_from_string1(v) (PyUnicode_FromString((char *)v))"""
+needs['pyobj_from_string1size'] = ['string']
+cppmacros['pyobj_from_string1size'] = """
+#define pyobj_from_string1size(v,len) (PyUnicode_FromStringAndSize((char *)v, len))"""
+needs['TRYPYARRAYTEMPLATE'] = ['PRINTPYOBJERR']
+cppmacros['TRYPYARRAYTEMPLATE'] = """
+/* New SciPy */
+#define TRYPYARRAYTEMPLATECHAR case NPY_STRING: *(char *)(PyArray_DATA(arr))=*v; break;
+#define TRYPYARRAYTEMPLATELONG case NPY_LONG: *(long *)(PyArray_DATA(arr))=*v; break;
+#define TRYPYARRAYTEMPLATEOBJECT case NPY_OBJECT: PyArray_SETITEM(arr,PyArray_DATA(arr),pyobj_from_ ## ctype ## 1(*v)); break;
+
+#define TRYPYARRAYTEMPLATE(ctype,typecode) \\
+        PyArrayObject *arr = NULL;\\
+        if (!obj) return -2;\\
+        if (!PyArray_Check(obj)) return -1;\\
+        if (!(arr=(PyArrayObject *)obj)) {fprintf(stderr,\"TRYPYARRAYTEMPLATE:\");PRINTPYOBJERR(obj);return 0;}\\
+        if (PyArray_DESCR(arr)->type==typecode)  {*(ctype *)(PyArray_DATA(arr))=*v; return 1;}\\
+        switch (PyArray_TYPE(arr)) {\\
+                case NPY_DOUBLE: *(npy_double *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_INT: *(npy_int *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_LONG: *(npy_long *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_FLOAT: *(npy_float *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_CDOUBLE: *(npy_double *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_CFLOAT: *(npy_float *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_BOOL: *(npy_bool *)(PyArray_DATA(arr))=(*v!=0); break;\\
+                case NPY_UBYTE: *(npy_ubyte *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_BYTE: *(npy_byte *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_SHORT: *(npy_short *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_USHORT: *(npy_ushort *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_UINT: *(npy_uint *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_ULONG: *(npy_ulong *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_LONGLONG: *(npy_longlong *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_ULONGLONG: *(npy_ulonglong *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_LONGDOUBLE: *(npy_longdouble *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_CLONGDOUBLE: *(npy_longdouble *)(PyArray_DATA(arr))=*v; break;\\
+                case NPY_OBJECT: PyArray_SETITEM(arr, PyArray_DATA(arr), pyobj_from_ ## ctype ## 1(*v)); break;\\
+        default: return -2;\\
+        };\\
+        return 1
+"""
+
+needs['TRYCOMPLEXPYARRAYTEMPLATE'] = ['PRINTPYOBJERR']
+cppmacros['TRYCOMPLEXPYARRAYTEMPLATE'] = """
+#define TRYCOMPLEXPYARRAYTEMPLATEOBJECT case NPY_OBJECT: PyArray_SETITEM(arr, PyArray_DATA(arr), pyobj_from_complex_ ## ctype ## 1((*v))); break;
+#define TRYCOMPLEXPYARRAYTEMPLATE(ctype,typecode)\\
+        PyArrayObject *arr = NULL;\\
+        if (!obj) return -2;\\
+        if (!PyArray_Check(obj)) return -1;\\
+        if (!(arr=(PyArrayObject *)obj)) {fprintf(stderr,\"TRYCOMPLEXPYARRAYTEMPLATE:\");PRINTPYOBJERR(obj);return 0;}\\
+        if (PyArray_DESCR(arr)->type==typecode) {\\
+            *(ctype *)(PyArray_DATA(arr))=(*v).r;\\
+            *(ctype *)(PyArray_DATA(arr)+sizeof(ctype))=(*v).i;\\
+            return 1;\\
+        }\\
+        switch (PyArray_TYPE(arr)) {\\
+                case NPY_CDOUBLE: *(npy_double *)(PyArray_DATA(arr))=(*v).r;\\
+                                  *(npy_double *)(PyArray_DATA(arr)+sizeof(npy_double))=(*v).i;\\
+                                  break;\\
+                case NPY_CFLOAT: *(npy_float *)(PyArray_DATA(arr))=(*v).r;\\
+                                 *(npy_float *)(PyArray_DATA(arr)+sizeof(npy_float))=(*v).i;\\
+                                 break;\\
+                case NPY_DOUBLE: *(npy_double *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_LONG: *(npy_long *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_FLOAT: *(npy_float *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_INT: *(npy_int *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_SHORT: *(npy_short *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_UBYTE: *(npy_ubyte *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_BYTE: *(npy_byte *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_BOOL: *(npy_bool *)(PyArray_DATA(arr))=((*v).r!=0 && (*v).i!=0); break;\\
+                case NPY_USHORT: *(npy_ushort *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_UINT: *(npy_uint *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_ULONG: *(npy_ulong *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_LONGLONG: *(npy_longlong *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_ULONGLONG: *(npy_ulonglong *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_LONGDOUBLE: *(npy_longdouble *)(PyArray_DATA(arr))=(*v).r; break;\\
+                case NPY_CLONGDOUBLE: *(npy_longdouble *)(PyArray_DATA(arr))=(*v).r;\\
+                                      *(npy_longdouble *)(PyArray_DATA(arr)+sizeof(npy_longdouble))=(*v).i;\\
+                                      break;\\
+                case NPY_OBJECT: PyArray_SETITEM(arr, PyArray_DATA(arr), pyobj_from_complex_ ## ctype ## 1((*v))); break;\\
+                default: return -2;\\
+        };\\
+        return -1;
+"""
+# cppmacros['NUMFROMARROBJ']="""
+# define NUMFROMARROBJ(typenum,ctype) \\
+#     if (PyArray_Check(obj)) arr = (PyArrayObject *)obj;\\
+#     else arr = (PyArrayObject *)PyArray_ContiguousFromObject(obj,typenum,0,0);\\
+#     if (arr) {\\
+#         if (PyArray_TYPE(arr)==NPY_OBJECT) {\\
+#             if (!ctype ## _from_pyobj(v,(PyArray_DESCR(arr)->getitem)(PyArray_DATA(arr)),\"\"))\\
+#             goto capi_fail;\\
+#         } else {\\
+#             (PyArray_DESCR(arr)->cast[typenum])(PyArray_DATA(arr),1,(char*)v,1,1);\\
+#         }\\
+#         if ((PyObject *)arr != obj) { Py_DECREF(arr); }\\
+#         return 1;\\
+#     }
+# """
+# XXX: Note that CNUMFROMARROBJ is identical with NUMFROMARROBJ
+# cppmacros['CNUMFROMARROBJ']="""
+# define CNUMFROMARROBJ(typenum,ctype) \\
+#     if (PyArray_Check(obj)) arr = (PyArrayObject *)obj;\\
+#     else arr = (PyArrayObject *)PyArray_ContiguousFromObject(obj,typenum,0,0);\\
+#     if (arr) {\\
+#         if (PyArray_TYPE(arr)==NPY_OBJECT) {\\
+#             if (!ctype ## _from_pyobj(v,(PyArray_DESCR(arr)->getitem)(PyArray_DATA(arr)),\"\"))\\
+#             goto capi_fail;\\
+#         } else {\\
+#             (PyArray_DESCR(arr)->cast[typenum])((void *)(PyArray_DATA(arr)),1,(void *)(v),1,1);\\
+#         }\\
+#         if ((PyObject *)arr != obj) { Py_DECREF(arr); }\\
+#         return 1;\\
+#     }
+# """
+
+
+needs['GETSTRFROMPYTUPLE'] = ['STRINGCOPYN', 'PRINTPYOBJERR']
+cppmacros['GETSTRFROMPYTUPLE'] = """
+#define GETSTRFROMPYTUPLE(tuple,index,str,len) {\\
+        PyObject *rv_cb_str = PyTuple_GetItem((tuple),(index));\\
+        if (rv_cb_str == NULL)\\
+            goto capi_fail;\\
+        if (PyBytes_Check(rv_cb_str)) {\\
+            str[len-1]='\\0';\\
+            STRINGCOPYN((str),PyBytes_AS_STRING((PyBytesObject*)rv_cb_str),(len));\\
+        } else {\\
+            PRINTPYOBJERR(rv_cb_str);\\
+            PyErr_SetString(#modulename#_error,\"string object expected\");\\
+            goto capi_fail;\\
+        }\\
+    }
+"""
+cppmacros['GETSCALARFROMPYTUPLE'] = """
+#define GETSCALARFROMPYTUPLE(tuple,index,var,ctype,mess) {\\
+        if ((capi_tmp = PyTuple_GetItem((tuple),(index)))==NULL) goto capi_fail;\\
+        if (!(ctype ## _from_pyobj((var),capi_tmp,mess)))\\
+            goto capi_fail;\\
+    }
+"""
+
+cppmacros['FAILNULL'] = """\
+#define FAILNULL(p) do {                                            \\
+    if ((p) == NULL) {                                              \\
+        PyErr_SetString(PyExc_MemoryError, "NULL pointer found");   \\
+        goto capi_fail;                                             \\
+    }                                                               \\
+} while (0)
+"""
+needs['MEMCOPY'] = ['string.h', 'FAILNULL']
+cppmacros['MEMCOPY'] = """
+#define MEMCOPY(to,from,n)\\
+    do { FAILNULL(to); FAILNULL(from); (void)memcpy(to,from,n); } while (0)
+"""
+cppmacros['STRINGMALLOC'] = """
+#define STRINGMALLOC(str,len)\\
+    if ((str = (string)malloc(len+1)) == NULL) {\\
+        PyErr_SetString(PyExc_MemoryError, \"out of memory\");\\
+        goto capi_fail;\\
+    } else {\\
+        (str)[len] = '\\0';\\
+    }
+"""
+cppmacros['STRINGFREE'] = """
+#define STRINGFREE(str) do {if (!(str == NULL)) free(str);} while (0)
+"""
+needs['STRINGPADN'] = ['string.h']
+cppmacros['STRINGPADN'] = """
+/*
+STRINGPADN replaces null values with padding values from the right.
+
+`to` must have size of at least N bytes.
+
+If the `to[N-1]` has null value, then replace it and all the
+preceding, nulls with the given padding.
+
+STRINGPADN(to, N, PADDING, NULLVALUE) is an inverse operation.
+*/
+#define STRINGPADN(to, N, NULLVALUE, PADDING)                   \\
+    do {                                                        \\
+        int _m = (N);                                           \\
+        char *_to = (to);                                       \\
+        for (_m -= 1; _m >= 0 && _to[_m] == NULLVALUE; _m--) {  \\
+             _to[_m] = PADDING;                                 \\
+        }                                                       \\
+    } while (0)
+"""
+needs['STRINGCOPYN'] = ['string.h', 'FAILNULL']
+cppmacros['STRINGCOPYN'] = """
+/*
+STRINGCOPYN copies N bytes.
+
+`to` and `from` buffers must have sizes of at least N bytes.
+*/
+#define STRINGCOPYN(to,from,N)                                  \\
+    do {                                                        \\
+        int _m = (N);                                           \\
+        char *_to = (to);                                       \\
+        char *_from = (from);                                   \\
+        FAILNULL(_to); FAILNULL(_from);                         \\
+        (void)strncpy(_to, _from, _m);             \\
+    } while (0)
+"""
+needs['STRINGCOPY'] = ['string.h', 'FAILNULL']
+cppmacros['STRINGCOPY'] = """
+#define STRINGCOPY(to,from)\\
+    do { FAILNULL(to); FAILNULL(from); (void)strcpy(to,from); } while (0)
+"""
+cppmacros['CHECKGENERIC'] = """
+#define CHECKGENERIC(check,tcheck,name) \\
+    if (!(check)) {\\
+        PyErr_SetString(#modulename#_error,\"(\"tcheck\") failed for \"name);\\
+        /*goto capi_fail;*/\\
+    } else """
+cppmacros['CHECKARRAY'] = """
+#define CHECKARRAY(check,tcheck,name) \\
+    if (!(check)) {\\
+        PyErr_SetString(#modulename#_error,\"(\"tcheck\") failed for \"name);\\
+        /*goto capi_fail;*/\\
+    } else """
+cppmacros['CHECKSTRING'] = """
+#define CHECKSTRING(check,tcheck,name,show,var)\\
+    if (!(check)) {\\
+        char errstring[256];\\
+        sprintf(errstring, \"%s: \"show, \"(\"tcheck\") failed for \"name, slen(var), var);\\
+        PyErr_SetString(#modulename#_error, errstring);\\
+        /*goto capi_fail;*/\\
+    } else """
+cppmacros['CHECKSCALAR'] = """
+#define CHECKSCALAR(check,tcheck,name,show,var)\\
+    if (!(check)) {\\
+        char errstring[256];\\
+        sprintf(errstring, \"%s: \"show, \"(\"tcheck\") failed for \"name, var);\\
+        PyErr_SetString(#modulename#_error,errstring);\\
+        /*goto capi_fail;*/\\
+    } else """
+# cppmacros['CHECKDIMS']="""
+# define CHECKDIMS(dims,rank) \\
+#     for (int i=0;i<(rank);i++)\\
+#         if (dims[i]<0) {\\
+#             fprintf(stderr,\"Unspecified array argument requires a complete dimension specification.\\n\");\\
+#             goto capi_fail;\\
+#         }
+# """
+cppmacros[
+    'ARRSIZE'] = '#define ARRSIZE(dims,rank) (_PyArray_multiply_list(dims,rank))'
+cppmacros['OLDPYNUM'] = """
+#ifdef OLDPYNUM
+#error You need to install NumPy version 0.13 or higher. See https://scipy.org/install.html
+#endif
+"""
+
+# Defining the correct value to indicate thread-local storage in C without
+# running a compile-time check (which we have no control over in generated
+# code used outside of NumPy) is hard. Therefore we support overriding this
+# via an external define - the f2py-using package can then use the same
+# compile-time checks as we use for `NPY_TLS` when building NumPy (see
+# scipy#21860 for an example of that).
+#
+# __STDC_NO_THREADS__ should not be coupled to the availability of _Thread_local.
+# In case we get a bug report, guard it with __STDC_NO_THREADS__ after all.
+#
+# `thread_local` has become a keyword in C23, but don't try to use that yet
+# (too new, doing so while C23 support is preliminary will likely cause more
+#  problems than it solves).
+#
+# Note: do not try to use `threads.h`, its availability is very low
+# *and* threads.h isn't actually used where `F2PY_THREAD_LOCAL_DECL` is
+# in the generated code. See gh-27718 for more details.
+cppmacros["F2PY_THREAD_LOCAL_DECL"] = """
+#ifndef F2PY_THREAD_LOCAL_DECL
+#if defined(_MSC_VER)
+#define F2PY_THREAD_LOCAL_DECL __declspec(thread)
+#elif defined(NPY_OS_MINGW)
+#define F2PY_THREAD_LOCAL_DECL __thread
+#elif defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L)
+#define F2PY_THREAD_LOCAL_DECL _Thread_local
+#elif defined(__GNUC__) \\
+      && (__GNUC__ > 4 || (__GNUC__ == 4 && (__GNUC_MINOR__ >= 4)))
+#define F2PY_THREAD_LOCAL_DECL __thread
+#endif
+#endif
+"""
+################# C functions ###############
+
+cfuncs['calcarrindex'] = """
+static int calcarrindex(int *i,PyArrayObject *arr) {
+    int k,ii = i[0];
+    for (k=1; k < PyArray_NDIM(arr); k++)
+        ii += (ii*(PyArray_DIM(arr,k) - 1)+i[k]); /* assuming contiguous arr */
+    return ii;
+}"""
+cfuncs['calcarrindextr'] = """
+static int calcarrindextr(int *i,PyArrayObject *arr) {
+    int k,ii = i[PyArray_NDIM(arr)-1];
+    for (k=1; k < PyArray_NDIM(arr); k++)
+        ii += (ii*(PyArray_DIM(arr,PyArray_NDIM(arr)-k-1) - 1)+i[PyArray_NDIM(arr)-k-1]); /* assuming contiguous arr */
+    return ii;
+}"""
+cfuncs['forcomb'] = """
+struct ForcombCache { int nd;npy_intp *d;int *i,*i_tr,tr; };
+static int initforcomb(struct ForcombCache *cache, npy_intp *dims,int nd,int tr) {
+  int k;
+  if (dims==NULL) return 0;
+  if (nd<0) return 0;
+  cache->nd = nd;
+  cache->d = dims;
+  cache->tr = tr;
+
+  cache->i = (int *)malloc(sizeof(int)*nd);
+  if (cache->i==NULL) return 0;
+  cache->i_tr = (int *)malloc(sizeof(int)*nd);
+  if (cache->i_tr==NULL) {free(cache->i); return 0;};
+
+  for (k=1;k<nd;k++) {
+    cache->i[k] = cache->i_tr[nd-k-1] = 0;
+  }
+  cache->i[0] = cache->i_tr[nd-1] = -1;
+  return 1;
+}
+static int *nextforcomb(struct ForcombCache *cache) {
+  if (cache==NULL) return NULL;
+  int j,*i,*i_tr,k;
+  int nd=cache->nd;
+  if ((i=cache->i) == NULL) return NULL;
+  if ((i_tr=cache->i_tr) == NULL) return NULL;
+  if (cache->d == NULL) return NULL;
+  i[0]++;
+  if (i[0]==cache->d[0]) {
+    j=1;
+    while ((j<nd) && (i[j]==cache->d[j]-1)) j++;
+    if (j==nd) {
+      free(i);
+      free(i_tr);
+      return NULL;
+    }
+    for (k=0;k<j;k++) i[k] = i_tr[nd-k-1] = 0;
+    i[j]++;
+    i_tr[nd-j-1]++;
+  } else
+    i_tr[nd-1]++;
+  if (cache->tr) return i_tr;
+  return i;
+}"""
+needs['try_pyarr_from_string'] = ['STRINGCOPYN', 'PRINTPYOBJERR', 'string']
+cfuncs['try_pyarr_from_string'] = """
+/*
+  try_pyarr_from_string copies str[:len(obj)] to the data of an `ndarray`.
+
+  If obj is an `ndarray`, it is assumed to be contiguous.
+
+  If the specified len==-1, str must be null-terminated.
+*/
+static int try_pyarr_from_string(PyObject *obj,
+                                 const string str, const int len) {
+#ifdef DEBUGCFUNCS
+fprintf(stderr, "try_pyarr_from_string(str='%s', len=%d, obj=%p)\\n",
+        (char*)str,len, obj);
+#endif
+    if (!obj) return -2; /* Object missing */
+    if (obj == Py_None) return -1; /* None */
+    if (!PyArray_Check(obj)) goto capi_fail; /* not an ndarray */
+    if (PyArray_Check(obj)) {
+        PyArrayObject *arr = (PyArrayObject *)obj;
+        assert(ISCONTIGUOUS(arr));
+        string buf = PyArray_DATA(arr);
+        npy_intp n = len;
+        if (n == -1) {
+            /* Assuming null-terminated str. */
+            n = strlen(str);
+        }
+        if (n > PyArray_NBYTES(arr)) {
+            n = PyArray_NBYTES(arr);
+        }
+        STRINGCOPYN(buf, str, n);
+        return 1;
+    }
+capi_fail:
+    PRINTPYOBJERR(obj);
+    PyErr_SetString(#modulename#_error, \"try_pyarr_from_string failed\");
+    return 0;
+}
+"""
+needs['string_from_pyobj'] = ['string', 'STRINGMALLOC', 'STRINGCOPYN']
+cfuncs['string_from_pyobj'] = """
+/*
+  Create a new string buffer `str` of at most length `len` from a
+  Python string-like object `obj`.
+
+  The string buffer has given size (len) or the size of inistr when len==-1.
+
+  The string buffer is padded with blanks: in Fortran, trailing blanks
+  are insignificant contrary to C nulls.
+ */
+static int
+string_from_pyobj(string *str, int *len, const string inistr, PyObject *obj,
+                  const char *errmess)
+{
+    PyObject *tmp = NULL;
+    string buf = NULL;
+    npy_intp n = -1;
+#ifdef DEBUGCFUNCS
+fprintf(stderr,\"string_from_pyobj(str='%s',len=%d,inistr='%s',obj=%p)\\n\",
+               (char*)str, *len, (char *)inistr, obj);
+#endif
+    if (obj == Py_None) {
+        n = strlen(inistr);
+        buf = inistr;
+    }
+    else if (PyArray_Check(obj)) {
+        PyArrayObject *arr = (PyArrayObject *)obj;
+        if (!ISCONTIGUOUS(arr)) {
+            PyErr_SetString(PyExc_ValueError,
+                            \"array object is non-contiguous.\");
+            goto capi_fail;
+        }
+        n = PyArray_NBYTES(arr);
+        buf = PyArray_DATA(arr);
+        n = strnlen(buf, n);
+    }
+    else {
+        if (PyBytes_Check(obj)) {
+            tmp = obj;
+            Py_INCREF(tmp);
+        }
+        else if (PyUnicode_Check(obj)) {
+            tmp = PyUnicode_AsASCIIString(obj);
+        }
+        else {
+            PyObject *tmp2;
+            tmp2 = PyObject_Str(obj);
+            if (tmp2) {
+                tmp = PyUnicode_AsASCIIString(tmp2);
+                Py_DECREF(tmp2);
+            }
+            else {
+                tmp = NULL;
+            }
+        }
+        if (tmp == NULL) goto capi_fail;
+        n = PyBytes_GET_SIZE(tmp);
+        buf = PyBytes_AS_STRING(tmp);
+    }
+    if (*len == -1) {
+        /* TODO: change the type of `len` so that we can remove this */
+        if (n > NPY_MAX_INT) {
+            PyErr_SetString(PyExc_OverflowError,
+                            "object too large for a 32-bit int");
+            goto capi_fail;
+        }
+        *len = n;
+    }
+    else if (*len < n) {
+        /* discard the last (len-n) bytes of input buf */
+        n = *len;
+    }
+    if (n < 0 || *len < 0 || buf == NULL) {
+        goto capi_fail;
+    }
+    STRINGMALLOC(*str, *len);  // *str is allocated with size (*len + 1)
+    if (n < *len) {
+        /*
+          Pad fixed-width string with nulls. The caller will replace
+          nulls with blanks when the corresponding argument is not
+          intent(c).
+        */
+        memset(*str + n, '\\0', *len - n);
+    }
+    STRINGCOPYN(*str, buf, n);
+    Py_XDECREF(tmp);
+    return 1;
+capi_fail:
+    Py_XDECREF(tmp);
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = #modulename#_error;
+        }
+        PyErr_SetString(err, errmess);
+    }
+    return 0;
+}
+"""
+
+cfuncs['character_from_pyobj'] = """
+static int
+character_from_pyobj(character* v, PyObject *obj, const char *errmess) {
+    if (PyBytes_Check(obj)) {
+        /* empty bytes has trailing null, so dereferencing is always safe */
+        *v = PyBytes_AS_STRING(obj)[0];
+        return 1;
+    } else if (PyUnicode_Check(obj)) {
+        PyObject* tmp = PyUnicode_AsASCIIString(obj);
+        if (tmp != NULL) {
+            *v = PyBytes_AS_STRING(tmp)[0];
+            Py_DECREF(tmp);
+            return 1;
+        }
+    } else if (PyArray_Check(obj)) {
+        PyArrayObject* arr = (PyArrayObject*)obj;
+        if (F2PY_ARRAY_IS_CHARACTER_COMPATIBLE(arr)) {
+            *v = PyArray_BYTES(arr)[0];
+            return 1;
+        } else if (F2PY_IS_UNICODE_ARRAY(arr)) {
+            // TODO: update when numpy will support 1-byte and
+            // 2-byte unicode dtypes
+            PyObject* tmp = PyUnicode_FromKindAndData(
+                              PyUnicode_4BYTE_KIND,
+                              PyArray_BYTES(arr),
+                              (PyArray_NBYTES(arr)>0?1:0));
+            if (tmp != NULL) {
+                if (character_from_pyobj(v, tmp, errmess)) {
+                    Py_DECREF(tmp);
+                    return 1;
+                }
+                Py_DECREF(tmp);
+            }
+        }
+    } else if (PySequence_Check(obj)) {
+        PyObject* tmp = PySequence_GetItem(obj,0);
+        if (tmp != NULL) {
+            if (character_from_pyobj(v, tmp, errmess)) {
+                Py_DECREF(tmp);
+                return 1;
+            }
+            Py_DECREF(tmp);
+        }
+    }
+    {
+        /* TODO: This error (and most other) error handling needs cleaning. */
+        char mess[F2PY_MESSAGE_BUFFER_SIZE];
+        strcpy(mess, errmess);
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = PyExc_TypeError;
+            Py_INCREF(err);
+        }
+        else {
+            Py_INCREF(err);
+            PyErr_Clear();
+        }
+        sprintf(mess + strlen(mess),
+                " -- expected str|bytes|sequence-of-str-or-bytes, got ");
+        f2py_describe(obj, mess + strlen(mess));
+        PyErr_SetString(err, mess);
+        Py_DECREF(err);
+    }
+    return 0;
+}
+"""
+
+# TODO: These should be dynamically generated, too many mapped to int things,
+# see note in _isocbind.py
+needs['char_from_pyobj'] = ['int_from_pyobj']
+cfuncs['char_from_pyobj'] = """
+static int
+char_from_pyobj(char* v, PyObject *obj, const char *errmess) {
+    int i = 0;
+    if (int_from_pyobj(&i, obj, errmess)) {
+        *v = (char)i;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+needs['signed_char_from_pyobj'] = ['int_from_pyobj', 'signed_char']
+cfuncs['signed_char_from_pyobj'] = """
+static int
+signed_char_from_pyobj(signed_char* v, PyObject *obj, const char *errmess) {
+    int i = 0;
+    if (int_from_pyobj(&i, obj, errmess)) {
+        *v = (signed_char)i;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+needs['short_from_pyobj'] = ['int_from_pyobj']
+cfuncs['short_from_pyobj'] = """
+static int
+short_from_pyobj(short* v, PyObject *obj, const char *errmess) {
+    int i = 0;
+    if (int_from_pyobj(&i, obj, errmess)) {
+        *v = (short)i;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+cfuncs['int_from_pyobj'] = """
+static int
+int_from_pyobj(int* v, PyObject *obj, const char *errmess)
+{
+    PyObject* tmp = NULL;
+
+    if (PyLong_Check(obj)) {
+        *v = Npy__PyLong_AsInt(obj);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    tmp = PyNumber_Long(obj);
+    if (tmp) {
+        *v = Npy__PyLong_AsInt(tmp);
+        Py_DECREF(tmp);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    if (PyComplex_Check(obj)) {
+        PyErr_Clear();
+        tmp = PyObject_GetAttrString(obj,\"real\");
+    }
+    else if (PyBytes_Check(obj) || PyUnicode_Check(obj)) {
+        /*pass*/;
+    }
+    else if (PySequence_Check(obj)) {
+        PyErr_Clear();
+        tmp = PySequence_GetItem(obj, 0);
+    }
+
+    if (tmp) {
+        if (int_from_pyobj(v, tmp, errmess)) {
+            Py_DECREF(tmp);
+            return 1;
+        }
+        Py_DECREF(tmp);
+    }
+
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = #modulename#_error;
+        }
+        PyErr_SetString(err, errmess);
+    }
+    return 0;
+}
+"""
+
+
+cfuncs['long_from_pyobj'] = """
+static int
+long_from_pyobj(long* v, PyObject *obj, const char *errmess) {
+    PyObject* tmp = NULL;
+
+    if (PyLong_Check(obj)) {
+        *v = PyLong_AsLong(obj);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    tmp = PyNumber_Long(obj);
+    if (tmp) {
+        *v = PyLong_AsLong(tmp);
+        Py_DECREF(tmp);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    if (PyComplex_Check(obj)) {
+        PyErr_Clear();
+        tmp = PyObject_GetAttrString(obj,\"real\");
+    }
+    else if (PyBytes_Check(obj) || PyUnicode_Check(obj)) {
+        /*pass*/;
+    }
+    else if (PySequence_Check(obj)) {
+        PyErr_Clear();
+        tmp = PySequence_GetItem(obj, 0);
+    }
+
+    if (tmp) {
+        if (long_from_pyobj(v, tmp, errmess)) {
+            Py_DECREF(tmp);
+            return 1;
+        }
+        Py_DECREF(tmp);
+    }
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = #modulename#_error;
+        }
+        PyErr_SetString(err, errmess);
+    }
+    return 0;
+}
+"""
+
+
+needs['long_long_from_pyobj'] = ['long_long']
+cfuncs['long_long_from_pyobj'] = """
+static int
+long_long_from_pyobj(long_long* v, PyObject *obj, const char *errmess)
+{
+    PyObject* tmp = NULL;
+
+    if (PyLong_Check(obj)) {
+        *v = PyLong_AsLongLong(obj);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    tmp = PyNumber_Long(obj);
+    if (tmp) {
+        *v = PyLong_AsLongLong(tmp);
+        Py_DECREF(tmp);
+        return !(*v == -1 && PyErr_Occurred());
+    }
+
+    if (PyComplex_Check(obj)) {
+        PyErr_Clear();
+        tmp = PyObject_GetAttrString(obj,\"real\");
+    }
+    else if (PyBytes_Check(obj) || PyUnicode_Check(obj)) {
+        /*pass*/;
+    }
+    else if (PySequence_Check(obj)) {
+        PyErr_Clear();
+        tmp = PySequence_GetItem(obj, 0);
+    }
+
+    if (tmp) {
+        if (long_long_from_pyobj(v, tmp, errmess)) {
+            Py_DECREF(tmp);
+            return 1;
+        }
+        Py_DECREF(tmp);
+    }
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = #modulename#_error;
+        }
+        PyErr_SetString(err,errmess);
+    }
+    return 0;
+}
+"""
+
+
+needs['long_double_from_pyobj'] = ['double_from_pyobj', 'long_double']
+cfuncs['long_double_from_pyobj'] = """
+static int
+long_double_from_pyobj(long_double* v, PyObject *obj, const char *errmess)
+{
+    double d=0;
+    if (PyArray_CheckScalar(obj)){
+        if PyArray_IsScalar(obj, LongDouble) {
+            PyArray_ScalarAsCtype(obj, v);
+            return 1;
+        }
+        else if (PyArray_Check(obj)) {
+            PyArrayObject *arr = (PyArrayObject *)obj;
+            if (PyArray_TYPE(arr) == NPY_LONGDOUBLE) {
+                (*v) = *((npy_longdouble *)PyArray_DATA(arr));
+                return 1;
+            }
+        }
+    }
+    if (double_from_pyobj(&d, obj, errmess)) {
+        *v = (long_double)d;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+cfuncs['double_from_pyobj'] = """
+static int
+double_from_pyobj(double* v, PyObject *obj, const char *errmess)
+{
+    PyObject* tmp = NULL;
+    if (PyFloat_Check(obj)) {
+        *v = PyFloat_AsDouble(obj);
+        return !(*v == -1.0 && PyErr_Occurred());
+    }
+
+    tmp = PyNumber_Float(obj);
+    if (tmp) {
+        *v = PyFloat_AsDouble(tmp);
+        Py_DECREF(tmp);
+        return !(*v == -1.0 && PyErr_Occurred());
+    }
+
+    if (PyComplex_Check(obj)) {
+        PyErr_Clear();
+        tmp = PyObject_GetAttrString(obj,\"real\");
+    }
+    else if (PyBytes_Check(obj) || PyUnicode_Check(obj)) {
+        /*pass*/;
+    }
+    else if (PySequence_Check(obj)) {
+        PyErr_Clear();
+        tmp = PySequence_GetItem(obj, 0);
+    }
+
+    if (tmp) {
+        if (double_from_pyobj(v,tmp,errmess)) {Py_DECREF(tmp); return 1;}
+        Py_DECREF(tmp);
+    }
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err==NULL) err = #modulename#_error;
+        PyErr_SetString(err,errmess);
+    }
+    return 0;
+}
+"""
+
+
+needs['float_from_pyobj'] = ['double_from_pyobj']
+cfuncs['float_from_pyobj'] = """
+static int
+float_from_pyobj(float* v, PyObject *obj, const char *errmess)
+{
+    double d=0.0;
+    if (double_from_pyobj(&d,obj,errmess)) {
+        *v = (float)d;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+needs['complex_long_double_from_pyobj'] = ['complex_long_double', 'long_double',
+                                           'complex_double_from_pyobj', 'npy_math.h']
+cfuncs['complex_long_double_from_pyobj'] = """
+static int
+complex_long_double_from_pyobj(complex_long_double* v, PyObject *obj, const char *errmess)
+{
+    complex_double cd = {0.0,0.0};
+    if (PyArray_CheckScalar(obj)){
+        if PyArray_IsScalar(obj, CLongDouble) {
+            PyArray_ScalarAsCtype(obj, v);
+            return 1;
+        }
+        else if (PyArray_Check(obj)) {
+            PyArrayObject *arr = (PyArrayObject *)obj;
+            if (PyArray_TYPE(arr)==NPY_CLONGDOUBLE) {
+                (*v).r = npy_creall(*(((npy_clongdouble *)PyArray_DATA(arr))));
+                (*v).i = npy_cimagl(*(((npy_clongdouble *)PyArray_DATA(arr))));
+                return 1;
+            }
+        }
+    }
+    if (complex_double_from_pyobj(&cd,obj,errmess)) {
+        (*v).r = (long_double)cd.r;
+        (*v).i = (long_double)cd.i;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+needs['complex_double_from_pyobj'] = ['complex_double', 'npy_math.h']
+cfuncs['complex_double_from_pyobj'] = """
+static int
+complex_double_from_pyobj(complex_double* v, PyObject *obj, const char *errmess) {
+    Py_complex c;
+    if (PyComplex_Check(obj)) {
+        c = PyComplex_AsCComplex(obj);
+        (*v).r = c.real;
+        (*v).i = c.imag;
+        return 1;
+    }
+    if (PyArray_IsScalar(obj, ComplexFloating)) {
+        if (PyArray_IsScalar(obj, CFloat)) {
+            npy_cfloat new;
+            PyArray_ScalarAsCtype(obj, &new);
+            (*v).r = (double)npy_crealf(new);
+            (*v).i = (double)npy_cimagf(new);
+        }
+        else if (PyArray_IsScalar(obj, CLongDouble)) {
+            npy_clongdouble new;
+            PyArray_ScalarAsCtype(obj, &new);
+            (*v).r = (double)npy_creall(new);
+            (*v).i = (double)npy_cimagl(new);
+        }
+        else { /* if (PyArray_IsScalar(obj, CDouble)) */
+            PyArray_ScalarAsCtype(obj, v);
+        }
+        return 1;
+    }
+    if (PyArray_CheckScalar(obj)) { /* 0-dim array or still array scalar */
+        PyArrayObject *arr;
+        if (PyArray_Check(obj)) {
+            arr = (PyArrayObject *)PyArray_Cast((PyArrayObject *)obj, NPY_CDOUBLE);
+        }
+        else {
+            arr = (PyArrayObject *)PyArray_FromScalar(obj, PyArray_DescrFromType(NPY_CDOUBLE));
+        }
+        if (arr == NULL) {
+            return 0;
+        }
+        (*v).r = npy_creal(*(((npy_cdouble *)PyArray_DATA(arr))));
+        (*v).i = npy_cimag(*(((npy_cdouble *)PyArray_DATA(arr))));
+        Py_DECREF(arr);
+        return 1;
+    }
+    /* Python does not provide PyNumber_Complex function :-( */
+    (*v).i = 0.0;
+    if (PyFloat_Check(obj)) {
+        (*v).r = PyFloat_AsDouble(obj);
+        return !((*v).r == -1.0 && PyErr_Occurred());
+    }
+    if (PyLong_Check(obj)) {
+        (*v).r = PyLong_AsDouble(obj);
+        return !((*v).r == -1.0 && PyErr_Occurred());
+    }
+    if (PySequence_Check(obj) && !(PyBytes_Check(obj) || PyUnicode_Check(obj))) {
+        PyObject *tmp = PySequence_GetItem(obj,0);
+        if (tmp) {
+            if (complex_double_from_pyobj(v,tmp,errmess)) {
+                Py_DECREF(tmp);
+                return 1;
+            }
+            Py_DECREF(tmp);
+        }
+    }
+    {
+        PyObject* err = PyErr_Occurred();
+        if (err==NULL)
+            err = PyExc_TypeError;
+        PyErr_SetString(err,errmess);
+    }
+    return 0;
+}
+"""
+
+
+needs['complex_float_from_pyobj'] = [
+    'complex_float', 'complex_double_from_pyobj']
+cfuncs['complex_float_from_pyobj'] = """
+static int
+complex_float_from_pyobj(complex_float* v,PyObject *obj,const char *errmess)
+{
+    complex_double cd={0.0,0.0};
+    if (complex_double_from_pyobj(&cd,obj,errmess)) {
+        (*v).r = (float)cd.r;
+        (*v).i = (float)cd.i;
+        return 1;
+    }
+    return 0;
+}
+"""
+
+
+cfuncs['try_pyarr_from_character'] = """
+static int try_pyarr_from_character(PyObject* obj, character* v) {
+    PyArrayObject *arr = (PyArrayObject*)obj;
+    if (!obj) return -2;
+    if (PyArray_Check(obj)) {
+        if (F2PY_ARRAY_IS_CHARACTER_COMPATIBLE(arr))  {
+            *(character *)(PyArray_DATA(arr)) = *v;
+            return 1;
+        }
+    }
+    {
+        char mess[F2PY_MESSAGE_BUFFER_SIZE];
+        PyObject* err = PyErr_Occurred();
+        if (err == NULL) {
+            err = PyExc_ValueError;
+            strcpy(mess, "try_pyarr_from_character failed"
+                         " -- expected bytes array-scalar|array, got ");
+            f2py_describe(obj, mess + strlen(mess));
+            PyErr_SetString(err, mess);
+        }
+    }
+    return 0;
+}
+"""
+
+needs['try_pyarr_from_char'] = ['pyobj_from_char1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_char'] = 'static int try_pyarr_from_char(PyObject* obj,char* v) {\n    TRYPYARRAYTEMPLATE(char,\'c\');\n}\n'
+needs['try_pyarr_from_signed_char'] = ['TRYPYARRAYTEMPLATE', 'unsigned_char']
+cfuncs[
+    'try_pyarr_from_unsigned_char'] = 'static int try_pyarr_from_unsigned_char(PyObject* obj,unsigned_char* v) {\n    TRYPYARRAYTEMPLATE(unsigned_char,\'b\');\n}\n'
+needs['try_pyarr_from_signed_char'] = ['TRYPYARRAYTEMPLATE', 'signed_char']
+cfuncs[
+    'try_pyarr_from_signed_char'] = 'static int try_pyarr_from_signed_char(PyObject* obj,signed_char* v) {\n    TRYPYARRAYTEMPLATE(signed_char,\'1\');\n}\n'
+needs['try_pyarr_from_short'] = ['pyobj_from_short1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_short'] = 'static int try_pyarr_from_short(PyObject* obj,short* v) {\n    TRYPYARRAYTEMPLATE(short,\'s\');\n}\n'
+needs['try_pyarr_from_int'] = ['pyobj_from_int1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_int'] = 'static int try_pyarr_from_int(PyObject* obj,int* v) {\n    TRYPYARRAYTEMPLATE(int,\'i\');\n}\n'
+needs['try_pyarr_from_long'] = ['pyobj_from_long1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_long'] = 'static int try_pyarr_from_long(PyObject* obj,long* v) {\n    TRYPYARRAYTEMPLATE(long,\'l\');\n}\n'
+needs['try_pyarr_from_long_long'] = [
+    'pyobj_from_long_long1', 'TRYPYARRAYTEMPLATE', 'long_long']
+cfuncs[
+    'try_pyarr_from_long_long'] = 'static int try_pyarr_from_long_long(PyObject* obj,long_long* v) {\n    TRYPYARRAYTEMPLATE(long_long,\'L\');\n}\n'
+needs['try_pyarr_from_float'] = ['pyobj_from_float1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_float'] = 'static int try_pyarr_from_float(PyObject* obj,float* v) {\n    TRYPYARRAYTEMPLATE(float,\'f\');\n}\n'
+needs['try_pyarr_from_double'] = ['pyobj_from_double1', 'TRYPYARRAYTEMPLATE']
+cfuncs[
+    'try_pyarr_from_double'] = 'static int try_pyarr_from_double(PyObject* obj,double* v) {\n    TRYPYARRAYTEMPLATE(double,\'d\');\n}\n'
+needs['try_pyarr_from_complex_float'] = [
+    'pyobj_from_complex_float1', 'TRYCOMPLEXPYARRAYTEMPLATE', 'complex_float']
+cfuncs[
+    'try_pyarr_from_complex_float'] = 'static int try_pyarr_from_complex_float(PyObject* obj,complex_float* v) {\n    TRYCOMPLEXPYARRAYTEMPLATE(float,\'F\');\n}\n'
+needs['try_pyarr_from_complex_double'] = [
+    'pyobj_from_complex_double1', 'TRYCOMPLEXPYARRAYTEMPLATE', 'complex_double']
+cfuncs[
+    'try_pyarr_from_complex_double'] = 'static int try_pyarr_from_complex_double(PyObject* obj,complex_double* v) {\n    TRYCOMPLEXPYARRAYTEMPLATE(double,\'D\');\n}\n'
+
+
+needs['create_cb_arglist'] = ['CFUNCSMESS', 'PRINTPYOBJERR', 'MINMAX']
+# create the list of arguments to be used when calling back to python
+cfuncs['create_cb_arglist'] = """
+static int
+create_cb_arglist(PyObject* fun, PyTupleObject* xa , const int maxnofargs,
+                  const int nofoptargs, int *nofargs, PyTupleObject **args,
+                  const char *errmess)
+{
+    PyObject *tmp = NULL;
+    PyObject *tmp_fun = NULL;
+    Py_ssize_t tot, opt, ext, siz, i, di = 0;
+    CFUNCSMESS(\"create_cb_arglist\\n\");
+    tot=opt=ext=siz=0;
+    /* Get the total number of arguments */
+    if (PyFunction_Check(fun)) {
+        tmp_fun = fun;
+        Py_INCREF(tmp_fun);
+    }
+    else {
+        di = 1;
+        if (PyObject_HasAttrString(fun,\"im_func\")) {
+            tmp_fun = PyObject_GetAttrString(fun,\"im_func\");
+        }
+        else if (PyObject_HasAttrString(fun,\"__call__\")) {
+            tmp = PyObject_GetAttrString(fun,\"__call__\");
+            if (PyObject_HasAttrString(tmp,\"im_func\"))
+                tmp_fun = PyObject_GetAttrString(tmp,\"im_func\");
+            else {
+                tmp_fun = fun; /* built-in function */
+                Py_INCREF(tmp_fun);
+                tot = maxnofargs;
+                if (PyCFunction_Check(fun)) {
+                    /* In case the function has a co_argcount (like on PyPy) */
+                    di = 0;
+                }
+                if (xa != NULL)
+                    tot += PyTuple_Size((PyObject *)xa);
+            }
+            Py_XDECREF(tmp);
+        }
+        else if (PyFortran_Check(fun) || PyFortran_Check1(fun)) {
+            tot = maxnofargs;
+            if (xa != NULL)
+                tot += PyTuple_Size((PyObject *)xa);
+            tmp_fun = fun;
+            Py_INCREF(tmp_fun);
+        }
+        else if (F2PyCapsule_Check(fun)) {
+            tot = maxnofargs;
+            if (xa != NULL)
+                ext = PyTuple_Size((PyObject *)xa);
+            if(ext>0) {
+                fprintf(stderr,\"extra arguments tuple cannot be used with PyCapsule call-back\\n\");
+                goto capi_fail;
+            }
+            tmp_fun = fun;
+            Py_INCREF(tmp_fun);
+        }
+    }
+
+    if (tmp_fun == NULL) {
+        fprintf(stderr,
+                \"Call-back argument must be function|instance|instance.__call__|f2py-function \"
+                \"but got %s.\\n\",
+                ((fun == NULL) ? \"NULL\" : Py_TYPE(fun)->tp_name));
+        goto capi_fail;
+    }
+
+    if (PyObject_HasAttrString(tmp_fun,\"__code__\")) {
+        if (PyObject_HasAttrString(tmp = PyObject_GetAttrString(tmp_fun,\"__code__\"),\"co_argcount\")) {
+            PyObject *tmp_argcount = PyObject_GetAttrString(tmp,\"co_argcount\");
+            Py_DECREF(tmp);
+            if (tmp_argcount == NULL) {
+                goto capi_fail;
+            }
+            tot = PyLong_AsSsize_t(tmp_argcount) - di;
+            Py_DECREF(tmp_argcount);
+        }
+    }
+    /* Get the number of optional arguments */
+    if (PyObject_HasAttrString(tmp_fun,\"__defaults__\")) {
+        if (PyTuple_Check(tmp = PyObject_GetAttrString(tmp_fun,\"__defaults__\")))
+            opt = PyTuple_Size(tmp);
+        Py_XDECREF(tmp);
+    }
+    /* Get the number of extra arguments */
+    if (xa != NULL)
+        ext = PyTuple_Size((PyObject *)xa);
+    /* Calculate the size of call-backs argument list */
+    siz = MIN(maxnofargs+ext,tot);
+    *nofargs = MAX(0,siz-ext);
+
+#ifdef DEBUGCFUNCS
+    fprintf(stderr,
+            \"debug-capi:create_cb_arglist:maxnofargs(-nofoptargs),\"
+            \"tot,opt,ext,siz,nofargs = %d(-%d), %zd, %zd, %zd, %zd, %d\\n\",
+            maxnofargs, nofoptargs, tot, opt, ext, siz, *nofargs);
+#endif
+
+    if (siz < tot-opt) {
+        fprintf(stderr,
+                \"create_cb_arglist: Failed to build argument list \"
+                \"(siz) with enough arguments (tot-opt) required by \"
+                \"user-supplied function (siz,tot,opt=%zd, %zd, %zd).\\n\",
+                siz, tot, opt);
+        goto capi_fail;
+    }
+
+    /* Initialize argument list */
+    *args = (PyTupleObject *)PyTuple_New(siz);
+    for (i=0;i<*nofargs;i++) {
+        Py_INCREF(Py_None);
+        PyTuple_SET_ITEM((PyObject *)(*args),i,Py_None);
+    }
+    if (xa != NULL)
+        for (i=(*nofargs);i<siz;i++) {
+            tmp = PyTuple_GetItem((PyObject *)xa,i-(*nofargs));
+            Py_INCREF(tmp);
+            PyTuple_SET_ITEM(*args,i,tmp);
+        }
+    CFUNCSMESS(\"create_cb_arglist-end\\n\");
+    Py_DECREF(tmp_fun);
+    return 1;
+
+capi_fail:
+    if (PyErr_Occurred() == NULL)
+        PyErr_SetString(#modulename#_error, errmess);
+    Py_XDECREF(tmp_fun);
+    return 0;
+}
+"""
+
+
+def buildcfuncs():
+    from .capi_maps import c2capi_map
+    for k in c2capi_map.keys():
+        m = f'pyarr_from_p_{k}1'
+        cppmacros[
+            m] = f'#define {m}(v) (PyArray_SimpleNewFromData(0,NULL,{c2capi_map[k]},(char *)v))'
+    k = 'string'
+    m = f'pyarr_from_p_{k}1'
+    # NPY_CHAR compatibility, NPY_STRING with itemsize 1
+    cppmacros[
+        m] = f'#define {m}(v,dims) (PyArray_New(&PyArray_Type, 1, dims, NPY_STRING, NULL, v, 1, NPY_ARRAY_CARRAY, NULL))'
+
+
+############ Auxiliary functions for sorting needs ###################
+
+def append_needs(need, flag=1):
+    # This function modifies the contents of the global `outneeds` dict.
+    if isinstance(need, list):
+        for n in need:
+            append_needs(n, flag)
+    elif isinstance(need, str):
+        if not need:
+            return
+        if need in includes0:
+            n = 'includes0'
+        elif need in includes:
+            n = 'includes'
+        elif need in typedefs:
+            n = 'typedefs'
+        elif need in typedefs_generated:
+            n = 'typedefs_generated'
+        elif need in cppmacros:
+            n = 'cppmacros'
+        elif need in cfuncs:
+            n = 'cfuncs'
+        elif need in callbacks:
+            n = 'callbacks'
+        elif need in f90modhooks:
+            n = 'f90modhooks'
+        elif need in commonhooks:
+            n = 'commonhooks'
+        else:
+            errmess(f'append_needs: unknown need {repr(need)}\n')
+            return
+        if need in outneeds[n]:
+            return
+        if flag:
+            tmp = {}
+            if need in needs:
+                for nn in needs[need]:
+                    t = append_needs(nn, 0)
+                    if isinstance(t, dict):
+                        for nnn in t.keys():
+                            if nnn in tmp:
+                                tmp[nnn] = tmp[nnn] + t[nnn]
+                            else:
+                                tmp[nnn] = t[nnn]
+            for nn in tmp.keys():
+                for nnn in tmp[nn]:
+                    if nnn not in outneeds[nn]:
+                        outneeds[nn] = [nnn] + outneeds[nn]
+            outneeds[n].append(need)
+        else:
+            tmp = {}
+            if need in needs:
+                for nn in needs[need]:
+                    t = append_needs(nn, flag)
+                    if isinstance(t, dict):
+                        for nnn in t.keys():
+                            if nnn in tmp:
+                                tmp[nnn] = t[nnn] + tmp[nnn]
+                            else:
+                                tmp[nnn] = t[nnn]
+            if n not in tmp:
+                tmp[n] = []
+            tmp[n].append(need)
+            return tmp
+    else:
+        errmess(f'append_needs: expected list or string but got :{repr(need)}\n')
+
+
+def get_needs():
+    # This function modifies the contents of the global `outneeds` dict.
+    res = {}
+    for n in outneeds.keys():
+        out = []
+        saveout = copy.copy(outneeds[n])
+        while len(outneeds[n]) > 0:
+            if outneeds[n][0] not in needs:
+                out.append(outneeds[n][0])
+                del outneeds[n][0]
+            else:
+                flag = 0
+                for k in outneeds[n][1:]:
+                    if k in needs[outneeds[n][0]]:
+                        flag = 1
+                        break
+                if flag:
+                    outneeds[n] = outneeds[n][1:] + [outneeds[n][0]]
+                else:
+                    out.append(outneeds[n][0])
+                    del outneeds[n][0]
+            if saveout and (0 not in map(lambda x, y: x == y, saveout, outneeds[n])) \
+                    and outneeds[n] != []:
+                print(n, saveout)
+                errmess(
+                    'get_needs: no progress in sorting needs, probably circular dependence, skipping.\n')
+                out = out + saveout
+                break
+            saveout = copy.copy(outneeds[n])
+        if out == []:
+            out = [n]
+        res[n] = out
+    return res
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..aad89073c656139d71ae2f4322081f14e2501cb4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/cfuncs.pyi
@@ -0,0 +1,31 @@
+from typing import Final, TypeAlias
+
+from .__version__ import version
+
+###
+
+_NeedListDict: TypeAlias = dict[str, list[str]]
+_NeedDict: TypeAlias = dict[str, str]
+
+###
+
+f2py_version: Final = version
+
+outneeds: Final[_NeedListDict] = ...
+needs: Final[_NeedListDict] = ...
+
+includes0: Final[_NeedDict] = ...
+includes: Final[_NeedDict] = ...
+userincludes: Final[_NeedDict] = ...
+typedefs: Final[_NeedDict] = ...
+typedefs_generated: Final[_NeedDict] = ...
+cppmacros: Final[_NeedDict] = ...
+cfuncs: Final[_NeedDict] = ...
+callbacks: Final[_NeedDict] = ...
+f90modhooks: Final[_NeedDict] = ...
+commonhooks: Final[_NeedDict] = ...
+
+def errmess(s: str) -> None: ...
+def buildcfuncs() -> None: ...
+def get_needs() -> _NeedListDict: ...
+def append_needs(need: str | list[str], flag: int = 1) -> _NeedListDict: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.py b/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.py
new file mode 100644
index 0000000000000000000000000000000000000000..206928e9a02cc5c9204bd8ba858fd224173dde07
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.py
@@ -0,0 +1,143 @@
+"""
+Build common block mechanism for f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+from . import __version__
+
+f2py_version = __version__.version
+
+from . import capi_maps, func2subr
+from .auxfuncs import getuseblocks, hasbody, hascommon, hasnote, isintent_hide, outmess
+from .crackfortran import rmbadname
+
+
+def findcommonblocks(block, top=1):
+    ret = []
+    if hascommon(block):
+        for key, value in block['common'].items():
+            vars_ = {v: block['vars'][v] for v in value}
+            ret.append((key, value, vars_))
+    elif hasbody(block):
+        for b in block['body']:
+            ret = ret + findcommonblocks(b, 0)
+    if top:
+        tret = []
+        names = []
+        for t in ret:
+            if t[0] not in names:
+                names.append(t[0])
+                tret.append(t)
+        return tret
+    return ret
+
+
+def buildhooks(m):
+    ret = {'commonhooks': [], 'initcommonhooks': [],
+           'docs': ['"COMMON blocks:\\n"']}
+    fwrap = ['']
+
+    def fadd(line, s=fwrap):
+        s[0] = f'{s[0]}\n      {line}'
+    chooks = ['']
+
+    def cadd(line, s=chooks):
+        s[0] = f'{s[0]}\n{line}'
+    ihooks = ['']
+
+    def iadd(line, s=ihooks):
+        s[0] = f'{s[0]}\n{line}'
+    doc = ['']
+
+    def dadd(line, s=doc):
+        s[0] = f'{s[0]}\n{line}'
+    for (name, vnames, vars) in findcommonblocks(m):
+        lower_name = name.lower()
+        hnames, inames = [], []
+        for n in vnames:
+            if isintent_hide(vars[n]):
+                hnames.append(n)
+            else:
+                inames.append(n)
+        if hnames:
+            outmess('\t\tConstructing COMMON block support for "%s"...\n\t\t  %s\n\t\t  Hidden: %s\n' % (
+                name, ','.join(inames), ','.join(hnames)))
+        else:
+            outmess('\t\tConstructing COMMON block support for "%s"...\n\t\t  %s\n' % (
+                name, ','.join(inames)))
+        fadd(f'subroutine f2pyinit{name}(setupfunc)')
+        for usename in getuseblocks(m):
+            fadd(f'use {usename}')
+        fadd('external setupfunc')
+        for n in vnames:
+            fadd(func2subr.var2fixfortran(vars, n))
+        if name == '_BLNK_':
+            fadd(f"common {','.join(vnames)}")
+        else:
+            fadd(f"common /{name}/ {','.join(vnames)}")
+        fadd(f"call setupfunc({','.join(inames)})")
+        fadd('end\n')
+        cadd('static FortranDataDef f2py_%s_def[] = {' % (name))
+        idims = []
+        for n in inames:
+            ct = capi_maps.getctype(vars[n])
+            elsize = capi_maps.get_elsize(vars[n])
+            at = capi_maps.c2capi_map[ct]
+            dm = capi_maps.getarrdims(n, vars[n])
+            if dm['dims']:
+                idims.append(f"({dm['dims']})")
+            else:
+                idims.append('')
+            dms = dm['dims'].strip()
+            if not dms:
+                dms = '-1'
+            cadd('\t{\"%s\",%s,{{%s}},%s, %s},'
+                 % (n, dm['rank'], dms, at, elsize))
+        cadd('\t{NULL}\n};')
+        inames1 = rmbadname(inames)
+        inames1_tps = ','.join(['char *' + s for s in inames1])
+        cadd('static void f2py_setup_%s(%s) {' % (name, inames1_tps))
+        cadd('\tint i_f2py=0;')
+        for n in inames1:
+            cadd(f'\tf2py_{name}_def[i_f2py++].data = {n};')
+        cadd('}')
+        if '_' in lower_name:
+            F_FUNC = 'F_FUNC_US'
+        else:
+            F_FUNC = 'F_FUNC'
+        cadd('extern void %s(f2pyinit%s,F2PYINIT%s)(void(*)(%s));'
+             % (F_FUNC, lower_name, name.upper(),
+                ','.join(['char*'] * len(inames1))))
+        cadd('static void f2py_init_%s(void) {' % name)
+        cadd('\t%s(f2pyinit%s,F2PYINIT%s)(f2py_setup_%s);'
+             % (F_FUNC, lower_name, name.upper(), name))
+        cadd('}\n')
+        iadd(f'\ttmp = PyFortranObject_New(f2py_{name}_def,f2py_init_{name});')
+        iadd('\tif (tmp == NULL) return NULL;')
+        iadd(f'\tif (F2PyDict_SetItemString(d, "{name}", tmp) == -1) return NULL;')
+        iadd('\tPy_DECREF(tmp);')
+        tname = name.replace('_', '\\_')
+        dadd('\\subsection{Common block \\texttt{%s}}\n' % (tname))
+        dadd('\\begin{description}')
+        for n in inames:
+            dadd('\\item[]{{}\\verb@%s@{}}' %
+                 (capi_maps.getarrdocsign(n, vars[n])))
+            if hasnote(vars[n]):
+                note = vars[n]['note']
+                if isinstance(note, list):
+                    note = '\n'.join(note)
+                dadd(f'--- {note}')
+        dadd('\\end{description}')
+        ret['docs'].append(
+            f"\"\t/{name}/ {','.join(map(lambda v, d: v + d, inames, idims))}\\n\"")
+    ret['commonhooks'] = chooks
+    ret['initcommonhooks'] = ihooks
+    ret['latexdoc'] = doc[0]
+    if len(ret['docs']) <= 1:
+        ret['docs'] = ''
+    return ret, fwrap[0]
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..58fec3159753e292a9e18585c643f3416426060f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/common_rules.pyi
@@ -0,0 +1,9 @@
+from collections.abc import Mapping
+from typing import Any, Final
+
+from .__version__ import version
+
+f2py_version: Final = version
+
+def findcommonblocks(block: Mapping[str, object], top: int = 1) -> list[tuple[str, list[str], dict[str, Any]]]: ...
+def buildhooks(m: Mapping[str, object]) -> tuple[dict[str, Any], str]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.py b/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.py
new file mode 100644
index 0000000000000000000000000000000000000000..8befbded4b94b6b156638fce197554471345a747
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.py
@@ -0,0 +1,3725 @@
+"""
+crackfortran --- read fortran (77,90) code and extract declaration information.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+
+
+Usage of crackfortran:
+======================
+Command line keys: -quiet,-verbose,-fix,-f77,-f90,-show,-h <pyffilename>
+                   -m <module name for f77 routines>,--ignore-contains
+Functions: crackfortran, crack2fortran
+The following Fortran statements/constructions are supported
+(or will be if needed):
+   block data,byte,call,character,common,complex,contains,data,
+   dimension,double complex,double precision,end,external,function,
+   implicit,integer,intent,interface,intrinsic,
+   logical,module,optional,parameter,private,public,
+   program,real,(sequence?),subroutine,type,use,virtual,
+   include,pythonmodule
+Note: 'virtual' is mapped to 'dimension'.
+Note: 'implicit integer (z) static (z)' is 'implicit static (z)' (this is minor bug).
+Note: code after 'contains' will be ignored until its scope ends.
+Note: 'common' statement is extended: dimensions are moved to variable definitions
+Note: f2py directive: <commentchar>f2py<line> is read as <line>
+Note: pythonmodule is introduced to represent Python module
+
+Usage:
+  `postlist=crackfortran(files)`
+  `postlist` contains declaration information read from the list of files `files`.
+  `crack2fortran(postlist)` returns a fortran code to be saved to pyf-file
+
+  `postlist` has the following structure:
+ *** it is a list of dictionaries containing `blocks':
+     B = {'block','body','vars','parent_block'[,'name','prefix','args','result',
+          'implicit','externals','interfaced','common','sortvars',
+          'commonvars','note']}
+     B['block'] = 'interface' | 'function' | 'subroutine' | 'module' |
+                  'program' | 'block data' | 'type' | 'pythonmodule' |
+                  'abstract interface'
+     B['body'] --- list containing `subblocks' with the same structure as `blocks'
+     B['parent_block'] --- dictionary of a parent block:
+                             C['body'][<index>]['parent_block'] is C
+     B['vars'] --- dictionary of variable definitions
+     B['sortvars'] --- dictionary of variable definitions sorted by dependence (independent first)
+     B['name'] --- name of the block (not if B['block']=='interface')
+     B['prefix'] --- prefix string (only if B['block']=='function')
+     B['args'] --- list of argument names if B['block']== 'function' | 'subroutine'
+     B['result'] --- name of the return value (only if B['block']=='function')
+     B['implicit'] --- dictionary {'a':<variable definition>,'b':...} | None
+     B['externals'] --- list of variables being external
+     B['interfaced'] --- list of variables being external and defined
+     B['common'] --- dictionary of common blocks (list of objects)
+     B['commonvars'] --- list of variables used in common blocks (dimensions are moved to variable definitions)
+     B['from'] --- string showing the 'parents' of the current block
+     B['use'] --- dictionary of modules used in current block:
+         {<modulename>:{['only':<0|1>],['map':{<local_name1>:<use_name1>,...}]}}
+     B['note'] --- list of LaTeX comments on the block
+     B['f2pyenhancements'] --- optional dictionary
+          {'threadsafe':'','fortranname':<name>,
+           'callstatement':<C-expr>|<multi-line block>,
+           'callprotoargument':<C-expr-list>,
+           'usercode':<multi-line block>|<list of multi-line blocks>,
+           'pymethoddef:<multi-line block>'
+           }
+     B['entry'] --- dictionary {entryname:argslist,..}
+     B['varnames'] --- list of variable names given in the order of reading the
+                       Fortran code, useful for derived types.
+     B['saved_interface'] --- a string of scanned routine signature, defines explicit interface
+ *** Variable definition is a dictionary
+     D = B['vars'][<variable name>] =
+     {'typespec'[,'attrspec','kindselector','charselector','=','typename']}
+     D['typespec'] = 'byte' | 'character' | 'complex' | 'double complex' |
+                     'double precision' | 'integer' | 'logical' | 'real' | 'type'
+     D['attrspec'] --- list of attributes (e.g. 'dimension(<arrayspec>)',
+                       'external','intent(in|out|inout|hide|c|callback|cache|aligned4|aligned8|aligned16)',
+                       'optional','required', etc)
+     K = D['kindselector'] = {['*','kind']} (only if D['typespec'] =
+                         'complex' | 'integer' | 'logical' | 'real' )
+     C = D['charselector'] = {['*','len','kind','f2py_len']}
+                             (only if D['typespec']=='character')
+     D['='] --- initialization expression string
+     D['typename'] --- name of the type if D['typespec']=='type'
+     D['dimension'] --- list of dimension bounds
+     D['intent'] --- list of intent specifications
+     D['depend'] --- list of variable names on which current variable depends on
+     D['check'] --- list of C-expressions; if C-expr returns zero, exception is raised
+     D['note'] --- list of LaTeX comments on the variable
+ *** Meaning of kind/char selectors (few examples):
+     D['typespec>']*K['*']
+     D['typespec'](kind=K['kind'])
+     character*C['*']
+     character(len=C['len'],kind=C['kind'], f2py_len=C['f2py_len'])
+     (see also fortran type declaration statement formats below)
+
+Fortran 90 type declaration statement format (F77 is subset of F90)
+====================================================================
+(Main source: IBM XL Fortran 5.1 Language Reference Manual)
+type declaration = <typespec> [[<attrspec>]::] <entitydecl>
+<typespec> = byte                          |
+             character[<charselector>]     |
+             complex[<kindselector>]       |
+             double complex                |
+             double precision              |
+             integer[<kindselector>]       |
+             logical[<kindselector>]       |
+             real[<kindselector>]          |
+             type(<typename>)
+<charselector> = * <charlen>               |
+             ([len=]<len>[,[kind=]<kind>]) |
+             (kind=<kind>[,len=<len>])
+<kindselector> = * <intlen>                |
+             ([kind=]<kind>)
+<attrspec> = comma separated list of attributes.
+             Only the following attributes are used in
+             building up the interface:
+                external
+                (parameter --- affects '=' key)
+                optional
+                intent
+             Other attributes are ignored.
+<intentspec> = in | out | inout
+<arrayspec> = comma separated list of dimension bounds.
+<entitydecl> = <name> [[*<charlen>][(<arrayspec>)] | [(<arrayspec>)]*<charlen>]
+                      [/<init_expr>/ | =<init_expr>] [,<entitydecl>]
+
+In addition, the following attributes are used: check,depend,note
+
+TODO:
+    * Apply 'parameter' attribute (e.g. 'integer parameter :: i=2' 'real x(i)'
+                                   -> 'real x(2)')
+    The above may be solved by creating appropriate preprocessor program, for example.
+
+"""
+import codecs
+import copy
+import fileinput
+import os
+import platform
+import re
+import string
+import sys
+from pathlib import Path
+
+try:
+    import charset_normalizer
+except ImportError:
+    charset_normalizer = None
+
+from . import __version__, symbolic
+
+# The environment provided by auxfuncs.py is needed for some calls to eval.
+# As the needed functions cannot be determined by static inspection of the
+# code, it is safest to use import * pending a major refactoring of f2py.
+from .auxfuncs import *
+
+f2py_version = __version__.version
+
+# Global flags:
+strictf77 = 1          # Ignore `!' comments unless line[0]=='!'
+sourcecodeform = 'fix'  # 'fix','free'
+quiet = 0              # Be verbose if 0 (Obsolete: not used any more)
+verbose = 1            # Be quiet if 0, extra verbose if > 1.
+tabchar = 4 * ' '
+pyffilename = ''
+f77modulename = ''
+skipemptyends = 0      # for old F77 programs without 'program' statement
+ignorecontains = 1
+dolowercase = 1
+debug = []
+
+# Global variables
+beginpattern = ''
+currentfilename = ''
+expectbegin = 1
+f90modulevars = {}
+filepositiontext = ''
+gotnextfile = 1
+groupcache = None
+groupcounter = 0
+grouplist = {groupcounter: []}
+groupname = ''
+include_paths = []
+neededmodule = -1
+onlyfuncs = []
+previous_context = None
+skipblocksuntil = -1
+skipfuncs = []
+skipfunctions = []
+usermodules = []
+
+
+def reset_global_f2py_vars():
+    global groupcounter, grouplist, neededmodule, expectbegin
+    global skipblocksuntil, usermodules, f90modulevars, gotnextfile
+    global filepositiontext, currentfilename, skipfunctions, skipfuncs
+    global onlyfuncs, include_paths, previous_context
+    global strictf77, sourcecodeform, quiet, verbose, tabchar, pyffilename
+    global f77modulename, skipemptyends, ignorecontains, dolowercase, debug
+
+    # flags
+    strictf77 = 1
+    sourcecodeform = 'fix'
+    quiet = 0
+    verbose = 1
+    tabchar = 4 * ' '
+    pyffilename = ''
+    f77modulename = ''
+    skipemptyends = 0
+    ignorecontains = 1
+    dolowercase = 1
+    debug = []
+    # variables
+    groupcounter = 0
+    grouplist = {groupcounter: []}
+    neededmodule = -1
+    expectbegin = 1
+    skipblocksuntil = -1
+    usermodules = []
+    f90modulevars = {}
+    gotnextfile = 1
+    filepositiontext = ''
+    currentfilename = ''
+    skipfunctions = []
+    skipfuncs = []
+    onlyfuncs = []
+    include_paths = []
+    previous_context = None
+
+
+def outmess(line, flag=1):
+    global filepositiontext
+
+    if not verbose:
+        return
+    if not quiet:
+        if flag:
+            sys.stdout.write(filepositiontext)
+        sys.stdout.write(line)
+
+
+re._MAXCACHE = 50
+defaultimplicitrules = {}
+for c in "abcdefghopqrstuvwxyz$_":
+    defaultimplicitrules[c] = {'typespec': 'real'}
+for c in "ijklmn":
+    defaultimplicitrules[c] = {'typespec': 'integer'}
+badnames = {}
+invbadnames = {}
+for n in ['int', 'double', 'float', 'char', 'short', 'long', 'void', 'case', 'while',
+          'return', 'signed', 'unsigned', 'if', 'for', 'typedef', 'sizeof', 'union',
+          'struct', 'static', 'register', 'new', 'break', 'do', 'goto', 'switch',
+          'continue', 'else', 'inline', 'extern', 'delete', 'const', 'auto',
+          'len', 'rank', 'shape', 'index', 'slen', 'size', '_i',
+          'max', 'min',
+          'flen', 'fshape',
+          'string', 'complex_double', 'float_double', 'stdin', 'stderr', 'stdout',
+          'type', 'default']:
+    badnames[n] = n + '_bn'
+    invbadnames[n + '_bn'] = n
+
+
+def rmbadname1(name):
+    if name in badnames:
+        errmess(f'rmbadname1: Replacing "{name}" with "{badnames[name]}".\n')
+        return badnames[name]
+    return name
+
+
+def rmbadname(names):
+    return [rmbadname1(_m) for _m in names]
+
+
+def undo_rmbadname1(name):
+    if name in invbadnames:
+        errmess(f'undo_rmbadname1: Replacing "{name}" with "{invbadnames[name]}".\n')
+        return invbadnames[name]
+    return name
+
+
+def undo_rmbadname(names):
+    return [undo_rmbadname1(_m) for _m in names]
+
+
+_has_f_header = re.compile(r'-\*-\s*fortran\s*-\*-', re.I).search
+_has_f90_header = re.compile(r'-\*-\s*f90\s*-\*-', re.I).search
+_has_fix_header = re.compile(r'-\*-\s*fix\s*-\*-', re.I).search
+_free_f90_start = re.compile(r'[^c*]\s*[^\s\d\t]', re.I).match
+
+# Extensions
+COMMON_FREE_EXTENSIONS = ['.f90', '.f95', '.f03', '.f08']
+COMMON_FIXED_EXTENSIONS = ['.for', '.ftn', '.f77', '.f']
+
+
+def openhook(filename, mode):
+    """Ensures that filename is opened with correct encoding parameter.
+
+    This function uses charset_normalizer package, when available, for
+    determining the encoding of the file to be opened. When charset_normalizer
+    is not available, the function detects only UTF encodings, otherwise, ASCII
+    encoding is used as fallback.
+    """
+    # Reads in the entire file. Robust detection of encoding.
+    # Correctly handles comments or late stage unicode characters
+    # gh-22871
+    if charset_normalizer is not None:
+        encoding = charset_normalizer.from_path(filename).best().encoding
+    else:
+        # hint: install charset_normalizer for correct encoding handling
+        # No need to read the whole file for trying with startswith
+        nbytes = min(32, os.path.getsize(filename))
+        with open(filename, 'rb') as fhandle:
+            raw = fhandle.read(nbytes)
+            if raw.startswith(codecs.BOM_UTF8):
+                encoding = 'UTF-8-SIG'
+            elif raw.startswith((codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE)):
+                encoding = 'UTF-32'
+            elif raw.startswith((codecs.BOM_LE, codecs.BOM_BE)):
+                encoding = 'UTF-16'
+            else:
+                # Fallback, without charset_normalizer
+                encoding = 'ascii'
+    return open(filename, mode, encoding=encoding)
+
+
+def is_free_format(fname):
+    """Check if file is in free format Fortran."""
+    # f90 allows both fixed and free format, assuming fixed unless
+    # signs of free format are detected.
+    result = False
+    if Path(fname).suffix.lower() in COMMON_FREE_EXTENSIONS:
+        result = True
+    with openhook(fname, 'r') as fhandle:
+        line = fhandle.readline()
+        n = 15  # the number of non-comment lines to scan for hints
+        if _has_f_header(line):
+            n = 0
+        elif _has_f90_header(line):
+            n = 0
+            result = True
+        while n > 0 and line:
+            if line[0] != '!' and line.strip():
+                n -= 1
+                if (line[0] != '\t' and _free_f90_start(line[:5])) or line[-2:-1] == '&':
+                    result = True
+                    break
+            line = fhandle.readline()
+    return result
+
+
+# Read fortran (77,90) code
+def readfortrancode(ffile, dowithline=show, istop=1):
+    """
+    Read fortran codes from files and
+     1) Get rid of comments, line continuations, and empty lines; lower cases.
+     2) Call dowithline(line) on every line.
+     3) Recursively call itself when statement \"include '<filename>'\" is met.
+    """
+    global gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77
+    global beginpattern, quiet, verbose, dolowercase, include_paths
+
+    if not istop:
+        saveglobals = gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77,\
+            beginpattern, quiet, verbose, dolowercase
+    if ffile == []:
+        return
+    localdolowercase = dolowercase
+    # cont: set to True when the content of the last line read
+    # indicates statement continuation
+    cont = False
+    finalline = ''
+    ll = ''
+    includeline = re.compile(
+        r'\s*include\s*(\'|")(?P<name>[^\'"]*)(\'|")', re.I)
+    cont1 = re.compile(r'(?P<line>.*)&\s*\Z')
+    cont2 = re.compile(r'(\s*&|)(?P<line>.*)')
+    mline_mark = re.compile(r".*?'''")
+    if istop:
+        dowithline('', -1)
+    ll, l1 = '', ''
+    spacedigits = [' '] + [str(_m) for _m in range(10)]
+    filepositiontext = ''
+    fin = fileinput.FileInput(ffile, openhook=openhook)
+    while True:
+        try:
+            l = fin.readline()
+        except UnicodeDecodeError as msg:
+            raise Exception(
+                f'readfortrancode: reading {fin.filename()}#{fin.lineno()}'
+                f' failed with\n{msg}.\nIt is likely that installing charset_normalizer'
+                ' package will help f2py determine the input file encoding'
+                ' correctly.')
+        if not l:
+            break
+        if fin.isfirstline():
+            filepositiontext = ''
+            currentfilename = fin.filename()
+            gotnextfile = 1
+            l1 = l
+            strictf77 = 0
+            sourcecodeform = 'fix'
+            ext = os.path.splitext(currentfilename)[1]
+            if Path(currentfilename).suffix.lower() in COMMON_FIXED_EXTENSIONS and \
+                    not (_has_f90_header(l) or _has_fix_header(l)):
+                strictf77 = 1
+            elif is_free_format(currentfilename) and not _has_fix_header(l):
+                sourcecodeform = 'free'
+            if strictf77:
+                beginpattern = beginpattern77
+            else:
+                beginpattern = beginpattern90
+            outmess('\tReading file %s (format:%s%s)\n'
+                    % (repr(currentfilename), sourcecodeform,
+                       (strictf77 and ',strict') or ''))
+
+        l = l.expandtabs().replace('\xa0', ' ')
+        # Get rid of newline characters
+        while not l == '':
+            if l[-1] not in "\n\r\f":
+                break
+            l = l[:-1]
+        # Do not lower for directives, gh-2547, gh-27697, gh-26681
+        is_f2py_directive = False
+        # Unconditionally remove comments
+        (l, rl) = split_by_unquoted(l, '!')
+        l += ' '
+        if rl[:5].lower() == '!f2py':  # f2py directive
+            l, _ = split_by_unquoted(l + 4 * ' ' + rl[5:], '!')
+            is_f2py_directive = True
+        if l.strip() == '':  # Skip empty line
+            if sourcecodeform == 'free':
+                # In free form, a statement continues in the next line
+                # that is not a comment line [3.3.2.4^1], lines with
+                # blanks are comment lines [3.3.2.3^1]. Hence, the
+                # line continuation flag must retain its state.
+                pass
+            else:
+                # In fixed form, statement continuation is determined
+                # by a non-blank character at the 6-th position. Empty
+                # line indicates a start of a new statement
+                # [3.3.3.3^1]. Hence, the line continuation flag must
+                # be reset.
+                cont = False
+            continue
+        if sourcecodeform == 'fix':
+            if l[0] in ['*', 'c', '!', 'C', '#']:
+                if l[1:5].lower() == 'f2py':  # f2py directive
+                    l = '     ' + l[5:]
+                    is_f2py_directive = True
+                else:  # Skip comment line
+                    cont = False
+                    is_f2py_directive = False
+                    continue
+            elif strictf77:
+                if len(l) > 72:
+                    l = l[:72]
+            if l[0] not in spacedigits:
+                raise Exception('readfortrancode: Found non-(space,digit) char '
+                                'in the first column.\n\tAre you sure that '
+                                'this code is in fix form?\n\tline=%s' % repr(l))
+
+            if (not cont or strictf77) and (len(l) > 5 and not l[5] == ' '):
+                # Continuation of a previous line
+                ll = ll + l[6:]
+                finalline = ''
+                origfinalline = ''
+            else:
+                r = cont1.match(l)
+                if r:
+                    l = r.group('line')  # Continuation follows ..
+                if cont:
+                    ll = ll + cont2.match(l).group('line')
+                    finalline = ''
+                    origfinalline = ''
+                else:
+                    # clean up line beginning from possible digits.
+                    l = '     ' + l[5:]
+                    # f2py directives are already stripped by this point
+                    if localdolowercase:
+                        finalline = ll.lower()
+                    else:
+                        finalline = ll
+                    origfinalline = ll
+                    ll = l
+
+        elif sourcecodeform == 'free':
+            if not cont and ext == '.pyf' and mline_mark.match(l):
+                l = l + '\n'
+                while True:
+                    lc = fin.readline()
+                    if not lc:
+                        errmess(
+                            'Unexpected end of file when reading multiline\n')
+                        break
+                    l = l + lc
+                    if mline_mark.match(lc):
+                        break
+                l = l.rstrip()
+            r = cont1.match(l)
+            if r:
+                l = r.group('line')  # Continuation follows ..
+            if cont:
+                ll = ll + cont2.match(l).group('line')
+                finalline = ''
+                origfinalline = ''
+            else:
+                if localdolowercase:
+                    # only skip lowering for C style constructs
+                    # gh-2547, gh-27697, gh-26681, gh-28014
+                    finalline = ll.lower() if not (is_f2py_directive and iscstyledirective(ll)) else ll
+                else:
+                    finalline = ll
+                origfinalline = ll
+                ll = l
+            cont = (r is not None)
+        else:
+            raise ValueError(
+                f"Flag sourcecodeform must be either 'fix' or 'free': {repr(sourcecodeform)}")
+        filepositiontext = 'Line #%d in %s:"%s"\n\t' % (
+            fin.filelineno() - 1, currentfilename, l1)
+        m = includeline.match(origfinalline)
+        if m:
+            fn = m.group('name')
+            if os.path.isfile(fn):
+                readfortrancode(fn, dowithline=dowithline, istop=0)
+            else:
+                include_dirs = [
+                    os.path.dirname(currentfilename)] + include_paths
+                foundfile = 0
+                for inc_dir in include_dirs:
+                    fn1 = os.path.join(inc_dir, fn)
+                    if os.path.isfile(fn1):
+                        foundfile = 1
+                        readfortrancode(fn1, dowithline=dowithline, istop=0)
+                        break
+                if not foundfile:
+                    outmess('readfortrancode: could not find include file %s in %s. Ignoring.\n' % (
+                        repr(fn), os.pathsep.join(include_dirs)))
+        else:
+            dowithline(finalline)
+        l1 = ll
+    # Last line should never have an f2py directive anyway
+    if localdolowercase:
+        finalline = ll.lower()
+    else:
+        finalline = ll
+    origfinalline = ll
+    filepositiontext = 'Line #%d in %s:"%s"\n\t' % (
+        fin.filelineno() - 1, currentfilename, l1)
+    m = includeline.match(origfinalline)
+    if m:
+        fn = m.group('name')
+        if os.path.isfile(fn):
+            readfortrancode(fn, dowithline=dowithline, istop=0)
+        else:
+            include_dirs = [os.path.dirname(currentfilename)] + include_paths
+            foundfile = 0
+            for inc_dir in include_dirs:
+                fn1 = os.path.join(inc_dir, fn)
+                if os.path.isfile(fn1):
+                    foundfile = 1
+                    readfortrancode(fn1, dowithline=dowithline, istop=0)
+                    break
+            if not foundfile:
+                outmess('readfortrancode: could not find include file %s in %s. Ignoring.\n' % (
+                    repr(fn), os.pathsep.join(include_dirs)))
+    else:
+        dowithline(finalline)
+    filepositiontext = ''
+    fin.close()
+    if istop:
+        dowithline('', 1)
+    else:
+        gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77,\
+            beginpattern, quiet, verbose, dolowercase = saveglobals
+
+
+# Crack line
+beforethisafter = r'\s*(?P<before>%s(?=\s*(\b(%s)\b)))'\
+    r'\s*(?P<this>(\b(%s)\b))'\
+    r'\s*(?P<after>%s)\s*\Z'
+##
+fortrantypes = r'character|logical|integer|real|complex|double\s*(precision\s*(complex|)|complex)|type(?=\s*\([\w\s,=(*)]*\))|byte'
+typespattern = re.compile(
+    beforethisafter % ('', fortrantypes, fortrantypes, '.*'), re.I), 'type'
+typespattern4implicit = re.compile(beforethisafter % (
+    '', fortrantypes + '|static|automatic|undefined', fortrantypes + '|static|automatic|undefined', '.*'), re.I)
+#
+functionpattern = re.compile(beforethisafter % (
+    r'([a-z]+[\w\s(=*+-/)]*?|)', 'function', 'function', '.*'), re.I), 'begin'
+subroutinepattern = re.compile(beforethisafter % (
+    r'[a-z\s]*?', 'subroutine', 'subroutine', '.*'), re.I), 'begin'
+# modulepattern=re.compile(beforethisafter%('[a-z\s]*?','module','module','.*'),re.I),'begin'
+#
+groupbegins77 = r'program|block\s*data'
+beginpattern77 = re.compile(
+    beforethisafter % ('', groupbegins77, groupbegins77, '.*'), re.I), 'begin'
+groupbegins90 = groupbegins77 + \
+    r'|module(?!\s*procedure)|python\s*module|(abstract|)\s*interface|'\
+    r'type(?!\s*\()'
+beginpattern90 = re.compile(
+    beforethisafter % ('', groupbegins90, groupbegins90, '.*'), re.I), 'begin'
+groupends = (r'end|endprogram|endblockdata|endmodule|endpythonmodule|'
+             r'endinterface|endsubroutine|endfunction')
+endpattern = re.compile(
+    beforethisafter % ('', groupends, groupends, '.*'), re.I), 'end'
+# block, the Fortran 2008 construct needs special handling in the rest of the file
+endifs = r'end\s*(if|do|where|select|while|forall|associate|'\
+         r'critical|enum|team)'
+endifpattern = re.compile(
+    beforethisafter % (r'[\w]*?', endifs, endifs, '.*'), re.I), 'endif'
+#
+moduleprocedures = r'module\s*procedure'
+moduleprocedurepattern = re.compile(
+    beforethisafter % ('', moduleprocedures, moduleprocedures, '.*'), re.I), \
+    'moduleprocedure'
+implicitpattern = re.compile(
+    beforethisafter % ('', 'implicit', 'implicit', '.*'), re.I), 'implicit'
+dimensionpattern = re.compile(beforethisafter % (
+    '', 'dimension|virtual', 'dimension|virtual', '.*'), re.I), 'dimension'
+externalpattern = re.compile(
+    beforethisafter % ('', 'external', 'external', '.*'), re.I), 'external'
+optionalpattern = re.compile(
+    beforethisafter % ('', 'optional', 'optional', '.*'), re.I), 'optional'
+requiredpattern = re.compile(
+    beforethisafter % ('', 'required', 'required', '.*'), re.I), 'required'
+publicpattern = re.compile(
+    beforethisafter % ('', 'public', 'public', '.*'), re.I), 'public'
+privatepattern = re.compile(
+    beforethisafter % ('', 'private', 'private', '.*'), re.I), 'private'
+intrinsicpattern = re.compile(
+    beforethisafter % ('', 'intrinsic', 'intrinsic', '.*'), re.I), 'intrinsic'
+intentpattern = re.compile(beforethisafter % (
+    '', 'intent|depend|note|check', 'intent|depend|note|check', r'\s*\(.*?\).*'), re.I), 'intent'
+parameterpattern = re.compile(
+    beforethisafter % ('', 'parameter', 'parameter', r'\s*\(.*'), re.I), 'parameter'
+datapattern = re.compile(
+    beforethisafter % ('', 'data', 'data', '.*'), re.I), 'data'
+callpattern = re.compile(
+    beforethisafter % ('', 'call', 'call', '.*'), re.I), 'call'
+entrypattern = re.compile(
+    beforethisafter % ('', 'entry', 'entry', '.*'), re.I), 'entry'
+callfunpattern = re.compile(
+    beforethisafter % ('', 'callfun', 'callfun', '.*'), re.I), 'callfun'
+commonpattern = re.compile(
+    beforethisafter % ('', 'common', 'common', '.*'), re.I), 'common'
+usepattern = re.compile(
+    beforethisafter % ('', 'use', 'use', '.*'), re.I), 'use'
+containspattern = re.compile(
+    beforethisafter % ('', 'contains', 'contains', ''), re.I), 'contains'
+formatpattern = re.compile(
+    beforethisafter % ('', 'format', 'format', '.*'), re.I), 'format'
+# Non-fortran and f2py-specific statements
+f2pyenhancementspattern = re.compile(beforethisafter % ('', 'threadsafe|fortranname|callstatement|callprotoargument|usercode|pymethoddef',
+                                                        'threadsafe|fortranname|callstatement|callprotoargument|usercode|pymethoddef', '.*'), re.I | re.S), 'f2pyenhancements'
+multilinepattern = re.compile(
+    r"\s*(?P<before>''')(?P<this>.*?)(?P<after>''')\s*\Z", re.S), 'multiline'
+##
+
+def split_by_unquoted(line, characters):
+    """
+    Splits the line into (line[:i], line[i:]),
+    where i is the index of first occurrence of one of the characters
+    not within quotes, or len(line) if no such index exists
+    """
+    assert not (set('"\'') & set(characters)), "cannot split by unquoted quotes"
+    r = re.compile(
+        r"\A(?P<before>({single_quoted}|{double_quoted}|{not_quoted})*)"
+        r"(?P<after>{char}.*)\Z".format(
+            not_quoted=f"[^\"'{re.escape(characters)}]",
+            char=f"[{re.escape(characters)}]",
+            single_quoted=r"('([^'\\]|(\\.))*')",
+            double_quoted=r'("([^"\\]|(\\.))*")'))
+    m = r.match(line)
+    if m:
+        d = m.groupdict()
+        return (d["before"], d["after"])
+    return (line, "")
+
+def _simplifyargs(argsline):
+    a = []
+    for n in markoutercomma(argsline).split('@,@'):
+        for r in '(),':
+            n = n.replace(r, '_')
+        a.append(n)
+    return ','.join(a)
+
+
+crackline_re_1 = re.compile(r'\s*(?P<result>\b[a-z]+\w*\b)\s*=.*', re.I)
+crackline_bind_1 = re.compile(r'\s*(?P<bind>\b[a-z]+\w*\b)\s*=.*', re.I)
+crackline_bindlang = re.compile(r'\s*bind\(\s*(?P<lang>[^,]+)\s*,\s*name\s*=\s*"(?P<lang_name>[^"]+)"\s*\)', re.I)
+
+def crackline(line, reset=0):
+    """
+    reset=-1  --- initialize
+    reset=0   --- crack the line
+    reset=1   --- final check if mismatch of blocks occurred
+
+    Cracked data is saved in grouplist[0].
+    """
+    global beginpattern, groupcounter, groupname, groupcache, grouplist
+    global filepositiontext, currentfilename, neededmodule, expectbegin
+    global skipblocksuntil, skipemptyends, previous_context, gotnextfile
+
+    _, has_semicolon = split_by_unquoted(line, ";")
+    if has_semicolon and not (f2pyenhancementspattern[0].match(line) or
+                               multilinepattern[0].match(line)):
+        # XXX: non-zero reset values need testing
+        assert reset == 0, repr(reset)
+        # split line on unquoted semicolons
+        line, semicolon_line = split_by_unquoted(line, ";")
+        while semicolon_line:
+            crackline(line, reset)
+            line, semicolon_line = split_by_unquoted(semicolon_line[1:], ";")
+        crackline(line, reset)
+        return
+    if reset < 0:
+        groupcounter = 0
+        groupname = {groupcounter: ''}
+        groupcache = {groupcounter: {}}
+        grouplist = {groupcounter: []}
+        groupcache[groupcounter]['body'] = []
+        groupcache[groupcounter]['vars'] = {}
+        groupcache[groupcounter]['block'] = ''
+        groupcache[groupcounter]['name'] = ''
+        neededmodule = -1
+        skipblocksuntil = -1
+        return
+    if reset > 0:
+        fl = 0
+        if f77modulename and neededmodule == groupcounter:
+            fl = 2
+        while groupcounter > fl:
+            outmess('crackline: groupcounter=%s groupname=%s\n' %
+                    (repr(groupcounter), repr(groupname)))
+            outmess(
+                'crackline: Mismatch of blocks encountered. Trying to fix it by assuming "end" statement.\n')
+            grouplist[groupcounter - 1].append(groupcache[groupcounter])
+            grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+            del grouplist[groupcounter]
+            groupcounter = groupcounter - 1
+        if f77modulename and neededmodule == groupcounter:
+            grouplist[groupcounter - 1].append(groupcache[groupcounter])
+            grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+            del grouplist[groupcounter]
+            groupcounter = groupcounter - 1  # end interface
+            grouplist[groupcounter - 1].append(groupcache[groupcounter])
+            grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+            del grouplist[groupcounter]
+            groupcounter = groupcounter - 1  # end module
+            neededmodule = -1
+        return
+    if line == '':
+        return
+    flag = 0
+    for pat in [dimensionpattern, externalpattern, intentpattern, optionalpattern,
+                requiredpattern,
+                parameterpattern, datapattern, publicpattern, privatepattern,
+                intrinsicpattern,
+                endifpattern, endpattern,
+                formatpattern,
+                beginpattern, functionpattern, subroutinepattern,
+                implicitpattern, typespattern, commonpattern,
+                callpattern, usepattern, containspattern,
+                entrypattern,
+                f2pyenhancementspattern,
+                multilinepattern,
+                moduleprocedurepattern
+                ]:
+        m = pat[0].match(line)
+        if m:
+            break
+        flag = flag + 1
+    if not m:
+        re_1 = crackline_re_1
+        if 0 <= skipblocksuntil <= groupcounter:
+            return
+        if 'externals' in groupcache[groupcounter]:
+            for name in groupcache[groupcounter]['externals']:
+                if name in invbadnames:
+                    name = invbadnames[name]
+                if 'interfaced' in groupcache[groupcounter] and name in groupcache[groupcounter]['interfaced']:
+                    continue
+                m1 = re.match(
+                    r'(?P<before>[^"]*)\b%s\b\s*@\(@(?P<args>[^@]*)@\)@.*\Z' % name, markouterparen(line), re.I)
+                if m1:
+                    m2 = re_1.match(m1.group('before'))
+                    a = _simplifyargs(m1.group('args'))
+                    if m2:
+                        line = f"callfun {name}({a}) result ({m2.group('result')})"
+                    else:
+                        line = f'callfun {name}({a})'
+                    m = callfunpattern[0].match(line)
+                    if not m:
+                        outmess(
+                            f'crackline: could not resolve function call for line={repr(line)}.\n')
+                        return
+                    analyzeline(m, 'callfun', line)
+                    return
+        if verbose > 1 or (verbose == 1 and currentfilename.lower().endswith('.pyf')):
+            previous_context = None
+            outmess('crackline:%d: No pattern for line\n' % (groupcounter))
+        return
+    elif pat[1] == 'end':
+        if 0 <= skipblocksuntil < groupcounter:
+            groupcounter = groupcounter - 1
+            if skipblocksuntil <= groupcounter:
+                return
+        if groupcounter <= 0:
+            raise Exception('crackline: groupcounter(=%s) is nonpositive. '
+                            'Check the blocks.'
+                            % (groupcounter))
+        m1 = beginpattern[0].match(line)
+        if (m1) and (not m1.group('this') == groupname[groupcounter]):
+            raise Exception('crackline: End group %s does not match with '
+                            'previous Begin group %s\n\t%s' %
+                            (repr(m1.group('this')), repr(groupname[groupcounter]),
+                             filepositiontext)
+                            )
+        if skipblocksuntil == groupcounter:
+            skipblocksuntil = -1
+        grouplist[groupcounter - 1].append(groupcache[groupcounter])
+        grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+        del grouplist[groupcounter]
+        groupcounter = groupcounter - 1
+        if not skipemptyends:
+            expectbegin = 1
+    elif pat[1] == 'begin':
+        if 0 <= skipblocksuntil <= groupcounter:
+            groupcounter = groupcounter + 1
+            return
+        gotnextfile = 0
+        analyzeline(m, pat[1], line)
+        expectbegin = 0
+    elif pat[1] == 'endif':
+        pass
+    elif pat[1] == 'moduleprocedure':
+        analyzeline(m, pat[1], line)
+    elif pat[1] == 'contains':
+        if ignorecontains:
+            return
+        if 0 <= skipblocksuntil <= groupcounter:
+            return
+        skipblocksuntil = groupcounter
+    else:
+        if 0 <= skipblocksuntil <= groupcounter:
+            return
+        analyzeline(m, pat[1], line)
+
+
+def markouterparen(line):
+    l = ''
+    f = 0
+    for c in line:
+        if c == '(':
+            f = f + 1
+            if f == 1:
+                l = l + '@(@'
+                continue
+        elif c == ')':
+            f = f - 1
+            if f == 0:
+                l = l + '@)@'
+                continue
+        l = l + c
+    return l
+
+
+def markoutercomma(line, comma=','):
+    l = ''
+    f = 0
+    before, after = split_by_unquoted(line, comma + '()')
+    l += before
+    while after:
+        if (after[0] == comma) and (f == 0):
+            l += '@' + comma + '@'
+        else:
+            l += after[0]
+            if after[0] == '(':
+                f += 1
+            elif after[0] == ')':
+                f -= 1
+        before, after = split_by_unquoted(after[1:], comma + '()')
+        l += before
+    assert not f, repr((f, line, l))
+    return l
+
+def unmarkouterparen(line):
+    r = line.replace('@(@', '(').replace('@)@', ')')
+    return r
+
+
+def appenddecl(decl, decl2, force=1):
+    if not decl:
+        decl = {}
+    if not decl2:
+        return decl
+    if decl is decl2:
+        return decl
+    for k in list(decl2.keys()):
+        if k == 'typespec':
+            if force or k not in decl:
+                decl[k] = decl2[k]
+        elif k == 'attrspec':
+            for l in decl2[k]:
+                decl = setattrspec(decl, l, force)
+        elif k == 'kindselector':
+            decl = setkindselector(decl, decl2[k], force)
+        elif k == 'charselector':
+            decl = setcharselector(decl, decl2[k], force)
+        elif k in ['=', 'typename']:
+            if force or k not in decl:
+                decl[k] = decl2[k]
+        elif k == 'note':
+            pass
+        elif k in ['intent', 'check', 'dimension', 'optional',
+                   'required', 'depend']:
+            errmess(f'appenddecl: "{k}" not implemented.\n')
+        else:
+            raise Exception('appenddecl: Unknown variable definition key: ' +
+                            str(k))
+    return decl
+
+
+selectpattern = re.compile(
+    r'\s*(?P<this>(@\(@.*?@\)@|\*[\d*]+|\*\s*@\(@.*?@\)@|))(?P<after>.*)\Z', re.I)
+typedefpattern = re.compile(
+    r'(?:,(?P<attributes>[\w(),]+))?(::)?(?P<name>\b[a-z$_][\w$]*\b)'
+    r'(?:\((?P<params>[\w,]*)\))?\Z', re.I)
+nameargspattern = re.compile(
+    r'\s*(?P<name>\b[\w$]+\b)\s*(@\(@\s*(?P<args>[\w\s,]*)\s*@\)@|)\s*((result(\s*@\(@\s*(?P<result>\b[\w$]+\b)\s*@\)@|))|(bind\s*@\(@\s*(?P<bind>(?:(?!@\)@).)*)\s*@\)@))*\s*\Z', re.I)
+operatorpattern = re.compile(
+    r'\s*(?P<scheme>(operator|assignment))'
+    r'@\(@\s*(?P<name>[^)]+)\s*@\)@\s*\Z', re.I)
+callnameargspattern = re.compile(
+    r'\s*(?P<name>\b[\w$]+\b)\s*@\(@\s*(?P<args>.*)\s*@\)@\s*\Z', re.I)
+real16pattern = re.compile(
+    r'([-+]?(?:\d+(?:\.\d*)?|\d*\.\d+))[dD]((?:[-+]?\d+)?)')
+real8pattern = re.compile(
+    r'([-+]?((?:\d+(?:\.\d*)?|\d*\.\d+))[eE]((?:[-+]?\d+)?)|(\d+\.\d*))')
+
+_intentcallbackpattern = re.compile(r'intent\s*\(.*?\bcallback\b', re.I)
+
+
+def _is_intent_callback(vdecl):
+    for a in vdecl.get('attrspec', []):
+        if _intentcallbackpattern.match(a):
+            return 1
+    return 0
+
+
+def _resolvetypedefpattern(line):
+    line = ''.join(line.split())  # removes whitespace
+    m1 = typedefpattern.match(line)
+    print(line, m1)
+    if m1:
+        attrs = m1.group('attributes')
+        attrs = [a.lower() for a in attrs.split(',')] if attrs else []
+        return m1.group('name'), attrs, m1.group('params')
+    return None, [], None
+
+def parse_name_for_bind(line):
+    pattern = re.compile(r'bind\(\s*(?P<lang>[^,]+)(?:\s*,\s*name\s*=\s*["\'](?P<name>[^"\']+)["\']\s*)?\)', re.I)
+    match = pattern.search(line)
+    bind_statement = None
+    if match:
+        bind_statement = match.group(0)
+        # Remove the 'bind' construct from the line.
+        line = line[:match.start()] + line[match.end():]
+    return line, bind_statement
+
+def _resolvenameargspattern(line):
+    line, bind_cname = parse_name_for_bind(line)
+    line = markouterparen(line)
+    m1 = nameargspattern.match(line)
+    if m1:
+        return m1.group('name'), m1.group('args'), m1.group('result'), bind_cname
+    m1 = operatorpattern.match(line)
+    if m1:
+        name = m1.group('scheme') + '(' + m1.group('name') + ')'
+        return name, [], None, None
+    m1 = callnameargspattern.match(line)
+    if m1:
+        return m1.group('name'), m1.group('args'), None, None
+    return None, [], None, None
+
+
+def analyzeline(m, case, line):
+    """
+    Reads each line in the input file in sequence and updates global vars.
+
+    Effectively reads and collects information from the input file to the
+    global variable groupcache, a dictionary containing info about each part
+    of the fortran module.
+
+    At the end of analyzeline, information is filtered into the correct dict
+    keys, but parameter values and dimensions are not yet interpreted.
+    """
+    global groupcounter, groupname, groupcache, grouplist, filepositiontext
+    global currentfilename, f77modulename, neededinterface, neededmodule
+    global expectbegin, gotnextfile, previous_context
+
+    block = m.group('this')
+    if case != 'multiline':
+        previous_context = None
+    if expectbegin and case not in ['begin', 'call', 'callfun', 'type'] \
+       and not skipemptyends and groupcounter < 1:
+        newname = os.path.basename(currentfilename).split('.')[0]
+        outmess(
+            f'analyzeline: no group yet. Creating program group with name "{newname}".\n')
+        gotnextfile = 0
+        groupcounter = groupcounter + 1
+        groupname[groupcounter] = 'program'
+        groupcache[groupcounter] = {}
+        grouplist[groupcounter] = []
+        groupcache[groupcounter]['body'] = []
+        groupcache[groupcounter]['vars'] = {}
+        groupcache[groupcounter]['block'] = 'program'
+        groupcache[groupcounter]['name'] = newname
+        groupcache[groupcounter]['from'] = 'fromsky'
+        expectbegin = 0
+    if case in ['begin', 'call', 'callfun']:
+        # Crack line => block,name,args,result
+        block = block.lower()
+        if re.match(r'block\s*data', block, re.I):
+            block = 'block data'
+        elif re.match(r'python\s*module', block, re.I):
+            block = 'python module'
+        elif re.match(r'abstract\s*interface', block, re.I):
+            block = 'abstract interface'
+        if block == 'type':
+            name, attrs, _ = _resolvetypedefpattern(m.group('after'))
+            groupcache[groupcounter]['vars'][name] = {'attrspec': attrs}
+            args = []
+            result = None
+        else:
+            name, args, result, bindcline = _resolvenameargspattern(m.group('after'))
+        if name is None:
+            if block == 'block data':
+                name = '_BLOCK_DATA_'
+            else:
+                name = ''
+            if block not in ['interface', 'block data', 'abstract interface']:
+                outmess('analyzeline: No name/args pattern found for line.\n')
+
+        previous_context = (block, name, groupcounter)
+        if args:
+            args = rmbadname([x.strip()
+                              for x in markoutercomma(args).split('@,@')])
+        else:
+            args = []
+        if '' in args:
+            while '' in args:
+                args.remove('')
+            outmess(
+                'analyzeline: argument list is malformed (missing argument).\n')
+
+        # end of crack line => block,name,args,result
+        needmodule = 0
+        needinterface = 0
+
+        if case in ['call', 'callfun']:
+            needinterface = 1
+            if 'args' not in groupcache[groupcounter]:
+                return
+            if name not in groupcache[groupcounter]['args']:
+                return
+            for it in grouplist[groupcounter]:
+                if it['name'] == name:
+                    return
+            if name in groupcache[groupcounter]['interfaced']:
+                return
+            block = {'call': 'subroutine', 'callfun': 'function'}[case]
+        if f77modulename and neededmodule == -1 and groupcounter <= 1:
+            neededmodule = groupcounter + 2
+            needmodule = 1
+            if block not in ['interface', 'abstract interface']:
+                needinterface = 1
+        # Create new block(s)
+        groupcounter = groupcounter + 1
+        groupcache[groupcounter] = {}
+        grouplist[groupcounter] = []
+        if needmodule:
+            if verbose > 1:
+                outmess('analyzeline: Creating module block %s\n' %
+                        repr(f77modulename), 0)
+            groupname[groupcounter] = 'module'
+            groupcache[groupcounter]['block'] = 'python module'
+            groupcache[groupcounter]['name'] = f77modulename
+            groupcache[groupcounter]['from'] = ''
+            groupcache[groupcounter]['body'] = []
+            groupcache[groupcounter]['externals'] = []
+            groupcache[groupcounter]['interfaced'] = []
+            groupcache[groupcounter]['vars'] = {}
+            groupcounter = groupcounter + 1
+            groupcache[groupcounter] = {}
+            grouplist[groupcounter] = []
+        if needinterface:
+            if verbose > 1:
+                outmess('analyzeline: Creating additional interface block (groupcounter=%s).\n' % (
+                    groupcounter), 0)
+            groupname[groupcounter] = 'interface'
+            groupcache[groupcounter]['block'] = 'interface'
+            groupcache[groupcounter]['name'] = 'unknown_interface'
+            groupcache[groupcounter]['from'] = '%s:%s' % (
+                groupcache[groupcounter - 1]['from'], groupcache[groupcounter - 1]['name'])
+            groupcache[groupcounter]['body'] = []
+            groupcache[groupcounter]['externals'] = []
+            groupcache[groupcounter]['interfaced'] = []
+            groupcache[groupcounter]['vars'] = {}
+            groupcounter = groupcounter + 1
+            groupcache[groupcounter] = {}
+            grouplist[groupcounter] = []
+        groupname[groupcounter] = block
+        groupcache[groupcounter]['block'] = block
+        if not name:
+            name = 'unknown_' + block.replace(' ', '_')
+        groupcache[groupcounter]['prefix'] = m.group('before')
+        groupcache[groupcounter]['name'] = rmbadname1(name)
+        groupcache[groupcounter]['result'] = result
+        if groupcounter == 1:
+            groupcache[groupcounter]['from'] = currentfilename
+        elif f77modulename and groupcounter == 3:
+            groupcache[groupcounter]['from'] = '%s:%s' % (
+                groupcache[groupcounter - 1]['from'], currentfilename)
+        else:
+            groupcache[groupcounter]['from'] = '%s:%s' % (
+                groupcache[groupcounter - 1]['from'], groupcache[groupcounter - 1]['name'])
+        for k in list(groupcache[groupcounter].keys()):
+            if not groupcache[groupcounter][k]:
+                del groupcache[groupcounter][k]
+
+        groupcache[groupcounter]['args'] = args
+        groupcache[groupcounter]['body'] = []
+        groupcache[groupcounter]['externals'] = []
+        groupcache[groupcounter]['interfaced'] = []
+        groupcache[groupcounter]['vars'] = {}
+        groupcache[groupcounter]['entry'] = {}
+        # end of creation
+        if block == 'type':
+            groupcache[groupcounter]['varnames'] = []
+
+        if case in ['call', 'callfun']:  # set parents variables
+            if name not in groupcache[groupcounter - 2]['externals']:
+                groupcache[groupcounter - 2]['externals'].append(name)
+            groupcache[groupcounter]['vars'] = copy.deepcopy(
+                groupcache[groupcounter - 2]['vars'])
+            try:
+                del groupcache[groupcounter]['vars'][name][
+                    groupcache[groupcounter]['vars'][name]['attrspec'].index('external')]
+            except Exception:
+                pass
+        if block in ['function', 'subroutine']:  # set global attributes
+            # name is fortran name
+            if bindcline:
+                bindcdat = re.search(crackline_bindlang, bindcline)
+                if bindcdat:
+                    groupcache[groupcounter]['bindlang'] = {name: {}}
+                    groupcache[groupcounter]['bindlang'][name]["lang"] = bindcdat.group('lang')
+                    if bindcdat.group('lang_name'):
+                        groupcache[groupcounter]['bindlang'][name]["name"] = bindcdat.group('lang_name')
+            try:
+                groupcache[groupcounter]['vars'][name] = appenddecl(
+                    groupcache[groupcounter]['vars'][name], groupcache[groupcounter - 2]['vars'][''])
+            except Exception:
+                pass
+            if case == 'callfun':  # return type
+                if result and result in groupcache[groupcounter]['vars']:
+                    if not name == result:
+                        groupcache[groupcounter]['vars'][name] = appenddecl(
+                            groupcache[groupcounter]['vars'][name], groupcache[groupcounter]['vars'][result])
+            # if groupcounter>1: # name is interfaced
+            try:
+                groupcache[groupcounter - 2]['interfaced'].append(name)
+            except Exception:
+                pass
+        if block == 'function':
+            t = typespattern[0].match(m.group('before') + ' ' + name)
+            if t:
+                typespec, selector, attr, edecl = cracktypespec0(
+                    t.group('this'), t.group('after'))
+                updatevars(typespec, selector, attr, edecl)
+
+        if case in ['call', 'callfun']:
+            grouplist[groupcounter - 1].append(groupcache[groupcounter])
+            grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+            del grouplist[groupcounter]
+            groupcounter = groupcounter - 1  # end routine
+            grouplist[groupcounter - 1].append(groupcache[groupcounter])
+            grouplist[groupcounter - 1][-1]['body'] = grouplist[groupcounter]
+            del grouplist[groupcounter]
+            groupcounter = groupcounter - 1  # end interface
+
+    elif case == 'entry':
+        name, args, result, _ = _resolvenameargspattern(m.group('after'))
+        if name is not None:
+            if args:
+                args = rmbadname([x.strip()
+                                  for x in markoutercomma(args).split('@,@')])
+            else:
+                args = []
+            assert result is None, repr(result)
+            groupcache[groupcounter]['entry'][name] = args
+            previous_context = ('entry', name, groupcounter)
+    elif case == 'type':
+        typespec, selector, attr, edecl = cracktypespec0(
+            block, m.group('after'))
+        last_name = updatevars(typespec, selector, attr, edecl)
+        if last_name is not None:
+            previous_context = ('variable', last_name, groupcounter)
+    elif case in ['dimension', 'intent', 'optional', 'required', 'external', 'public', 'private', 'intrinsic']:
+        edecl = groupcache[groupcounter]['vars']
+        ll = m.group('after').strip()
+        i = ll.find('::')
+        if i < 0 and case == 'intent':
+            i = markouterparen(ll).find('@)@') - 2
+            ll = ll[:i + 1] + '::' + ll[i + 1:]
+            i = ll.find('::')
+            if ll[i:] == '::' and 'args' in groupcache[groupcounter]:
+                outmess('All arguments will have attribute %s%s\n' %
+                        (m.group('this'), ll[:i]))
+                ll = ll + ','.join(groupcache[groupcounter]['args'])
+        if i < 0:
+            i = 0
+            pl = ''
+        else:
+            pl = ll[:i].strip()
+            ll = ll[i + 2:]
+        ch = markoutercomma(pl).split('@,@')
+        if len(ch) > 1:
+            pl = ch[0]
+            outmess('analyzeline: cannot handle multiple attributes without type specification. Ignoring %r.\n' % (
+                ','.join(ch[1:])))
+        last_name = None
+
+        for e in [x.strip() for x in markoutercomma(ll).split('@,@')]:
+            m1 = namepattern.match(e)
+            if not m1:
+                if case in ['public', 'private']:
+                    k = ''
+                else:
+                    print(m.groupdict())
+                    outmess('analyzeline: no name pattern found in %s statement for %s. Skipping.\n' % (
+                        case, repr(e)))
+                    continue
+            else:
+                k = rmbadname1(m1.group('name'))
+            if case in ['public', 'private'] and k in {'operator', 'assignment'}:
+                k += m1.group('after')
+            if k not in edecl:
+                edecl[k] = {}
+            if case == 'dimension':
+                ap = case + m1.group('after')
+            if case == 'intent':
+                ap = m.group('this') + pl
+                if _intentcallbackpattern.match(ap):
+                    if k not in groupcache[groupcounter]['args']:
+                        if groupcounter > 1:
+                            if '__user__' not in groupcache[groupcounter - 2]['name']:
+                                outmess(
+                                    'analyzeline: missing __user__ module (could be nothing)\n')
+                            # fixes ticket 1693
+                            if k != groupcache[groupcounter]['name']:
+                                outmess('analyzeline: appending intent(callback) %s'
+                                        ' to %s arguments\n' % (k, groupcache[groupcounter]['name']))
+                                groupcache[groupcounter]['args'].append(k)
+                        else:
+                            errmess(
+                                f'analyzeline: intent(callback) {k} is ignored\n')
+                    else:
+                        errmess('analyzeline: intent(callback) %s is already'
+                                ' in argument list\n' % (k))
+            if case in ['optional', 'required', 'public', 'external', 'private', 'intrinsic']:
+                ap = case
+            if 'attrspec' in edecl[k]:
+                edecl[k]['attrspec'].append(ap)
+            else:
+                edecl[k]['attrspec'] = [ap]
+            if case == 'external':
+                if groupcache[groupcounter]['block'] == 'program':
+                    outmess('analyzeline: ignoring program arguments\n')
+                    continue
+                if k not in groupcache[groupcounter]['args']:
+                    continue
+                if 'externals' not in groupcache[groupcounter]:
+                    groupcache[groupcounter]['externals'] = []
+                groupcache[groupcounter]['externals'].append(k)
+            last_name = k
+        groupcache[groupcounter]['vars'] = edecl
+        if last_name is not None:
+            previous_context = ('variable', last_name, groupcounter)
+    elif case == 'moduleprocedure':
+        groupcache[groupcounter]['implementedby'] = \
+            [x.strip() for x in m.group('after').split(',')]
+    elif case == 'parameter':
+        edecl = groupcache[groupcounter]['vars']
+        ll = m.group('after').strip()[1:-1]
+        last_name = None
+        for e in markoutercomma(ll).split('@,@'):
+            try:
+                k, initexpr = [x.strip() for x in e.split('=')]
+            except Exception:
+                outmess(
+                    f'analyzeline: could not extract name,expr in parameter statement "{e}" of "{ll}\"\n')
+                continue
+            params = get_parameters(edecl)
+            k = rmbadname1(k)
+            if k not in edecl:
+                edecl[k] = {}
+            if '=' in edecl[k] and (not edecl[k]['='] == initexpr):
+                outmess('analyzeline: Overwriting the value of parameter "%s" ("%s") with "%s".\n' % (
+                    k, edecl[k]['='], initexpr))
+            t = determineexprtype(initexpr, params)
+            if t:
+                if t.get('typespec') == 'real':
+                    tt = list(initexpr)
+                    for m in real16pattern.finditer(initexpr):
+                        tt[m.start():m.end()] = list(
+                            initexpr[m.start():m.end()].lower().replace('d', 'e'))
+                    initexpr = ''.join(tt)
+                elif t.get('typespec') == 'complex':
+                    initexpr = initexpr[1:].lower().replace('d', 'e').\
+                        replace(',', '+1j*(')
+            try:
+                v = eval(initexpr, {}, params)
+            except (SyntaxError, NameError, TypeError) as msg:
+                errmess('analyzeline: Failed to evaluate %r. Ignoring: %s\n'
+                        % (initexpr, msg))
+                continue
+            edecl[k]['='] = repr(v)
+            if 'attrspec' in edecl[k]:
+                edecl[k]['attrspec'].append('parameter')
+            else:
+                edecl[k]['attrspec'] = ['parameter']
+            last_name = k
+        groupcache[groupcounter]['vars'] = edecl
+        if last_name is not None:
+            previous_context = ('variable', last_name, groupcounter)
+    elif case == 'implicit':
+        if m.group('after').strip().lower() == 'none':
+            groupcache[groupcounter]['implicit'] = None
+        elif m.group('after'):
+            impl = groupcache[groupcounter].get('implicit', {})
+            if impl is None:
+                outmess(
+                    'analyzeline: Overwriting earlier "implicit none" statement.\n')
+                impl = {}
+            for e in markoutercomma(m.group('after')).split('@,@'):
+                decl = {}
+                m1 = re.match(
+                    r'\s*(?P<this>.*?)\s*(\(\s*(?P<after>[a-z-, ]+)\s*\)\s*|)\Z', e, re.I)
+                if not m1:
+                    outmess(
+                        f'analyzeline: could not extract info of implicit statement part "{e}\"\n')
+                    continue
+                m2 = typespattern4implicit.match(m1.group('this'))
+                if not m2:
+                    outmess(
+                        f'analyzeline: could not extract types pattern of implicit statement part "{e}\"\n')
+                    continue
+                typespec, selector, attr, edecl = cracktypespec0(
+                    m2.group('this'), m2.group('after'))
+                kindselect, charselect, typename = cracktypespec(
+                    typespec, selector)
+                decl['typespec'] = typespec
+                decl['kindselector'] = kindselect
+                decl['charselector'] = charselect
+                decl['typename'] = typename
+                for k in list(decl.keys()):
+                    if not decl[k]:
+                        del decl[k]
+                for r in markoutercomma(m1.group('after')).split('@,@'):
+                    if '-' in r:
+                        try:
+                            begc, endc = [x.strip() for x in r.split('-')]
+                        except Exception:
+                            outmess(
+                                f'analyzeline: expected "<char>-<char>" instead of "{r}" in range list of implicit statement\n')
+                            continue
+                    else:
+                        begc = endc = r.strip()
+                    if not len(begc) == len(endc) == 1:
+                        outmess(
+                            f'analyzeline: expected "<char>-<char>" instead of "{r}" in range list of implicit statement (2)\n')
+                        continue
+                    for o in range(ord(begc), ord(endc) + 1):
+                        impl[chr(o)] = decl
+            groupcache[groupcounter]['implicit'] = impl
+    elif case == 'data':
+        ll = []
+        dl = ''
+        il = ''
+        f = 0
+        fc = 1
+        inp = 0
+        for c in m.group('after'):
+            if not inp:
+                if c == "'":
+                    fc = not fc
+                if c == '/' and fc:
+                    f = f + 1
+                    continue
+            if c == '(':
+                inp = inp + 1
+            elif c == ')':
+                inp = inp - 1
+            if f == 0:
+                dl = dl + c
+            elif f == 1:
+                il = il + c
+            elif f == 2:
+                dl = dl.strip()
+                if dl.startswith(','):
+                    dl = dl[1:].strip()
+                ll.append([dl, il])
+                dl = c
+                il = ''
+                f = 0
+        if f == 2:
+            dl = dl.strip()
+            if dl.startswith(','):
+                dl = dl[1:].strip()
+            ll.append([dl, il])
+        vars = groupcache[groupcounter].get('vars', {})
+        last_name = None
+        for l in ll:
+            l[0], l[1] = l[0].strip().removeprefix(','), l[1].strip()
+            if l[0].startswith('('):
+                outmess(f'analyzeline: implied-DO list "{l[0]}" is not supported. Skipping.\n')
+                continue
+            for idx, v in enumerate(rmbadname([x.strip() for x in markoutercomma(l[0]).split('@,@')])):
+                if v.startswith('('):
+                    outmess(f'analyzeline: implied-DO list "{v}" is not supported. Skipping.\n')
+                    # XXX: subsequent init expressions may get wrong values.
+                    # Ignoring since data statements are irrelevant for
+                    # wrapping.
+                    continue
+                if '!' in l[1]:
+                    # Fixes gh-24746 pyf generation
+                    # XXX: This essentially ignores the value for generating the pyf which is fine:
+                    # integer dimension(3) :: mytab
+                    # common /mycom/ mytab
+                    # Since in any case it is initialized in the Fortran code
+                    outmess(f'Comment line in declaration "{l[1]}" is not supported. Skipping.\n')
+                    continue
+                vars.setdefault(v, {})
+                vtype = vars[v].get('typespec')
+                vdim = getdimension(vars[v])
+                matches = re.findall(r"\(.*?\)", l[1]) if vtype == 'complex' else l[1].split(',')
+                try:
+                    new_val = f"(/{', '.join(matches)}/)" if vdim else matches[idx]
+                except IndexError:
+                    # gh-24746
+                    # Runs only if above code fails. Fixes the line
+                    # DATA IVAR1, IVAR2, IVAR3, IVAR4, EVAR5 /4*0,0.0D0/
+                    # by expanding to ['0', '0', '0', '0', '0.0d0']
+                    if any("*" in m for m in matches):
+                        expanded_list = []
+                        for match in matches:
+                            if "*" in match:
+                                try:
+                                    multiplier, value = match.split("*")
+                                    expanded_list.extend([value.strip()] * int(multiplier))
+                                except ValueError:  # if int(multiplier) fails
+                                    expanded_list.append(match.strip())
+                            else:
+                                expanded_list.append(match.strip())
+                        matches = expanded_list
+                    new_val = f"(/{', '.join(matches)}/)" if vdim else matches[idx]
+                current_val = vars[v].get('=')
+                if current_val and (current_val != new_val):
+                    outmess(f'analyzeline: changing init expression of "{v}" ("{current_val}") to "{new_val}\"\n')
+                vars[v]['='] = new_val
+                last_name = v
+        groupcache[groupcounter]['vars'] = vars
+        if last_name:
+            previous_context = ('variable', last_name, groupcounter)
+    elif case == 'common':
+        line = m.group('after').strip()
+        if not line[0] == '/':
+            line = '//' + line
+
+        cl = []
+        [_, bn, ol] = re.split('/', line, maxsplit=2)  # noqa: RUF039
+        bn = bn.strip()
+        if not bn:
+            bn = '_BLNK_'
+        cl.append([bn, ol])
+        commonkey = {}
+        if 'common' in groupcache[groupcounter]:
+            commonkey = groupcache[groupcounter]['common']
+        for c in cl:
+            if c[0] not in commonkey:
+                commonkey[c[0]] = []
+            for i in [x.strip() for x in markoutercomma(c[1]).split('@,@')]:
+                if i:
+                    commonkey[c[0]].append(i)
+        groupcache[groupcounter]['common'] = commonkey
+        previous_context = ('common', bn, groupcounter)
+    elif case == 'use':
+        m1 = re.match(
+            r'\A\s*(?P<name>\b\w+\b)\s*((,(\s*\bonly\b\s*:|(?P<notonly>))\s*(?P<list>.*))|)\s*\Z', m.group('after'), re.I)
+        if m1:
+            mm = m1.groupdict()
+            if 'use' not in groupcache[groupcounter]:
+                groupcache[groupcounter]['use'] = {}
+            name = m1.group('name')
+            groupcache[groupcounter]['use'][name] = {}
+            isonly = 0
+            if 'list' in mm and mm['list'] is not None:
+                if 'notonly' in mm and mm['notonly'] is None:
+                    isonly = 1
+                groupcache[groupcounter]['use'][name]['only'] = isonly
+                ll = [x.strip() for x in mm['list'].split(',')]
+                rl = {}
+                for l in ll:
+                    if '=' in l:
+                        m2 = re.match(
+                            r'\A\s*(?P<local>\b\w+\b)\s*=\s*>\s*(?P<use>\b\w+\b)\s*\Z', l, re.I)
+                        if m2:
+                            rl[m2.group('local').strip()] = m2.group(
+                                'use').strip()
+                        else:
+                            outmess(
+                                f'analyzeline: Not local=>use pattern found in {repr(l)}\n')
+                    else:
+                        rl[l] = l
+                    groupcache[groupcounter]['use'][name]['map'] = rl
+        else:
+            print(m.groupdict())
+            outmess('analyzeline: Could not crack the use statement.\n')
+    elif case in ['f2pyenhancements']:
+        if 'f2pyenhancements' not in groupcache[groupcounter]:
+            groupcache[groupcounter]['f2pyenhancements'] = {}
+        d = groupcache[groupcounter]['f2pyenhancements']
+        if m.group('this') == 'usercode' and 'usercode' in d:
+            if isinstance(d['usercode'], str):
+                d['usercode'] = [d['usercode']]
+            d['usercode'].append(m.group('after'))
+        else:
+            d[m.group('this')] = m.group('after')
+    elif case == 'multiline':
+        if previous_context is None:
+            if verbose:
+                outmess('analyzeline: No context for multiline block.\n')
+            return
+        gc = groupcounter
+        appendmultiline(groupcache[gc],
+                        previous_context[:2],
+                        m.group('this'))
+    elif verbose > 1:
+        print(m.groupdict())
+        outmess('analyzeline: No code implemented for line.\n')
+
+
+def appendmultiline(group, context_name, ml):
+    if 'f2pymultilines' not in group:
+        group['f2pymultilines'] = {}
+    d = group['f2pymultilines']
+    if context_name not in d:
+        d[context_name] = []
+    d[context_name].append(ml)
+
+
+def cracktypespec0(typespec, ll):
+    selector = None
+    attr = None
+    if re.match(r'double\s*complex', typespec, re.I):
+        typespec = 'double complex'
+    elif re.match(r'double\s*precision', typespec, re.I):
+        typespec = 'double precision'
+    else:
+        typespec = typespec.strip().lower()
+    m1 = selectpattern.match(markouterparen(ll))
+    if not m1:
+        outmess(
+            'cracktypespec0: no kind/char_selector pattern found for line.\n')
+        return
+    d = m1.groupdict()
+    for k in list(d.keys()):
+        d[k] = unmarkouterparen(d[k])
+    if typespec in ['complex', 'integer', 'logical', 'real', 'character', 'type']:
+        selector = d['this']
+        ll = d['after']
+    i = ll.find('::')
+    if i >= 0:
+        attr = ll[:i].strip()
+        ll = ll[i + 2:]
+    return typespec, selector, attr, ll
+
+
+#####
+namepattern = re.compile(r'\s*(?P<name>\b\w+\b)\s*(?P<after>.*)\s*\Z', re.I)
+kindselector = re.compile(
+    r'\s*(\(\s*(kind\s*=)?\s*(?P<kind>.*)\s*\)|\*\s*(?P<kind2>.*?))\s*\Z', re.I)
+charselector = re.compile(
+    r'\s*(\((?P<lenkind>.*)\)|\*\s*(?P<charlen>.*))\s*\Z', re.I)
+lenkindpattern = re.compile(
+    r'\s*(kind\s*=\s*(?P<kind>.*?)\s*(@,@\s*len\s*=\s*(?P<len>.*)|)'
+    r'|(len\s*=\s*|)(?P<len2>.*?)\s*(@,@\s*(kind\s*=\s*|)(?P<kind2>.*)'
+    r'|(f2py_len\s*=\s*(?P<f2py_len>.*))|))\s*\Z', re.I)
+lenarraypattern = re.compile(
+    r'\s*(@\(@\s*(?!/)\s*(?P<array>.*?)\s*@\)@\s*\*\s*(?P<len>.*?)|(\*\s*(?P<len2>.*?)|)\s*(@\(@\s*(?!/)\s*(?P<array2>.*?)\s*@\)@|))\s*(=\s*(?P<init>.*?)|(@\(@|)/\s*(?P<init2>.*?)\s*/(@\)@|)|)\s*\Z', re.I)
+
+
+def removespaces(expr):
+    expr = expr.strip()
+    if len(expr) <= 1:
+        return expr
+    expr2 = expr[0]
+    for i in range(1, len(expr) - 1):
+        if (expr[i] == ' ' and
+            ((expr[i + 1] in "()[]{}=+-/* ") or
+                (expr[i - 1] in "()[]{}=+-/* "))):
+            continue
+        expr2 = expr2 + expr[i]
+    expr2 = expr2 + expr[-1]
+    return expr2
+
+
+def markinnerspaces(line):
+    """
+    The function replace all spaces in the input variable line which are
+    surrounded with quotation marks, with the triplet "@_@".
+
+    For instance, for the input "a 'b c'" the function returns "a 'b@_@c'"
+
+    Parameters
+    ----------
+    line : str
+
+    Returns
+    -------
+    str
+
+    """
+    fragment = ''
+    inside = False
+    current_quote = None
+    escaped = ''
+    for c in line:
+        if escaped == '\\' and c in ['\\', '\'', '"']:
+            fragment += c
+            escaped = c
+            continue
+        if not inside and c in ['\'', '"']:
+            current_quote = c
+        if c == current_quote:
+            inside = not inside
+        elif c == ' ' and inside:
+            fragment += '@_@'
+            continue
+        fragment += c
+        escaped = c  # reset to non-backslash
+    return fragment
+
+
+def updatevars(typespec, selector, attrspec, entitydecl):
+    """
+    Returns last_name, the variable name without special chars, parenthesis
+        or dimension specifiers.
+
+    Alters groupcache to add the name, typespec, attrspec (and possibly value)
+    of current variable.
+    """
+    global groupcache, groupcounter
+
+    last_name = None
+    kindselect, charselect, typename = cracktypespec(typespec, selector)
+    # Clean up outer commas, whitespace and undesired chars from attrspec
+    if attrspec:
+        attrspec = [x.strip() for x in markoutercomma(attrspec).split('@,@')]
+        l = []
+        c = re.compile(r'(?P<start>[a-zA-Z]+)')
+        for a in attrspec:
+            if not a:
+                continue
+            m = c.match(a)
+            if m:
+                s = m.group('start').lower()
+                a = s + a[len(s):]
+            l.append(a)
+        attrspec = l
+    el = [x.strip() for x in markoutercomma(entitydecl).split('@,@')]
+    el1 = []
+    for e in el:
+        for e1 in [x.strip() for x in markoutercomma(removespaces(markinnerspaces(e)), comma=' ').split('@ @')]:
+            if e1:
+                el1.append(e1.replace('@_@', ' '))
+    for e in el1:
+        m = namepattern.match(e)
+        if not m:
+            outmess(
+                f'updatevars: no name pattern found for entity={repr(e)}. Skipping.\n')
+            continue
+        ename = rmbadname1(m.group('name'))
+        edecl = {}
+        if ename in groupcache[groupcounter]['vars']:
+            edecl = groupcache[groupcounter]['vars'][ename].copy()
+            not_has_typespec = 'typespec' not in edecl
+            if not_has_typespec:
+                edecl['typespec'] = typespec
+            elif typespec and (not typespec == edecl['typespec']):
+                outmess('updatevars: attempt to change the type of "%s" ("%s") to "%s". Ignoring.\n' % (
+                    ename, edecl['typespec'], typespec))
+            if 'kindselector' not in edecl:
+                edecl['kindselector'] = copy.copy(kindselect)
+            elif kindselect:
+                for k in list(kindselect.keys()):
+                    if k in edecl['kindselector'] and (not kindselect[k] == edecl['kindselector'][k]):
+                        outmess('updatevars: attempt to change the kindselector "%s" of "%s" ("%s") to "%s". Ignoring.\n' % (
+                            k, ename, edecl['kindselector'][k], kindselect[k]))
+                    else:
+                        edecl['kindselector'][k] = copy.copy(kindselect[k])
+            if 'charselector' not in edecl and charselect:
+                if not_has_typespec:
+                    edecl['charselector'] = charselect
+                else:
+                    errmess('updatevars:%s: attempt to change empty charselector to %r. Ignoring.\n'
+                            % (ename, charselect))
+            elif charselect:
+                for k in list(charselect.keys()):
+                    if k in edecl['charselector'] and (not charselect[k] == edecl['charselector'][k]):
+                        outmess('updatevars: attempt to change the charselector "%s" of "%s" ("%s") to "%s". Ignoring.\n' % (
+                            k, ename, edecl['charselector'][k], charselect[k]))
+                    else:
+                        edecl['charselector'][k] = copy.copy(charselect[k])
+            if 'typename' not in edecl:
+                edecl['typename'] = typename
+            elif typename and (not edecl['typename'] == typename):
+                outmess('updatevars: attempt to change the typename of "%s" ("%s") to "%s". Ignoring.\n' % (
+                    ename, edecl['typename'], typename))
+            if 'attrspec' not in edecl:
+                edecl['attrspec'] = copy.copy(attrspec)
+            elif attrspec:
+                for a in attrspec:
+                    if a not in edecl['attrspec']:
+                        edecl['attrspec'].append(a)
+        else:
+            edecl['typespec'] = copy.copy(typespec)
+            edecl['kindselector'] = copy.copy(kindselect)
+            edecl['charselector'] = copy.copy(charselect)
+            edecl['typename'] = typename
+            edecl['attrspec'] = copy.copy(attrspec)
+        if 'external' in (edecl.get('attrspec') or []) and e in groupcache[groupcounter]['args']:
+            if 'externals' not in groupcache[groupcounter]:
+                groupcache[groupcounter]['externals'] = []
+            groupcache[groupcounter]['externals'].append(e)
+        if m.group('after'):
+            m1 = lenarraypattern.match(markouterparen(m.group('after')))
+            if m1:
+                d1 = m1.groupdict()
+                for lk in ['len', 'array', 'init']:
+                    if d1[lk + '2'] is not None:
+                        d1[lk] = d1[lk + '2']
+                        del d1[lk + '2']
+                for k in list(d1.keys()):
+                    if d1[k] is not None:
+                        d1[k] = unmarkouterparen(d1[k])
+                    else:
+                        del d1[k]
+
+                if 'len' in d1 and 'array' in d1:
+                    if d1['len'] == '':
+                        d1['len'] = d1['array']
+                        del d1['array']
+                    elif typespec == 'character':
+                        if ('charselector' not in edecl) or (not edecl['charselector']):
+                            edecl['charselector'] = {}
+                        if 'len' in edecl['charselector']:
+                            del edecl['charselector']['len']
+                        edecl['charselector']['*'] = d1['len']
+                        del d1['len']
+                    else:
+                        d1['array'] = d1['array'] + ',' + d1['len']
+                        del d1['len']
+                        errmess('updatevars: "%s %s" is mapped to "%s %s(%s)"\n' % (
+                            typespec, e, typespec, ename, d1['array']))
+
+                if 'len' in d1:
+                    if typespec in ['complex', 'integer', 'logical', 'real']:
+                        if ('kindselector' not in edecl) or (not edecl['kindselector']):
+                            edecl['kindselector'] = {}
+                        edecl['kindselector']['*'] = d1['len']
+                        del d1['len']
+                    elif typespec == 'character':
+                        if ('charselector' not in edecl) or (not edecl['charselector']):
+                            edecl['charselector'] = {}
+                        if 'len' in edecl['charselector']:
+                            del edecl['charselector']['len']
+                        edecl['charselector']['*'] = d1['len']
+                        del d1['len']
+
+                if 'init' in d1:
+                    if '=' in edecl and (not edecl['='] == d1['init']):
+                        outmess('updatevars: attempt to change the init expression of "%s" ("%s") to "%s". Ignoring.\n' % (
+                            ename, edecl['='], d1['init']))
+                    else:
+                        edecl['='] = d1['init']
+
+                if 'array' in d1:
+                    dm = f"dimension({d1['array']})"
+                    if 'attrspec' not in edecl or (not edecl['attrspec']):
+                        edecl['attrspec'] = [dm]
+                    else:
+                        edecl['attrspec'].append(dm)
+                        for dm1 in edecl['attrspec']:
+                            if dm1[:9] == 'dimension' and dm1 != dm:
+                                del edecl['attrspec'][-1]
+                                errmess('updatevars:%s: attempt to change %r to %r. Ignoring.\n'
+                                        % (ename, dm1, dm))
+                                break
+
+            else:
+                outmess('updatevars: could not crack entity declaration "%s". Ignoring.\n' % (
+                    ename + m.group('after')))
+        for k in list(edecl.keys()):
+            if not edecl[k]:
+                del edecl[k]
+        groupcache[groupcounter]['vars'][ename] = edecl
+        if 'varnames' in groupcache[groupcounter]:
+            groupcache[groupcounter]['varnames'].append(ename)
+        last_name = ename
+    return last_name
+
+
+def cracktypespec(typespec, selector):
+    kindselect = None
+    charselect = None
+    typename = None
+    if selector:
+        if typespec in ['complex', 'integer', 'logical', 'real']:
+            kindselect = kindselector.match(selector)
+            if not kindselect:
+                outmess(
+                    f'cracktypespec: no kindselector pattern found for {repr(selector)}\n')
+                return
+            kindselect = kindselect.groupdict()
+            kindselect['*'] = kindselect['kind2']
+            del kindselect['kind2']
+            for k in list(kindselect.keys()):
+                if not kindselect[k]:
+                    del kindselect[k]
+            for k, i in list(kindselect.items()):
+                kindselect[k] = rmbadname1(i)
+        elif typespec == 'character':
+            charselect = charselector.match(selector)
+            if not charselect:
+                outmess(
+                    f'cracktypespec: no charselector pattern found for {repr(selector)}\n')
+                return
+            charselect = charselect.groupdict()
+            charselect['*'] = charselect['charlen']
+            del charselect['charlen']
+            if charselect['lenkind']:
+                lenkind = lenkindpattern.match(
+                    markoutercomma(charselect['lenkind']))
+                lenkind = lenkind.groupdict()
+                for lk in ['len', 'kind']:
+                    if lenkind[lk + '2']:
+                        lenkind[lk] = lenkind[lk + '2']
+                    charselect[lk] = lenkind[lk]
+                    del lenkind[lk + '2']
+                if lenkind['f2py_len'] is not None:
+                    # used to specify the length of assumed length strings
+                    charselect['f2py_len'] = lenkind['f2py_len']
+            del charselect['lenkind']
+            for k in list(charselect.keys()):
+                if not charselect[k]:
+                    del charselect[k]
+            for k, i in list(charselect.items()):
+                charselect[k] = rmbadname1(i)
+        elif typespec == 'type':
+            typename = re.match(r'\s*\(\s*(?P<name>\w+)\s*\)', selector, re.I)
+            if typename:
+                typename = typename.group('name')
+            else:
+                outmess('cracktypespec: no typename found in %s\n' %
+                        (repr(typespec + selector)))
+        else:
+            outmess(f'cracktypespec: no selector used for {repr(selector)}\n')
+    return kindselect, charselect, typename
+######
+
+
+def setattrspec(decl, attr, force=0):
+    if not decl:
+        decl = {}
+    if not attr:
+        return decl
+    if 'attrspec' not in decl:
+        decl['attrspec'] = [attr]
+        return decl
+    if force:
+        decl['attrspec'].append(attr)
+    if attr in decl['attrspec']:
+        return decl
+    if attr == 'static' and 'automatic' not in decl['attrspec']:
+        decl['attrspec'].append(attr)
+    elif attr == 'automatic' and 'static' not in decl['attrspec']:
+        decl['attrspec'].append(attr)
+    elif attr == 'public':
+        if 'private' not in decl['attrspec']:
+            decl['attrspec'].append(attr)
+    elif attr == 'private':
+        if 'public' not in decl['attrspec']:
+            decl['attrspec'].append(attr)
+    else:
+        decl['attrspec'].append(attr)
+    return decl
+
+
+def setkindselector(decl, sel, force=0):
+    if not decl:
+        decl = {}
+    if not sel:
+        return decl
+    if 'kindselector' not in decl:
+        decl['kindselector'] = sel
+        return decl
+    for k in list(sel.keys()):
+        if force or k not in decl['kindselector']:
+            decl['kindselector'][k] = sel[k]
+    return decl
+
+
+def setcharselector(decl, sel, force=0):
+    if not decl:
+        decl = {}
+    if not sel:
+        return decl
+    if 'charselector' not in decl:
+        decl['charselector'] = sel
+        return decl
+
+    for k in list(sel.keys()):
+        if force or k not in decl['charselector']:
+            decl['charselector'][k] = sel[k]
+    return decl
+
+
+def getblockname(block, unknown='unknown'):
+    if 'name' in block:
+        return block['name']
+    return unknown
+
+# post processing
+
+
+def setmesstext(block):
+    global filepositiontext
+
+    try:
+        filepositiontext = f"In: {block['from']}:{block['name']}\n"
+    except Exception:
+        pass
+
+
+def get_usedict(block):
+    usedict = {}
+    if 'parent_block' in block:
+        usedict = get_usedict(block['parent_block'])
+    if 'use' in block:
+        usedict.update(block['use'])
+    return usedict
+
+
+def get_useparameters(block, param_map=None):
+    global f90modulevars
+
+    if param_map is None:
+        param_map = {}
+    usedict = get_usedict(block)
+    if not usedict:
+        return param_map
+    for usename, mapping in list(usedict.items()):
+        usename = usename.lower()
+        if usename not in f90modulevars:
+            outmess('get_useparameters: no module %s info used by %s\n' %
+                    (usename, block.get('name')))
+            continue
+        mvars = f90modulevars[usename]
+        params = get_parameters(mvars)
+        if not params:
+            continue
+        # XXX: apply mapping
+        if mapping:
+            errmess(f'get_useparameters: mapping for {mapping} not impl.\n')
+        for k, v in list(params.items()):
+            if k in param_map:
+                outmess('get_useparameters: overriding parameter %s with'
+                        ' value from module %s\n' % (repr(k), repr(usename)))
+            param_map[k] = v
+
+    return param_map
+
+
+def postcrack2(block, tab='', param_map=None):
+    global f90modulevars
+
+    if not f90modulevars:
+        return block
+    if isinstance(block, list):
+        ret = [postcrack2(g, tab=tab + '\t', param_map=param_map)
+               for g in block]
+        return ret
+    setmesstext(block)
+    outmess(f"{tab}Block: {block['name']}\n", 0)
+
+    if param_map is None:
+        param_map = get_useparameters(block)
+
+    if param_map is not None and 'vars' in block:
+        vars = block['vars']
+        for n in list(vars.keys()):
+            var = vars[n]
+            if 'kindselector' in var:
+                kind = var['kindselector']
+                if 'kind' in kind:
+                    val = kind['kind']
+                    if val in param_map:
+                        kind['kind'] = param_map[val]
+    new_body = [postcrack2(b, tab=tab + '\t', param_map=param_map)
+                for b in block['body']]
+    block['body'] = new_body
+
+    return block
+
+
+def postcrack(block, args=None, tab=''):
+    """
+    TODO:
+          function return values
+          determine expression types if in argument list
+    """
+    global usermodules, onlyfunctions
+
+    if isinstance(block, list):
+        gret = []
+        uret = []
+        for g in block:
+            setmesstext(g)
+            g = postcrack(g, tab=tab + '\t')
+            # sort user routines to appear first
+            if 'name' in g and '__user__' in g['name']:
+                uret.append(g)
+            else:
+                gret.append(g)
+        return uret + gret
+    setmesstext(block)
+    if not isinstance(block, dict) and 'block' not in block:
+        raise Exception('postcrack: Expected block dictionary instead of ' +
+                        str(block))
+    if 'name' in block and not block['name'] == 'unknown_interface':
+        outmess(f"{tab}Block: {block['name']}\n", 0)
+    block = analyzeargs(block)
+    block = analyzecommon(block)
+    block['vars'] = analyzevars(block)
+    block['sortvars'] = sortvarnames(block['vars'])
+    if block.get('args'):
+        args = block['args']
+    block['body'] = analyzebody(block, args, tab=tab)
+
+    userisdefined = []
+    if 'use' in block:
+        useblock = block['use']
+        for k in list(useblock.keys()):
+            if '__user__' in k:
+                userisdefined.append(k)
+    else:
+        useblock = {}
+    name = ''
+    if 'name' in block:
+        name = block['name']
+    # and not userisdefined: # Build a __user__ module
+    if block.get('externals'):
+        interfaced = []
+        if 'interfaced' in block:
+            interfaced = block['interfaced']
+        mvars = copy.copy(block['vars'])
+        if name:
+            mname = name + '__user__routines'
+        else:
+            mname = 'unknown__user__routines'
+        if mname in userisdefined:
+            i = 1
+            while f"{mname}_{i}" in userisdefined:
+                i = i + 1
+            mname = f"{mname}_{i}"
+        interface = {'block': 'interface', 'body': [],
+                     'vars': {}, 'name': name + '_user_interface'}
+        for e in block['externals']:
+            if e in interfaced:
+                edef = []
+                j = -1
+                for b in block['body']:
+                    j = j + 1
+                    if b['block'] == 'interface':
+                        i = -1
+                        for bb in b['body']:
+                            i = i + 1
+                            if 'name' in bb and bb['name'] == e:
+                                edef = copy.copy(bb)
+                                del b['body'][i]
+                                break
+                        if edef:
+                            if not b['body']:
+                                del block['body'][j]
+                            del interfaced[interfaced.index(e)]
+                            break
+                interface['body'].append(edef)
+            elif e in mvars and not isexternal(mvars[e]):
+                interface['vars'][e] = mvars[e]
+        if interface['vars'] or interface['body']:
+            block['interfaced'] = interfaced
+            mblock = {'block': 'python module', 'body': [
+                interface], 'vars': {}, 'name': mname, 'interfaced': block['externals']}
+            useblock[mname] = {}
+            usermodules.append(mblock)
+    if useblock:
+        block['use'] = useblock
+    return block
+
+
+def sortvarnames(vars):
+    indep = []
+    dep = []
+    for v in list(vars.keys()):
+        if 'depend' in vars[v] and vars[v]['depend']:
+            dep.append(v)
+        else:
+            indep.append(v)
+    n = len(dep)
+    i = 0
+    while dep:  # XXX: How to catch dependence cycles correctly?
+        v = dep[0]
+        fl = 0
+        for w in dep[1:]:
+            if w in vars[v]['depend']:
+                fl = 1
+                break
+        if fl:
+            dep = dep[1:] + [v]
+            i = i + 1
+            if i > n:
+                errmess('sortvarnames: failed to compute dependencies because'
+                        ' of cyclic dependencies between '
+                        + ', '.join(dep) + '\n')
+                indep = indep + dep
+                break
+        else:
+            indep.append(v)
+            dep = dep[1:]
+            n = len(dep)
+            i = 0
+    return indep
+
+
+def analyzecommon(block):
+    if not hascommon(block):
+        return block
+    commonvars = []
+    for k in list(block['common'].keys()):
+        comvars = []
+        for e in block['common'][k]:
+            m = re.match(
+                r'\A\s*\b(?P<name>.*?)\b\s*(\((?P<dims>.*?)\)|)\s*\Z', e, re.I)
+            if m:
+                dims = []
+                if m.group('dims'):
+                    dims = [x.strip()
+                            for x in markoutercomma(m.group('dims')).split('@,@')]
+                n = rmbadname1(m.group('name').strip())
+                if n in block['vars']:
+                    if 'attrspec' in block['vars'][n]:
+                        block['vars'][n]['attrspec'].append(
+                            f"dimension({','.join(dims)})")
+                    else:
+                        block['vars'][n]['attrspec'] = [
+                            f"dimension({','.join(dims)})"]
+                elif dims:
+                    block['vars'][n] = {
+                        'attrspec': [f"dimension({','.join(dims)})"]}
+                else:
+                    block['vars'][n] = {}
+                if n not in commonvars:
+                    commonvars.append(n)
+            else:
+                n = e
+                errmess(
+                    f'analyzecommon: failed to extract "<name>[(<dims>)]" from "{e}" in common /{k}/.\n')
+            comvars.append(n)
+        block['common'][k] = comvars
+    if 'commonvars' not in block:
+        block['commonvars'] = commonvars
+    else:
+        block['commonvars'] = block['commonvars'] + commonvars
+    return block
+
+
+def analyzebody(block, args, tab=''):
+    global usermodules, skipfuncs, onlyfuncs, f90modulevars
+
+    setmesstext(block)
+
+    maybe_private = {
+        key: value
+        for key, value in block['vars'].items()
+        if 'attrspec' not in value or 'public' not in value['attrspec']
+    }
+
+    body = []
+    for b in block['body']:
+        b['parent_block'] = block
+        if b['block'] in ['function', 'subroutine']:
+            if args is not None and b['name'] not in args:
+                continue
+            else:
+                as_ = b['args']
+            # Add private members to skipfuncs for gh-23879
+            if b['name'] in maybe_private.keys():
+                skipfuncs.append(b['name'])
+            if b['name'] in skipfuncs:
+                continue
+            if onlyfuncs and b['name'] not in onlyfuncs:
+                continue
+            b['saved_interface'] = crack2fortrangen(
+                b, '\n' + ' ' * 6, as_interface=True)
+
+        else:
+            as_ = args
+        b = postcrack(b, as_, tab=tab + '\t')
+        if b['block'] in ['interface', 'abstract interface'] and \
+           not b['body'] and not b.get('implementedby'):
+            if 'f2pyenhancements' not in b:
+                continue
+        if b['block'].replace(' ', '') == 'pythonmodule':
+            usermodules.append(b)
+        else:
+            if b['block'] == 'module':
+                f90modulevars[b['name']] = b['vars']
+            body.append(b)
+    return body
+
+
+def buildimplicitrules(block):
+    setmesstext(block)
+    implicitrules = defaultimplicitrules
+    attrrules = {}
+    if 'implicit' in block:
+        if block['implicit'] is None:
+            implicitrules = None
+            if verbose > 1:
+                outmess(
+                    f"buildimplicitrules: no implicit rules for routine {repr(block['name'])}.\n")
+        else:
+            for k in list(block['implicit'].keys()):
+                if block['implicit'][k].get('typespec') not in ['static', 'automatic']:
+                    implicitrules[k] = block['implicit'][k]
+                else:
+                    attrrules[k] = block['implicit'][k]['typespec']
+    return implicitrules, attrrules
+
+
+def myeval(e, g=None, l=None):
+    """ Like `eval` but returns only integers and floats """
+    r = eval(e, g, l)
+    if type(r) in [int, float]:
+        return r
+    raise ValueError(f'r={r!r}')
+
+
+getlincoef_re_1 = re.compile(r'\A\b\w+\b\Z', re.I)
+
+
+def getlincoef(e, xset):  # e = a*x+b ; x in xset
+    """
+    Obtain ``a`` and ``b`` when ``e == "a*x+b"``, where ``x`` is a symbol in
+    xset.
+
+    >>> getlincoef('2*x + 1', {'x'})
+    (2, 1, 'x')
+    >>> getlincoef('3*x + x*2 + 2 + 1', {'x'})
+    (5, 3, 'x')
+    >>> getlincoef('0', {'x'})
+    (0, 0, None)
+    >>> getlincoef('0*x', {'x'})
+    (0, 0, 'x')
+    >>> getlincoef('x*x', {'x'})
+    (None, None, None)
+
+    This can be tricked by sufficiently complex expressions
+
+    >>> getlincoef('(x - 0.5)*(x - 1.5)*(x - 1)*x + 2*x + 3', {'x'})
+    (2.0, 3.0, 'x')
+    """
+    try:
+        c = int(myeval(e, {}, {}))
+        return 0, c, None
+    except Exception:
+        pass
+    if getlincoef_re_1.match(e):
+        return 1, 0, e
+    len_e = len(e)
+    for x in xset:
+        if len(x) > len_e:
+            continue
+        if re.search(r'\w\s*\([^)]*\b' + x + r'\b', e):
+            # skip function calls having x as an argument, e.g max(1, x)
+            continue
+        re_1 = re.compile(r'(?P<before>.*?)\b' + x + r'\b(?P<after>.*)', re.I)
+        m = re_1.match(e)
+        if m:
+            try:
+                m1 = re_1.match(e)
+                while m1:
+                    ee = f"{m1.group('before')}({0}){m1.group('after')}"
+                    m1 = re_1.match(ee)
+                b = myeval(ee, {}, {})
+                m1 = re_1.match(e)
+                while m1:
+                    ee = f"{m1.group('before')}({1}){m1.group('after')}"
+                    m1 = re_1.match(ee)
+                a = myeval(ee, {}, {}) - b
+                m1 = re_1.match(e)
+                while m1:
+                    ee = f"{m1.group('before')}({0.5}){m1.group('after')}"
+                    m1 = re_1.match(ee)
+                c = myeval(ee, {}, {})
+                # computing another point to be sure that expression is linear
+                m1 = re_1.match(e)
+                while m1:
+                    ee = f"{m1.group('before')}({1.5}){m1.group('after')}"
+                    m1 = re_1.match(ee)
+                c2 = myeval(ee, {}, {})
+                if (a * 0.5 + b == c and a * 1.5 + b == c2):
+                    return a, b, x
+            except Exception:
+                pass
+            break
+    return None, None, None
+
+
+word_pattern = re.compile(r'\b[a-z][\w$]*\b', re.I)
+
+
+def _get_depend_dict(name, vars, deps):
+    if name in vars:
+        words = vars[name].get('depend', [])
+
+        if '=' in vars[name] and not isstring(vars[name]):
+            for word in word_pattern.findall(vars[name]['=']):
+                # The word_pattern may return values that are not
+                # only variables, they can be string content for instance
+                if word not in words and word in vars and word != name:
+                    words.append(word)
+        for word in words[:]:
+            for w in deps.get(word, []) \
+                    or _get_depend_dict(word, vars, deps):
+                if w not in words:
+                    words.append(w)
+    else:
+        outmess(f'_get_depend_dict: no dependence info for {repr(name)}\n')
+        words = []
+    deps[name] = words
+    return words
+
+
+def _calc_depend_dict(vars):
+    names = list(vars.keys())
+    depend_dict = {}
+    for n in names:
+        _get_depend_dict(n, vars, depend_dict)
+    return depend_dict
+
+
+def get_sorted_names(vars):
+    depend_dict = _calc_depend_dict(vars)
+    names = []
+    for name in list(depend_dict.keys()):
+        if not depend_dict[name]:
+            names.append(name)
+            del depend_dict[name]
+    while depend_dict:
+        for name, lst in list(depend_dict.items()):
+            new_lst = [n for n in lst if n in depend_dict]
+            if not new_lst:
+                names.append(name)
+                del depend_dict[name]
+            else:
+                depend_dict[name] = new_lst
+    return [name for name in names if name in vars]
+
+
+def _kind_func(string):
+    # XXX: return something sensible.
+    if string[0] in "'\"":
+        string = string[1:-1]
+    if real16pattern.match(string):
+        return 8
+    elif real8pattern.match(string):
+        return 4
+    return 'kind(' + string + ')'
+
+
+def _selected_int_kind_func(r):
+    # XXX: This should be processor dependent
+    m = 10 ** r
+    if m <= 2 ** 8:
+        return 1
+    if m <= 2 ** 16:
+        return 2
+    if m <= 2 ** 32:
+        return 4
+    if m <= 2 ** 63:
+        return 8
+    if m <= 2 ** 128:
+        return 16
+    return -1
+
+
+def _selected_real_kind_func(p, r=0, radix=0):
+    # XXX: This should be processor dependent
+    # This is only verified for 0 <= p <= 20, possibly good for p <= 33 and above
+    if p < 7:
+        return 4
+    if p < 16:
+        return 8
+    machine = platform.machine().lower()
+    if machine.startswith(('aarch64', 'alpha', 'arm64', 'loongarch', 'mips', 'power', 'ppc', 'riscv', 's390x', 'sparc')):
+        if p <= 33:
+            return 16
+    elif p < 19:
+        return 10
+    elif p <= 33:
+        return 16
+    return -1
+
+
+def get_parameters(vars, global_params={}):
+    params = copy.copy(global_params)
+    g_params = copy.copy(global_params)
+    for name, func in [('kind', _kind_func),
+                       ('selected_int_kind', _selected_int_kind_func),
+                       ('selected_real_kind', _selected_real_kind_func), ]:
+        if name not in g_params:
+            g_params[name] = func
+    param_names = []
+    for n in get_sorted_names(vars):
+        if 'attrspec' in vars[n] and 'parameter' in vars[n]['attrspec']:
+            param_names.append(n)
+    kind_re = re.compile(r'\bkind\s*\(\s*(?P<value>.*)\s*\)', re.I)
+    selected_int_kind_re = re.compile(
+        r'\bselected_int_kind\s*\(\s*(?P<value>.*)\s*\)', re.I)
+    selected_kind_re = re.compile(
+        r'\bselected_(int|real)_kind\s*\(\s*(?P<value>.*)\s*\)', re.I)
+    for n in param_names:
+        if '=' in vars[n]:
+            v = vars[n]['=']
+            if islogical(vars[n]):
+                v = v.lower()
+                for repl in [
+                    ('.false.', 'False'),
+                    ('.true.', 'True'),
+                    # TODO: test .eq., .neq., etc replacements.
+                ]:
+                    v = v.replace(*repl)
+
+            v = kind_re.sub(r'kind("\1")', v)
+            v = selected_int_kind_re.sub(r'selected_int_kind(\1)', v)
+
+            # We need to act according to the data.
+            # The easy case is if the data has a kind-specifier,
+            # then we may easily remove those specifiers.
+            # However, it may be that the user uses other specifiers...(!)
+            is_replaced = False
+
+            if 'kindselector' in vars[n]:
+                # Remove kind specifier (including those defined
+                # by parameters)
+                if 'kind' in vars[n]['kindselector']:
+                    orig_v_len = len(v)
+                    v = v.replace('_' + vars[n]['kindselector']['kind'], '')
+                    # Again, this will be true if even a single specifier
+                    # has been replaced, see comment above.
+                    is_replaced = len(v) < orig_v_len
+
+            if not is_replaced:
+                if not selected_kind_re.match(v):
+                    v_ = v.split('_')
+                    # In case there are additive parameters
+                    if len(v_) > 1:
+                        v = ''.join(v_[:-1]).lower().replace(v_[-1].lower(), '')
+
+            # Currently this will not work for complex numbers.
+            # There is missing code for extracting a complex number,
+            # which may be defined in either of these:
+            #  a) (Re, Im)
+            #  b) cmplx(Re, Im)
+            #  c) dcmplx(Re, Im)
+            #  d) cmplx(Re, Im, <prec>)
+
+            if isdouble(vars[n]):
+                tt = list(v)
+                for m in real16pattern.finditer(v):
+                    tt[m.start():m.end()] = list(
+                        v[m.start():m.end()].lower().replace('d', 'e'))
+                v = ''.join(tt)
+
+            elif iscomplex(vars[n]):
+                outmess(f'get_parameters[TODO]: '
+                        f'implement evaluation of complex expression {v}\n')
+
+            dimspec = ([s.removeprefix('dimension').strip()
+                        for s in vars[n]['attrspec']
+                       if s.startswith('dimension')] or [None])[0]
+
+            # Handle _dp for gh-6624
+            # Also fixes gh-20460
+            if real16pattern.search(v):
+                v = 8
+            elif real8pattern.search(v):
+                v = 4
+            try:
+                params[n] = param_eval(v, g_params, params, dimspec=dimspec)
+            except Exception as msg:
+                params[n] = v
+                outmess(f'get_parameters: got "{msg}" on {n!r}\n')
+
+            if isstring(vars[n]) and isinstance(params[n], int):
+                params[n] = chr(params[n])
+            nl = n.lower()
+            if nl != n:
+                params[nl] = params[n]
+        else:
+            print(vars[n])
+            outmess(f'get_parameters:parameter {n!r} does not have value?!\n')
+    return params
+
+
+def _eval_length(length, params):
+    if length in ['(:)', '(*)', '*']:
+        return '(*)'
+    return _eval_scalar(length, params)
+
+
+_is_kind_number = re.compile(r'\d+_').match
+
+
+def _eval_scalar(value, params):
+    if _is_kind_number(value):
+        value = value.split('_')[0]
+    try:
+        # TODO: use symbolic from PR #19805
+        value = eval(value, {}, params)
+        value = (repr if isinstance(value, str) else str)(value)
+    except (NameError, SyntaxError, TypeError):
+        return value
+    except Exception as msg:
+        errmess('"%s" in evaluating %r '
+                '(available names: %s)\n'
+                % (msg, value, list(params.keys())))
+    return value
+
+
+def analyzevars(block):
+    """
+    Sets correct dimension information for each variable/parameter
+    """
+
+    global f90modulevars
+
+    setmesstext(block)
+    implicitrules, attrrules = buildimplicitrules(block)
+    vars = copy.copy(block['vars'])
+    if block['block'] == 'function' and block['name'] not in vars:
+        vars[block['name']] = {}
+    if '' in block['vars']:
+        del vars['']
+        if 'attrspec' in block['vars']['']:
+            gen = block['vars']['']['attrspec']
+            for n in set(vars) | {b['name'] for b in block['body']}:
+                for k in ['public', 'private']:
+                    if k in gen:
+                        vars[n] = setattrspec(vars.get(n, {}), k)
+    svars = []
+    args = block['args']
+    for a in args:
+        try:
+            vars[a]
+            svars.append(a)
+        except KeyError:
+            pass
+    for n in list(vars.keys()):
+        if n not in args:
+            svars.append(n)
+
+    params = get_parameters(vars, get_useparameters(block))
+    # At this point, params are read and interpreted, but
+    # the params used to define vars are not yet parsed
+    dep_matches = {}
+    name_match = re.compile(r'[A-Za-z][\w$]*').match
+    for v in list(vars.keys()):
+        m = name_match(v)
+        if m:
+            n = v[m.start():m.end()]
+            try:
+                dep_matches[n]
+            except KeyError:
+                dep_matches[n] = re.compile(r'.*\b%s\b' % (v), re.I).match
+    for n in svars:
+        if n[0] in list(attrrules.keys()):
+            vars[n] = setattrspec(vars[n], attrrules[n[0]])
+        if 'typespec' not in vars[n]:
+            if not ('attrspec' in vars[n] and 'external' in vars[n]['attrspec']):
+                if implicitrules:
+                    ln0 = n[0].lower()
+                    for k in list(implicitrules[ln0].keys()):
+                        if k == 'typespec' and implicitrules[ln0][k] == 'undefined':
+                            continue
+                        if k not in vars[n]:
+                            vars[n][k] = implicitrules[ln0][k]
+                        elif k == 'attrspec':
+                            for l in implicitrules[ln0][k]:
+                                vars[n] = setattrspec(vars[n], l)
+                elif n in block['args']:
+                    outmess('analyzevars: typespec of variable %s is not defined in routine %s.\n' % (
+                        repr(n), block['name']))
+        if 'charselector' in vars[n]:
+            if 'len' in vars[n]['charselector']:
+                l = vars[n]['charselector']['len']
+                try:
+                    l = str(eval(l, {}, params))
+                except Exception:
+                    pass
+                vars[n]['charselector']['len'] = l
+
+        if 'kindselector' in vars[n]:
+            if 'kind' in vars[n]['kindselector']:
+                l = vars[n]['kindselector']['kind']
+                try:
+                    l = str(eval(l, {}, params))
+                except Exception:
+                    pass
+                vars[n]['kindselector']['kind'] = l
+
+        dimension_exprs = {}
+        if 'attrspec' in vars[n]:
+            attr = vars[n]['attrspec']
+            attr.reverse()
+            vars[n]['attrspec'] = []
+            dim, intent, depend, check, note = None, None, None, None, None
+            for a in attr:
+                if a[:9] == 'dimension':
+                    dim = (a[9:].strip())[1:-1]
+                elif a[:6] == 'intent':
+                    intent = (a[6:].strip())[1:-1]
+                elif a[:6] == 'depend':
+                    depend = (a[6:].strip())[1:-1]
+                elif a[:5] == 'check':
+                    check = (a[5:].strip())[1:-1]
+                elif a[:4] == 'note':
+                    note = (a[4:].strip())[1:-1]
+                else:
+                    vars[n] = setattrspec(vars[n], a)
+                if intent:
+                    if 'intent' not in vars[n]:
+                        vars[n]['intent'] = []
+                    for c in [x.strip() for x in markoutercomma(intent).split('@,@')]:
+                        # Remove spaces so that 'in out' becomes 'inout'
+                        tmp = c.replace(' ', '')
+                        if tmp not in vars[n]['intent']:
+                            vars[n]['intent'].append(tmp)
+                    intent = None
+                if note:
+                    note = note.replace('\\n\\n', '\n\n')
+                    note = note.replace('\\n ', '\n')
+                    if 'note' not in vars[n]:
+                        vars[n]['note'] = [note]
+                    else:
+                        vars[n]['note'].append(note)
+                    note = None
+                if depend is not None:
+                    if 'depend' not in vars[n]:
+                        vars[n]['depend'] = []
+                    for c in rmbadname([x.strip() for x in markoutercomma(depend).split('@,@')]):
+                        if c not in vars[n]['depend']:
+                            vars[n]['depend'].append(c)
+                    depend = None
+                if check is not None:
+                    if 'check' not in vars[n]:
+                        vars[n]['check'] = []
+                    for c in [x.strip() for x in markoutercomma(check).split('@,@')]:
+                        if c not in vars[n]['check']:
+                            vars[n]['check'].append(c)
+                    check = None
+            if dim and 'dimension' not in vars[n]:
+                vars[n]['dimension'] = []
+                for d in rmbadname(
+                        [x.strip() for x in markoutercomma(dim).split('@,@')]
+                ):
+                    # d is the expression inside the dimension declaration
+                    # Evaluate `d` with respect to params
+                    try:
+                        # the dimension for this variable depends on a
+                        # previously defined parameter
+                        d = param_parse(d, params)
+                    except (ValueError, IndexError, KeyError):
+                        outmess(
+                            'analyzevars: could not parse dimension for '
+                            f'variable {d!r}\n'
+                        )
+
+                    dim_char = ':' if d == ':' else '*'
+                    if d == dim_char:
+                        dl = [dim_char]
+                    else:
+                        dl = markoutercomma(d, ':').split('@:@')
+                    if len(dl) == 2 and '*' in dl:  # e.g. dimension(5:*)
+                        dl = ['*']
+                        d = '*'
+                    if len(dl) == 1 and dl[0] != dim_char:
+                        dl = ['1', dl[0]]
+                    if len(dl) == 2:
+                        d1, d2 = map(symbolic.Expr.parse, dl)
+                        dsize = d2 - d1 + 1
+                        d = dsize.tostring(language=symbolic.Language.C)
+                        # find variables v that define d as a linear
+                        # function, `d == a * v + b`, and store
+                        # coefficients a and b for further analysis.
+                        solver_and_deps = {}
+                        for v in block['vars']:
+                            s = symbolic.as_symbol(v)
+                            if dsize.contains(s):
+                                try:
+                                    a, b = dsize.linear_solve(s)
+
+                                    def solve_v(s, a=a, b=b):
+                                        return (s - b) / a
+
+                                    all_symbols = set(a.symbols())
+                                    all_symbols.update(b.symbols())
+                                except RuntimeError as msg:
+                                    # d is not a linear function of v,
+                                    # however, if v can be determined
+                                    # from d using other means,
+                                    # implement the corresponding
+                                    # solve_v function here.
+                                    solve_v = None
+                                    all_symbols = set(dsize.symbols())
+                                v_deps = {
+                                    s.data for s in all_symbols
+                                    if s.data in vars}
+                                solver_and_deps[v] = solve_v, list(v_deps)
+                        # Note that dsize may contain symbols that are
+                        # not defined in block['vars']. Here we assume
+                        # these correspond to Fortran/C intrinsic
+                        # functions or that are defined by other
+                        # means. We'll let the compiler validate the
+                        # definiteness of such symbols.
+                        dimension_exprs[d] = solver_and_deps
+                    vars[n]['dimension'].append(d)
+
+        if 'check' not in vars[n] and 'args' in block and n in block['args']:
+            # n is an argument that has no checks defined. Here we
+            # generate some consistency checks for n, and when n is an
+            # array, generate checks for its dimensions and construct
+            # initialization expressions.
+            n_deps = vars[n].get('depend', [])
+            n_checks = []
+            n_is_input = l_or(isintent_in, isintent_inout,
+                              isintent_inplace)(vars[n])
+            if isarray(vars[n]):  # n is array
+                for i, d in enumerate(vars[n]['dimension']):
+                    coeffs_and_deps = dimension_exprs.get(d)
+                    if coeffs_and_deps is None:
+                        # d is `:` or `*` or a constant expression
+                        pass
+                    elif n_is_input:
+                        # n is an input array argument and its shape
+                        # may define variables used in dimension
+                        # specifications.
+                        for v, (solver, deps) in coeffs_and_deps.items():
+                            def compute_deps(v, deps):
+                                for v1 in coeffs_and_deps.get(v, [None, []])[1]:
+                                    if v1 not in deps:
+                                        deps.add(v1)
+                                        compute_deps(v1, deps)
+                            all_deps = set()
+                            compute_deps(v, all_deps)
+                            if (v in n_deps
+                                 or '=' in vars[v]
+                                 or 'depend' in vars[v]):
+                                # Skip a variable that
+                                # - n depends on
+                                # - has user-defined initialization expression
+                                # - has user-defined dependencies
+                                continue
+                            if solver is not None and v not in all_deps:
+                                # v can be solved from d, hence, we
+                                # make it an optional argument with
+                                # initialization expression:
+                                is_required = False
+                                init = solver(symbolic.as_symbol(
+                                    f'shape({n}, {i})'))
+                                init = init.tostring(
+                                    language=symbolic.Language.C)
+                                vars[v]['='] = init
+                                # n needs to be initialized before v. So,
+                                # making v dependent on n and on any
+                                # variables in solver or d.
+                                vars[v]['depend'] = [n] + deps
+                                if 'check' not in vars[v]:
+                                    # add check only when no
+                                    # user-specified checks exist
+                                    vars[v]['check'] = [
+                                        f'shape({n}, {i}) == {d}']
+                            else:
+                                # d is a non-linear function on v,
+                                # hence, v must be a required input
+                                # argument that n will depend on
+                                is_required = True
+                                if 'intent' not in vars[v]:
+                                    vars[v]['intent'] = []
+                                if 'in' not in vars[v]['intent']:
+                                    vars[v]['intent'].append('in')
+                                # v needs to be initialized before n
+                                n_deps.append(v)
+                                n_checks.append(
+                                    f'shape({n}, {i}) == {d}')
+                            v_attr = vars[v].get('attrspec', [])
+                            if not ('optional' in v_attr
+                                    or 'required' in v_attr):
+                                v_attr.append(
+                                    'required' if is_required else 'optional')
+                            if v_attr:
+                                vars[v]['attrspec'] = v_attr
+                    if coeffs_and_deps is not None:
+                        # extend v dependencies with ones specified in attrspec
+                        for v, (solver, deps) in coeffs_and_deps.items():
+                            v_deps = vars[v].get('depend', [])
+                            for aa in vars[v].get('attrspec', []):
+                                if aa.startswith('depend'):
+                                    aa = ''.join(aa.split())
+                                    v_deps.extend(aa[7:-1].split(','))
+                            if v_deps:
+                                vars[v]['depend'] = list(set(v_deps))
+                            if n not in v_deps:
+                                n_deps.append(v)
+            elif isstring(vars[n]):
+                if 'charselector' in vars[n]:
+                    if '*' in vars[n]['charselector']:
+                        length = _eval_length(vars[n]['charselector']['*'],
+                                              params)
+                        vars[n]['charselector']['*'] = length
+                    elif 'len' in vars[n]['charselector']:
+                        length = _eval_length(vars[n]['charselector']['len'],
+                                              params)
+                        del vars[n]['charselector']['len']
+                        vars[n]['charselector']['*'] = length
+            if n_checks:
+                vars[n]['check'] = n_checks
+            if n_deps:
+                vars[n]['depend'] = list(set(n_deps))
+
+        if '=' in vars[n]:
+            if 'attrspec' not in vars[n]:
+                vars[n]['attrspec'] = []
+            if ('optional' not in vars[n]['attrspec']) and \
+               ('required' not in vars[n]['attrspec']):
+                vars[n]['attrspec'].append('optional')
+            if 'depend' not in vars[n]:
+                vars[n]['depend'] = []
+                for v, m in list(dep_matches.items()):
+                    if m(vars[n]['=']):
+                        vars[n]['depend'].append(v)
+                if not vars[n]['depend']:
+                    del vars[n]['depend']
+            if isscalar(vars[n]):
+                vars[n]['='] = _eval_scalar(vars[n]['='], params)
+
+    for n in list(vars.keys()):
+        if n == block['name']:  # n is block name
+            if 'note' in vars[n]:
+                block['note'] = vars[n]['note']
+            if block['block'] == 'function':
+                if 'result' in block and block['result'] in vars:
+                    vars[n] = appenddecl(vars[n], vars[block['result']])
+                if 'prefix' in block:
+                    pr = block['prefix']
+                    pr1 = pr.replace('pure', '')
+                    ispure = (not pr == pr1)
+                    pr = pr1.replace('recursive', '')
+                    isrec = (not pr == pr1)
+                    m = typespattern[0].match(pr)
+                    if m:
+                        typespec, selector, attr, edecl = cracktypespec0(
+                            m.group('this'), m.group('after'))
+                        kindselect, charselect, typename = cracktypespec(
+                            typespec, selector)
+                        vars[n]['typespec'] = typespec
+                        try:
+                            if block['result']:
+                                vars[block['result']]['typespec'] = typespec
+                        except Exception:
+                            pass
+                        if kindselect:
+                            if 'kind' in kindselect:
+                                try:
+                                    kindselect['kind'] = eval(
+                                        kindselect['kind'], {}, params)
+                                except Exception:
+                                    pass
+                            vars[n]['kindselector'] = kindselect
+                        if charselect:
+                            vars[n]['charselector'] = charselect
+                        if typename:
+                            vars[n]['typename'] = typename
+                        if ispure:
+                            vars[n] = setattrspec(vars[n], 'pure')
+                        if isrec:
+                            vars[n] = setattrspec(vars[n], 'recursive')
+                    else:
+                        outmess(
+                            f"analyzevars: prefix ({repr(block['prefix'])}) were not used\n")
+    if block['block'] not in ['module', 'pythonmodule', 'python module', 'block data']:
+        if 'commonvars' in block:
+            neededvars = copy.copy(block['args'] + block['commonvars'])
+        else:
+            neededvars = copy.copy(block['args'])
+        for n in list(vars.keys()):
+            if l_or(isintent_callback, isintent_aux)(vars[n]):
+                neededvars.append(n)
+        if 'entry' in block:
+            neededvars.extend(list(block['entry'].keys()))
+            for k in list(block['entry'].keys()):
+                for n in block['entry'][k]:
+                    if n not in neededvars:
+                        neededvars.append(n)
+        if block['block'] == 'function':
+            if 'result' in block:
+                neededvars.append(block['result'])
+            else:
+                neededvars.append(block['name'])
+        if block['block'] in ['subroutine', 'function']:
+            name = block['name']
+            if name in vars and 'intent' in vars[name]:
+                block['intent'] = vars[name]['intent']
+        if block['block'] == 'type':
+            neededvars.extend(list(vars.keys()))
+        for n in list(vars.keys()):
+            if n not in neededvars:
+                del vars[n]
+    return vars
+
+
+analyzeargs_re_1 = re.compile(r'\A[a-z]+[\w$]*\Z', re.I)
+
+
+def param_eval(v, g_params, params, dimspec=None):
+    """
+    Creates a dictionary of indices and values for each parameter in a
+    parameter array to be evaluated later.
+
+    WARNING: It is not possible to initialize multidimensional array
+    parameters e.g. dimension(-3:1, 4, 3:5) at this point. This is because in
+    Fortran initialization through array constructor requires the RESHAPE
+    intrinsic function. Since the right-hand side of the parameter declaration
+    is not executed in f2py, but rather at the compiled c/fortran extension,
+    later, it is not possible to execute a reshape of a parameter array.
+    One issue remains: if the user wants to access the array parameter from
+    python, we should either
+    1) allow them to access the parameter array using python standard indexing
+       (which is often incompatible with the original fortran indexing)
+    2) allow the parameter array to be accessed in python as a dictionary with
+       fortran indices as keys
+    We are choosing 2 for now.
+    """
+    if dimspec is None:
+        try:
+            p = eval(v, g_params, params)
+        except Exception as msg:
+            p = v
+            outmess(f'param_eval: got "{msg}" on {v!r}\n')
+        return p
+
+    # This is an array parameter.
+    # First, we parse the dimension information
+    if len(dimspec) < 2 or dimspec[::len(dimspec) - 1] != "()":
+        raise ValueError(f'param_eval: dimension {dimspec} can\'t be parsed')
+    dimrange = dimspec[1:-1].split(',')
+    if len(dimrange) == 1:
+        # e.g. dimension(2) or dimension(-1:1)
+        dimrange = dimrange[0].split(':')
+        # now, dimrange is a list of 1 or 2 elements
+        if len(dimrange) == 1:
+            bound = param_parse(dimrange[0], params)
+            dimrange = range(1, int(bound) + 1)
+        else:
+            lbound = param_parse(dimrange[0], params)
+            ubound = param_parse(dimrange[1], params)
+            dimrange = range(int(lbound), int(ubound) + 1)
+    else:
+        raise ValueError('param_eval: multidimensional array parameters '
+                         f'{dimspec} not supported')
+
+    # Parse parameter value
+    v = (v[2:-2] if v.startswith('(/') else v).split(',')
+    v_eval = []
+    for item in v:
+        try:
+            item = eval(item, g_params, params)
+        except Exception as msg:
+            outmess(f'param_eval: got "{msg}" on {item!r}\n')
+        v_eval.append(item)
+
+    p = dict(zip(dimrange, v_eval))
+
+    return p
+
+
+def param_parse(d, params):
+    """Recursively parse array dimensions.
+
+    Parses the declaration of an array variable or parameter
+    `dimension` keyword, and is called recursively if the
+    dimension for this array is a previously defined parameter
+    (found in `params`).
+
+    Parameters
+    ----------
+    d : str
+        Fortran expression describing the dimension of an array.
+    params : dict
+        Previously parsed parameters declared in the Fortran source file.
+
+    Returns
+    -------
+    out : str
+        Parsed dimension expression.
+
+    Examples
+    --------
+
+    * If the line being analyzed is
+
+      `integer, parameter, dimension(2) :: pa = (/ 3, 5 /)`
+
+      then `d = 2` and we return immediately, with
+
+    >>> d = '2'
+    >>> param_parse(d, params)
+    2
+
+    * If the line being analyzed is
+
+      `integer, parameter, dimension(pa) :: pb = (/1, 2, 3/)`
+
+      then `d = 'pa'`; since `pa` is a previously parsed parameter,
+      and `pa = 3`, we call `param_parse` recursively, to obtain
+
+    >>> d = 'pa'
+    >>> params = {'pa': 3}
+    >>> param_parse(d, params)
+    3
+
+    * If the line being analyzed is
+
+      `integer, parameter, dimension(pa(1)) :: pb = (/1, 2, 3/)`
+
+      then `d = 'pa(1)'`; since `pa` is a previously parsed parameter,
+      and `pa(1) = 3`, we call `param_parse` recursively, to obtain
+
+    >>> d = 'pa(1)'
+    >>> params = dict(pa={1: 3, 2: 5})
+    >>> param_parse(d, params)
+    3
+    """
+    if "(" in d:
+        # this dimension expression is an array
+        dname = d[:d.find("(")]
+        ddims = d[d.find("(") + 1:d.rfind(")")]
+        # this dimension expression is also a parameter;
+        # parse it recursively
+        index = int(param_parse(ddims, params))
+        return str(params[dname][index])
+    elif d in params:
+        return str(params[d])
+    else:
+        for p in params:
+            re_1 = re.compile(
+                r'(?P<before>.*?)\b' + p + r'\b(?P<after>.*)', re.I
+            )
+            m = re_1.match(d)
+            while m:
+                d = m.group('before') + \
+                    str(params[p]) + m.group('after')
+                m = re_1.match(d)
+        return d
+
+
+def expr2name(a, block, args=[]):
+    orig_a = a
+    a_is_expr = not analyzeargs_re_1.match(a)
+    if a_is_expr:  # `a` is an expression
+        implicitrules, attrrules = buildimplicitrules(block)
+        at = determineexprtype(a, block['vars'], implicitrules)
+        na = 'e_'
+        for c in a:
+            c = c.lower()
+            if c not in string.ascii_lowercase + string.digits:
+                c = '_'
+            na = na + c
+        if na[-1] == '_':
+            na = na + 'e'
+        else:
+            na = na + '_e'
+        a = na
+        while a in block['vars'] or a in block['args']:
+            a = a + 'r'
+    if a in args:
+        k = 1
+        while a + str(k) in args:
+            k = k + 1
+        a = a + str(k)
+    if a_is_expr:
+        block['vars'][a] = at
+    else:
+        if a not in block['vars']:
+            block['vars'][a] = block['vars'].get(orig_a, {})
+        if 'externals' in block and orig_a in block['externals'] + block['interfaced']:
+            block['vars'][a] = setattrspec(block['vars'][a], 'external')
+    return a
+
+
+def analyzeargs(block):
+    setmesstext(block)
+    implicitrules, _ = buildimplicitrules(block)
+    if 'args' not in block:
+        block['args'] = []
+    args = []
+    for a in block['args']:
+        a = expr2name(a, block, args)
+        args.append(a)
+    block['args'] = args
+    if 'entry' in block:
+        for k, args1 in list(block['entry'].items()):
+            for a in args1:
+                if a not in block['vars']:
+                    block['vars'][a] = {}
+
+    for b in block['body']:
+        if b['name'] in args:
+            if 'externals' not in block:
+                block['externals'] = []
+            if b['name'] not in block['externals']:
+                block['externals'].append(b['name'])
+    if 'result' in block and block['result'] not in block['vars']:
+        block['vars'][block['result']] = {}
+    return block
+
+
+determineexprtype_re_1 = re.compile(r'\A\(.+?,.+?\)\Z', re.I)
+determineexprtype_re_2 = re.compile(r'\A[+-]?\d+(_(?P<name>\w+)|)\Z', re.I)
+determineexprtype_re_3 = re.compile(
+    r'\A[+-]?[\d.]+[-\d+de.]*(_(?P<name>\w+)|)\Z', re.I)
+determineexprtype_re_4 = re.compile(r'\A\(.*\)\Z', re.I)
+determineexprtype_re_5 = re.compile(r'\A(?P<name>\w+)\s*\(.*?\)\s*\Z', re.I)
+
+
+def _ensure_exprdict(r):
+    if isinstance(r, int):
+        return {'typespec': 'integer'}
+    if isinstance(r, float):
+        return {'typespec': 'real'}
+    if isinstance(r, complex):
+        return {'typespec': 'complex'}
+    if isinstance(r, dict):
+        return r
+    raise AssertionError(repr(r))
+
+
+def determineexprtype(expr, vars, rules={}):
+    if expr in vars:
+        return _ensure_exprdict(vars[expr])
+    expr = expr.strip()
+    if determineexprtype_re_1.match(expr):
+        return {'typespec': 'complex'}
+    m = determineexprtype_re_2.match(expr)
+    if m:
+        if 'name' in m.groupdict() and m.group('name'):
+            outmess(
+                f'determineexprtype: selected kind types not supported ({repr(expr)})\n')
+        return {'typespec': 'integer'}
+    m = determineexprtype_re_3.match(expr)
+    if m:
+        if 'name' in m.groupdict() and m.group('name'):
+            outmess(
+                f'determineexprtype: selected kind types not supported ({repr(expr)})\n')
+        return {'typespec': 'real'}
+    for op in ['+', '-', '*', '/']:
+        for e in [x.strip() for x in markoutercomma(expr, comma=op).split('@' + op + '@')]:
+            if e in vars:
+                return _ensure_exprdict(vars[e])
+    t = {}
+    if determineexprtype_re_4.match(expr):  # in parenthesis
+        t = determineexprtype(expr[1:-1], vars, rules)
+    else:
+        m = determineexprtype_re_5.match(expr)
+        if m:
+            rn = m.group('name')
+            t = determineexprtype(m.group('name'), vars, rules)
+            if t and 'attrspec' in t:
+                del t['attrspec']
+            if not t:
+                if rn[0] in rules:
+                    return _ensure_exprdict(rules[rn[0]])
+    if expr[0] in '\'"':
+        return {'typespec': 'character', 'charselector': {'*': '*'}}
+    if not t:
+        outmess(
+            f'determineexprtype: could not determine expressions ({repr(expr)}) type.\n')
+    return t
+
+######
+
+
+def crack2fortrangen(block, tab='\n', as_interface=False):
+    global skipfuncs, onlyfuncs
+
+    setmesstext(block)
+    ret = ''
+    if isinstance(block, list):
+        for g in block:
+            if g and g['block'] in ['function', 'subroutine']:
+                if g['name'] in skipfuncs:
+                    continue
+                if onlyfuncs and g['name'] not in onlyfuncs:
+                    continue
+            ret = ret + crack2fortrangen(g, tab, as_interface=as_interface)
+        return ret
+    prefix = ''
+    name = ''
+    args = ''
+    blocktype = block['block']
+    if blocktype == 'program':
+        return ''
+    argsl = []
+    if 'name' in block:
+        name = block['name']
+    if 'args' in block:
+        vars = block['vars']
+        for a in block['args']:
+            a = expr2name(a, block, argsl)
+            if not isintent_callback(vars[a]):
+                argsl.append(a)
+        if block['block'] == 'function' or argsl:
+            args = f"({','.join(argsl)})"
+    f2pyenhancements = ''
+    if 'f2pyenhancements' in block:
+        for k in list(block['f2pyenhancements'].keys()):
+            f2pyenhancements = '%s%s%s %s' % (
+                f2pyenhancements, tab + tabchar, k, block['f2pyenhancements'][k])
+    intent_lst = block.get('intent', [])[:]
+    if blocktype == 'function' and 'callback' in intent_lst:
+        intent_lst.remove('callback')
+    if intent_lst:
+        f2pyenhancements = '%s%sintent(%s) %s' %\
+                           (f2pyenhancements, tab + tabchar,
+                            ','.join(intent_lst), name)
+    use = ''
+    if 'use' in block:
+        use = use2fortran(block['use'], tab + tabchar)
+    common = ''
+    if 'common' in block:
+        common = common2fortran(block['common'], tab + tabchar)
+    if name == 'unknown_interface':
+        name = ''
+    result = ''
+    if 'result' in block:
+        result = f" result ({block['result']})"
+        if block['result'] not in argsl:
+            argsl.append(block['result'])
+    body = crack2fortrangen(block['body'], tab + tabchar, as_interface=as_interface)
+    vars = vars2fortran(
+        block, block['vars'], argsl, tab + tabchar, as_interface=as_interface)
+    mess = ''
+    if 'from' in block and not as_interface:
+        mess = f"! in {block['from']}"
+    if 'entry' in block:
+        entry_stmts = ''
+        for k, i in list(block['entry'].items()):
+            entry_stmts = f"{entry_stmts}{tab + tabchar}entry {k}({','.join(i)})"
+        body = body + entry_stmts
+    if blocktype == 'block data' and name == '_BLOCK_DATA_':
+        name = ''
+    ret = '%s%s%s %s%s%s %s%s%s%s%s%s%send %s %s' % (
+        tab, prefix, blocktype, name, args, result, mess, f2pyenhancements, use, vars, common, body, tab, blocktype, name)
+    return ret
+
+
+def common2fortran(common, tab=''):
+    ret = ''
+    for k in list(common.keys()):
+        if k == '_BLNK_':
+            ret = f"{ret}{tab}common {','.join(common[k])}"
+        else:
+            ret = f"{ret}{tab}common /{k}/ {','.join(common[k])}"
+    return ret
+
+
+def use2fortran(use, tab=''):
+    ret = ''
+    for m in list(use.keys()):
+        ret = f'{ret}{tab}use {m},'
+        if use[m] == {}:
+            if ret and ret[-1] == ',':
+                ret = ret[:-1]
+            continue
+        if 'only' in use[m] and use[m]['only']:
+            ret = f'{ret} only:'
+        if 'map' in use[m] and use[m]['map']:
+            c = ' '
+            for k in list(use[m]['map'].keys()):
+                if k == use[m]['map'][k]:
+                    ret = f'{ret}{c}{k}'
+                    c = ','
+                else:
+                    ret = f"{ret}{c}{k}=>{use[m]['map'][k]}"
+                    c = ','
+        if ret and ret[-1] == ',':
+            ret = ret[:-1]
+    return ret
+
+
+def true_intent_list(var):
+    lst = var['intent']
+    ret = []
+    for intent in lst:
+        try:
+            f = globals()[f'isintent_{intent}']
+        except KeyError:
+            pass
+        else:
+            if f(var):
+                ret.append(intent)
+    return ret
+
+
+def vars2fortran(block, vars, args, tab='', as_interface=False):
+    setmesstext(block)
+    ret = ''
+    nout = []
+    for a in args:
+        if a in block['vars']:
+            nout.append(a)
+    if 'commonvars' in block:
+        for a in block['commonvars']:
+            if a in vars:
+                if a not in nout:
+                    nout.append(a)
+            else:
+                errmess(
+                    f'vars2fortran: Confused?!: "{a}" is not defined in vars.\n')
+    if 'varnames' in block:
+        nout.extend(block['varnames'])
+    if not as_interface:
+        for a in list(vars.keys()):
+            if a not in nout:
+                nout.append(a)
+    for a in nout:
+        if 'depend' in vars[a]:
+            for d in vars[a]['depend']:
+                if d in vars and 'depend' in vars[d] and a in vars[d]['depend']:
+                    errmess(
+                        f'vars2fortran: Warning: cross-dependence between variables "{a}" and "{d}\"\n')
+        if 'externals' in block and a in block['externals']:
+            if isintent_callback(vars[a]):
+                ret = f'{ret}{tab}intent(callback) {a}'
+            ret = f'{ret}{tab}external {a}'
+            if isoptional(vars[a]):
+                ret = f'{ret}{tab}optional {a}'
+            if a in vars and 'typespec' not in vars[a]:
+                continue
+            cont = 1
+            for b in block['body']:
+                if a == b['name'] and b['block'] == 'function':
+                    cont = 0
+                    break
+            if cont:
+                continue
+        if a not in vars:
+            show(vars)
+            outmess(f'vars2fortran: No definition for argument "{a}".\n')
+            continue
+        if a == block['name']:
+            if block['block'] != 'function' or block.get('result'):
+                # 1) skip declaring a variable that name matches with
+                #    subroutine name
+                # 2) skip declaring function when its type is
+                #    declared via `result` construction
+                continue
+        if 'typespec' not in vars[a]:
+            if 'attrspec' in vars[a] and 'external' in vars[a]['attrspec']:
+                if a in args:
+                    ret = f'{ret}{tab}external {a}'
+                continue
+            show(vars[a])
+            outmess(f'vars2fortran: No typespec for argument "{a}".\n')
+            continue
+        vardef = vars[a]['typespec']
+        if vardef == 'type' and 'typename' in vars[a]:
+            vardef = f"{vardef}({vars[a]['typename']})"
+        selector = {}
+        if 'kindselector' in vars[a]:
+            selector = vars[a]['kindselector']
+        elif 'charselector' in vars[a]:
+            selector = vars[a]['charselector']
+        if '*' in selector:
+            if selector['*'] in ['*', ':']:
+                vardef = f"{vardef}*({selector['*']})"
+            else:
+                vardef = f"{vardef}*{selector['*']}"
+        elif 'len' in selector:
+            vardef = f"{vardef}(len={selector['len']}"
+            if 'kind' in selector:
+                vardef = f"{vardef},kind={selector['kind']})"
+            else:
+                vardef = f'{vardef})'
+        elif 'kind' in selector:
+            vardef = f"{vardef}(kind={selector['kind']})"
+        c = ' '
+        if 'attrspec' in vars[a]:
+            attr = [l for l in vars[a]['attrspec']
+                    if l not in ['external']]
+            if as_interface and 'intent(in)' in attr and 'intent(out)' in attr:
+                # In Fortran, intent(in, out) are conflicting while
+                # intent(in, out) can be specified only via
+                # `!f2py intent(out) ..`.
+                # So, for the Fortran interface, we'll drop
+                # intent(out) to resolve the conflict.
+                attr.remove('intent(out)')
+            if attr:
+                vardef = f"{vardef}, {','.join(attr)}"
+                c = ','
+        if 'dimension' in vars[a]:
+            vardef = f"{vardef}{c}dimension({','.join(vars[a]['dimension'])})"
+            c = ','
+        if 'intent' in vars[a]:
+            lst = true_intent_list(vars[a])
+            if lst:
+                vardef = f"{vardef}{c}intent({','.join(lst)})"
+            c = ','
+        if 'check' in vars[a]:
+            vardef = f"{vardef}{c}check({','.join(vars[a]['check'])})"
+            c = ','
+        if 'depend' in vars[a]:
+            vardef = f"{vardef}{c}depend({','.join(vars[a]['depend'])})"
+            c = ','
+        if '=' in vars[a]:
+            v = vars[a]['=']
+            if vars[a]['typespec'] in ['complex', 'double complex']:
+                try:
+                    v = eval(v)
+                    v = f'({v.real},{v.imag})'
+                except Exception:
+                    pass
+            vardef = f'{vardef} :: {a}={v}'
+        else:
+            vardef = f'{vardef} :: {a}'
+        ret = f'{ret}{tab}{vardef}'
+    return ret
+######
+
+
+# We expose post_processing_hooks as global variable so that
+# user-libraries could register their own hooks to f2py.
+post_processing_hooks = []
+
+
+def crackfortran(files):
+    global usermodules, post_processing_hooks
+
+    outmess('Reading fortran codes...\n', 0)
+    readfortrancode(files, crackline)
+    outmess('Post-processing...\n', 0)
+    usermodules = []
+    postlist = postcrack(grouplist[0])
+    outmess('Applying post-processing hooks...\n', 0)
+    for hook in post_processing_hooks:
+        outmess(f'  {hook.__name__}\n', 0)
+        postlist = traverse(postlist, hook)
+    outmess('Post-processing (stage 2)...\n', 0)
+    postlist = postcrack2(postlist)
+    return usermodules + postlist
+
+
+def crack2fortran(block):
+    global f2py_version
+
+    pyf = crack2fortrangen(block) + '\n'
+    header = """!    -*- f90 -*-
+! Note: the context of this file is case sensitive.
+"""
+    footer = """
+! This file was auto-generated with f2py (version:%s).
+! See:
+! https://web.archive.org/web/20140822061353/http://cens.ioc.ee/projects/f2py2e
+""" % (f2py_version)
+    return header + pyf + footer
+
+
+def _is_visit_pair(obj):
+    return (isinstance(obj, tuple)
+            and len(obj) == 2
+            and isinstance(obj[0], (int, str)))
+
+
+def traverse(obj, visit, parents=[], result=None, *args, **kwargs):
+    '''Traverse f2py data structure with the following visit function:
+
+    def visit(item, parents, result, *args, **kwargs):
+        """
+
+        parents is a list of key-"f2py data structure" pairs from which
+        items are taken from.
+
+        result is a f2py data structure that is filled with the
+        return value of the visit function.
+
+        item is 2-tuple (index, value) if parents[-1][1] is a list
+        item is 2-tuple (key, value) if parents[-1][1] is a dict
+
+        The return value of visit must be None, or of the same kind as
+        item, that is, if parents[-1] is a list, the return value must
+        be 2-tuple (new_index, new_value), or if parents[-1] is a
+        dict, the return value must be 2-tuple (new_key, new_value).
+
+        If new_index or new_value is None, the return value of visit
+        is ignored, that is, it will not be added to the result.
+
+        If the return value is None, the content of obj will be
+        traversed, otherwise not.
+        """
+    '''
+
+    if _is_visit_pair(obj):
+        if obj[0] == 'parent_block':
+            # avoid infinite recursion
+            return obj
+        new_result = visit(obj, parents, result, *args, **kwargs)
+        if new_result is not None:
+            assert _is_visit_pair(new_result)
+            return new_result
+        parent = obj
+        result_key, obj = obj
+    else:
+        parent = (None, obj)
+        result_key = None
+
+    if isinstance(obj, list):
+        new_result = []
+        for index, value in enumerate(obj):
+            new_index, new_item = traverse((index, value), visit,
+                                           parents + [parent], result,
+                                           *args, **kwargs)
+            if new_index is not None:
+                new_result.append(new_item)
+    elif isinstance(obj, dict):
+        new_result = {}
+        for key, value in obj.items():
+            new_key, new_value = traverse((key, value), visit,
+                                          parents + [parent], result,
+                                          *args, **kwargs)
+            if new_key is not None:
+                new_result[new_key] = new_value
+    else:
+        new_result = obj
+
+    if result_key is None:
+        return new_result
+    return result_key, new_result
+
+
+def character_backward_compatibility_hook(item, parents, result,
+                                          *args, **kwargs):
+    """Previously, Fortran character was incorrectly treated as
+    character*1. This hook fixes the usage of the corresponding
+    variables in `check`, `dimension`, `=`, and `callstatement`
+    expressions.
+
+    The usage of `char*` in `callprotoargument` expression can be left
+    unchanged because C `character` is C typedef of `char`, although,
+    new implementations should use `character*` in the corresponding
+    expressions.
+
+    See https://github.com/numpy/numpy/pull/19388 for more information.
+
+    """
+    parent_key, parent_value = parents[-1]
+    key, value = item
+
+    def fix_usage(varname, value):
+        value = re.sub(r'[*]\s*\b' + varname + r'\b', varname, value)
+        value = re.sub(r'\b' + varname + r'\b\s*[\[]\s*0\s*[\]]',
+                       varname, value)
+        return value
+
+    if parent_key in ['dimension', 'check']:
+        assert parents[-3][0] == 'vars'
+        vars_dict = parents[-3][1]
+    elif key == '=':
+        assert parents[-2][0] == 'vars'
+        vars_dict = parents[-2][1]
+    else:
+        vars_dict = None
+
+    new_value = None
+    if vars_dict is not None:
+        new_value = value
+        for varname, vd in vars_dict.items():
+            if ischaracter(vd):
+                new_value = fix_usage(varname, new_value)
+    elif key == 'callstatement':
+        vars_dict = parents[-2][1]['vars']
+        new_value = value
+        for varname, vd in vars_dict.items():
+            if ischaracter(vd):
+                # replace all occurrences of `<varname>` with
+                # `&<varname>` in argument passing
+                new_value = re.sub(
+                    r'(?<![&])\b' + varname + r'\b', '&' + varname, new_value)
+
+    if new_value is not None:
+        if new_value != value:
+            # We report the replacements here so that downstream
+            # software could update their source codes
+            # accordingly. However, such updates are recommended only
+            # when BC with numpy 1.21 or older is not required.
+            outmess(f'character_bc_hook[{parent_key}.{key}]:'
+                    f' replaced `{value}` -> `{new_value}`\n', 1)
+        return (key, new_value)
+
+
+post_processing_hooks.append(character_backward_compatibility_hook)
+
+
+if __name__ == "__main__":
+    files = []
+    funcs = []
+    f = 1
+    f2 = 0
+    f3 = 0
+    showblocklist = 0
+    for l in sys.argv[1:]:
+        if l == '':
+            pass
+        elif l[0] == ':':
+            f = 0
+        elif l == '-quiet':
+            quiet = 1
+            verbose = 0
+        elif l == '-verbose':
+            verbose = 2
+            quiet = 0
+        elif l == '-fix':
+            if strictf77:
+                outmess(
+                    'Use option -f90 before -fix if Fortran 90 code is in fix form.\n', 0)
+            skipemptyends = 1
+            sourcecodeform = 'fix'
+        elif l == '-skipemptyends':
+            skipemptyends = 1
+        elif l == '--ignore-contains':
+            ignorecontains = 1
+        elif l == '-f77':
+            strictf77 = 1
+            sourcecodeform = 'fix'
+        elif l == '-f90':
+            strictf77 = 0
+            sourcecodeform = 'free'
+            skipemptyends = 1
+        elif l == '-h':
+            f2 = 1
+        elif l == '-show':
+            showblocklist = 1
+        elif l == '-m':
+            f3 = 1
+        elif l[0] == '-':
+            errmess(f'Unknown option {repr(l)}\n')
+        elif f2:
+            f2 = 0
+            pyffilename = l
+        elif f3:
+            f3 = 0
+            f77modulename = l
+        elif f:
+            try:
+                open(l).close()
+                files.append(l)
+            except OSError as detail:
+                errmess(f'OSError: {detail!s}\n')
+        else:
+            funcs.append(l)
+    if not strictf77 and f77modulename and not skipemptyends:
+        outmess("""\
+  Warning: You have specified module name for non Fortran 77 code that
+  should not need one (expect if you are scanning F90 code for non
+  module blocks but then you should use flag -skipemptyends and also
+  be sure that the files do not contain programs without program
+  statement).
+""", 0)
+
+    postlist = crackfortran(files)
+    if pyffilename:
+        outmess(f'Writing fortran code to file {repr(pyffilename)}\n', 0)
+        pyf = crack2fortran(postlist)
+        with open(pyffilename, 'w') as f:
+            f.write(pyf)
+    if showblocklist:
+        show(postlist)
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..4d51a4d9594834ece7d12f2b5d8c2fdf33e0feba
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/crackfortran.pyi
@@ -0,0 +1,266 @@
+import re
+from _typeshed import StrOrBytesPath, StrPath
+from collections.abc import Callable, Iterable, Mapping
+from typing import (
+    IO,
+    Any,
+    Concatenate,
+    Final,
+    Literal as L,
+    Never,
+    ParamSpec,
+    TypeAlias,
+    overload,
+)
+
+from .__version__ import version
+from .auxfuncs import isintent_dict as isintent_dict
+
+###
+
+_Tss = ParamSpec("_Tss")
+
+_VisitResult: TypeAlias = list[Any] | dict[str, Any] | None
+_VisitItem: TypeAlias = tuple[str | None, _VisitResult]
+_VisitFunc: TypeAlias = Callable[Concatenate[_VisitItem, list[_VisitItem], _VisitResult, _Tss], _VisitItem | None]
+
+###
+
+COMMON_FREE_EXTENSIONS: Final[list[str]] = ...
+COMMON_FIXED_EXTENSIONS: Final[list[str]] = ...
+
+f2py_version: Final = version
+tabchar: Final[str] = "    "
+
+f77modulename: str
+pyffilename: str
+sourcecodeform: L["fix", "gree"]
+strictf77: L[0, 1]
+quiet: L[0, 1]
+verbose: L[0, 1, 2]
+skipemptyends: L[0, 1]
+ignorecontains: L[1]
+dolowercase: L[1]
+
+beginpattern: str | re.Pattern[str]
+currentfilename: str
+filepositiontext: str
+expectbegin: L[0, 1]
+gotnextfile: L[0, 1]
+neededmodule: int
+skipblocksuntil: int
+groupcounter: int
+groupname: dict[int, str] | str
+groupcache: dict[int, dict[str, Any]] | None
+grouplist: dict[int, list[dict[str, Any]]] | None
+previous_context: tuple[str, str, int] | None
+
+f90modulevars: dict[str, dict[str, Any]] = {}
+debug: list[Never] = []
+include_paths: list[str] = []
+onlyfuncs: list[str] = []
+skipfuncs: list[str] = []
+skipfunctions: Final[list[str]] = []
+usermodules: Final[list[dict[str, Any]]] = []
+
+defaultimplicitrules: Final[dict[str, dict[str, str]]] = {}
+badnames: Final[dict[str, str]] = {}
+invbadnames: Final[dict[str, str]] = {}
+
+beforethisafter: Final[str] = ...
+fortrantypes: Final[str] = ...
+groupbegins77: Final[str] = ...
+groupbegins90: Final[str] = ...
+groupends: Final[str] = ...
+endifs: Final[str] = ...
+moduleprocedures: Final[str] = ...
+
+beginpattern77: Final[tuple[re.Pattern[str], L["begin"]]] = ...
+beginpattern90: Final[tuple[re.Pattern[str], L["begin"]]] = ...
+callpattern: Final[tuple[re.Pattern[str], L["call"]]] = ...
+callfunpattern: Final[tuple[re.Pattern[str], L["callfun"]]] = ...
+commonpattern: Final[tuple[re.Pattern[str], L["common"]]] = ...
+containspattern: Final[tuple[re.Pattern[str], L["contains"]]] = ...
+datapattern: Final[tuple[re.Pattern[str], L["data"]]] = ...
+dimensionpattern: Final[tuple[re.Pattern[str], L["dimension"]]] = ...
+endifpattern: Final[tuple[re.Pattern[str], L["endif"]]] = ...
+endpattern: Final[tuple[re.Pattern[str], L["end"]]] = ...
+entrypattern: Final[tuple[re.Pattern[str], L["entry"]]] = ...
+externalpattern: Final[tuple[re.Pattern[str], L["external"]]] = ...
+f2pyenhancementspattern: Final[tuple[re.Pattern[str], L["f2pyenhancements"]]] = ...
+formatpattern: Final[tuple[re.Pattern[str], L["format"]]] = ...
+functionpattern: Final[tuple[re.Pattern[str], L["begin"]]] = ...
+implicitpattern: Final[tuple[re.Pattern[str], L["implicit"]]] = ...
+intentpattern: Final[tuple[re.Pattern[str], L["intent"]]] = ...
+intrinsicpattern: Final[tuple[re.Pattern[str], L["intrinsic"]]] = ...
+optionalpattern: Final[tuple[re.Pattern[str], L["optional"]]] = ...
+moduleprocedurepattern: Final[tuple[re.Pattern[str], L["moduleprocedure"]]] = ...
+multilinepattern: Final[tuple[re.Pattern[str], L["multiline"]]] = ...
+parameterpattern: Final[tuple[re.Pattern[str], L["parameter"]]] = ...
+privatepattern: Final[tuple[re.Pattern[str], L["private"]]] = ...
+publicpattern: Final[tuple[re.Pattern[str], L["public"]]] = ...
+requiredpattern: Final[tuple[re.Pattern[str], L["required"]]] = ...
+subroutinepattern: Final[tuple[re.Pattern[str], L["begin"]]] = ...
+typespattern: Final[tuple[re.Pattern[str], L["type"]]] = ...
+usepattern: Final[tuple[re.Pattern[str], L["use"]]] = ...
+
+analyzeargs_re_1: Final[re.Pattern[str]] = ...
+callnameargspattern: Final[re.Pattern[str]] = ...
+charselector: Final[re.Pattern[str]] = ...
+crackline_bind_1: Final[re.Pattern[str]] = ...
+crackline_bindlang: Final[re.Pattern[str]] = ...
+crackline_re_1: Final[re.Pattern[str]] = ...
+determineexprtype_re_1: Final[re.Pattern[str]] = ...
+determineexprtype_re_2: Final[re.Pattern[str]] = ...
+determineexprtype_re_3: Final[re.Pattern[str]] = ...
+determineexprtype_re_4: Final[re.Pattern[str]] = ...
+determineexprtype_re_5: Final[re.Pattern[str]] = ...
+getlincoef_re_1: Final[re.Pattern[str]] = ...
+kindselector: Final[re.Pattern[str]] = ...
+lenarraypattern: Final[re.Pattern[str]] = ...
+lenkindpattern: Final[re.Pattern[str]] = ...
+namepattern: Final[re.Pattern[str]] = ...
+nameargspattern: Final[re.Pattern[str]] = ...
+operatorpattern: Final[re.Pattern[str]] = ...
+real16pattern: Final[re.Pattern[str]] = ...
+real8pattern: Final[re.Pattern[str]] = ...
+selectpattern: Final[re.Pattern[str]] = ...
+typedefpattern: Final[re.Pattern[str]] = ...
+typespattern4implicit: Final[re.Pattern[str]] = ...
+word_pattern: Final[re.Pattern[str]] = ...
+
+post_processing_hooks: Final[list[_VisitFunc[...]]] = []
+
+#
+def outmess(line: str, flag: int = 1) -> None: ...
+def reset_global_f2py_vars() -> None: ...
+
+#
+def rmbadname1(name: str) -> str: ...
+def undo_rmbadname1(name: str) -> str: ...
+def rmbadname(names: Iterable[str]) -> list[str]: ...
+def undo_rmbadname(names: Iterable[str]) -> list[str]: ...
+
+#
+def openhook(filename: StrPath, mode: str) -> IO[Any]: ...
+def is_free_format(fname: StrPath) -> bool: ...
+def readfortrancode(
+    ffile: StrOrBytesPath | Iterable[StrOrBytesPath],
+    dowithline: Callable[[str, int], object] = ...,
+    istop: int = 1,
+) -> None: ...
+
+#
+def split_by_unquoted(line: str, characters: str) -> tuple[str, str]: ...
+
+#
+def crackline(line: str, reset: int = 0) -> None: ...
+def markouterparen(line: str) -> str: ...
+def markoutercomma(line: str, comma: str = ",") -> str: ...
+def unmarkouterparen(line: str) -> str: ...
+def appenddecl(decl: Mapping[str, object] | None, decl2: Mapping[str, object] | None, force: int = 1) -> dict[str, Any]: ...
+
+#
+def parse_name_for_bind(line: str) -> tuple[str, str | None]: ...
+def analyzeline(m: re.Match[str], case: str, line: str) -> None: ...
+def appendmultiline(group: dict[str, Any], context_name: str, ml: str) -> None: ...
+def cracktypespec0(typespec: str, ll: str | None) -> tuple[str, str | None, str | None, str | None]: ...
+
+#
+def removespaces(expr: str) -> str: ...
+def markinnerspaces(line: str) -> str: ...
+def updatevars(typespec: str, selector: str | None, attrspec: str, entitydecl: str) -> str: ...
+def cracktypespec(typespec: str, selector: str | None) -> tuple[dict[str, str] | None, dict[str, str] | None, str | None]: ...
+
+#
+def setattrspec(decl: dict[str, list[str]], attr: str | None, force: int = 0) -> dict[str, list[str]]: ...
+def setkindselector(decl: dict[str, dict[str, str]], sel: dict[str, str], force: int = 0) -> dict[str, dict[str, str]]: ...
+def setcharselector(decl: dict[str, dict[str, str]], sel: dict[str, str], force: int = 0) -> dict[str, dict[str, str]]: ...
+def getblockname(block: Mapping[str, object], unknown: str = "unknown") -> str: ...
+def setmesstext(block: Mapping[str, object]) -> None: ...
+def get_usedict(block: Mapping[str, object]) -> dict[str, str]: ...
+def get_useparameters(block: Mapping[str, object], param_map: Mapping[str, str] | None = None) -> dict[str, str]: ...
+
+#
+@overload
+def postcrack2(
+    block: dict[str, Any],
+    tab: str = "",
+    param_map: Mapping[str, str] | None = None,
+) -> dict[str, str | Any]: ...
+@overload
+def postcrack2(
+    block: list[dict[str, Any]],
+    tab: str = "",
+    param_map: Mapping[str, str] | None = None,
+) -> list[dict[str, str | Any]]: ...
+
+#
+@overload
+def postcrack(block: dict[str, Any], args: Mapping[str, str] | None = None, tab: str = "") -> dict[str, Any]: ...
+@overload
+def postcrack(block: list[dict[str, str]], args: Mapping[str, str] | None = None, tab: str = "") -> list[dict[str, Any]]: ...
+
+#
+def sortvarnames(vars: Mapping[str, object]) -> list[str]: ...
+def analyzecommon(block: Mapping[str, object]) -> dict[str, Any]: ...
+def analyzebody(block: Mapping[str, object], args: Mapping[str, str], tab: str = "") -> list[dict[str, Any]]: ...
+def buildimplicitrules(block: Mapping[str, object]) -> tuple[dict[str, dict[str, str]], dict[str, str]]: ...
+def myeval(e: str, g: object | None = None, l: object | None = None) -> float: ...
+
+#
+def getlincoef(e: str, xset: set[str]) -> tuple[float | None, float | None, str | None]: ...
+
+#
+def get_sorted_names(vars: Mapping[str, Mapping[str, str]]) -> list[str]: ...
+def get_parameters(vars: Mapping[str, Mapping[str, str]], global_params: dict[str, str] = {}) -> dict[str, str]: ...
+
+#
+def analyzevars(block: Mapping[str, Any]) -> dict[str, dict[str, str]]: ...
+
+#
+def param_eval(v: str, g_params: dict[str, Any], params: Mapping[str, object], dimspec: str | None = None) -> dict[str, Any]: ...
+def param_parse(d: str, params: Mapping[str, str]) -> str: ...
+def expr2name(a: str, block: Mapping[str, object], args: list[str] = []) -> str: ...
+def analyzeargs(block: Mapping[str, object]) -> dict[str, Any]: ...
+
+#
+def determineexprtype(expr: str, vars: Mapping[str, object], rules: dict[str, Any] = {}) -> dict[str, Any]: ...
+def crack2fortrangen(block: Mapping[str, object], tab: str = "\n", as_interface: bool = False) -> str: ...
+def common2fortran(common: Mapping[str, object], tab: str = "") -> str: ...
+def use2fortran(use: Mapping[str, object], tab: str = "") -> str: ...
+def true_intent_list(var: dict[str, list[str]]) -> list[str]: ...
+def vars2fortran(
+    block: Mapping[str, Mapping[str, object]],
+    vars: Mapping[str, object],
+    args: Mapping[str, str],
+    tab: str = "",
+    as_interface: bool = False,
+) -> str: ...
+
+#
+def crackfortran(files: StrOrBytesPath | Iterable[StrOrBytesPath]) -> list[dict[str, Any]]: ...
+def crack2fortran(block: Mapping[str, Any]) -> str: ...
+
+#
+def traverse(
+    obj: tuple[str | None, _VisitResult],
+    visit: _VisitFunc[_Tss],
+    parents: list[tuple[str | None, _VisitResult]] = [],
+    result: list[Any] | dict[str, Any] | None = None,
+    *args: _Tss.args,
+    **kwargs: _Tss.kwargs,
+) -> _VisitItem | _VisitResult: ...
+
+#
+def character_backward_compatibility_hook(
+    item: _VisitItem,
+    parents: list[_VisitItem],
+    result: object,  # ignored
+    *args: object,  # ignored
+    **kwargs: object,  # ignored
+) -> _VisitItem | None: ...
+
+# namespace pollution
+c: str
+n: str
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.py b/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b8045c0c9d9b18ce55d492826893e95a0c87c7f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.py
@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+import os
+import sys
+import tempfile
+
+
+def run():
+    _path = os.getcwd()
+    os.chdir(tempfile.gettempdir())
+    print('------')
+    print(f'os.name={os.name!r}')
+    print('------')
+    print(f'sys.platform={sys.platform!r}')
+    print('------')
+    print('sys.version:')
+    print(sys.version)
+    print('------')
+    print('sys.prefix:')
+    print(sys.prefix)
+    print('------')
+    print(f"sys.path={':'.join(sys.path)!r}")
+    print('------')
+
+    try:
+        import numpy
+        has_newnumpy = 1
+    except ImportError as e:
+        print('Failed to import new numpy:', e)
+        has_newnumpy = 0
+
+    try:
+        from numpy.f2py import f2py2e
+        has_f2py2e = 1
+    except ImportError as e:
+        print('Failed to import f2py2e:', e)
+        has_f2py2e = 0
+
+    try:
+        import numpy.distutils
+        has_numpy_distutils = 2
+    except ImportError:
+        try:
+            import numpy_distutils
+            has_numpy_distutils = 1
+        except ImportError as e:
+            print('Failed to import numpy_distutils:', e)
+            has_numpy_distutils = 0
+
+    if has_newnumpy:
+        try:
+            print(f'Found new numpy version {numpy.__version__!r} in {numpy.__file__}')
+        except Exception as msg:
+            print('error:', msg)
+            print('------')
+
+    if has_f2py2e:
+        try:
+            print('Found f2py2e version %r in %s' %
+                  (f2py2e.__version__.version, f2py2e.__file__))
+        except Exception as msg:
+            print('error:', msg)
+            print('------')
+
+    if has_numpy_distutils:
+        try:
+            if has_numpy_distutils == 2:
+                print('Found numpy.distutils version %r in %r' % (
+                    numpy.distutils.__version__,
+                    numpy.distutils.__file__))
+            else:
+                print('Found numpy_distutils version %r in %r' % (
+                    numpy_distutils.numpy_distutils_version.numpy_distutils_version,
+                    numpy_distutils.__file__))
+            print('------')
+        except Exception as msg:
+            print('error:', msg)
+            print('------')
+        try:
+            if has_numpy_distutils == 1:
+                print(
+                    'Importing numpy_distutils.command.build_flib ...', end=' ')
+                import numpy_distutils.command.build_flib as build_flib
+                print('ok')
+                print('------')
+                try:
+                    print(
+                        'Checking availability of supported Fortran compilers:')
+                    for compiler_class in build_flib.all_compilers:
+                        compiler_class(verbose=1).is_available()
+                        print('------')
+                except Exception as msg:
+                    print('error:', msg)
+                    print('------')
+        except Exception as msg:
+            print(
+                'error:', msg, '(ignore it, build_flib is obsolete for numpy.distutils 0.2.2 and up)')
+            print('------')
+        try:
+            if has_numpy_distutils == 2:
+                print('Importing numpy.distutils.fcompiler ...', end=' ')
+                import numpy.distutils.fcompiler as fcompiler
+            else:
+                print('Importing numpy_distutils.fcompiler ...', end=' ')
+                import numpy_distutils.fcompiler as fcompiler
+            print('ok')
+            print('------')
+            try:
+                print('Checking availability of supported Fortran compilers:')
+                fcompiler.show_fcompilers()
+                print('------')
+            except Exception as msg:
+                print('error:', msg)
+                print('------')
+        except Exception as msg:
+            print('error:', msg)
+            print('------')
+        try:
+            if has_numpy_distutils == 2:
+                print('Importing numpy.distutils.cpuinfo ...', end=' ')
+                from numpy.distutils.cpuinfo import cpuinfo
+                print('ok')
+                print('------')
+            else:
+                try:
+                    print(
+                        'Importing numpy_distutils.command.cpuinfo ...', end=' ')
+                    from numpy_distutils.command.cpuinfo import cpuinfo
+                    print('ok')
+                    print('------')
+                except Exception as msg:
+                    print('error:', msg, '(ignore it)')
+                    print('Importing numpy_distutils.cpuinfo ...', end=' ')
+                    from numpy_distutils.cpuinfo import cpuinfo
+                    print('ok')
+                    print('------')
+            cpu = cpuinfo()
+            print('CPU information:', end=' ')
+            for name in dir(cpuinfo):
+                if name[0] == '_' and name[1] != '_' and getattr(cpu, name[1:])():
+                    print(name[1:], end=' ')
+            print('------')
+        except Exception as msg:
+            print('error:', msg)
+            print('------')
+    os.chdir(_path)
+
+
+if __name__ == "__main__":
+    run()
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..a01716406e010e9b12d804bf60ca5a53df61c661
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/diagnose.pyi
@@ -0,0 +1 @@
+def run() -> None: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.py b/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.py
new file mode 100644
index 0000000000000000000000000000000000000000..a239f1e9a90d48ab60edbfa01056c75bc4775e25
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.py
@@ -0,0 +1,788 @@
+"""
+
+f2py2e - Fortran to Python C/API generator. 2nd Edition.
+         See __usage__ below.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+import argparse
+import os
+import pprint
+import re
+import sys
+
+from numpy.f2py._backends import f2py_build_generator
+
+from . import (
+    __version__,
+    auxfuncs,
+    capi_maps,
+    cb_rules,
+    cfuncs,
+    crackfortran,
+    f90mod_rules,
+    rules,
+)
+from .cfuncs import errmess
+
+f2py_version = __version__.version
+numpy_version = __version__.version
+
+# outmess=sys.stdout.write
+show = pprint.pprint
+outmess = auxfuncs.outmess
+MESON_ONLY_VER = (sys.version_info >= (3, 12))
+
+__usage__ =\
+f"""Usage:
+
+1) To construct extension module sources:
+
+      f2py [<options>] <fortran files> [[[only:]||[skip:]] \\
+                                        <fortran functions> ] \\
+                                       [: <fortran files> ...]
+
+2) To compile fortran files and build extension modules:
+
+      f2py -c [<options>, <build_flib options>, <extra options>] <fortran files>
+
+3) To generate signature files:
+
+      f2py -h <filename.pyf> ...< same options as in (1) >
+
+Description: This program generates a Python C/API file (<modulename>module.c)
+             that contains wrappers for given fortran functions so that they
+             can be called from Python. With the -c option the corresponding
+             extension modules are built.
+
+Options:
+
+  -h <filename>    Write signatures of the fortran routines to file <filename>
+                   and exit. You can then edit <filename> and use it instead
+                   of <fortran files>. If <filename>==stdout then the
+                   signatures are printed to stdout.
+  <fortran functions>  Names of fortran routines for which Python C/API
+                   functions will be generated. Default is all that are found
+                   in <fortran files>.
+  <fortran files>  Paths to fortran/signature files that will be scanned for
+                   <fortran functions> in order to determine their signatures.
+  skip:            Ignore fortran functions that follow until `:'.
+  only:            Use only fortran functions that follow until `:'.
+  :                Get back to <fortran files> mode.
+
+  -m <modulename>  Name of the module; f2py generates a Python/C API
+                   file <modulename>module.c or extension module <modulename>.
+                   Default is 'untitled'.
+
+  '-include<header>'  Writes additional headers in the C wrapper, can be passed
+                      multiple times, generates #include <header> each time.
+
+  --[no-]lower     Do [not] lower the cases in <fortran files>. By default,
+                   --lower is assumed with -h key, and --no-lower without -h key.
+
+  --build-dir <dirname>  All f2py generated files are created in <dirname>.
+                   Default is tempfile.mkdtemp().
+
+  --overwrite-signature  Overwrite existing signature file.
+
+  --[no-]latex-doc Create (or not) <modulename>module.tex.
+                   Default is --no-latex-doc.
+  --short-latex    Create 'incomplete' LaTeX document (without commands
+                   \\documentclass, \\tableofcontents, and \\begin{{document}},
+                   \\end{{document}}).
+
+  --[no-]rest-doc Create (or not) <modulename>module.rst.
+                   Default is --no-rest-doc.
+
+  --debug-capi     Create C/API code that reports the state of the wrappers
+                   during runtime. Useful for debugging.
+
+  --[no-]wrap-functions    Create Fortran subroutine wrappers to Fortran 77
+                   functions. --wrap-functions is default because it ensures
+                   maximum portability/compiler independence.
+
+  --[no-]freethreading-compatible    Create a module that declares it does or
+                   doesn't require the GIL. The default is
+                   --freethreading-compatible for backward
+                   compatibility. Inspect the Fortran code you are wrapping for
+                   thread safety issues before passing
+                   --no-freethreading-compatible, as f2py does not analyze
+                   fortran code for thread safety issues.
+
+  --include-paths <path1>:<path2>:...   Search include files from the given
+                   directories.
+
+  --help-link [..] List system resources found by system_info.py. See also
+                   --link-<resource> switch below. [..] is optional list
+                   of resources names. E.g. try 'f2py --help-link lapack_opt'.
+
+  --f2cmap <filename>  Load Fortran-to-Python KIND specification from the given
+                   file. Default: .f2py_f2cmap in current directory.
+
+  --quiet          Run quietly.
+  --verbose        Run with extra verbosity.
+  --skip-empty-wrappers   Only generate wrapper files when needed.
+  -v               Print f2py version ID and exit.
+
+
+build backend options (only effective with -c)
+[NO_MESON] is used to indicate an option not meant to be used
+with the meson backend or above Python 3.12:
+
+  --fcompiler=         Specify Fortran compiler type by vendor [NO_MESON]
+  --compiler=          Specify distutils C compiler type [NO_MESON]
+
+  --help-fcompiler     List available Fortran compilers and exit [NO_MESON]
+  --f77exec=           Specify the path to F77 compiler [NO_MESON]
+  --f90exec=           Specify the path to F90 compiler [NO_MESON]
+  --f77flags=          Specify F77 compiler flags
+  --f90flags=          Specify F90 compiler flags
+  --opt=               Specify optimization flags [NO_MESON]
+  --arch=              Specify architecture specific optimization flags [NO_MESON]
+  --noopt              Compile without optimization [NO_MESON]
+  --noarch             Compile without arch-dependent optimization [NO_MESON]
+  --debug              Compile with debugging information
+
+  --dep                <dependency>
+                       Specify a meson dependency for the module. This may
+                       be passed multiple times for multiple dependencies.
+                       Dependencies are stored in a list for further processing.
+
+                       Example: --dep lapack --dep scalapack
+                       This will identify "lapack" and "scalapack" as dependencies
+                       and remove them from argv, leaving a dependencies list
+                       containing ["lapack", "scalapack"].
+
+  --backend            <backend_type>
+                       Specify the build backend for the compilation process.
+                       The supported backends are 'meson' and 'distutils'.
+                       If not specified, defaults to 'distutils'. On
+                       Python 3.12 or higher, the default is 'meson'.
+
+Extra options (only effective with -c):
+
+  --link-<resource>    Link extension module with <resource> as defined
+                       by numpy.distutils/system_info.py. E.g. to link
+                       with optimized LAPACK libraries (vecLib on MacOSX,
+                       ATLAS elsewhere), use --link-lapack_opt.
+                       See also --help-link switch. [NO_MESON]
+
+  -L/path/to/lib/ -l<libname>
+  -D<define> -U<name>
+  -I/path/to/include/
+  <filename>.o <filename>.so <filename>.a
+
+  Using the following macros may be required with non-gcc Fortran
+  compilers:
+    -DPREPEND_FORTRAN -DNO_APPEND_FORTRAN -DUPPERCASE_FORTRAN
+
+  When using -DF2PY_REPORT_ATEXIT, a performance report of F2PY
+  interface is printed out at exit (platforms: Linux).
+
+  When using -DF2PY_REPORT_ON_ARRAY_COPY=<int>, a message is
+  sent to stderr whenever F2PY interface makes a copy of an
+  array. Integer <int> sets the threshold for array sizes when
+  a message should be shown.
+
+Version:     {f2py_version}
+numpy Version: {numpy_version}
+License:     NumPy license (see LICENSE.txt in the NumPy source code)
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+https://numpy.org/doc/stable/f2py/index.html\n"""
+
+
+def scaninputline(inputline):
+    files, skipfuncs, onlyfuncs, debug = [], [], [], []
+    f, f2, f3, f5, f6, f8, f9, f10 = 1, 0, 0, 0, 0, 0, 0, 0
+    verbose = 1
+    emptygen = True
+    dolc = -1
+    dolatexdoc = 0
+    dorestdoc = 0
+    wrapfuncs = 1
+    buildpath = '.'
+    include_paths, freethreading_compatible, inputline = get_newer_options(inputline)
+    signsfile, modulename = None, None
+    options = {'buildpath': buildpath,
+               'coutput': None,
+               'f2py_wrapper_output': None}
+    for l in inputline:
+        if l == '':
+            pass
+        elif l == 'only:':
+            f = 0
+        elif l == 'skip:':
+            f = -1
+        elif l == ':':
+            f = 1
+        elif l[:8] == '--debug-':
+            debug.append(l[8:])
+        elif l == '--lower':
+            dolc = 1
+        elif l == '--build-dir':
+            f6 = 1
+        elif l == '--no-lower':
+            dolc = 0
+        elif l == '--quiet':
+            verbose = 0
+        elif l == '--verbose':
+            verbose += 1
+        elif l == '--latex-doc':
+            dolatexdoc = 1
+        elif l == '--no-latex-doc':
+            dolatexdoc = 0
+        elif l == '--rest-doc':
+            dorestdoc = 1
+        elif l == '--no-rest-doc':
+            dorestdoc = 0
+        elif l == '--wrap-functions':
+            wrapfuncs = 1
+        elif l == '--no-wrap-functions':
+            wrapfuncs = 0
+        elif l == '--short-latex':
+            options['shortlatex'] = 1
+        elif l == '--coutput':
+            f8 = 1
+        elif l == '--f2py-wrapper-output':
+            f9 = 1
+        elif l == '--f2cmap':
+            f10 = 1
+        elif l == '--overwrite-signature':
+            options['h-overwrite'] = 1
+        elif l == '-h':
+            f2 = 1
+        elif l == '-m':
+            f3 = 1
+        elif l[:2] == '-v':
+            print(f2py_version)
+            sys.exit()
+        elif l == '--show-compilers':
+            f5 = 1
+        elif l[:8] == '-include':
+            cfuncs.outneeds['userincludes'].append(l[9:-1])
+            cfuncs.userincludes[l[9:-1]] = '#include ' + l[8:]
+        elif l == '--skip-empty-wrappers':
+            emptygen = False
+        elif l[0] == '-':
+            errmess(f'Unknown option {repr(l)}\n')
+            sys.exit()
+        elif f2:
+            f2 = 0
+            signsfile = l
+        elif f3:
+            f3 = 0
+            modulename = l
+        elif f6:
+            f6 = 0
+            buildpath = l
+        elif f8:
+            f8 = 0
+            options["coutput"] = l
+        elif f9:
+            f9 = 0
+            options["f2py_wrapper_output"] = l
+        elif f10:
+            f10 = 0
+            options["f2cmap_file"] = l
+        elif f == 1:
+            try:
+                with open(l):
+                    pass
+                files.append(l)
+            except OSError as detail:
+                errmess(f'OSError: {detail!s}. Skipping file "{l!s}".\n')
+        elif f == -1:
+            skipfuncs.append(l)
+        elif f == 0:
+            onlyfuncs.append(l)
+    if not f5 and not files and not modulename:
+        print(__usage__)
+        sys.exit()
+    if not os.path.isdir(buildpath):
+        if not verbose:
+            outmess(f'Creating build directory {buildpath}\n')
+        os.mkdir(buildpath)
+    if signsfile:
+        signsfile = os.path.join(buildpath, signsfile)
+    if signsfile and os.path.isfile(signsfile) and 'h-overwrite' not in options:
+        errmess(
+            f'Signature file "{signsfile}" exists!!! Use --overwrite-signature to overwrite.\n')
+        sys.exit()
+
+    options['emptygen'] = emptygen
+    options['debug'] = debug
+    options['verbose'] = verbose
+    if dolc == -1 and not signsfile:
+        options['do-lower'] = 0
+    else:
+        options['do-lower'] = dolc
+    if modulename:
+        options['module'] = modulename
+    if signsfile:
+        options['signsfile'] = signsfile
+    if onlyfuncs:
+        options['onlyfuncs'] = onlyfuncs
+    if skipfuncs:
+        options['skipfuncs'] = skipfuncs
+    options['dolatexdoc'] = dolatexdoc
+    options['dorestdoc'] = dorestdoc
+    options['wrapfuncs'] = wrapfuncs
+    options['buildpath'] = buildpath
+    options['include_paths'] = include_paths
+    options['requires_gil'] = not freethreading_compatible
+    options.setdefault('f2cmap_file', None)
+    return files, options
+
+
+def callcrackfortran(files, options):
+    rules.options = options
+    crackfortran.debug = options['debug']
+    crackfortran.verbose = options['verbose']
+    if 'module' in options:
+        crackfortran.f77modulename = options['module']
+    if 'skipfuncs' in options:
+        crackfortran.skipfuncs = options['skipfuncs']
+    if 'onlyfuncs' in options:
+        crackfortran.onlyfuncs = options['onlyfuncs']
+    crackfortran.include_paths[:] = options['include_paths']
+    crackfortran.dolowercase = options['do-lower']
+    postlist = crackfortran.crackfortran(files)
+    if 'signsfile' in options:
+        outmess(f"Saving signatures to file \"{options['signsfile']}\"\n")
+        pyf = crackfortran.crack2fortran(postlist)
+        if options['signsfile'][-6:] == 'stdout':
+            sys.stdout.write(pyf)
+        else:
+            with open(options['signsfile'], 'w') as f:
+                f.write(pyf)
+    if options["coutput"] is None:
+        for mod in postlist:
+            mod["coutput"] = f"{mod['name']}module.c"
+    else:
+        for mod in postlist:
+            mod["coutput"] = options["coutput"]
+    if options["f2py_wrapper_output"] is None:
+        for mod in postlist:
+            mod["f2py_wrapper_output"] = f"{mod['name']}-f2pywrappers.f"
+    else:
+        for mod in postlist:
+            mod["f2py_wrapper_output"] = options["f2py_wrapper_output"]
+    for mod in postlist:
+        if options["requires_gil"]:
+            mod['gil_used'] = 'Py_MOD_GIL_USED'
+        else:
+            mod['gil_used'] = 'Py_MOD_GIL_NOT_USED'
+    # gh-26718 Reset global
+    crackfortran.f77modulename = ''
+    return postlist
+
+
+def buildmodules(lst):
+    cfuncs.buildcfuncs()
+    outmess('Building modules...\n')
+    modules, mnames, isusedby = [], [], {}
+    for item in lst:
+        if '__user__' in item['name']:
+            cb_rules.buildcallbacks(item)
+        else:
+            if 'use' in item:
+                for u in item['use'].keys():
+                    if u not in isusedby:
+                        isusedby[u] = []
+                    isusedby[u].append(item['name'])
+            modules.append(item)
+            mnames.append(item['name'])
+    ret = {}
+    for module, name in zip(modules, mnames):
+        if name in isusedby:
+            outmess('\tSkipping module "%s" which is used by %s.\n' % (
+                name, ','.join('"%s"' % s for s in isusedby[name])))
+        else:
+            um = []
+            if 'use' in module:
+                for u in module['use'].keys():
+                    if u in isusedby and u in mnames:
+                        um.append(modules[mnames.index(u)])
+                    else:
+                        outmess(
+                            f'\tModule "{name}" uses nonexisting "{u}" '
+                            'which will be ignored.\n')
+            ret[name] = {}
+            dict_append(ret[name], rules.buildmodule(module, um))
+    return ret
+
+
+def dict_append(d_out, d_in):
+    for (k, v) in d_in.items():
+        if k not in d_out:
+            d_out[k] = []
+        if isinstance(v, list):
+            d_out[k] = d_out[k] + v
+        else:
+            d_out[k].append(v)
+
+
+def run_main(comline_list):
+    """
+    Equivalent to running::
+
+        f2py <args>
+
+    where ``<args>=string.join(<list>,' ')``, but in Python.  Unless
+    ``-h`` is used, this function returns a dictionary containing
+    information on generated modules and their dependencies on source
+    files.
+
+    You cannot build extension modules with this function, that is,
+    using ``-c`` is not allowed. Use the ``compile`` command instead.
+
+    Examples
+    --------
+    The command ``f2py -m scalar scalar.f`` can be executed from Python as
+    follows.
+
+    .. literalinclude:: ../../source/f2py/code/results/run_main_session.dat
+        :language: python
+
+    """
+    crackfortran.reset_global_f2py_vars()
+    f2pydir = os.path.dirname(os.path.abspath(cfuncs.__file__))
+    fobjhsrc = os.path.join(f2pydir, 'src', 'fortranobject.h')
+    fobjcsrc = os.path.join(f2pydir, 'src', 'fortranobject.c')
+    # gh-22819 -- begin
+    parser = make_f2py_compile_parser()
+    args, comline_list = parser.parse_known_args(comline_list)
+    pyf_files, _ = filter_files("", "[.]pyf([.]src|)", comline_list)
+    # Checks that no existing modulename is defined in a pyf file
+    # TODO: Remove all this when scaninputline is replaced
+    if args.module_name:
+        if "-h" in comline_list:
+            modname = (
+                args.module_name
+            )  # Directly use from args when -h is present
+        else:
+            modname = validate_modulename(
+                pyf_files, args.module_name
+            )  # Validate modname when -h is not present
+        comline_list += ['-m', modname]  # needed for the rest of scaninputline
+    # gh-22819 -- end
+    files, options = scaninputline(comline_list)
+    auxfuncs.options = options
+    capi_maps.load_f2cmap_file(options['f2cmap_file'])
+    postlist = callcrackfortran(files, options)
+    isusedby = {}
+    for plist in postlist:
+        if 'use' in plist:
+            for u in plist['use'].keys():
+                if u not in isusedby:
+                    isusedby[u] = []
+                isusedby[u].append(plist['name'])
+    for plist in postlist:
+        module_name = plist['name']
+        if plist['block'] == 'python module' and '__user__' in module_name:
+            if module_name in isusedby:
+                # if not quiet:
+                usedby = ','.join(f'"{s}"' for s in isusedby[module_name])
+                outmess(
+                    f'Skipping Makefile build for module "{module_name}" '
+                    f'which is used by {usedby}\n')
+    if 'signsfile' in options:
+        if options['verbose'] > 1:
+            outmess(
+                'Stopping. Edit the signature file and then run f2py on the signature file: ')
+            outmess(f"{os.path.basename(sys.argv[0])} {options['signsfile']}\n")
+        return
+    for plist in postlist:
+        if plist['block'] != 'python module':
+            if 'python module' not in options:
+                errmess(
+                    'Tip: If your original code is Fortran source then you must use -m option.\n')
+            raise TypeError('All blocks must be python module blocks but got %s' % (
+                repr(plist['block'])))
+    auxfuncs.debugoptions = options['debug']
+    f90mod_rules.options = options
+    auxfuncs.wrapfuncs = options['wrapfuncs']
+
+    ret = buildmodules(postlist)
+
+    for mn in ret.keys():
+        dict_append(ret[mn], {'csrc': fobjcsrc, 'h': fobjhsrc})
+    return ret
+
+
+def filter_files(prefix, suffix, files, remove_prefix=None):
+    """
+    Filter files by prefix and suffix.
+    """
+    filtered, rest = [], []
+    match = re.compile(prefix + r'.*' + suffix + r'\Z').match
+    if remove_prefix:
+        ind = len(prefix)
+    else:
+        ind = 0
+    for file in [x.strip() for x in files]:
+        if match(file):
+            filtered.append(file[ind:])
+        else:
+            rest.append(file)
+    return filtered, rest
+
+
+def get_prefix(module):
+    p = os.path.dirname(os.path.dirname(module.__file__))
+    return p
+
+
+class CombineIncludePaths(argparse.Action):
+    def __call__(self, parser, namespace, values, option_string=None):
+        include_paths_set = set(getattr(namespace, 'include_paths', []) or [])
+        if option_string == "--include_paths":
+            outmess("Use --include-paths or -I instead of --include_paths which will be removed")
+        if option_string in {"--include-paths", "--include_paths"}:
+            include_paths_set.update(values.split(':'))
+        else:
+            include_paths_set.add(values)
+        namespace.include_paths = list(include_paths_set)
+
+def f2py_parser():
+    parser = argparse.ArgumentParser(add_help=False)
+    parser.add_argument("-I", dest="include_paths", action=CombineIncludePaths)
+    parser.add_argument("--include-paths", dest="include_paths", action=CombineIncludePaths)
+    parser.add_argument("--include_paths", dest="include_paths", action=CombineIncludePaths)
+    parser.add_argument("--freethreading-compatible", dest="ftcompat", action=argparse.BooleanOptionalAction)
+    return parser
+
+def get_newer_options(iline):
+    iline = (' '.join(iline)).split()
+    parser = f2py_parser()
+    args, remain = parser.parse_known_args(iline)
+    ipaths = args.include_paths
+    if args.include_paths is None:
+        ipaths = []
+    return ipaths, args.ftcompat, remain
+
+def make_f2py_compile_parser():
+    parser = argparse.ArgumentParser(add_help=False)
+    parser.add_argument("--dep", action="append", dest="dependencies")
+    parser.add_argument("--backend", choices=['meson', 'distutils'], default='distutils')
+    parser.add_argument("-m", dest="module_name")
+    return parser
+
+def preparse_sysargv():
+    # To keep backwards bug compatibility, newer flags are handled by argparse,
+    # and `sys.argv` is passed to the rest of `f2py` as is.
+    parser = make_f2py_compile_parser()
+
+    args, remaining_argv = parser.parse_known_args()
+    sys.argv = [sys.argv[0]] + remaining_argv
+
+    backend_key = args.backend
+    if MESON_ONLY_VER and backend_key == 'distutils':
+        outmess("Cannot use distutils backend with Python>=3.12,"
+                " using meson backend instead.\n")
+        backend_key = "meson"
+
+    return {
+        "dependencies": args.dependencies or [],
+        "backend": backend_key,
+        "modulename": args.module_name,
+    }
+
+def run_compile():
+    """
+    Do it all in one call!
+    """
+    import tempfile
+
+    # Collect dependency flags, preprocess sys.argv
+    argy = preparse_sysargv()
+    modulename = argy["modulename"]
+    if modulename is None:
+        modulename = 'untitled'
+    dependencies = argy["dependencies"]
+    backend_key = argy["backend"]
+    build_backend = f2py_build_generator(backend_key)
+
+    i = sys.argv.index('-c')
+    del sys.argv[i]
+
+    remove_build_dir = 0
+    try:
+        i = sys.argv.index('--build-dir')
+    except ValueError:
+        i = None
+    if i is not None:
+        build_dir = sys.argv[i + 1]
+        del sys.argv[i + 1]
+        del sys.argv[i]
+    else:
+        remove_build_dir = 1
+        build_dir = tempfile.mkdtemp()
+
+    _reg1 = re.compile(r'--link-')
+    sysinfo_flags = [_m for _m in sys.argv[1:] if _reg1.match(_m)]
+    sys.argv = [_m for _m in sys.argv if _m not in sysinfo_flags]
+    if sysinfo_flags:
+        sysinfo_flags = [f[7:] for f in sysinfo_flags]
+
+    _reg2 = re.compile(
+        r'--((no-|)(wrap-functions|lower|freethreading-compatible)|debug-capi|quiet|skip-empty-wrappers)|-include')
+    f2py_flags = [_m for _m in sys.argv[1:] if _reg2.match(_m)]
+    sys.argv = [_m for _m in sys.argv if _m not in f2py_flags]
+    f2py_flags2 = []
+    fl = 0
+    for a in sys.argv[1:]:
+        if a in ['only:', 'skip:']:
+            fl = 1
+        elif a == ':':
+            fl = 0
+        if fl or a == ':':
+            f2py_flags2.append(a)
+    if f2py_flags2 and f2py_flags2[-1] != ':':
+        f2py_flags2.append(':')
+    f2py_flags.extend(f2py_flags2)
+    sys.argv = [_m for _m in sys.argv if _m not in f2py_flags2]
+    _reg3 = re.compile(
+        r'--((f(90)?compiler(-exec|)|compiler)=|help-compiler)')
+    flib_flags = [_m for _m in sys.argv[1:] if _reg3.match(_m)]
+    sys.argv = [_m for _m in sys.argv if _m not in flib_flags]
+    # TODO: Once distutils is dropped completely, i.e. min_ver >= 3.12, unify into --fflags
+    reg_f77_f90_flags = re.compile(r'--f(77|90)flags=')
+    reg_distutils_flags = re.compile(r'--((f(77|90)exec|opt|arch)=|(debug|noopt|noarch|help-fcompiler))')
+    fc_flags = [_m for _m in sys.argv[1:] if reg_f77_f90_flags.match(_m)]
+    distutils_flags = [_m for _m in sys.argv[1:] if reg_distutils_flags.match(_m)]
+    if not (MESON_ONLY_VER or backend_key == 'meson'):
+        fc_flags.extend(distutils_flags)
+    sys.argv = [_m for _m in sys.argv if _m not in (fc_flags + distutils_flags)]
+
+    del_list = []
+    for s in flib_flags:
+        v = '--fcompiler='
+        if s[:len(v)] == v:
+            if MESON_ONLY_VER or backend_key == 'meson':
+                outmess(
+                    "--fcompiler cannot be used with meson,"
+                    "set compiler with the FC environment variable\n"
+                    )
+            else:
+                from numpy.distutils import fcompiler
+                fcompiler.load_all_fcompiler_classes()
+                allowed_keys = list(fcompiler.fcompiler_class.keys())
+                nv = ov = s[len(v):].lower()
+                if ov not in allowed_keys:
+                    vmap = {}  # XXX
+                    try:
+                        nv = vmap[ov]
+                    except KeyError:
+                        if ov not in vmap.values():
+                            print(f'Unknown vendor: "{s[len(v):]}"')
+                    nv = ov
+                i = flib_flags.index(s)
+                flib_flags[i] = '--fcompiler=' + nv  # noqa: B909
+                continue
+    for s in del_list:
+        i = flib_flags.index(s)
+        del flib_flags[i]
+    assert len(flib_flags) <= 2, repr(flib_flags)
+
+    _reg5 = re.compile(r'--(verbose)')
+    setup_flags = [_m for _m in sys.argv[1:] if _reg5.match(_m)]
+    sys.argv = [_m for _m in sys.argv if _m not in setup_flags]
+
+    if '--quiet' in f2py_flags:
+        setup_flags.append('--quiet')
+
+    # Ugly filter to remove everything but sources
+    sources = sys.argv[1:]
+    f2cmapopt = '--f2cmap'
+    if f2cmapopt in sys.argv:
+        i = sys.argv.index(f2cmapopt)
+        f2py_flags.extend(sys.argv[i:i + 2])
+        del sys.argv[i + 1], sys.argv[i]
+        sources = sys.argv[1:]
+
+    pyf_files, _sources = filter_files("", "[.]pyf([.]src|)", sources)
+    sources = pyf_files + _sources
+    modulename = validate_modulename(pyf_files, modulename)
+    extra_objects, sources = filter_files('', '[.](o|a|so|dylib)', sources)
+    library_dirs, sources = filter_files('-L', '', sources, remove_prefix=1)
+    libraries, sources = filter_files('-l', '', sources, remove_prefix=1)
+    undef_macros, sources = filter_files('-U', '', sources, remove_prefix=1)
+    define_macros, sources = filter_files('-D', '', sources, remove_prefix=1)
+    for i in range(len(define_macros)):
+        name_value = define_macros[i].split('=', 1)
+        if len(name_value) == 1:
+            name_value.append(None)
+        if len(name_value) == 2:
+            define_macros[i] = tuple(name_value)
+        else:
+            print('Invalid use of -D:', name_value)
+
+    # Construct wrappers / signatures / things
+    if backend_key == 'meson':
+        if not pyf_files:
+            outmess('Using meson backend\nWill pass --lower to f2py\nSee https://numpy.org/doc/stable/f2py/buildtools/meson.html\n')
+            f2py_flags.append('--lower')
+            run_main(f" {' '.join(f2py_flags)} -m {modulename} {' '.join(sources)}".split())
+        else:
+            run_main(f" {' '.join(f2py_flags)} {' '.join(pyf_files)}".split())
+
+    # Order matters here, includes are needed for run_main above
+    include_dirs, _, sources = get_newer_options(sources)
+    # Now use the builder
+    builder = build_backend(
+        modulename,
+        sources,
+        extra_objects,
+        build_dir,
+        include_dirs,
+        library_dirs,
+        libraries,
+        define_macros,
+        undef_macros,
+        f2py_flags,
+        sysinfo_flags,
+        fc_flags,
+        flib_flags,
+        setup_flags,
+        remove_build_dir,
+        {"dependencies": dependencies},
+    )
+
+    builder.compile()
+
+
+def validate_modulename(pyf_files, modulename='untitled'):
+    if len(pyf_files) > 1:
+        raise ValueError("Only one .pyf file per call")
+    if pyf_files:
+        pyff = pyf_files[0]
+        pyf_modname = auxfuncs.get_f2py_modulename(pyff)
+        if modulename != pyf_modname:
+            outmess(
+                f"Ignoring -m {modulename}.\n"
+                f"{pyff} defines {pyf_modname} to be the modulename.\n"
+            )
+            modulename = pyf_modname
+    return modulename
+
+def main():
+    if '--help-link' in sys.argv[1:]:
+        sys.argv.remove('--help-link')
+        if MESON_ONLY_VER:
+            outmess("Use --dep for meson builds\n")
+        else:
+            from numpy.distutils.system_info import show_all
+            show_all()
+        return
+
+    if '-c' in sys.argv[1:]:
+        run_compile()
+    else:
+        run_main(sys.argv[1:])
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..ee16cca9321c038fc7a72aedbdc3923bc33fea56
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/f2py2e.pyi
@@ -0,0 +1,74 @@
+import argparse
+import pprint
+from collections.abc import Hashable, Iterable, Mapping, MutableMapping, Sequence
+from types import ModuleType
+from typing import Any, Final, NotRequired, TypedDict, type_check_only
+from typing_extensions import TypeVar, override
+
+from .__version__ import version
+from .auxfuncs import _Bool, outmess as outmess
+
+###
+
+_KT = TypeVar("_KT", bound=Hashable)
+_VT = TypeVar("_VT")
+
+@type_check_only
+class _F2PyDict(TypedDict):
+    csrc: list[str]
+    h: list[str]
+    fsrc: NotRequired[list[str]]
+    ltx: NotRequired[list[str]]
+
+@type_check_only
+class _PreparseResult(TypedDict):
+    dependencies: list[str]
+    backend: str
+    modulename: str
+
+###
+
+MESON_ONLY_VER: Final[bool]
+f2py_version: Final = version
+numpy_version: Final = version
+__usage__: Final[str]
+
+show = pprint.pprint
+
+class CombineIncludePaths(argparse.Action):
+    @override
+    def __call__(
+        self,
+        /,
+        parser: argparse.ArgumentParser,
+        namespace: argparse.Namespace,
+        values: str | Sequence[str] | None,
+        option_string: str | None = None,
+    ) -> None: ...
+
+#
+def run_main(comline_list: Iterable[str]) -> dict[str, _F2PyDict]: ...
+def run_compile() -> None: ...
+def main() -> None: ...
+
+#
+def scaninputline(inputline: Iterable[str]) -> tuple[list[str], dict[str, _Bool]]: ...
+def callcrackfortran(files: list[str], options: dict[str, bool]) -> list[dict[str, Any]]: ...
+def buildmodules(lst: Iterable[Mapping[str, object]]) -> dict[str, dict[str, Any]]: ...
+def dict_append(d_out: MutableMapping[_KT, _VT], d_in: Mapping[_KT, _VT]) -> None: ...
+def filter_files(
+    prefix: str,
+    suffix: str,
+    files: Iterable[str],
+    remove_prefix: _Bool | None = None,
+) -> tuple[list[str], list[str]]: ...
+def get_prefix(module: ModuleType) -> str: ...
+def get_newer_options(iline: Iterable[str]) -> tuple[list[str], Any, list[str]]: ...
+
+#
+def f2py_parser() -> argparse.ArgumentParser: ...
+def make_f2py_compile_parser() -> argparse.ArgumentParser: ...
+
+#
+def preparse_sysargv() -> _PreparseResult: ...
+def validate_modulename(pyf_files: Sequence[str], modulename: str = "untitled") -> str: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.py b/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.py
new file mode 100644
index 0000000000000000000000000000000000000000..85c1399e80548d7440b6dddd69a9c67e5e27bf84
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.py
@@ -0,0 +1,269 @@
+"""
+Build F90 module support for f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+__version__ = "$Revision: 1.27 $"[10:-1]
+
+f2py_version = 'See `f2py -v`'
+
+import numpy as np
+
+from . import capi_maps, func2subr
+
+# The environment provided by auxfuncs.py is needed for some calls to eval.
+# As the needed functions cannot be determined by static inspection of the
+# code, it is safest to use import * pending a major refactoring of f2py.
+from .auxfuncs import *
+from .crackfortran import undo_rmbadname, undo_rmbadname1
+
+options = {}
+
+
+def findf90modules(m):
+    if ismodule(m):
+        return [m]
+    if not hasbody(m):
+        return []
+    ret = []
+    for b in m['body']:
+        if ismodule(b):
+            ret.append(b)
+        else:
+            ret = ret + findf90modules(b)
+    return ret
+
+
+fgetdims1 = """\
+      external f2pysetdata
+      logical ns
+      integer r,i
+      integer(%d) s(*)
+      ns = .FALSE.
+      if (allocated(d)) then
+         do i=1,r
+            if ((size(d,i).ne.s(i)).and.(s(i).ge.0)) then
+               ns = .TRUE.
+            end if
+         end do
+         if (ns) then
+            deallocate(d)
+         end if
+      end if
+      if ((.not.allocated(d)).and.(s(1).ge.1)) then""" % np.intp().itemsize
+
+fgetdims2 = """\
+      end if
+      if (allocated(d)) then
+         do i=1,r
+            s(i) = size(d,i)
+         end do
+      end if
+      flag = 1
+      call f2pysetdata(d,allocated(d))"""
+
+fgetdims2_sa = """\
+      end if
+      if (allocated(d)) then
+         do i=1,r
+            s(i) = size(d,i)
+         end do
+         !s(r) must be equal to len(d(1))
+      end if
+      flag = 2
+      call f2pysetdata(d,allocated(d))"""
+
+
+def buildhooks(pymod):
+    from . import rules
+    ret = {'f90modhooks': [], 'initf90modhooks': [], 'body': [],
+           'need': ['F_FUNC', 'arrayobject.h'],
+           'separatorsfor': {'includes0': '\n', 'includes': '\n'},
+           'docs': ['"Fortran 90/95 modules:\\n"'],
+           'latexdoc': []}
+    fhooks = ['']
+
+    def fadd(line, s=fhooks):
+        s[0] = f'{s[0]}\n      {line}'
+    doc = ['']
+
+    def dadd(line, s=doc):
+        s[0] = f'{s[0]}\n{line}'
+
+    usenames = getuseblocks(pymod)
+    for m in findf90modules(pymod):
+        sargs, fargs, efargs, modobjs, notvars, onlyvars = [], [], [], [], [
+            m['name']], []
+        sargsp = []
+        ifargs = []
+        mfargs = []
+        if hasbody(m):
+            for b in m['body']:
+                notvars.append(b['name'])
+        for n in m['vars'].keys():
+            var = m['vars'][n]
+
+            if (n not in notvars and isvariable(var)) and (not l_or(isintent_hide, isprivate)(var)):
+                onlyvars.append(n)
+                mfargs.append(n)
+        outmess(f"\t\tConstructing F90 module support for \"{m['name']}\"...\n")
+        if len(onlyvars) == 0 and len(notvars) == 1 and m['name'] in notvars:
+            outmess(f"\t\t\tSkipping {m['name']} since there are no public vars/func in this module...\n")
+            continue
+
+        # gh-25186
+        if m['name'] in usenames and containscommon(m):
+            outmess(f"\t\t\tSkipping {m['name']} since it is in 'use' and contains a common block...\n")
+            continue
+        # skip modules with derived types
+        if m['name'] in usenames and containsderivedtypes(m):
+            outmess(f"\t\t\tSkipping {m['name']} since it is in 'use' and contains a derived type...\n")
+            continue
+        if onlyvars:
+            outmess(f"\t\t  Variables: {' '.join(onlyvars)}\n")
+        chooks = ['']
+
+        def cadd(line, s=chooks):
+            s[0] = f'{s[0]}\n{line}'
+        ihooks = ['']
+
+        def iadd(line, s=ihooks):
+            s[0] = f'{s[0]}\n{line}'
+
+        vrd = capi_maps.modsign2map(m)
+        cadd('static FortranDataDef f2py_%s_def[] = {' % (m['name']))
+        dadd('\\subsection{Fortran 90/95 module \\texttt{%s}}\n' % (m['name']))
+        if hasnote(m):
+            note = m['note']
+            if isinstance(note, list):
+                note = '\n'.join(note)
+            dadd(note)
+        if onlyvars:
+            dadd('\\begin{description}')
+        for n in onlyvars:
+            var = m['vars'][n]
+            modobjs.append(n)
+            ct = capi_maps.getctype(var)
+            at = capi_maps.c2capi_map[ct]
+            dm = capi_maps.getarrdims(n, var)
+            dms = dm['dims'].replace('*', '-1').strip()
+            dms = dms.replace(':', '-1').strip()
+            if not dms:
+                dms = '-1'
+            use_fgetdims2 = fgetdims2
+            cadd('\t{"%s",%s,{{%s}},%s, %s},' %
+                 (undo_rmbadname1(n), dm['rank'], dms, at,
+                  capi_maps.get_elsize(var)))
+            dadd('\\item[]{{}\\verb@%s@{}}' %
+                 (capi_maps.getarrdocsign(n, var)))
+            if hasnote(var):
+                note = var['note']
+                if isinstance(note, list):
+                    note = '\n'.join(note)
+                dadd(f'--- {note}')
+            if isallocatable(var):
+                fargs.append(f"f2py_{m['name']}_getdims_{n}")
+                efargs.append(fargs[-1])
+                sargs.append(
+                    f'void (*{n})(int*,npy_intp*,void(*)(char*,npy_intp*),int*)')
+                sargsp.append('void (*)(int*,npy_intp*,void(*)(char*,npy_intp*),int*)')
+                iadd(f"\tf2py_{m['name']}_def[i_f2py++].func = {n};")
+                fadd(f'subroutine {fargs[-1]}(r,s,f2pysetdata,flag)')
+                fadd(f"use {m['name']}, only: d => {undo_rmbadname1(n)}\n")
+                fadd('integer flag\n')
+                fhooks[0] = fhooks[0] + fgetdims1
+                dms = range(1, int(dm['rank']) + 1)
+                fadd(' allocate(d(%s))\n' %
+                     (','.join(['s(%s)' % i for i in dms])))
+                fhooks[0] = fhooks[0] + use_fgetdims2
+                fadd(f'end subroutine {fargs[-1]}')
+            else:
+                fargs.append(n)
+                sargs.append(f'char *{n}')
+                sargsp.append('char*')
+                iadd(f"\tf2py_{m['name']}_def[i_f2py++].data = {n};")
+        if onlyvars:
+            dadd('\\end{description}')
+        if hasbody(m):
+            for b in m['body']:
+                if not isroutine(b):
+                    outmess("f90mod_rules.buildhooks:"
+                            f" skipping {b['block']} {b['name']}\n")
+                    continue
+                modobjs.append(f"{b['name']}()")
+                b['modulename'] = m['name']
+                api, wrap = rules.buildapi(b)
+                if isfunction(b):
+                    fhooks[0] = fhooks[0] + wrap
+                    fargs.append(f"f2pywrap_{m['name']}_{b['name']}")
+                    ifargs.append(func2subr.createfuncwrapper(b, signature=1))
+                elif wrap:
+                    fhooks[0] = fhooks[0] + wrap
+                    fargs.append(f"f2pywrap_{m['name']}_{b['name']}")
+                    ifargs.append(
+                        func2subr.createsubrwrapper(b, signature=1))
+                else:
+                    fargs.append(b['name'])
+                    mfargs.append(fargs[-1])
+                api['externroutines'] = []
+                ar = applyrules(api, vrd)
+                ar['docs'] = []
+                ar['docshort'] = []
+                ret = dictappend(ret, ar)
+                cadd(('\t{"%s",-1,{{-1}},0,0,NULL,(void *)'
+                      'f2py_rout_#modulename#_%s_%s,'
+                      'doc_f2py_rout_#modulename#_%s_%s},')
+                     % (b['name'], m['name'], b['name'], m['name'], b['name']))
+                sargs.append(f"char *{b['name']}")
+                sargsp.append('char *')
+                iadd(f"\tf2py_{m['name']}_def[i_f2py++].data = {b['name']};")
+        cadd('\t{NULL}\n};\n')
+        iadd('}')
+        ihooks[0] = 'static void f2py_setup_%s(%s) {\n\tint i_f2py=0;%s' % (
+            m['name'], ','.join(sargs), ihooks[0])
+        if '_' in m['name']:
+            F_FUNC = 'F_FUNC_US'
+        else:
+            F_FUNC = 'F_FUNC'
+        iadd('extern void %s(f2pyinit%s,F2PYINIT%s)(void (*)(%s));'
+             % (F_FUNC, m['name'], m['name'].upper(), ','.join(sargsp)))
+        iadd('static void f2py_init_%s(void) {' % (m['name']))
+        iadd('\t%s(f2pyinit%s,F2PYINIT%s)(f2py_setup_%s);'
+             % (F_FUNC, m['name'], m['name'].upper(), m['name']))
+        iadd('}\n')
+        ret['f90modhooks'] = ret['f90modhooks'] + chooks + ihooks
+        ret['initf90modhooks'] = ['\tPyDict_SetItemString(d, "%s", PyFortranObject_New(f2py_%s_def,f2py_init_%s));' % (
+            m['name'], m['name'], m['name'])] + ret['initf90modhooks']
+        fadd('')
+        fadd(f"subroutine f2pyinit{m['name']}(f2pysetupfunc)")
+        if mfargs:
+            for a in undo_rmbadname(mfargs):
+                fadd(f"use {m['name']}, only : {a}")
+        if ifargs:
+            fadd(' '.join(['interface'] + ifargs))
+            fadd('end interface')
+        fadd('external f2pysetupfunc')
+        if efargs:
+            for a in undo_rmbadname(efargs):
+                fadd(f'external {a}')
+        fadd(f"call f2pysetupfunc({','.join(undo_rmbadname(fargs))})")
+        fadd(f"end subroutine f2pyinit{m['name']}\n")
+
+        dadd('\n'.join(ret['latexdoc']).replace(
+            r'\subsection{', r'\subsubsection{'))
+
+        ret['latexdoc'] = []
+        ret['docs'].append(f"\"\t{m['name']} --- {','.join(undo_rmbadname(modobjs))}\"")
+
+    ret['routine_defs'] = ''
+    ret['doc'] = []
+    ret['docshort'] = []
+    ret['latexdoc'] = doc[0]
+    if len(ret['docs']) <= 1:
+        ret['docs'] = ''
+    return ret, fhooks[0]
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..7d033bc1ef88642cdebcc522b1051f58f10b1dbc
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/f90mod_rules.pyi
@@ -0,0 +1,16 @@
+from collections.abc import Mapping
+from typing import Any, Final
+
+from .auxfuncs import isintent_dict as isintent_dict
+
+__version__: Final[str] = ...
+f2py_version: Final = "See `f2py -v`"
+
+options: Final[dict[str, bool]]
+
+fgetdims1: Final[str] = ...
+fgetdims2: Final[str] = ...
+fgetdims2_sa: Final[str] = ...
+
+def findf90modules(m: Mapping[str, object]) -> list[dict[str, Any]]: ...
+def buildhooks(pymod: Mapping[str, object]) -> dict[str, Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.py b/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.py
new file mode 100644
index 0000000000000000000000000000000000000000..f298bd1526a380053170786f93610b0a79305a1a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.py
@@ -0,0 +1,329 @@
+"""
+
+Rules for building C/API module with f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+import copy
+
+from ._isocbind import isoc_kindmap
+from .auxfuncs import (
+    getfortranname,
+    isexternal,
+    isfunction,
+    isfunction_wrap,
+    isintent_in,
+    isintent_out,
+    islogicalfunction,
+    ismoduleroutine,
+    isscalar,
+    issubroutine,
+    issubroutine_wrap,
+    outmess,
+    show,
+)
+
+
+def var2fixfortran(vars, a, fa=None, f90mode=None):
+    if fa is None:
+        fa = a
+    if a not in vars:
+        show(vars)
+        outmess(f'var2fixfortran: No definition for argument "{a}".\n')
+        return ''
+    if 'typespec' not in vars[a]:
+        show(vars[a])
+        outmess(f'var2fixfortran: No typespec for argument "{a}".\n')
+        return ''
+    vardef = vars[a]['typespec']
+    if vardef == 'type' and 'typename' in vars[a]:
+        vardef = f"{vardef}({vars[a]['typename']})"
+    selector = {}
+    lk = ''
+    if 'kindselector' in vars[a]:
+        selector = vars[a]['kindselector']
+        lk = 'kind'
+    elif 'charselector' in vars[a]:
+        selector = vars[a]['charselector']
+        lk = 'len'
+    if '*' in selector:
+        if f90mode:
+            if selector['*'] in ['*', ':', '(*)']:
+                vardef = f'{vardef}(len=*)'
+            else:
+                vardef = f"{vardef}({lk}={selector['*']})"
+        elif selector['*'] in ['*', ':']:
+            vardef = f"{vardef}*({selector['*']})"
+        else:
+            vardef = f"{vardef}*{selector['*']}"
+    elif 'len' in selector:
+        vardef = f"{vardef}(len={selector['len']}"
+        if 'kind' in selector:
+            vardef = f"{vardef},kind={selector['kind']})"
+        else:
+            vardef = f'{vardef})'
+    elif 'kind' in selector:
+        vardef = f"{vardef}(kind={selector['kind']})"
+
+    vardef = f'{vardef} {fa}'
+    if 'dimension' in vars[a]:
+        vardef = f"{vardef}({','.join(vars[a]['dimension'])})"
+    return vardef
+
+def useiso_c_binding(rout):
+    useisoc = False
+    for value in rout['vars'].values():
+        kind_value = value.get('kindselector', {}).get('kind')
+        if kind_value in isoc_kindmap:
+            return True
+    return useisoc
+
+def createfuncwrapper(rout, signature=0):
+    assert isfunction(rout)
+
+    extra_args = []
+    vars = rout['vars']
+    for a in rout['args']:
+        v = rout['vars'][a]
+        for i, d in enumerate(v.get('dimension', [])):
+            if d == ':':
+                dn = f'f2py_{a}_d{i}'
+                dv = {'typespec': 'integer', 'intent': ['hide']}
+                dv['='] = f'shape({a}, {i})'
+                extra_args.append(dn)
+                vars[dn] = dv
+                v['dimension'][i] = dn
+    rout['args'].extend(extra_args)
+    need_interface = bool(extra_args)
+
+    ret = ['']
+
+    def add(line, ret=ret):
+        ret[0] = f'{ret[0]}\n      {line}'
+    name = rout['name']
+    fortranname = getfortranname(rout)
+    f90mode = ismoduleroutine(rout)
+    newname = f'{name}f2pywrap'
+
+    if newname not in vars:
+        vars[newname] = vars[name]
+        args = [newname] + rout['args'][1:]
+    else:
+        args = [newname] + rout['args']
+
+    l_tmpl = var2fixfortran(vars, name, '@@@NAME@@@', f90mode)
+    if l_tmpl[:13] == 'character*(*)':
+        if f90mode:
+            l_tmpl = 'character(len=10)' + l_tmpl[13:]
+        else:
+            l_tmpl = 'character*10' + l_tmpl[13:]
+        charselect = vars[name]['charselector']
+        if charselect.get('*', '') == '(*)':
+            charselect['*'] = '10'
+
+    l1 = l_tmpl.replace('@@@NAME@@@', newname)
+    rl = None
+
+    useisoc = useiso_c_binding(rout)
+    sargs = ', '.join(args)
+    if f90mode:
+        # gh-23598 fix warning
+        # Essentially, this gets called again with modules where the name of the
+        # function is added to the arguments, which is not required, and removed
+        sargs = sargs.replace(f"{name}, ", '')
+        args = [arg for arg in args if arg != name]
+        rout['args'] = args
+        add(f"subroutine f2pywrap_{rout['modulename']}_{name} ({sargs})")
+        if not signature:
+            add(f"use {rout['modulename']}, only : {fortranname}")
+        if useisoc:
+            add('use iso_c_binding')
+    else:
+        add(f'subroutine f2pywrap{name} ({sargs})')
+        if useisoc:
+            add('use iso_c_binding')
+        if not need_interface:
+            add(f'external {fortranname}')
+            rl = l_tmpl.replace('@@@NAME@@@', '') + ' ' + fortranname
+
+    if need_interface:
+        for line in rout['saved_interface'].split('\n'):
+            if line.lstrip().startswith('use ') and '__user__' not in line:
+                add(line)
+
+    args = args[1:]
+    dumped_args = []
+    for a in args:
+        if isexternal(vars[a]):
+            add(f'external {a}')
+            dumped_args.append(a)
+    for a in args:
+        if a in dumped_args:
+            continue
+        if isscalar(vars[a]):
+            add(var2fixfortran(vars, a, f90mode=f90mode))
+            dumped_args.append(a)
+    for a in args:
+        if a in dumped_args:
+            continue
+        if isintent_in(vars[a]):
+            add(var2fixfortran(vars, a, f90mode=f90mode))
+            dumped_args.append(a)
+    for a in args:
+        if a in dumped_args:
+            continue
+        add(var2fixfortran(vars, a, f90mode=f90mode))
+
+    add(l1)
+    if rl is not None:
+        add(rl)
+
+    if need_interface:
+        if f90mode:
+            # f90 module already defines needed interface
+            pass
+        else:
+            add('interface')
+            add(rout['saved_interface'].lstrip())
+            add('end interface')
+
+    sargs = ', '.join([a for a in args if a not in extra_args])
+
+    if not signature:
+        if islogicalfunction(rout):
+            add(f'{newname} = .not.(.not.{fortranname}({sargs}))')
+        else:
+            add(f'{newname} = {fortranname}({sargs})')
+    if f90mode:
+        add(f"end subroutine f2pywrap_{rout['modulename']}_{name}")
+    else:
+        add('end')
+    return ret[0]
+
+
+def createsubrwrapper(rout, signature=0):
+    assert issubroutine(rout)
+
+    extra_args = []
+    vars = rout['vars']
+    for a in rout['args']:
+        v = rout['vars'][a]
+        for i, d in enumerate(v.get('dimension', [])):
+            if d == ':':
+                dn = f'f2py_{a}_d{i}'
+                dv = {'typespec': 'integer', 'intent': ['hide']}
+                dv['='] = f'shape({a}, {i})'
+                extra_args.append(dn)
+                vars[dn] = dv
+                v['dimension'][i] = dn
+    rout['args'].extend(extra_args)
+    need_interface = bool(extra_args)
+
+    ret = ['']
+
+    def add(line, ret=ret):
+        ret[0] = f'{ret[0]}\n      {line}'
+    name = rout['name']
+    fortranname = getfortranname(rout)
+    f90mode = ismoduleroutine(rout)
+
+    args = rout['args']
+
+    useisoc = useiso_c_binding(rout)
+    sargs = ', '.join(args)
+    if f90mode:
+        add(f"subroutine f2pywrap_{rout['modulename']}_{name} ({sargs})")
+        if useisoc:
+            add('use iso_c_binding')
+        if not signature:
+            add(f"use {rout['modulename']}, only : {fortranname}")
+    else:
+        add(f'subroutine f2pywrap{name} ({sargs})')
+        if useisoc:
+            add('use iso_c_binding')
+        if not need_interface:
+            add(f'external {fortranname}')
+
+    if need_interface:
+        for line in rout['saved_interface'].split('\n'):
+            if line.lstrip().startswith('use ') and '__user__' not in line:
+                add(line)
+
+    dumped_args = []
+    for a in args:
+        if isexternal(vars[a]):
+            add(f'external {a}')
+            dumped_args.append(a)
+    for a in args:
+        if a in dumped_args:
+            continue
+        if isscalar(vars[a]):
+            add(var2fixfortran(vars, a, f90mode=f90mode))
+            dumped_args.append(a)
+    for a in args:
+        if a in dumped_args:
+            continue
+        add(var2fixfortran(vars, a, f90mode=f90mode))
+
+    if need_interface:
+        if f90mode:
+            # f90 module already defines needed interface
+            pass
+        else:
+            add('interface')
+            for line in rout['saved_interface'].split('\n'):
+                if line.lstrip().startswith('use ') and '__user__' in line:
+                    continue
+                add(line)
+            add('end interface')
+
+    sargs = ', '.join([a for a in args if a not in extra_args])
+
+    if not signature:
+        add(f'call {fortranname}({sargs})')
+    if f90mode:
+        add(f"end subroutine f2pywrap_{rout['modulename']}_{name}")
+    else:
+        add('end')
+    return ret[0]
+
+
+def assubr(rout):
+    if isfunction_wrap(rout):
+        fortranname = getfortranname(rout)
+        name = rout['name']
+        outmess('\t\tCreating wrapper for Fortran function "%s"("%s")...\n' % (
+            name, fortranname))
+        rout = copy.copy(rout)
+        fname = name
+        rname = fname
+        if 'result' in rout:
+            rname = rout['result']
+            rout['vars'][fname] = rout['vars'][rname]
+        fvar = rout['vars'][fname]
+        if not isintent_out(fvar):
+            if 'intent' not in fvar:
+                fvar['intent'] = []
+            fvar['intent'].append('out')
+            flag = 1
+            for i in fvar['intent']:
+                if i.startswith('out='):
+                    flag = 0
+                    break
+            if flag:
+                fvar['intent'].append(f'out={rname}')
+        rout['args'][:] = [fname] + rout['args']
+        return rout, createfuncwrapper(rout)
+    if issubroutine_wrap(rout):
+        fortranname = getfortranname(rout)
+        name = rout['name']
+        outmess('\t\tCreating wrapper for Fortran subroutine "%s"("%s")...\n'
+                % (name, fortranname))
+        rout = copy.copy(rout)
+        return rout, createsubrwrapper(rout)
+    return rout, ''
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..58497b96949ad820378172dc29a5e26177832088
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/func2subr.pyi
@@ -0,0 +1,7 @@
+from .auxfuncs import _Bool, _ROut, _Var
+
+def var2fixfortran(vars: _Var, a: str, fa: str | None = None, f90mode: _Bool | None = None) -> str: ...
+def useiso_c_binding(rout: _ROut) -> bool: ...
+def createfuncwrapper(rout: _ROut, signature: int = 0) -> str: ...
+def createsubrwrapper(rout: _ROut, signature: int = 0) -> str: ...
+def assubr(rout: _ROut) -> tuple[dict[str, str], str]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/rules.py b/python/user_packages/Python313/site-packages/numpy/f2py/rules.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbbad061c892db7660fcdebba00c337535735abb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/rules.py
@@ -0,0 +1,1629 @@
+"""
+
+Rules for building C/API module with f2py2e.
+
+Here is a skeleton of a new wrapper function (13Dec2001):
+
+wrapper_function(args)
+  declarations
+  get_python_arguments, say, `a' and `b'
+
+  get_a_from_python
+  if (successful) {
+
+    get_b_from_python
+    if (successful) {
+
+      callfortran
+      if (successful) {
+
+        put_a_to_python
+        if (successful) {
+
+          put_b_to_python
+          if (successful) {
+
+            buildvalue = ...
+
+          }
+
+        }
+
+      }
+
+    }
+    cleanup_b
+
+  }
+  cleanup_a
+
+  return buildvalue
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+import copy
+import os
+import sys
+import time
+from pathlib import Path
+
+# __version__.version is now the same as the NumPy version
+from . import (
+    __version__,
+    capi_maps,
+    cfuncs,
+    common_rules,
+    f90mod_rules,
+    func2subr,
+    use_rules,
+)
+from .auxfuncs import (
+    applyrules,
+    debugcapi,
+    dictappend,
+    errmess,
+    gentitle,
+    getargs2,
+    hascallstatement,
+    hasexternals,
+    hasinitvalue,
+    hasnote,
+    hasresultnote,
+    isarray,
+    isarrayofstrings,
+    isattr_value,
+    ischaracter,
+    ischaracter_or_characterarray,
+    ischaracterarray,
+    iscomplex,
+    iscomplexarray,
+    iscomplexfunction,
+    iscomplexfunction_warn,
+    isdummyroutine,
+    isexternal,
+    isfunction,
+    isfunction_wrap,
+    isint1,
+    isint1array,
+    isintent_aux,
+    isintent_c,
+    isintent_callback,
+    isintent_copy,
+    isintent_hide,
+    isintent_inout,
+    isintent_nothide,
+    isintent_out,
+    isintent_overwrite,
+    islogical,
+    islong_complex,
+    islong_double,
+    islong_doublefunction,
+    islong_long,
+    islong_longfunction,
+    ismoduleroutine,
+    isoptional,
+    isrequired,
+    isscalar,
+    issigned_long_longarray,
+    isstring,
+    isstringarray,
+    isstringfunction,
+    issubroutine,
+    issubroutine_wrap,
+    isthreadsafe,
+    isunsigned,
+    isunsigned_char,
+    isunsigned_chararray,
+    isunsigned_long_long,
+    isunsigned_long_longarray,
+    isunsigned_short,
+    isunsigned_shortarray,
+    l_and,
+    l_not,
+    l_or,
+    outmess,
+    replace,
+    requiresf90wrapper,
+    stripcomma,
+)
+
+f2py_version = __version__.version
+numpy_version = __version__.version
+
+options = {}
+sepdict = {}
+# for k in ['need_cfuncs']: sepdict[k]=','
+for k in ['decl',
+          'frompyobj',
+          'cleanupfrompyobj',
+          'topyarr', 'method',
+          'pyobjfrom', 'closepyobjfrom',
+          'freemem',
+          'userincludes',
+          'includes0', 'includes', 'typedefs', 'typedefs_generated',
+          'cppmacros', 'cfuncs', 'callbacks',
+          'latexdoc',
+          'restdoc',
+          'routine_defs', 'externroutines',
+          'initf2pywraphooks',
+          'commonhooks', 'initcommonhooks',
+          'f90modhooks', 'initf90modhooks']:
+    sepdict[k] = '\n'
+
+#################### Rules for C/API module #################
+
+generationtime = int(os.environ.get('SOURCE_DATE_EPOCH', time.time()))
+module_rules = {
+    'modulebody': """\
+/* File: #modulename#module.c
+ * This file is auto-generated with f2py (version:#f2py_version#).
+ * f2py is a Fortran to Python Interface Generator (FPIG), Second Edition,
+ * written by Pearu Peterson <pearu@cens.ioc.ee>.
+ * Generation date: """ + time.asctime(time.gmtime(generationtime)) + """
+ * Do not edit this file directly unless you know what you are doing!!!
+ */
+
+#ifdef __cplusplus
+extern \"C\" {
+#endif
+
+#ifndef PY_SSIZE_T_CLEAN
+#define PY_SSIZE_T_CLEAN
+#endif /* PY_SSIZE_T_CLEAN */
+
+/* Unconditionally included */
+#include <Python.h>
+#include <numpy/npy_os.h>
+
+""" + gentitle("See f2py2e/cfuncs.py: includes") + """
+#includes#
+#includes0#
+
+""" + gentitle("See f2py2e/rules.py: mod_rules['modulebody']") + """
+static PyObject *#modulename#_error;
+static PyObject *#modulename#_module;
+
+""" + gentitle("See f2py2e/cfuncs.py: typedefs") + """
+#typedefs#
+
+""" + gentitle("See f2py2e/cfuncs.py: typedefs_generated") + """
+#typedefs_generated#
+
+""" + gentitle("See f2py2e/cfuncs.py: cppmacros") + """
+#cppmacros#
+
+""" + gentitle("See f2py2e/cfuncs.py: cfuncs") + """
+#cfuncs#
+
+""" + gentitle("See f2py2e/cfuncs.py: userincludes") + """
+#userincludes#
+
+""" + gentitle("See f2py2e/capi_rules.py: usercode") + """
+#usercode#
+
+/* See f2py2e/rules.py */
+#externroutines#
+
+""" + gentitle("See f2py2e/capi_rules.py: usercode1") + """
+#usercode1#
+
+""" + gentitle("See f2py2e/cb_rules.py: buildcallback") + """
+#callbacks#
+
+""" + gentitle("See f2py2e/rules.py: buildapi") + """
+#body#
+
+""" + gentitle("See f2py2e/f90mod_rules.py: buildhooks") + """
+#f90modhooks#
+
+""" + gentitle("See f2py2e/rules.py: module_rules['modulebody']") + """
+
+""" + gentitle("See f2py2e/common_rules.py: buildhooks") + """
+#commonhooks#
+
+""" + gentitle("See f2py2e/rules.py") + """
+
+static FortranDataDef f2py_routine_defs[] = {
+#routine_defs#
+    {NULL}
+};
+
+static PyMethodDef f2py_module_methods[] = {
+#pymethoddef#
+    {NULL,NULL}
+};
+
+static struct PyModuleDef moduledef = {
+    PyModuleDef_HEAD_INIT,
+    "#modulename#",
+    NULL,
+    -1,
+    f2py_module_methods,
+    NULL,
+    NULL,
+    NULL,
+    NULL
+};
+
+PyMODINIT_FUNC PyInit_#modulename#(void) {
+    int i;
+    PyObject *m,*d, *s, *tmp;
+    m = #modulename#_module = PyModule_Create(&moduledef);
+    Py_SET_TYPE(&PyFortran_Type, &PyType_Type);
+    import_array();
+    if (PyErr_Occurred())
+        {PyErr_SetString(PyExc_ImportError, \"can't initialize module #modulename# (failed to import numpy)\"); return m;}
+    d = PyModule_GetDict(m);
+    s = PyUnicode_FromString(\"#f2py_version#\");
+    PyDict_SetItemString(d, \"__version__\", s);
+    Py_DECREF(s);
+    s = PyUnicode_FromString(
+        \"This module '#modulename#' is auto-generated with f2py (version:#f2py_version#).\\nFunctions:\\n\"\n#docs#\".\");
+    PyDict_SetItemString(d, \"__doc__\", s);
+    Py_DECREF(s);
+    s = PyUnicode_FromString(\"""" + numpy_version + """\");
+    PyDict_SetItemString(d, \"__f2py_numpy_version__\", s);
+    Py_DECREF(s);
+    #modulename#_error = PyErr_NewException (\"#modulename#.error\", NULL, NULL);
+    /*
+     * Store the error object inside the dict, so that it could get deallocated.
+     * (in practice, this is a module, so it likely will not and cannot.)
+     */
+    PyDict_SetItemString(d, \"_#modulename#_error\", #modulename#_error);
+    Py_DECREF(#modulename#_error);
+    for(i=0;f2py_routine_defs[i].name!=NULL;i++) {
+        tmp = PyFortranObject_NewAsAttr(&f2py_routine_defs[i]);
+        PyDict_SetItemString(d, f2py_routine_defs[i].name, tmp);
+        Py_DECREF(tmp);
+    }
+#initf2pywraphooks#
+#initf90modhooks#
+#initcommonhooks#
+#interface_usercode#
+
+#ifdef Py_GIL_DISABLED
+    // signal whether this module supports running with the GIL disabled
+    PyUnstable_Module_SetGIL(m , #gil_used#);
+#endif
+
+#ifdef F2PY_REPORT_ATEXIT
+    if (! PyErr_Occurred())
+        on_exit(f2py_report_on_exit,(void*)\"#modulename#\");
+#endif
+
+    if (PyType_Ready(&PyFortran_Type) < 0) {
+        return NULL;
+    }
+
+    return m;
+}
+#ifdef __cplusplus
+}
+#endif
+""",
+    'separatorsfor': {'latexdoc': '\n\n',
+                      'restdoc': '\n\n'},
+    'latexdoc': ['\\section{Module \\texttt{#texmodulename#}}\n',
+                 '#modnote#\n',
+                 '#latexdoc#'],
+    'restdoc': ['Module #modulename#\n' + '=' * 80,
+                '\n#restdoc#']
+}
+
+defmod_rules = [
+    {'body': '/*eof body*/',
+     'method': '/*eof method*/',
+     'externroutines': '/*eof externroutines*/',
+     'routine_defs': '/*eof routine_defs*/',
+     'initf90modhooks': '/*eof initf90modhooks*/',
+     'initf2pywraphooks': '/*eof initf2pywraphooks*/',
+     'initcommonhooks': '/*eof initcommonhooks*/',
+     'latexdoc': '',
+     'restdoc': '',
+     'modnote': {hasnote: '#note#', l_not(hasnote): ''},
+     }
+]
+
+routine_rules = {
+    'separatorsfor': sepdict,
+    'body': """
+#begintitle#
+static char doc_#apiname#[] = \"\\\n#docreturn##name#(#docsignatureshort#)\\n\\nWrapper for ``#name#``.\\\n\\n#docstrsigns#\";
+/* #declfortranroutine# */
+static PyObject *#apiname#(const PyObject *capi_self,
+                           PyObject *capi_args,
+                           PyObject *capi_keywds,
+                           #functype# (*f2py_func)(#callprotoargument#)) {
+    PyObject * volatile capi_buildvalue = NULL;
+    volatile int f2py_success = 1;
+#decl#
+    static char *capi_kwlist[] = {#kwlist##kwlistopt##kwlistxa#NULL};
+#usercode#
+#routdebugenter#
+#ifdef F2PY_REPORT_ATEXIT
+f2py_start_clock();
+#endif
+    if (!PyArg_ParseTupleAndKeywords(capi_args,capi_keywds,\\
+        \"#argformat#|#keyformat##xaformat#:#pyname#\",\\
+        capi_kwlist#args_capi##keys_capi##keys_xa#))\n        return NULL;
+#frompyobj#
+/*end of frompyobj*/
+#ifdef F2PY_REPORT_ATEXIT
+f2py_start_call_clock();
+#endif
+#callfortranroutine#
+if (PyErr_Occurred())
+  f2py_success = 0;
+#ifdef F2PY_REPORT_ATEXIT
+f2py_stop_call_clock();
+#endif
+/*end of callfortranroutine*/
+        if (f2py_success) {
+#pyobjfrom#
+/*end of pyobjfrom*/
+        CFUNCSMESS(\"Building return value.\\n\");
+        capi_buildvalue = Py_BuildValue(\"#returnformat#\"#return#);
+/*closepyobjfrom*/
+#closepyobjfrom#
+        } /*if (f2py_success) after callfortranroutine*/
+/*cleanupfrompyobj*/
+#cleanupfrompyobj#
+    if (capi_buildvalue == NULL) {
+#routdebugfailure#
+    } else {
+#routdebugleave#
+    }
+    CFUNCSMESS(\"Freeing memory.\\n\");
+#freemem#
+#ifdef F2PY_REPORT_ATEXIT
+f2py_stop_clock();
+#endif
+    return capi_buildvalue;
+}
+#endtitle#
+""",
+    'routine_defs': '#routine_def#',
+    'initf2pywraphooks': '#initf2pywraphook#',
+    'externroutines': '#declfortranroutine#',
+    'doc': '#docreturn##name#(#docsignature#)',
+    'docshort': '#docreturn##name#(#docsignatureshort#)',
+    'docs': '"    #docreturn##name#(#docsignature#)\\n"\n',
+    'need': ['arrayobject.h', 'CFUNCSMESS', 'MINMAX'],
+    'cppmacros': {debugcapi: '#define DEBUGCFUNCS'},
+    'latexdoc': ['\\subsection{Wrapper function \\texttt{#texname#}}\n',
+                 """
+\\noindent{{}\\verb@#docreturn##name#@{}}\\texttt{(#latexdocsignatureshort#)}
+#routnote#
+
+#latexdocstrsigns#
+"""],
+    'restdoc': ['Wrapped function ``#name#``\n' + '-' * 80,
+
+                ]
+}
+
+################## Rules for C/API function ##############
+
+rout_rules = [
+    {  # Init
+        'separatorsfor': {'callfortranroutine': '\n', 'routdebugenter': '\n', 'decl': '\n',
+                          'routdebugleave': '\n', 'routdebugfailure': '\n',
+                          'setjmpbuf': ' || ',
+                          'docstrreq': '\n', 'docstropt': '\n', 'docstrout': '\n',
+                          'docstrcbs': '\n', 'docstrsigns': '\\n"\n"',
+                          'latexdocstrsigns': '\n',
+                          'latexdocstrreq': '\n', 'latexdocstropt': '\n',
+                          'latexdocstrout': '\n', 'latexdocstrcbs': '\n',
+                          },
+        'kwlist': '', 'kwlistopt': '', 'callfortran': '', 'callfortranappend': '',
+        'docsign': '', 'docsignopt': '', 'decl': '/*decl*/',
+        'freemem': '/*freemem*/',
+        'docsignshort': '', 'docsignoptshort': '',
+        'docstrsigns': '', 'latexdocstrsigns': '',
+        'docstrreq': '\\nParameters\\n----------',
+        'docstropt': '\\nOther Parameters\\n----------------',
+        'docstrout': '\\nReturns\\n-------',
+        'docstrcbs': '\\nNotes\\n-----\\nCall-back functions::\\n',
+        'latexdocstrreq': '\\noindent Required arguments:',
+        'latexdocstropt': '\\noindent Optional arguments:',
+        'latexdocstrout': '\\noindent Return objects:',
+        'latexdocstrcbs': '\\noindent Call-back functions:',
+        'args_capi': '', 'keys_capi': '', 'functype': '',
+        'frompyobj': '/*frompyobj*/',
+        # this list will be reversed
+        'cleanupfrompyobj': ['/*end of cleanupfrompyobj*/'],
+        'pyobjfrom': '/*pyobjfrom*/',
+        # this list will be reversed
+        'closepyobjfrom': ['/*end of closepyobjfrom*/'],
+        'topyarr': '/*topyarr*/', 'routdebugleave': '/*routdebugleave*/',
+        'routdebugenter': '/*routdebugenter*/',
+        'routdebugfailure': '/*routdebugfailure*/',
+        'callfortranroutine': '/*callfortranroutine*/',
+        'argformat': '', 'keyformat': '', 'need_cfuncs': '',
+        'docreturn': '', 'return': '', 'returnformat': '', 'rformat': '',
+        'kwlistxa': '', 'keys_xa': '', 'xaformat': '', 'docsignxa': '', 'docsignxashort': '',
+        'initf2pywraphook': '',
+        'routnote': {hasnote: '--- #note#', l_not(hasnote): ''},
+    }, {
+        'apiname': 'f2py_rout_#modulename#_#name#',
+        'pyname': '#modulename#.#name#',
+        'decl': '',
+        '_check': l_not(ismoduleroutine)
+    }, {
+        'apiname': 'f2py_rout_#modulename#_#f90modulename#_#name#',
+        'pyname': '#modulename#.#f90modulename#.#name#',
+        'decl': '',
+        '_check': ismoduleroutine
+    }, {  # Subroutine
+        'functype': 'void',
+        'declfortranroutine': {l_and(l_not(l_or(ismoduleroutine, isintent_c)), l_not(isdummyroutine)): 'extern void #F_FUNC#(#fortranname#,#FORTRANNAME#)(#callprotoargument#);',
+                               l_and(l_not(ismoduleroutine), isintent_c, l_not(isdummyroutine)): 'extern void #fortranname#(#callprotoargument#);',
+                               ismoduleroutine: '',
+                               isdummyroutine: ''
+                               },
+        'routine_def': {
+            l_not(l_or(ismoduleroutine, isintent_c, isdummyroutine)):
+            '    {\"#name#\",-1,{{-1}},0,0,(char *)'
+            '  #F_FUNC#(#fortranname#,#FORTRANNAME#),'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+            l_and(l_not(ismoduleroutine), isintent_c, l_not(isdummyroutine)):
+            '    {\"#name#\",-1,{{-1}},0,0,(char *)#fortranname#,'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+            l_and(l_not(ismoduleroutine), isdummyroutine):
+            '    {\"#name#\",-1,{{-1}},0,0,NULL,'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+        },
+        'need': {l_and(l_not(l_or(ismoduleroutine, isintent_c)), l_not(isdummyroutine)): 'F_FUNC'},
+        'callfortranroutine': [
+            {debugcapi: [
+                """    fprintf(stderr,\"debug-capi:Fortran subroutine `#fortranname#(#callfortran#)\'\\n\");"""]},
+            {hasexternals: """\
+        if (#setjmpbuf#) {
+            f2py_success = 0;
+        } else {"""},
+            {isthreadsafe: '            Py_BEGIN_ALLOW_THREADS'},
+            {hascallstatement: '''                #callstatement#;
+                /*(*f2py_func)(#callfortran#);*/'''},
+            {l_not(l_or(hascallstatement, isdummyroutine))
+                   : '                (*f2py_func)(#callfortran#);'},
+            {isthreadsafe: '            Py_END_ALLOW_THREADS'},
+            {hasexternals: """        }"""}
+        ],
+        '_check': l_and(issubroutine, l_not(issubroutine_wrap)),
+    }, {  # Wrapped function
+        'functype': 'void',
+        'declfortranroutine': {l_not(l_or(ismoduleroutine, isdummyroutine)): 'extern void #F_WRAPPEDFUNC#(#name_lower#,#NAME#)(#callprotoargument#);',
+                               isdummyroutine: '',
+                               },
+
+        'routine_def': {
+            l_not(l_or(ismoduleroutine, isdummyroutine)):
+            '    {\"#name#\",-1,{{-1}},0,0,(char *)'
+            '  #F_WRAPPEDFUNC#(#name_lower#,#NAME#),'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+            isdummyroutine:
+            '    {\"#name#\",-1,{{-1}},0,0,NULL,'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+        },
+        'initf2pywraphook': {l_not(l_or(ismoduleroutine, isdummyroutine)): '''
+    {
+      extern #ctype# #F_FUNC#(#name_lower#,#NAME#)(void);
+      PyObject* o = PyDict_GetItemString(d,"#name#");
+      tmp = F2PyCapsule_FromVoidPtr((void*)#F_WRAPPEDFUNC#(#name_lower#,#NAME#),NULL);
+      PyObject_SetAttrString(o,"_cpointer", tmp);
+      Py_DECREF(tmp);
+      s = PyUnicode_FromString("#name#");
+      PyObject_SetAttrString(o,"__name__", s);
+      Py_DECREF(s);
+    }
+    '''},
+        'need': {l_not(l_or(ismoduleroutine, isdummyroutine)): ['F_WRAPPEDFUNC', 'F_FUNC']},
+        'callfortranroutine': [
+            {debugcapi: [
+                """    fprintf(stderr,\"debug-capi:Fortran subroutine `f2pywrap#name_lower#(#callfortran#)\'\\n\");"""]},
+            {hasexternals: """\
+    if (#setjmpbuf#) {
+        f2py_success = 0;
+    } else {"""},
+            {isthreadsafe: '    Py_BEGIN_ALLOW_THREADS'},
+            {l_not(l_or(hascallstatement, isdummyroutine))
+                   : '    (*f2py_func)(#callfortran#);'},
+            {hascallstatement:
+                '    #callstatement#;\n    /*(*f2py_func)(#callfortran#);*/'},
+            {isthreadsafe: '    Py_END_ALLOW_THREADS'},
+            {hasexternals: '    }'}
+        ],
+        '_check': isfunction_wrap,
+    }, {  # Wrapped subroutine
+        'functype': 'void',
+        'declfortranroutine': {l_not(l_or(ismoduleroutine, isdummyroutine)): 'extern void #F_WRAPPEDFUNC#(#name_lower#,#NAME#)(#callprotoargument#);',
+                               isdummyroutine: '',
+                               },
+
+        'routine_def': {
+            l_not(l_or(ismoduleroutine, isdummyroutine)):
+            '    {\"#name#\",-1,{{-1}},0,0,(char *)'
+            '  #F_WRAPPEDFUNC#(#name_lower#,#NAME#),'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+            isdummyroutine:
+            '    {\"#name#\",-1,{{-1}},0,0,NULL,'
+            '  (f2py_init_func)#apiname#,doc_#apiname#},',
+        },
+        'initf2pywraphook': {l_not(l_or(ismoduleroutine, isdummyroutine)): '''
+    {
+      extern void #F_FUNC#(#name_lower#,#NAME#)(void);
+      PyObject* o = PyDict_GetItemString(d,"#name#");
+      tmp = F2PyCapsule_FromVoidPtr((void*)#F_FUNC#(#name_lower#,#NAME#),NULL);
+      PyObject_SetAttrString(o,"_cpointer", tmp);
+      Py_DECREF(tmp);
+      s = PyUnicode_FromString("#name#");
+      PyObject_SetAttrString(o,"__name__", s);
+      Py_DECREF(s);
+    }
+    '''},
+        'need': {l_not(l_or(ismoduleroutine, isdummyroutine)): ['F_WRAPPEDFUNC', 'F_FUNC']},
+        'callfortranroutine': [
+            {debugcapi: [
+                """    fprintf(stderr,\"debug-capi:Fortran subroutine `f2pywrap#name_lower#(#callfortran#)\'\\n\");"""]},
+            {hasexternals: """\
+    if (#setjmpbuf#) {
+        f2py_success = 0;
+    } else {"""},
+            {isthreadsafe: '    Py_BEGIN_ALLOW_THREADS'},
+            {l_not(l_or(hascallstatement, isdummyroutine))
+                   : '    (*f2py_func)(#callfortran#);'},
+            {hascallstatement:
+                '    #callstatement#;\n    /*(*f2py_func)(#callfortran#);*/'},
+            {isthreadsafe: '    Py_END_ALLOW_THREADS'},
+            {hasexternals: '    }'}
+        ],
+        '_check': issubroutine_wrap,
+    }, {  # Function
+        'functype': '#ctype#',
+        'docreturn': {l_not(isintent_hide): '#rname#,'},
+        'docstrout': '#pydocsignout#',
+        'latexdocstrout': ['\\item[]{{}\\verb@#pydocsignout#@{}}',
+                           {hasresultnote: '--- #resultnote#'}],
+        'callfortranroutine': [{l_and(debugcapi, isstringfunction): """\
+#ifdef USESCOMPAQFORTRAN
+    fprintf(stderr,\"debug-capi:Fortran function #ctype# #fortranname#(#callcompaqfortran#)\\n\");
+#else
+    fprintf(stderr,\"debug-capi:Fortran function #ctype# #fortranname#(#callfortran#)\\n\");
+#endif
+"""},
+                               {l_and(debugcapi, l_not(isstringfunction)): """\
+    fprintf(stderr,\"debug-capi:Fortran function #ctype# #fortranname#(#callfortran#)\\n\");
+"""}
+                               ],
+        '_check': l_and(isfunction, l_not(isfunction_wrap))
+    }, {  # Scalar function
+        'declfortranroutine': {l_and(l_not(l_or(ismoduleroutine, isintent_c)), l_not(isdummyroutine)): 'extern #ctype# #F_FUNC#(#fortranname#,#FORTRANNAME#)(#callprotoargument#);',
+                               l_and(l_not(ismoduleroutine), isintent_c, l_not(isdummyroutine)): 'extern #ctype# #fortranname#(#callprotoargument#);',
+                               isdummyroutine: ''
+                               },
+        'routine_def': {
+            l_and(l_not(l_or(ismoduleroutine, isintent_c)),
+                  l_not(isdummyroutine)):
+            ('    {\"#name#\",-1,{{-1}},0,0,(char *)'
+             '  #F_FUNC#(#fortranname#,#FORTRANNAME#),'
+             '  (f2py_init_func)#apiname#,doc_#apiname#},'),
+            l_and(l_not(ismoduleroutine), isintent_c, l_not(isdummyroutine)):
+            ('    {\"#name#\",-1,{{-1}},0,0,(char *)#fortranname#,'
+             '  (f2py_init_func)#apiname#,doc_#apiname#},'),
+            isdummyroutine:
+            '    {\"#name#\",-1,{{-1}},0,0,NULL,'
+            '(f2py_init_func)#apiname#,doc_#apiname#},',
+        },
+        'decl': [{iscomplexfunction_warn: '    #ctype# #name#_return_value={0,0};',
+                  l_not(iscomplexfunction): '    #ctype# #name#_return_value=0;'},
+                 {iscomplexfunction:
+                  '    PyObject *#name#_return_value_capi = Py_None;'}
+                 ],
+        'callfortranroutine': [
+            {hasexternals: """\
+    if (#setjmpbuf#) {
+        f2py_success = 0;
+    } else {"""},
+            {isthreadsafe: '    Py_BEGIN_ALLOW_THREADS'},
+            {hascallstatement: '''    #callstatement#;
+/*    #name#_return_value = (*f2py_func)(#callfortran#);*/
+'''},
+            {l_not(l_or(hascallstatement, isdummyroutine))
+                   : '    #name#_return_value = (*f2py_func)(#callfortran#);'},
+            {isthreadsafe: '    Py_END_ALLOW_THREADS'},
+            {hasexternals: '    }'},
+            {l_and(debugcapi, iscomplexfunction)
+                   : '    fprintf(stderr,"#routdebugshowvalue#\\n",#name#_return_value.r,#name#_return_value.i);'},
+            {l_and(debugcapi, l_not(iscomplexfunction)): '    fprintf(stderr,"#routdebugshowvalue#\\n",#name#_return_value);'}],
+        'pyobjfrom': {iscomplexfunction: '    #name#_return_value_capi = pyobj_from_#ctype#1(#name#_return_value);'},
+        'need': [{l_not(isdummyroutine): 'F_FUNC'},
+                 {iscomplexfunction: 'pyobj_from_#ctype#1'},
+                 {islong_longfunction: 'long_long'},
+                 {islong_doublefunction: 'long_double'}],
+        'returnformat': {l_not(isintent_hide): '#rformat#'},
+        'return': {iscomplexfunction: ',#name#_return_value_capi',
+                   l_not(l_or(iscomplexfunction, isintent_hide)): ',#name#_return_value'},
+        '_check': l_and(isfunction, l_not(isstringfunction), l_not(isfunction_wrap))
+    }, {  # String function # in use for --no-wrap
+        'declfortranroutine': 'extern void #F_FUNC#(#fortranname#,#FORTRANNAME#)(#callprotoargument#);',
+        'routine_def': {l_not(l_or(ismoduleroutine, isintent_c)):
+                        '    {\"#name#\",-1,{{-1}},0,0,(char *)#F_FUNC#(#fortranname#,#FORTRANNAME#),(f2py_init_func)#apiname#,doc_#apiname#},',
+                        l_and(l_not(ismoduleroutine), isintent_c):
+                        '    {\"#name#\",-1,{{-1}},0,0,(char *)#fortranname#,(f2py_init_func)#apiname#,doc_#apiname#},'
+                        },
+        'decl': ['    #ctype# #name#_return_value = NULL;',
+                 '    int #name#_return_value_len = 0;'],
+        'callfortran': '#name#_return_value,#name#_return_value_len,',
+        'callfortranroutine': ['    #name#_return_value_len = #rlength#;',
+                               '    if ((#name#_return_value = (string)malloc(#name#_return_value_len+1) == NULL) {',
+                               '        PyErr_SetString(PyExc_MemoryError, \"out of memory\");',
+                               '        f2py_success = 0;',
+                               '    } else {',
+                               "        (#name#_return_value)[#name#_return_value_len] = '\\0';",
+                               '    }',
+                               '    if (f2py_success) {',
+                               {hasexternals: """\
+        if (#setjmpbuf#) {
+            f2py_success = 0;
+        } else {"""},
+                               {isthreadsafe: '        Py_BEGIN_ALLOW_THREADS'},
+                              """\
+#ifdef USESCOMPAQFORTRAN
+        (*f2py_func)(#callcompaqfortran#);
+#else
+        (*f2py_func)(#callfortran#);
+#endif
+""",
+                               {isthreadsafe: '        Py_END_ALLOW_THREADS'},
+                               {hasexternals: '        }'},
+                               {debugcapi:
+                                  '        fprintf(stderr,"#routdebugshowvalue#\\n",#name#_return_value_len,#name#_return_value);'},
+                               '    } /* if (f2py_success) after (string)malloc */',
+                              ],
+        'returnformat': '#rformat#',
+        'return': ',#name#_return_value',
+        'freemem': '    STRINGFREE(#name#_return_value);',
+        'need': ['F_FUNC', '#ctype#', 'STRINGFREE'],
+        '_check': l_and(isstringfunction, l_not(isfunction_wrap))  # ???obsolete
+    },
+    {  # Debugging
+        'routdebugenter': '    fprintf(stderr,"debug-capi:Python C/API function #modulename#.#name#(#docsignature#)\\n");',
+        'routdebugleave': '    fprintf(stderr,"debug-capi:Python C/API function #modulename#.#name#: successful.\\n");',
+        'routdebugfailure': '    fprintf(stderr,"debug-capi:Python C/API function #modulename#.#name#: failure.\\n");',
+        '_check': debugcapi
+    }
+]
+
+################ Rules for arguments ##################
+
+typedef_need_dict = {islong_long: 'long_long',
+                     islong_double: 'long_double',
+                     islong_complex: 'complex_long_double',
+                     isunsigned_char: 'unsigned_char',
+                     isunsigned_short: 'unsigned_short',
+                     isunsigned: 'unsigned',
+                     isunsigned_long_long: 'unsigned_long_long',
+                     isunsigned_chararray: 'unsigned_char',
+                     isunsigned_shortarray: 'unsigned_short',
+                     isunsigned_long_longarray: 'unsigned_long_long',
+                     issigned_long_longarray: 'long_long',
+                     isint1: 'signed_char',
+                     ischaracter_or_characterarray: 'character',
+                     }
+
+aux_rules = [
+    {
+        'separatorsfor': sepdict
+    },
+    {  # Common
+        'frompyobj': ['    /* Processing auxiliary variable #varname# */',
+                      {debugcapi: '    fprintf(stderr,"#vardebuginfo#\\n");'}, ],
+        'cleanupfrompyobj': '    /* End of cleaning variable #varname# */',
+        'need': typedef_need_dict,
+    },
+    # Scalars (not complex)
+    {  # Common
+        'decl': '    #ctype# #varname# = 0;',
+        'need': {hasinitvalue: 'math.h'},
+        'frompyobj': {hasinitvalue: '    #varname# = #init#;'},
+        '_check': l_and(isscalar, l_not(iscomplex)),
+    },
+    {
+        'return': ',#varname#',
+        'docstrout': '#pydocsignout#',
+        'docreturn': '#outvarname#,',
+        'returnformat': '#varrformat#',
+        '_check': l_and(isscalar, l_not(iscomplex), isintent_out),
+    },
+    # Complex scalars
+    {  # Common
+        'decl': '    #ctype# #varname#;',
+        'frompyobj': {hasinitvalue: '    #varname#.r = #init.r#, #varname#.i = #init.i#;'},
+        '_check': iscomplex
+    },
+    # String
+    {  # Common
+        'decl': ['    #ctype# #varname# = NULL;',
+                 '    int slen(#varname#);',
+                 ],
+        'need': ['len..'],
+        '_check': isstring
+    },
+    # Array
+    {  # Common
+        'decl': ['    #ctype# *#varname# = NULL;',
+                 '    npy_intp #varname#_Dims[#rank#] = {#rank*[-1]#};',
+                 '    const int #varname#_Rank = #rank#;',
+                 ],
+        'need': ['len..', {hasinitvalue: 'forcomb'}, {hasinitvalue: 'CFUNCSMESS'}],
+        '_check': isarray
+    },
+    # Scalararray
+    {  # Common
+        '_check': l_and(isarray, l_not(iscomplexarray))
+    }, {  # Not hidden
+        '_check': l_and(isarray, l_not(iscomplexarray), isintent_nothide)
+    },
+    # Integer*1 array
+    {'need': '#ctype#',
+     '_check': isint1array,
+     '_depend': ''
+     },
+    # Integer*-1 array
+    {'need': '#ctype#',
+     '_check': l_or(isunsigned_chararray, isunsigned_char),
+     '_depend': ''
+     },
+    # Integer*-2 array
+    {'need': '#ctype#',
+     '_check': isunsigned_shortarray,
+     '_depend': ''
+     },
+    # Integer*-8 array
+    {'need': '#ctype#',
+     '_check': isunsigned_long_longarray,
+     '_depend': ''
+     },
+    # Complexarray
+    {'need': '#ctype#',
+     '_check': iscomplexarray,
+     '_depend': ''
+     },
+    # Stringarray
+    {
+        'callfortranappend': {isarrayofstrings: 'flen(#varname#),'},
+        'need': 'string',
+        '_check': isstringarray
+    }
+]
+
+arg_rules = [
+    {
+        'separatorsfor': sepdict
+    },
+    {  # Common
+        'frompyobj': ['    /* Processing variable #varname# */',
+                      {debugcapi: '    fprintf(stderr,"#vardebuginfo#\\n");'}, ],
+        'cleanupfrompyobj': '    /* End of cleaning variable #varname# */',
+        '_depend': '',
+        'need': typedef_need_dict,
+    },
+    # Doc signatures
+    {
+        'docstropt': {l_and(isoptional, isintent_nothide): '#pydocsign#'},
+        'docstrreq': {l_and(isrequired, isintent_nothide): '#pydocsign#'},
+        'docstrout': {isintent_out: '#pydocsignout#'},
+        'latexdocstropt': {l_and(isoptional, isintent_nothide): ['\\item[]{{}\\verb@#pydocsign#@{}}',
+                                                                 {hasnote: '--- #note#'}]},
+        'latexdocstrreq': {l_and(isrequired, isintent_nothide): ['\\item[]{{}\\verb@#pydocsign#@{}}',
+                                                                 {hasnote: '--- #note#'}]},
+        'latexdocstrout': {isintent_out: ['\\item[]{{}\\verb@#pydocsignout#@{}}',
+                                          {l_and(hasnote, isintent_hide): '--- #note#',
+                                           l_and(hasnote, isintent_nothide): '--- See above.'}]},
+        'depend': ''
+    },
+    # Required/Optional arguments
+    {
+        'kwlist': '"#varname#",',
+        'docsign': '#varname#,',
+        '_check': l_and(isintent_nothide, l_not(isoptional))
+    },
+    {
+        'kwlistopt': '"#varname#",',
+        'docsignopt': '#varname#=#showinit#,',
+        'docsignoptshort': '#varname#,',
+        '_check': l_and(isintent_nothide, isoptional)
+    },
+    # Docstring/BuildValue
+    {
+        'docreturn': '#outvarname#,',
+        'returnformat': '#varrformat#',
+        '_check': isintent_out
+    },
+    # Externals (call-back functions)
+    {  # Common
+        'docsignxa': {isintent_nothide: '#varname#_extra_args=(),'},
+        'docsignxashort': {isintent_nothide: '#varname#_extra_args,'},
+        'docstropt': {isintent_nothide: '#varname#_extra_args : input tuple, optional\\n    Default: ()'},
+        'docstrcbs': '#cbdocstr#',
+        'latexdocstrcbs': '\\item[] #cblatexdocstr#',
+        'latexdocstropt': {isintent_nothide: '\\item[]{{}\\verb@#varname#_extra_args := () input tuple@{}} --- Extra arguments for call-back function {{}\\verb@#varname#@{}}.'},
+        'decl': ['    #cbname#_t #varname#_cb = { Py_None, NULL, 0 };',
+                 '    #cbname#_t *#varname#_cb_ptr = &#varname#_cb;',
+                 '    PyTupleObject *#varname#_xa_capi = NULL;',
+                 {l_not(isintent_callback):
+                  '    #cbname#_typedef #varname#_cptr;'}
+                 ],
+        'kwlistxa': {isintent_nothide: '"#varname#_extra_args",'},
+        'argformat': {isrequired: 'O'},
+        'keyformat': {isoptional: 'O'},
+        'xaformat': {isintent_nothide: 'O!'},
+        'args_capi': {isrequired: ',&#varname#_cb.capi'},
+        'keys_capi': {isoptional: ',&#varname#_cb.capi'},
+        'keys_xa': ',&PyTuple_Type,&#varname#_xa_capi',
+        'setjmpbuf': '(setjmp(#varname#_cb.jmpbuf))',
+        'callfortran': {l_not(isintent_callback): '#varname#_cptr,'},
+        'need': ['#cbname#', 'setjmp.h'],
+        '_check': isexternal
+    },
+    {
+        'frompyobj': [{l_not(isintent_callback): """\
+if(F2PyCapsule_Check(#varname#_cb.capi)) {
+  #varname#_cptr = F2PyCapsule_AsVoidPtr(#varname#_cb.capi);
+} else {
+  #varname#_cptr = #cbname#;
+}
+"""}, {isintent_callback: """\
+if (#varname#_cb.capi==Py_None) {
+  #varname#_cb.capi = PyObject_GetAttrString(#modulename#_module,\"#varname#\");
+  if (#varname#_cb.capi) {
+    if (#varname#_xa_capi==NULL) {
+      if (PyObject_HasAttrString(#modulename#_module,\"#varname#_extra_args\")) {
+        PyObject* capi_tmp = PyObject_GetAttrString(#modulename#_module,\"#varname#_extra_args\");
+        if (capi_tmp) {
+          #varname#_xa_capi = (PyTupleObject *)PySequence_Tuple(capi_tmp);
+          Py_DECREF(capi_tmp);
+        }
+        else {
+          #varname#_xa_capi = (PyTupleObject *)Py_BuildValue(\"()\");
+        }
+        if (#varname#_xa_capi==NULL) {
+          PyErr_SetString(#modulename#_error,\"Failed to convert #modulename#.#varname#_extra_args to tuple.\\n\");
+          return NULL;
+        }
+      }
+    }
+  }
+  if (#varname#_cb.capi==NULL) {
+    PyErr_SetString(#modulename#_error,\"Callback #varname# not defined (as an argument or module #modulename# attribute).\\n\");
+    return NULL;
+  }
+}
+"""},
+            """\
+    if (create_cb_arglist(#varname#_cb.capi,#varname#_xa_capi,#maxnofargs#,#nofoptargs#,&#varname#_cb.nofargs,&#varname#_cb.args_capi,\"failed in processing argument list for call-back #varname#.\")) {
+""",
+            {debugcapi: ["""\
+        fprintf(stderr,\"debug-capi:Assuming %d arguments; at most #maxnofargs#(-#nofoptargs#) is expected.\\n\",#varname#_cb.nofargs);
+        CFUNCSMESSPY(\"for #varname#=\",#varname#_cb.capi);""",
+                         {l_not(isintent_callback): """        fprintf(stderr,\"#vardebugshowvalue# (call-back in C).\\n\",#cbname#);"""}]},
+            """\
+        CFUNCSMESS(\"Saving callback variables for `#varname#`.\\n\");
+        #varname#_cb_ptr = swap_active_#cbname#(#varname#_cb_ptr);""",
+        ],
+        'cleanupfrompyobj':
+        """\
+        CFUNCSMESS(\"Restoring callback variables for `#varname#`.\\n\");
+        #varname#_cb_ptr = swap_active_#cbname#(#varname#_cb_ptr);
+        Py_DECREF(#varname#_cb.args_capi);
+    }""",
+        'need': ['SWAP', 'create_cb_arglist'],
+        '_check': isexternal,
+        '_depend': ''
+    },
+    # Scalars (not complex)
+    {  # Common
+        'decl': '    #ctype# #varname# = 0;',
+        'pyobjfrom': {debugcapi: '    fprintf(stderr,"#vardebugshowvalue#\\n",#varname#);'},
+        'callfortran': {l_or(isintent_c, isattr_value): '#varname#,', l_not(l_or(isintent_c, isattr_value)): '&#varname#,'},
+        'return': {isintent_out: ',#varname#'},
+        '_check': l_and(isscalar, l_not(iscomplex))
+    }, {
+        'need': {hasinitvalue: 'math.h'},
+        '_check': l_and(isscalar, l_not(iscomplex)),
+    }, {  # Not hidden
+        'decl': '    PyObject *#varname#_capi = Py_None;',
+        'argformat': {isrequired: 'O'},
+        'keyformat': {isoptional: 'O'},
+        'args_capi': {isrequired: ',&#varname#_capi'},
+        'keys_capi': {isoptional: ',&#varname#_capi'},
+        'pyobjfrom': {isintent_inout: """\
+    f2py_success = try_pyarr_from_#ctype#(#varname#_capi,&#varname#);
+    if (f2py_success) {"""},
+        'closepyobjfrom': {isintent_inout: "    } /*if (f2py_success) of #varname# pyobjfrom*/"},
+        'need': {isintent_inout: 'try_pyarr_from_#ctype#'},
+        '_check': l_and(isscalar, l_not(iscomplex), l_not(isstring),
+                        isintent_nothide)
+    }, {
+        'frompyobj': [
+            # hasinitvalue...
+            #   if pyobj is None:
+            #     varname = init
+            #   else
+            #     from_pyobj(varname)
+            #
+            # isoptional and noinitvalue...
+            #   if pyobj is not None:
+            #     from_pyobj(varname)
+            #   else:
+            #     varname is uninitialized
+            #
+            # ...
+            #   from_pyobj(varname)
+            #
+            {hasinitvalue: '    if (#varname#_capi == Py_None) #varname# = #init#; else',
+             '_depend': ''},
+            {l_and(isoptional, l_not(hasinitvalue)): '    if (#varname#_capi != Py_None)',
+             '_depend': ''},
+            {l_not(islogical): '''\
+        f2py_success = #ctype#_from_pyobj(&#varname#,#varname#_capi,"#pyname#() #nth# (#varname#) can\'t be converted to #ctype#");
+    if (f2py_success) {'''},
+            {islogical: '''\
+        #varname# = (#ctype#)PyObject_IsTrue(#varname#_capi);
+        f2py_success = 1;
+    if (f2py_success) {'''},
+        ],
+        'cleanupfrompyobj': '    } /*if (f2py_success) of #varname#*/',
+        'need': {l_not(islogical): '#ctype#_from_pyobj'},
+        '_check': l_and(isscalar, l_not(iscomplex), isintent_nothide),
+        '_depend': ''
+    }, {  # Hidden
+        'frompyobj': {hasinitvalue: '    #varname# = #init#;'},
+        'need': typedef_need_dict,
+        '_check': l_and(isscalar, l_not(iscomplex), isintent_hide),
+        '_depend': ''
+    }, {  # Common
+        'frompyobj': {debugcapi: '    fprintf(stderr,"#vardebugshowvalue#\\n",#varname#);'},
+        '_check': l_and(isscalar, l_not(iscomplex)),
+        '_depend': ''
+    },
+    # Complex scalars
+    {  # Common
+        'decl': '    #ctype# #varname#;',
+        'callfortran': {isintent_c: '#varname#,', l_not(isintent_c): '&#varname#,'},
+        'pyobjfrom': {debugcapi: '    fprintf(stderr,"#vardebugshowvalue#\\n",#varname#.r,#varname#.i);'},
+        'return': {isintent_out: ',#varname#_capi'},
+        '_check': iscomplex
+    }, {  # Not hidden
+        'decl': '    PyObject *#varname#_capi = Py_None;',
+        'argformat': {isrequired: 'O'},
+        'keyformat': {isoptional: 'O'},
+        'args_capi': {isrequired: ',&#varname#_capi'},
+        'keys_capi': {isoptional: ',&#varname#_capi'},
+        'need': {isintent_inout: 'try_pyarr_from_#ctype#'},
+        'pyobjfrom': {isintent_inout: """\
+        f2py_success = try_pyarr_from_#ctype#(#varname#_capi,&#varname#);
+        if (f2py_success) {"""},
+        'closepyobjfrom': {isintent_inout: "        } /*if (f2py_success) of #varname# pyobjfrom*/"},
+        '_check': l_and(iscomplex, isintent_nothide)
+    }, {
+        'frompyobj': [{hasinitvalue: '    if (#varname#_capi==Py_None) {#varname#.r = #init.r#, #varname#.i = #init.i#;} else'},
+                      {l_and(isoptional, l_not(hasinitvalue))
+                             : '    if (#varname#_capi != Py_None)'},
+                      '        f2py_success = #ctype#_from_pyobj(&#varname#,#varname#_capi,"#pyname#() #nth# (#varname#) can\'t be converted to #ctype#");'
+                      '\n    if (f2py_success) {'],
+        'cleanupfrompyobj': '    }  /*if (f2py_success) of #varname# frompyobj*/',
+        'need': ['#ctype#_from_pyobj'],
+        '_check': l_and(iscomplex, isintent_nothide),
+        '_depend': ''
+    }, {  # Hidden
+        'decl': {isintent_out: '    PyObject *#varname#_capi = Py_None;'},
+        '_check': l_and(iscomplex, isintent_hide)
+    }, {
+        'frompyobj': {hasinitvalue: '    #varname#.r = #init.r#, #varname#.i = #init.i#;'},
+        '_check': l_and(iscomplex, isintent_hide),
+        '_depend': ''
+    }, {  # Common
+        'pyobjfrom': {isintent_out: '    #varname#_capi = pyobj_from_#ctype#1(#varname#);'},
+        'need': ['pyobj_from_#ctype#1'],
+        '_check': iscomplex
+    }, {
+        'frompyobj': {debugcapi: '    fprintf(stderr,"#vardebugshowvalue#\\n",#varname#.r,#varname#.i);'},
+        '_check': iscomplex,
+        '_depend': ''
+    },
+    # String
+    {  # Common
+        'decl': ['    #ctype# #varname# = NULL;',
+                 '    int slen(#varname#);',
+                 '    PyObject *#varname#_capi = Py_None;'],
+        'callfortran': '#varname#,',
+        'callfortranappend': 'slen(#varname#),',
+        'pyobjfrom': [
+            {debugcapi:
+             '    fprintf(stderr,'
+             '"#vardebugshowvalue#\\n",slen(#varname#),#varname#);'},
+            # The trailing null value for Fortran is blank.
+            {l_and(isintent_out, l_not(isintent_c)):
+             "        STRINGPADN(#varname#, slen(#varname#), ' ', '\\0');"},
+        ],
+        'return': {isintent_out: ',#varname#'},
+        'need': ['len..',
+                 {l_and(isintent_out, l_not(isintent_c)): 'STRINGPADN'}],
+        '_check': isstring
+    }, {  # Common
+        'frompyobj': [
+            """\
+    slen(#varname#) = #elsize#;
+    f2py_success = #ctype#_from_pyobj(&#varname#,&slen(#varname#),#init#,"""
+"""#varname#_capi,\"#ctype#_from_pyobj failed in converting #nth#"""
+"""`#varname#\' of #pyname# to C #ctype#\");
+    if (f2py_success) {""",
+            # The trailing null value for Fortran is blank.
+            {l_not(isintent_c):
+             "        STRINGPADN(#varname#, slen(#varname#), '\\0', ' ');"},
+        ],
+        'cleanupfrompyobj': """\
+        STRINGFREE(#varname#);
+    }  /*if (f2py_success) of #varname#*/""",
+        'need': ['#ctype#_from_pyobj', 'len..', 'STRINGFREE',
+                 {l_not(isintent_c): 'STRINGPADN'}],
+        '_check': isstring,
+        '_depend': ''
+    }, {  # Not hidden
+        'argformat': {isrequired: 'O'},
+        'keyformat': {isoptional: 'O'},
+        'args_capi': {isrequired: ',&#varname#_capi'},
+        'keys_capi': {isoptional: ',&#varname#_capi'},
+        'pyobjfrom': [
+            {l_and(isintent_inout, l_not(isintent_c)):
+             "        STRINGPADN(#varname#, slen(#varname#), ' ', '\\0');"},
+            {isintent_inout: '''\
+    f2py_success = try_pyarr_from_#ctype#(#varname#_capi, #varname#,
+                                          slen(#varname#));
+    if (f2py_success) {'''}],
+        'closepyobjfrom': {isintent_inout: '    } /*if (f2py_success) of #varname# pyobjfrom*/'},
+        'need': {isintent_inout: 'try_pyarr_from_#ctype#',
+                 l_and(isintent_inout, l_not(isintent_c)): 'STRINGPADN'},
+        '_check': l_and(isstring, isintent_nothide)
+    }, {  # Hidden
+        '_check': l_and(isstring, isintent_hide)
+    }, {
+        'frompyobj': {debugcapi: '    fprintf(stderr,"#vardebugshowvalue#\\n",slen(#varname#),#varname#);'},
+        '_check': isstring,
+        '_depend': ''
+    },
+    # Array
+    {  # Common
+        'decl': ['    #ctype# *#varname# = NULL;',
+                 '    npy_intp #varname#_Dims[#rank#] = {#rank*[-1]#};',
+                 '    const int #varname#_Rank = #rank#;',
+                 '    PyArrayObject *capi_#varname#_as_array = NULL;',
+                 '    int capi_#varname#_intent = 0;',
+                 {isstringarray: '    int slen(#varname#) = 0;'},
+                 ],
+        'callfortran': '#varname#,',
+        'callfortranappend': {isstringarray: 'slen(#varname#),'},
+        'return': {isintent_out: ',capi_#varname#_as_array'},
+        'need': 'len..',
+        '_check': isarray
+    }, {  # intent(overwrite) array
+        'decl': '    int capi_overwrite_#varname# = 1;',
+        'kwlistxa': '"overwrite_#varname#",',
+        'xaformat': 'i',
+        'keys_xa': ',&capi_overwrite_#varname#',
+        'docsignxa': 'overwrite_#varname#=1,',
+        'docsignxashort': 'overwrite_#varname#,',
+        'docstropt': 'overwrite_#varname# : input int, optional\\n    Default: 1',
+        '_check': l_and(isarray, isintent_overwrite),
+    }, {
+        'frompyobj': '    capi_#varname#_intent |= (capi_overwrite_#varname#?0:F2PY_INTENT_COPY);',
+        '_check': l_and(isarray, isintent_overwrite),
+        '_depend': '',
+    },
+    {  # intent(copy) array
+        'decl': '    int capi_overwrite_#varname# = 0;',
+        'kwlistxa': '"overwrite_#varname#",',
+        'xaformat': 'i',
+        'keys_xa': ',&capi_overwrite_#varname#',
+        'docsignxa': 'overwrite_#varname#=0,',
+        'docsignxashort': 'overwrite_#varname#,',
+        'docstropt': 'overwrite_#varname# : input int, optional\\n    Default: 0',
+        '_check': l_and(isarray, isintent_copy),
+    }, {
+        'frompyobj': '    capi_#varname#_intent |= (capi_overwrite_#varname#?0:F2PY_INTENT_COPY);',
+        '_check': l_and(isarray, isintent_copy),
+        '_depend': '',
+    }, {
+        'need': [{hasinitvalue: 'forcomb'}, {hasinitvalue: 'CFUNCSMESS'}],
+        '_check': isarray,
+        '_depend': ''
+    }, {  # Not hidden
+        'decl': '    PyObject *#varname#_capi = Py_None;',
+        'argformat': {isrequired: 'O'},
+        'keyformat': {isoptional: 'O'},
+        'args_capi': {isrequired: ',&#varname#_capi'},
+        'keys_capi': {isoptional: ',&#varname#_capi'},
+        '_check': l_and(isarray, isintent_nothide)
+    }, {
+        'frompyobj': [
+            '    #setdims#;',
+            '    capi_#varname#_intent |= #intent#;',
+            ('    const char capi_errmess[] = "#modulename#.#pyname#:'
+             ' failed to create array from the #nth# `#varname#`";'),
+            {isintent_hide:
+             '    capi_#varname#_as_array = ndarray_from_pyobj('
+             '  #atype#,#elsize#,#varname#_Dims,#varname#_Rank,'
+             '  capi_#varname#_intent,Py_None,capi_errmess);'},
+            {isintent_nothide:
+             '    capi_#varname#_as_array = ndarray_from_pyobj('
+             '  #atype#,#elsize#,#varname#_Dims,#varname#_Rank,'
+             '  capi_#varname#_intent,#varname#_capi,capi_errmess);'},
+            """\
+    if (capi_#varname#_as_array == NULL) {
+        PyObject* capi_err = PyErr_Occurred();
+        if (capi_err == NULL) {
+            capi_err = #modulename#_error;
+            PyErr_SetString(capi_err, capi_errmess);
+        }
+    } else {
+        #varname# = (#ctype# *)(PyArray_DATA(capi_#varname#_as_array));
+""",
+            {isstringarray:
+             '    slen(#varname#) = f2py_itemsize(#varname#);'},
+            {hasinitvalue: [
+                {isintent_nothide:
+                 '    if (#varname#_capi == Py_None) {'},
+                {isintent_hide: '    {'},
+                {iscomplexarray: '        #ctype# capi_c;'},
+                """\
+        int *_i,capi_i=0;
+        CFUNCSMESS(\"#name#: Initializing #varname#=#init#\\n\");
+        struct ForcombCache cache;
+        if (initforcomb(&cache, PyArray_DIMS(capi_#varname#_as_array),
+                        PyArray_NDIM(capi_#varname#_as_array),1)) {
+            while ((_i = nextforcomb(&cache)))
+                #varname#[capi_i++] = #init#; /* fortran way */
+        } else {
+            PyObject *exc, *val, *tb;
+            PyErr_Fetch(&exc, &val, &tb);
+            PyErr_SetString(exc ? exc : #modulename#_error,
+                \"Initialization of #nth# #varname# failed (initforcomb).\");
+            npy_PyErr_ChainExceptionsCause(exc, val, tb);
+            f2py_success = 0;
+        }
+    }
+    if (f2py_success) {"""]},
+                      ],
+        'cleanupfrompyobj': [  # note that this list will be reversed
+            '    }  '
+            '/* if (capi_#varname#_as_array == NULL) ... else of #varname# */',
+            {l_not(l_or(isintent_out, isintent_hide)): """\
+    if((PyObject *)capi_#varname#_as_array!=#varname#_capi) {
+        Py_XDECREF(capi_#varname#_as_array); }"""},
+            {l_and(isintent_hide, l_not(isintent_out))
+                   : """        Py_XDECREF(capi_#varname#_as_array);"""},
+            {hasinitvalue: '    }  /*if (f2py_success) of #varname# init*/'},
+        ],
+        '_check': isarray,
+        '_depend': ''
+    },
+    # Scalararray
+    {  # Common
+        '_check': l_and(isarray, l_not(iscomplexarray))
+    }, {  # Not hidden
+        '_check': l_and(isarray, l_not(iscomplexarray), isintent_nothide)
+    },
+    # Integer*1 array
+    {'need': '#ctype#',
+     '_check': isint1array,
+     '_depend': ''
+     },
+    # Integer*-1 array
+    {'need': '#ctype#',
+     '_check': isunsigned_chararray,
+     '_depend': ''
+     },
+    # Integer*-2 array
+    {'need': '#ctype#',
+     '_check': isunsigned_shortarray,
+     '_depend': ''
+     },
+    # Integer*-8 array
+    {'need': '#ctype#',
+     '_check': isunsigned_long_longarray,
+     '_depend': ''
+     },
+    # Complexarray
+    {'need': '#ctype#',
+     '_check': iscomplexarray,
+     '_depend': ''
+     },
+    # Character
+    {
+        'need': 'string',
+        '_check': ischaracter,
+    },
+    # Character array
+    {
+        'need': 'string',
+        '_check': ischaracterarray,
+    },
+    # Stringarray
+    {
+        'callfortranappend': {isarrayofstrings: 'flen(#varname#),'},
+        'need': 'string',
+        '_check': isstringarray
+    }
+]
+
+################# Rules for checking ###############
+
+check_rules = [
+    {
+        'frompyobj': {debugcapi: '    fprintf(stderr,\"debug-capi:Checking `#check#\'\\n\");'},
+        'need': 'len..'
+    }, {
+        'frompyobj': '    CHECKSCALAR(#check#,\"#check#\",\"#nth# #varname#\",\"#varshowvalue#\",#varname#) {',
+        'cleanupfrompyobj': '    } /*CHECKSCALAR(#check#)*/',
+        'need': 'CHECKSCALAR',
+        '_check': l_and(isscalar, l_not(iscomplex)),
+        '_break': ''
+    }, {
+        'frompyobj': '    CHECKSTRING(#check#,\"#check#\",\"#nth# #varname#\",\"#varshowvalue#\",#varname#) {',
+        'cleanupfrompyobj': '    } /*CHECKSTRING(#check#)*/',
+        'need': 'CHECKSTRING',
+        '_check': isstring,
+        '_break': ''
+    }, {
+        'need': 'CHECKARRAY',
+        'frompyobj': '    CHECKARRAY(#check#,\"#check#\",\"#nth# #varname#\") {',
+        'cleanupfrompyobj': '    } /*CHECKARRAY(#check#)*/',
+        '_check': isarray,
+        '_break': ''
+    }, {
+        'need': 'CHECKGENERIC',
+        'frompyobj': '    CHECKGENERIC(#check#,\"#check#\",\"#nth# #varname#\") {',
+        'cleanupfrompyobj': '    } /*CHECKGENERIC(#check#)*/',
+    }
+]
+
+########## Applying the rules. No need to modify what follows #############
+
+#################### Build C/API module #######################
+
+
+def buildmodule(m, um):
+    """
+    Return
+    """
+    outmess(f"    Building module \"{m['name']}\"...\n")
+    ret = {}
+    mod_rules = defmod_rules[:]
+    vrd = capi_maps.modsign2map(m)
+    rd = dictappend({'f2py_version': f2py_version}, vrd)
+    funcwrappers = []
+    funcwrappers2 = []  # F90 codes
+    for n in m['interfaced']:
+        nb = None
+        for bi in m['body']:
+            if bi['block'] not in ['interface', 'abstract interface']:
+                errmess('buildmodule: Expected interface block. Skipping.\n')
+                continue
+            for b in bi['body']:
+                if b['name'] == n:
+                    nb = b
+                    break
+
+        if not nb:
+            print(
+                f'buildmodule: Could not find the body of interfaced routine "{n}". Skipping.\n', file=sys.stderr)
+            continue
+        nb_list = [nb]
+        if 'entry' in nb:
+            for k, a in nb['entry'].items():
+                nb1 = copy.deepcopy(nb)
+                del nb1['entry']
+                nb1['name'] = k
+                nb1['args'] = a
+                nb_list.append(nb1)
+        for nb in nb_list:
+            # requiresf90wrapper must be called before buildapi as it
+            # rewrites assumed shape arrays as automatic arrays.
+            isf90 = requiresf90wrapper(nb)
+            # options is in scope here
+            if options['emptygen']:
+                b_path = options['buildpath']
+                m_name = vrd['modulename']
+                outmess('    Generating possibly empty wrappers"\n')
+                Path(f"{b_path}/{vrd['coutput']}").touch()
+                if isf90:
+                    # f77 + f90 wrappers
+                    outmess(f'    Maybe empty "{m_name}-f2pywrappers2.f90"\n')
+                    Path(f'{b_path}/{m_name}-f2pywrappers2.f90').touch()
+                    outmess(f'    Maybe empty "{m_name}-f2pywrappers.f"\n')
+                    Path(f'{b_path}/{m_name}-f2pywrappers.f').touch()
+                else:
+                    # only f77 wrappers
+                    outmess(f'    Maybe empty "{m_name}-f2pywrappers.f"\n')
+                    Path(f'{b_path}/{m_name}-f2pywrappers.f').touch()
+            api, wrap = buildapi(nb)
+            if wrap:
+                if isf90:
+                    funcwrappers2.append(wrap)
+                else:
+                    funcwrappers.append(wrap)
+            ar = applyrules(api, vrd)
+            rd = dictappend(rd, ar)
+
+    # Construct COMMON block support
+    cr, wrap = common_rules.buildhooks(m)
+    if wrap:
+        funcwrappers.append(wrap)
+    ar = applyrules(cr, vrd)
+    rd = dictappend(rd, ar)
+
+    # Construct F90 module support
+    mr, wrap = f90mod_rules.buildhooks(m)
+    if wrap:
+        funcwrappers2.append(wrap)
+    ar = applyrules(mr, vrd)
+    rd = dictappend(rd, ar)
+
+    for u in um:
+        ar = use_rules.buildusevars(u, m['use'][u['name']])
+        rd = dictappend(rd, ar)
+
+    needs = cfuncs.get_needs()
+    # Add mapped definitions
+    needs['typedefs'] += [cvar for cvar in capi_maps.f2cmap_mapped  #
+                          if cvar in typedef_need_dict.values()]
+    code = {}
+    for n in needs.keys():
+        code[n] = []
+        for k in needs[n]:
+            c = ''
+            if k in cfuncs.includes0:
+                c = cfuncs.includes0[k]
+            elif k in cfuncs.includes:
+                c = cfuncs.includes[k]
+            elif k in cfuncs.userincludes:
+                c = cfuncs.userincludes[k]
+            elif k in cfuncs.typedefs:
+                c = cfuncs.typedefs[k]
+            elif k in cfuncs.typedefs_generated:
+                c = cfuncs.typedefs_generated[k]
+            elif k in cfuncs.cppmacros:
+                c = cfuncs.cppmacros[k]
+            elif k in cfuncs.cfuncs:
+                c = cfuncs.cfuncs[k]
+            elif k in cfuncs.callbacks:
+                c = cfuncs.callbacks[k]
+            elif k in cfuncs.f90modhooks:
+                c = cfuncs.f90modhooks[k]
+            elif k in cfuncs.commonhooks:
+                c = cfuncs.commonhooks[k]
+            else:
+                errmess(f'buildmodule: unknown need {repr(k)}.\n')
+                continue
+            code[n].append(c)
+    mod_rules.append(code)
+    for r in mod_rules:
+        if ('_check' in r and r['_check'](m)) or ('_check' not in r):
+            ar = applyrules(r, vrd, m)
+            rd = dictappend(rd, ar)
+    ar = applyrules(module_rules, rd)
+
+    fn = os.path.join(options['buildpath'], vrd['coutput'])
+    ret['csrc'] = fn
+    with open(fn, 'w') as f:
+        f.write(ar['modulebody'].replace('\t', 2 * ' '))
+    outmess(f"    Wrote C/API module \"{m['name']}\" to file \"{fn}\"\n")
+
+    if options['dorestdoc']:
+        fn = os.path.join(
+            options['buildpath'], vrd['modulename'] + 'module.rest')
+        with open(fn, 'w') as f:
+            f.write('.. -*- rest -*-\n')
+            f.write('\n'.join(ar['restdoc']))
+        outmess('    ReST Documentation is saved to file "%s/%smodule.rest"\n' %
+                (options['buildpath'], vrd['modulename']))
+    if options['dolatexdoc']:
+        fn = os.path.join(
+            options['buildpath'], vrd['modulename'] + 'module.tex')
+        ret['ltx'] = fn
+        with open(fn, 'w') as f:
+            f.write(
+                f'% This file is auto-generated with f2py (version:{f2py_version})\n')
+            if 'shortlatex' not in options:
+                f.write(
+                    '\\documentclass{article}\n\\usepackage{a4wide}\n\\begin{document}\n\\tableofcontents\n\n')
+                f.write('\n'.join(ar['latexdoc']))
+            if 'shortlatex' not in options:
+                f.write('\\end{document}')
+        outmess('    Documentation is saved to file "%s/%smodule.tex"\n' %
+                (options['buildpath'], vrd['modulename']))
+    if funcwrappers:
+        wn = os.path.join(options['buildpath'], vrd['f2py_wrapper_output'])
+        ret['fsrc'] = wn
+        with open(wn, 'w') as f:
+            f.write('C     -*- fortran -*-\n')
+            f.write(
+                f'C     This file is autogenerated with f2py (version:{f2py_version})\n')
+            f.write(
+                'C     It contains Fortran 77 wrappers to fortran functions.\n')
+            lines = []
+            for l in ('\n\n'.join(funcwrappers) + '\n').split('\n'):
+                if 0 <= l.find('!') < 66:
+                    # don't split comment lines
+                    lines.append(l + '\n')
+                elif l and l[0] == ' ':
+                    while len(l) >= 66:
+                        lines.append(l[:66] + '\n     &')
+                        l = l[66:]
+                    lines.append(l + '\n')
+                else:
+                    lines.append(l + '\n')
+            lines = ''.join(lines).replace('\n     &\n', '\n')
+            f.write(lines)
+        outmess(f'    Fortran 77 wrappers are saved to "{wn}\"\n')
+    if funcwrappers2:
+        wn = os.path.join(
+            options['buildpath'], f"{vrd['modulename']}-f2pywrappers2.f90")
+        ret['fsrc'] = wn
+        with open(wn, 'w') as f:
+            f.write('!     -*- f90 -*-\n')
+            f.write(
+                f'!     This file is autogenerated with f2py (version:{f2py_version})\n')
+            f.write(
+                '!     It contains Fortran 90 wrappers to fortran functions.\n')
+            lines = []
+            for l in ('\n\n'.join(funcwrappers2) + '\n').split('\n'):
+                if 0 <= l.find('!') < 72:
+                    # don't split comment lines
+                    lines.append(l + '\n')
+                elif len(l) > 72 and l[0] == ' ':
+                    lines.append(l[:72] + '&\n     &')
+                    l = l[72:]
+                    while len(l) > 66:
+                        lines.append(l[:66] + '&\n     &')
+                        l = l[66:]
+                    lines.append(l + '\n')
+                else:
+                    lines.append(l + '\n')
+            lines = ''.join(lines).replace('\n     &\n', '\n')
+            f.write(lines)
+        outmess(f'    Fortran 90 wrappers are saved to "{wn}\"\n')
+    return ret
+
+################## Build C/API function #############
+
+
+stnd = {1: 'st', 2: 'nd', 3: 'rd', 4: 'th', 5: 'th',
+        6: 'th', 7: 'th', 8: 'th', 9: 'th', 0: 'th'}
+
+
+def buildapi(rout):
+    rout, wrap = func2subr.assubr(rout)
+    args, depargs = getargs2(rout)
+    capi_maps.depargs = depargs
+    var = rout['vars']
+
+    if ismoduleroutine(rout):
+        outmess('            Constructing wrapper function "%s.%s"...\n' %
+                (rout['modulename'], rout['name']))
+    else:
+        outmess(f"        Constructing wrapper function \"{rout['name']}\"...\n")
+    # Routine
+    vrd = capi_maps.routsign2map(rout)
+    rd = dictappend({}, vrd)
+    for r in rout_rules:
+        if ('_check' in r and r['_check'](rout)) or ('_check' not in r):
+            ar = applyrules(r, vrd, rout)
+            rd = dictappend(rd, ar)
+
+    # Args
+    nth, nthk = 0, 0
+    savevrd = {}
+    for a in args:
+        vrd = capi_maps.sign2map(a, var[a])
+        if isintent_aux(var[a]):
+            _rules = aux_rules
+        else:
+            _rules = arg_rules
+            if not isintent_hide(var[a]):
+                if not isoptional(var[a]):
+                    nth = nth + 1
+                    vrd['nth'] = repr(nth) + stnd[nth % 10] + ' argument'
+                else:
+                    nthk = nthk + 1
+                    vrd['nth'] = repr(nthk) + stnd[nthk % 10] + ' keyword'
+            else:
+                vrd['nth'] = 'hidden'
+        savevrd[a] = vrd
+        for r in _rules:
+            if '_depend' in r:
+                continue
+            if ('_check' in r and r['_check'](var[a])) or ('_check' not in r):
+                ar = applyrules(r, vrd, var[a])
+                rd = dictappend(rd, ar)
+                if '_break' in r:
+                    break
+    for a in depargs:
+        if isintent_aux(var[a]):
+            _rules = aux_rules
+        else:
+            _rules = arg_rules
+        vrd = savevrd[a]
+        for r in _rules:
+            if '_depend' not in r:
+                continue
+            if ('_check' in r and r['_check'](var[a])) or ('_check' not in r):
+                ar = applyrules(r, vrd, var[a])
+                rd = dictappend(rd, ar)
+                if '_break' in r:
+                    break
+        if 'check' in var[a]:
+            for c in var[a]['check']:
+                vrd['check'] = c
+                ar = applyrules(check_rules, vrd, var[a])
+                rd = dictappend(rd, ar)
+    if isinstance(rd['cleanupfrompyobj'], list):
+        rd['cleanupfrompyobj'].reverse()
+    if isinstance(rd['closepyobjfrom'], list):
+        rd['closepyobjfrom'].reverse()
+    rd['docsignature'] = stripcomma(replace('#docsign##docsignopt##docsignxa#',
+                                            {'docsign': rd['docsign'],
+                                             'docsignopt': rd['docsignopt'],
+                                             'docsignxa': rd['docsignxa']}))
+    optargs = stripcomma(replace('#docsignopt##docsignxa#',
+                                 {'docsignxa': rd['docsignxashort'],
+                                  'docsignopt': rd['docsignoptshort']}
+                                 ))
+    if optargs == '':
+        rd['docsignatureshort'] = stripcomma(
+            replace('#docsign#', {'docsign': rd['docsign']}))
+    else:
+        rd['docsignatureshort'] = replace('#docsign#[#docsignopt#]',
+                                          {'docsign': rd['docsign'],
+                                           'docsignopt': optargs,
+                                           })
+    rd['latexdocsignatureshort'] = rd['docsignatureshort'].replace('_', '\\_')
+    rd['latexdocsignatureshort'] = rd[
+        'latexdocsignatureshort'].replace(',', ', ')
+    cfs = stripcomma(replace('#callfortran##callfortranappend#', {
+                     'callfortran': rd['callfortran'], 'callfortranappend': rd['callfortranappend']}))
+    if len(rd['callfortranappend']) > 1:
+        rd['callcompaqfortran'] = stripcomma(replace('#callfortran# 0,#callfortranappend#', {
+                                             'callfortran': rd['callfortran'], 'callfortranappend': rd['callfortranappend']}))
+    else:
+        rd['callcompaqfortran'] = cfs
+    rd['callfortran'] = cfs
+    if isinstance(rd['docreturn'], list):
+        rd['docreturn'] = stripcomma(
+            replace('#docreturn#', {'docreturn': rd['docreturn']})) + ' = '
+    rd['docstrsigns'] = []
+    rd['latexdocstrsigns'] = []
+    for k in ['docstrreq', 'docstropt', 'docstrout', 'docstrcbs']:
+        if k in rd and isinstance(rd[k], list):
+            rd['docstrsigns'] = rd['docstrsigns'] + rd[k]
+        k = 'latex' + k
+        if k in rd and isinstance(rd[k], list):
+            rd['latexdocstrsigns'] = rd['latexdocstrsigns'] + rd[k][0:1] +\
+                ['\\begin{description}'] + rd[k][1:] +\
+                ['\\end{description}']
+
+    ar = applyrules(routine_rules, rd)
+    if ismoduleroutine(rout):
+        outmess(f"              {ar['docshort']}\n")
+    else:
+        outmess(f"          {ar['docshort']}\n")
+    return ar, wrap
+
+
+#################### EOF rules.py #######################
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/rules.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/rules.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..811a38c2da89f891462d4b19f38a349207cba751
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/rules.pyi
@@ -0,0 +1,41 @@
+from collections.abc import Callable, Iterable, Mapping
+from typing import Any, Final, Literal as L, TypeAlias
+from typing_extensions import TypeVar
+
+from .__version__ import version
+from .auxfuncs import _Bool, _Var
+
+###
+
+_VT = TypeVar("_VT", default=str)
+
+_Predicate: TypeAlias = Callable[[_Var], _Bool]
+_RuleDict: TypeAlias = dict[str, _VT]
+_DefDict: TypeAlias = dict[_Predicate, _VT]
+
+###
+
+f2py_version: Final = version
+numpy_version: Final = version
+
+options: Final[dict[str, bool]] = ...
+sepdict: Final[dict[str, str]] = ...
+
+generationtime: Final[int] = ...
+typedef_need_dict: Final[_DefDict[str]] = ...
+
+module_rules: Final[_RuleDict[str | list[str] | _RuleDict]] = ...
+routine_rules: Final[_RuleDict[str | list[str] | _DefDict | _RuleDict]] = ...
+defmod_rules: Final[list[_RuleDict[str | _DefDict]]] = ...
+rout_rules: Final[list[_RuleDict[str | Any]]] = ...
+aux_rules: Final[list[_RuleDict[str | Any]]] = ...
+arg_rules: Final[list[_RuleDict[str | Any]]] = ...
+check_rules: Final[list[_RuleDict[str | Any]]] = ...
+
+stnd: Final[dict[L[1, 2, 3, 4, 5, 6, 7, 8, 9, 0], L["st", "nd", "rd", "th"]]] = ...
+
+def buildmodule(m: Mapping[str, str | Any], um: Iterable[Mapping[str, str | Any]]) -> _RuleDict: ...
+def buildapi(rout: Mapping[str, str]) -> tuple[_RuleDict, str]: ...
+
+# namespace pollution
+k: str
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/setup.cfg b/python/user_packages/Python313/site-packages/numpy/f2py/setup.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..fd3c6f4895e598adbd2c4c875052f464066a5742
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/setup.cfg
@@ -0,0 +1,3 @@
+[bdist_rpm]
+doc_files = docs/
+            tests/
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.py b/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.py
new file mode 100644
index 0000000000000000000000000000000000000000..47a3e6b61e63902df5d472373295ba707bcff2fe
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.py
@@ -0,0 +1,1518 @@
+"""Fortran/C symbolic expressions
+
+References:
+- J3/21-007: Draft Fortran 202x. https://j3-fortran.org/doc/year/21/21-007.pdf
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+
+# To analyze Fortran expressions to solve dimensions specifications,
+# for instances, we implement a minimal symbolic engine for parsing
+# expressions into a tree of expression instances. As a first
+# instance, we care only about arithmetic expressions involving
+# integers and operations like addition (+), subtraction (-),
+# multiplication (*), division (Fortran / is Python //, Fortran // is
+# concatenate), and exponentiation (**).  In addition, .pyf files may
+# contain C expressions that support here is implemented as well.
+#
+# TODO: support logical constants (Op.BOOLEAN)
+# TODO: support logical operators (.AND., ...)
+# TODO: support defined operators (.MYOP., ...)
+#
+__all__ = ['Expr']
+
+
+import re
+import warnings
+from enum import Enum
+from math import gcd
+
+
+class Language(Enum):
+    """
+    Used as Expr.tostring language argument.
+    """
+    Python = 0
+    Fortran = 1
+    C = 2
+
+
+class Op(Enum):
+    """
+    Used as Expr op attribute.
+    """
+    INTEGER = 10
+    REAL = 12
+    COMPLEX = 15
+    STRING = 20
+    ARRAY = 30
+    SYMBOL = 40
+    TERNARY = 100
+    APPLY = 200
+    INDEXING = 210
+    CONCAT = 220
+    RELATIONAL = 300
+    TERMS = 1000
+    FACTORS = 2000
+    REF = 3000
+    DEREF = 3001
+
+
+class RelOp(Enum):
+    """
+    Used in Op.RELATIONAL expression to specify the function part.
+    """
+    EQ = 1
+    NE = 2
+    LT = 3
+    LE = 4
+    GT = 5
+    GE = 6
+
+    @classmethod
+    def fromstring(cls, s, language=Language.C):
+        if language is Language.Fortran:
+            return {'.eq.': RelOp.EQ, '.ne.': RelOp.NE,
+                    '.lt.': RelOp.LT, '.le.': RelOp.LE,
+                    '.gt.': RelOp.GT, '.ge.': RelOp.GE}[s.lower()]
+        return {'==': RelOp.EQ, '!=': RelOp.NE, '<': RelOp.LT,
+                '<=': RelOp.LE, '>': RelOp.GT, '>=': RelOp.GE}[s]
+
+    def tostring(self, language=Language.C):
+        if language is Language.Fortran:
+            return {RelOp.EQ: '.eq.', RelOp.NE: '.ne.',
+                    RelOp.LT: '.lt.', RelOp.LE: '.le.',
+                    RelOp.GT: '.gt.', RelOp.GE: '.ge.'}[self]
+        return {RelOp.EQ: '==', RelOp.NE: '!=',
+                RelOp.LT: '<', RelOp.LE: '<=',
+                RelOp.GT: '>', RelOp.GE: '>='}[self]
+
+
+class ArithOp(Enum):
+    """
+    Used in Op.APPLY expression to specify the function part.
+    """
+    POS = 1
+    NEG = 2
+    ADD = 3
+    SUB = 4
+    MUL = 5
+    DIV = 6
+    POW = 7
+
+
+class OpError(Exception):
+    pass
+
+
+class Precedence(Enum):
+    """
+    Used as Expr.tostring precedence argument.
+    """
+    ATOM = 0
+    POWER = 1
+    UNARY = 2
+    PRODUCT = 3
+    SUM = 4
+    LT = 6
+    EQ = 7
+    LAND = 11
+    LOR = 12
+    TERNARY = 13
+    ASSIGN = 14
+    TUPLE = 15
+    NONE = 100
+
+
+integer_types = (int,)
+number_types = (int, float)
+
+
+def _pairs_add(d, k, v):
+    # Internal utility method for updating terms and factors data.
+    c = d.get(k)
+    if c is None:
+        d[k] = v
+    else:
+        c = c + v
+        if c:
+            d[k] = c
+        else:
+            del d[k]
+
+
+class ExprWarning(UserWarning):
+    pass
+
+
+def ewarn(message):
+    warnings.warn(message, ExprWarning, stacklevel=2)
+
+
+class Expr:
+    """Represents a Fortran expression as an op-data pair.
+
+    Expr instances are hashable and sortable.
+    """
+
+    @staticmethod
+    def parse(s, language=Language.C):
+        """Parse a Fortran expression to an Expr.
+        """
+        return fromstring(s, language=language)
+
+    def __init__(self, op, data):
+        assert isinstance(op, Op)
+
+        # sanity checks
+        if op is Op.INTEGER:
+            # data is a 2-tuple of numeric object and a kind value
+            # (default is 4)
+            assert isinstance(data, tuple) and len(data) == 2
+            assert isinstance(data[0], int)
+            assert isinstance(data[1], (int, str)), data
+        elif op is Op.REAL:
+            # data is a 2-tuple of numeric object and a kind value
+            # (default is 4)
+            assert isinstance(data, tuple) and len(data) == 2
+            assert isinstance(data[0], float)
+            assert isinstance(data[1], (int, str)), data
+        elif op is Op.COMPLEX:
+            # data is a 2-tuple of constant expressions
+            assert isinstance(data, tuple) and len(data) == 2
+        elif op is Op.STRING:
+            # data is a 2-tuple of quoted string and a kind value
+            # (default is 1)
+            assert isinstance(data, tuple) and len(data) == 2
+            assert (isinstance(data[0], str)
+                    and data[0][::len(data[0]) - 1] in ('""', "''", '@@'))
+            assert isinstance(data[1], (int, str)), data
+        elif op is Op.SYMBOL:
+            # data is any hashable object
+            assert hash(data) is not None
+        elif op in (Op.ARRAY, Op.CONCAT):
+            # data is a tuple of expressions
+            assert isinstance(data, tuple)
+            assert all(isinstance(item, Expr) for item in data), data
+        elif op in (Op.TERMS, Op.FACTORS):
+            # data is {<term|base>:<coeff|exponent>} where dict values
+            # are nonzero Python integers
+            assert isinstance(data, dict)
+        elif op is Op.APPLY:
+            # data is (<function>, <operands>, <kwoperands>) where
+            # operands are Expr instances
+            assert isinstance(data, tuple) and len(data) == 3
+            # function is any hashable object
+            assert hash(data[0]) is not None
+            assert isinstance(data[1], tuple)
+            assert isinstance(data[2], dict)
+        elif op is Op.INDEXING:
+            # data is (<object>, <indices>)
+            assert isinstance(data, tuple) and len(data) == 2
+            # function is any hashable object
+            assert hash(data[0]) is not None
+        elif op is Op.TERNARY:
+            # data is (<cond>, <expr1>, <expr2>)
+            assert isinstance(data, tuple) and len(data) == 3
+        elif op in (Op.REF, Op.DEREF):
+            # data is Expr instance
+            assert isinstance(data, Expr)
+        elif op is Op.RELATIONAL:
+            # data is (<relop>, <left>, <right>)
+            assert isinstance(data, tuple) and len(data) == 3
+        else:
+            raise NotImplementedError(
+                f'unknown op or missing sanity check: {op}')
+
+        self.op = op
+        self.data = data
+
+    def __eq__(self, other):
+        return (isinstance(other, Expr)
+                and self.op is other.op
+                and self.data == other.data)
+
+    def __hash__(self):
+        if self.op in (Op.TERMS, Op.FACTORS):
+            data = tuple(sorted(self.data.items()))
+        elif self.op is Op.APPLY:
+            data = self.data[:2] + tuple(sorted(self.data[2].items()))
+        else:
+            data = self.data
+        return hash((self.op, data))
+
+    def __lt__(self, other):
+        if isinstance(other, Expr):
+            if self.op is not other.op:
+                return self.op.value < other.op.value
+            if self.op in (Op.TERMS, Op.FACTORS):
+                return (tuple(sorted(self.data.items()))
+                        < tuple(sorted(other.data.items())))
+            if self.op is Op.APPLY:
+                if self.data[:2] != other.data[:2]:
+                    return self.data[:2] < other.data[:2]
+                return tuple(sorted(self.data[2].items())) < tuple(
+                    sorted(other.data[2].items()))
+            return self.data < other.data
+        return NotImplemented
+
+    def __le__(self, other): return self == other or self < other
+
+    def __gt__(self, other): return not (self <= other)
+
+    def __ge__(self, other): return not (self < other)
+
+    def __repr__(self):
+        return f'{type(self).__name__}({self.op}, {self.data!r})'
+
+    def __str__(self):
+        return self.tostring()
+
+    def tostring(self, parent_precedence=Precedence.NONE,
+                 language=Language.Fortran):
+        """Return a string representation of Expr.
+        """
+        if self.op in (Op.INTEGER, Op.REAL):
+            precedence = (Precedence.SUM if self.data[0] < 0
+                          else Precedence.ATOM)
+            r = str(self.data[0]) + (f'_{self.data[1]}'
+                                     if self.data[1] != 4 else '')
+        elif self.op is Op.COMPLEX:
+            r = ', '.join(item.tostring(Precedence.TUPLE, language=language)
+                          for item in self.data)
+            r = '(' + r + ')'
+            precedence = Precedence.ATOM
+        elif self.op is Op.SYMBOL:
+            precedence = Precedence.ATOM
+            r = str(self.data)
+        elif self.op is Op.STRING:
+            r = self.data[0]
+            if self.data[1] != 1:
+                r = self.data[1] + '_' + r
+            precedence = Precedence.ATOM
+        elif self.op is Op.ARRAY:
+            r = ', '.join(item.tostring(Precedence.TUPLE, language=language)
+                          for item in self.data)
+            r = '[' + r + ']'
+            precedence = Precedence.ATOM
+        elif self.op is Op.TERMS:
+            terms = []
+            for term, coeff in sorted(self.data.items()):
+                if coeff < 0:
+                    op = ' - '
+                    coeff = -coeff
+                else:
+                    op = ' + '
+                if coeff == 1:
+                    term = term.tostring(Precedence.SUM, language=language)
+                elif term == as_number(1):
+                    term = str(coeff)
+                else:
+                    term = f'{coeff} * ' + term.tostring(
+                        Precedence.PRODUCT, language=language)
+                if terms:
+                    terms.append(op)
+                elif op == ' - ':
+                    terms.append('-')
+                terms.append(term)
+            r = ''.join(terms) or '0'
+            precedence = Precedence.SUM if terms else Precedence.ATOM
+        elif self.op is Op.FACTORS:
+            factors = []
+            tail = []
+            for base, exp in sorted(self.data.items()):
+                op = ' * '
+                if exp == 1:
+                    factor = base.tostring(Precedence.PRODUCT,
+                                           language=language)
+                elif language is Language.C:
+                    if exp in range(2, 10):
+                        factor = base.tostring(Precedence.PRODUCT,
+                                               language=language)
+                        factor = ' * '.join([factor] * exp)
+                    elif exp in range(-10, 0):
+                        factor = base.tostring(Precedence.PRODUCT,
+                                               language=language)
+                        tail += [factor] * -exp
+                        continue
+                    else:
+                        factor = base.tostring(Precedence.TUPLE,
+                                               language=language)
+                        factor = f'pow({factor}, {exp})'
+                else:
+                    factor = base.tostring(Precedence.POWER,
+                                           language=language) + f' ** {exp}'
+                if factors:
+                    factors.append(op)
+                factors.append(factor)
+            if tail:
+                if not factors:
+                    factors += ['1']
+                factors += ['/', '(', ' * '.join(tail), ')']
+            r = ''.join(factors) or '1'
+            precedence = Precedence.PRODUCT if factors else Precedence.ATOM
+        elif self.op is Op.APPLY:
+            name, args, kwargs = self.data
+            if name is ArithOp.DIV and language is Language.C:
+                numer, denom = [arg.tostring(Precedence.PRODUCT,
+                                             language=language)
+                                for arg in args]
+                r = f'{numer} / {denom}'
+                precedence = Precedence.PRODUCT
+            else:
+                args = [arg.tostring(Precedence.TUPLE, language=language)
+                        for arg in args]
+                args += [k + '=' + v.tostring(Precedence.NONE)
+                         for k, v in kwargs.items()]
+                r = f'{name}({", ".join(args)})'
+                precedence = Precedence.ATOM
+        elif self.op is Op.INDEXING:
+            name = self.data[0]
+            args = [arg.tostring(Precedence.TUPLE, language=language)
+                    for arg in self.data[1:]]
+            r = f'{name}[{", ".join(args)}]'
+            precedence = Precedence.ATOM
+        elif self.op is Op.CONCAT:
+            args = [arg.tostring(Precedence.PRODUCT, language=language)
+                    for arg in self.data]
+            r = " // ".join(args)
+            precedence = Precedence.PRODUCT
+        elif self.op is Op.TERNARY:
+            cond, expr1, expr2 = [a.tostring(Precedence.TUPLE,
+                                             language=language)
+                                  for a in self.data]
+            if language is Language.C:
+                r = f'({cond}?{expr1}:{expr2})'
+            elif language is Language.Python:
+                r = f'({expr1} if {cond} else {expr2})'
+            elif language is Language.Fortran:
+                r = f'merge({expr1}, {expr2}, {cond})'
+            else:
+                raise NotImplementedError(
+                    f'tostring for {self.op} and {language}')
+            precedence = Precedence.ATOM
+        elif self.op is Op.REF:
+            r = '&' + self.data.tostring(Precedence.UNARY, language=language)
+            precedence = Precedence.UNARY
+        elif self.op is Op.DEREF:
+            r = '*' + self.data.tostring(Precedence.UNARY, language=language)
+            precedence = Precedence.UNARY
+        elif self.op is Op.RELATIONAL:
+            rop, left, right = self.data
+            precedence = (Precedence.EQ if rop in (RelOp.EQ, RelOp.NE)
+                          else Precedence.LT)
+            left = left.tostring(precedence, language=language)
+            right = right.tostring(precedence, language=language)
+            rop = rop.tostring(language=language)
+            r = f'{left} {rop} {right}'
+        else:
+            raise NotImplementedError(f'tostring for op {self.op}')
+        if parent_precedence.value < precedence.value:
+            # If parent precedence is higher than operand precedence,
+            # operand will be enclosed in parenthesis.
+            return '(' + r + ')'
+        return r
+
+    def __pos__(self):
+        return self
+
+    def __neg__(self):
+        return self * -1
+
+    def __add__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            if self.op is other.op:
+                if self.op in (Op.INTEGER, Op.REAL):
+                    return as_number(
+                        self.data[0] + other.data[0],
+                        max(self.data[1], other.data[1]))
+                if self.op is Op.COMPLEX:
+                    r1, i1 = self.data
+                    r2, i2 = other.data
+                    return as_complex(r1 + r2, i1 + i2)
+                if self.op is Op.TERMS:
+                    r = Expr(self.op, dict(self.data))
+                    for k, v in other.data.items():
+                        _pairs_add(r.data, k, v)
+                    return normalize(r)
+            if self.op is Op.COMPLEX and other.op in (Op.INTEGER, Op.REAL):
+                return self + as_complex(other)
+            elif self.op in (Op.INTEGER, Op.REAL) and other.op is Op.COMPLEX:
+                return as_complex(self) + other
+            elif self.op is Op.REAL and other.op is Op.INTEGER:
+                return self + as_real(other, kind=self.data[1])
+            elif self.op is Op.INTEGER and other.op is Op.REAL:
+                return as_real(self, kind=other.data[1]) + other
+            return as_terms(self) + as_terms(other)
+        return NotImplemented
+
+    def __radd__(self, other):
+        if isinstance(other, number_types):
+            return as_number(other) + self
+        return NotImplemented
+
+    def __sub__(self, other):
+        return self + (-other)
+
+    def __rsub__(self, other):
+        if isinstance(other, number_types):
+            return as_number(other) - self
+        return NotImplemented
+
+    def __mul__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            if self.op is other.op:
+                if self.op in (Op.INTEGER, Op.REAL):
+                    return as_number(self.data[0] * other.data[0],
+                                     max(self.data[1], other.data[1]))
+                elif self.op is Op.COMPLEX:
+                    r1, i1 = self.data
+                    r2, i2 = other.data
+                    return as_complex(r1 * r2 - i1 * i2, r1 * i2 + r2 * i1)
+
+                if self.op is Op.FACTORS:
+                    r = Expr(self.op, dict(self.data))
+                    for k, v in other.data.items():
+                        _pairs_add(r.data, k, v)
+                    return normalize(r)
+                elif self.op is Op.TERMS:
+                    r = Expr(self.op, {})
+                    for t1, c1 in self.data.items():
+                        for t2, c2 in other.data.items():
+                            _pairs_add(r.data, t1 * t2, c1 * c2)
+                    return normalize(r)
+
+            if self.op is Op.COMPLEX and other.op in (Op.INTEGER, Op.REAL):
+                return self * as_complex(other)
+            elif other.op is Op.COMPLEX and self.op in (Op.INTEGER, Op.REAL):
+                return as_complex(self) * other
+            elif self.op is Op.REAL and other.op is Op.INTEGER:
+                return self * as_real(other, kind=self.data[1])
+            elif self.op is Op.INTEGER and other.op is Op.REAL:
+                return as_real(self, kind=other.data[1]) * other
+
+            if self.op is Op.TERMS:
+                return self * as_terms(other)
+            elif other.op is Op.TERMS:
+                return as_terms(self) * other
+
+            return as_factors(self) * as_factors(other)
+        return NotImplemented
+
+    def __rmul__(self, other):
+        if isinstance(other, number_types):
+            return as_number(other) * self
+        return NotImplemented
+
+    def __pow__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            if other.op is Op.INTEGER:
+                exponent = other.data[0]
+                # TODO: other kind not used
+                if exponent == 0:
+                    return as_number(1)
+                if exponent == 1:
+                    return self
+                if exponent > 0:
+                    if self.op is Op.FACTORS:
+                        r = Expr(self.op, {})
+                        for k, v in self.data.items():
+                            r.data[k] = v * exponent
+                        return normalize(r)
+                    return self * (self ** (exponent - 1))
+                elif exponent != -1:
+                    return (self ** (-exponent)) ** -1
+                return Expr(Op.FACTORS, {self: exponent})
+            return as_apply(ArithOp.POW, self, other)
+        return NotImplemented
+
+    def __truediv__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            # Fortran / is different from Python /:
+            # - `/` is a truncate operation for integer operands
+            return normalize(as_apply(ArithOp.DIV, self, other))
+        return NotImplemented
+
+    def __rtruediv__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            return other / self
+        return NotImplemented
+
+    def __floordiv__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            # Fortran // is different from Python //:
+            # - `//` is a concatenate operation for string operands
+            return normalize(Expr(Op.CONCAT, (self, other)))
+        return NotImplemented
+
+    def __rfloordiv__(self, other):
+        other = as_expr(other)
+        if isinstance(other, Expr):
+            return other // self
+        return NotImplemented
+
+    def __call__(self, *args, **kwargs):
+        # In Fortran, parenthesis () are use for both function call as
+        # well as indexing operations.
+        #
+        # TODO: implement a method for deciding when __call__ should
+        # return an INDEXING expression.
+        return as_apply(self, *map(as_expr, args),
+                        **{k: as_expr(v) for k, v in kwargs.items()})
+
+    def __getitem__(self, index):
+        # Provided to support C indexing operations that .pyf files
+        # may contain.
+        index = as_expr(index)
+        if not isinstance(index, tuple):
+            index = index,
+        if len(index) > 1:
+            ewarn(f'C-index should be a single expression but got `{index}`')
+        return Expr(Op.INDEXING, (self,) + index)
+
+    def substitute(self, symbols_map):
+        """Recursively substitute symbols with values in symbols map.
+
+        Symbols map is a dictionary of symbol-expression pairs.
+        """
+        if self.op is Op.SYMBOL:
+            value = symbols_map.get(self)
+            if value is None:
+                return self
+            m = re.match(r'\A(@__f2py_PARENTHESIS_(\w+)_\d+@)\Z', self.data)
+            if m:
+                # complement to fromstring method
+                items, paren = m.groups()
+                if paren in ['ROUNDDIV', 'SQUARE']:
+                    return as_array(value)
+                assert paren == 'ROUND', (paren, value)
+            return value
+        if self.op in (Op.INTEGER, Op.REAL, Op.STRING):
+            return self
+        if self.op in (Op.ARRAY, Op.COMPLEX):
+            return Expr(self.op, tuple(item.substitute(symbols_map)
+                                       for item in self.data))
+        if self.op is Op.CONCAT:
+            return normalize(Expr(self.op, tuple(item.substitute(symbols_map)
+                                                 for item in self.data)))
+        if self.op is Op.TERMS:
+            r = None
+            for term, coeff in self.data.items():
+                if r is None:
+                    r = term.substitute(symbols_map) * coeff
+                else:
+                    r += term.substitute(symbols_map) * coeff
+            if r is None:
+                ewarn('substitute: empty TERMS expression interpreted as'
+                      ' int-literal 0')
+                return as_number(0)
+            return r
+        if self.op is Op.FACTORS:
+            r = None
+            for base, exponent in self.data.items():
+                if r is None:
+                    r = base.substitute(symbols_map) ** exponent
+                else:
+                    r *= base.substitute(symbols_map) ** exponent
+            if r is None:
+                ewarn('substitute: empty FACTORS expression interpreted'
+                      ' as int-literal 1')
+                return as_number(1)
+            return r
+        if self.op is Op.APPLY:
+            target, args, kwargs = self.data
+            if isinstance(target, Expr):
+                target = target.substitute(symbols_map)
+            args = tuple(a.substitute(symbols_map) for a in args)
+            kwargs = {k: v.substitute(symbols_map)
+                          for k, v in kwargs.items()}
+            return normalize(Expr(self.op, (target, args, kwargs)))
+        if self.op is Op.INDEXING:
+            func = self.data[0]
+            if isinstance(func, Expr):
+                func = func.substitute(symbols_map)
+            args = tuple(a.substitute(symbols_map) for a in self.data[1:])
+            return normalize(Expr(self.op, (func,) + args))
+        if self.op is Op.TERNARY:
+            operands = tuple(a.substitute(symbols_map) for a in self.data)
+            return normalize(Expr(self.op, operands))
+        if self.op in (Op.REF, Op.DEREF):
+            return normalize(Expr(self.op, self.data.substitute(symbols_map)))
+        if self.op is Op.RELATIONAL:
+            rop, left, right = self.data
+            left = left.substitute(symbols_map)
+            right = right.substitute(symbols_map)
+            return normalize(Expr(self.op, (rop, left, right)))
+        raise NotImplementedError(f'substitute method for {self.op}: {self!r}')
+
+    def traverse(self, visit, *args, **kwargs):
+        """Traverse expression tree with visit function.
+
+        The visit function is applied to an expression with given args
+        and kwargs.
+
+        Traverse call returns an expression returned by visit when not
+        None, otherwise return a new normalized expression with
+        traverse-visit sub-expressions.
+        """
+        result = visit(self, *args, **kwargs)
+        if result is not None:
+            return result
+
+        if self.op in (Op.INTEGER, Op.REAL, Op.STRING, Op.SYMBOL):
+            return self
+        elif self.op in (Op.COMPLEX, Op.ARRAY, Op.CONCAT, Op.TERNARY):
+            return normalize(Expr(self.op, tuple(
+                item.traverse(visit, *args, **kwargs)
+                for item in self.data)))
+        elif self.op in (Op.TERMS, Op.FACTORS):
+            data = {}
+            for k, v in self.data.items():
+                k = k.traverse(visit, *args, **kwargs)
+                v = (v.traverse(visit, *args, **kwargs)
+                     if isinstance(v, Expr) else v)
+                if k in data:
+                    v = data[k] + v
+                data[k] = v
+            return normalize(Expr(self.op, data))
+        elif self.op is Op.APPLY:
+            obj = self.data[0]
+            func = (obj.traverse(visit, *args, **kwargs)
+                    if isinstance(obj, Expr) else obj)
+            operands = tuple(operand.traverse(visit, *args, **kwargs)
+                             for operand in self.data[1])
+            kwoperands = {k: v.traverse(visit, *args, **kwargs)
+                              for k, v in self.data[2].items()}
+            return normalize(Expr(self.op, (func, operands, kwoperands)))
+        elif self.op is Op.INDEXING:
+            obj = self.data[0]
+            obj = (obj.traverse(visit, *args, **kwargs)
+                   if isinstance(obj, Expr) else obj)
+            indices = tuple(index.traverse(visit, *args, **kwargs)
+                            for index in self.data[1:])
+            return normalize(Expr(self.op, (obj,) + indices))
+        elif self.op in (Op.REF, Op.DEREF):
+            return normalize(Expr(self.op,
+                                  self.data.traverse(visit, *args, **kwargs)))
+        elif self.op is Op.RELATIONAL:
+            rop, left, right = self.data
+            left = left.traverse(visit, *args, **kwargs)
+            right = right.traverse(visit, *args, **kwargs)
+            return normalize(Expr(self.op, (rop, left, right)))
+        raise NotImplementedError(f'traverse method for {self.op}')
+
+    def contains(self, other):
+        """Check if self contains other.
+        """
+        found = []
+
+        def visit(expr, found=found):
+            if found:
+                return expr
+            elif expr == other:
+                found.append(1)
+                return expr
+
+        self.traverse(visit)
+
+        return len(found) != 0
+
+    def symbols(self):
+        """Return a set of symbols contained in self.
+        """
+        found = set()
+
+        def visit(expr, found=found):
+            if expr.op is Op.SYMBOL:
+                found.add(expr)
+
+        self.traverse(visit)
+
+        return found
+
+    def polynomial_atoms(self):
+        """Return a set of expressions used as atoms in polynomial self.
+        """
+        found = set()
+
+        def visit(expr, found=found):
+            if expr.op is Op.FACTORS:
+                for b in expr.data:
+                    b.traverse(visit)
+                return expr
+            if expr.op in (Op.TERMS, Op.COMPLEX):
+                return
+            if expr.op is Op.APPLY and isinstance(expr.data[0], ArithOp):
+                if expr.data[0] is ArithOp.POW:
+                    expr.data[1][0].traverse(visit)
+                    return expr
+                return
+            if expr.op in (Op.INTEGER, Op.REAL):
+                return expr
+
+            found.add(expr)
+
+            if expr.op in (Op.INDEXING, Op.APPLY):
+                return expr
+
+        self.traverse(visit)
+
+        return found
+
+    def linear_solve(self, symbol):
+        """Return a, b such that a * symbol + b == self.
+
+        If self is not linear with respect to symbol, raise RuntimeError.
+        """
+        b = self.substitute({symbol: as_number(0)})
+        ax = self - b
+        a = ax.substitute({symbol: as_number(1)})
+
+        zero, _ = as_numer_denom(a * symbol - ax)
+
+        if zero != as_number(0):
+            raise RuntimeError(f'not a {symbol}-linear equation:'
+                               f' {a} * {symbol} + {b} == {self}')
+        return a, b
+
+
+def normalize(obj):
+    """Normalize Expr and apply basic evaluation methods.
+    """
+    if not isinstance(obj, Expr):
+        return obj
+
+    if obj.op is Op.TERMS:
+        d = {}
+        for t, c in obj.data.items():
+            if c == 0:
+                continue
+            if t.op is Op.COMPLEX and c != 1:
+                t = t * c
+                c = 1
+            if t.op is Op.TERMS:
+                for t1, c1 in t.data.items():
+                    _pairs_add(d, t1, c1 * c)
+            else:
+                _pairs_add(d, t, c)
+        if len(d) == 0:
+            # TODO: determine correct kind
+            return as_number(0)
+        elif len(d) == 1:
+            (t, c), = d.items()
+            if c == 1:
+                return t
+        return Expr(Op.TERMS, d)
+
+    if obj.op is Op.FACTORS:
+        coeff = 1
+        d = {}
+        for b, e in obj.data.items():
+            if e == 0:
+                continue
+            if b.op is Op.TERMS and isinstance(e, integer_types) and e > 1:
+                # expand integer powers of sums
+                b = b * (b ** (e - 1))
+                e = 1
+
+            if b.op in (Op.INTEGER, Op.REAL):
+                if e == 1:
+                    coeff *= b.data[0]
+                elif e > 0:
+                    coeff *= b.data[0] ** e
+                else:
+                    _pairs_add(d, b, e)
+            elif b.op is Op.FACTORS:
+                if e > 0 and isinstance(e, integer_types):
+                    for b1, e1 in b.data.items():
+                        _pairs_add(d, b1, e1 * e)
+                else:
+                    _pairs_add(d, b, e)
+            else:
+                _pairs_add(d, b, e)
+        if len(d) == 0 or coeff == 0:
+            # TODO: determine correct kind
+            assert isinstance(coeff, number_types)
+            return as_number(coeff)
+        elif len(d) == 1:
+            (b, e), = d.items()
+            if e == 1:
+                t = b
+            else:
+                t = Expr(Op.FACTORS, d)
+            if coeff == 1:
+                return t
+            return Expr(Op.TERMS, {t: coeff})
+        elif coeff == 1:
+            return Expr(Op.FACTORS, d)
+        else:
+            return Expr(Op.TERMS, {Expr(Op.FACTORS, d): coeff})
+
+    if obj.op is Op.APPLY and obj.data[0] is ArithOp.DIV:
+        dividend, divisor = obj.data[1]
+        t1, c1 = as_term_coeff(dividend)
+        t2, c2 = as_term_coeff(divisor)
+        if isinstance(c1, integer_types) and isinstance(c2, integer_types):
+            g = gcd(c1, c2)
+            c1, c2 = c1 // g, c2 // g
+        else:
+            c1, c2 = c1 / c2, 1
+
+        if t1.op is Op.APPLY and t1.data[0] is ArithOp.DIV:
+            numer = t1.data[1][0] * c1
+            denom = t1.data[1][1] * t2 * c2
+            return as_apply(ArithOp.DIV, numer, denom)
+
+        if t2.op is Op.APPLY and t2.data[0] is ArithOp.DIV:
+            numer = t2.data[1][1] * t1 * c1
+            denom = t2.data[1][0] * c2
+            return as_apply(ArithOp.DIV, numer, denom)
+
+        d = dict(as_factors(t1).data)
+        for b, e in as_factors(t2).data.items():
+            _pairs_add(d, b, -e)
+        numer, denom = {}, {}
+        for b, e in d.items():
+            if e > 0:
+                numer[b] = e
+            else:
+                denom[b] = -e
+        numer = normalize(Expr(Op.FACTORS, numer)) * c1
+        denom = normalize(Expr(Op.FACTORS, denom)) * c2
+
+        if denom.op in (Op.INTEGER, Op.REAL) and denom.data[0] == 1:
+            # TODO: denom kind not used
+            return numer
+        return as_apply(ArithOp.DIV, numer, denom)
+
+    if obj.op is Op.CONCAT:
+        lst = [obj.data[0]]
+        for s in obj.data[1:]:
+            last = lst[-1]
+            if (
+                    last.op is Op.STRING
+                    and s.op is Op.STRING
+                    and last.data[0][0] in '"\''
+                    and s.data[0][0] == last.data[0][-1]
+            ):
+                new_last = as_string(last.data[0][:-1] + s.data[0][1:],
+                                     max(last.data[1], s.data[1]))
+                lst[-1] = new_last
+            else:
+                lst.append(s)
+        if len(lst) == 1:
+            return lst[0]
+        return Expr(Op.CONCAT, tuple(lst))
+
+    if obj.op is Op.TERNARY:
+        cond, expr1, expr2 = map(normalize, obj.data)
+        if cond.op is Op.INTEGER:
+            return expr1 if cond.data[0] else expr2
+        return Expr(Op.TERNARY, (cond, expr1, expr2))
+
+    return obj
+
+
+def as_expr(obj):
+    """Convert non-Expr objects to Expr objects.
+    """
+    if isinstance(obj, complex):
+        return as_complex(obj.real, obj.imag)
+    if isinstance(obj, number_types):
+        return as_number(obj)
+    if isinstance(obj, str):
+        # STRING expression holds string with boundary quotes, hence
+        # applying repr:
+        return as_string(repr(obj))
+    if isinstance(obj, tuple):
+        return tuple(map(as_expr, obj))
+    return obj
+
+
+def as_symbol(obj):
+    """Return object as SYMBOL expression (variable or unparsed expression).
+    """
+    return Expr(Op.SYMBOL, obj)
+
+
+def as_number(obj, kind=4):
+    """Return object as INTEGER or REAL constant.
+    """
+    if isinstance(obj, int):
+        return Expr(Op.INTEGER, (obj, kind))
+    if isinstance(obj, float):
+        return Expr(Op.REAL, (obj, kind))
+    if isinstance(obj, Expr):
+        if obj.op in (Op.INTEGER, Op.REAL):
+            return obj
+    raise OpError(f'cannot convert {obj} to INTEGER or REAL constant')
+
+
+def as_integer(obj, kind=4):
+    """Return object as INTEGER constant.
+    """
+    if isinstance(obj, int):
+        return Expr(Op.INTEGER, (obj, kind))
+    if isinstance(obj, Expr):
+        if obj.op is Op.INTEGER:
+            return obj
+    raise OpError(f'cannot convert {obj} to INTEGER constant')
+
+
+def as_real(obj, kind=4):
+    """Return object as REAL constant.
+    """
+    if isinstance(obj, int):
+        return Expr(Op.REAL, (float(obj), kind))
+    if isinstance(obj, float):
+        return Expr(Op.REAL, (obj, kind))
+    if isinstance(obj, Expr):
+        if obj.op is Op.REAL:
+            return obj
+        elif obj.op is Op.INTEGER:
+            return Expr(Op.REAL, (float(obj.data[0]), kind))
+    raise OpError(f'cannot convert {obj} to REAL constant')
+
+
+def as_string(obj, kind=1):
+    """Return object as STRING expression (string literal constant).
+    """
+    return Expr(Op.STRING, (obj, kind))
+
+
+def as_array(obj):
+    """Return object as ARRAY expression (array constant).
+    """
+    if isinstance(obj, Expr):
+        obj = obj,
+    return Expr(Op.ARRAY, obj)
+
+
+def as_complex(real, imag=0):
+    """Return object as COMPLEX expression (complex literal constant).
+    """
+    return Expr(Op.COMPLEX, (as_expr(real), as_expr(imag)))
+
+
+def as_apply(func, *args, **kwargs):
+    """Return object as APPLY expression (function call, constructor, etc.)
+    """
+    return Expr(Op.APPLY,
+                (func, tuple(map(as_expr, args)),
+                 {k: as_expr(v) for k, v in kwargs.items()}))
+
+
+def as_ternary(cond, expr1, expr2):
+    """Return object as TERNARY expression (cond?expr1:expr2).
+    """
+    return Expr(Op.TERNARY, (cond, expr1, expr2))
+
+
+def as_ref(expr):
+    """Return object as referencing expression.
+    """
+    return Expr(Op.REF, expr)
+
+
+def as_deref(expr):
+    """Return object as dereferencing expression.
+    """
+    return Expr(Op.DEREF, expr)
+
+
+def as_eq(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.EQ, left, right))
+
+
+def as_ne(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.NE, left, right))
+
+
+def as_lt(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.LT, left, right))
+
+
+def as_le(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.LE, left, right))
+
+
+def as_gt(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.GT, left, right))
+
+
+def as_ge(left, right):
+    return Expr(Op.RELATIONAL, (RelOp.GE, left, right))
+
+
+def as_terms(obj):
+    """Return expression as TERMS expression.
+    """
+    if isinstance(obj, Expr):
+        obj = normalize(obj)
+        if obj.op is Op.TERMS:
+            return obj
+        if obj.op is Op.INTEGER:
+            return Expr(Op.TERMS, {as_integer(1, obj.data[1]): obj.data[0]})
+        if obj.op is Op.REAL:
+            return Expr(Op.TERMS, {as_real(1, obj.data[1]): obj.data[0]})
+        return Expr(Op.TERMS, {obj: 1})
+    raise OpError(f'cannot convert {type(obj)} to terms Expr')
+
+
+def as_factors(obj):
+    """Return expression as FACTORS expression.
+    """
+    if isinstance(obj, Expr):
+        obj = normalize(obj)
+        if obj.op is Op.FACTORS:
+            return obj
+        if obj.op is Op.TERMS:
+            if len(obj.data) == 1:
+                (term, coeff), = obj.data.items()
+                if coeff == 1:
+                    return Expr(Op.FACTORS, {term: 1})
+                return Expr(Op.FACTORS, {term: 1, Expr.number(coeff): 1})
+        if (obj.op is Op.APPLY
+             and obj.data[0] is ArithOp.DIV
+             and not obj.data[2]):
+            return Expr(Op.FACTORS, {obj.data[1][0]: 1, obj.data[1][1]: -1})
+        return Expr(Op.FACTORS, {obj: 1})
+    raise OpError(f'cannot convert {type(obj)} to terms Expr')
+
+
+def as_term_coeff(obj):
+    """Return expression as term-coefficient pair.
+    """
+    if isinstance(obj, Expr):
+        obj = normalize(obj)
+        if obj.op is Op.INTEGER:
+            return as_integer(1, obj.data[1]), obj.data[0]
+        if obj.op is Op.REAL:
+            return as_real(1, obj.data[1]), obj.data[0]
+        if obj.op is Op.TERMS:
+            if len(obj.data) == 1:
+                (term, coeff), = obj.data.items()
+                return term, coeff
+            # TODO: find common divisor of coefficients
+        if obj.op is Op.APPLY and obj.data[0] is ArithOp.DIV:
+            t, c = as_term_coeff(obj.data[1][0])
+            return as_apply(ArithOp.DIV, t, obj.data[1][1]), c
+        return obj, 1
+    raise OpError(f'cannot convert {type(obj)} to term and coeff')
+
+
+def as_numer_denom(obj):
+    """Return expression as numer-denom pair.
+    """
+    if isinstance(obj, Expr):
+        obj = normalize(obj)
+        if obj.op in (Op.INTEGER, Op.REAL, Op.COMPLEX, Op.SYMBOL,
+                      Op.INDEXING, Op.TERNARY):
+            return obj, as_number(1)
+        elif obj.op is Op.APPLY:
+            if obj.data[0] is ArithOp.DIV and not obj.data[2]:
+                numers, denoms = map(as_numer_denom, obj.data[1])
+                return numers[0] * denoms[1], numers[1] * denoms[0]
+            return obj, as_number(1)
+        elif obj.op is Op.TERMS:
+            numers, denoms = [], []
+            for term, coeff in obj.data.items():
+                n, d = as_numer_denom(term)
+                n = n * coeff
+                numers.append(n)
+                denoms.append(d)
+            numer, denom = as_number(0), as_number(1)
+            for i in range(len(numers)):
+                n = numers[i]
+                for j in range(len(numers)):
+                    if i != j:
+                        n *= denoms[j]
+                numer += n
+                denom *= denoms[i]
+            if denom.op in (Op.INTEGER, Op.REAL) and denom.data[0] < 0:
+                numer, denom = -numer, -denom
+            return numer, denom
+        elif obj.op is Op.FACTORS:
+            numer, denom = as_number(1), as_number(1)
+            for b, e in obj.data.items():
+                bnumer, bdenom = as_numer_denom(b)
+                if e > 0:
+                    numer *= bnumer ** e
+                    denom *= bdenom ** e
+                elif e < 0:
+                    numer *= bdenom ** (-e)
+                    denom *= bnumer ** (-e)
+            return numer, denom
+    raise OpError(f'cannot convert {type(obj)} to numer and denom')
+
+
+def _counter():
+    # Used internally to generate unique dummy symbols
+    counter = 0
+    while True:
+        counter += 1
+        yield counter
+
+
+COUNTER = _counter()
+
+
+def eliminate_quotes(s):
+    """Replace quoted substrings of input string.
+
+    Return a new string and a mapping of replacements.
+    """
+    d = {}
+
+    def repl(m):
+        kind, value = m.groups()[:2]
+        if kind:
+            # remove trailing underscore
+            kind = kind[:-1]
+        p = {"'": "SINGLE", '"': "DOUBLE"}[value[0]]
+        k = f'{kind}@__f2py_QUOTES_{p}_{COUNTER.__next__()}@'
+        d[k] = value
+        return k
+
+    new_s = re.sub(r'({kind}_|)({single_quoted}|{double_quoted})'.format(
+        kind=r'\w[\w\d_]*',
+        single_quoted=r"('([^'\\]|(\\.))*')",
+        double_quoted=r'("([^"\\]|(\\.))*")'),
+        repl, s)
+
+    assert '"' not in new_s
+    assert "'" not in new_s
+
+    return new_s, d
+
+
+def insert_quotes(s, d):
+    """Inverse of eliminate_quotes.
+    """
+    for k, v in d.items():
+        kind = k[:k.find('@')]
+        if kind:
+            kind += '_'
+        s = s.replace(k, kind + v)
+    return s
+
+
+def replace_parenthesis(s):
+    """Replace substrings of input that are enclosed in parenthesis.
+
+    Return a new string and a mapping of replacements.
+    """
+    # Find a parenthesis pair that appears first.
+
+    # Fortran deliminator are `(`, `)`, `[`, `]`, `(/', '/)`, `/`.
+    # We don't handle `/` deliminator because it is not a part of an
+    # expression.
+    left, right = None, None
+    mn_i = len(s)
+    for left_, right_ in (('(/', '/)'),
+                          '()',
+                          '{}',  # to support C literal structs
+                          '[]'):
+        i = s.find(left_)
+        if i == -1:
+            continue
+        if i < mn_i:
+            mn_i = i
+            left, right = left_, right_
+
+    if left is None:
+        return s, {}
+
+    i = mn_i
+    j = s.find(right, i)
+    if j == -1:
+        raise ValueError(f'Mismatch of {left + right} parenthesis in {s!r}')
+
+    while s.count(left, i + 1, j) != s.count(right, i + 1, j):
+        j = s.find(right, j + 1)
+        if j == -1:
+            raise ValueError(f'Mismatch of {left + right} parenthesis in {s!r}')
+
+    p = {'(': 'ROUND', '[': 'SQUARE', '{': 'CURLY', '(/': 'ROUNDDIV'}[left]
+
+    k = f'@__f2py_PARENTHESIS_{p}_{COUNTER.__next__()}@'
+    v = s[i + len(left):j]
+    r, d = replace_parenthesis(s[j + len(right):])
+    d[k] = v
+    return s[:i] + k + r, d
+
+
+def _get_parenthesis_kind(s):
+    assert s.startswith('@__f2py_PARENTHESIS_'), s
+    return s.split('_')[4]
+
+
+def unreplace_parenthesis(s, d):
+    """Inverse of replace_parenthesis.
+    """
+    for k, v in d.items():
+        p = _get_parenthesis_kind(k)
+        left = {'ROUND': '(', 'SQUARE': '[', 'CURLY': '{', 'ROUNDDIV': '(/'}[p]
+        right = {'ROUND': ')', 'SQUARE': ']', 'CURLY': '}', 'ROUNDDIV': '/)'}[p]
+        s = s.replace(k, left + v + right)
+    return s
+
+
+def fromstring(s, language=Language.C):
+    """Create an expression from a string.
+
+    This is a "lazy" parser, that is, only arithmetic operations are
+    resolved, non-arithmetic operations are treated as symbols.
+    """
+    r = _FromStringWorker(language=language).parse(s)
+    if isinstance(r, Expr):
+        return r
+    raise ValueError(f'failed to parse `{s}` to Expr instance: got `{r}`')
+
+
+class _Pair:
+    # Internal class to represent a pair of expressions
+
+    def __init__(self, left, right):
+        self.left = left
+        self.right = right
+
+    def substitute(self, symbols_map):
+        left, right = self.left, self.right
+        if isinstance(left, Expr):
+            left = left.substitute(symbols_map)
+        if isinstance(right, Expr):
+            right = right.substitute(symbols_map)
+        return _Pair(left, right)
+
+    def __repr__(self):
+        return f'{type(self).__name__}({self.left}, {self.right})'
+
+
+class _FromStringWorker:
+
+    def __init__(self, language=Language.C):
+        self.original = None
+        self.quotes_map = None
+        self.language = language
+
+    def finalize_string(self, s):
+        return insert_quotes(s, self.quotes_map)
+
+    def parse(self, inp):
+        self.original = inp
+        unquoted, self.quotes_map = eliminate_quotes(inp)
+        return self.process(unquoted)
+
+    def process(self, s, context='expr'):
+        """Parse string within the given context.
+
+        The context may define the result in case of ambiguous
+        expressions. For instance, consider expressions `f(x, y)` and
+        `(x, y) + (a, b)` where `f` is a function and pair `(x, y)`
+        denotes complex number. Specifying context as "args" or
+        "expr", the subexpression `(x, y)` will be parse to an
+        argument list or to a complex number, respectively.
+        """
+        if isinstance(s, (list, tuple)):
+            return type(s)(self.process(s_, context) for s_ in s)
+
+        assert isinstance(s, str), (type(s), s)
+
+        # replace subexpressions in parenthesis with f2py @-names
+        r, raw_symbols_map = replace_parenthesis(s)
+        r = r.strip()
+
+        def restore(r):
+            # restores subexpressions marked with f2py @-names
+            if isinstance(r, (list, tuple)):
+                return type(r)(map(restore, r))
+            return unreplace_parenthesis(r, raw_symbols_map)
+
+        # comma-separated tuple
+        if ',' in r:
+            operands = restore(r.split(','))
+            if context == 'args':
+                return tuple(self.process(operands))
+            if context == 'expr':
+                if len(operands) == 2:
+                    # complex number literal
+                    return as_complex(*self.process(operands))
+            raise NotImplementedError(
+                f'parsing comma-separated list (context={context}): {r}')
+
+        # ternary operation
+        m = re.match(r'\A([^?]+)[?]([^:]+)[:](.+)\Z', r)
+        if m:
+            assert context == 'expr', context
+            oper, expr1, expr2 = restore(m.groups())
+            oper = self.process(oper)
+            expr1 = self.process(expr1)
+            expr2 = self.process(expr2)
+            return as_ternary(oper, expr1, expr2)
+
+        # relational expression
+        if self.language is Language.Fortran:
+            m = re.match(
+                r'\A(.+)\s*[.](eq|ne|lt|le|gt|ge)[.]\s*(.+)\Z', r, re.I)
+        else:
+            m = re.match(
+                r'\A(.+)\s*([=][=]|[!][=]|[<][=]|[<]|[>][=]|[>])\s*(.+)\Z', r)
+        if m:
+            left, rop, right = m.groups()
+            if self.language is Language.Fortran:
+                rop = '.' + rop + '.'
+            left, right = self.process(restore((left, right)))
+            rop = RelOp.fromstring(rop, language=self.language)
+            return Expr(Op.RELATIONAL, (rop, left, right))
+
+        # keyword argument
+        m = re.match(r'\A(\w[\w\d_]*)\s*[=](.*)\Z', r)
+        if m:
+            keyname, value = m.groups()
+            value = restore(value)
+            return _Pair(keyname, self.process(value))
+
+        # addition/subtraction operations
+        operands = re.split(r'((?<!\d[edED])[+-])', r)
+        if len(operands) > 1:
+            result = self.process(restore(operands[0] or '0'))
+            for op, operand in zip(operands[1::2], operands[2::2]):
+                operand = self.process(restore(operand))
+                op = op.strip()
+                if op == '+':
+                    result += operand
+                else:
+                    assert op == '-'
+                    result -= operand
+            return result
+
+        # string concatenate operation
+        if self.language is Language.Fortran and '//' in r:
+            operands = restore(r.split('//'))
+            return Expr(Op.CONCAT,
+                        tuple(self.process(operands)))
+
+        # multiplication/division operations
+        operands = re.split(r'(?<=[@\w\d_])\s*([*]|/)',
+                            (r if self.language is Language.C
+                             else r.replace('**', '@__f2py_DOUBLE_STAR@')))
+        if len(operands) > 1:
+            operands = restore(operands)
+            if self.language is not Language.C:
+                operands = [operand.replace('@__f2py_DOUBLE_STAR@', '**')
+                            for operand in operands]
+            # Expression is an arithmetic product
+            result = self.process(operands[0])
+            for op, operand in zip(operands[1::2], operands[2::2]):
+                operand = self.process(operand)
+                op = op.strip()
+                if op == '*':
+                    result *= operand
+                else:
+                    assert op == '/'
+                    result /= operand
+            return result
+
+        # referencing/dereferencing
+        if r.startswith(('*', '&')):
+            op = {'*': Op.DEREF, '&': Op.REF}[r[0]]
+            operand = self.process(restore(r[1:]))
+            return Expr(op, operand)
+
+        # exponentiation operations
+        if self.language is not Language.C and '**' in r:
+            operands = list(reversed(restore(r.split('**'))))
+            result = self.process(operands[0])
+            for operand in operands[1:]:
+                operand = self.process(operand)
+                result = operand ** result
+            return result
+
+        # int-literal-constant
+        m = re.match(r'\A({digit_string})({kind}|)\Z'.format(
+            digit_string=r'\d+',
+            kind=r'_(\d+|\w[\w\d_]*)'), r)
+        if m:
+            value, _, kind = m.groups()
+            if kind and kind.isdigit():
+                kind = int(kind)
+            return as_integer(int(value), kind or 4)
+
+        # real-literal-constant
+        m = re.match(r'\A({significant}({exponent}|)|\d+{exponent})({kind}|)\Z'
+                     .format(
+                         significant=r'[.]\d+|\d+[.]\d*',
+                         exponent=r'[edED][+-]?\d+',
+                         kind=r'_(\d+|\w[\w\d_]*)'), r)
+        if m:
+            value, _, _, kind = m.groups()
+            if kind and kind.isdigit():
+                kind = int(kind)
+            value = value.lower()
+            if 'd' in value:
+                return as_real(float(value.replace('d', 'e')), kind or 8)
+            return as_real(float(value), kind or 4)
+
+        # string-literal-constant with kind parameter specification
+        if r in self.quotes_map:
+            kind = r[:r.find('@')]
+            return as_string(self.quotes_map[r], kind or 1)
+
+        # array constructor or literal complex constant or
+        # parenthesized expression
+        if r in raw_symbols_map:
+            paren = _get_parenthesis_kind(r)
+            items = self.process(restore(raw_symbols_map[r]),
+                                 'expr' if paren == 'ROUND' else 'args')
+            if paren == 'ROUND':
+                if isinstance(items, Expr):
+                    return items
+            if paren in ['ROUNDDIV', 'SQUARE']:
+                # Expression is an array constructor
+                if isinstance(items, Expr):
+                    items = (items,)
+                return as_array(items)
+
+        # function call/indexing
+        m = re.match(r'\A(.+)\s*(@__f2py_PARENTHESIS_(ROUND|SQUARE)_\d+@)\Z',
+                     r)
+        if m:
+            target, args, paren = m.groups()
+            target = self.process(restore(target))
+            args = self.process(restore(args)[1:-1], 'args')
+            if not isinstance(args, tuple):
+                args = args,
+            if paren == 'ROUND':
+                kwargs = {a.left: a.right for a in args
+                              if isinstance(a, _Pair)}
+                args = tuple(a for a in args if not isinstance(a, _Pair))
+                # Warning: this could also be Fortran indexing operation..
+                return as_apply(target, *args, **kwargs)
+            else:
+                # Expression is a C/Python indexing operation
+                # (e.g. used in .pyf files)
+                assert paren == 'SQUARE'
+                return target[args]
+
+        # Fortran standard conforming identifier
+        m = re.match(r'\A\w[\w\d_]*\Z', r)
+        if m:
+            return as_symbol(r)
+
+        # fall-back to symbol
+        r = self.finalize_string(restore(r))
+        ewarn(
+            f'fromstring: treating {r!r} as symbol (original={self.original})')
+        return as_symbol(r)
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..3d4b8a70dc8526c5c119b70f50964fd5b2b25e48
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/symbolic.pyi
@@ -0,0 +1,219 @@
+from collections.abc import Callable, Mapping
+from enum import Enum
+from typing import Any, Generic, Literal as L, ParamSpec, Self, TypeAlias, overload
+from typing_extensions import TypeVar
+
+__all__ = ["Expr"]
+
+###
+
+_Tss = ParamSpec("_Tss")
+_ExprT = TypeVar("_ExprT", bound=Expr)
+_ExprT1 = TypeVar("_ExprT1", bound=Expr)
+_ExprT2 = TypeVar("_ExprT2", bound=Expr)
+_OpT_co = TypeVar("_OpT_co", bound=Op, default=Op, covariant=True)
+_LanguageT_co = TypeVar("_LanguageT_co", bound=Language, default=Language, covariant=True)
+_DataT_co = TypeVar("_DataT_co", default=Any, covariant=True)
+_LeftT_co = TypeVar("_LeftT_co", default=Any, covariant=True)
+_RightT_co = TypeVar("_RightT_co", default=Any, covariant=True)
+
+_RelCOrPy: TypeAlias = L["==", "!=", "<", "<=", ">", ">="]
+_RelFortran: TypeAlias = L[".eq.", ".ne.", ".lt.", ".le.", ".gt.", ".ge."]
+
+_ToExpr: TypeAlias = Expr | complex | str
+_ToExprN: TypeAlias = _ToExpr | tuple[_ToExprN, ...]
+_NestedString: TypeAlias = str | tuple[_NestedString, ...] | list[_NestedString]
+
+###
+
+class OpError(Exception): ...
+class ExprWarning(UserWarning): ...
+
+class Language(Enum):
+    Python = 0
+    Fortran = 1
+    C = 2
+
+class Op(Enum):
+    INTEGER = 10
+    REAL = 12
+    COMPLEX = 15
+    STRING = 20
+    ARRAY = 30
+    SYMBOL = 40
+    TERNARY = 100
+    APPLY = 200
+    INDEXING = 210
+    CONCAT = 220
+    RELATIONAL = 300
+    TERMS = 1_000
+    FACTORS = 2_000
+    REF = 3_000
+    DEREF = 3_001
+
+class RelOp(Enum):
+    EQ = 1
+    NE = 2
+    LT = 3
+    LE = 4
+    GT = 5
+    GE = 6
+
+    @overload
+    @classmethod
+    def fromstring(cls, s: _RelCOrPy, language: L[Language.C, Language.Python] = ...) -> RelOp: ...
+    @overload
+    @classmethod
+    def fromstring(cls, s: _RelFortran, language: L[Language.Fortran]) -> RelOp: ...
+
+    #
+    @overload
+    def tostring(self, /, language: L[Language.C, Language.Python] = ...) -> _RelCOrPy: ...
+    @overload
+    def tostring(self, /, language: L[Language.Fortran]) -> _RelFortran: ...
+
+class ArithOp(Enum):
+    POS = 1
+    NEG = 2
+    ADD = 3
+    SUB = 4
+    MUL = 5
+    DIV = 6
+    POW = 7
+
+class Precedence(Enum):
+    ATOM = 0
+    POWER = 1
+    UNARY = 2
+    PRODUCT = 3
+    SUM = 4
+    LT = 6
+    EQ = 7
+    LAND = 11
+    LOR = 12
+    TERNARY = 13
+    ASSIGN = 14
+    TUPLE = 15
+    NONE = 100
+
+class Expr(Generic[_OpT_co, _DataT_co]):
+    op: _OpT_co
+    data: _DataT_co
+
+    @staticmethod
+    def parse(s: str, language: Language = ...) -> Expr: ...
+
+    #
+    def __init__(self, /, op: Op, data: _DataT_co) -> None: ...
+
+    #
+    def __lt__(self, other: Expr, /) -> bool: ...
+    def __le__(self, other: Expr, /) -> bool: ...
+    def __gt__(self, other: Expr, /) -> bool: ...
+    def __ge__(self, other: Expr, /) -> bool: ...
+
+    #
+    def __pos__(self, /) -> Self: ...
+    def __neg__(self, /) -> Expr: ...
+
+    #
+    def __add__(self, other: Expr, /) -> Expr: ...
+    def __radd__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __sub__(self, other: Expr, /) -> Expr: ...
+    def __rsub__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __mul__(self, other: Expr, /) -> Expr: ...
+    def __rmul__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __pow__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __truediv__(self, other: Expr, /) -> Expr: ...
+    def __rtruediv__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __floordiv__(self, other: Expr, /) -> Expr: ...
+    def __rfloordiv__(self, other: Expr, /) -> Expr: ...
+
+    #
+    def __call__(
+        self,
+        /,
+        *args: _ToExprN,
+        **kwargs: _ToExprN,
+    ) -> Expr[L[Op.APPLY], tuple[Self, tuple[Expr, ...], dict[str, Expr]]]: ...
+
+    #
+    @overload
+    def __getitem__(self, index: _ExprT | tuple[_ExprT], /) -> Expr[L[Op.INDEXING], tuple[Self, _ExprT]]: ...
+    @overload
+    def __getitem__(self, index: _ToExpr | tuple[_ToExpr], /) -> Expr[L[Op.INDEXING], tuple[Self, Expr]]: ...
+
+    #
+    def substitute(self, /, symbols_map: Mapping[Expr, Expr]) -> Expr: ...
+
+    #
+    @overload
+    def traverse(self, /, visit: Callable[_Tss, None], *args: _Tss.args, **kwargs: _Tss.kwargs) -> Expr: ...
+    @overload
+    def traverse(self, /, visit: Callable[_Tss, _ExprT], *args: _Tss.args, **kwargs: _Tss.kwargs) -> _ExprT: ...
+
+    #
+    def contains(self, /, other: Expr) -> bool: ...
+
+    #
+    def symbols(self, /) -> set[Expr]: ...
+    def polynomial_atoms(self, /) -> set[Expr]: ...
+
+    #
+    def linear_solve(self, /, symbol: Expr) -> tuple[Expr, Expr]: ...
+
+    #
+    def tostring(self, /, parent_precedence: Precedence = ..., language: Language = ...) -> str: ...
+
+class _Pair(Generic[_LeftT_co, _RightT_co]):
+    left: _LeftT_co
+    right: _RightT_co
+
+    def __init__(self, /, left: _LeftT_co, right: _RightT_co) -> None: ...
+
+    #
+    @overload
+    def substitute(self: _Pair[_ExprT1, _ExprT2], /, symbols_map: Mapping[Expr, Expr]) -> _Pair[Expr, Expr]: ...
+    @overload
+    def substitute(self: _Pair[_ExprT1, object], /, symbols_map: Mapping[Expr, Expr]) -> _Pair[Expr, Any]: ...
+    @overload
+    def substitute(self: _Pair[object, _ExprT2], /, symbols_map: Mapping[Expr, Expr]) -> _Pair[Any, Expr]: ...
+    @overload
+    def substitute(self, /, symbols_map: Mapping[Expr, Expr]) -> _Pair: ...
+
+class _FromStringWorker(Generic[_LanguageT_co]):
+    language: _LanguageT_co
+
+    original: str | None
+    quotes_map: dict[str, str]
+
+    @overload
+    def __init__(self: _FromStringWorker[L[Language.C]], /, language: L[Language.C] = ...) -> None: ...
+    @overload
+    def __init__(self, /, language: _LanguageT_co) -> None: ...
+
+    #
+    def finalize_string(self, /, s: str) -> str: ...
+
+    #
+    def parse(self, /, inp: str) -> Expr | _Pair: ...
+
+    #
+    @overload
+    def process(self, /, s: str, context: str = "expr") -> Expr | _Pair: ...
+    @overload
+    def process(self, /, s: list[str], context: str = "expr") -> list[Expr | _Pair]: ...
+    @overload
+    def process(self, /, s: tuple[str, ...], context: str = "expr") -> tuple[Expr | _Pair, ...]: ...
+    @overload
+    def process(self, /, s: _NestedString, context: str = "expr") -> Any: ...  # noqa: ANN401
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.py b/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.py
new file mode 100644
index 0000000000000000000000000000000000000000..e7b7e8a2ba0220752afbc01f1170b6717fbdfd93
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.py
@@ -0,0 +1,99 @@
+"""
+Build 'use others module data' mechanism for f2py2e.
+
+Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
+Copyright 2011 -- present NumPy Developers.
+Permission to use, modify, and distribute this software is given under the
+terms of the NumPy License.
+
+NO WARRANTY IS EXPRESSED OR IMPLIED.  USE AT YOUR OWN RISK.
+"""
+__version__ = "$Revision: 1.3 $"[10:-1]
+
+f2py_version = 'See `f2py -v`'
+
+
+from .auxfuncs import applyrules, dictappend, gentitle, hasnote, outmess
+
+usemodule_rules = {
+    'body': """
+#begintitle#
+static char doc_#apiname#[] = \"\\\nVariable wrapper signature:\\n\\
+\t #name# = get_#name#()\\n\\
+Arguments:\\n\\
+#docstr#\";
+extern F_MODFUNC(#usemodulename#,#USEMODULENAME#,#realname#,#REALNAME#);
+static PyObject *#apiname#(PyObject *capi_self, PyObject *capi_args) {
+/*#decl#*/
+\tif (!PyArg_ParseTuple(capi_args, \"\")) goto capi_fail;
+printf(\"c: %d\\n\",F_MODFUNC(#usemodulename#,#USEMODULENAME#,#realname#,#REALNAME#));
+\treturn Py_BuildValue(\"\");
+capi_fail:
+\treturn NULL;
+}
+""",
+    'method': '\t{\"get_#name#\",#apiname#,METH_VARARGS|METH_KEYWORDS,doc_#apiname#},',
+    'need': ['F_MODFUNC']
+}
+
+################
+
+
+def buildusevars(m, r):
+    ret = {}
+    outmess(
+        f"\t\tBuilding use variable hooks for module \"{m['name']}\" (feature only for F90/F95)...\n")
+    varsmap = {}
+    revmap = {}
+    if 'map' in r:
+        for k in r['map'].keys():
+            if r['map'][k] in revmap:
+                outmess('\t\t\tVariable "%s<=%s" is already mapped by "%s". Skipping.\n' % (
+                    r['map'][k], k, revmap[r['map'][k]]))
+            else:
+                revmap[r['map'][k]] = k
+    if r.get('only'):
+        for v in r['map'].keys():
+            if r['map'][v] in m['vars']:
+
+                if revmap[r['map'][v]] == v:
+                    varsmap[v] = r['map'][v]
+                else:
+                    outmess(f"\t\t\tIgnoring map \"{v}=>{r['map'][v]}\". See above.\n")
+            else:
+                outmess(
+                    f"\t\t\tNo definition for variable \"{v}=>{r['map'][v]}\". Skipping.\n")
+    else:
+        for v in m['vars'].keys():
+            varsmap[v] = revmap.get(v, v)
+    for v in varsmap.keys():
+        ret = dictappend(ret, buildusevar(v, varsmap[v], m['vars'], m['name']))
+    return ret
+
+
+def buildusevar(name, realname, vars, usemodulename):
+    outmess('\t\t\tConstructing wrapper function for variable "%s=>%s"...\n' % (
+        name, realname))
+    ret = {}
+    vrd = {'name': name,
+           'realname': realname,
+           'REALNAME': realname.upper(),
+           'usemodulename': usemodulename,
+           'USEMODULENAME': usemodulename.upper(),
+           'texname': name.replace('_', '\\_'),
+           'begintitle': gentitle(f'{name}=>{realname}'),
+           'endtitle': gentitle(f'end of {name}=>{realname}'),
+           'apiname': f'#modulename#_use_{realname}_from_{usemodulename}'
+           }
+    nummap = {0: 'Ro', 1: 'Ri', 2: 'Rii', 3: 'Riii', 4: 'Riv',
+              5: 'Rv', 6: 'Rvi', 7: 'Rvii', 8: 'Rviii', 9: 'Rix'}
+    vrd['texnamename'] = name
+    for i in nummap.keys():
+        vrd['texnamename'] = vrd['texnamename'].replace(repr(i), nummap[i])
+    if hasnote(vars[realname]):
+        vrd['note'] = vars[realname]['note']
+    rd = dictappend({}, vrd)
+
+    print(name, realname, vars[realname])
+    ret = applyrules(usemodule_rules, rd)
+    return ret
diff --git a/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.pyi b/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..b7f2002a32dec2d95f699157f35b8c45b8759df3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/f2py/use_rules.pyi
@@ -0,0 +1,9 @@
+from collections.abc import Mapping
+from typing import Any, Final
+
+__version__: Final[str] = ...
+f2py_version: Final = "See `f2py -v`"
+usemodule_rules: Final[dict[str, str | list[str]]] = ...
+
+def buildusevars(m: Mapping[str, object], r: Mapping[str, Mapping[str, object]]) -> dict[str, Any]: ...
+def buildusevar(name: str, realname: str, vars: Mapping[str, Mapping[str, object]], usemodulename: str) -> dict[str, Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/__init__.py b/python/user_packages/Python313/site-packages/numpy/fft/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a24f3a533bf3b9eb999604ee0809825ba6c7747c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/__init__.py
@@ -0,0 +1,213 @@
+"""
+Discrete Fourier Transform
+==========================
+
+.. currentmodule:: numpy.fft
+
+The SciPy module `scipy.fft` is a more comprehensive superset
+of `numpy.fft`, which includes only a basic set of routines.
+
+Standard FFTs
+-------------
+
+.. autosummary::
+   :toctree: generated/
+
+   fft       Discrete Fourier transform.
+   ifft      Inverse discrete Fourier transform.
+   fft2      Discrete Fourier transform in two dimensions.
+   ifft2     Inverse discrete Fourier transform in two dimensions.
+   fftn      Discrete Fourier transform in N-dimensions.
+   ifftn     Inverse discrete Fourier transform in N dimensions.
+
+Real FFTs
+---------
+
+.. autosummary::
+   :toctree: generated/
+
+   rfft      Real discrete Fourier transform.
+   irfft     Inverse real discrete Fourier transform.
+   rfft2     Real discrete Fourier transform in two dimensions.
+   irfft2    Inverse real discrete Fourier transform in two dimensions.
+   rfftn     Real discrete Fourier transform in N dimensions.
+   irfftn    Inverse real discrete Fourier transform in N dimensions.
+
+Hermitian FFTs
+--------------
+
+.. autosummary::
+   :toctree: generated/
+
+   hfft      Hermitian discrete Fourier transform.
+   ihfft     Inverse Hermitian discrete Fourier transform.
+
+Helper routines
+---------------
+
+.. autosummary::
+   :toctree: generated/
+
+   fftfreq   Discrete Fourier Transform sample frequencies.
+   rfftfreq  DFT sample frequencies (for usage with rfft, irfft).
+   fftshift  Shift zero-frequency component to center of spectrum.
+   ifftshift Inverse of fftshift.
+
+
+Background information
+----------------------
+
+Fourier analysis is fundamentally a method for expressing a function as a
+sum of periodic components, and for recovering the function from those
+components.  When both the function and its Fourier transform are
+replaced with discretized counterparts, it is called the discrete Fourier
+transform (DFT).  The DFT has become a mainstay of numerical computing in
+part because of a very fast algorithm for computing it, called the Fast
+Fourier Transform (FFT), which was known to Gauss (1805) and was brought
+to light in its current form by Cooley and Tukey [CT]_.  Press et al. [NR]_
+provide an accessible introduction to Fourier analysis and its
+applications.
+
+Because the discrete Fourier transform separates its input into
+components that contribute at discrete frequencies, it has a great number
+of applications in digital signal processing, e.g., for filtering, and in
+this context the discretized input to the transform is customarily
+referred to as a *signal*, which exists in the *time domain*.  The output
+is called a *spectrum* or *transform* and exists in the *frequency
+domain*.
+
+Implementation details
+----------------------
+
+There are many ways to define the DFT, varying in the sign of the
+exponent, normalization, etc.  In this implementation, the DFT is defined
+as
+
+.. math::
+   A_k =  \\sum_{m=0}^{n-1} a_m \\exp\\left\\{-2\\pi i{mk \\over n}\\right\\}
+   \\qquad k = 0,\\ldots,n-1.
+
+The DFT is in general defined for complex inputs and outputs, and a
+single-frequency component at linear frequency :math:`f` is
+represented by a complex exponential
+:math:`a_m = \\exp\\{2\\pi i\\,f m\\Delta t\\}`, where :math:`\\Delta t`
+is the sampling interval.
+
+The values in the result follow so-called "standard" order: If ``A =
+fft(a, n)``, then ``A[0]`` contains the zero-frequency term (the sum of
+the signal), which is always purely real for real inputs. Then ``A[1:n/2]``
+contains the positive-frequency terms, and ``A[n/2+1:]`` contains the
+negative-frequency terms, in order of decreasingly negative frequency.
+For an even number of input points, ``A[n/2]`` represents both positive and
+negative Nyquist frequency, and is also purely real for real input.  For
+an odd number of input points, ``A[(n-1)/2]`` contains the largest positive
+frequency, while ``A[(n+1)/2]`` contains the largest negative frequency.
+The routine ``np.fft.fftfreq(n)`` returns an array giving the frequencies
+of corresponding elements in the output.  The routine
+``np.fft.fftshift(A)`` shifts transforms and their frequencies to put the
+zero-frequency components in the middle, and ``np.fft.ifftshift(A)`` undoes
+that shift.
+
+When the input `a` is a time-domain signal and ``A = fft(a)``, ``np.abs(A)``
+is its amplitude spectrum and ``np.abs(A)**2`` is its power spectrum.
+The phase spectrum is obtained by ``np.angle(A)``.
+
+The inverse DFT is defined as
+
+.. math::
+   a_m = \\frac{1}{n}\\sum_{k=0}^{n-1}A_k\\exp\\left\\{2\\pi i{mk\\over n}\\right\\}
+   \\qquad m = 0,\\ldots,n-1.
+
+It differs from the forward transform by the sign of the exponential
+argument and the default normalization by :math:`1/n`.
+
+Type Promotion
+--------------
+
+`numpy.fft` promotes ``float32`` and ``complex64`` arrays to ``float64`` and
+``complex128`` arrays respectively. For an FFT implementation that does not
+promote input arrays, see `scipy.fftpack`.
+
+Normalization
+-------------
+
+The argument ``norm`` indicates which direction of the pair of direct/inverse
+transforms is scaled and with what normalization factor.
+The default normalization (``"backward"``) has the direct (forward) transforms
+unscaled and the inverse (backward) transforms scaled by :math:`1/n`. It is
+possible to obtain unitary transforms by setting the keyword argument ``norm``
+to ``"ortho"`` so that both direct and inverse transforms are scaled by
+:math:`1/\\sqrt{n}`. Finally, setting the keyword argument ``norm`` to
+``"forward"`` has the direct transforms scaled by :math:`1/n` and the inverse
+transforms unscaled (i.e. exactly opposite to the default ``"backward"``).
+`None` is an alias of the default option ``"backward"`` for backward
+compatibility.
+
+Real and Hermitian transforms
+-----------------------------
+
+When the input is purely real, its transform is Hermitian, i.e., the
+component at frequency :math:`f_k` is the complex conjugate of the
+component at frequency :math:`-f_k`, which means that for real
+inputs there is no information in the negative frequency components that
+is not already available from the positive frequency components.
+The family of `rfft` functions is
+designed to operate on real inputs, and exploits this symmetry by
+computing only the positive frequency components, up to and including the
+Nyquist frequency.  Thus, ``n`` input points produce ``n/2+1`` complex
+output points.  The inverses of this family assumes the same symmetry of
+its input, and for an output of ``n`` points uses ``n/2+1`` input points.
+
+Correspondingly, when the spectrum is purely real, the signal is
+Hermitian.  The `hfft` family of functions exploits this symmetry by
+using ``n/2+1`` complex points in the input (time) domain for ``n`` real
+points in the frequency domain.
+
+In higher dimensions, FFTs are used, e.g., for image analysis and
+filtering.  The computational efficiency of the FFT means that it can
+also be a faster way to compute large convolutions, using the property
+that a convolution in the time domain is equivalent to a point-by-point
+multiplication in the frequency domain.
+
+Higher dimensions
+-----------------
+
+In two dimensions, the DFT is defined as
+
+.. math::
+   A_{kl} =  \\sum_{m=0}^{M-1} \\sum_{n=0}^{N-1}
+   a_{mn}\\exp\\left\\{-2\\pi i \\left({mk\\over M}+{nl\\over N}\\right)\\right\\}
+   \\qquad k = 0, \\ldots, M-1;\\quad l = 0, \\ldots, N-1,
+
+which extends in the obvious way to higher dimensions, and the inverses
+in higher dimensions also extend in the same way.
+
+References
+----------
+
+.. [CT] Cooley, James W., and John W. Tukey, 1965, "An algorithm for the
+        machine calculation of complex Fourier series," *Math. Comput.*
+        19: 297-301.
+
+.. [NR] Press, W., Teukolsky, S., Vetterline, W.T., and Flannery, B.P.,
+        2007, *Numerical Recipes: The Art of Scientific Computing*, ch.
+        12-13.  Cambridge Univ. Press, Cambridge, UK.
+
+Examples
+--------
+
+For examples, see the various functions.
+
+"""
+
+from . import _helper, _pocketfft
+from ._helper import *
+from ._pocketfft import *
+
+__all__ = _pocketfft.__all__.copy()  # noqa: PLE0605
+__all__ += _helper.__all__
+
+from numpy._pytesttester import PytestTester
+
+test = PytestTester(__name__)
+del PytestTester
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/fft/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..bb7fa064cca5d5c9bbff322def21186cd06c3293
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/__init__.pyi
@@ -0,0 +1,38 @@
+from ._helper import fftfreq, fftshift, ifftshift, rfftfreq
+from ._pocketfft import (
+    fft,
+    fft2,
+    fftn,
+    hfft,
+    ifft,
+    ifft2,
+    ifftn,
+    ihfft,
+    irfft,
+    irfft2,
+    irfftn,
+    rfft,
+    rfft2,
+    rfftn,
+)
+
+__all__ = [
+    "fft",
+    "ifft",
+    "rfft",
+    "irfft",
+    "hfft",
+    "ihfft",
+    "rfftn",
+    "irfftn",
+    "rfft2",
+    "irfft2",
+    "fft2",
+    "ifft2",
+    "fftn",
+    "ifftn",
+    "fftshift",
+    "ifftshift",
+    "fftfreq",
+    "rfftfreq",
+]
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/_helper.py b/python/user_packages/Python313/site-packages/numpy/fft/_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..cafa85a5695a75ba297591b4a9643a0944291c02
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/_helper.py
@@ -0,0 +1,235 @@
+"""
+Discrete Fourier Transforms - _helper.py
+
+"""
+from numpy._core import arange, asarray, empty, integer, roll
+from numpy._core.overrides import array_function_dispatch, set_module
+
+# Created by Pearu Peterson, September 2002
+
+__all__ = ['fftshift', 'ifftshift', 'fftfreq', 'rfftfreq']
+
+integer_types = (int, integer)
+
+
+def _fftshift_dispatcher(x, axes=None):
+    return (x,)
+
+
+@array_function_dispatch(_fftshift_dispatcher, module='numpy.fft')
+def fftshift(x, axes=None):
+    """
+    Shift the zero-frequency component to the center of the spectrum.
+
+    This function swaps half-spaces for all axes listed (defaults to all).
+    Note that ``y[0]`` is the Nyquist component only if ``len(x)`` is even.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.
+    axes : int or shape tuple, optional
+        Axes over which to shift.  Default is None, which shifts all axes.
+
+    Returns
+    -------
+    y : ndarray
+        The shifted array.
+
+    See Also
+    --------
+    ifftshift : The inverse of `fftshift`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> freqs = np.fft.fftfreq(10, 0.1)
+    >>> freqs
+    array([ 0.,  1.,  2., ..., -3., -2., -1.])
+    >>> np.fft.fftshift(freqs)
+    array([-5., -4., -3., -2., -1.,  0.,  1.,  2.,  3.,  4.])
+
+    Shift the zero-frequency component only along the second axis:
+
+    >>> freqs = np.fft.fftfreq(9, d=1./9).reshape(3, 3)
+    >>> freqs
+    array([[ 0.,  1.,  2.],
+           [ 3.,  4., -4.],
+           [-3., -2., -1.]])
+    >>> np.fft.fftshift(freqs, axes=(1,))
+    array([[ 2.,  0.,  1.],
+           [-4.,  3.,  4.],
+           [-1., -3., -2.]])
+
+    """
+    x = asarray(x)
+    if axes is None:
+        axes = tuple(range(x.ndim))
+        shift = [dim // 2 for dim in x.shape]
+    elif isinstance(axes, integer_types):
+        shift = x.shape[axes] // 2
+    else:
+        shift = [x.shape[ax] // 2 for ax in axes]
+
+    return roll(x, shift, axes)
+
+
+@array_function_dispatch(_fftshift_dispatcher, module='numpy.fft')
+def ifftshift(x, axes=None):
+    """
+    The inverse of `fftshift`. Although identical for even-length `x`, the
+    functions differ by one sample for odd-length `x`.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.
+    axes : int or shape tuple, optional
+        Axes over which to calculate.  Defaults to None, which shifts all axes.
+
+    Returns
+    -------
+    y : ndarray
+        The shifted array.
+
+    See Also
+    --------
+    fftshift : Shift zero-frequency component to the center of the spectrum.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> freqs = np.fft.fftfreq(9, d=1./9).reshape(3, 3)
+    >>> freqs
+    array([[ 0.,  1.,  2.],
+           [ 3.,  4., -4.],
+           [-3., -2., -1.]])
+    >>> np.fft.ifftshift(np.fft.fftshift(freqs))
+    array([[ 0.,  1.,  2.],
+           [ 3.,  4., -4.],
+           [-3., -2., -1.]])
+
+    """
+    x = asarray(x)
+    if axes is None:
+        axes = tuple(range(x.ndim))
+        shift = [-(dim // 2) for dim in x.shape]
+    elif isinstance(axes, integer_types):
+        shift = -(x.shape[axes] // 2)
+    else:
+        shift = [-(x.shape[ax] // 2) for ax in axes]
+
+    return roll(x, shift, axes)
+
+
+@set_module('numpy.fft')
+def fftfreq(n, d=1.0, device=None):
+    """
+    Return the Discrete Fourier Transform sample frequencies.
+
+    The returned float array `f` contains the frequency bin centers in cycles
+    per unit of the sample spacing (with zero at the start).  For instance, if
+    the sample spacing is in seconds, then the frequency unit is cycles/second.
+
+    Given a window length `n` and a sample spacing `d`::
+
+      f = [0, 1, ...,   n/2-1,     -n/2, ..., -1] / (d*n)   if n is even
+      f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (d*n)   if n is odd
+
+    Parameters
+    ----------
+    n : int
+        Window length.
+    d : scalar, optional
+        Sample spacing (inverse of the sampling rate). Defaults to 1.
+    device : str, optional
+        The device on which to place the created array. Default: ``None``.
+        For Array-API interoperability only, so must be ``"cpu"`` if passed.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    f : ndarray
+        Array of length `n` containing the sample frequencies.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
+    >>> fourier = np.fft.fft(signal)
+    >>> n = signal.size
+    >>> timestep = 0.1
+    >>> freq = np.fft.fftfreq(n, d=timestep)
+    >>> freq
+    array([ 0.  ,  1.25,  2.5 , ..., -3.75, -2.5 , -1.25])
+
+    """
+    if not isinstance(n, integer_types):
+        raise ValueError("n should be an integer")
+    val = 1.0 / (n * d)
+    results = empty(n, int, device=device)
+    N = (n - 1) // 2 + 1
+    p1 = arange(0, N, dtype=int, device=device)
+    results[:N] = p1
+    p2 = arange(-(n // 2), 0, dtype=int, device=device)
+    results[N:] = p2
+    return results * val
+
+
+@set_module('numpy.fft')
+def rfftfreq(n, d=1.0, device=None):
+    """
+    Return the Discrete Fourier Transform sample frequencies
+    (for usage with rfft, irfft).
+
+    The returned float array `f` contains the frequency bin centers in cycles
+    per unit of the sample spacing (with zero at the start).  For instance, if
+    the sample spacing is in seconds, then the frequency unit is cycles/second.
+
+    Given a window length `n` and a sample spacing `d`::
+
+      f = [0, 1, ...,     n/2-1,     n/2] / (d*n)   if n is even
+      f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*n)   if n is odd
+
+    Unlike `fftfreq` (but like `scipy.fftpack.rfftfreq`)
+    the Nyquist frequency component is considered to be positive.
+
+    Parameters
+    ----------
+    n : int
+        Window length.
+    d : scalar, optional
+        Sample spacing (inverse of the sampling rate). Defaults to 1.
+    device : str, optional
+        The device on which to place the created array. Default: ``None``.
+        For Array-API interoperability only, so must be ``"cpu"`` if passed.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    f : ndarray
+        Array of length ``n//2 + 1`` containing the sample frequencies.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4], dtype=float)
+    >>> fourier = np.fft.rfft(signal)
+    >>> n = signal.size
+    >>> sample_rate = 100
+    >>> freq = np.fft.fftfreq(n, d=1./sample_rate)
+    >>> freq
+    array([  0.,  10.,  20., ..., -30., -20., -10.])
+    >>> freq = np.fft.rfftfreq(n, d=1./sample_rate)
+    >>> freq
+    array([  0.,  10.,  20.,  30.,  40.,  50.])
+
+    """
+    if not isinstance(n, integer_types):
+        raise ValueError("n should be an integer")
+    val = 1.0 / (n * d)
+    N = n // 2 + 1
+    results = arange(0, N, dtype=int, device=device)
+    return results * val
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/_helper.pyi b/python/user_packages/Python313/site-packages/numpy/fft/_helper.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..cb6d41977463fc50ce5140d0811b55e18fc6b102
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/_helper.pyi
@@ -0,0 +1,44 @@
+from typing import Any, Final, Literal as L, TypeVar, overload
+
+from numpy import complexfloating, floating, generic, integer
+from numpy._typing import (
+    ArrayLike,
+    NDArray,
+    _ArrayLike,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ShapeLike,
+)
+
+__all__ = ["fftfreq", "fftshift", "ifftshift", "rfftfreq"]
+
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+
+###
+
+integer_types: Final[tuple[type[int], type[integer]]] = ...
+
+###
+
+@overload
+def fftshift(x: _ArrayLike[_ScalarT], axes: _ShapeLike | None = None) -> NDArray[_ScalarT]: ...
+@overload
+def fftshift(x: ArrayLike, axes: _ShapeLike | None = None) -> NDArray[Any]: ...
+
+#
+@overload
+def ifftshift(x: _ArrayLike[_ScalarT], axes: _ShapeLike | None = None) -> NDArray[_ScalarT]: ...
+@overload
+def ifftshift(x: ArrayLike, axes: _ShapeLike | None = None) -> NDArray[Any]: ...
+
+#
+@overload
+def fftfreq(n: int | integer, d: _ArrayLikeFloat_co = 1.0, device: L["cpu"] | None = None) -> NDArray[floating]: ...
+@overload
+def fftfreq(n: int | integer, d: _ArrayLikeComplex_co = 1.0, device: L["cpu"] | None = None) -> NDArray[complexfloating]: ...
+
+#
+@overload
+def rfftfreq(n: int | integer, d: _ArrayLikeFloat_co = 1.0, device: L["cpu"] | None = None) -> NDArray[floating]: ...
+@overload
+def rfftfreq(n: int | integer, d: _ArrayLikeComplex_co = 1.0, device: L["cpu"] | None = None) -> NDArray[complexfloating]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.py b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.py
new file mode 100644
index 0000000000000000000000000000000000000000..ffac7935f301809e8eac74981b83d625b6c2a2f8
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.py
@@ -0,0 +1,1693 @@
+"""
+Discrete Fourier Transforms
+
+Routines in this module:
+
+fft(a, n=None, axis=-1, norm="backward")
+ifft(a, n=None, axis=-1, norm="backward")
+rfft(a, n=None, axis=-1, norm="backward")
+irfft(a, n=None, axis=-1, norm="backward")
+hfft(a, n=None, axis=-1, norm="backward")
+ihfft(a, n=None, axis=-1, norm="backward")
+fftn(a, s=None, axes=None, norm="backward")
+ifftn(a, s=None, axes=None, norm="backward")
+rfftn(a, s=None, axes=None, norm="backward")
+irfftn(a, s=None, axes=None, norm="backward")
+fft2(a, s=None, axes=(-2,-1), norm="backward")
+ifft2(a, s=None, axes=(-2, -1), norm="backward")
+rfft2(a, s=None, axes=(-2,-1), norm="backward")
+irfft2(a, s=None, axes=(-2, -1), norm="backward")
+
+i = inverse transform
+r = transform of purely real data
+h = Hermite transform
+n = n-dimensional transform
+2 = 2-dimensional transform
+(Note: 2D routines are just nD routines with different default
+behavior.)
+
+"""
+__all__ = ['fft', 'ifft', 'rfft', 'irfft', 'hfft', 'ihfft', 'rfftn',
+           'irfftn', 'rfft2', 'irfft2', 'fft2', 'ifft2', 'fftn', 'ifftn']
+
+import functools
+import warnings
+
+from numpy._core import (
+    asarray,
+    conjugate,
+    empty_like,
+    overrides,
+    reciprocal,
+    result_type,
+    sqrt,
+    take,
+)
+from numpy.lib.array_utils import normalize_axis_index
+
+from . import _pocketfft_umath as pfu
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy.fft')
+
+
+# `inv_norm` is a float by which the result of the transform needs to be
+# divided. This replaces the original, more intuitive 'fct` parameter to avoid
+# divisions by zero (or alternatively additional checks) in the case of
+# zero-length axes during its computation.
+def _raw_fft(a, n, axis, is_real, is_forward, norm, out=None):
+    if n < 1:
+        raise ValueError(f"Invalid number of FFT data points ({n}) specified.")
+
+    # Calculate the normalization factor, passing in the array dtype to
+    # avoid precision loss in the possible sqrt or reciprocal.
+    if not is_forward:
+        norm = _swap_direction(norm)
+
+    real_dtype = result_type(a.real.dtype, 1.0)
+    if norm is None or norm == "backward":
+        fct = 1
+    elif norm == "ortho":
+        fct = reciprocal(sqrt(n, dtype=real_dtype))
+    elif norm == "forward":
+        fct = reciprocal(n, dtype=real_dtype)
+    else:
+        raise ValueError(f'Invalid norm value {norm}; should be "backward",'
+                         '"ortho" or "forward".')
+
+    n_out = n
+    if is_real:
+        if is_forward:
+            ufunc = pfu.rfft_n_even if n % 2 == 0 else pfu.rfft_n_odd
+            n_out = n // 2 + 1
+        else:
+            ufunc = pfu.irfft
+    else:
+        ufunc = pfu.fft if is_forward else pfu.ifft
+
+    axis = normalize_axis_index(axis, a.ndim)
+
+    if out is None:
+        if is_real and not is_forward:  # irfft, complex in, real output.
+            out_dtype = real_dtype
+        else:  # Others, complex output.
+            out_dtype = result_type(a.dtype, 1j)
+        out = empty_like(a, shape=a.shape[:axis] + (n_out,) + a.shape[axis + 1:],
+                         dtype=out_dtype)
+    elif ((shape := getattr(out, "shape", None)) is not None
+          and (len(shape) != a.ndim or shape[axis] != n_out)):
+        raise ValueError("output array has wrong shape.")
+
+    return ufunc(a, fct, axes=[(axis,), (), (axis,)], out=out)
+
+
+_SWAP_DIRECTION_MAP = {"backward": "forward", None: "forward",
+                       "ortho": "ortho", "forward": "backward"}
+
+
+def _swap_direction(norm):
+    try:
+        return _SWAP_DIRECTION_MAP[norm]
+    except KeyError:
+        raise ValueError(f'Invalid norm value {norm}; should be "backward", '
+                         '"ortho" or "forward".') from None
+
+
+def _fft_dispatcher(a, n=None, axis=None, norm=None, out=None):
+    return (a, out)
+
+
+@array_function_dispatch(_fft_dispatcher)
+def fft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Compute the one-dimensional discrete Fourier Transform.
+
+    This function computes the one-dimensional *n*-point discrete Fourier
+    Transform (DFT) with the efficient Fast Fourier Transform (FFT)
+    algorithm [CT]_.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex.
+    n : int, optional
+        Length of the transformed axis of the output.
+        If `n` is smaller than the length of the input, the input is cropped.
+        If it is larger, the input is padded with zeros.  If `n` is not given,
+        the length of the input along the axis specified by `axis` is used.
+    axis : int, optional
+        Axis over which to compute the FFT.  If not given, the last axis is
+        used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+
+    Raises
+    ------
+    IndexError
+        If `axis` is not a valid axis of `a`.
+
+    See Also
+    --------
+    numpy.fft : for definition of the DFT and conventions used.
+    ifft : The inverse of `fft`.
+    fft2 : The two-dimensional FFT.
+    fftn : The *n*-dimensional FFT.
+    rfftn : The *n*-dimensional FFT of real input.
+    fftfreq : Frequency bins for given FFT parameters.
+
+    Notes
+    -----
+    FFT (Fast Fourier Transform) refers to a way the discrete Fourier
+    Transform (DFT) can be calculated efficiently, by using symmetries in the
+    calculated terms.  The symmetry is highest when `n` is a power of 2, and
+    the transform is therefore most efficient for these sizes.
+
+    The DFT is defined, with the conventions used in this implementation, in
+    the documentation for the `numpy.fft` module.
+
+    References
+    ----------
+    .. [CT] Cooley, James W., and John W. Tukey, 1965, "An algorithm for the
+            machine calculation of complex Fourier series," *Math. Comput.*
+            19: 297-301.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.fft.fft(np.exp(2j * np.pi * np.arange(8) / 8))
+    array([-2.33486982e-16+1.14423775e-17j,  8.00000000e+00-1.25557246e-15j,
+            2.33486982e-16+2.33486982e-16j,  0.00000000e+00+1.22464680e-16j,
+           -1.14423775e-17+2.33486982e-16j,  0.00000000e+00+5.20784380e-16j,
+            1.14423775e-17+1.14423775e-17j,  0.00000000e+00+1.22464680e-16j])
+
+    In this example, real input has an FFT which is Hermitian, i.e., symmetric
+    in the real part and anti-symmetric in the imaginary part, as described in
+    the `numpy.fft` documentation:
+
+    >>> import matplotlib.pyplot as plt
+    >>> t = np.arange(256)
+    >>> sp = np.fft.fft(np.sin(t))
+    >>> freq = np.fft.fftfreq(t.shape[-1])
+    >>> _ = plt.plot(freq, sp.real, freq, sp.imag)
+    >>> plt.show()
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = a.shape[axis]
+    output = _raw_fft(a, n, axis, False, True, norm, out)
+    return output
+
+
+@array_function_dispatch(_fft_dispatcher)
+def ifft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Compute the one-dimensional inverse discrete Fourier Transform.
+
+    This function computes the inverse of the one-dimensional *n*-point
+    discrete Fourier transform computed by `fft`.  In other words,
+    ``ifft(fft(a)) == a`` to within numerical accuracy.
+    For a general description of the algorithm and definitions,
+    see `numpy.fft`.
+
+    The input should be ordered in the same way as is returned by `fft`,
+    i.e.,
+
+    * ``a[0]`` should contain the zero frequency term,
+    * ``a[1:n//2]`` should contain the positive-frequency terms,
+    * ``a[n//2 + 1:]`` should contain the negative-frequency terms, in
+      increasing order starting from the most negative frequency.
+
+    For an even number of input points, ``A[n//2]`` represents the sum of
+    the values at the positive and negative Nyquist frequencies, as the two
+    are aliased together. See `numpy.fft` for details.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex.
+    n : int, optional
+        Length of the transformed axis of the output.
+        If `n` is smaller than the length of the input, the input is cropped.
+        If it is larger, the input is padded with zeros.  If `n` is not given,
+        the length of the input along the axis specified by `axis` is used.
+        See notes about padding issues.
+    axis : int, optional
+        Axis over which to compute the inverse DFT.  If not given, the last
+        axis is used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+
+    Raises
+    ------
+    IndexError
+        If `axis` is not a valid axis of `a`.
+
+    See Also
+    --------
+    numpy.fft : An introduction, with definitions and general explanations.
+    fft : The one-dimensional (forward) FFT, of which `ifft` is the inverse
+    ifft2 : The two-dimensional inverse FFT.
+    ifftn : The n-dimensional inverse FFT.
+
+    Notes
+    -----
+    If the input parameter `n` is larger than the size of the input, the input
+    is padded by appending zeros at the end.  Even though this is the common
+    approach, it might lead to surprising results.  If a different padding is
+    desired, it must be performed before calling `ifft`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.fft.ifft([0, 4, 0, 0])
+    array([ 1.+0.j,  0.+1.j, -1.+0.j,  0.-1.j]) # may vary
+
+    Create and plot a band-limited signal with random phases:
+
+    >>> import matplotlib.pyplot as plt
+    >>> t = np.arange(400)
+    >>> n = np.zeros((400,), dtype=complex)
+    >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,)))
+    >>> s = np.fft.ifft(n)
+    >>> plt.plot(t, s.real, label='real')
+    [<matplotlib.lines.Line2D object at ...>]
+    >>> plt.plot(t, s.imag, '--', label='imaginary')
+    [<matplotlib.lines.Line2D object at ...>]
+    >>> plt.legend()
+    <matplotlib.legend.Legend object at ...>
+    >>> plt.show()
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = a.shape[axis]
+    output = _raw_fft(a, n, axis, False, False, norm, out=out)
+    return output
+
+
+@array_function_dispatch(_fft_dispatcher)
+def rfft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Compute the one-dimensional discrete Fourier Transform for real input.
+
+    This function computes the one-dimensional *n*-point discrete Fourier
+    Transform (DFT) of a real-valued array by means of an efficient algorithm
+    called the Fast Fourier Transform (FFT).
+
+    Parameters
+    ----------
+    a : array_like
+        Input array
+    n : int, optional
+        Number of points along transformation axis in the input to use.
+        If `n` is smaller than the length of the input, the input is cropped.
+        If it is larger, the input is padded with zeros. If `n` is not given,
+        the length of the input along the axis specified by `axis` is used.
+    axis : int, optional
+        Axis over which to compute the FFT. If not given, the last axis is
+        used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+        If `n` is even, the length of the transformed axis is ``(n/2)+1``.
+        If `n` is odd, the length is ``(n+1)/2``.
+
+    Raises
+    ------
+    IndexError
+        If `axis` is not a valid axis of `a`.
+
+    See Also
+    --------
+    numpy.fft : For definition of the DFT and conventions used.
+    irfft : The inverse of `rfft`.
+    fft : The one-dimensional FFT of general (complex) input.
+    fftn : The *n*-dimensional FFT.
+    rfftn : The *n*-dimensional FFT of real input.
+
+    Notes
+    -----
+    When the DFT is computed for purely real input, the output is
+    Hermitian-symmetric, i.e. the negative frequency terms are just the complex
+    conjugates of the corresponding positive-frequency terms, and the
+    negative-frequency terms are therefore redundant.  This function does not
+    compute the negative frequency terms, and the length of the transformed
+    axis of the output is therefore ``n//2 + 1``.
+
+    When ``A = rfft(a)`` and fs is the sampling frequency, ``A[0]`` contains
+    the zero-frequency term 0*fs, which is real due to Hermitian symmetry.
+
+    If `n` is even, ``A[-1]`` contains the term representing both positive
+    and negative Nyquist frequency (+fs/2 and -fs/2), and must also be purely
+    real. If `n` is odd, there is no term at fs/2; ``A[-1]`` contains
+    the largest positive frequency (fs/2*(n-1)/n), and is complex in the
+    general case.
+
+    If the input `a` contains an imaginary part, it is silently discarded.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.fft.fft([0, 1, 0, 0])
+    array([ 1.+0.j,  0.-1.j, -1.+0.j,  0.+1.j]) # may vary
+    >>> np.fft.rfft([0, 1, 0, 0])
+    array([ 1.+0.j,  0.-1.j, -1.+0.j]) # may vary
+
+    Notice how the final element of the `fft` output is the complex conjugate
+    of the second element, for real input. For `rfft`, this symmetry is
+    exploited to compute only the non-negative frequency terms.
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = a.shape[axis]
+    output = _raw_fft(a, n, axis, True, True, norm, out=out)
+    return output
+
+
+@array_function_dispatch(_fft_dispatcher)
+def irfft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Computes the inverse of `rfft`.
+
+    This function computes the inverse of the one-dimensional *n*-point
+    discrete Fourier Transform of real input computed by `rfft`.
+    In other words, ``irfft(rfft(a), len(a)) == a`` to within numerical
+    accuracy. (See Notes below for why ``len(a)`` is necessary here.)
+
+    The input is expected to be in the form returned by `rfft`, i.e. the
+    real zero-frequency term followed by the complex positive frequency terms
+    in order of increasing frequency.  Since the discrete Fourier Transform of
+    real input is Hermitian-symmetric, the negative frequency terms are taken
+    to be the complex conjugates of the corresponding positive frequency terms.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array.
+    n : int, optional
+        Length of the transformed axis of the output.
+        For `n` output points, ``n//2+1`` input points are necessary.  If the
+        input is longer than this, it is cropped.  If it is shorter than this,
+        it is padded with zeros.  If `n` is not given, it is taken to be
+        ``2*(m-1)`` where ``m`` is the length of the input along the axis
+        specified by `axis`.
+    axis : int, optional
+        Axis over which to compute the inverse FFT. If not given, the last
+        axis is used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+        The length of the transformed axis is `n`, or, if `n` is not given,
+        ``2*(m-1)`` where ``m`` is the length of the transformed axis of the
+        input. To get an odd number of output points, `n` must be specified.
+
+    Raises
+    ------
+    IndexError
+        If `axis` is not a valid axis of `a`.
+
+    See Also
+    --------
+    numpy.fft : For definition of the DFT and conventions used.
+    rfft : The one-dimensional FFT of real input, of which `irfft` is inverse.
+    fft : The one-dimensional FFT.
+    irfft2 : The inverse of the two-dimensional FFT of real input.
+    irfftn : The inverse of the *n*-dimensional FFT of real input.
+
+    Notes
+    -----
+    Returns the real valued `n`-point inverse discrete Fourier transform
+    of `a`, where `a` contains the non-negative frequency terms of a
+    Hermitian-symmetric sequence. `n` is the length of the result, not the
+    input.
+
+    If you specify an `n` such that `a` must be zero-padded or truncated, the
+    extra/removed values will be added/removed at high frequencies. One can
+    thus resample a series to `m` points via Fourier interpolation by:
+    ``a_resamp = irfft(rfft(a), m)``.
+
+    The correct interpretation of the hermitian input depends on the length of
+    the original data, as given by `n`. This is because each input shape could
+    correspond to either an odd or even length signal. By default, `irfft`
+    assumes an even output length which puts the last entry at the Nyquist
+    frequency; aliasing with its symmetric counterpart. By Hermitian symmetry,
+    the value is thus treated as purely real. To avoid losing information, the
+    correct length of the real input **must** be given.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.fft.ifft([1, -1j, -1, 1j])
+    array([0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j]) # may vary
+    >>> np.fft.irfft([1, -1j, -1])
+    array([0.,  1.,  0.,  0.])
+
+    Notice how the last term in the input to the ordinary `ifft` is the
+    complex conjugate of the second term, and the output has zero imaginary
+    part everywhere.  When calling `irfft`, the negative frequencies are not
+    specified, and the output array is purely real.
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = (a.shape[axis] - 1) * 2
+    output = _raw_fft(a, n, axis, True, False, norm, out=out)
+    return output
+
+
+@array_function_dispatch(_fft_dispatcher)
+def hfft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Compute the FFT of a signal that has Hermitian symmetry, i.e., a real
+    spectrum.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array.
+    n : int, optional
+        Length of the transformed axis of the output. For `n` output
+        points, ``n//2 + 1`` input points are necessary.  If the input is
+        longer than this, it is cropped.  If it is shorter than this, it is
+        padded with zeros.  If `n` is not given, it is taken to be ``2*(m-1)``
+        where ``m`` is the length of the input along the axis specified by
+        `axis`.
+    axis : int, optional
+        Axis over which to compute the FFT. If not given, the last
+        axis is used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+        The length of the transformed axis is `n`, or, if `n` is not given,
+        ``2*m - 2`` where ``m`` is the length of the transformed axis of
+        the input. To get an odd number of output points, `n` must be
+        specified, for instance as ``2*m - 1`` in the typical case,
+
+    Raises
+    ------
+    IndexError
+        If `axis` is not a valid axis of `a`.
+
+    See also
+    --------
+    rfft : Compute the one-dimensional FFT for real input.
+    ihfft : The inverse of `hfft`.
+
+    Notes
+    -----
+    `hfft`/`ihfft` are a pair analogous to `rfft`/`irfft`, but for the
+    opposite case: here the signal has Hermitian symmetry in the time
+    domain and is real in the frequency domain. So here it's `hfft` for
+    which you must supply the length of the result if it is to be odd.
+
+    * even: ``ihfft(hfft(a, 2*len(a) - 2)) == a``, within roundoff error,
+    * odd: ``ihfft(hfft(a, 2*len(a) - 1)) == a``, within roundoff error.
+
+    The correct interpretation of the hermitian input depends on the length of
+    the original data, as given by `n`. This is because each input shape could
+    correspond to either an odd or even length signal. By default, `hfft`
+    assumes an even output length which puts the last entry at the Nyquist
+    frequency; aliasing with its symmetric counterpart. By Hermitian symmetry,
+    the value is thus treated as purely real. To avoid losing information, the
+    shape of the full signal **must** be given.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> signal = np.array([1, 2, 3, 4, 3, 2])
+    >>> np.fft.fft(signal)
+    array([15.+0.j,  -4.+0.j,   0.+0.j,  -1.-0.j,   0.+0.j,  -4.+0.j]) # may vary
+    >>> np.fft.hfft(signal[:4]) # Input first half of signal
+    array([15.,  -4.,   0.,  -1.,   0.,  -4.])
+    >>> np.fft.hfft(signal, 6)  # Input entire signal and truncate
+    array([15.,  -4.,   0.,  -1.,   0.,  -4.])
+
+
+    >>> signal = np.array([[1, 1.j], [-1.j, 2]])
+    >>> np.conj(signal.T) - signal   # check Hermitian symmetry
+    array([[ 0.-0.j,  -0.+0.j], # may vary
+           [ 0.+0.j,  0.-0.j]])
+    >>> freq_spectrum = np.fft.hfft(signal)
+    >>> freq_spectrum
+    array([[ 1.,  1.],
+           [ 2., -2.]])
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = (a.shape[axis] - 1) * 2
+    new_norm = _swap_direction(norm)
+    output = irfft(conjugate(a), n, axis, norm=new_norm, out=None)
+    return output
+
+
+@array_function_dispatch(_fft_dispatcher)
+def ihfft(a, n=None, axis=-1, norm=None, out=None):
+    """
+    Compute the inverse FFT of a signal that has Hermitian symmetry.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    n : int, optional
+        Length of the inverse FFT, the number of points along
+        transformation axis in the input to use.  If `n` is smaller than
+        the length of the input, the input is cropped.  If it is larger,
+        the input is padded with zeros. If `n` is not given, the length of
+        the input along the axis specified by `axis` is used.
+    axis : int, optional
+        Axis over which to compute the inverse FFT. If not given, the last
+        axis is used.
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axis
+        indicated by `axis`, or the last one if `axis` is not specified.
+        The length of the transformed axis is ``n//2 + 1``.
+
+    See also
+    --------
+    hfft, irfft
+
+    Notes
+    -----
+    `hfft`/`ihfft` are a pair analogous to `rfft`/`irfft`, but for the
+    opposite case: here the signal has Hermitian symmetry in the time
+    domain and is real in the frequency domain. So here it's `hfft` for
+    which you must supply the length of the result if it is to be odd:
+
+    * even: ``ihfft(hfft(a, 2*len(a) - 2)) == a``, within roundoff error,
+    * odd: ``ihfft(hfft(a, 2*len(a) - 1)) == a``, within roundoff error.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> spectrum = np.array([ 15, -4, 0, -1, 0, -4])
+    >>> np.fft.ifft(spectrum)
+    array([1.+0.j,  2.+0.j,  3.+0.j,  4.+0.j,  3.+0.j,  2.+0.j]) # may vary
+    >>> np.fft.ihfft(spectrum)
+    array([ 1.-0.j,  2.-0.j,  3.-0.j,  4.-0.j]) # may vary
+
+    """
+    a = asarray(a)
+    if n is None:
+        n = a.shape[axis]
+    new_norm = _swap_direction(norm)
+    out = rfft(a, n, axis, norm=new_norm, out=out)
+    return conjugate(out, out=out)
+
+
+def _cook_nd_args(a, s=None, axes=None, invreal=0):
+    if s is None:
+        shapeless = True
+        if axes is None:
+            s = list(a.shape)
+        else:
+            s = take(a.shape, axes)
+    else:
+        shapeless = False
+    s = list(s)
+    if axes is None:
+        if not shapeless:
+            msg = ("`axes` should not be `None` if `s` is not `None` "
+                   "(Deprecated in NumPy 2.0). In a future version of NumPy, "
+                   "this will raise an error and `s[i]` will correspond to "
+                   "the size along the transformed axis specified by "
+                   "`axes[i]`. To retain current behaviour, pass a sequence "
+                   "[0, ..., k-1] to `axes` for an array of dimension k.")
+            warnings.warn(msg, DeprecationWarning, stacklevel=3)
+        axes = list(range(-len(s), 0))
+    if len(s) != len(axes):
+        raise ValueError("Shape and axes have different lengths.")
+    if invreal and shapeless:
+        s[-1] = (a.shape[axes[-1]] - 1) * 2
+    if None in s:
+        msg = ("Passing an array containing `None` values to `s` is "
+               "deprecated in NumPy 2.0 and will raise an error in "
+               "a future version of NumPy. To use the default behaviour "
+               "of the corresponding 1-D transform, pass the value matching "
+               "the default for its `n` parameter. To use the default "
+               "behaviour for every axis, the `s` argument can be omitted.")
+        warnings.warn(msg, DeprecationWarning, stacklevel=3)
+    # use the whole input array along axis `i` if `s[i] == -1`
+    s = [a.shape[_a] if _s == -1 else _s for _s, _a in zip(s, axes)]
+    return s, axes
+
+
+def _raw_fftnd(a, s=None, axes=None, function=fft, norm=None, out=None):
+    a = asarray(a)
+    s, axes = _cook_nd_args(a, s, axes)
+    itl = list(range(len(axes)))
+    itl.reverse()
+    for ii in itl:
+        a = function(a, n=s[ii], axis=axes[ii], norm=norm, out=out)
+    return a
+
+
+def _fftn_dispatcher(a, s=None, axes=None, norm=None, out=None):
+    return (a, out)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def fftn(a, s=None, axes=None, norm=None, out=None):
+    """
+    Compute the N-dimensional discrete Fourier Transform.
+
+    This function computes the *N*-dimensional discrete Fourier Transform over
+    any number of axes in an *M*-dimensional array by means of the Fast Fourier
+    Transform (FFT).
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex.
+    s : sequence of ints, optional
+        Shape (length of each transformed axis) of the output
+        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
+        This corresponds to ``n`` for ``fft(x, n)``.
+        Along any axis, if the given shape is smaller than that of the input,
+        the input is cropped. If it is larger, the input is padded with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes specified
+        by `axes` is used.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the FFT.  If not given, the last ``len(s)``
+        axes are used, or all axes if `s` is also not specified.
+        Repeated indices in `axes` means that the transform over that axis is
+        performed multiple times.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must be explicitly specified too.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for all axes (and hence is
+        incompatible with passing in all but the trivial ``s``).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or by a combination of `s` and `a`,
+        as explained in the parameters section above.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    numpy.fft : Overall view of discrete Fourier transforms, with definitions
+        and conventions used.
+    ifftn : The inverse of `fftn`, the inverse *n*-dimensional FFT.
+    fft : The one-dimensional FFT, with definitions and conventions used.
+    rfftn : The *n*-dimensional FFT of real input.
+    fft2 : The two-dimensional FFT.
+    fftshift : Shifts zero-frequency terms to centre of array
+
+    Notes
+    -----
+    The output, analogously to `fft`, contains the term for zero frequency in
+    the low-order corner of all axes, the positive frequency terms in the
+    first half of all axes, the term for the Nyquist frequency in the middle
+    of all axes and the negative frequency terms in the second half of all
+    axes, in order of decreasingly negative frequency.
+
+    See `numpy.fft` for details, definitions and conventions used.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.mgrid[:3, :3, :3][0]
+    >>> np.fft.fftn(a, axes=(1, 2))
+    array([[[ 0.+0.j,   0.+0.j,   0.+0.j], # may vary
+            [ 0.+0.j,   0.+0.j,   0.+0.j],
+            [ 0.+0.j,   0.+0.j,   0.+0.j]],
+           [[ 9.+0.j,   0.+0.j,   0.+0.j],
+            [ 0.+0.j,   0.+0.j,   0.+0.j],
+            [ 0.+0.j,   0.+0.j,   0.+0.j]],
+           [[18.+0.j,   0.+0.j,   0.+0.j],
+            [ 0.+0.j,   0.+0.j,   0.+0.j],
+            [ 0.+0.j,   0.+0.j,   0.+0.j]]])
+    >>> np.fft.fftn(a, (2, 2), axes=(0, 1))
+    array([[[ 2.+0.j,  2.+0.j,  2.+0.j], # may vary
+            [ 0.+0.j,  0.+0.j,  0.+0.j]],
+           [[-2.+0.j, -2.+0.j, -2.+0.j],
+            [ 0.+0.j,  0.+0.j,  0.+0.j]]])
+
+    >>> import matplotlib.pyplot as plt
+    >>> [X, Y] = np.meshgrid(2 * np.pi * np.arange(200) / 12,
+    ...                      2 * np.pi * np.arange(200) / 34)
+    >>> S = np.sin(X) + np.cos(Y) + np.random.uniform(0, 1, X.shape)
+    >>> FS = np.fft.fftn(S)
+    >>> plt.imshow(np.log(np.abs(np.fft.fftshift(FS))**2))
+    <matplotlib.image.AxesImage object at 0x...>
+    >>> plt.show()
+
+    """
+    return _raw_fftnd(a, s, axes, fft, norm, out=out)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def ifftn(a, s=None, axes=None, norm=None, out=None):
+    """
+    Compute the N-dimensional inverse discrete Fourier Transform.
+
+    This function computes the inverse of the N-dimensional discrete
+    Fourier Transform over any number of axes in an M-dimensional array by
+    means of the Fast Fourier Transform (FFT).  In other words,
+    ``ifftn(fftn(a)) == a`` to within numerical accuracy.
+    For a description of the definitions and conventions used, see `numpy.fft`.
+
+    The input, analogously to `ifft`, should be ordered in the same way as is
+    returned by `fftn`, i.e. it should have the term for zero frequency
+    in all axes in the low-order corner, the positive frequency terms in the
+    first half of all axes, the term for the Nyquist frequency in the middle
+    of all axes and the negative frequency terms in the second half of all
+    axes, in order of decreasingly negative frequency.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex.
+    s : sequence of ints, optional
+        Shape (length of each transformed axis) of the output
+        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
+        This corresponds to ``n`` for ``ifft(x, n)``.
+        Along any axis, if the given shape is smaller than that of the input,
+        the input is cropped. If it is larger, the input is padded with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes specified
+        by `axes` is used. See notes for issue on `ifft` zero padding.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the IFFT.  If not given, the last ``len(s)``
+        axes are used, or all axes if `s` is also not specified.
+        Repeated indices in `axes` means that the inverse transform over that
+        axis is performed multiple times.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must be explicitly specified too.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for all axes (and hence is
+        incompatible with passing in all but the trivial ``s``).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or by a combination of `s` or `a`,
+        as explained in the parameters section above.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    numpy.fft : Overall view of discrete Fourier transforms, with definitions
+         and conventions used.
+    fftn : The forward *n*-dimensional FFT, of which `ifftn` is the inverse.
+    ifft : The one-dimensional inverse FFT.
+    ifft2 : The two-dimensional inverse FFT.
+    ifftshift : Undoes `fftshift`, shifts zero-frequency terms to beginning
+        of array.
+
+    Notes
+    -----
+    See `numpy.fft` for definitions and conventions used.
+
+    Zero-padding, analogously with `ifft`, is performed by appending zeros to
+    the input along the specified dimension.  Although this is the common
+    approach, it might lead to surprising results.  If another form of zero
+    padding is desired, it must be performed before `ifftn` is called.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.eye(4)
+    >>> np.fft.ifftn(np.fft.fftn(a, axes=(0,)), axes=(1,))
+    array([[1.+0.j,  0.+0.j,  0.+0.j,  0.+0.j], # may vary
+           [0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j],
+           [0.+0.j,  0.+0.j,  1.+0.j,  0.+0.j],
+           [0.+0.j,  0.+0.j,  0.+0.j,  1.+0.j]])
+
+
+    Create and plot an image with band-limited frequency content:
+
+    >>> import matplotlib.pyplot as plt
+    >>> n = np.zeros((200,200), dtype=complex)
+    >>> n[60:80, 20:40] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20, 20)))
+    >>> im = np.fft.ifftn(n).real
+    >>> plt.imshow(im)
+    <matplotlib.image.AxesImage object at 0x...>
+    >>> plt.show()
+
+    """
+    return _raw_fftnd(a, s, axes, ifft, norm, out=out)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def fft2(a, s=None, axes=(-2, -1), norm=None, out=None):
+    """
+    Compute the 2-dimensional discrete Fourier Transform.
+
+    This function computes the *n*-dimensional discrete Fourier Transform
+    over any axes in an *M*-dimensional array by means of the
+    Fast Fourier Transform (FFT).  By default, the transform is computed over
+    the last two axes of the input array, i.e., a 2-dimensional FFT.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex
+    s : sequence of ints, optional
+        Shape (length of each transformed axis) of the output
+        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
+        This corresponds to ``n`` for ``fft(x, n)``.
+        Along each axis, if the given shape is smaller than that of the input,
+        the input is cropped. If it is larger, the input is padded with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes specified
+        by `axes` is used.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the FFT.  If not given, the last two
+        axes are used.  A repeated index in `axes` means the transform over
+        that axis is performed multiple times.  A one-element sequence means
+        that a one-dimensional FFT is performed. Default: ``(-2, -1)``.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must not be ``None``.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for all axes (and hence only the
+        last axis can have ``s`` not equal to the shape at that axis).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or the last two axes if `axes` is not given.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length, or `axes` not given and
+        ``len(s) != 2``.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    numpy.fft : Overall view of discrete Fourier transforms, with definitions
+         and conventions used.
+    ifft2 : The inverse two-dimensional FFT.
+    fft : The one-dimensional FFT.
+    fftn : The *n*-dimensional FFT.
+    fftshift : Shifts zero-frequency terms to the center of the array.
+        For two-dimensional input, swaps first and third quadrants, and second
+        and fourth quadrants.
+
+    Notes
+    -----
+    `fft2` is just `fftn` with a different default for `axes`.
+
+    The output, analogously to `fft`, contains the term for zero frequency in
+    the low-order corner of the transformed axes, the positive frequency terms
+    in the first half of these axes, the term for the Nyquist frequency in the
+    middle of the axes and the negative frequency terms in the second half of
+    the axes, in order of decreasingly negative frequency.
+
+    See `fftn` for details and a plotting example, and `numpy.fft` for
+    definitions and conventions used.
+
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.mgrid[:5, :5][0]
+    >>> np.fft.fft2(a)
+    array([[ 50.  +0.j        ,   0.  +0.j        ,   0.  +0.j        , # may vary
+              0.  +0.j        ,   0.  +0.j        ],
+           [-12.5+17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
+              0.  +0.j        ,   0.  +0.j        ],
+           [-12.5 +4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
+              0.  +0.j        ,   0.  +0.j        ],
+           [-12.5 -4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
+              0.  +0.j        ,   0.  +0.j        ],
+           [-12.5-17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
+              0.  +0.j        ,   0.  +0.j        ]])
+
+    """
+    return _raw_fftnd(a, s, axes, fft, norm, out=out)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def ifft2(a, s=None, axes=(-2, -1), norm=None, out=None):
+    """
+    Compute the 2-dimensional inverse discrete Fourier Transform.
+
+    This function computes the inverse of the 2-dimensional discrete Fourier
+    Transform over any number of axes in an M-dimensional array by means of
+    the Fast Fourier Transform (FFT).  In other words, ``ifft2(fft2(a)) == a``
+    to within numerical accuracy.  By default, the inverse transform is
+    computed over the last two axes of the input array.
+
+    The input, analogously to `ifft`, should be ordered in the same way as is
+    returned by `fft2`, i.e. it should have the term for zero frequency
+    in the low-order corner of the two axes, the positive frequency terms in
+    the first half of these axes, the term for the Nyquist frequency in the
+    middle of the axes and the negative frequency terms in the second half of
+    both axes, in order of decreasingly negative frequency.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, can be complex.
+    s : sequence of ints, optional
+        Shape (length of each axis) of the output (``s[0]`` refers to axis 0,
+        ``s[1]`` to axis 1, etc.).  This corresponds to `n` for ``ifft(x, n)``.
+        Along each axis, if the given shape is smaller than that of the input,
+        the input is cropped. If it is larger, the input is padded with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes specified
+        by `axes` is used.  See notes for issue on `ifft` zero padding.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the FFT.  If not given, the last two
+        axes are used.  A repeated index in `axes` means the transform over
+        that axis is performed multiple times.  A one-element sequence means
+        that a one-dimensional FFT is performed. Default: ``(-2, -1)``.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must not be ``None``.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for all axes (and hence is
+        incompatible with passing in all but the trivial ``s``).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or the last two axes if `axes` is not given.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length, or `axes` not given and
+        ``len(s) != 2``.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    numpy.fft : Overall view of discrete Fourier transforms, with definitions
+         and conventions used.
+    fft2 : The forward 2-dimensional FFT, of which `ifft2` is the inverse.
+    ifftn : The inverse of the *n*-dimensional FFT.
+    fft : The one-dimensional FFT.
+    ifft : The one-dimensional inverse FFT.
+
+    Notes
+    -----
+    `ifft2` is just `ifftn` with a different default for `axes`.
+
+    See `ifftn` for details and a plotting example, and `numpy.fft` for
+    definition and conventions used.
+
+    Zero-padding, analogously with `ifft`, is performed by appending zeros to
+    the input along the specified dimension.  Although this is the common
+    approach, it might lead to surprising results.  If another form of zero
+    padding is desired, it must be performed before `ifft2` is called.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = 4 * np.eye(4)
+    >>> np.fft.ifft2(a)
+    array([[1.+0.j,  0.+0.j,  0.+0.j,  0.+0.j], # may vary
+           [0.+0.j,  0.+0.j,  0.+0.j,  1.+0.j],
+           [0.+0.j,  0.+0.j,  1.+0.j,  0.+0.j],
+           [0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j]])
+
+    """
+    return _raw_fftnd(a, s, axes, ifft, norm, out=None)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def rfftn(a, s=None, axes=None, norm=None, out=None):
+    """
+    Compute the N-dimensional discrete Fourier Transform for real input.
+
+    This function computes the N-dimensional discrete Fourier Transform over
+    any number of axes in an M-dimensional real array by means of the Fast
+    Fourier Transform (FFT).  By default, all axes are transformed, with the
+    real transform performed over the last axis, while the remaining
+    transforms are complex.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, taken to be real.
+    s : sequence of ints, optional
+        Shape (length along each transformed axis) to use from the input.
+        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
+        The final element of `s` corresponds to `n` for ``rfft(x, n)``, while
+        for the remaining axes, it corresponds to `n` for ``fft(x, n)``.
+        Along any axis, if the given shape is smaller than that of the input,
+        the input is cropped. If it is larger, the input is padded with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes specified
+        by `axes` is used.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the FFT.  If not given, the last ``len(s)``
+        axes are used, or all axes if `s` is also not specified.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must be explicitly specified too.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for all axes (and hence is
+        incompatible with passing in all but the trivial ``s``).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : complex ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or by a combination of `s` and `a`,
+        as explained in the parameters section above.
+        The length of the last axis transformed will be ``s[-1]//2+1``,
+        while the remaining transformed axes will have lengths according to
+        `s`, or unchanged from the input.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    irfftn : The inverse of `rfftn`, i.e. the inverse of the n-dimensional FFT
+         of real input.
+    fft : The one-dimensional FFT, with definitions and conventions used.
+    rfft : The one-dimensional FFT of real input.
+    fftn : The n-dimensional FFT.
+    rfft2 : The two-dimensional FFT of real input.
+
+    Notes
+    -----
+    The transform for real input is performed over the last transformation
+    axis, as by `rfft`, then the transform over the remaining axes is
+    performed as by `fftn`.  The order of the output is as for `rfft` for the
+    final transformation axis, and as for `fftn` for the remaining
+    transformation axes.
+
+    See `fft` for details, definitions and conventions used.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ones((2, 2, 2))
+    >>> np.fft.rfftn(a)
+    array([[[8.+0.j,  0.+0.j], # may vary
+            [0.+0.j,  0.+0.j]],
+           [[0.+0.j,  0.+0.j],
+            [0.+0.j,  0.+0.j]]])
+
+    >>> np.fft.rfftn(a, axes=(2, 0))
+    array([[[4.+0.j,  0.+0.j], # may vary
+            [4.+0.j,  0.+0.j]],
+           [[0.+0.j,  0.+0.j],
+            [0.+0.j,  0.+0.j]]])
+
+    """
+    a = asarray(a)
+    s, axes = _cook_nd_args(a, s, axes)
+    a = rfft(a, s[-1], axes[-1], norm, out=out)
+    for ii in range(len(axes) - 2, -1, -1):
+        a = fft(a, s[ii], axes[ii], norm, out=out)
+    return a
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def rfft2(a, s=None, axes=(-2, -1), norm=None, out=None):
+    """
+    Compute the 2-dimensional FFT of a real array.
+
+    Parameters
+    ----------
+    a : array
+        Input array, taken to be real.
+    s : sequence of ints, optional
+        Shape of the FFT.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the FFT. Default: ``(-2, -1)``.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must not be ``None``.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : complex ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for the last inverse transform.
+        incompatible with passing in all but the trivial ``s``).
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : ndarray
+        The result of the real 2-D FFT.
+
+    See Also
+    --------
+    rfftn : Compute the N-dimensional discrete Fourier Transform for real
+            input.
+
+    Notes
+    -----
+    This is really just `rfftn` with different default behavior.
+    For more details see `rfftn`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.mgrid[:5, :5][0]
+    >>> np.fft.rfft2(a)
+    array([[ 50.  +0.j        ,   0.  +0.j        ,   0.  +0.j        ],
+           [-12.5+17.20477401j,   0.  +0.j        ,   0.  +0.j        ],
+           [-12.5 +4.0614962j ,   0.  +0.j        ,   0.  +0.j        ],
+           [-12.5 -4.0614962j ,   0.  +0.j        ,   0.  +0.j        ],
+           [-12.5-17.20477401j,   0.  +0.j        ,   0.  +0.j        ]])
+    """
+    return rfftn(a, s, axes, norm, out=out)
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def irfftn(a, s=None, axes=None, norm=None, out=None):
+    """
+    Computes the inverse of `rfftn`.
+
+    This function computes the inverse of the N-dimensional discrete
+    Fourier Transform for real input over any number of axes in an
+    M-dimensional array by means of the Fast Fourier Transform (FFT).  In
+    other words, ``irfftn(rfftn(a), a.shape) == a`` to within numerical
+    accuracy. (The ``a.shape`` is necessary like ``len(a)`` is for `irfft`,
+    and for the same reason.)
+
+    The input should be ordered in the same way as is returned by `rfftn`,
+    i.e. as for `irfft` for the final transformation axis, and as for `ifftn`
+    along all the other axes.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    s : sequence of ints, optional
+        Shape (length of each transformed axis) of the output
+        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.). `s` is also the
+        number of input points used along this axis, except for the last axis,
+        where ``s[-1]//2+1`` points of the input are used.
+        Along any axis, if the shape indicated by `s` is smaller than that of
+        the input, the input is cropped.  If it is larger, the input is padded
+        with zeros.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        If `s` is not given, the shape of the input along the axes
+        specified by axes is used. Except for the last axis which is taken to
+        be ``2*(m-1)`` where ``m`` is the length of the input along that axis.
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        Axes over which to compute the inverse FFT. If not given, the last
+        `len(s)` axes are used, or all axes if `s` is also not specified.
+        Repeated indices in `axes` means that the inverse transform over that
+        axis is performed multiple times.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must be explicitly specified too.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for the last transformation.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : ndarray
+        The truncated or zero-padded input, transformed along the axes
+        indicated by `axes`, or by a combination of `s` or `a`,
+        as explained in the parameters section above.
+        The length of each transformed axis is as given by the corresponding
+        element of `s`, or the length of the input in every axis except for the
+        last one if `s` is not given.  In the final transformed axis the length
+        of the output when `s` is not given is ``2*(m-1)`` where ``m`` is the
+        length of the final transformed axis of the input.  To get an odd
+        number of output points in the final axis, `s` must be specified.
+
+    Raises
+    ------
+    ValueError
+        If `s` and `axes` have different length.
+    IndexError
+        If an element of `axes` is larger than than the number of axes of `a`.
+
+    See Also
+    --------
+    rfftn : The forward n-dimensional FFT of real input,
+            of which `ifftn` is the inverse.
+    fft : The one-dimensional FFT, with definitions and conventions used.
+    irfft : The inverse of the one-dimensional FFT of real input.
+    irfft2 : The inverse of the two-dimensional FFT of real input.
+
+    Notes
+    -----
+    See `fft` for definitions and conventions used.
+
+    See `rfft` for definitions and conventions used for real input.
+
+    The correct interpretation of the hermitian input depends on the shape of
+    the original data, as given by `s`. This is because each input shape could
+    correspond to either an odd or even length signal. By default, `irfftn`
+    assumes an even output length which puts the last entry at the Nyquist
+    frequency; aliasing with its symmetric counterpart. When performing the
+    final complex to real transform, the last value is thus treated as purely
+    real. To avoid losing information, the correct shape of the real input
+    **must** be given.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.zeros((3, 2, 2))
+    >>> a[0, 0, 0] = 3 * 2 * 2
+    >>> np.fft.irfftn(a)
+    array([[[1.,  1.],
+            [1.,  1.]],
+           [[1.,  1.],
+            [1.,  1.]],
+           [[1.,  1.],
+            [1.,  1.]]])
+
+    """
+    a = asarray(a)
+    s, axes = _cook_nd_args(a, s, axes, invreal=1)
+    for ii in range(len(axes) - 1):
+        a = ifft(a, s[ii], axes[ii], norm)
+    a = irfft(a, s[-1], axes[-1], norm, out=out)
+    return a
+
+
+@array_function_dispatch(_fftn_dispatcher)
+def irfft2(a, s=None, axes=(-2, -1), norm=None, out=None):
+    """
+    Computes the inverse of `rfft2`.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array
+    s : sequence of ints, optional
+        Shape of the real output to the inverse FFT.
+
+        .. versionchanged:: 2.0
+
+            If it is ``-1``, the whole input is used (no padding/trimming).
+
+        .. deprecated:: 2.0
+
+            If `s` is not ``None``, `axes` must not be ``None`` either.
+
+        .. deprecated:: 2.0
+
+            `s` must contain only ``int`` s, not ``None`` values. ``None``
+            values currently mean that the default value for ``n`` is used
+            in the corresponding 1-D transform, but this behaviour is
+            deprecated.
+
+    axes : sequence of ints, optional
+        The axes over which to compute the inverse fft.
+        Default: ``(-2, -1)``, the last two axes.
+
+        .. deprecated:: 2.0
+
+            If `s` is specified, the corresponding `axes` to be transformed
+            must not be ``None``.
+
+    norm : {"backward", "ortho", "forward"}, optional
+        Normalization mode (see `numpy.fft`). Default is "backward".
+        Indicates which direction of the forward/backward pair of transforms
+        is scaled and with what normalization factor.
+
+        .. versionadded:: 1.20.0
+
+            The "backward", "forward" values were added.
+
+    out : ndarray, optional
+        If provided, the result will be placed in this array. It should be
+        of the appropriate shape and dtype for the last transformation.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    out : ndarray
+        The result of the inverse real 2-D FFT.
+
+    See Also
+    --------
+    rfft2 : The forward two-dimensional FFT of real input,
+            of which `irfft2` is the inverse.
+    rfft : The one-dimensional FFT for real input.
+    irfft : The inverse of the one-dimensional FFT of real input.
+    irfftn : Compute the inverse of the N-dimensional FFT of real input.
+
+    Notes
+    -----
+    This is really `irfftn` with different defaults.
+    For more details see `irfftn`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.mgrid[:5, :5][0]
+    >>> A = np.fft.rfft2(a)
+    >>> np.fft.irfft2(A, s=a.shape)
+    array([[0., 0., 0., 0., 0.],
+           [1., 1., 1., 1., 1.],
+           [2., 2., 2., 2., 2.],
+           [3., 3., 3., 3., 3.],
+           [4., 4., 4., 4., 4.]])
+    """
+    return irfftn(a, s, axes, norm, out=None)
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.pyi b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..8dd1b43f0ff11b3441555bbeaaad6145bc64a052
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft.pyi
@@ -0,0 +1,137 @@
+from collections.abc import Sequence
+from typing import Literal as L, TypeAlias
+
+from numpy import complex128, float64
+from numpy._typing import ArrayLike, NDArray, _ArrayLikeNumber_co
+
+__all__ = [
+    "fft",
+    "ifft",
+    "rfft",
+    "irfft",
+    "hfft",
+    "ihfft",
+    "rfftn",
+    "irfftn",
+    "rfft2",
+    "irfft2",
+    "fft2",
+    "ifft2",
+    "fftn",
+    "ifftn",
+]
+
+_NormKind: TypeAlias = L["backward", "ortho", "forward"] | None
+
+def fft(
+    a: ArrayLike,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def ifft(
+    a: ArrayLike,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def rfft(
+    a: ArrayLike,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def irfft(
+    a: ArrayLike,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[float64] | None = None,
+) -> NDArray[float64]: ...
+
+# Input array must be compatible with `np.conjugate`
+def hfft(
+    a: _ArrayLikeNumber_co,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[float64] | None = None,
+) -> NDArray[float64]: ...
+
+def ihfft(
+    a: ArrayLike,
+    n: int | None = None,
+    axis: int = -1,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def fftn(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = None,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def ifftn(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = None,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def rfftn(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = None,
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def irfftn(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = None,
+    norm: _NormKind = None,
+    out: NDArray[float64] | None = None,
+) -> NDArray[float64]: ...
+
+def fft2(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = (-2, -1),
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def ifft2(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = (-2, -1),
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def rfft2(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = (-2, -1),
+    norm: _NormKind = None,
+    out: NDArray[complex128] | None = None,
+) -> NDArray[complex128]: ...
+
+def irfft2(
+    a: ArrayLike,
+    s: Sequence[int] | None = None,
+    axes: Sequence[int] | None = (-2, -1),
+    norm: _NormKind = None,
+    out: NDArray[float64] | None = None,
+) -> NDArray[float64]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft_umath.cp313-win_amd64.lib b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft_umath.cp313-win_amd64.lib
new file mode 100644
index 0000000000000000000000000000000000000000..c475d20a36e1940345accb1b0afbf5058b85a60e
Binary files /dev/null and b/python/user_packages/Python313/site-packages/numpy/fft/_pocketfft_umath.cp313-win_amd64.lib differ
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/__init__.py b/python/user_packages/Python313/site-packages/numpy/lib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e38e7e7c6e05db903d270eff6a3a67188f294dac
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/__init__.py
@@ -0,0 +1,97 @@
+"""
+``numpy.lib`` is mostly a space for implementing functions that don't
+belong in core or in another NumPy submodule with a clear purpose
+(e.g. ``random``, ``fft``, ``linalg``, ``ma``).
+
+``numpy.lib``'s private submodules contain basic functions that are used by
+other public modules and are useful to have in the main name-space.
+
+"""
+
+# Public submodules
+# Note: recfunctions is public, but not imported
+from numpy._core._multiarray_umath import add_docstring, tracemalloc_domain
+from numpy._core.function_base import add_newdoc
+
+# Private submodules
+# load module names. See https://github.com/networkx/networkx/issues/5838
+from . import (
+    _arraypad_impl,
+    _arraysetops_impl,
+    _arrayterator_impl,
+    _function_base_impl,
+    _histograms_impl,
+    _index_tricks_impl,
+    _nanfunctions_impl,
+    _npyio_impl,
+    _polynomial_impl,
+    _shape_base_impl,
+    _stride_tricks_impl,
+    _twodim_base_impl,
+    _type_check_impl,
+    _ufunclike_impl,
+    _utils_impl,
+    _version,
+    array_utils,
+    format,
+    introspect,
+    mixins,
+    npyio,
+    scimath,
+    stride_tricks,
+)
+
+# numpy.lib namespace members
+from ._arrayterator_impl import Arrayterator
+from ._version import NumpyVersion
+
+__all__ = [
+    "Arrayterator", "add_docstring", "add_newdoc", "array_utils",
+    "format", "introspect", "mixins", "NumpyVersion", "npyio", "scimath",
+    "stride_tricks", "tracemalloc_domain",
+]
+
+add_newdoc.__module__ = "numpy.lib"
+
+from numpy._pytesttester import PytestTester
+
+test = PytestTester(__name__)
+del PytestTester
+
+def __getattr__(attr):
+    # Warn for deprecated/removed aliases
+    import math
+    import warnings
+
+    if attr == "math":
+        warnings.warn(
+            "`np.lib.math` is a deprecated alias for the standard library "
+            "`math` module (Deprecated Numpy 1.25). Replace usages of "
+            "`numpy.lib.math` with `math`", DeprecationWarning, stacklevel=2)
+        return math
+    elif attr == "emath":
+        raise AttributeError(
+            "numpy.lib.emath was an alias for emath module that was removed "
+            "in NumPy 2.0. Replace usages of numpy.lib.emath with "
+            "numpy.emath.",
+            name=None
+        )
+    elif attr in (
+        "histograms", "type_check", "nanfunctions", "function_base",
+        "arraypad", "arraysetops", "ufunclike", "utils", "twodim_base",
+        "shape_base", "polynomial", "index_tricks",
+    ):
+        raise AttributeError(
+            f"numpy.lib.{attr} is now private. If you are using a public "
+            "function, it should be available in the main numpy namespace, "
+            "otherwise check the NumPy 2.0 migration guide.",
+            name=None
+        )
+    elif attr == "arrayterator":
+        raise AttributeError(
+            "numpy.lib.arrayterator submodule is now private. To access "
+            "Arrayterator class use numpy.lib.Arrayterator.",
+            name=None
+        )
+    else:
+        raise AttributeError(f"module {__name__!r} has no attribute {attr!r}")
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/lib/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..a0794c21512966a7c52621cc416067bc4e39936c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/__init__.pyi
@@ -0,0 +1,52 @@
+from numpy._core.function_base import add_newdoc
+from numpy._core.multiarray import add_docstring, tracemalloc_domain
+
+# all submodules of `lib` are accessible at runtime through `__getattr__`,
+# so we implicitly re-export them here
+from . import (
+    _array_utils_impl as _array_utils_impl,
+    _arraypad_impl as _arraypad_impl,
+    _arraysetops_impl as _arraysetops_impl,
+    _arrayterator_impl as _arrayterator_impl,
+    _datasource as _datasource,
+    _format_impl as _format_impl,
+    _function_base_impl as _function_base_impl,
+    _histograms_impl as _histograms_impl,
+    _index_tricks_impl as _index_tricks_impl,
+    _iotools as _iotools,
+    _nanfunctions_impl as _nanfunctions_impl,
+    _npyio_impl as _npyio_impl,
+    _polynomial_impl as _polynomial_impl,
+    _scimath_impl as _scimath_impl,
+    _shape_base_impl as _shape_base_impl,
+    _stride_tricks_impl as _stride_tricks_impl,
+    _twodim_base_impl as _twodim_base_impl,
+    _type_check_impl as _type_check_impl,
+    _ufunclike_impl as _ufunclike_impl,
+    _utils_impl as _utils_impl,
+    _version as _version,
+    array_utils,
+    format,
+    introspect,
+    mixins,
+    npyio,
+    scimath,
+    stride_tricks,
+)
+from ._arrayterator_impl import Arrayterator
+from ._version import NumpyVersion
+
+__all__ = [
+    "Arrayterator",
+    "add_docstring",
+    "add_newdoc",
+    "array_utils",
+    "format",
+    "introspect",
+    "mixins",
+    "NumpyVersion",
+    "npyio",
+    "scimath",
+    "stride_tricks",
+    "tracemalloc_domain",
+]
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..3fa8210a69eaff9521b79a50abff792860546a8a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.py
@@ -0,0 +1,62 @@
+"""
+Miscellaneous utils.
+"""
+from numpy._core import asarray
+from numpy._core.numeric import normalize_axis_index, normalize_axis_tuple
+from numpy._utils import set_module
+
+__all__ = ["byte_bounds", "normalize_axis_tuple", "normalize_axis_index"]
+
+
+@set_module("numpy.lib.array_utils")
+def byte_bounds(a):
+    """
+    Returns pointers to the end-points of an array.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input array. It must conform to the Python-side of the array
+        interface.
+
+    Returns
+    -------
+    (low, high) : tuple of 2 integers
+        The first integer is the first byte of the array, the second
+        integer is just past the last byte of the array.  If `a` is not
+        contiguous it will not use every byte between the (`low`, `high`)
+        values.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> I = np.eye(2, dtype='f'); I.dtype
+    dtype('float32')
+    >>> low, high = np.lib.array_utils.byte_bounds(I)
+    >>> high - low == I.size*I.itemsize
+    True
+    >>> I = np.eye(2); I.dtype
+    dtype('float64')
+    >>> low, high = np.lib.array_utils.byte_bounds(I)
+    >>> high - low == I.size*I.itemsize
+    True
+
+    """
+    ai = a.__array_interface__
+    a_data = ai['data'][0]
+    astrides = ai['strides']
+    ashape = ai['shape']
+    bytes_a = asarray(a).dtype.itemsize
+
+    a_low = a_high = a_data
+    if astrides is None:
+        # contiguous case
+        a_high += a.size * bytes_a
+    else:
+        for shape, stride in zip(ashape, astrides):
+            if stride < 0:
+                a_low += (shape - 1) * stride
+            else:
+                a_high += (shape - 1) * stride
+        a_high += bytes_a
+    return a_low, a_high
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..999594d037e3fe53cc8c18bfe1d3da04136ea84f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_array_utils_impl.pyi
@@ -0,0 +1,10 @@
+import numpy as np
+from numpy._core.numeric import normalize_axis_index, normalize_axis_tuple
+
+__all__ = ["byte_bounds", "normalize_axis_tuple", "normalize_axis_index"]
+
+# NOTE: In practice `byte_bounds` can (potentially) take any object
+# implementing the `__array_interface__` protocol. The caveat is
+# that certain keys, marked as optional in the spec, must be present for
+#  `byte_bounds`. This concerns `"strides"` and `"data"`.
+def byte_bounds(a: np.generic | np.ndarray) -> tuple[int, int]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..01516351fcc76803e0626d73ba9426b9253a3482
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.py
@@ -0,0 +1,926 @@
+"""
+The arraypad module contains a group of functions to pad values onto the edges
+of an n-dimensional array.
+
+"""
+import typing
+
+import numpy as np
+from numpy._core.overrides import array_function_dispatch
+from numpy.lib._index_tricks_impl import ndindex
+
+__all__ = ['pad']
+
+
+###############################################################################
+# Private utility functions.
+
+
+def _round_if_needed(arr, dtype):
+    """
+    Rounds arr inplace if destination dtype is integer.
+
+    Parameters
+    ----------
+    arr : ndarray
+        Input array.
+    dtype : dtype
+        The dtype of the destination array.
+    """
+    if np.issubdtype(dtype, np.integer):
+        arr.round(out=arr)
+
+
+def _slice_at_axis(sl, axis):
+    """
+    Construct tuple of slices to slice an array in the given dimension.
+
+    Parameters
+    ----------
+    sl : slice
+        The slice for the given dimension.
+    axis : int
+        The axis to which `sl` is applied. All other dimensions are left
+        "unsliced".
+
+    Returns
+    -------
+    sl : tuple of slices
+        A tuple with slices matching `shape` in length.
+
+    Examples
+    --------
+    >>> np._slice_at_axis(slice(None, 3, -1), 1)
+    (slice(None, None, None), slice(None, 3, -1), (...,))
+    """
+    return (slice(None),) * axis + (sl,) + (...,)
+
+
+def _view_roi(array, original_area_slice, axis):
+    """
+    Get a view of the current region of interest during iterative padding.
+
+    When padding multiple dimensions iteratively corner values are
+    unnecessarily overwritten multiple times. This function reduces the
+    working area for the first dimensions so that corners are excluded.
+
+    Parameters
+    ----------
+    array : ndarray
+        The array with the region of interest.
+    original_area_slice : tuple of slices
+        Denotes the area with original values of the unpadded array.
+    axis : int
+        The currently padded dimension assuming that `axis` is padded before
+        `axis` + 1.
+
+    Returns
+    -------
+    roi : ndarray
+        The region of interest of the original `array`.
+    """
+    axis += 1
+    sl = (slice(None),) * axis + original_area_slice[axis:]
+    return array[sl]
+
+
+def _pad_simple(array, pad_width, fill_value=None):
+    """
+    Pad array on all sides with either a single value or undefined values.
+
+    Parameters
+    ----------
+    array : ndarray
+        Array to grow.
+    pad_width : sequence of tuple[int, int]
+        Pad width on both sides for each dimension in `arr`.
+    fill_value : scalar, optional
+        If provided the padded area is filled with this value, otherwise
+        the pad area left undefined.
+
+    Returns
+    -------
+    padded : ndarray
+        The padded array with the same dtype as`array`. Its order will default
+        to C-style if `array` is not F-contiguous.
+    original_area_slice : tuple
+        A tuple of slices pointing to the area of the original array.
+    """
+    # Allocate grown array
+    new_shape = tuple(
+        left + size + right
+        for size, (left, right) in zip(array.shape, pad_width)
+    )
+    order = 'F' if array.flags.fnc else 'C'  # Fortran and not also C-order
+    padded = np.empty(new_shape, dtype=array.dtype, order=order)
+
+    if fill_value is not None:
+        padded.fill(fill_value)
+
+    # Copy old array into correct space
+    original_area_slice = tuple(
+        slice(left, left + size)
+        for size, (left, right) in zip(array.shape, pad_width)
+    )
+    padded[original_area_slice] = array
+
+    return padded, original_area_slice
+
+
+def _set_pad_area(padded, axis, width_pair, value_pair):
+    """
+    Set empty-padded area in given dimension.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Array with the pad area which is modified inplace.
+    axis : int
+        Dimension with the pad area to set.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+    value_pair : tuple of scalars or ndarrays
+        Values inserted into the pad area on each side. It must match or be
+        broadcastable to the shape of `arr`.
+    """
+    left_slice = _slice_at_axis(slice(None, width_pair[0]), axis)
+    padded[left_slice] = value_pair[0]
+
+    right_slice = _slice_at_axis(
+        slice(padded.shape[axis] - width_pair[1], None), axis)
+    padded[right_slice] = value_pair[1]
+
+
+def _get_edges(padded, axis, width_pair):
+    """
+    Retrieve edge values from empty-padded array in given dimension.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Empty-padded array.
+    axis : int
+        Dimension in which the edges are considered.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+
+    Returns
+    -------
+    left_edge, right_edge : ndarray
+        Edge values of the valid area in `padded` in the given dimension. Its
+        shape will always match `padded` except for the dimension given by
+        `axis` which will have a length of 1.
+    """
+    left_index = width_pair[0]
+    left_slice = _slice_at_axis(slice(left_index, left_index + 1), axis)
+    left_edge = padded[left_slice]
+
+    right_index = padded.shape[axis] - width_pair[1]
+    right_slice = _slice_at_axis(slice(right_index - 1, right_index), axis)
+    right_edge = padded[right_slice]
+
+    return left_edge, right_edge
+
+
+def _get_linear_ramps(padded, axis, width_pair, end_value_pair):
+    """
+    Construct linear ramps for empty-padded array in given dimension.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Empty-padded array.
+    axis : int
+        Dimension in which the ramps are constructed.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+    end_value_pair : (scalar, scalar)
+        End values for the linear ramps which form the edge of the fully padded
+        array. These values are included in the linear ramps.
+
+    Returns
+    -------
+    left_ramp, right_ramp : ndarray
+        Linear ramps to set on both sides of `padded`.
+    """
+    edge_pair = _get_edges(padded, axis, width_pair)
+
+    left_ramp, right_ramp = (
+        np.linspace(
+            start=end_value,
+            stop=edge.squeeze(axis),  # Dimension is replaced by linspace
+            num=width,
+            endpoint=False,
+            dtype=padded.dtype,
+            axis=axis
+        )
+        for end_value, edge, width in zip(
+            end_value_pair, edge_pair, width_pair
+        )
+    )
+
+    # Reverse linear space in appropriate dimension
+    right_ramp = right_ramp[_slice_at_axis(slice(None, None, -1), axis)]
+
+    return left_ramp, right_ramp
+
+
+def _get_stats(padded, axis, width_pair, length_pair, stat_func):
+    """
+    Calculate statistic for the empty-padded array in given dimension.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Empty-padded array.
+    axis : int
+        Dimension in which the statistic is calculated.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+    length_pair : 2-element sequence of None or int
+        Gives the number of values in valid area from each side that is
+        taken into account when calculating the statistic. If None the entire
+        valid area in `padded` is considered.
+    stat_func : function
+        Function to compute statistic. The expected signature is
+        ``stat_func(x: ndarray, axis: int, keepdims: bool) -> ndarray``.
+
+    Returns
+    -------
+    left_stat, right_stat : ndarray
+        Calculated statistic for both sides of `padded`.
+    """
+    # Calculate indices of the edges of the area with original values
+    left_index = width_pair[0]
+    right_index = padded.shape[axis] - width_pair[1]
+    # as well as its length
+    max_length = right_index - left_index
+
+    # Limit stat_lengths to max_length
+    left_length, right_length = length_pair
+    if left_length is None or max_length < left_length:
+        left_length = max_length
+    if right_length is None or max_length < right_length:
+        right_length = max_length
+
+    if (left_length == 0 or right_length == 0) \
+            and stat_func in {np.amax, np.amin}:
+        # amax and amin can't operate on an empty array,
+        # raise a more descriptive warning here instead of the default one
+        raise ValueError("stat_length of 0 yields no value for padding")
+
+    # Calculate statistic for the left side
+    left_slice = _slice_at_axis(
+        slice(left_index, left_index + left_length), axis)
+    left_chunk = padded[left_slice]
+    left_stat = stat_func(left_chunk, axis=axis, keepdims=True)
+    _round_if_needed(left_stat, padded.dtype)
+
+    if left_length == right_length == max_length:
+        # return early as right_stat must be identical to left_stat
+        return left_stat, left_stat
+
+    # Calculate statistic for the right side
+    right_slice = _slice_at_axis(
+        slice(right_index - right_length, right_index), axis)
+    right_chunk = padded[right_slice]
+    right_stat = stat_func(right_chunk, axis=axis, keepdims=True)
+    _round_if_needed(right_stat, padded.dtype)
+
+    return left_stat, right_stat
+
+
+def _set_reflect_both(padded, axis, width_pair, method,
+                      original_period, include_edge=False):
+    """
+    Pad `axis` of `arr` with reflection.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Input array of arbitrary shape.
+    axis : int
+        Axis along which to pad `arr`.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+    method : str
+        Controls method of reflection; options are 'even' or 'odd'.
+    original_period : int
+        Original length of data on `axis` of `arr`.
+    include_edge : bool
+        If true, edge value is included in reflection, otherwise the edge
+        value forms the symmetric axis to the reflection.
+
+    Returns
+    -------
+    pad_amt : tuple of ints, length 2
+        New index positions of padding to do along the `axis`. If these are
+        both 0, padding is done in this dimension.
+    """
+    left_pad, right_pad = width_pair
+    old_length = padded.shape[axis] - right_pad - left_pad
+
+    if include_edge:
+        # Avoid wrapping with only a subset of the original area
+        # by ensuring period can only be a multiple of the original
+        # area's length.
+        old_length = old_length // original_period * original_period
+        # Edge is included, we need to offset the pad amount by 1
+        edge_offset = 1
+    else:
+        # Avoid wrapping with only a subset of the original area
+        # by ensuring period can only be a multiple of the original
+        # area's length.
+        old_length = ((old_length - 1) // (original_period - 1)
+            * (original_period - 1) + 1)
+        edge_offset = 0  # Edge is not included, no need to offset pad amount
+        old_length -= 1  # but must be omitted from the chunk
+
+    if left_pad > 0:
+        # Pad with reflected values on left side:
+        # First limit chunk size which can't be larger than pad area
+        chunk_length = min(old_length, left_pad)
+        # Slice right to left, stop on or next to edge, start relative to stop
+        stop = left_pad - edge_offset
+        start = stop + chunk_length
+        left_slice = _slice_at_axis(slice(start, stop, -1), axis)
+        left_chunk = padded[left_slice]
+
+        if method == "odd":
+            # Negate chunk and align with edge
+            edge_slice = _slice_at_axis(slice(left_pad, left_pad + 1), axis)
+            left_chunk = 2 * padded[edge_slice] - left_chunk
+
+        # Insert chunk into padded area
+        start = left_pad - chunk_length
+        stop = left_pad
+        pad_area = _slice_at_axis(slice(start, stop), axis)
+        padded[pad_area] = left_chunk
+        # Adjust pointer to left edge for next iteration
+        left_pad -= chunk_length
+
+    if right_pad > 0:
+        # Pad with reflected values on right side:
+        # First limit chunk size which can't be larger than pad area
+        chunk_length = min(old_length, right_pad)
+        # Slice right to left, start on or next to edge, stop relative to start
+        start = -right_pad + edge_offset - 2
+        stop = start - chunk_length
+        right_slice = _slice_at_axis(slice(start, stop, -1), axis)
+        right_chunk = padded[right_slice]
+
+        if method == "odd":
+            # Negate chunk and align with edge
+            edge_slice = _slice_at_axis(
+                slice(-right_pad - 1, -right_pad), axis)
+            right_chunk = 2 * padded[edge_slice] - right_chunk
+
+        # Insert chunk into padded area
+        start = padded.shape[axis] - right_pad
+        stop = start + chunk_length
+        pad_area = _slice_at_axis(slice(start, stop), axis)
+        padded[pad_area] = right_chunk
+        # Adjust pointer to right edge for next iteration
+        right_pad -= chunk_length
+
+    return left_pad, right_pad
+
+
+def _set_wrap_both(padded, axis, width_pair, original_period):
+    """
+    Pad `axis` of `arr` with wrapped values.
+
+    Parameters
+    ----------
+    padded : ndarray
+        Input array of arbitrary shape.
+    axis : int
+        Axis along which to pad `arr`.
+    width_pair : (int, int)
+        Pair of widths that mark the pad area on both sides in the given
+        dimension.
+    original_period : int
+        Original length of data on `axis` of `arr`.
+
+    Returns
+    -------
+    pad_amt : tuple of ints, length 2
+        New index positions of padding to do along the `axis`. If these are
+        both 0, padding is done in this dimension.
+    """
+    left_pad, right_pad = width_pair
+    period = padded.shape[axis] - right_pad - left_pad
+    # Avoid wrapping with only a subset of the original area by ensuring period
+    # can only be a multiple of the original area's length.
+    period = period // original_period * original_period
+
+    # If the current dimension of `arr` doesn't contain enough valid values
+    # (not part of the undefined pad area) we need to pad multiple times.
+    # Each time the pad area shrinks on both sides which is communicated with
+    # these variables.
+    new_left_pad = 0
+    new_right_pad = 0
+
+    if left_pad > 0:
+        # Pad with wrapped values on left side
+        # First slice chunk from left side of the non-pad area.
+        # Use min(period, left_pad) to ensure that chunk is not larger than
+        # pad area.
+        slice_end = left_pad + period
+        slice_start = slice_end - min(period, left_pad)
+        right_slice = _slice_at_axis(slice(slice_start, slice_end), axis)
+        right_chunk = padded[right_slice]
+
+        if left_pad > period:
+            # Chunk is smaller than pad area
+            pad_area = _slice_at_axis(slice(left_pad - period, left_pad), axis)
+            new_left_pad = left_pad - period
+        else:
+            # Chunk matches pad area
+            pad_area = _slice_at_axis(slice(None, left_pad), axis)
+        padded[pad_area] = right_chunk
+
+    if right_pad > 0:
+        # Pad with wrapped values on right side
+        # First slice chunk from right side of the non-pad area.
+        # Use min(period, right_pad) to ensure that chunk is not larger than
+        # pad area.
+        slice_start = -right_pad - period
+        slice_end = slice_start + min(period, right_pad)
+        left_slice = _slice_at_axis(slice(slice_start, slice_end), axis)
+        left_chunk = padded[left_slice]
+
+        if right_pad > period:
+            # Chunk is smaller than pad area
+            pad_area = _slice_at_axis(
+                slice(-right_pad, -right_pad + period), axis)
+            new_right_pad = right_pad - period
+        else:
+            # Chunk matches pad area
+            pad_area = _slice_at_axis(slice(-right_pad, None), axis)
+        padded[pad_area] = left_chunk
+
+    return new_left_pad, new_right_pad
+
+
+def _as_pairs(x, ndim, as_index=False):
+    """
+    Broadcast `x` to an array with the shape (`ndim`, 2).
+
+    A helper function for `pad` that prepares and validates arguments like
+    `pad_width` for iteration in pairs.
+
+    Parameters
+    ----------
+    x : {None, scalar, array-like}
+        The object to broadcast to the shape (`ndim`, 2).
+    ndim : int
+        Number of pairs the broadcasted `x` will have.
+    as_index : bool, optional
+        If `x` is not None, try to round each element of `x` to an integer
+        (dtype `np.intp`) and ensure every element is positive.
+
+    Returns
+    -------
+    pairs : nested iterables, shape (`ndim`, 2)
+        The broadcasted version of `x`.
+
+    Raises
+    ------
+    ValueError
+        If `as_index` is True and `x` contains negative elements.
+        Or if `x` is not broadcastable to the shape (`ndim`, 2).
+    """
+    if x is None:
+        # Pass through None as a special case, otherwise np.round(x) fails
+        # with an AttributeError
+        return ((None, None),) * ndim
+
+    x = np.array(x)
+    if as_index:
+        x = np.round(x).astype(np.intp, copy=False)
+
+    if x.ndim < 3:
+        # Optimization: Possibly use faster paths for cases where `x` has
+        # only 1 or 2 elements. `np.broadcast_to` could handle these as well
+        # but is currently slower
+
+        if x.size == 1:
+            # x was supplied as a single value
+            x = x.ravel()  # Ensure x[0] works for x.ndim == 0, 1, 2
+            if as_index and x < 0:
+                raise ValueError("index can't contain negative values")
+            return ((x[0], x[0]),) * ndim
+
+        if x.size == 2 and x.shape != (2, 1):
+            # x was supplied with a single value for each side
+            # but except case when each dimension has a single value
+            # which should be broadcasted to a pair,
+            # e.g. [[1], [2]] -> [[1, 1], [2, 2]] not [[1, 2], [1, 2]]
+            x = x.ravel()  # Ensure x[0], x[1] works
+            if as_index and (x[0] < 0 or x[1] < 0):
+                raise ValueError("index can't contain negative values")
+            return ((x[0], x[1]),) * ndim
+
+    if as_index and x.min() < 0:
+        raise ValueError("index can't contain negative values")
+
+    # Converting the array with `tolist` seems to improve performance
+    # when iterating and indexing the result (see usage in `pad`)
+    return np.broadcast_to(x, (ndim, 2)).tolist()
+
+
+def _pad_dispatcher(array, pad_width, mode=None, **kwargs):
+    return (array,)
+
+
+###############################################################################
+# Public functions
+
+
+@array_function_dispatch(_pad_dispatcher, module='numpy')
+def pad(array, pad_width, mode='constant', **kwargs):
+    """
+    Pad an array.
+
+    Parameters
+    ----------
+    array : array_like of rank N
+        The array to pad.
+    pad_width : {sequence, array_like, int, dict}
+        Number of values padded to the edges of each axis.
+        ``((before_1, after_1), ... (before_N, after_N))`` unique pad widths
+        for each axis.
+        ``(before, after)`` or ``((before, after),)`` yields same before
+        and after pad for each axis.
+        ``(pad,)`` or ``int`` is a shortcut for before = after = pad width
+        for all axes.
+        If a ``dict``, each key is an axis and its corresponding value is an ``int`` or
+        ``int`` pair describing the padding ``(before, after)`` or ``pad`` width for
+        that axis.
+    mode : str or function, optional
+        One of the following string values or a user supplied function.
+
+        'constant' (default)
+            Pads with a constant value.
+        'edge'
+            Pads with the edge values of array.
+        'linear_ramp'
+            Pads with the linear ramp between end_value and the
+            array edge value.
+        'maximum'
+            Pads with the maximum value of all or part of the
+            vector along each axis.
+        'mean'
+            Pads with the mean value of all or part of the
+            vector along each axis.
+        'median'
+            Pads with the median value of all or part of the
+            vector along each axis.
+        'minimum'
+            Pads with the minimum value of all or part of the
+            vector along each axis.
+        'reflect'
+            Pads with the reflection of the vector mirrored on
+            the first and last values of the vector along each
+            axis.
+        'symmetric'
+            Pads with the reflection of the vector mirrored
+            along the edge of the array.
+        'wrap'
+            Pads with the wrap of the vector along the axis.
+            The first values are used to pad the end and the
+            end values are used to pad the beginning.
+        'empty'
+            Pads with undefined values.
+
+        <function>
+            Padding function, see Notes.
+    stat_length : sequence or int, optional
+        Used in 'maximum', 'mean', 'median', and 'minimum'.  Number of
+        values at edge of each axis used to calculate the statistic value.
+
+        ``((before_1, after_1), ... (before_N, after_N))`` unique statistic
+        lengths for each axis.
+
+        ``(before, after)`` or ``((before, after),)`` yields same before
+        and after statistic lengths for each axis.
+
+        ``(stat_length,)`` or ``int`` is a shortcut for
+        ``before = after = statistic`` length for all axes.
+
+        Default is ``None``, to use the entire axis.
+    constant_values : sequence or scalar, optional
+        Used in 'constant'.  The values to set the padded values for each
+        axis.
+
+        ``((before_1, after_1), ... (before_N, after_N))`` unique pad constants
+        for each axis.
+
+        ``(before, after)`` or ``((before, after),)`` yields same before
+        and after constants for each axis.
+
+        ``(constant,)`` or ``constant`` is a shortcut for
+        ``before = after = constant`` for all axes.
+
+        Default is 0.
+    end_values : sequence or scalar, optional
+        Used in 'linear_ramp'.  The values used for the ending value of the
+        linear_ramp and that will form the edge of the padded array.
+
+        ``((before_1, after_1), ... (before_N, after_N))`` unique end values
+        for each axis.
+
+        ``(before, after)`` or ``((before, after),)`` yields same before
+        and after end values for each axis.
+
+        ``(constant,)`` or ``constant`` is a shortcut for
+        ``before = after = constant`` for all axes.
+
+        Default is 0.
+    reflect_type : {'even', 'odd'}, optional
+        Used in 'reflect', and 'symmetric'.  The 'even' style is the
+        default with an unaltered reflection around the edge value.  For
+        the 'odd' style, the extended part of the array is created by
+        subtracting the reflected values from two times the edge value.
+
+    Returns
+    -------
+    pad : ndarray
+        Padded array of rank equal to `array` with shape increased
+        according to `pad_width`.
+
+    Notes
+    -----
+    For an array with rank greater than 1, some of the padding of later
+    axes is calculated from padding of previous axes.  This is easiest to
+    think about with a rank 2 array where the corners of the padded array
+    are calculated by using padded values from the first axis.
+
+    The padding function, if used, should modify a rank 1 array in-place. It
+    has the following signature::
+
+        padding_func(vector, iaxis_pad_width, iaxis, kwargs)
+
+    where
+
+    vector : ndarray
+        A rank 1 array already padded with zeros.  Padded values are
+        vector[:iaxis_pad_width[0]] and vector[-iaxis_pad_width[1]:].
+    iaxis_pad_width : tuple
+        A 2-tuple of ints, iaxis_pad_width[0] represents the number of
+        values padded at the beginning of vector where
+        iaxis_pad_width[1] represents the number of values padded at
+        the end of vector.
+    iaxis : int
+        The axis currently being calculated.
+    kwargs : dict
+        Any keyword arguments the function requires.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = [1, 2, 3, 4, 5]
+    >>> np.pad(a, (2, 3), 'constant', constant_values=(4, 6))
+    array([4, 4, 1, ..., 6, 6, 6])
+
+    >>> np.pad(a, (2, 3), 'edge')
+    array([1, 1, 1, ..., 5, 5, 5])
+
+    >>> np.pad(a, (2, 3), 'linear_ramp', end_values=(5, -4))
+    array([ 5,  3,  1,  2,  3,  4,  5,  2, -1, -4])
+
+    >>> np.pad(a, (2,), 'maximum')
+    array([5, 5, 1, 2, 3, 4, 5, 5, 5])
+
+    >>> np.pad(a, (2,), 'mean')
+    array([3, 3, 1, 2, 3, 4, 5, 3, 3])
+
+    >>> np.pad(a, (2,), 'median')
+    array([3, 3, 1, 2, 3, 4, 5, 3, 3])
+
+    >>> a = [[1, 2], [3, 4]]
+    >>> np.pad(a, ((3, 2), (2, 3)), 'minimum')
+    array([[1, 1, 1, 2, 1, 1, 1],
+           [1, 1, 1, 2, 1, 1, 1],
+           [1, 1, 1, 2, 1, 1, 1],
+           [1, 1, 1, 2, 1, 1, 1],
+           [3, 3, 3, 4, 3, 3, 3],
+           [1, 1, 1, 2, 1, 1, 1],
+           [1, 1, 1, 2, 1, 1, 1]])
+
+    >>> a = [1, 2, 3, 4, 5]
+    >>> np.pad(a, (2, 3), 'reflect')
+    array([3, 2, 1, 2, 3, 4, 5, 4, 3, 2])
+
+    >>> np.pad(a, (2, 3), 'reflect', reflect_type='odd')
+    array([-1,  0,  1,  2,  3,  4,  5,  6,  7,  8])
+
+    >>> np.pad(a, (2, 3), 'symmetric')
+    array([2, 1, 1, 2, 3, 4, 5, 5, 4, 3])
+
+    >>> np.pad(a, (2, 3), 'symmetric', reflect_type='odd')
+    array([0, 1, 1, 2, 3, 4, 5, 5, 6, 7])
+
+    >>> np.pad(a, (2, 3), 'wrap')
+    array([4, 5, 1, 2, 3, 4, 5, 1, 2, 3])
+
+    >>> def pad_with(vector, pad_width, iaxis, kwargs):
+    ...     pad_value = kwargs.get('padder', 10)
+    ...     vector[:pad_width[0]] = pad_value
+    ...     vector[-pad_width[1]:] = pad_value
+    >>> a = np.arange(6)
+    >>> a = a.reshape((2, 3))
+    >>> np.pad(a, 2, pad_with)
+    array([[10, 10, 10, 10, 10, 10, 10],
+           [10, 10, 10, 10, 10, 10, 10],
+           [10, 10,  0,  1,  2, 10, 10],
+           [10, 10,  3,  4,  5, 10, 10],
+           [10, 10, 10, 10, 10, 10, 10],
+           [10, 10, 10, 10, 10, 10, 10]])
+    >>> np.pad(a, 2, pad_with, padder=100)
+    array([[100, 100, 100, 100, 100, 100, 100],
+           [100, 100, 100, 100, 100, 100, 100],
+           [100, 100,   0,   1,   2, 100, 100],
+           [100, 100,   3,   4,   5, 100, 100],
+           [100, 100, 100, 100, 100, 100, 100],
+           [100, 100, 100, 100, 100, 100, 100]])
+
+    >>> a = np.arange(1, 7).reshape(2, 3)
+    >>> np.pad(a, {1: (1, 2)})
+    array([[0, 1, 2, 3, 0, 0],
+           [0, 4, 5, 6, 0, 0]])
+    >>> np.pad(a, {-1: 2})
+    array([[0, 0, 1, 2, 3, 0, 0],
+           [0, 0, 4, 5, 6, 0, 0]])
+    >>> np.pad(a, {0: (3, 0)})
+    array([[0, 0, 0],
+           [0, 0, 0],
+           [0, 0, 0],
+           [1, 2, 3],
+           [4, 5, 6]])
+    >>> np.pad(a, {0: (3, 0), 1: 2})
+    array([[0, 0, 0, 0, 0, 0, 0],
+           [0, 0, 0, 0, 0, 0, 0],
+           [0, 0, 0, 0, 0, 0, 0],
+           [0, 0, 1, 2, 3, 0, 0],
+           [0, 0, 4, 5, 6, 0, 0]])
+    """
+    array = np.asarray(array)
+    if isinstance(pad_width, dict):
+        seq = [(0, 0)] * array.ndim
+        for axis, width in pad_width.items():
+            match width:
+                case int(both):
+                    seq[axis] = both, both
+                case tuple((int(before), int(after))):
+                    seq[axis] = before, after
+                case _ as invalid:
+                    typing.assert_never(invalid)
+        pad_width = seq
+    pad_width = np.asarray(pad_width)
+
+    if not pad_width.dtype.kind == 'i':
+        raise TypeError('`pad_width` must be of integral type.')
+
+    # Broadcast to shape (array.ndim, 2)
+    pad_width = _as_pairs(pad_width, array.ndim, as_index=True)
+
+    if callable(mode):
+        # Old behavior: Use user-supplied function with np.apply_along_axis
+        function = mode
+        # Create a new zero padded array
+        padded, _ = _pad_simple(array, pad_width, fill_value=0)
+        # And apply along each axis
+
+        for axis in range(padded.ndim):
+            # Iterate using ndindex as in apply_along_axis, but assuming that
+            # function operates inplace on the padded array.
+
+            # view with the iteration axis at the end
+            view = np.moveaxis(padded, axis, -1)
+
+            # compute indices for the iteration axes, and append a trailing
+            # ellipsis to prevent 0d arrays decaying to scalars (gh-8642)
+            inds = ndindex(view.shape[:-1])
+            inds = (ind + (Ellipsis,) for ind in inds)
+            for ind in inds:
+                function(view[ind], pad_width[axis], axis, kwargs)
+
+        return padded
+
+    # Make sure that no unsupported keywords were passed for the current mode
+    allowed_kwargs = {
+        'empty': [], 'edge': [], 'wrap': [],
+        'constant': ['constant_values'],
+        'linear_ramp': ['end_values'],
+        'maximum': ['stat_length'],
+        'mean': ['stat_length'],
+        'median': ['stat_length'],
+        'minimum': ['stat_length'],
+        'reflect': ['reflect_type'],
+        'symmetric': ['reflect_type'],
+    }
+    try:
+        unsupported_kwargs = set(kwargs) - set(allowed_kwargs[mode])
+    except KeyError:
+        raise ValueError(f"mode '{mode}' is not supported") from None
+    if unsupported_kwargs:
+        raise ValueError("unsupported keyword arguments for mode "
+                         f"'{mode}': {unsupported_kwargs}")
+
+    stat_functions = {"maximum": np.amax, "minimum": np.amin,
+                      "mean": np.mean, "median": np.median}
+
+    # Create array with final shape and original values
+    # (padded area is undefined)
+    padded, original_area_slice = _pad_simple(array, pad_width)
+    # And prepare iteration over all dimensions
+    # (zipping may be more readable than using enumerate)
+    axes = range(padded.ndim)
+
+    if mode == "constant":
+        values = kwargs.get("constant_values", 0)
+        values = _as_pairs(values, padded.ndim)
+        for axis, width_pair, value_pair in zip(axes, pad_width, values):
+            roi = _view_roi(padded, original_area_slice, axis)
+            _set_pad_area(roi, axis, width_pair, value_pair)
+
+    elif mode == "empty":
+        pass  # Do nothing as _pad_simple already returned the correct result
+
+    elif array.size == 0:
+        # Only modes "constant" and "empty" can extend empty axes, all other
+        # modes depend on `array` not being empty
+        # -> ensure every empty axis is only "padded with 0"
+        for axis, width_pair in zip(axes, pad_width):
+            if array.shape[axis] == 0 and any(width_pair):
+                raise ValueError(
+                    f"can't extend empty axis {axis} using modes other than "
+                    "'constant' or 'empty'"
+                )
+        # passed, don't need to do anything more as _pad_simple already
+        # returned the correct result
+
+    elif mode == "edge":
+        for axis, width_pair in zip(axes, pad_width):
+            roi = _view_roi(padded, original_area_slice, axis)
+            edge_pair = _get_edges(roi, axis, width_pair)
+            _set_pad_area(roi, axis, width_pair, edge_pair)
+
+    elif mode == "linear_ramp":
+        end_values = kwargs.get("end_values", 0)
+        end_values = _as_pairs(end_values, padded.ndim)
+        for axis, width_pair, value_pair in zip(axes, pad_width, end_values):
+            roi = _view_roi(padded, original_area_slice, axis)
+            ramp_pair = _get_linear_ramps(roi, axis, width_pair, value_pair)
+            _set_pad_area(roi, axis, width_pair, ramp_pair)
+
+    elif mode in stat_functions:
+        func = stat_functions[mode]
+        length = kwargs.get("stat_length")
+        length = _as_pairs(length, padded.ndim, as_index=True)
+        for axis, width_pair, length_pair in zip(axes, pad_width, length):
+            roi = _view_roi(padded, original_area_slice, axis)
+            stat_pair = _get_stats(roi, axis, width_pair, length_pair, func)
+            _set_pad_area(roi, axis, width_pair, stat_pair)
+
+    elif mode in {"reflect", "symmetric"}:
+        method = kwargs.get("reflect_type", "even")
+        include_edge = mode == "symmetric"
+        for axis, (left_index, right_index) in zip(axes, pad_width):
+            if array.shape[axis] == 1 and (left_index > 0 or right_index > 0):
+                # Extending singleton dimension for 'reflect' is legacy
+                # behavior; it really should raise an error.
+                edge_pair = _get_edges(padded, axis, (left_index, right_index))
+                _set_pad_area(
+                    padded, axis, (left_index, right_index), edge_pair)
+                continue
+
+            roi = _view_roi(padded, original_area_slice, axis)
+            while left_index > 0 or right_index > 0:
+                # Iteratively pad until dimension is filled with reflected
+                # values. This is necessary if the pad area is larger than
+                # the length of the original values in the current dimension.
+                left_index, right_index = _set_reflect_both(
+                    roi, axis, (left_index, right_index),
+                    method, array.shape[axis], include_edge
+                )
+
+    elif mode == "wrap":
+        for axis, (left_index, right_index) in zip(axes, pad_width):
+            roi = _view_roi(padded, original_area_slice, axis)
+            original_period = padded.shape[axis] - right_index - left_index
+            while left_index > 0 or right_index > 0:
+                # Iteratively pad until dimension is filled with wrapped
+                # values. This is necessary if the pad area is larger than
+                # the length of the original values in the current dimension.
+                left_index, right_index = _set_wrap_both(
+                    roi, axis, (left_index, right_index), original_period)
+
+    return padded
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..1e91aa17916d292ab441601744168f902d3b85d3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arraypad_impl.pyi
@@ -0,0 +1,88 @@
+from typing import (
+    Any,
+    Literal as L,
+    Protocol,
+    TypeAlias,
+    TypeVar,
+    overload,
+    type_check_only,
+)
+
+from numpy import generic
+from numpy._typing import ArrayLike, NDArray, _ArrayLike, _ArrayLikeInt
+
+__all__ = ["pad"]
+
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+
+@type_check_only
+class _ModeFunc(Protocol):
+    def __call__(
+        self,
+        vector: NDArray[Any],
+        iaxis_pad_width: tuple[int, int],
+        iaxis: int,
+        kwargs: dict[str, Any],
+        /,
+    ) -> None: ...
+
+_ModeKind: TypeAlias = L[
+    "constant",
+    "edge",
+    "linear_ramp",
+    "maximum",
+    "mean",
+    "median",
+    "minimum",
+    "reflect",
+    "symmetric",
+    "wrap",
+    "empty",
+]
+
+# TODO: In practice each keyword argument is exclusive to one or more
+# specific modes. Consider adding more overloads to express this in the future.
+
+_PadWidth: TypeAlias = (
+    _ArrayLikeInt
+    | dict[int, int]
+    | dict[int, tuple[int, int]]
+    | dict[int, int | tuple[int, int]]
+)
+# Expand `**kwargs` into explicit keyword-only arguments
+@overload
+def pad(
+    array: _ArrayLike[_ScalarT],
+    pad_width: _PadWidth,
+    mode: _ModeKind = "constant",
+    *,
+    stat_length: _ArrayLikeInt | None = None,
+    constant_values: ArrayLike = 0,
+    end_values: ArrayLike = 0,
+    reflect_type: L["odd", "even"] = "even",
+) -> NDArray[_ScalarT]: ...
+@overload
+def pad(
+    array: ArrayLike,
+    pad_width: _PadWidth,
+    mode: _ModeKind = "constant",
+    *,
+    stat_length: _ArrayLikeInt | None = None,
+    constant_values: ArrayLike = 0,
+    end_values: ArrayLike = 0,
+    reflect_type: L["odd", "even"] = "even",
+) -> NDArray[Any]: ...
+@overload
+def pad(
+    array: _ArrayLike[_ScalarT],
+    pad_width: _PadWidth,
+    mode: _ModeFunc,
+    **kwargs: Any,
+) -> NDArray[_ScalarT]: ...
+@overload
+def pad(
+    array: ArrayLike,
+    pad_width: _PadWidth,
+    mode: _ModeFunc,
+    **kwargs: Any,
+) -> NDArray[Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a9d14675f7cffd838309dbcaaed6b336df69c3d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.py
@@ -0,0 +1,1158 @@
+"""
+Set operations for arrays based on sorting.
+
+Notes
+-----
+
+For floating point arrays, inaccurate results may appear due to usual round-off
+and floating point comparison issues.
+
+Speed could be gained in some operations by an implementation of
+`numpy.sort`, that can provide directly the permutation vectors, thus avoiding
+calls to `numpy.argsort`.
+
+Original author: Robert Cimrman
+
+"""
+import functools
+from typing import NamedTuple
+
+import numpy as np
+from numpy._core import overrides
+from numpy._core._multiarray_umath import _array_converter, _unique_hash
+from numpy.lib.array_utils import normalize_axis_index
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+__all__ = [
+    "ediff1d", "intersect1d", "isin", "setdiff1d", "setxor1d",
+    "union1d", "unique", "unique_all", "unique_counts", "unique_inverse",
+    "unique_values"
+]
+
+
+def _ediff1d_dispatcher(ary, to_end=None, to_begin=None):
+    return (ary, to_end, to_begin)
+
+
+@array_function_dispatch(_ediff1d_dispatcher)
+def ediff1d(ary, to_end=None, to_begin=None):
+    """
+    The differences between consecutive elements of an array.
+
+    Parameters
+    ----------
+    ary : array_like
+        If necessary, will be flattened before the differences are taken.
+    to_end : array_like, optional
+        Number(s) to append at the end of the returned differences.
+    to_begin : array_like, optional
+        Number(s) to prepend at the beginning of the returned differences.
+
+    Returns
+    -------
+    ediff1d : ndarray
+        The differences. Loosely, this is ``ary.flat[1:] - ary.flat[:-1]``.
+
+    See Also
+    --------
+    diff, gradient
+
+    Notes
+    -----
+    When applied to masked arrays, this function drops the mask information
+    if the `to_begin` and/or `to_end` parameters are used.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([1, 2, 4, 7, 0])
+    >>> np.ediff1d(x)
+    array([ 1,  2,  3, -7])
+
+    >>> np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99]))
+    array([-99,   1,   2, ...,  -7,  88,  99])
+
+    The returned array is always 1D.
+
+    >>> y = [[1, 2, 4], [1, 6, 24]]
+    >>> np.ediff1d(y)
+    array([ 1,  2, -3,  5, 18])
+
+    """
+    conv = _array_converter(ary)
+    # Convert to (any) array and ravel:
+    ary = conv[0].ravel()
+
+    # enforce that the dtype of `ary` is used for the output
+    dtype_req = ary.dtype
+
+    # fast track default case
+    if to_begin is None and to_end is None:
+        return ary[1:] - ary[:-1]
+
+    if to_begin is None:
+        l_begin = 0
+    else:
+        to_begin = np.asanyarray(to_begin)
+        if not np.can_cast(to_begin, dtype_req, casting="same_kind"):
+            raise TypeError("dtype of `to_begin` must be compatible "
+                            "with input `ary` under the `same_kind` rule.")
+
+        to_begin = to_begin.ravel()
+        l_begin = len(to_begin)
+
+    if to_end is None:
+        l_end = 0
+    else:
+        to_end = np.asanyarray(to_end)
+        if not np.can_cast(to_end, dtype_req, casting="same_kind"):
+            raise TypeError("dtype of `to_end` must be compatible "
+                            "with input `ary` under the `same_kind` rule.")
+
+        to_end = to_end.ravel()
+        l_end = len(to_end)
+
+    # do the calculation in place and copy to_begin and to_end
+    l_diff = max(len(ary) - 1, 0)
+    result = np.empty_like(ary, shape=l_diff + l_begin + l_end)
+
+    if l_begin > 0:
+        result[:l_begin] = to_begin
+    if l_end > 0:
+        result[l_begin + l_diff:] = to_end
+    np.subtract(ary[1:], ary[:-1], result[l_begin:l_begin + l_diff])
+
+    return conv.wrap(result)
+
+
+def _unpack_tuple(x):
+    """ Unpacks one-element tuples for use as return values """
+    if len(x) == 1:
+        return x[0]
+    else:
+        return x
+
+
+def _unique_dispatcher(ar, return_index=None, return_inverse=None,
+                       return_counts=None, axis=None, *, equal_nan=None,
+                       sorted=True):
+    return (ar,)
+
+
+@array_function_dispatch(_unique_dispatcher)
+def unique(ar, return_index=False, return_inverse=False,
+           return_counts=False, axis=None, *, equal_nan=True,
+           sorted=True):
+    """
+    Find the unique elements of an array.
+
+    Returns the sorted unique elements of an array. There are three optional
+    outputs in addition to the unique elements:
+
+    * the indices of the input array that give the unique values
+    * the indices of the unique array that reconstruct the input array
+    * the number of times each unique value comes up in the input array
+
+    Parameters
+    ----------
+    ar : array_like
+        Input array. Unless `axis` is specified, this will be flattened if it
+        is not already 1-D.
+    return_index : bool, optional
+        If True, also return the indices of `ar` (along the specified axis,
+        if provided, or in the flattened array) that result in the unique array.
+    return_inverse : bool, optional
+        If True, also return the indices of the unique array (for the specified
+        axis, if provided) that can be used to reconstruct `ar`.
+    return_counts : bool, optional
+        If True, also return the number of times each unique item appears
+        in `ar`.
+    axis : int or None, optional
+        The axis to operate on. If None, `ar` will be flattened. If an integer,
+        the subarrays indexed by the given axis will be flattened and treated
+        as the elements of a 1-D array with the dimension of the given axis,
+        see the notes for more details.  Object arrays or structured arrays
+        that contain objects are not supported if the `axis` kwarg is used. The
+        default is None.
+
+    equal_nan : bool, optional
+        If True, collapses multiple NaN values in the return array into one.
+
+        .. versionadded:: 1.24
+
+    sorted : bool, optional
+        If True, the unique elements are sorted. Elements may be sorted in
+        practice even if ``sorted=False``, but this could change without
+        notice.
+
+        .. versionadded:: 2.3
+
+    Returns
+    -------
+    unique : ndarray
+        The sorted unique values.
+    unique_indices : ndarray, optional
+        The indices of the first occurrences of the unique values in the
+        original array. Only provided if `return_index` is True.
+    unique_inverse : ndarray, optional
+        The indices to reconstruct the original array from the
+        unique array. Only provided if `return_inverse` is True.
+    unique_counts : ndarray, optional
+        The number of times each of the unique values comes up in the
+        original array. Only provided if `return_counts` is True.
+
+    See Also
+    --------
+    repeat : Repeat elements of an array.
+    sort : Return a sorted copy of an array.
+
+    Notes
+    -----
+    When an axis is specified the subarrays indexed by the axis are sorted.
+    This is done by making the specified axis the first dimension of the array
+    (move the axis to the first dimension to keep the order of the other axes)
+    and then flattening the subarrays in C order. The flattened subarrays are
+    then viewed as a structured type with each element given a label, with the
+    effect that we end up with a 1-D array of structured types that can be
+    treated in the same way as any other 1-D array. The result is that the
+    flattened subarrays are sorted in lexicographic order starting with the
+    first element.
+
+    .. versionchanged:: 1.21
+        Like np.sort, NaN will sort to the end of the values.
+        For complex arrays all NaN values are considered equivalent
+        (no matter whether the NaN is in the real or imaginary part).
+        As the representant for the returned array the smallest one in the
+        lexicographical order is chosen - see np.sort for how the lexicographical
+        order is defined for complex arrays.
+
+    .. versionchanged:: 2.0
+        For multi-dimensional inputs, ``unique_inverse`` is reshaped
+        such that the input can be reconstructed using
+        ``np.take(unique, unique_inverse, axis=axis)``. The result is
+        now not 1-dimensional when ``axis=None``.
+
+        Note that in NumPy 2.0.0 a higher dimensional array was returned also
+        when ``axis`` was not ``None``.  This was reverted, but
+        ``inverse.reshape(-1)`` can be used to ensure compatibility with both
+        versions.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.unique([1, 1, 2, 2, 3, 3])
+    array([1, 2, 3])
+    >>> a = np.array([[1, 1], [2, 3]])
+    >>> np.unique(a)
+    array([1, 2, 3])
+
+    Return the unique rows of a 2D array
+
+    >>> a = np.array([[1, 0, 0], [1, 0, 0], [2, 3, 4]])
+    >>> np.unique(a, axis=0)
+    array([[1, 0, 0], [2, 3, 4]])
+
+    Return the indices of the original array that give the unique values:
+
+    >>> a = np.array(['a', 'b', 'b', 'c', 'a'])
+    >>> u, indices = np.unique(a, return_index=True)
+    >>> u
+    array(['a', 'b', 'c'], dtype='<U1')
+    >>> indices
+    array([0, 1, 3])
+    >>> a[indices]
+    array(['a', 'b', 'c'], dtype='<U1')
+
+    Reconstruct the input array from the unique values and inverse:
+
+    >>> a = np.array([1, 2, 6, 4, 2, 3, 2])
+    >>> u, indices = np.unique(a, return_inverse=True)
+    >>> u
+    array([1, 2, 3, 4, 6])
+    >>> indices
+    array([0, 1, 4, 3, 1, 2, 1])
+    >>> u[indices]
+    array([1, 2, 6, 4, 2, 3, 2])
+
+    Reconstruct the input values from the unique values and counts:
+
+    >>> a = np.array([1, 2, 6, 4, 2, 3, 2])
+    >>> values, counts = np.unique(a, return_counts=True)
+    >>> values
+    array([1, 2, 3, 4, 6])
+    >>> counts
+    array([1, 3, 1, 1, 1])
+    >>> np.repeat(values, counts)
+    array([1, 2, 2, 2, 3, 4, 6])    # original order not preserved
+
+    """
+    ar = np.asanyarray(ar)
+    if axis is None or ar.ndim == 1:
+        if axis is not None:
+            normalize_axis_index(axis, ar.ndim)
+        ret = _unique1d(ar, return_index, return_inverse, return_counts,
+                        equal_nan=equal_nan, inverse_shape=ar.shape, axis=None,
+                        sorted=sorted)
+        return _unpack_tuple(ret)
+
+    # axis was specified and not None
+    try:
+        ar = np.moveaxis(ar, axis, 0)
+    except np.exceptions.AxisError:
+        # this removes the "axis1" or "axis2" prefix from the error message
+        raise np.exceptions.AxisError(axis, ar.ndim) from None
+    inverse_shape = [1] * ar.ndim
+    inverse_shape[axis] = ar.shape[0]
+
+    # Must reshape to a contiguous 2D array for this to work...
+    orig_shape, orig_dtype = ar.shape, ar.dtype
+    ar = ar.reshape(orig_shape[0], np.prod(orig_shape[1:], dtype=np.intp))
+    ar = np.ascontiguousarray(ar)
+    dtype = [(f'f{i}', ar.dtype) for i in range(ar.shape[1])]
+
+    # At this point, `ar` has shape `(n, m)`, and `dtype` is a structured
+    # data type with `m` fields where each field has the data type of `ar`.
+    # In the following, we create the array `consolidated`, which has
+    # shape `(n,)` with data type `dtype`.
+    try:
+        if ar.shape[1] > 0:
+            consolidated = ar.view(dtype)
+        else:
+            # If ar.shape[1] == 0, then dtype will be `np.dtype([])`, which is
+            # a data type with itemsize 0, and the call `ar.view(dtype)` will
+            # fail.  Instead, we'll use `np.empty` to explicitly create the
+            # array with shape `(len(ar),)`.  Because `dtype` in this case has
+            # itemsize 0, the total size of the result is still 0 bytes.
+            consolidated = np.empty(len(ar), dtype=dtype)
+    except TypeError as e:
+        # There's no good way to do this for object arrays, etc...
+        msg = 'The axis argument to unique is not supported for dtype {dt}'
+        raise TypeError(msg.format(dt=ar.dtype)) from e
+
+    def reshape_uniq(uniq):
+        n = len(uniq)
+        uniq = uniq.view(orig_dtype)
+        uniq = uniq.reshape(n, *orig_shape[1:])
+        uniq = np.moveaxis(uniq, 0, axis)
+        return uniq
+
+    output = _unique1d(consolidated, return_index,
+                       return_inverse, return_counts,
+                       equal_nan=equal_nan, inverse_shape=inverse_shape,
+                       axis=axis, sorted=sorted)
+    output = (reshape_uniq(output[0]),) + output[1:]
+    return _unpack_tuple(output)
+
+
+def _unique1d(ar, return_index=False, return_inverse=False,
+              return_counts=False, *, equal_nan=True, inverse_shape=None,
+              axis=None, sorted=True):
+    """
+    Find the unique elements of an array, ignoring shape.
+
+    Uses a hash table to find the unique elements if possible.
+    """
+    ar = np.asanyarray(ar).flatten()
+    if len(ar.shape) != 1:
+        # np.matrix, and maybe some other array subclasses, insist on keeping
+        # two dimensions for all operations. Coerce to an ndarray in such cases.
+        ar = np.asarray(ar).flatten()
+
+    optional_indices = return_index or return_inverse
+
+    # masked arrays are not supported yet.
+    if not optional_indices and not return_counts and not np.ma.is_masked(ar):
+        # First we convert the array to a numpy array, later we wrap it back
+        # in case it was a subclass of numpy.ndarray.
+        conv = _array_converter(ar)
+        ar_, = conv
+
+        if (hash_unique := _unique_hash(ar_, equal_nan=equal_nan)) \
+            is not NotImplemented:
+            if sorted:
+                hash_unique.sort()
+            # We wrap the result back in case it was a subclass of numpy.ndarray.
+            return (conv.wrap(hash_unique),)
+
+    # If we don't use the hash map, we use the slower sorting method.
+    if optional_indices:
+        perm = ar.argsort(kind='mergesort' if return_index else 'quicksort')
+        aux = ar[perm]
+    else:
+        ar.sort()
+        aux = ar
+    mask = np.empty(aux.shape, dtype=np.bool)
+    mask[:1] = True
+    if (equal_nan and aux.shape[0] > 0 and aux.dtype.kind in "cfmM" and
+            np.isnan(aux[-1])):
+        if aux.dtype.kind == "c":  # for complex all NaNs are considered equivalent
+            aux_firstnan = np.searchsorted(np.isnan(aux), True, side='left')
+        else:
+            aux_firstnan = np.searchsorted(aux, aux[-1], side='left')
+        if aux_firstnan > 0:
+            mask[1:aux_firstnan] = (
+                aux[1:aux_firstnan] != aux[:aux_firstnan - 1])
+        mask[aux_firstnan] = True
+        mask[aux_firstnan + 1:] = False
+    else:
+        mask[1:] = aux[1:] != aux[:-1]
+
+    ret = (aux[mask],)
+    if return_index:
+        ret += (perm[mask],)
+    if return_inverse:
+        imask = np.cumsum(mask) - 1
+        inv_idx = np.empty(mask.shape, dtype=np.intp)
+        inv_idx[perm] = imask
+        ret += (inv_idx.reshape(inverse_shape) if axis is None else inv_idx,)
+    if return_counts:
+        idx = np.concatenate(np.nonzero(mask) + ([mask.size],))
+        ret += (np.diff(idx),)
+    return ret
+
+
+# Array API set functions
+
+class UniqueAllResult(NamedTuple):
+    values: np.ndarray
+    indices: np.ndarray
+    inverse_indices: np.ndarray
+    counts: np.ndarray
+
+
+class UniqueCountsResult(NamedTuple):
+    values: np.ndarray
+    counts: np.ndarray
+
+
+class UniqueInverseResult(NamedTuple):
+    values: np.ndarray
+    inverse_indices: np.ndarray
+
+
+def _unique_all_dispatcher(x, /):
+    return (x,)
+
+
+@array_function_dispatch(_unique_all_dispatcher)
+def unique_all(x):
+    """
+    Find the unique elements of an array, and counts, inverse, and indices.
+
+    This function is an Array API compatible alternative to::
+
+        np.unique(x, return_index=True, return_inverse=True,
+                  return_counts=True, equal_nan=False, sorted=False)
+
+    but returns a namedtuple for easier access to each output.
+
+    .. note::
+        This function currently always returns a sorted result, however,
+        this could change in any NumPy minor release.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array. It will be flattened if it is not already 1-D.
+
+    Returns
+    -------
+    out : namedtuple
+        The result containing:
+
+        * values - The unique elements of an input array.
+        * indices - The first occurring indices for each unique element.
+        * inverse_indices - The indices from the set of unique elements
+          that reconstruct `x`.
+        * counts - The corresponding counts for each unique element.
+
+    See Also
+    --------
+    unique : Find the unique elements of an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = [1, 1, 2]
+    >>> uniq = np.unique_all(x)
+    >>> uniq.values
+    array([1, 2])
+    >>> uniq.indices
+    array([0, 2])
+    >>> uniq.inverse_indices
+    array([0, 0, 1])
+    >>> uniq.counts
+    array([2, 1])
+    """
+    result = unique(
+        x,
+        return_index=True,
+        return_inverse=True,
+        return_counts=True,
+        equal_nan=False,
+    )
+    return UniqueAllResult(*result)
+
+
+def _unique_counts_dispatcher(x, /):
+    return (x,)
+
+
+@array_function_dispatch(_unique_counts_dispatcher)
+def unique_counts(x):
+    """
+    Find the unique elements and counts of an input array `x`.
+
+    This function is an Array API compatible alternative to::
+
+        np.unique(x, return_counts=True, equal_nan=False, sorted=False)
+
+    but returns a namedtuple for easier access to each output.
+
+    .. note::
+        This function currently always returns a sorted result, however,
+        this could change in any NumPy minor release.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array. It will be flattened if it is not already 1-D.
+
+    Returns
+    -------
+    out : namedtuple
+        The result containing:
+
+        * values - The unique elements of an input array.
+        * counts - The corresponding counts for each unique element.
+
+    See Also
+    --------
+    unique : Find the unique elements of an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = [1, 1, 2]
+    >>> uniq = np.unique_counts(x)
+    >>> uniq.values
+    array([1, 2])
+    >>> uniq.counts
+    array([2, 1])
+    """
+    result = unique(
+        x,
+        return_index=False,
+        return_inverse=False,
+        return_counts=True,
+        equal_nan=False,
+    )
+    return UniqueCountsResult(*result)
+
+
+def _unique_inverse_dispatcher(x, /):
+    return (x,)
+
+
+@array_function_dispatch(_unique_inverse_dispatcher)
+def unique_inverse(x):
+    """
+    Find the unique elements of `x` and indices to reconstruct `x`.
+
+    This function is an Array API compatible alternative to::
+
+        np.unique(x, return_inverse=True, equal_nan=False, sorted=False)
+
+    but returns a namedtuple for easier access to each output.
+
+    .. note::
+        This function currently always returns a sorted result, however,
+        this could change in any NumPy minor release.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array. It will be flattened if it is not already 1-D.
+
+    Returns
+    -------
+    out : namedtuple
+        The result containing:
+
+        * values - The unique elements of an input array.
+        * inverse_indices - The indices from the set of unique elements
+          that reconstruct `x`.
+
+    See Also
+    --------
+    unique : Find the unique elements of an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = [1, 1, 2]
+    >>> uniq = np.unique_inverse(x)
+    >>> uniq.values
+    array([1, 2])
+    >>> uniq.inverse_indices
+    array([0, 0, 1])
+    """
+    result = unique(
+        x,
+        return_index=False,
+        return_inverse=True,
+        return_counts=False,
+        equal_nan=False,
+    )
+    return UniqueInverseResult(*result)
+
+
+def _unique_values_dispatcher(x, /):
+    return (x,)
+
+
+@array_function_dispatch(_unique_values_dispatcher)
+def unique_values(x):
+    """
+    Returns the unique elements of an input array `x`.
+
+    This function is an Array API compatible alternative to::
+
+        np.unique(x, equal_nan=False, sorted=False)
+
+    .. versionchanged:: 2.3
+       The algorithm was changed to a faster one that does not rely on
+       sorting, and hence the results are no longer implicitly sorted.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array. It will be flattened if it is not already 1-D.
+
+    Returns
+    -------
+    out : ndarray
+        The unique elements of an input array.
+
+    See Also
+    --------
+    unique : Find the unique elements of an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.unique_values([1, 1, 2])
+    array([1, 2])  # may vary
+
+    """
+    return unique(
+        x,
+        return_index=False,
+        return_inverse=False,
+        return_counts=False,
+        equal_nan=False,
+        sorted=False,
+    )
+
+
+def _intersect1d_dispatcher(
+        ar1, ar2, assume_unique=None, return_indices=None):
+    return (ar1, ar2)
+
+
+@array_function_dispatch(_intersect1d_dispatcher)
+def intersect1d(ar1, ar2, assume_unique=False, return_indices=False):
+    """
+    Find the intersection of two arrays.
+
+    Return the sorted, unique values that are in both of the input arrays.
+
+    Parameters
+    ----------
+    ar1, ar2 : array_like
+        Input arrays. Will be flattened if not already 1D.
+    assume_unique : bool
+        If True, the input arrays are both assumed to be unique, which
+        can speed up the calculation.  If True but ``ar1`` or ``ar2`` are not
+        unique, incorrect results and out-of-bounds indices could result.
+        Default is False.
+    return_indices : bool
+        If True, the indices which correspond to the intersection of the two
+        arrays are returned. The first instance of a value is used if there are
+        multiple. Default is False.
+
+    Returns
+    -------
+    intersect1d : ndarray
+        Sorted 1D array of common and unique elements.
+    comm1 : ndarray
+        The indices of the first occurrences of the common values in `ar1`.
+        Only provided if `return_indices` is True.
+    comm2 : ndarray
+        The indices of the first occurrences of the common values in `ar2`.
+        Only provided if `return_indices` is True.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.intersect1d([1, 3, 4, 3], [3, 1, 2, 1])
+    array([1, 3])
+
+    To intersect more than two arrays, use functools.reduce:
+
+    >>> from functools import reduce
+    >>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2]))
+    array([3])
+
+    To return the indices of the values common to the input arrays
+    along with the intersected values:
+
+    >>> x = np.array([1, 1, 2, 3, 4])
+    >>> y = np.array([2, 1, 4, 6])
+    >>> xy, x_ind, y_ind = np.intersect1d(x, y, return_indices=True)
+    >>> x_ind, y_ind
+    (array([0, 2, 4]), array([1, 0, 2]))
+    >>> xy, x[x_ind], y[y_ind]
+    (array([1, 2, 4]), array([1, 2, 4]), array([1, 2, 4]))
+
+    """
+    ar1 = np.asanyarray(ar1)
+    ar2 = np.asanyarray(ar2)
+
+    if not assume_unique:
+        if return_indices:
+            ar1, ind1 = unique(ar1, return_index=True)
+            ar2, ind2 = unique(ar2, return_index=True)
+        else:
+            ar1 = unique(ar1)
+            ar2 = unique(ar2)
+    else:
+        ar1 = ar1.ravel()
+        ar2 = ar2.ravel()
+
+    aux = np.concatenate((ar1, ar2))
+    if return_indices:
+        aux_sort_indices = np.argsort(aux, kind='mergesort')
+        aux = aux[aux_sort_indices]
+    else:
+        aux.sort()
+
+    mask = aux[1:] == aux[:-1]
+    int1d = aux[:-1][mask]
+
+    if return_indices:
+        ar1_indices = aux_sort_indices[:-1][mask]
+        ar2_indices = aux_sort_indices[1:][mask] - ar1.size
+        if not assume_unique:
+            ar1_indices = ind1[ar1_indices]
+            ar2_indices = ind2[ar2_indices]
+
+        return int1d, ar1_indices, ar2_indices
+    else:
+        return int1d
+
+
+def _setxor1d_dispatcher(ar1, ar2, assume_unique=None):
+    return (ar1, ar2)
+
+
+@array_function_dispatch(_setxor1d_dispatcher)
+def setxor1d(ar1, ar2, assume_unique=False):
+    """
+    Find the set exclusive-or of two arrays.
+
+    Return the sorted, unique values that are in only one (not both) of the
+    input arrays.
+
+    Parameters
+    ----------
+    ar1, ar2 : array_like
+        Input arrays.
+    assume_unique : bool
+        If True, the input arrays are both assumed to be unique, which
+        can speed up the calculation. Default is False.
+
+    Returns
+    -------
+    setxor1d : ndarray
+        Sorted 1D array of unique values that are in only one of the input
+        arrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1, 2, 3, 2, 4])
+    >>> b = np.array([2, 3, 5, 7, 5])
+    >>> np.setxor1d(a,b)
+    array([1, 4, 5, 7])
+
+    """
+    if not assume_unique:
+        ar1 = unique(ar1)
+        ar2 = unique(ar2)
+
+    aux = np.concatenate((ar1, ar2), axis=None)
+    if aux.size == 0:
+        return aux
+
+    aux.sort()
+    flag = np.concatenate(([True], aux[1:] != aux[:-1], [True]))
+    return aux[flag[1:] & flag[:-1]]
+
+
+def _isin(ar1, ar2, assume_unique=False, invert=False, *, kind=None):
+    # Ravel both arrays, behavior for the first array could be different
+    ar1 = np.asarray(ar1).ravel()
+    ar2 = np.asarray(ar2).ravel()
+
+    # Ensure that iteration through object arrays yields size-1 arrays
+    if ar2.dtype == object:
+        ar2 = ar2.reshape(-1, 1)
+
+    if kind not in {None, 'sort', 'table'}:
+        raise ValueError(
+            f"Invalid kind: '{kind}'. Please use None, 'sort' or 'table'.")
+
+    # Can use the table method if all arrays are integers or boolean:
+    is_int_arrays = all(ar.dtype.kind in ("u", "i", "b") for ar in (ar1, ar2))
+    use_table_method = is_int_arrays and kind in {None, 'table'}
+
+    if use_table_method:
+        if ar2.size == 0:
+            if invert:
+                return np.ones_like(ar1, dtype=bool)
+            else:
+                return np.zeros_like(ar1, dtype=bool)
+
+        # Convert booleans to uint8 so we can use the fast integer algorithm
+        if ar1.dtype == bool:
+            ar1 = ar1.astype(np.uint8)
+        if ar2.dtype == bool:
+            ar2 = ar2.astype(np.uint8)
+
+        ar2_min = int(np.min(ar2))
+        ar2_max = int(np.max(ar2))
+
+        ar2_range = ar2_max - ar2_min
+
+        # Constraints on whether we can actually use the table method:
+        #  1. Assert memory usage is not too large
+        below_memory_constraint = ar2_range <= 6 * (ar1.size + ar2.size)
+        #  2. Check overflows for (ar2 - ar2_min); dtype=ar2.dtype
+        range_safe_from_overflow = ar2_range <= np.iinfo(ar2.dtype).max
+
+        # Optimal performance is for approximately
+        # log10(size) > (log10(range) - 2.27) / 0.927.
+        # However, here we set the requirement that by default
+        # the intermediate array can only be 6x
+        # the combined memory allocation of the original
+        # arrays. See discussion on
+        # https://github.com/numpy/numpy/pull/12065.
+
+        if (
+            range_safe_from_overflow and
+            (below_memory_constraint or kind == 'table')
+        ):
+
+            if invert:
+                outgoing_array = np.ones_like(ar1, dtype=bool)
+            else:
+                outgoing_array = np.zeros_like(ar1, dtype=bool)
+
+            # Make elements 1 where the integer exists in ar2
+            if invert:
+                isin_helper_ar = np.ones(ar2_range + 1, dtype=bool)
+                isin_helper_ar[ar2 - ar2_min] = 0
+            else:
+                isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool)
+                isin_helper_ar[ar2 - ar2_min] = 1
+
+            # Mask out elements we know won't work
+            basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min)
+            in_range_ar1 = ar1[basic_mask]
+            if in_range_ar1.size == 0:
+                # Nothing more to do, since all values are out of range.
+                return outgoing_array
+
+            # Unfortunately, ar2_min can be out of range for `intp` even
+            # if the calculation result must fit in range (and be positive).
+            # In that case, use ar2.dtype which must work for all unmasked
+            # values.
+            try:
+                ar2_min = np.array(ar2_min, dtype=np.intp)
+                dtype = np.intp
+            except OverflowError:
+                dtype = ar2.dtype
+
+            out = np.empty_like(in_range_ar1, dtype=np.intp)
+            outgoing_array[basic_mask] = isin_helper_ar[
+                    np.subtract(in_range_ar1, ar2_min, dtype=dtype,
+                                out=out, casting="unsafe")]
+
+            return outgoing_array
+        elif kind == 'table':  # not range_safe_from_overflow
+            raise RuntimeError(
+                "You have specified kind='table', "
+                "but the range of values in `ar2` or `ar1` exceed the "
+                "maximum integer of the datatype. "
+                "Please set `kind` to None or 'sort'."
+            )
+    elif kind == 'table':
+        raise ValueError(
+            "The 'table' method is only "
+            "supported for boolean or integer arrays. "
+            "Please select 'sort' or None for kind."
+        )
+
+    # Check if one of the arrays may contain arbitrary objects
+    contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject
+
+    # This code is run when
+    # a) the first condition is true, making the code significantly faster
+    # b) the second condition is true (i.e. `ar1` or `ar2` may contain
+    #    arbitrary objects), since then sorting is not guaranteed to work
+    if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object:
+        if invert:
+            mask = np.ones(len(ar1), dtype=bool)
+            for a in ar2:
+                mask &= (ar1 != a)
+        else:
+            mask = np.zeros(len(ar1), dtype=bool)
+            for a in ar2:
+                mask |= (ar1 == a)
+        return mask
+
+    # Otherwise use sorting
+    if not assume_unique:
+        ar1, rev_idx = np.unique(ar1, return_inverse=True)
+        ar2 = np.unique(ar2)
+
+    ar = np.concatenate((ar1, ar2))
+    # We need this to be a stable sort, so always use 'mergesort'
+    # here. The values from the first array should always come before
+    # the values from the second array.
+    order = ar.argsort(kind='mergesort')
+    sar = ar[order]
+    if invert:
+        bool_ar = (sar[1:] != sar[:-1])
+    else:
+        bool_ar = (sar[1:] == sar[:-1])
+    flag = np.concatenate((bool_ar, [invert]))
+    ret = np.empty(ar.shape, dtype=bool)
+    ret[order] = flag
+
+    if assume_unique:
+        return ret[:len(ar1)]
+    else:
+        return ret[rev_idx]
+
+
+def _isin_dispatcher(element, test_elements, assume_unique=None, invert=None,
+                     *, kind=None):
+    return (element, test_elements)
+
+
+@array_function_dispatch(_isin_dispatcher)
+def isin(element, test_elements, assume_unique=False, invert=False, *,
+         kind=None):
+    """
+    Calculates ``element in test_elements``, broadcasting over `element` only.
+    Returns a boolean array of the same shape as `element` that is True
+    where an element of `element` is in `test_elements` and False otherwise.
+
+    Parameters
+    ----------
+    element : array_like
+        Input array.
+    test_elements : array_like
+        The values against which to test each value of `element`.
+        This argument is flattened if it is an array or array_like.
+        See notes for behavior with non-array-like parameters.
+    assume_unique : bool, optional
+        If True, the input arrays are both assumed to be unique, which
+        can speed up the calculation.  Default is False.
+    invert : bool, optional
+        If True, the values in the returned array are inverted, as if
+        calculating `element not in test_elements`. Default is False.
+        ``np.isin(a, b, invert=True)`` is equivalent to (but faster
+        than) ``np.invert(np.isin(a, b))``.
+    kind : {None, 'sort', 'table'}, optional
+        The algorithm to use. This will not affect the final result,
+        but will affect the speed and memory use. The default, None,
+        will select automatically based on memory considerations.
+
+        * If 'sort', will use a mergesort-based approach. This will have
+          a memory usage of roughly 6 times the sum of the sizes of
+          `element` and `test_elements`, not accounting for size of dtypes.
+        * If 'table', will use a lookup table approach similar
+          to a counting sort. This is only available for boolean and
+          integer arrays. This will have a memory usage of the
+          size of `element` plus the max-min value of `test_elements`.
+          `assume_unique` has no effect when the 'table' option is used.
+        * If None, will automatically choose 'table' if
+          the required memory allocation is less than or equal to
+          6 times the sum of the sizes of `element` and `test_elements`,
+          otherwise will use 'sort'. This is done to not use
+          a large amount of memory by default, even though
+          'table' may be faster in most cases. If 'table' is chosen,
+          `assume_unique` will have no effect.
+
+
+    Returns
+    -------
+    isin : ndarray, bool
+        Has the same shape as `element`. The values `element[isin]`
+        are in `test_elements`.
+
+    Notes
+    -----
+    `isin` is an element-wise function version of the python keyword `in`.
+    ``isin(a, b)`` is roughly equivalent to
+    ``np.array([item in b for item in a])`` if `a` and `b` are 1-D sequences.
+
+    `element` and `test_elements` are converted to arrays if they are not
+    already. If `test_elements` is a set (or other non-sequence collection)
+    it will be converted to an object array with one element, rather than an
+    array of the values contained in `test_elements`. This is a consequence
+    of the `array` constructor's way of handling non-sequence collections.
+    Converting the set to a list usually gives the desired behavior.
+
+    Using ``kind='table'`` tends to be faster than `kind='sort'` if the
+    following relationship is true:
+    ``log10(len(test_elements)) >
+    (log10(max(test_elements)-min(test_elements)) - 2.27) / 0.927``,
+    but may use greater memory. The default value for `kind` will
+    be automatically selected based only on memory usage, so one may
+    manually set ``kind='table'`` if memory constraints can be relaxed.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> element = 2*np.arange(4).reshape((2, 2))
+    >>> element
+    array([[0, 2],
+           [4, 6]])
+    >>> test_elements = [1, 2, 4, 8]
+    >>> mask = np.isin(element, test_elements)
+    >>> mask
+    array([[False,  True],
+           [ True, False]])
+    >>> element[mask]
+    array([2, 4])
+
+    The indices of the matched values can be obtained with `nonzero`:
+
+    >>> np.nonzero(mask)
+    (array([0, 1]), array([1, 0]))
+
+    The test can also be inverted:
+
+    >>> mask = np.isin(element, test_elements, invert=True)
+    >>> mask
+    array([[ True, False],
+           [False,  True]])
+    >>> element[mask]
+    array([0, 6])
+
+    Because of how `array` handles sets, the following does not
+    work as expected:
+
+    >>> test_set = {1, 2, 4, 8}
+    >>> np.isin(element, test_set)
+    array([[False, False],
+           [False, False]])
+
+    Casting the set to a list gives the expected result:
+
+    >>> np.isin(element, list(test_set))
+    array([[False,  True],
+           [ True, False]])
+    """
+    element = np.asarray(element)
+    return _isin(element, test_elements, assume_unique=assume_unique,
+                 invert=invert, kind=kind).reshape(element.shape)
+
+
+def _union1d_dispatcher(ar1, ar2):
+    return (ar1, ar2)
+
+
+@array_function_dispatch(_union1d_dispatcher)
+def union1d(ar1, ar2):
+    """
+    Find the union of two arrays.
+
+    Return the unique, sorted array of values that are in either of the two
+    input arrays.
+
+    Parameters
+    ----------
+    ar1, ar2 : array_like
+        Input arrays. They are flattened if they are not already 1D.
+
+    Returns
+    -------
+    union1d : ndarray
+        Unique, sorted union of the input arrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.union1d([-1, 0, 1], [-2, 0, 2])
+    array([-2, -1,  0,  1,  2])
+
+    To find the union of more than two arrays, use functools.reduce:
+
+    >>> from functools import reduce
+    >>> reduce(np.union1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2]))
+    array([1, 2, 3, 4, 6])
+    """
+    return unique(np.concatenate((ar1, ar2), axis=None))
+
+
+def _setdiff1d_dispatcher(ar1, ar2, assume_unique=None):
+    return (ar1, ar2)
+
+
+@array_function_dispatch(_setdiff1d_dispatcher)
+def setdiff1d(ar1, ar2, assume_unique=False):
+    """
+    Find the set difference of two arrays.
+
+    Return the unique values in `ar1` that are not in `ar2`.
+
+    Parameters
+    ----------
+    ar1 : array_like
+        Input array.
+    ar2 : array_like
+        Input comparison array.
+    assume_unique : bool
+        If True, the input arrays are both assumed to be unique, which
+        can speed up the calculation.  Default is False.
+
+    Returns
+    -------
+    setdiff1d : ndarray
+        1D array of values in `ar1` that are not in `ar2`. The result
+        is sorted when `assume_unique=False`, but otherwise only sorted
+        if the input is sorted.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1, 2, 3, 2, 4, 1])
+    >>> b = np.array([3, 4, 5, 6])
+    >>> np.setdiff1d(a, b)
+    array([1, 2])
+
+    """
+    if assume_unique:
+        ar1 = np.asarray(ar1).ravel()
+    else:
+        ar1 = unique(ar1)
+        ar2 = unique(ar2)
+    return ar1[_isin(ar1, ar2, assume_unique=True, invert=True)]
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..777fca8a0f4dd43cccf85522e6fc24ede62d9764
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arraysetops_impl.pyi
@@ -0,0 +1,462 @@
+from typing import (
+    Any,
+    Generic,
+    Literal as L,
+    NamedTuple,
+    SupportsIndex,
+    TypeAlias,
+    overload,
+)
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy._typing import (
+    ArrayLike,
+    NDArray,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeNumber_co,
+)
+
+__all__ = [
+    "ediff1d",
+    "intersect1d",
+    "isin",
+    "setdiff1d",
+    "setxor1d",
+    "union1d",
+    "unique",
+    "unique_all",
+    "unique_counts",
+    "unique_inverse",
+    "unique_values",
+]
+
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_NumericT = TypeVar("_NumericT", bound=np.number | np.timedelta64 | np.object_)
+
+# Explicitly set all allowed values to prevent accidental castings to
+# abstract dtypes (their common super-type).
+# Only relevant if two or more arguments are parametrized, (e.g. `setdiff1d`)
+# which could result in, for example, `int64` and `float64`producing a
+# `number[_64Bit]` array
+_EitherSCT = TypeVar(
+    "_EitherSCT",
+    np.bool,
+    np.int8, np.int16, np.int32, np.int64, np.intp,
+    np.uint8, np.uint16, np.uint32, np.uint64, np.uintp,
+    np.float16, np.float32, np.float64, np.longdouble,
+    np.complex64, np.complex128, np.clongdouble,
+    np.timedelta64, np.datetime64,
+    np.bytes_, np.str_, np.void, np.object_,
+    np.integer, np.floating, np.complexfloating, np.character,
+)  # fmt: skip
+
+_AnyArray: TypeAlias = NDArray[Any]
+_IntArray: TypeAlias = NDArray[np.intp]
+
+###
+
+class UniqueAllResult(NamedTuple, Generic[_ScalarT]):
+    values: NDArray[_ScalarT]
+    indices: _IntArray
+    inverse_indices: _IntArray
+    counts: _IntArray
+
+class UniqueCountsResult(NamedTuple, Generic[_ScalarT]):
+    values: NDArray[_ScalarT]
+    counts: _IntArray
+
+class UniqueInverseResult(NamedTuple, Generic[_ScalarT]):
+    values: NDArray[_ScalarT]
+    inverse_indices: _IntArray
+
+#
+@overload
+def ediff1d(
+    ary: _ArrayLikeBool_co,
+    to_end: ArrayLike | None = None,
+    to_begin: ArrayLike | None = None,
+) -> NDArray[np.int8]: ...
+@overload
+def ediff1d(
+    ary: _ArrayLike[_NumericT],
+    to_end: ArrayLike | None = None,
+    to_begin: ArrayLike | None = None,
+) -> NDArray[_NumericT]: ...
+@overload
+def ediff1d(
+    ary: _ArrayLike[np.datetime64[Any]],
+    to_end: ArrayLike | None = None,
+    to_begin: ArrayLike | None = None,
+) -> NDArray[np.timedelta64]: ...
+@overload
+def ediff1d(
+    ary: _ArrayLikeNumber_co,
+    to_end: ArrayLike | None = None,
+    to_begin: ArrayLike | None = None,
+) -> _AnyArray: ...
+
+#
+@overload  # known scalar-type, FFF
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False] = False,
+    return_inverse: L[False] = False,
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> NDArray[_ScalarT]: ...
+@overload  # unknown scalar-type, FFF
+def unique(
+    ar: ArrayLike,
+    return_index: L[False] = False,
+    return_inverse: L[False] = False,
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> _AnyArray: ...
+@overload  # known scalar-type, TFF
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[True],
+    return_inverse: L[False] = False,
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray]: ...
+@overload  # unknown scalar-type, TFF
+def unique(
+    ar: ArrayLike,
+    return_index: L[True],
+    return_inverse: L[False] = False,
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray]: ...
+@overload  # known scalar-type, FTF (positional)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False],
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray]: ...
+@overload  # known scalar-type, FTF (keyword)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False] = False,
+    *,
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray]: ...
+@overload  # unknown scalar-type, FTF (positional)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False],
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray]: ...
+@overload  # unknown scalar-type, FTF (keyword)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False] = False,
+    *,
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray]: ...
+@overload  # known scalar-type, FFT (positional)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False],
+    return_inverse: L[False],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray]: ...
+@overload  # known scalar-type, FFT (keyword)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False] = False,
+    return_inverse: L[False] = False,
+    *,
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray]: ...
+@overload  # unknown scalar-type, FFT (positional)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False],
+    return_inverse: L[False],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray]: ...
+@overload  # unknown scalar-type, FFT (keyword)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False] = False,
+    return_inverse: L[False] = False,
+    *,
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray]: ...
+@overload  # known scalar-type, TTF
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[True],
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, TTF
+def unique(
+    ar: ArrayLike,
+    return_index: L[True],
+    return_inverse: L[True],
+    return_counts: L[False] = False,
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # known scalar-type, TFT (positional)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[True],
+    return_inverse: L[False],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray]: ...
+@overload  # known scalar-type, TFT (keyword)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[True],
+    return_inverse: L[False] = False,
+    *,
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, TFT (positional)
+def unique(
+    ar: ArrayLike,
+    return_index: L[True],
+    return_inverse: L[False],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, TFT (keyword)
+def unique(
+    ar: ArrayLike,
+    return_index: L[True],
+    return_inverse: L[False] = False,
+    *,
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # known scalar-type, FTT (positional)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False],
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray]: ...
+@overload  # known scalar-type, FTT (keyword)
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[False] = False,
+    *,
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, FTT (positional)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False],
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, FTT (keyword)
+def unique(
+    ar: ArrayLike,
+    return_index: L[False] = False,
+    *,
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # known scalar-type, TTT
+def unique(
+    ar: _ArrayLike[_ScalarT],
+    return_index: L[True],
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[NDArray[_ScalarT], _IntArray, _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, TTT
+def unique(
+    ar: ArrayLike,
+    return_index: L[True],
+    return_inverse: L[True],
+    return_counts: L[True],
+    axis: SupportsIndex | None = None,
+    *,
+    equal_nan: bool = True,
+    sorted: bool = True,
+) -> tuple[_AnyArray, _IntArray, _IntArray, _IntArray]: ...
+
+#
+@overload
+def unique_all(x: _ArrayLike[_ScalarT]) -> UniqueAllResult[_ScalarT]: ...
+@overload
+def unique_all(x: ArrayLike) -> UniqueAllResult[Any]: ...
+
+#
+@overload
+def unique_counts(x: _ArrayLike[_ScalarT]) -> UniqueCountsResult[_ScalarT]: ...
+@overload
+def unique_counts(x: ArrayLike) -> UniqueCountsResult[Any]: ...
+
+#
+@overload
+def unique_inverse(x: _ArrayLike[_ScalarT]) -> UniqueInverseResult[_ScalarT]: ...
+@overload
+def unique_inverse(x: ArrayLike) -> UniqueInverseResult[Any]: ...
+
+#
+@overload
+def unique_values(x: _ArrayLike[_ScalarT]) -> NDArray[_ScalarT]: ...
+@overload
+def unique_values(x: ArrayLike) -> _AnyArray: ...
+
+#
+@overload  # known scalar-type, return_indices=False (default)
+def intersect1d(
+    ar1: _ArrayLike[_EitherSCT],
+    ar2: _ArrayLike[_EitherSCT],
+    assume_unique: bool = False,
+    return_indices: L[False] = False,
+) -> NDArray[_EitherSCT]: ...
+@overload  # known scalar-type, return_indices=True (positional)
+def intersect1d(
+    ar1: _ArrayLike[_EitherSCT],
+    ar2: _ArrayLike[_EitherSCT],
+    assume_unique: bool,
+    return_indices: L[True],
+) -> tuple[NDArray[_EitherSCT], _IntArray, _IntArray]: ...
+@overload  # known scalar-type, return_indices=True (keyword)
+def intersect1d(
+    ar1: _ArrayLike[_EitherSCT],
+    ar2: _ArrayLike[_EitherSCT],
+    assume_unique: bool = False,
+    *,
+    return_indices: L[True],
+) -> tuple[NDArray[_EitherSCT], _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, return_indices=False (default)
+def intersect1d(
+    ar1: ArrayLike,
+    ar2: ArrayLike,
+    assume_unique: bool = False,
+    return_indices: L[False] = False,
+) -> _AnyArray: ...
+@overload  # unknown scalar-type, return_indices=True (positional)
+def intersect1d(
+    ar1: ArrayLike,
+    ar2: ArrayLike,
+    assume_unique: bool,
+    return_indices: L[True],
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+@overload  # unknown scalar-type, return_indices=True (keyword)
+def intersect1d(
+    ar1: ArrayLike,
+    ar2: ArrayLike,
+    assume_unique: bool = False,
+    *,
+    return_indices: L[True],
+) -> tuple[_AnyArray, _IntArray, _IntArray]: ...
+
+#
+@overload
+def setxor1d(ar1: _ArrayLike[_EitherSCT], ar2: _ArrayLike[_EitherSCT], assume_unique: bool = False) -> NDArray[_EitherSCT]: ...
+@overload
+def setxor1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = False) -> _AnyArray: ...
+
+#
+@overload
+def union1d(ar1: _ArrayLike[_EitherSCT], ar2: _ArrayLike[_EitherSCT]) -> NDArray[_EitherSCT]: ...
+@overload
+def union1d(ar1: ArrayLike, ar2: ArrayLike) -> _AnyArray: ...
+
+#
+@overload
+def setdiff1d(ar1: _ArrayLike[_EitherSCT], ar2: _ArrayLike[_EitherSCT], assume_unique: bool = False) -> NDArray[_EitherSCT]: ...
+@overload
+def setdiff1d(ar1: ArrayLike, ar2: ArrayLike, assume_unique: bool = False) -> _AnyArray: ...
+
+#
+def isin(
+    element: ArrayLike,
+    test_elements: ArrayLike,
+    assume_unique: bool = False,
+    invert: bool = False,
+    *,
+    kind: L["sort", "table"] | None = None,
+) -> NDArray[np.bool]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..844c0633dae90e77d058ea69a5a69df0005f657b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.py
@@ -0,0 +1,224 @@
+"""
+A buffered iterator for big arrays.
+
+This module solves the problem of iterating over a big file-based array
+without having to read it into memory. The `Arrayterator` class wraps
+an array object, and when iterated it will return sub-arrays with at most
+a user-specified number of elements.
+
+"""
+from functools import reduce
+from operator import mul
+
+__all__ = ['Arrayterator']
+
+
+class Arrayterator:
+    """
+    Buffered iterator for big arrays.
+
+    `Arrayterator` creates a buffered iterator for reading big arrays in small
+    contiguous blocks. The class is useful for objects stored in the
+    file system. It allows iteration over the object *without* reading
+    everything in memory; instead, small blocks are read and iterated over.
+
+    `Arrayterator` can be used with any object that supports multidimensional
+    slices. This includes NumPy arrays, but also variables from
+    Scientific.IO.NetCDF or pynetcdf for example.
+
+    Parameters
+    ----------
+    var : array_like
+        The object to iterate over.
+    buf_size : int, optional
+        The buffer size. If `buf_size` is supplied, the maximum amount of
+        data that will be read into memory is `buf_size` elements.
+        Default is None, which will read as many element as possible
+        into memory.
+
+    Attributes
+    ----------
+    var
+    buf_size
+    start
+    stop
+    step
+    shape
+    flat
+
+    See Also
+    --------
+    numpy.ndenumerate : Multidimensional array iterator.
+    numpy.flatiter : Flat array iterator.
+    numpy.memmap : Create a memory-map to an array stored
+                   in a binary file on disk.
+
+    Notes
+    -----
+    The algorithm works by first finding a "running dimension", along which
+    the blocks will be extracted. Given an array of dimensions
+    ``(d1, d2, ..., dn)``, e.g. if `buf_size` is smaller than ``d1``, the
+    first dimension will be used. If, on the other hand,
+    ``d1 < buf_size < d1*d2`` the second dimension will be used, and so on.
+    Blocks are extracted along this dimension, and when the last block is
+    returned the process continues from the next dimension, until all
+    elements have been read.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(3 * 4 * 5 * 6).reshape(3, 4, 5, 6)
+    >>> a_itor = np.lib.Arrayterator(a, 2)
+    >>> a_itor.shape
+    (3, 4, 5, 6)
+
+    Now we can iterate over ``a_itor``, and it will return arrays of size
+    two. Since `buf_size` was smaller than any dimension, the first
+    dimension will be iterated over first:
+
+    >>> for subarr in a_itor:
+    ...     if not subarr.all():
+    ...         print(subarr, subarr.shape) # doctest: +SKIP
+    >>> # [[[[0 1]]]] (1, 1, 1, 2)
+
+    """
+
+    __module__ = "numpy.lib"
+
+    def __init__(self, var, buf_size=None):
+        self.var = var
+        self.buf_size = buf_size
+
+        self.start = [0 for dim in var.shape]
+        self.stop = list(var.shape)
+        self.step = [1 for dim in var.shape]
+
+    def __getattr__(self, attr):
+        return getattr(self.var, attr)
+
+    def __getitem__(self, index):
+        """
+        Return a new arrayterator.
+
+        """
+        # Fix index, handling ellipsis and incomplete slices.
+        if not isinstance(index, tuple):
+            index = (index,)
+        fixed = []
+        length, dims = len(index), self.ndim
+        for slice_ in index:
+            if slice_ is Ellipsis:
+                fixed.extend([slice(None)] * (dims - length + 1))
+                length = len(fixed)
+            elif isinstance(slice_, int):
+                fixed.append(slice(slice_, slice_ + 1, 1))
+            else:
+                fixed.append(slice_)
+        index = tuple(fixed)
+        if len(index) < dims:
+            index += (slice(None),) * (dims - len(index))
+
+        # Return a new arrayterator object.
+        out = self.__class__(self.var, self.buf_size)
+        for i, (start, stop, step, slice_) in enumerate(
+                zip(self.start, self.stop, self.step, index)):
+            out.start[i] = start + (slice_.start or 0)
+            out.step[i] = step * (slice_.step or 1)
+            out.stop[i] = start + (slice_.stop or stop - start)
+            out.stop[i] = min(stop, out.stop[i])
+        return out
+
+    def __array__(self, dtype=None, copy=None):
+        """
+        Return corresponding data.
+
+        """
+        slice_ = tuple(slice(*t) for t in zip(
+                self.start, self.stop, self.step))
+        return self.var[slice_]
+
+    @property
+    def flat(self):
+        """
+        A 1-D flat iterator for Arrayterator objects.
+
+        This iterator returns elements of the array to be iterated over in
+        `~lib.Arrayterator` one by one.
+        It is similar to `flatiter`.
+
+        See Also
+        --------
+        lib.Arrayterator
+        flatiter
+
+        Examples
+        --------
+        >>> a = np.arange(3 * 4 * 5 * 6).reshape(3, 4, 5, 6)
+        >>> a_itor = np.lib.Arrayterator(a, 2)
+
+        >>> for subarr in a_itor.flat:
+        ...     if not subarr:
+        ...         print(subarr, type(subarr))
+        ...
+        0 <class 'numpy.int64'>
+
+        """
+        for block in self:
+            yield from block.flat
+
+    @property
+    def shape(self):
+        """
+        The shape of the array to be iterated over.
+
+        For an example, see `Arrayterator`.
+
+        """
+        return tuple(((stop - start - 1) // step + 1) for start, stop, step in
+                zip(self.start, self.stop, self.step))
+
+    def __iter__(self):
+        # Skip arrays with degenerate dimensions
+        if [dim for dim in self.shape if dim <= 0]:
+            return
+
+        start = self.start[:]
+        stop = self.stop[:]
+        step = self.step[:]
+        ndims = self.var.ndim
+
+        while True:
+            count = self.buf_size or reduce(mul, self.shape)
+
+            # iterate over each dimension, looking for the
+            # running dimension (ie, the dimension along which
+            # the blocks will be built from)
+            rundim = 0
+            for i in range(ndims - 1, -1, -1):
+                # if count is zero we ran out of elements to read
+                # along higher dimensions, so we read only a single position
+                if count == 0:
+                    stop[i] = start[i] + 1
+                elif count <= self.shape[i]:
+                    # limit along this dimension
+                    stop[i] = start[i] + count * step[i]
+                    rundim = i
+                else:
+                    # read everything along this dimension
+                    stop[i] = self.stop[i]
+                stop[i] = min(self.stop[i], stop[i])
+                count = count // self.shape[i]
+
+            # yield a block
+            slice_ = tuple(slice(*t) for t in zip(start, stop, step))
+            yield self.var[slice_]
+
+            # Update start position, taking care of overflow to
+            # other dimensions
+            start[rundim] = stop[rundim]  # start where we stopped
+            for i in range(ndims - 1, 0, -1):
+                if start[i] >= self.stop[i]:
+                    start[i] = self.start[i]
+                    start[i - 1] += self.step[i - 1]
+            if start[0] >= self.stop[0]:
+                return
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..eeddcf301ad1f2c10493c4a927753015660ff230
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_arrayterator_impl.pyi
@@ -0,0 +1,45 @@
+# pyright: reportIncompatibleMethodOverride=false
+
+from collections.abc import Generator
+from types import EllipsisType
+from typing import Any, Final, TypeAlias, overload
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy._typing import _AnyShape, _Shape
+
+__all__ = ["Arrayterator"]
+
+_ShapeT_co = TypeVar("_ShapeT_co", bound=_Shape, default=_AnyShape, covariant=True)
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+
+_AnyIndex: TypeAlias = EllipsisType | int | slice | tuple[EllipsisType | int | slice, ...]
+
+# NOTE: In reality `Arrayterator` does not actually inherit from `ndarray`,
+# but its ``__getattr__` method does wrap around the former and thus has
+# access to all its methods
+
+class Arrayterator(np.ndarray[_ShapeT_co, _DTypeT_co]):
+    var: np.ndarray[_ShapeT_co, _DTypeT_co]  # type: ignore[assignment]
+    buf_size: Final[int | None]
+    start: Final[list[int]]
+    stop: Final[list[int]]
+    step: Final[list[int]]
+
+    @property  # type: ignore[misc]
+    def shape(self) -> _ShapeT_co: ...
+    @property
+    def flat(self: Arrayterator[Any, np.dtype[_ScalarT]]) -> Generator[_ScalarT]: ...  # type: ignore[override]
+
+    #
+    def __init__(self, /, var: np.ndarray[_ShapeT_co, _DTypeT_co], buf_size: int | None = None) -> None: ...
+    def __getitem__(self, index: _AnyIndex, /) -> Arrayterator[_AnyShape, _DTypeT_co]: ...  # type: ignore[override]
+    def __iter__(self) -> Generator[np.ndarray[_AnyShape, _DTypeT_co]]: ...
+
+    #
+    @overload  # type: ignore[override]
+    def __array__(self, /, dtype: None = None, copy: bool | None = None) -> np.ndarray[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __array__(self, /, dtype: _DTypeT, copy: bool | None = None) -> np.ndarray[_ShapeT_co, _DTypeT]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_datasource.py b/python/user_packages/Python313/site-packages/numpy/lib/_datasource.py
new file mode 100644
index 0000000000000000000000000000000000000000..c36aa356bf4eb698ed5f616322e55bfab2104047
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_datasource.py
@@ -0,0 +1,700 @@
+"""A file interface for handling local and remote data files.
+
+The goal of datasource is to abstract some of the file system operations
+when dealing with data files so the researcher doesn't have to know all the
+low-level details.  Through datasource, a researcher can obtain and use a
+file with one function call, regardless of location of the file.
+
+DataSource is meant to augment standard python libraries, not replace them.
+It should work seamlessly with standard file IO operations and the os
+module.
+
+DataSource files can originate locally or remotely:
+
+- local files : '/home/guido/src/local/data.txt'
+- URLs (http, ftp, ...) : 'http://www.scipy.org/not/real/data.txt'
+
+DataSource files can also be compressed or uncompressed.  Currently only
+gzip, bz2 and xz are supported.
+
+Example::
+
+    >>> # Create a DataSource, use os.curdir (default) for local storage.
+    >>> from numpy import DataSource
+    >>> ds = DataSource()
+    >>>
+    >>> # Open a remote file.
+    >>> # DataSource downloads the file, stores it locally in:
+    >>> #     './www.google.com/index.html'
+    >>> # opens the file and returns a file object.
+    >>> fp = ds.open('http://www.google.com/') # doctest: +SKIP
+    >>>
+    >>> # Use the file as you normally would
+    >>> fp.read() # doctest: +SKIP
+    >>> fp.close() # doctest: +SKIP
+
+"""
+import os
+
+from numpy._utils import set_module
+
+_open = open
+
+
+def _check_mode(mode, encoding, newline):
+    """Check mode and that encoding and newline are compatible.
+
+    Parameters
+    ----------
+    mode : str
+        File open mode.
+    encoding : str
+        File encoding.
+    newline : str
+        Newline for text files.
+
+    """
+    if "t" in mode:
+        if "b" in mode:
+            raise ValueError(f"Invalid mode: {mode!r}")
+    else:
+        if encoding is not None:
+            raise ValueError("Argument 'encoding' not supported in binary mode")
+        if newline is not None:
+            raise ValueError("Argument 'newline' not supported in binary mode")
+
+
+# Using a class instead of a module-level dictionary
+# to reduce the initial 'import numpy' overhead by
+# deferring the import of lzma, bz2 and gzip until needed
+
+# TODO: .zip support, .tar support?
+class _FileOpeners:
+    """
+    Container for different methods to open (un-)compressed files.
+
+    `_FileOpeners` contains a dictionary that holds one method for each
+    supported file format. Attribute lookup is implemented in such a way
+    that an instance of `_FileOpeners` itself can be indexed with the keys
+    of that dictionary. Currently uncompressed files as well as files
+    compressed with ``gzip``, ``bz2`` or ``xz`` compression are supported.
+
+    Notes
+    -----
+    `_file_openers`, an instance of `_FileOpeners`, is made available for
+    use in the `_datasource` module.
+
+    Examples
+    --------
+    >>> import gzip
+    >>> np.lib._datasource._file_openers.keys()
+    [None, '.bz2', '.gz', '.xz', '.lzma']
+    >>> np.lib._datasource._file_openers['.gz'] is gzip.open
+    True
+
+    """
+
+    def __init__(self):
+        self._loaded = False
+        self._file_openers = {None: open}
+
+    def _load(self):
+        if self._loaded:
+            return
+
+        try:
+            import bz2
+            self._file_openers[".bz2"] = bz2.open
+        except ImportError:
+            pass
+
+        try:
+            import gzip
+            self._file_openers[".gz"] = gzip.open
+        except ImportError:
+            pass
+
+        try:
+            import lzma
+            self._file_openers[".xz"] = lzma.open
+            self._file_openers[".lzma"] = lzma.open
+        except (ImportError, AttributeError):
+            # There are incompatible backports of lzma that do not have the
+            # lzma.open attribute, so catch that as well as ImportError.
+            pass
+
+        self._loaded = True
+
+    def keys(self):
+        """
+        Return the keys of currently supported file openers.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        keys : list
+            The keys are None for uncompressed files and the file extension
+            strings (i.e. ``'.gz'``, ``'.xz'``) for supported compression
+            methods.
+
+        """
+        self._load()
+        return list(self._file_openers.keys())
+
+    def __getitem__(self, key):
+        self._load()
+        return self._file_openers[key]
+
+
+_file_openers = _FileOpeners()
+
+def open(path, mode='r', destpath=os.curdir, encoding=None, newline=None):
+    """
+    Open `path` with `mode` and return the file object.
+
+    If ``path`` is an URL, it will be downloaded, stored in the
+    `DataSource` `destpath` directory and opened from there.
+
+    Parameters
+    ----------
+    path : str or pathlib.Path
+        Local file path or URL to open.
+    mode : str, optional
+        Mode to open `path`. Mode 'r' for reading, 'w' for writing, 'a' to
+        append. Available modes depend on the type of object specified by
+        path.  Default is 'r'.
+    destpath : str, optional
+        Path to the directory where the source file gets downloaded to for
+        use.  If `destpath` is None, a temporary directory will be created.
+        The default path is the current directory.
+    encoding : {None, str}, optional
+        Open text file with given encoding. The default encoding will be
+        what `open` uses.
+    newline : {None, str}, optional
+        Newline to use when reading text file.
+
+    Returns
+    -------
+    out : file object
+        The opened file.
+
+    Notes
+    -----
+    This is a convenience function that instantiates a `DataSource` and
+    returns the file object from ``DataSource.open(path)``.
+
+    """
+
+    ds = DataSource(destpath)
+    return ds.open(path, mode, encoding=encoding, newline=newline)
+
+
+@set_module('numpy.lib.npyio')
+class DataSource:
+    """
+    DataSource(destpath='.')
+
+    A generic data source file (file, http, ftp, ...).
+
+    DataSources can be local files or remote files/URLs.  The files may
+    also be compressed or uncompressed. DataSource hides some of the
+    low-level details of downloading the file, allowing you to simply pass
+    in a valid file path (or URL) and obtain a file object.
+
+    Parameters
+    ----------
+    destpath : str or None, optional
+        Path to the directory where the source file gets downloaded to for
+        use.  If `destpath` is None, a temporary directory will be created.
+        The default path is the current directory.
+
+    Notes
+    -----
+    URLs require a scheme string (``http://``) to be used, without it they
+    will fail::
+
+        >>> repos = np.lib.npyio.DataSource()
+        >>> repos.exists('www.google.com/index.html')
+        False
+        >>> repos.exists('http://www.google.com/index.html')
+        True
+
+    Temporary directories are deleted when the DataSource is deleted.
+
+    Examples
+    --------
+    ::
+
+        >>> ds = np.lib.npyio.DataSource('/home/guido')
+        >>> urlname = 'http://www.google.com/'
+        >>> gfile = ds.open('http://www.google.com/')
+        >>> ds.abspath(urlname)
+        '/home/guido/www.google.com/index.html'
+
+        >>> ds = np.lib.npyio.DataSource(None)  # use with temporary file
+        >>> ds.open('/home/guido/foobar.txt')
+        <open file '/home/guido.foobar.txt', mode 'r' at 0x91d4430>
+        >>> ds.abspath('/home/guido/foobar.txt')
+        '/tmp/.../home/guido/foobar.txt'
+
+    """
+
+    def __init__(self, destpath=os.curdir):
+        """Create a DataSource with a local path at destpath."""
+        if destpath:
+            self._destpath = os.path.abspath(destpath)
+            self._istmpdest = False
+        else:
+            import tempfile  # deferring import to improve startup time
+            self._destpath = tempfile.mkdtemp()
+            self._istmpdest = True
+
+    def __del__(self):
+        # Remove temp directories
+        if hasattr(self, '_istmpdest') and self._istmpdest:
+            import shutil
+
+            shutil.rmtree(self._destpath)
+
+    def _iszip(self, filename):
+        """Test if the filename is a zip file by looking at the file extension.
+
+        """
+        fname, ext = os.path.splitext(filename)
+        return ext in _file_openers.keys()
+
+    def _iswritemode(self, mode):
+        """Test if the given mode will open a file for writing."""
+
+        # Currently only used to test the bz2 files.
+        _writemodes = ("w", "+")
+        return any(c in _writemodes for c in mode)
+
+    def _splitzipext(self, filename):
+        """Split zip extension from filename and return filename.
+
+        Returns
+        -------
+        base, zip_ext : {tuple}
+
+        """
+
+        if self._iszip(filename):
+            return os.path.splitext(filename)
+        else:
+            return filename, None
+
+    def _possible_names(self, filename):
+        """Return a tuple containing compressed filename variations."""
+        names = [filename]
+        if not self._iszip(filename):
+            for zipext in _file_openers.keys():
+                if zipext:
+                    names.append(filename + zipext)
+        return names
+
+    def _isurl(self, path):
+        """Test if path is a net location.  Tests the scheme and netloc."""
+
+        # We do this here to reduce the 'import numpy' initial import time.
+        from urllib.parse import urlparse
+
+        # BUG : URLs require a scheme string ('http://') to be used.
+        #       www.google.com will fail.
+        #       Should we prepend the scheme for those that don't have it and
+        #       test that also?  Similar to the way we append .gz and test for
+        #       for compressed versions of files.
+
+        scheme, netloc, upath, uparams, uquery, ufrag = urlparse(path)
+        return bool(scheme and netloc)
+
+    def _cache(self, path):
+        """Cache the file specified by path.
+
+        Creates a copy of the file in the datasource cache.
+
+        """
+        # We import these here because importing them is slow and
+        # a significant fraction of numpy's total import time.
+        import shutil
+        from urllib.request import urlopen
+
+        upath = self.abspath(path)
+
+        # ensure directory exists
+        if not os.path.exists(os.path.dirname(upath)):
+            os.makedirs(os.path.dirname(upath))
+
+        # TODO: Doesn't handle compressed files!
+        if self._isurl(path):
+            with urlopen(path) as openedurl:
+                with _open(upath, 'wb') as f:
+                    shutil.copyfileobj(openedurl, f)
+        else:
+            shutil.copyfile(path, upath)
+        return upath
+
+    def _findfile(self, path):
+        """Searches for ``path`` and returns full path if found.
+
+        If path is an URL, _findfile will cache a local copy and return the
+        path to the cached file.  If path is a local file, _findfile will
+        return a path to that local file.
+
+        The search will include possible compressed versions of the file
+        and return the first occurrence found.
+
+        """
+
+        # Build list of possible local file paths
+        if not self._isurl(path):
+            # Valid local paths
+            filelist = self._possible_names(path)
+            # Paths in self._destpath
+            filelist += self._possible_names(self.abspath(path))
+        else:
+            # Cached URLs in self._destpath
+            filelist = self._possible_names(self.abspath(path))
+            # Remote URLs
+            filelist = filelist + self._possible_names(path)
+
+        for name in filelist:
+            if self.exists(name):
+                if self._isurl(name):
+                    name = self._cache(name)
+                return name
+        return None
+
+    def abspath(self, path):
+        """
+        Return absolute path of file in the DataSource directory.
+
+        If `path` is an URL, then `abspath` will return either the location
+        the file exists locally or the location it would exist when opened
+        using the `open` method.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Can be a local file or a remote URL.
+
+        Returns
+        -------
+        out : str
+            Complete path, including the `DataSource` destination directory.
+
+        Notes
+        -----
+        The functionality is based on `os.path.abspath`.
+
+        """
+        # We do this here to reduce the 'import numpy' initial import time.
+        from urllib.parse import urlparse
+
+        # TODO:  This should be more robust.  Handles case where path includes
+        #        the destpath, but not other sub-paths. Failing case:
+        #        path = /home/guido/datafile.txt
+        #        destpath = /home/alex/
+        #        upath = self.abspath(path)
+        #        upath == '/home/alex/home/guido/datafile.txt'
+
+        # handle case where path includes self._destpath
+        splitpath = path.split(self._destpath, 2)
+        if len(splitpath) > 1:
+            path = splitpath[1]
+        scheme, netloc, upath, uparams, uquery, ufrag = urlparse(path)
+        netloc = self._sanitize_relative_path(netloc)
+        upath = self._sanitize_relative_path(upath)
+        return os.path.join(self._destpath, netloc, upath)
+
+    def _sanitize_relative_path(self, path):
+        """Return a sanitised relative path for which
+        os.path.abspath(os.path.join(base, path)).startswith(base)
+        """
+        last = None
+        path = os.path.normpath(path)
+        while path != last:
+            last = path
+            # Note: os.path.join treats '/' as os.sep on Windows
+            path = path.lstrip(os.sep).lstrip('/')
+            path = path.lstrip(os.pardir).removeprefix('..')
+            drive, path = os.path.splitdrive(path)  # for Windows
+        return path
+
+    def exists(self, path):
+        """
+        Test if path exists.
+
+        Test if `path` exists as (and in this order):
+
+        - a local file.
+        - a remote URL that has been downloaded and stored locally in the
+          `DataSource` directory.
+        - a remote URL that has not been downloaded, but is valid and
+          accessible.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Can be a local file or a remote URL.
+
+        Returns
+        -------
+        out : bool
+            True if `path` exists.
+
+        Notes
+        -----
+        When `path` is an URL, `exists` will return True if it's either
+        stored locally in the `DataSource` directory, or is a valid remote
+        URL.  `DataSource` does not discriminate between the two, the file
+        is accessible if it exists in either location.
+
+        """
+
+        # First test for local path
+        if os.path.exists(path):
+            return True
+
+        # We import this here because importing urllib is slow and
+        # a significant fraction of numpy's total import time.
+        from urllib.error import URLError
+        from urllib.request import urlopen
+
+        # Test cached url
+        upath = self.abspath(path)
+        if os.path.exists(upath):
+            return True
+
+        # Test remote url
+        if self._isurl(path):
+            try:
+                netfile = urlopen(path)
+                netfile.close()
+                del netfile
+                return True
+            except URLError:
+                return False
+        return False
+
+    def open(self, path, mode='r', encoding=None, newline=None):
+        """
+        Open and return file-like object.
+
+        If `path` is an URL, it will be downloaded, stored in the
+        `DataSource` directory and opened from there.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Local file path or URL to open.
+        mode : {'r', 'w', 'a'}, optional
+            Mode to open `path`.  Mode 'r' for reading, 'w' for writing,
+            'a' to append. Available modes depend on the type of object
+            specified by `path`. Default is 'r'.
+        encoding : {None, str}, optional
+            Open text file with given encoding. The default encoding will be
+            what `open` uses.
+        newline : {None, str}, optional
+            Newline to use when reading text file.
+
+        Returns
+        -------
+        out : file object
+            File object.
+
+        """
+
+        # TODO: There is no support for opening a file for writing which
+        #       doesn't exist yet (creating a file).  Should there be?
+
+        # TODO: Add a ``subdir`` parameter for specifying the subdirectory
+        #       used to store URLs in self._destpath.
+
+        if self._isurl(path) and self._iswritemode(mode):
+            raise ValueError("URLs are not writeable")
+
+        # NOTE: _findfile will fail on a new file opened for writing.
+        found = self._findfile(path)
+        if found:
+            _fname, ext = self._splitzipext(found)
+            if ext == 'bz2':
+                mode.replace("+", "")
+            return _file_openers[ext](found, mode=mode,
+                                      encoding=encoding, newline=newline)
+        else:
+            raise FileNotFoundError(f"{path} not found.")
+
+
+class Repository (DataSource):
+    """
+    Repository(baseurl, destpath='.')
+
+    A data repository where multiple DataSource's share a base
+    URL/directory.
+
+    `Repository` extends `DataSource` by prepending a base URL (or
+    directory) to all the files it handles. Use `Repository` when you will
+    be working with multiple files from one base URL.  Initialize
+    `Repository` with the base URL, then refer to each file by its filename
+    only.
+
+    Parameters
+    ----------
+    baseurl : str
+        Path to the local directory or remote location that contains the
+        data files.
+    destpath : str or None, optional
+        Path to the directory where the source file gets downloaded to for
+        use.  If `destpath` is None, a temporary directory will be created.
+        The default path is the current directory.
+
+    Examples
+    --------
+    To analyze all files in the repository, do something like this
+    (note: this is not self-contained code)::
+
+        >>> repos = np.lib._datasource.Repository('/home/user/data/dir/')
+        >>> for filename in filelist:
+        ...     fp = repos.open(filename)
+        ...     fp.analyze()
+        ...     fp.close()
+
+    Similarly you could use a URL for a repository::
+
+        >>> repos = np.lib._datasource.Repository('http://www.xyz.edu/data')
+
+    """
+
+    def __init__(self, baseurl, destpath=os.curdir):
+        """Create a Repository with a shared url or directory of baseurl."""
+        DataSource.__init__(self, destpath=destpath)
+        self._baseurl = baseurl
+
+    def __del__(self):
+        DataSource.__del__(self)
+
+    def _fullpath(self, path):
+        """Return complete path for path.  Prepends baseurl if necessary."""
+        splitpath = path.split(self._baseurl, 2)
+        if len(splitpath) == 1:
+            result = os.path.join(self._baseurl, path)
+        else:
+            result = path    # path contains baseurl already
+        return result
+
+    def _findfile(self, path):
+        """Extend DataSource method to prepend baseurl to ``path``."""
+        return DataSource._findfile(self, self._fullpath(path))
+
+    def abspath(self, path):
+        """
+        Return absolute path of file in the Repository directory.
+
+        If `path` is an URL, then `abspath` will return either the location
+        the file exists locally or the location it would exist when opened
+        using the `open` method.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Can be a local file or a remote URL. This may, but does not
+            have to, include the `baseurl` with which the `Repository` was
+            initialized.
+
+        Returns
+        -------
+        out : str
+            Complete path, including the `DataSource` destination directory.
+
+        """
+        return DataSource.abspath(self, self._fullpath(path))
+
+    def exists(self, path):
+        """
+        Test if path exists prepending Repository base URL to path.
+
+        Test if `path` exists as (and in this order):
+
+        - a local file.
+        - a remote URL that has been downloaded and stored locally in the
+          `DataSource` directory.
+        - a remote URL that has not been downloaded, but is valid and
+          accessible.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Can be a local file or a remote URL. This may, but does not
+            have to, include the `baseurl` with which the `Repository` was
+            initialized.
+
+        Returns
+        -------
+        out : bool
+            True if `path` exists.
+
+        Notes
+        -----
+        When `path` is an URL, `exists` will return True if it's either
+        stored locally in the `DataSource` directory, or is a valid remote
+        URL.  `DataSource` does not discriminate between the two, the file
+        is accessible if it exists in either location.
+
+        """
+        return DataSource.exists(self, self._fullpath(path))
+
+    def open(self, path, mode='r', encoding=None, newline=None):
+        """
+        Open and return file-like object prepending Repository base URL.
+
+        If `path` is an URL, it will be downloaded, stored in the
+        DataSource directory and opened from there.
+
+        Parameters
+        ----------
+        path : str or pathlib.Path
+            Local file path or URL to open. This may, but does not have to,
+            include the `baseurl` with which the `Repository` was
+            initialized.
+        mode : {'r', 'w', 'a'}, optional
+            Mode to open `path`.  Mode 'r' for reading, 'w' for writing,
+            'a' to append. Available modes depend on the type of object
+            specified by `path`. Default is 'r'.
+        encoding : {None, str}, optional
+            Open text file with given encoding. The default encoding will be
+            what `open` uses.
+        newline : {None, str}, optional
+            Newline to use when reading text file.
+
+        Returns
+        -------
+        out : file object
+            File object.
+
+        """
+        return DataSource.open(self, self._fullpath(path), mode,
+                               encoding=encoding, newline=newline)
+
+    def listdir(self):
+        """
+        List files in the source Repository.
+
+        Returns
+        -------
+        files : list of str or pathlib.Path
+            List of file names (not containing a directory part).
+
+        Notes
+        -----
+        Does not currently work for remote repositories.
+
+        """
+        if self._isurl(self._baseurl):
+            raise NotImplementedError(
+                  "Directory listing of URLs, not supported yet.")
+        else:
+            return os.listdir(self._baseurl)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_datasource.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_datasource.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..35631cf9f1f367107d89d3146f4e5bf4e6fd0ce2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_datasource.pyi
@@ -0,0 +1,30 @@
+from _typeshed import OpenBinaryMode, OpenTextMode
+from pathlib import Path
+from typing import IO, Any, TypeAlias
+
+_Mode: TypeAlias = OpenBinaryMode | OpenTextMode
+
+###
+
+# exported in numpy.lib.nppyio
+class DataSource:
+    def __init__(self, /, destpath: Path | str | None = ".") -> None: ...
+    def __del__(self, /) -> None: ...
+    def abspath(self, /, path: str) -> str: ...
+    def exists(self, /, path: str) -> bool: ...
+
+    # Whether the file-object is opened in string or bytes mode (by default)
+    # depends on the file-extension of `path`
+    def open(self, /, path: str, mode: _Mode = "r", encoding: str | None = None, newline: str | None = None) -> IO[Any]: ...
+
+class Repository(DataSource):
+    def __init__(self, /, baseurl: str, destpath: str | None = ".") -> None: ...
+    def listdir(self, /) -> list[str]: ...
+
+def open(
+    path: str,
+    mode: _Mode = "r",
+    destpath: str | None = ".",
+    encoding: str | None = None,
+    newline: str | None = None,
+) -> IO[Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..047806a2f115f6eabdf8e6702345c1fbf40cdc2e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.py
@@ -0,0 +1,1036 @@
+"""
+Binary serialization
+
+NPY format
+==========
+
+A simple format for saving numpy arrays to disk with the full
+information about them.
+
+The ``.npy`` format is the standard binary file format in NumPy for
+persisting a *single* arbitrary NumPy array on disk. The format stores all
+of the shape and dtype information necessary to reconstruct the array
+correctly even on another machine with a different architecture.
+The format is designed to be as simple as possible while achieving
+its limited goals.
+
+The ``.npz`` format is the standard format for persisting *multiple* NumPy
+arrays on disk. A ``.npz`` file is a zip file containing multiple ``.npy``
+files, one for each array.
+
+Capabilities
+------------
+
+- Can represent all NumPy arrays including nested record arrays and
+  object arrays.
+
+- Represents the data in its native binary form.
+
+- Supports Fortran-contiguous arrays directly.
+
+- Stores all of the necessary information to reconstruct the array
+  including shape and dtype on a machine of a different
+  architecture.  Both little-endian and big-endian arrays are
+  supported, and a file with little-endian numbers will yield
+  a little-endian array on any machine reading the file. The
+  types are described in terms of their actual sizes. For example,
+  if a machine with a 64-bit C "long int" writes out an array with
+  "long ints", a reading machine with 32-bit C "long ints" will yield
+  an array with 64-bit integers.
+
+- Is straightforward to reverse engineer. Datasets often live longer than
+  the programs that created them. A competent developer should be
+  able to create a solution in their preferred programming language to
+  read most ``.npy`` files that they have been given without much
+  documentation.
+
+- Allows memory-mapping of the data. See `open_memmap`.
+
+- Can be read from a filelike stream object instead of an actual file.
+
+- Stores object arrays, i.e. arrays containing elements that are arbitrary
+  Python objects. Files with object arrays are not to be mmapable, but
+  can be read and written to disk.
+
+Limitations
+-----------
+
+- Arbitrary subclasses of numpy.ndarray are not completely preserved.
+  Subclasses will be accepted for writing, but only the array data will
+  be written out. A regular numpy.ndarray object will be created
+  upon reading the file.
+
+.. warning::
+
+  Due to limitations in the interpretation of structured dtypes, dtypes
+  with fields with empty names will have the names replaced by 'f0', 'f1',
+  etc. Such arrays will not round-trip through the format entirely
+  accurately. The data is intact; only the field names will differ. We are
+  working on a fix for this. This fix will not require a change in the
+  file format. The arrays with such structures can still be saved and
+  restored, and the correct dtype may be restored by using the
+  ``loadedarray.view(correct_dtype)`` method.
+
+File extensions
+---------------
+
+We recommend using the ``.npy`` and ``.npz`` extensions for files saved
+in this format. This is by no means a requirement; applications may wish
+to use these file formats but use an extension specific to the
+application. In the absence of an obvious alternative, however,
+we suggest using ``.npy`` and ``.npz``.
+
+Version numbering
+-----------------
+
+The version numbering of these formats is independent of NumPy version
+numbering. If the format is upgraded, the code in `numpy.io` will still
+be able to read and write Version 1.0 files.
+
+Format Version 1.0
+------------------
+
+The first 6 bytes are a magic string: exactly ``\\x93NUMPY``.
+
+The next 1 byte is an unsigned byte: the major version number of the file
+format, e.g. ``\\x01``.
+
+The next 1 byte is an unsigned byte: the minor version number of the file
+format, e.g. ``\\x00``. Note: the version of the file format is not tied
+to the version of the numpy package.
+
+The next 2 bytes form a little-endian unsigned short int: the length of
+the header data HEADER_LEN.
+
+The next HEADER_LEN bytes form the header data describing the array's
+format. It is an ASCII string which contains a Python literal expression
+of a dictionary. It is terminated by a newline (``\\n``) and padded with
+spaces (``\\x20``) to make the total of
+``len(magic string) + 2 + len(length) + HEADER_LEN`` be evenly divisible
+by 64 for alignment purposes.
+
+The dictionary contains three keys:
+
+    "descr" : dtype.descr
+      An object that can be passed as an argument to the `numpy.dtype`
+      constructor to create the array's dtype.
+    "fortran_order" : bool
+      Whether the array data is Fortran-contiguous or not. Since
+      Fortran-contiguous arrays are a common form of non-C-contiguity,
+      we allow them to be written directly to disk for efficiency.
+    "shape" : tuple of int
+      The shape of the array.
+
+For repeatability and readability, the dictionary keys are sorted in
+alphabetic order. This is for convenience only. A writer SHOULD implement
+this if possible. A reader MUST NOT depend on this.
+
+Following the header comes the array data. If the dtype contains Python
+objects (i.e. ``dtype.hasobject is True``), then the data is a Python
+pickle of the array. Otherwise the data is the contiguous (either C-
+or Fortran-, depending on ``fortran_order``) bytes of the array.
+Consumers can figure out the number of bytes by multiplying the number
+of elements given by the shape (noting that ``shape=()`` means there is
+1 element) by ``dtype.itemsize``.
+
+Format Version 2.0
+------------------
+
+The version 1.0 format only allowed the array header to have a total size of
+65535 bytes.  This can be exceeded by structured arrays with a large number of
+columns.  The version 2.0 format extends the header size to 4 GiB.
+`numpy.save` will automatically save in 2.0 format if the data requires it,
+else it will always use the more compatible 1.0 format.
+
+The description of the fourth element of the header therefore has become:
+"The next 4 bytes form a little-endian unsigned int: the length of the header
+data HEADER_LEN."
+
+Format Version 3.0
+------------------
+
+This version replaces the ASCII string (which in practice was latin1) with
+a utf8-encoded string, so supports structured types with any unicode field
+names.
+
+Notes
+-----
+The ``.npy`` format, including motivation for creating it and a comparison of
+alternatives, is described in the
+:doc:`"npy-format" NEP <neps:nep-0001-npy-format>`, however details have
+evolved with time and this document is more current.
+
+"""
+import io
+import os
+import pickle
+import warnings
+
+import numpy
+from numpy._utils import set_module
+from numpy.lib._utils_impl import drop_metadata
+
+__all__ = []
+
+drop_metadata.__module__ = "numpy.lib.format"
+
+EXPECTED_KEYS = {'descr', 'fortran_order', 'shape'}
+MAGIC_PREFIX = b'\x93NUMPY'
+MAGIC_LEN = len(MAGIC_PREFIX) + 2
+ARRAY_ALIGN = 64  # plausible values are powers of 2 between 16 and 4096
+BUFFER_SIZE = 2**18  # size of buffer for reading npz files in bytes
+# allow growth within the address space of a 64 bit machine along one axis
+GROWTH_AXIS_MAX_DIGITS = 21  # = len(str(8*2**64-1)) hypothetical int1 dtype
+
+# difference between version 1.0 and 2.0 is a 4 byte (I) header length
+# instead of 2 bytes (H) allowing storage of large structured arrays
+_header_size_info = {
+    (1, 0): ('<H', 'latin1'),
+    (2, 0): ('<I', 'latin1'),
+    (3, 0): ('<I', 'utf8'),
+}
+
+# Python's literal_eval is not actually safe for large inputs, since parsing
+# may become slow or even cause interpreter crashes.
+# This is an arbitrary, low limit which should make it safe in practice.
+_MAX_HEADER_SIZE = 10000
+
+
+def _check_version(version):
+    if version not in [(1, 0), (2, 0), (3, 0), None]:
+        msg = "we only support format version (1,0), (2,0), and (3,0), not %s"
+        raise ValueError(msg % (version,))
+
+
+@set_module("numpy.lib.format")
+def magic(major, minor):
+    """ Return the magic string for the given file format version.
+
+    Parameters
+    ----------
+    major : int in [0, 255]
+    minor : int in [0, 255]
+
+    Returns
+    -------
+    magic : str
+
+    Raises
+    ------
+    ValueError if the version cannot be formatted.
+    """
+    if major < 0 or major > 255:
+        raise ValueError("major version must be 0 <= major < 256")
+    if minor < 0 or minor > 255:
+        raise ValueError("minor version must be 0 <= minor < 256")
+    return MAGIC_PREFIX + bytes([major, minor])
+
+
+@set_module("numpy.lib.format")
+def read_magic(fp):
+    """ Read the magic string to get the version of the file format.
+
+    Parameters
+    ----------
+    fp : filelike object
+
+    Returns
+    -------
+    major : int
+    minor : int
+    """
+    magic_str = _read_bytes(fp, MAGIC_LEN, "magic string")
+    if magic_str[:-2] != MAGIC_PREFIX:
+        msg = "the magic string is not correct; expected %r, got %r"
+        raise ValueError(msg % (MAGIC_PREFIX, magic_str[:-2]))
+    major, minor = magic_str[-2:]
+    return major, minor
+
+
+@set_module("numpy.lib.format")
+def dtype_to_descr(dtype):
+    """
+    Get a serializable descriptor from the dtype.
+
+    The .descr attribute of a dtype object cannot be round-tripped through
+    the dtype() constructor. Simple types, like dtype('float32'), have
+    a descr which looks like a record array with one field with '' as
+    a name. The dtype() constructor interprets this as a request to give
+    a default name.  Instead, we construct descriptor that can be passed to
+    dtype().
+
+    Parameters
+    ----------
+    dtype : dtype
+        The dtype of the array that will be written to disk.
+
+    Returns
+    -------
+    descr : object
+        An object that can be passed to `numpy.dtype()` in order to
+        replicate the input dtype.
+
+    """
+    # NOTE: that drop_metadata may not return the right dtype e.g. for user
+    #       dtypes.  In that case our code below would fail the same, though.
+    new_dtype = drop_metadata(dtype)
+    if new_dtype is not dtype:
+        warnings.warn("metadata on a dtype is not saved to an npy/npz. "
+                      "Use another format (such as pickle) to store it.",
+                      UserWarning, stacklevel=2)
+    dtype = new_dtype
+
+    if dtype.names is not None:
+        # This is a record array. The .descr is fine.  XXX: parts of the
+        # record array with an empty name, like padding bytes, still get
+        # fiddled with. This needs to be fixed in the C implementation of
+        # dtype().
+        return dtype.descr
+    elif not type(dtype)._legacy:
+        # this must be a user-defined dtype since numpy does not yet expose any
+        # non-legacy dtypes in the public API
+        #
+        # non-legacy dtypes don't yet have __array_interface__
+        # support. Instead, as a hack, we use pickle to save the array, and lie
+        # that the dtype is object. When the array is loaded, the descriptor is
+        # unpickled with the array and the object dtype in the header is
+        # discarded.
+        #
+        # a future NEP should define a way to serialize user-defined
+        # descriptors and ideally work out the possible security implications
+        warnings.warn("Custom dtypes are saved as python objects using the "
+                      "pickle protocol. Loading this file requires "
+                      "allow_pickle=True to be set.",
+                      UserWarning, stacklevel=2)
+        return "|O"
+    else:
+        return dtype.str
+
+
+@set_module("numpy.lib.format")
+def descr_to_dtype(descr):
+    """
+    Returns a dtype based off the given description.
+
+    This is essentially the reverse of `~lib.format.dtype_to_descr`. It will
+    remove the valueless padding fields created by, i.e. simple fields like
+    dtype('float32'), and then convert the description to its corresponding
+    dtype.
+
+    Parameters
+    ----------
+    descr : object
+        The object retrieved by dtype.descr. Can be passed to
+        `numpy.dtype` in order to replicate the input dtype.
+
+    Returns
+    -------
+    dtype : dtype
+        The dtype constructed by the description.
+
+    """
+    if isinstance(descr, str):
+        # No padding removal needed
+        return numpy.dtype(descr)
+    elif isinstance(descr, tuple):
+        # subtype, will always have a shape descr[1]
+        dt = descr_to_dtype(descr[0])
+        return numpy.dtype((dt, descr[1]))
+
+    titles = []
+    names = []
+    formats = []
+    offsets = []
+    offset = 0
+    for field in descr:
+        if len(field) == 2:
+            name, descr_str = field
+            dt = descr_to_dtype(descr_str)
+        else:
+            name, descr_str, shape = field
+            dt = numpy.dtype((descr_to_dtype(descr_str), shape))
+
+        # Ignore padding bytes, which will be void bytes with '' as name
+        # Once support for blank names is removed, only "if name == ''" needed)
+        is_pad = (name == '' and dt.type is numpy.void and dt.names is None)
+        if not is_pad:
+            title, name = name if isinstance(name, tuple) else (None, name)
+            titles.append(title)
+            names.append(name)
+            formats.append(dt)
+            offsets.append(offset)
+        offset += dt.itemsize
+
+    return numpy.dtype({'names': names, 'formats': formats, 'titles': titles,
+                        'offsets': offsets, 'itemsize': offset})
+
+
+@set_module("numpy.lib.format")
+def header_data_from_array_1_0(array):
+    """ Get the dictionary of header metadata from a numpy.ndarray.
+
+    Parameters
+    ----------
+    array : numpy.ndarray
+
+    Returns
+    -------
+    d : dict
+        This has the appropriate entries for writing its string representation
+        to the header of the file.
+    """
+    d = {'shape': array.shape}
+    if array.flags.c_contiguous:
+        d['fortran_order'] = False
+    elif array.flags.f_contiguous:
+        d['fortran_order'] = True
+    else:
+        # Totally non-contiguous data. We will have to make it C-contiguous
+        # before writing. Note that we need to test for C_CONTIGUOUS first
+        # because a 1-D array is both C_CONTIGUOUS and F_CONTIGUOUS.
+        d['fortran_order'] = False
+
+    d['descr'] = dtype_to_descr(array.dtype)
+    return d
+
+
+def _wrap_header(header, version):
+    """
+    Takes a stringified header, and attaches the prefix and padding to it
+    """
+    import struct
+    assert version is not None
+    fmt, encoding = _header_size_info[version]
+    header = header.encode(encoding)
+    hlen = len(header) + 1
+    padlen = ARRAY_ALIGN - ((MAGIC_LEN + struct.calcsize(fmt) + hlen) % ARRAY_ALIGN)
+    try:
+        header_prefix = magic(*version) + struct.pack(fmt, hlen + padlen)
+    except struct.error:
+        msg = f"Header length {hlen} too big for version={version}"
+        raise ValueError(msg) from None
+
+    # Pad the header with spaces and a final newline such that the magic
+    # string, the header-length short and the header are aligned on a
+    # ARRAY_ALIGN byte boundary.  This supports memory mapping of dtypes
+    # aligned up to ARRAY_ALIGN on systems like Linux where mmap()
+    # offset must be page-aligned (i.e. the beginning of the file).
+    return header_prefix + header + b' ' * padlen + b'\n'
+
+
+def _wrap_header_guess_version(header):
+    """
+    Like `_wrap_header`, but chooses an appropriate version given the contents
+    """
+    try:
+        return _wrap_header(header, (1, 0))
+    except ValueError:
+        pass
+
+    try:
+        ret = _wrap_header(header, (2, 0))
+    except UnicodeEncodeError:
+        pass
+    else:
+        warnings.warn("Stored array in format 2.0. It can only be"
+                      "read by NumPy >= 1.9", UserWarning, stacklevel=2)
+        return ret
+
+    header = _wrap_header(header, (3, 0))
+    warnings.warn("Stored array in format 3.0. It can only be "
+                  "read by NumPy >= 1.17", UserWarning, stacklevel=2)
+    return header
+
+
+def _write_array_header(fp, d, version=None):
+    """ Write the header for an array and returns the version used
+
+    Parameters
+    ----------
+    fp : filelike object
+    d : dict
+        This has the appropriate entries for writing its string representation
+        to the header of the file.
+    version : tuple or None
+        None means use oldest that works. Providing an explicit version will
+        raise a ValueError if the format does not allow saving this data.
+        Default: None
+    """
+    header = ["{"]
+    for key, value in sorted(d.items()):
+        # Need to use repr here, since we eval these when reading
+        header.append(f"'{key}': {repr(value)}, ")
+    header.append("}")
+    header = "".join(header)
+
+    # Add some spare space so that the array header can be modified in-place
+    # when changing the array size, e.g. when growing it by appending data at
+    # the end.
+    shape = d['shape']
+    header += " " * ((GROWTH_AXIS_MAX_DIGITS - len(repr(
+        shape[-1 if d['fortran_order'] else 0]
+    ))) if len(shape) > 0 else 0)
+
+    if version is None:
+        header = _wrap_header_guess_version(header)
+    else:
+        header = _wrap_header(header, version)
+    fp.write(header)
+
+
+@set_module("numpy.lib.format")
+def write_array_header_1_0(fp, d):
+    """ Write the header for an array using the 1.0 format.
+
+    Parameters
+    ----------
+    fp : filelike object
+    d : dict
+        This has the appropriate entries for writing its string
+        representation to the header of the file.
+    """
+    _write_array_header(fp, d, (1, 0))
+
+
+@set_module("numpy.lib.format")
+def write_array_header_2_0(fp, d):
+    """ Write the header for an array using the 2.0 format.
+        The 2.0 format allows storing very large structured arrays.
+
+    Parameters
+    ----------
+    fp : filelike object
+    d : dict
+        This has the appropriate entries for writing its string
+        representation to the header of the file.
+    """
+    _write_array_header(fp, d, (2, 0))
+
+
+@set_module("numpy.lib.format")
+def read_array_header_1_0(fp, max_header_size=_MAX_HEADER_SIZE):
+    """
+    Read an array header from a filelike object using the 1.0 file format
+    version.
+
+    This will leave the file object located just after the header.
+
+    Parameters
+    ----------
+    fp : filelike object
+        A file object or something with a `.read()` method like a file.
+
+    Returns
+    -------
+    shape : tuple of int
+        The shape of the array.
+    fortran_order : bool
+        The array data will be written out directly if it is either
+        C-contiguous or Fortran-contiguous. Otherwise, it will be made
+        contiguous before writing it out.
+    dtype : dtype
+        The dtype of the file's data.
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+
+    Raises
+    ------
+    ValueError
+        If the data is invalid.
+
+    """
+    return _read_array_header(
+            fp, version=(1, 0), max_header_size=max_header_size)
+
+
+@set_module("numpy.lib.format")
+def read_array_header_2_0(fp, max_header_size=_MAX_HEADER_SIZE):
+    """
+    Read an array header from a filelike object using the 2.0 file format
+    version.
+
+    This will leave the file object located just after the header.
+
+    Parameters
+    ----------
+    fp : filelike object
+        A file object or something with a `.read()` method like a file.
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+
+    Returns
+    -------
+    shape : tuple of int
+        The shape of the array.
+    fortran_order : bool
+        The array data will be written out directly if it is either
+        C-contiguous or Fortran-contiguous. Otherwise, it will be made
+        contiguous before writing it out.
+    dtype : dtype
+        The dtype of the file's data.
+
+    Raises
+    ------
+    ValueError
+        If the data is invalid.
+
+    """
+    return _read_array_header(
+            fp, version=(2, 0), max_header_size=max_header_size)
+
+
+def _filter_header(s):
+    """Clean up 'L' in npz header ints.
+
+    Cleans up the 'L' in strings representing integers. Needed to allow npz
+    headers produced in Python2 to be read in Python3.
+
+    Parameters
+    ----------
+    s : string
+        Npy file header.
+
+    Returns
+    -------
+    header : str
+        Cleaned up header.
+
+    """
+    import tokenize
+    from io import StringIO
+
+    tokens = []
+    last_token_was_number = False
+    for token in tokenize.generate_tokens(StringIO(s).readline):
+        token_type = token[0]
+        token_string = token[1]
+        if (last_token_was_number and
+                token_type == tokenize.NAME and
+                token_string == "L"):
+            continue
+        else:
+            tokens.append(token)
+        last_token_was_number = (token_type == tokenize.NUMBER)
+    return tokenize.untokenize(tokens)
+
+
+def _read_array_header(fp, version, max_header_size=_MAX_HEADER_SIZE):
+    """
+    see read_array_header_1_0
+    """
+    # Read an unsigned, little-endian short int which has the length of the
+    # header.
+    import ast
+    import struct
+    hinfo = _header_size_info.get(version)
+    if hinfo is None:
+        raise ValueError(f"Invalid version {version!r}")
+    hlength_type, encoding = hinfo
+
+    hlength_str = _read_bytes(fp, struct.calcsize(hlength_type), "array header length")
+    header_length = struct.unpack(hlength_type, hlength_str)[0]
+    header = _read_bytes(fp, header_length, "array header")
+    header = header.decode(encoding)
+    if len(header) > max_header_size:
+        raise ValueError(
+            f"Header info length ({len(header)}) is large and may not be safe "
+            "to load securely.\n"
+            "To allow loading, adjust `max_header_size` or fully trust "
+            "the `.npy` file using `allow_pickle=True`.\n"
+            "For safety against large resource use or crashes, sandboxing "
+            "may be necessary.")
+
+    # The header is a pretty-printed string representation of a literal
+    # Python dictionary with trailing newlines padded to an ARRAY_ALIGN byte
+    # boundary. The keys are strings.
+    #   "shape" : tuple of int
+    #   "fortran_order" : bool
+    #   "descr" : dtype.descr
+    # Versions (2, 0) and (1, 0) could have been created by a Python 2
+    # implementation before header filtering was implemented.
+    #
+    # For performance reasons, we try without _filter_header first though
+    try:
+        d = ast.literal_eval(header)
+    except SyntaxError as e:
+        if version <= (2, 0):
+            header = _filter_header(header)
+            try:
+                d = ast.literal_eval(header)
+            except SyntaxError as e2:
+                msg = "Cannot parse header: {!r}"
+                raise ValueError(msg.format(header)) from e2
+            else:
+                warnings.warn(
+                    "Reading `.npy` or `.npz` file required additional "
+                    "header parsing as it was created on Python 2. Save the "
+                    "file again to speed up loading and avoid this warning.",
+                    UserWarning, stacklevel=4)
+        else:
+            msg = "Cannot parse header: {!r}"
+            raise ValueError(msg.format(header)) from e
+    if not isinstance(d, dict):
+        msg = "Header is not a dictionary: {!r}"
+        raise ValueError(msg.format(d))
+
+    if EXPECTED_KEYS != d.keys():
+        keys = sorted(d.keys())
+        msg = "Header does not contain the correct keys: {!r}"
+        raise ValueError(msg.format(keys))
+
+    # Sanity-check the values.
+    if (not isinstance(d['shape'], tuple) or
+            not all(isinstance(x, int) for x in d['shape'])):
+        msg = "shape is not valid: {!r}"
+        raise ValueError(msg.format(d['shape']))
+    if not isinstance(d['fortran_order'], bool):
+        msg = "fortran_order is not a valid bool: {!r}"
+        raise ValueError(msg.format(d['fortran_order']))
+    try:
+        dtype = descr_to_dtype(d['descr'])
+    except TypeError as e:
+        msg = "descr is not a valid dtype descriptor: {!r}"
+        raise ValueError(msg.format(d['descr'])) from e
+
+    return d['shape'], d['fortran_order'], dtype
+
+
+@set_module("numpy.lib.format")
+def write_array(fp, array, version=None, allow_pickle=True, pickle_kwargs=None):
+    """
+    Write an array to an NPY file, including a header.
+
+    If the array is neither C-contiguous nor Fortran-contiguous AND the
+    file_like object is not a real file object, this function will have to
+    copy data in memory.
+
+    Parameters
+    ----------
+    fp : file_like object
+        An open, writable file object, or similar object with a
+        ``.write()`` method.
+    array : ndarray
+        The array to write to disk.
+    version : (int, int) or None, optional
+        The version number of the format. None means use the oldest
+        supported version that is able to store the data.  Default: None
+    allow_pickle : bool, optional
+        Whether to allow writing pickled data. Default: True
+    pickle_kwargs : dict, optional
+        Additional keyword arguments to pass to pickle.dump, excluding
+        'protocol'. These are only useful when pickling objects in object
+        arrays to Python 2 compatible format.
+
+    Raises
+    ------
+    ValueError
+        If the array cannot be persisted. This includes the case of
+        allow_pickle=False and array being an object array.
+    Various other errors
+        If the array contains Python objects as part of its dtype, the
+        process of pickling them may raise various errors if the objects
+        are not picklable.
+
+    """
+    _check_version(version)
+    _write_array_header(fp, header_data_from_array_1_0(array), version)
+
+    if array.itemsize == 0:
+        buffersize = 0
+    else:
+        # Set buffer size to 16 MiB to hide the Python loop overhead.
+        buffersize = max(16 * 1024 ** 2 // array.itemsize, 1)
+
+    dtype_class = type(array.dtype)
+
+    if array.dtype.hasobject or not dtype_class._legacy:
+        # We contain Python objects so we cannot write out the data
+        # directly.  Instead, we will pickle it out
+        if not allow_pickle:
+            if array.dtype.hasobject:
+                raise ValueError("Object arrays cannot be saved when "
+                                 "allow_pickle=False")
+            if not dtype_class._legacy:
+                raise ValueError("User-defined dtypes cannot be saved "
+                                 "when allow_pickle=False")
+        if pickle_kwargs is None:
+            pickle_kwargs = {}
+        pickle.dump(array, fp, protocol=4, **pickle_kwargs)
+    elif array.flags.f_contiguous and not array.flags.c_contiguous:
+        if isfileobj(fp):
+            array.T.tofile(fp)
+        else:
+            for chunk in numpy.nditer(
+                    array, flags=['external_loop', 'buffered', 'zerosize_ok'],
+                    buffersize=buffersize, order='F'):
+                fp.write(chunk.tobytes('C'))
+    elif isfileobj(fp):
+        array.tofile(fp)
+    else:
+        for chunk in numpy.nditer(
+                array, flags=['external_loop', 'buffered', 'zerosize_ok'],
+                buffersize=buffersize, order='C'):
+            fp.write(chunk.tobytes('C'))
+
+
+@set_module("numpy.lib.format")
+def read_array(fp, allow_pickle=False, pickle_kwargs=None, *,
+               max_header_size=_MAX_HEADER_SIZE):
+    """
+    Read an array from an NPY file.
+
+    Parameters
+    ----------
+    fp : file_like object
+        If this is not a real file object, then this may take extra memory
+        and time.
+    allow_pickle : bool, optional
+        Whether to allow writing pickled data. Default: False
+    pickle_kwargs : dict
+        Additional keyword arguments to pass to pickle.load. These are only
+        useful when loading object arrays saved on Python 2.
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+        This option is ignored when `allow_pickle` is passed.  In that case
+        the file is by definition trusted and the limit is unnecessary.
+
+    Returns
+    -------
+    array : ndarray
+        The array from the data on disk.
+
+    Raises
+    ------
+    ValueError
+        If the data is invalid, or allow_pickle=False and the file contains
+        an object array.
+
+    """
+    if allow_pickle:
+        # Effectively ignore max_header_size, since `allow_pickle` indicates
+        # that the input is fully trusted.
+        max_header_size = 2**64
+
+    version = read_magic(fp)
+    _check_version(version)
+    shape, fortran_order, dtype = _read_array_header(
+            fp, version, max_header_size=max_header_size)
+    if len(shape) == 0:
+        count = 1
+    else:
+        count = numpy.multiply.reduce(shape, dtype=numpy.int64)
+
+    # Now read the actual data.
+    if dtype.hasobject:
+        # The array contained Python objects. We need to unpickle the data.
+        if not allow_pickle:
+            raise ValueError("Object arrays cannot be loaded when "
+                             "allow_pickle=False")
+        if pickle_kwargs is None:
+            pickle_kwargs = {}
+        try:
+            array = pickle.load(fp, **pickle_kwargs)
+        except UnicodeError as err:
+            # Friendlier error message
+            raise UnicodeError("Unpickling a python object failed: %r\n"
+                               "You may need to pass the encoding= option "
+                               "to numpy.load" % (err,)) from err
+    else:
+        if isfileobj(fp):
+            # We can use the fast fromfile() function.
+            array = numpy.fromfile(fp, dtype=dtype, count=count)
+        else:
+            # This is not a real file. We have to read it the
+            # memory-intensive way.
+            # crc32 module fails on reads greater than 2 ** 32 bytes,
+            # breaking large reads from gzip streams. Chunk reads to
+            # BUFFER_SIZE bytes to avoid issue and reduce memory overhead
+            # of the read. In non-chunked case count < max_read_count, so
+            # only one read is performed.
+
+            # Use np.ndarray instead of np.empty since the latter does
+            # not correctly instantiate zero-width string dtypes; see
+            # https://github.com/numpy/numpy/pull/6430
+            array = numpy.ndarray(count, dtype=dtype)
+
+            if dtype.itemsize > 0:
+                # If dtype.itemsize == 0 then there's nothing more to read
+                max_read_count = BUFFER_SIZE // min(BUFFER_SIZE, dtype.itemsize)
+
+                for i in range(0, count, max_read_count):
+                    read_count = min(max_read_count, count - i)
+                    read_size = int(read_count * dtype.itemsize)
+                    data = _read_bytes(fp, read_size, "array data")
+                    array[i:i + read_count] = numpy.frombuffer(data, dtype=dtype,
+                                                             count=read_count)
+
+        if array.size != count:
+            raise ValueError(
+                "Failed to read all data for array. "
+                f"Expected {shape} = {count} elements, "
+                f"could only read {array.size} elements. "
+                "(file seems not fully written?)"
+            )
+
+        if fortran_order:
+            array = array.reshape(shape[::-1])
+            array = array.transpose()
+        else:
+            array = array.reshape(shape)
+
+    return array
+
+
+@set_module("numpy.lib.format")
+def open_memmap(filename, mode='r+', dtype=None, shape=None,
+                fortran_order=False, version=None, *,
+                max_header_size=_MAX_HEADER_SIZE):
+    """
+    Open a .npy file as a memory-mapped array.
+
+    This may be used to read an existing file or create a new one.
+
+    Parameters
+    ----------
+    filename : str or path-like
+        The name of the file on disk.  This may *not* be a file-like
+        object.
+    mode : str, optional
+        The mode in which to open the file; the default is 'r+'.  In
+        addition to the standard file modes, 'c' is also accepted to mean
+        "copy on write."  See `memmap` for the available mode strings.
+    dtype : data-type, optional
+        The data type of the array if we are creating a new file in "write"
+        mode, if not, `dtype` is ignored.  The default value is None, which
+        results in a data-type of `float64`.
+    shape : tuple of int
+        The shape of the array if we are creating a new file in "write"
+        mode, in which case this parameter is required.  Otherwise, this
+        parameter is ignored and is thus optional.
+    fortran_order : bool, optional
+        Whether the array should be Fortran-contiguous (True) or
+        C-contiguous (False, the default) if we are creating a new file in
+        "write" mode.
+    version : tuple of int (major, minor) or None
+        If the mode is a "write" mode, then this is the version of the file
+        format used to create the file.  None means use the oldest
+        supported version that is able to store the data.  Default: None
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+
+    Returns
+    -------
+    marray : memmap
+        The memory-mapped array.
+
+    Raises
+    ------
+    ValueError
+        If the data or the mode is invalid.
+    OSError
+        If the file is not found or cannot be opened correctly.
+
+    See Also
+    --------
+    numpy.memmap
+
+    """
+    if isfileobj(filename):
+        raise ValueError("Filename must be a string or a path-like object."
+                         "  Memmap cannot use existing file handles.")
+
+    if 'w' in mode:
+        # We are creating the file, not reading it.
+        # Check if we ought to create the file.
+        _check_version(version)
+        # Ensure that the given dtype is an authentic dtype object rather
+        # than just something that can be interpreted as a dtype object.
+        dtype = numpy.dtype(dtype)
+        if dtype.hasobject:
+            msg = "Array can't be memory-mapped: Python objects in dtype."
+            raise ValueError(msg)
+        d = {
+            "descr": dtype_to_descr(dtype),
+            "fortran_order": fortran_order,
+            "shape": shape,
+        }
+        # If we got here, then it should be safe to create the file.
+        with open(os.fspath(filename), mode + 'b') as fp:
+            _write_array_header(fp, d, version)
+            offset = fp.tell()
+    else:
+        # Read the header of the file first.
+        with open(os.fspath(filename), 'rb') as fp:
+            version = read_magic(fp)
+            _check_version(version)
+
+            shape, fortran_order, dtype = _read_array_header(
+                    fp, version, max_header_size=max_header_size)
+            if dtype.hasobject:
+                msg = "Array can't be memory-mapped: Python objects in dtype."
+                raise ValueError(msg)
+            offset = fp.tell()
+
+    if fortran_order:
+        order = 'F'
+    else:
+        order = 'C'
+
+    # We need to change a write-only mode to a read-write mode since we've
+    # already written data to the file.
+    if mode == 'w+':
+        mode = 'r+'
+
+    marray = numpy.memmap(filename, dtype=dtype, shape=shape, order=order,
+        mode=mode, offset=offset)
+
+    return marray
+
+
+def _read_bytes(fp, size, error_template="ran out of data"):
+    """
+    Read from file-like object until size bytes are read.
+    Raises ValueError if not EOF is encountered before size bytes are read.
+    Non-blocking objects only supported if they derive from io objects.
+
+    Required as e.g. ZipExtFile in python 2.6 can return less data than
+    requested.
+    """
+    data = b""
+    while True:
+        # io files (default in python3) return None or raise on
+        # would-block, python2 file will truncate, probably nothing can be
+        # done about that.  note that regular files can't be non-blocking
+        try:
+            r = fp.read(size - len(data))
+            data += r
+            if len(r) == 0 or len(data) == size:
+                break
+        except BlockingIOError:
+            pass
+    if len(data) != size:
+        msg = "EOF: reading %s, expected %d bytes got %d"
+        raise ValueError(msg % (error_template, size, len(data)))
+    else:
+        return data
+
+
+@set_module("numpy.lib.format")
+def isfileobj(f):
+    if not isinstance(f, (io.FileIO, io.BufferedReader, io.BufferedWriter)):
+        return False
+    try:
+        # BufferedReader/Writer may raise OSError when
+        # fetching `fileno()` (e.g. when wrapping BytesIO).
+        f.fileno()
+        return True
+    except OSError:
+        return False
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..06d49d3eaaf293f8fd7420d0309c3cfe890446f6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_format_impl.pyi
@@ -0,0 +1,56 @@
+import os
+from _typeshed import SupportsRead, SupportsWrite
+from typing import Any, BinaryIO, Final, TypeAlias, TypeGuard
+
+import numpy as np
+import numpy.typing as npt
+from numpy.lib._utils_impl import drop_metadata as drop_metadata
+
+__all__: list[str] = []
+
+_DTypeDescr: TypeAlias = list[tuple[str, str]] | list[tuple[str, str, tuple[int, ...]]]
+
+###
+
+EXPECTED_KEYS: Final[set[str]] = ...
+MAGIC_PREFIX: Final = b"\x93NUMPY"
+MAGIC_LEN: Final = 8
+ARRAY_ALIGN: Final = 64
+BUFFER_SIZE: Final = 262_144  # 1 << 18
+GROWTH_AXIS_MAX_DIGITS: Final = 21
+_MAX_HEADER_SIZE: Final = 10_000
+
+def magic(major: int, minor: int) -> bytes: ...
+def read_magic(fp: SupportsRead[bytes]) -> tuple[int, int]: ...
+def dtype_to_descr(dtype: np.dtype) -> _DTypeDescr: ...
+def descr_to_dtype(descr: _DTypeDescr) -> np.dtype: ...
+def header_data_from_array_1_0(array: np.ndarray) -> dict[str, Any]: ...
+def write_array_header_1_0(fp: SupportsWrite[bytes], d: dict[str, Any]) -> None: ...
+def write_array_header_2_0(fp: SupportsWrite[bytes], d: dict[str, Any]) -> None: ...
+def read_array_header_1_0(fp: SupportsRead[bytes], max_header_size: int = 10_000) -> tuple[tuple[int, ...], bool, np.dtype]: ...
+def read_array_header_2_0(fp: SupportsRead[bytes], max_header_size: int = 10_000) -> tuple[tuple[int, ...], bool, np.dtype]: ...
+def write_array(
+    fp: SupportsWrite[bytes],
+    array: np.ndarray,
+    version: tuple[int, int] | None = None,
+    allow_pickle: bool = True,
+    pickle_kwargs: dict[str, Any] | None = None,
+) -> None: ...
+def read_array(
+    fp: SupportsRead[bytes],
+    allow_pickle: bool = False,
+    pickle_kwargs: dict[str, Any] | None = None,
+    *,
+    max_header_size: int = 10_000,
+) -> np.ndarray: ...
+def open_memmap(
+    filename: str | os.PathLike[Any],
+    mode: str = "r+",
+    dtype: npt.DTypeLike | None = None,
+    shape: tuple[int, ...] | None = None,
+    fortran_order: bool = False,
+    version: tuple[int, int] | None = None,
+    *,
+    max_header_size: int = 10_000,
+) -> np.memmap: ...
+def isfileobj(f: object) -> TypeGuard[BinaryIO]: ...  # don't use `typing.TypeIs`
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..4daac6cb6f44b1f0a10da2c2b229e9a26fc87f68
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.py
@@ -0,0 +1,5760 @@
+import builtins
+import collections.abc
+import functools
+import re
+import warnings
+
+import numpy as np
+import numpy._core.numeric as _nx
+from numpy._core import overrides, transpose
+from numpy._core._multiarray_umath import _array_converter
+from numpy._core.fromnumeric import any, mean, nonzero, partition, ravel, sum
+from numpy._core.multiarray import (
+    _monotonicity,
+    _place,
+    bincount,
+    interp as compiled_interp,
+    interp_complex as compiled_interp_complex,
+    normalize_axis_index,
+)
+from numpy._core.numeric import (
+    absolute,
+    arange,
+    array,
+    asanyarray,
+    asarray,
+    concatenate,
+    dot,
+    empty,
+    integer,
+    intp,
+    isscalar,
+    ndarray,
+    ones,
+    take,
+    where,
+    zeros_like,
+)
+from numpy._core.numerictypes import typecodes
+from numpy._core.umath import (
+    add,
+    arctan2,
+    cos,
+    exp,
+    floor,
+    frompyfunc,
+    less_equal,
+    minimum,
+    mod,
+    not_equal,
+    pi,
+    sin,
+    sqrt,
+    subtract,
+)
+from numpy._utils import set_module
+
+# needed in this module for compatibility
+from numpy.lib._histograms_impl import histogram, histogramdd  # noqa: F401
+from numpy.lib._twodim_base_impl import diag
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+__all__ = [
+    'select', 'piecewise', 'trim_zeros', 'copy', 'iterable', 'percentile',
+    'diff', 'gradient', 'angle', 'unwrap', 'sort_complex', 'flip',
+    'rot90', 'extract', 'place', 'vectorize', 'asarray_chkfinite', 'average',
+    'bincount', 'digitize', 'cov', 'corrcoef',
+    'median', 'sinc', 'hamming', 'hanning', 'bartlett',
+    'blackman', 'kaiser', 'trapezoid', 'i0',
+    'meshgrid', 'delete', 'insert', 'append', 'interp',
+    'quantile'
+    ]
+
+# _QuantileMethods is a dictionary listing all the supported methods to
+# compute quantile/percentile.
+#
+# Below virtual_index refers to the index of the element where the percentile
+# would be found in the sorted sample.
+# When the sample contains exactly the percentile wanted, the virtual_index is
+# an integer to the index of this element.
+# When the percentile wanted is in between two elements, the virtual_index
+# is made of a integer part (a.k.a 'i' or 'left') and a fractional part
+# (a.k.a 'g' or 'gamma')
+#
+# Each method in _QuantileMethods has two properties
+# get_virtual_index : Callable
+#   The function used to compute the virtual_index.
+# fix_gamma : Callable
+#   A function used for discrete methods to force the index to a specific value.
+_QuantileMethods = {
+    # --- HYNDMAN and FAN METHODS
+    # Discrete methods
+    'inverted_cdf': {
+        'get_virtual_index': lambda n, quantiles: _inverted_cdf(n, quantiles),  # noqa: PLW0108
+        'fix_gamma': None,  # should never be called
+    },
+    'averaged_inverted_cdf': {
+        'get_virtual_index': lambda n, quantiles: (n * quantiles) - 1,
+        'fix_gamma': lambda gamma, _: _get_gamma_mask(
+            shape=gamma.shape,
+            default_value=1.,
+            conditioned_value=0.5,
+            where=gamma == 0),
+    },
+    'closest_observation': {
+        'get_virtual_index': lambda n, quantiles: _closest_observation(n, quantiles),  # noqa: PLW0108
+        'fix_gamma': None,  # should never be called
+    },
+    # Continuous methods
+    'interpolated_inverted_cdf': {
+        'get_virtual_index': lambda n, quantiles:
+        _compute_virtual_index(n, quantiles, 0, 1),
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    'hazen': {
+        'get_virtual_index': lambda n, quantiles:
+        _compute_virtual_index(n, quantiles, 0.5, 0.5),
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    'weibull': {
+        'get_virtual_index': lambda n, quantiles:
+        _compute_virtual_index(n, quantiles, 0, 0),
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    # Default method.
+    # To avoid some rounding issues, `(n-1) * quantiles` is preferred to
+    # `_compute_virtual_index(n, quantiles, 1, 1)`.
+    # They are mathematically equivalent.
+    'linear': {
+        'get_virtual_index': lambda n, quantiles: (n - 1) * quantiles,
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    'median_unbiased': {
+        'get_virtual_index': lambda n, quantiles:
+        _compute_virtual_index(n, quantiles, 1 / 3.0, 1 / 3.0),
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    'normal_unbiased': {
+        'get_virtual_index': lambda n, quantiles:
+        _compute_virtual_index(n, quantiles, 3 / 8.0, 3 / 8.0),
+        'fix_gamma': lambda gamma, _: gamma,
+    },
+    # --- OTHER METHODS
+    'lower': {
+        'get_virtual_index': lambda n, quantiles: np.floor(
+            (n - 1) * quantiles).astype(np.intp),
+        'fix_gamma': None,  # should never be called, index dtype is int
+    },
+    'higher': {
+        'get_virtual_index': lambda n, quantiles: np.ceil(
+            (n - 1) * quantiles).astype(np.intp),
+        'fix_gamma': None,  # should never be called, index dtype is int
+    },
+    'midpoint': {
+        'get_virtual_index': lambda n, quantiles: 0.5 * (
+                np.floor((n - 1) * quantiles)
+                + np.ceil((n - 1) * quantiles)),
+        'fix_gamma': lambda gamma, index: _get_gamma_mask(
+            shape=gamma.shape,
+            default_value=0.5,
+            conditioned_value=0.,
+            where=index % 1 == 0),
+    },
+    'nearest': {
+        'get_virtual_index': lambda n, quantiles: np.around(
+            (n - 1) * quantiles).astype(np.intp),
+        'fix_gamma': None,
+        # should never be called, index dtype is int
+    }}
+
+
+def _rot90_dispatcher(m, k=None, axes=None):
+    return (m,)
+
+
+@array_function_dispatch(_rot90_dispatcher)
+def rot90(m, k=1, axes=(0, 1)):
+    """
+    Rotate an array by 90 degrees in the plane specified by axes.
+
+    Rotation direction is from the first towards the second axis.
+    This means for a 2D array with the default `k` and `axes`, the
+    rotation will be counterclockwise.
+
+    Parameters
+    ----------
+    m : array_like
+        Array of two or more dimensions.
+    k : integer
+        Number of times the array is rotated by 90 degrees.
+    axes : (2,) array_like
+        The array is rotated in the plane defined by the axes.
+        Axes must be different.
+
+    Returns
+    -------
+    y : ndarray
+        A rotated view of `m`.
+
+    See Also
+    --------
+    flip : Reverse the order of elements in an array along the given axis.
+    fliplr : Flip an array horizontally.
+    flipud : Flip an array vertically.
+
+    Notes
+    -----
+    ``rot90(m, k=1, axes=(1,0))``  is the reverse of
+    ``rot90(m, k=1, axes=(0,1))``
+
+    ``rot90(m, k=1, axes=(1,0))`` is equivalent to
+    ``rot90(m, k=-1, axes=(0,1))``
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> m = np.array([[1,2],[3,4]], int)
+    >>> m
+    array([[1, 2],
+           [3, 4]])
+    >>> np.rot90(m)
+    array([[2, 4],
+           [1, 3]])
+    >>> np.rot90(m, 2)
+    array([[4, 3],
+           [2, 1]])
+    >>> m = np.arange(8).reshape((2,2,2))
+    >>> np.rot90(m, 1, (1,2))
+    array([[[1, 3],
+            [0, 2]],
+           [[5, 7],
+            [4, 6]]])
+
+    """
+    axes = tuple(axes)
+    if len(axes) != 2:
+        raise ValueError("len(axes) must be 2.")
+
+    m = asanyarray(m)
+
+    if axes[0] == axes[1] or absolute(axes[0] - axes[1]) == m.ndim:
+        raise ValueError("Axes must be different.")
+
+    if (axes[0] >= m.ndim or axes[0] < -m.ndim
+        or axes[1] >= m.ndim or axes[1] < -m.ndim):
+        raise ValueError(f"Axes={axes} out of range for array of ndim={m.ndim}.")
+
+    k %= 4
+
+    if k == 0:
+        return m[:]
+    if k == 2:
+        return flip(flip(m, axes[0]), axes[1])
+
+    axes_list = arange(0, m.ndim)
+    (axes_list[axes[0]], axes_list[axes[1]]) = (axes_list[axes[1]],
+                                                axes_list[axes[0]])
+
+    if k == 1:
+        return transpose(flip(m, axes[1]), axes_list)
+    else:
+        # k == 3
+        return flip(transpose(m, axes_list), axes[1])
+
+
+def _flip_dispatcher(m, axis=None):
+    return (m,)
+
+
+@array_function_dispatch(_flip_dispatcher)
+def flip(m, axis=None):
+    """
+    Reverse the order of elements in an array along the given axis.
+
+    The shape of the array is preserved, but the elements are reordered.
+
+    Parameters
+    ----------
+    m : array_like
+        Input array.
+    axis : None or int or tuple of ints, optional
+         Axis or axes along which to flip over. The default,
+         axis=None, will flip over all of the axes of the input array.
+         If axis is negative it counts from the last to the first axis.
+
+         If axis is a tuple of ints, flipping is performed on all of the axes
+         specified in the tuple.
+
+    Returns
+    -------
+    out : array_like
+        A view of `m` with the entries of axis reversed.  Since a view is
+        returned, this operation is done in constant time.
+
+    See Also
+    --------
+    flipud : Flip an array vertically (axis=0).
+    fliplr : Flip an array horizontally (axis=1).
+
+    Notes
+    -----
+    flip(m, 0) is equivalent to flipud(m).
+
+    flip(m, 1) is equivalent to fliplr(m).
+
+    flip(m, n) corresponds to ``m[...,::-1,...]`` with ``::-1`` at position n.
+
+    flip(m) corresponds to ``m[::-1,::-1,...,::-1]`` with ``::-1`` at all
+    positions.
+
+    flip(m, (0, 1)) corresponds to ``m[::-1,::-1,...]`` with ``::-1`` at
+    position 0 and position 1.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> A = np.arange(8).reshape((2,2,2))
+    >>> A
+    array([[[0, 1],
+            [2, 3]],
+           [[4, 5],
+            [6, 7]]])
+    >>> np.flip(A, 0)
+    array([[[4, 5],
+            [6, 7]],
+           [[0, 1],
+            [2, 3]]])
+    >>> np.flip(A, 1)
+    array([[[2, 3],
+            [0, 1]],
+           [[6, 7],
+            [4, 5]]])
+    >>> np.flip(A)
+    array([[[7, 6],
+            [5, 4]],
+           [[3, 2],
+            [1, 0]]])
+    >>> np.flip(A, (0, 2))
+    array([[[5, 4],
+            [7, 6]],
+           [[1, 0],
+            [3, 2]]])
+    >>> rng = np.random.default_rng()
+    >>> A = rng.normal(size=(3,4,5))
+    >>> np.all(np.flip(A,2) == A[:,:,::-1,...])
+    True
+    """
+    if not hasattr(m, 'ndim'):
+        m = asarray(m)
+    if axis is None:
+        indexer = (np.s_[::-1],) * m.ndim
+    else:
+        axis = _nx.normalize_axis_tuple(axis, m.ndim)
+        indexer = [np.s_[:]] * m.ndim
+        for ax in axis:
+            indexer[ax] = np.s_[::-1]
+        indexer = tuple(indexer)
+    return m[indexer]
+
+
+@set_module('numpy')
+def iterable(y):
+    """
+    Check whether or not an object can be iterated over.
+
+    Parameters
+    ----------
+    y : object
+      Input object.
+
+    Returns
+    -------
+    b : bool
+      Return ``True`` if the object has an iterator method or is a
+      sequence and ``False`` otherwise.
+
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.iterable([1, 2, 3])
+    True
+    >>> np.iterable(2)
+    False
+
+    Notes
+    -----
+    In most cases, the results of ``np.iterable(obj)`` are consistent with
+    ``isinstance(obj, collections.abc.Iterable)``. One notable exception is
+    the treatment of 0-dimensional arrays::
+
+        >>> from collections.abc import Iterable
+        >>> a = np.array(1.0)  # 0-dimensional numpy array
+        >>> isinstance(a, Iterable)
+        True
+        >>> np.iterable(a)
+        False
+
+    """
+    try:
+        iter(y)
+    except TypeError:
+        return False
+    return True
+
+
+def _weights_are_valid(weights, a, axis):
+    """Validate weights array.
+
+    We assume, weights is not None.
+    """
+    wgt = np.asanyarray(weights)
+
+    # Sanity checks
+    if a.shape != wgt.shape:
+        if axis is None:
+            raise TypeError(
+                "Axis must be specified when shapes of a and weights "
+                "differ.")
+        if wgt.shape != tuple(a.shape[ax] for ax in axis):
+            raise ValueError(
+                "Shape of weights must be consistent with "
+                "shape of a along specified axis.")
+
+        # setup wgt to broadcast along axis
+        wgt = wgt.transpose(np.argsort(axis))
+        wgt = wgt.reshape(tuple((s if ax in axis else 1)
+                                for ax, s in enumerate(a.shape)))
+    return wgt
+
+
+def _average_dispatcher(a, axis=None, weights=None, returned=None, *,
+                        keepdims=None):
+    return (a, weights)
+
+
+@array_function_dispatch(_average_dispatcher)
+def average(a, axis=None, weights=None, returned=False, *,
+            keepdims=np._NoValue):
+    """
+    Compute the weighted average along the specified axis.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing data to be averaged. If `a` is not an array, a
+        conversion is attempted.
+    axis : None or int or tuple of ints, optional
+        Axis or axes along which to average `a`.  The default,
+        `axis=None`, will average over all of the elements of the input array.
+        If axis is negative it counts from the last to the first axis.
+        If axis is a tuple of ints, averaging is performed on all of the axes
+        specified in the tuple instead of a single axis or all the axes as
+        before.
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the average according to its associated weight.
+        The array of weights must be the same shape as `a` if no axis is
+        specified, otherwise the weights must have dimensions and shape
+        consistent with `a` along the specified axis.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        The calculation is::
+
+            avg = sum(a * weights) / sum(weights)
+
+        where the sum is over all included elements.
+        The only constraint on the values of `weights` is that `sum(weights)`
+        must not be 0.
+    returned : bool, optional
+        Default is `False`. If `True`, the tuple (`average`, `sum_of_weights`)
+        is returned, otherwise only the average is returned.
+        If `weights=None`, `sum_of_weights` is equivalent to the number of
+        elements over which the average is taken.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+        *Note:* `keepdims` will not work with instances of `numpy.matrix`
+        or other classes whose methods do not support `keepdims`.
+
+        .. versionadded:: 1.23.0
+
+    Returns
+    -------
+    retval, [sum_of_weights] : array_type or double
+        Return the average along the specified axis. When `returned` is `True`,
+        return a tuple with the average as the first element and the sum
+        of the weights as the second element. `sum_of_weights` is of the
+        same type as `retval`. The result dtype follows a general pattern.
+        If `weights` is None, the result dtype will be that of `a` , or ``float64``
+        if `a` is integral. Otherwise, if `weights` is not None and `a` is non-
+        integral, the result type will be the type of lowest precision capable of
+        representing values of both `a` and `weights`. If `a` happens to be
+        integral, the previous rules still applies but the result dtype will
+        at least be ``float64``.
+
+    Raises
+    ------
+    ZeroDivisionError
+        When all weights along axis are zero. See `numpy.ma.average` for a
+        version robust to this type of error.
+    TypeError
+        When `weights` does not have the same shape as `a`, and `axis=None`.
+    ValueError
+        When `weights` does not have dimensions and shape consistent with `a`
+        along specified `axis`.
+
+    See Also
+    --------
+    mean
+
+    ma.average : average for masked arrays -- useful if your data contains
+                 "missing" values
+    numpy.result_type : Returns the type that results from applying the
+                        numpy type promotion rules to the arguments.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> data = np.arange(1, 5)
+    >>> data
+    array([1, 2, 3, 4])
+    >>> np.average(data)
+    2.5
+    >>> np.average(np.arange(1, 11), weights=np.arange(10, 0, -1))
+    4.0
+
+    >>> data = np.arange(6).reshape((3, 2))
+    >>> data
+    array([[0, 1],
+           [2, 3],
+           [4, 5]])
+    >>> np.average(data, axis=1, weights=[1./4, 3./4])
+    array([0.75, 2.75, 4.75])
+    >>> np.average(data, weights=[1./4, 3./4])
+    Traceback (most recent call last):
+        ...
+    TypeError: Axis must be specified when shapes of a and weights differ.
+
+    With ``keepdims=True``, the following result has shape (3, 1).
+
+    >>> np.average(data, axis=1, keepdims=True)
+    array([[0.5],
+           [2.5],
+           [4.5]])
+
+    >>> data = np.arange(8).reshape((2, 2, 2))
+    >>> data
+    array([[[0, 1],
+            [2, 3]],
+           [[4, 5],
+            [6, 7]]])
+    >>> np.average(data, axis=(0, 1), weights=[[1./4, 3./4], [1., 1./2]])
+    array([3.4, 4.4])
+    >>> np.average(data, axis=0, weights=[[1./4, 3./4], [1., 1./2]])
+    Traceback (most recent call last):
+        ...
+    ValueError: Shape of weights must be consistent
+    with shape of a along specified axis.
+    """
+    a = np.asanyarray(a)
+
+    if axis is not None:
+        axis = _nx.normalize_axis_tuple(axis, a.ndim, argname="axis")
+
+    if keepdims is np._NoValue:
+        # Don't pass on the keepdims argument if one wasn't given.
+        keepdims_kw = {}
+    else:
+        keepdims_kw = {'keepdims': keepdims}
+
+    if weights is None:
+        avg = a.mean(axis, **keepdims_kw)
+        avg_as_array = np.asanyarray(avg)
+        scl = avg_as_array.dtype.type(a.size / avg_as_array.size)
+    else:
+        wgt = _weights_are_valid(weights=weights, a=a, axis=axis)
+
+        if issubclass(a.dtype.type, (np.integer, np.bool)):
+            result_dtype = np.result_type(a.dtype, wgt.dtype, 'f8')
+        else:
+            result_dtype = np.result_type(a.dtype, wgt.dtype)
+
+        scl = wgt.sum(axis=axis, dtype=result_dtype, **keepdims_kw)
+        if np.any(scl == 0.0):
+            raise ZeroDivisionError(
+                "Weights sum to zero, can't be normalized")
+
+        avg = avg_as_array = np.multiply(a, wgt,
+                          dtype=result_dtype).sum(axis, **keepdims_kw) / scl
+
+    if returned:
+        if scl.shape != avg_as_array.shape:
+            scl = np.broadcast_to(scl, avg_as_array.shape, subok=True).copy()
+        return avg, scl
+    else:
+        return avg
+
+
+@set_module('numpy')
+def asarray_chkfinite(a, dtype=None, order=None):
+    """Convert the input to an array, checking for NaNs or Infs.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data, in any form that can be converted to an array.  This
+        includes lists, lists of tuples, tuples, tuples of tuples, tuples
+        of lists and ndarrays.  Success requires no NaNs or Infs.
+    dtype : data-type, optional
+        By default, the data-type is inferred from the input data.
+    order : {'C', 'F', 'A', 'K'}, optional
+        The memory layout of the output.
+        'C' gives a row-major layout (C-style),
+        'F' gives a column-major layout (Fortran-style).
+        'C' and 'F' will copy if needed to ensure the output format.
+        'A' (any) is equivalent to 'F' if input a is non-contiguous or
+        Fortran-contiguous, otherwise, it is equivalent to 'C'.
+        Unlike 'C' or 'F', 'A' does not ensure that the result is contiguous.
+        'K' (keep) preserves the input order for the output.
+        'C' is the default.
+
+    Returns
+    -------
+    out : ndarray
+        Array interpretation of `a`.  No copy is performed if the input
+        is already an ndarray.  If `a` is a subclass of ndarray, a base
+        class ndarray is returned.
+
+    Raises
+    ------
+    ValueError
+        Raises ValueError if `a` contains NaN (Not a Number) or Inf (Infinity).
+
+    See Also
+    --------
+    asarray : Create and array.
+    asanyarray : Similar function which passes through subclasses.
+    ascontiguousarray : Convert input to a contiguous array.
+    asfortranarray : Convert input to an ndarray with column-major
+                     memory order.
+    fromiter : Create an array from an iterator.
+    fromfunction : Construct an array by executing a function on grid
+                   positions.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Convert a list into an array. If all elements are finite, then
+    ``asarray_chkfinite`` is identical to ``asarray``.
+
+    >>> a = [1, 2]
+    >>> np.asarray_chkfinite(a, dtype=float)
+    array([1., 2.])
+
+    Raises ValueError if array_like contains Nans or Infs.
+
+    >>> a = [1, 2, np.inf]
+    >>> try:
+    ...     np.asarray_chkfinite(a)
+    ... except ValueError:
+    ...     print('ValueError')
+    ...
+    ValueError
+
+    """
+    a = asarray(a, dtype=dtype, order=order)
+    if a.dtype.char in typecodes['AllFloat'] and not np.isfinite(a).all():
+        raise ValueError(
+            "array must not contain infs or NaNs")
+    return a
+
+
+def _piecewise_dispatcher(x, condlist, funclist, *args, **kw):
+    yield x
+    # support the undocumented behavior of allowing scalars
+    if np.iterable(condlist):
+        yield from condlist
+
+
+@array_function_dispatch(_piecewise_dispatcher)
+def piecewise(x, condlist, funclist, *args, **kw):
+    """
+    Evaluate a piecewise-defined function.
+
+    Given a set of conditions and corresponding functions, evaluate each
+    function on the input data wherever its condition is true.
+
+    Parameters
+    ----------
+    x : ndarray or scalar
+        The input domain.
+    condlist : list of bool arrays or bool scalars
+        Each boolean array corresponds to a function in `funclist`.  Wherever
+        `condlist[i]` is True, `funclist[i](x)` is used as the output value.
+
+        Each boolean array in `condlist` selects a piece of `x`,
+        and should therefore be of the same shape as `x`.
+
+        The length of `condlist` must correspond to that of `funclist`.
+        If one extra function is given, i.e. if
+        ``len(funclist) == len(condlist) + 1``, then that extra function
+        is the default value, used wherever all conditions are false.
+    funclist : list of callables, f(x,*args,**kw), or scalars
+        Each function is evaluated over `x` wherever its corresponding
+        condition is True.  It should take a 1d array as input and give a 1d
+        array or a scalar value as output.  If, instead of a callable,
+        a scalar is provided then a constant function (``lambda x: scalar``) is
+        assumed.
+    args : tuple, optional
+        Any further arguments given to `piecewise` are passed to the functions
+        upon execution, i.e., if called ``piecewise(..., ..., 1, 'a')``, then
+        each function is called as ``f(x, 1, 'a')``.
+    kw : dict, optional
+        Keyword arguments used in calling `piecewise` are passed to the
+        functions upon execution, i.e., if called
+        ``piecewise(..., ..., alpha=1)``, then each function is called as
+        ``f(x, alpha=1)``.
+
+    Returns
+    -------
+    out : ndarray
+        The output is the same shape and type as x and is found by
+        calling the functions in `funclist` on the appropriate portions of `x`,
+        as defined by the boolean arrays in `condlist`.  Portions not covered
+        by any condition have a default value of 0.
+
+
+    See Also
+    --------
+    choose, select, where
+
+    Notes
+    -----
+    This is similar to choose or select, except that functions are
+    evaluated on elements of `x` that satisfy the corresponding condition from
+    `condlist`.
+
+    The result is::
+
+            |--
+            |funclist[0](x[condlist[0]])
+      out = |funclist[1](x[condlist[1]])
+            |...
+            |funclist[n2](x[condlist[n2]])
+            |--
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Define the signum function, which is -1 for ``x < 0`` and +1 for ``x >= 0``.
+
+    >>> x = np.linspace(-2.5, 2.5, 6)
+    >>> np.piecewise(x, [x < 0, x >= 0], [-1, 1])
+    array([-1., -1., -1.,  1.,  1.,  1.])
+
+    Define the absolute value, which is ``-x`` for ``x <0`` and ``x`` for
+    ``x >= 0``.
+
+    >>> np.piecewise(x, [x < 0, x >= 0], [lambda x: -x, lambda x: x])
+    array([2.5,  1.5,  0.5,  0.5,  1.5,  2.5])
+
+    Apply the same function to a scalar value.
+
+    >>> y = -2
+    >>> np.piecewise(y, [y < 0, y >= 0], [lambda x: -x, lambda x: x])
+    array(2)
+
+    """
+    x = asanyarray(x)
+    n2 = len(funclist)
+
+    # undocumented: single condition is promoted to a list of one condition
+    if isscalar(condlist) or (
+            not isinstance(condlist[0], (list, ndarray)) and x.ndim != 0):
+        condlist = [condlist]
+
+    condlist = asarray(condlist, dtype=bool)
+    n = len(condlist)
+
+    if n == n2 - 1:  # compute the "otherwise" condition.
+        condelse = ~np.any(condlist, axis=0, keepdims=True)
+        condlist = np.concatenate([condlist, condelse], axis=0)
+        n += 1
+    elif n != n2:
+        raise ValueError(
+            f"with {n} condition(s), either {n} or {n + 1} functions are expected"
+        )
+
+    y = zeros_like(x)
+    for cond, func in zip(condlist, funclist):
+        if not isinstance(func, collections.abc.Callable):
+            y[cond] = func
+        else:
+            vals = x[cond]
+            if vals.size > 0:
+                y[cond] = func(vals, *args, **kw)
+
+    return y
+
+
+def _select_dispatcher(condlist, choicelist, default=None):
+    yield from condlist
+    yield from choicelist
+
+
+@array_function_dispatch(_select_dispatcher)
+def select(condlist, choicelist, default=0):
+    """
+    Return an array drawn from elements in choicelist, depending on conditions.
+
+    Parameters
+    ----------
+    condlist : list of bool ndarrays
+        The list of conditions which determine from which array in `choicelist`
+        the output elements are taken. When multiple conditions are satisfied,
+        the first one encountered in `condlist` is used.
+    choicelist : list of ndarrays
+        The list of arrays from which the output elements are taken. It has
+        to be of the same length as `condlist`.
+    default : array_like, optional
+        The element inserted in `output` when all conditions evaluate to False.
+
+    Returns
+    -------
+    output : ndarray
+        The output at position m is the m-th element of the array in
+        `choicelist` where the m-th element of the corresponding array in
+        `condlist` is True.
+
+    See Also
+    --------
+    where : Return elements from one of two arrays depending on condition.
+    take, choose, compress, diag, diagonal
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Beginning with an array of integers from 0 to 5 (inclusive),
+    elements less than ``3`` are negated, elements greater than ``3``
+    are squared, and elements not meeting either of these conditions
+    (exactly ``3``) are replaced with a `default` value of ``42``.
+
+    >>> x = np.arange(6)
+    >>> condlist = [x<3, x>3]
+    >>> choicelist = [-x, x**2]
+    >>> np.select(condlist, choicelist, 42)
+    array([ 0,  -1,  -2, 42, 16, 25])
+
+    When multiple conditions are satisfied, the first one encountered in
+    `condlist` is used.
+
+    >>> condlist = [x<=4, x>3]
+    >>> choicelist = [x, x**2]
+    >>> np.select(condlist, choicelist, 55)
+    array([ 0,  1,  2,  3,  4, 25])
+
+    """
+    # Check the size of condlist and choicelist are the same, or abort.
+    if len(condlist) != len(choicelist):
+        raise ValueError(
+            'list of cases must be same length as list of conditions')
+
+    # Now that the dtype is known, handle the deprecated select([], []) case
+    if len(condlist) == 0:
+        raise ValueError("select with an empty condition list is not possible")
+
+    # TODO: This preserves the Python int, float, complex manually to get the
+    #       right `result_type` with NEP 50.  Most likely we will grow a better
+    #       way to spell this (and this can be replaced).
+    choicelist = [
+        choice if type(choice) in (int, float, complex) else np.asarray(choice)
+        for choice in choicelist]
+    choicelist.append(default if type(default) in (int, float, complex)
+                      else np.asarray(default))
+
+    try:
+        dtype = np.result_type(*choicelist)
+    except TypeError as e:
+        msg = f'Choicelist and default value do not have a common dtype: {e}'
+        raise TypeError(msg) from None
+
+    # Convert conditions to arrays and broadcast conditions and choices
+    # as the shape is needed for the result. Doing it separately optimizes
+    # for example when all choices are scalars.
+    condlist = np.broadcast_arrays(*condlist)
+    choicelist = np.broadcast_arrays(*choicelist)
+
+    # If cond array is not an ndarray in boolean format or scalar bool, abort.
+    for i, cond in enumerate(condlist):
+        if cond.dtype.type is not np.bool:
+            raise TypeError(
+                f'invalid entry {i} in condlist: should be boolean ndarray')
+
+    if choicelist[0].ndim == 0:
+        # This may be common, so avoid the call.
+        result_shape = condlist[0].shape
+    else:
+        result_shape = np.broadcast_arrays(condlist[0], choicelist[0])[0].shape
+
+    result = np.full(result_shape, choicelist[-1], dtype)
+
+    # Use np.copyto to burn each choicelist array onto result, using the
+    # corresponding condlist as a boolean mask. This is done in reverse
+    # order since the first choice should take precedence.
+    choicelist = choicelist[-2::-1]
+    condlist = condlist[::-1]
+    for choice, cond in zip(choicelist, condlist):
+        np.copyto(result, choice, where=cond)
+
+    return result
+
+
+def _copy_dispatcher(a, order=None, subok=None):
+    return (a,)
+
+
+@array_function_dispatch(_copy_dispatcher)
+def copy(a, order='K', subok=False):
+    """
+    Return an array copy of the given object.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data.
+    order : {'C', 'F', 'A', 'K'}, optional
+        Controls the memory layout of the copy. 'C' means C-order,
+        'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,
+        'C' otherwise. 'K' means match the layout of `a` as closely
+        as possible. (Note that this function and :meth:`ndarray.copy` are very
+        similar, but have different default values for their order=
+        arguments.)
+    subok : bool, optional
+        If True, then sub-classes will be passed-through, otherwise the
+        returned array will be forced to be a base-class array (defaults to False).
+
+    Returns
+    -------
+    arr : ndarray
+        Array interpretation of `a`.
+
+    See Also
+    --------
+    ndarray.copy : Preferred method for creating an array copy
+
+    Notes
+    -----
+    This is equivalent to:
+
+    >>> np.array(a, copy=True)  #doctest: +SKIP
+
+    The copy made of the data is shallow, i.e., for arrays with object dtype,
+    the new array will point to the same objects.
+    See Examples from `ndarray.copy`.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create an array x, with a reference y and a copy z:
+
+    >>> x = np.array([1, 2, 3])
+    >>> y = x
+    >>> z = np.copy(x)
+
+    Note that, when we modify x, y changes, but not z:
+
+    >>> x[0] = 10
+    >>> x[0] == y[0]
+    True
+    >>> x[0] == z[0]
+    False
+
+    Note that, np.copy clears previously set WRITEABLE=False flag.
+
+    >>> a = np.array([1, 2, 3])
+    >>> a.flags["WRITEABLE"] = False
+    >>> b = np.copy(a)
+    >>> b.flags["WRITEABLE"]
+    True
+    >>> b[0] = 3
+    >>> b
+    array([3, 2, 3])
+    """
+    return array(a, order=order, subok=subok, copy=True)
+
+# Basic operations
+
+
+def _gradient_dispatcher(f, *varargs, axis=None, edge_order=None):
+    yield f
+    yield from varargs
+
+
+@array_function_dispatch(_gradient_dispatcher)
+def gradient(f, *varargs, axis=None, edge_order=1):
+    """
+    Return the gradient of an N-dimensional array.
+
+    The gradient is computed using second order accurate central differences
+    in the interior points and either first or second order accurate one-sides
+    (forward or backwards) differences at the boundaries.
+    The returned gradient hence has the same shape as the input array.
+
+    Parameters
+    ----------
+    f : array_like
+        An N-dimensional array containing samples of a scalar function.
+    varargs : list of scalar or array, optional
+        Spacing between f values. Default unitary spacing for all dimensions.
+        Spacing can be specified using:
+
+        1. single scalar to specify a sample distance for all dimensions.
+        2. N scalars to specify a constant sample distance for each dimension.
+           i.e. `dx`, `dy`, `dz`, ...
+        3. N arrays to specify the coordinates of the values along each
+           dimension of F. The length of the array must match the size of
+           the corresponding dimension
+        4. Any combination of N scalars/arrays with the meaning of 2. and 3.
+
+        If `axis` is given, the number of varargs must equal the number of axes
+        specified in the axis parameter.
+        Default: 1. (see Examples below).
+
+    edge_order : {1, 2}, optional
+        Gradient is calculated using N-th order accurate differences
+        at the boundaries. Default: 1.
+    axis : None or int or tuple of ints, optional
+        Gradient is calculated only along the given axis or axes
+        The default (axis = None) is to calculate the gradient for all the axes
+        of the input array. axis may be negative, in which case it counts from
+        the last to the first axis.
+
+    Returns
+    -------
+    gradient : ndarray or tuple of ndarray
+        A tuple of ndarrays (or a single ndarray if there is only one
+        dimension) corresponding to the derivatives of f with respect
+        to each dimension. Each derivative has the same shape as f.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> f = np.array([1, 2, 4, 7, 11, 16])
+    >>> np.gradient(f)
+    array([1. , 1.5, 2.5, 3.5, 4.5, 5. ])
+    >>> np.gradient(f, 2)
+    array([0.5 ,  0.75,  1.25,  1.75,  2.25,  2.5 ])
+
+    Spacing can be also specified with an array that represents the coordinates
+    of the values F along the dimensions.
+    For instance a uniform spacing:
+
+    >>> x = np.arange(f.size)
+    >>> np.gradient(f, x)
+    array([1. ,  1.5,  2.5,  3.5,  4.5,  5. ])
+
+    Or a non uniform one:
+
+    >>> x = np.array([0., 1., 1.5, 3.5, 4., 6.])
+    >>> np.gradient(f, x)
+    array([1. ,  3. ,  3.5,  6.7,  6.9,  2.5])
+
+    For two dimensional arrays, the return will be two arrays ordered by
+    axis. In this example the first array stands for the gradient in
+    rows and the second one in columns direction:
+
+    >>> np.gradient(np.array([[1, 2, 6], [3, 4, 5]]))
+    (array([[ 2.,  2., -1.],
+            [ 2.,  2., -1.]]),
+     array([[1. , 2.5, 4. ],
+            [1. , 1. , 1. ]]))
+
+    In this example the spacing is also specified:
+    uniform for axis=0 and non uniform for axis=1
+
+    >>> dx = 2.
+    >>> y = [1., 1.5, 3.5]
+    >>> np.gradient(np.array([[1, 2, 6], [3, 4, 5]]), dx, y)
+    (array([[ 1. ,  1. , -0.5],
+            [ 1. ,  1. , -0.5]]),
+     array([[2. , 2. , 2. ],
+            [2. , 1.7, 0.5]]))
+
+    It is possible to specify how boundaries are treated using `edge_order`
+
+    >>> x = np.array([0, 1, 2, 3, 4])
+    >>> f = x**2
+    >>> np.gradient(f, edge_order=1)
+    array([1.,  2.,  4.,  6.,  7.])
+    >>> np.gradient(f, edge_order=2)
+    array([0., 2., 4., 6., 8.])
+
+    The `axis` keyword can be used to specify a subset of axes of which the
+    gradient is calculated
+
+    >>> np.gradient(np.array([[1, 2, 6], [3, 4, 5]]), axis=0)
+    array([[ 2.,  2., -1.],
+           [ 2.,  2., -1.]])
+
+    The `varargs` argument defines the spacing between sample points in the
+    input array. It can take two forms:
+
+    1. An array, specifying coordinates, which may be unevenly spaced:
+
+    >>> x = np.array([0., 2., 3., 6., 8.])
+    >>> y = x ** 2
+    >>> np.gradient(y, x, edge_order=2)
+    array([ 0.,  4.,  6., 12., 16.])
+
+    2. A scalar, representing the fixed sample distance:
+
+    >>> dx = 2
+    >>> x = np.array([0., 2., 4., 6., 8.])
+    >>> y = x ** 2
+    >>> np.gradient(y, dx, edge_order=2)
+    array([ 0.,  4.,  8., 12., 16.])
+
+    It's possible to provide different data for spacing along each dimension.
+    The number of arguments must match the number of dimensions in the input
+    data.
+
+    >>> dx = 2
+    >>> dy = 3
+    >>> x = np.arange(0, 6, dx)
+    >>> y = np.arange(0, 9, dy)
+    >>> xs, ys = np.meshgrid(x, y)
+    >>> zs = xs + 2 * ys
+    >>> np.gradient(zs, dy, dx)  # Passing two scalars
+    (array([[2., 2., 2.],
+            [2., 2., 2.],
+            [2., 2., 2.]]),
+     array([[1., 1., 1.],
+            [1., 1., 1.],
+            [1., 1., 1.]]))
+
+    Mixing scalars and arrays is also allowed:
+
+    >>> np.gradient(zs, y, dx)  # Passing one array and one scalar
+    (array([[2., 2., 2.],
+            [2., 2., 2.],
+            [2., 2., 2.]]),
+     array([[1., 1., 1.],
+            [1., 1., 1.],
+            [1., 1., 1.]]))
+
+    Notes
+    -----
+    Assuming that :math:`f\\in C^{3}` (i.e., :math:`f` has at least 3 continuous
+    derivatives) and let :math:`h_{*}` be a non-homogeneous stepsize, we
+    minimize the "consistency error" :math:`\\eta_{i}` between the true gradient
+    and its estimate from a linear combination of the neighboring grid-points:
+
+    .. math::
+
+        \\eta_{i} = f_{i}^{\\left(1\\right)} -
+                    \\left[ \\alpha f\\left(x_{i}\\right) +
+                            \\beta f\\left(x_{i} + h_{d}\\right) +
+                            \\gamma f\\left(x_{i}-h_{s}\\right)
+                    \\right]
+
+    By substituting :math:`f(x_{i} + h_{d})` and :math:`f(x_{i} - h_{s})`
+    with their Taylor series expansion, this translates into solving
+    the following the linear system:
+
+    .. math::
+
+        \\left\\{
+            \\begin{array}{r}
+                \\alpha+\\beta+\\gamma=0 \\\\
+                \\beta h_{d}-\\gamma h_{s}=1 \\\\
+                \\beta h_{d}^{2}+\\gamma h_{s}^{2}=0
+            \\end{array}
+        \\right.
+
+    The resulting approximation of :math:`f_{i}^{(1)}` is the following:
+
+    .. math::
+
+        \\hat f_{i}^{(1)} =
+            \\frac{
+                h_{s}^{2}f\\left(x_{i} + h_{d}\\right)
+                + \\left(h_{d}^{2} - h_{s}^{2}\\right)f\\left(x_{i}\\right)
+                - h_{d}^{2}f\\left(x_{i}-h_{s}\\right)}
+                { h_{s}h_{d}\\left(h_{d} + h_{s}\\right)}
+            + \\mathcal{O}\\left(\\frac{h_{d}h_{s}^{2}
+                                + h_{s}h_{d}^{2}}{h_{d}
+                                + h_{s}}\\right)
+
+    It is worth noting that if :math:`h_{s}=h_{d}`
+    (i.e., data are evenly spaced)
+    we find the standard second order approximation:
+
+    .. math::
+
+        \\hat f_{i}^{(1)}=
+            \\frac{f\\left(x_{i+1}\\right) - f\\left(x_{i-1}\\right)}{2h}
+            + \\mathcal{O}\\left(h^{2}\\right)
+
+    With a similar procedure the forward/backward approximations used for
+    boundaries can be derived.
+
+    References
+    ----------
+    .. [1]  Quarteroni A., Sacco R., Saleri F. (2007) Numerical Mathematics
+            (Texts in Applied Mathematics). New York: Springer.
+    .. [2]  Durran D. R. (1999) Numerical Methods for Wave Equations
+            in Geophysical Fluid Dynamics. New York: Springer.
+    .. [3]  Fornberg B. (1988) Generation of Finite Difference Formulas on
+            Arbitrarily Spaced Grids,
+            Mathematics of Computation 51, no. 184 : 699-706.
+            `PDF <https://www.ams.org/journals/mcom/1988-51-184/
+            S0025-5718-1988-0935077-0/S0025-5718-1988-0935077-0.pdf>`_.
+    """
+    f = np.asanyarray(f)
+    N = f.ndim  # number of dimensions
+
+    if axis is None:
+        axes = tuple(range(N))
+    else:
+        axes = _nx.normalize_axis_tuple(axis, N)
+
+    len_axes = len(axes)
+    n = len(varargs)
+    if n == 0:
+        # no spacing argument - use 1 in all axes
+        dx = [1.0] * len_axes
+    elif n == 1 and np.ndim(varargs[0]) == 0:
+        # single scalar for all axes
+        dx = varargs * len_axes
+    elif n == len_axes:
+        # scalar or 1d array for each axis
+        dx = list(varargs)
+        for i, distances in enumerate(dx):
+            distances = np.asanyarray(distances)
+            if distances.ndim == 0:
+                continue
+            elif distances.ndim != 1:
+                raise ValueError("distances must be either scalars or 1d")
+            if len(distances) != f.shape[axes[i]]:
+                raise ValueError("when 1d, distances must match "
+                                 "the length of the corresponding dimension")
+            if np.issubdtype(distances.dtype, np.integer):
+                # Convert numpy integer types to float64 to avoid modular
+                # arithmetic in np.diff(distances).
+                distances = distances.astype(np.float64)
+            diffx = np.diff(distances)
+            # if distances are constant reduce to the scalar case
+            # since it brings a consistent speedup
+            if (diffx == diffx[0]).all():
+                diffx = diffx[0]
+            dx[i] = diffx
+    else:
+        raise TypeError("invalid number of arguments")
+
+    if edge_order > 2:
+        raise ValueError("'edge_order' greater than 2 not supported")
+
+    # use central differences on interior and one-sided differences on the
+    # endpoints. This preserves second order-accuracy over the full domain.
+
+    outvals = []
+
+    # create slice objects --- initially all are [:, :, ..., :]
+    slice1 = [slice(None)] * N
+    slice2 = [slice(None)] * N
+    slice3 = [slice(None)] * N
+    slice4 = [slice(None)] * N
+
+    otype = f.dtype
+    if otype.type is np.datetime64:
+        # the timedelta dtype with the same unit information
+        otype = np.dtype(otype.name.replace('datetime', 'timedelta'))
+        # view as timedelta to allow addition
+        f = f.view(otype)
+    elif otype.type is np.timedelta64:
+        pass
+    elif np.issubdtype(otype, np.inexact):
+        pass
+    else:
+        # All other types convert to floating point.
+        # First check if f is a numpy integer type; if so, convert f to float64
+        # to avoid modular arithmetic when computing the changes in f.
+        if np.issubdtype(otype, np.integer):
+            f = f.astype(np.float64)
+        otype = np.float64
+
+    for axis, ax_dx in zip(axes, dx):
+        if f.shape[axis] < edge_order + 1:
+            raise ValueError(
+                "Shape of array too small to calculate a numerical gradient, "
+                "at least (edge_order + 1) elements are required.")
+        # result allocation
+        out = np.empty_like(f, dtype=otype)
+
+        # spacing for the current axis
+        uniform_spacing = np.ndim(ax_dx) == 0
+
+        # Numerical differentiation: 2nd order interior
+        slice1[axis] = slice(1, -1)
+        slice2[axis] = slice(None, -2)
+        slice3[axis] = slice(1, -1)
+        slice4[axis] = slice(2, None)
+
+        if uniform_spacing:
+            out[tuple(slice1)] = (f[tuple(slice4)] - f[tuple(slice2)]) / (2. * ax_dx)
+        else:
+            dx1 = ax_dx[0:-1]
+            dx2 = ax_dx[1:]
+            a = -(dx2) / (dx1 * (dx1 + dx2))
+            b = (dx2 - dx1) / (dx1 * dx2)
+            c = dx1 / (dx2 * (dx1 + dx2))
+            # fix the shape for broadcasting
+            shape = np.ones(N, dtype=int)
+            shape[axis] = -1
+
+            a = a.reshape(shape)
+            b = b.reshape(shape)
+            c = c.reshape(shape)
+            # 1D equivalent -- out[1:-1] = a * f[:-2] + b * f[1:-1] + c * f[2:]
+            out[tuple(slice1)] = a * f[tuple(slice2)] + b * f[tuple(slice3)] \
+                                                + c * f[tuple(slice4)]
+
+        # Numerical differentiation: 1st order edges
+        if edge_order == 1:
+            slice1[axis] = 0
+            slice2[axis] = 1
+            slice3[axis] = 0
+            dx_0 = ax_dx if uniform_spacing else ax_dx[0]
+            # 1D equivalent -- out[0] = (f[1] - f[0]) / (x[1] - x[0])
+            out[tuple(slice1)] = (f[tuple(slice2)] - f[tuple(slice3)]) / dx_0
+
+            slice1[axis] = -1
+            slice2[axis] = -1
+            slice3[axis] = -2
+            dx_n = ax_dx if uniform_spacing else ax_dx[-1]
+            # 1D equivalent -- out[-1] = (f[-1] - f[-2]) / (x[-1] - x[-2])
+            out[tuple(slice1)] = (f[tuple(slice2)] - f[tuple(slice3)]) / dx_n
+
+        # Numerical differentiation: 2nd order edges
+        else:
+            slice1[axis] = 0
+            slice2[axis] = 0
+            slice3[axis] = 1
+            slice4[axis] = 2
+            if uniform_spacing:
+                a = -1.5 / ax_dx
+                b = 2. / ax_dx
+                c = -0.5 / ax_dx
+            else:
+                dx1 = ax_dx[0]
+                dx2 = ax_dx[1]
+                a = -(2. * dx1 + dx2) / (dx1 * (dx1 + dx2))
+                b = (dx1 + dx2) / (dx1 * dx2)
+                c = - dx1 / (dx2 * (dx1 + dx2))
+            # 1D equivalent -- out[0] = a * f[0] + b * f[1] + c * f[2]
+            out[tuple(slice1)] = a * f[tuple(slice2)] + b * f[tuple(slice3)] \
+                                                        + c * f[tuple(slice4)]
+
+            slice1[axis] = -1
+            slice2[axis] = -3
+            slice3[axis] = -2
+            slice4[axis] = -1
+            if uniform_spacing:
+                a = 0.5 / ax_dx
+                b = -2. / ax_dx
+                c = 1.5 / ax_dx
+            else:
+                dx1 = ax_dx[-2]
+                dx2 = ax_dx[-1]
+                a = (dx2) / (dx1 * (dx1 + dx2))
+                b = - (dx2 + dx1) / (dx1 * dx2)
+                c = (2. * dx2 + dx1) / (dx2 * (dx1 + dx2))
+            # 1D equivalent -- out[-1] = a * f[-3] + b * f[-2] + c * f[-1]
+            out[tuple(slice1)] = a * f[tuple(slice2)] + b * f[tuple(slice3)] \
+                                                        + c * f[tuple(slice4)]
+
+        outvals.append(out)
+
+        # reset the slice object in this dimension to ":"
+        slice1[axis] = slice(None)
+        slice2[axis] = slice(None)
+        slice3[axis] = slice(None)
+        slice4[axis] = slice(None)
+
+    if len_axes == 1:
+        return outvals[0]
+    return tuple(outvals)
+
+
+def _diff_dispatcher(a, n=None, axis=None, prepend=None, append=None):
+    return (a, prepend, append)
+
+
+@array_function_dispatch(_diff_dispatcher)
+def diff(a, n=1, axis=-1, prepend=np._NoValue, append=np._NoValue):
+    """
+    Calculate the n-th discrete difference along the given axis.
+
+    The first difference is given by ``out[i] = a[i+1] - a[i]`` along
+    the given axis, higher differences are calculated by using `diff`
+    recursively.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array
+    n : int, optional
+        The number of times values are differenced. If zero, the input
+        is returned as-is.
+    axis : int, optional
+        The axis along which the difference is taken, default is the
+        last axis.
+    prepend, append : array_like, optional
+        Values to prepend or append to `a` along axis prior to
+        performing the difference.  Scalar values are expanded to
+        arrays with length 1 in the direction of axis and the shape
+        of the input array in along all other axes.  Otherwise the
+        dimension and shape must match `a` except along axis.
+
+    Returns
+    -------
+    diff : ndarray
+        The n-th differences. The shape of the output is the same as `a`
+        except along `axis` where the dimension is smaller by `n`. The
+        type of the output is the same as the type of the difference
+        between any two elements of `a`. This is the same as the type of
+        `a` in most cases. A notable exception is `datetime64`, which
+        results in a `timedelta64` output array.
+
+    See Also
+    --------
+    gradient, ediff1d, cumsum
+
+    Notes
+    -----
+    Type is preserved for boolean arrays, so the result will contain
+    `False` when consecutive elements are the same and `True` when they
+    differ.
+
+    For unsigned integer arrays, the results will also be unsigned. This
+    should not be surprising, as the result is consistent with
+    calculating the difference directly:
+
+    >>> u8_arr = np.array([1, 0], dtype=np.uint8)
+    >>> np.diff(u8_arr)
+    array([255], dtype=uint8)
+    >>> u8_arr[1,...] - u8_arr[0,...]
+    np.uint8(255)
+
+    If this is not desirable, then the array should be cast to a larger
+    integer type first:
+
+    >>> i16_arr = u8_arr.astype(np.int16)
+    >>> np.diff(i16_arr)
+    array([-1], dtype=int16)
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([1, 2, 4, 7, 0])
+    >>> np.diff(x)
+    array([ 1,  2,  3, -7])
+    >>> np.diff(x, n=2)
+    array([  1,   1, -10])
+
+    >>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
+    >>> np.diff(x)
+    array([[2, 3, 4],
+           [5, 1, 2]])
+    >>> np.diff(x, axis=0)
+    array([[-1,  2,  0, -2]])
+
+    >>> x = np.arange('1066-10-13', '1066-10-16', dtype=np.datetime64)
+    >>> np.diff(x)
+    array([1, 1], dtype='timedelta64[D]')
+
+    """
+    if n == 0:
+        return a
+    if n < 0:
+        raise ValueError(
+            "order must be non-negative but got " + repr(n))
+
+    a = asanyarray(a)
+    nd = a.ndim
+    if nd == 0:
+        raise ValueError("diff requires input that is at least one dimensional")
+    axis = normalize_axis_index(axis, nd)
+
+    combined = []
+    if prepend is not np._NoValue:
+        prepend = np.asanyarray(prepend)
+        if prepend.ndim == 0:
+            shape = list(a.shape)
+            shape[axis] = 1
+            prepend = np.broadcast_to(prepend, tuple(shape))
+        combined.append(prepend)
+
+    combined.append(a)
+
+    if append is not np._NoValue:
+        append = np.asanyarray(append)
+        if append.ndim == 0:
+            shape = list(a.shape)
+            shape[axis] = 1
+            append = np.broadcast_to(append, tuple(shape))
+        combined.append(append)
+
+    if len(combined) > 1:
+        a = np.concatenate(combined, axis)
+
+    slice1 = [slice(None)] * nd
+    slice2 = [slice(None)] * nd
+    slice1[axis] = slice(1, None)
+    slice2[axis] = slice(None, -1)
+    slice1 = tuple(slice1)
+    slice2 = tuple(slice2)
+
+    op = not_equal if a.dtype == np.bool else subtract
+    for _ in range(n):
+        a = op(a[slice1], a[slice2])
+
+    return a
+
+
+def _interp_dispatcher(x, xp, fp, left=None, right=None, period=None):
+    return (x, xp, fp)
+
+
+@array_function_dispatch(_interp_dispatcher)
+def interp(x, xp, fp, left=None, right=None, period=None):
+    """
+    One-dimensional linear interpolation for monotonically increasing sample points.
+
+    Returns the one-dimensional piecewise linear interpolant to a function
+    with given discrete data points (`xp`, `fp`), evaluated at `x`.
+
+    Parameters
+    ----------
+    x : array_like
+        The x-coordinates at which to evaluate the interpolated values.
+
+    xp : 1-D sequence of floats
+        The x-coordinates of the data points, must be increasing if argument
+        `period` is not specified. Otherwise, `xp` is internally sorted after
+        normalizing the periodic boundaries with ``xp = xp % period``.
+
+    fp : 1-D sequence of float or complex
+        The y-coordinates of the data points, same length as `xp`.
+
+    left : optional float or complex corresponding to fp
+        Value to return for `x < xp[0]`, default is `fp[0]`.
+
+    right : optional float or complex corresponding to fp
+        Value to return for `x > xp[-1]`, default is `fp[-1]`.
+
+    period : None or float, optional
+        A period for the x-coordinates. This parameter allows the proper
+        interpolation of angular x-coordinates. Parameters `left` and `right`
+        are ignored if `period` is specified.
+
+    Returns
+    -------
+    y : float or complex (corresponding to fp) or ndarray
+        The interpolated values, same shape as `x`.
+
+    Raises
+    ------
+    ValueError
+        If `xp` and `fp` have different length
+        If `xp` or `fp` are not 1-D sequences
+        If `period == 0`
+
+    See Also
+    --------
+    scipy.interpolate
+
+    Warnings
+    --------
+    The x-coordinate sequence is expected to be increasing, but this is not
+    explicitly enforced.  However, if the sequence `xp` is non-increasing,
+    interpolation results are meaningless.
+
+    Note that, since NaN is unsortable, `xp` also cannot contain NaNs.
+
+    A simple check for `xp` being strictly increasing is::
+
+        np.all(np.diff(xp) > 0)
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> xp = [1, 2, 3]
+    >>> fp = [3, 2, 0]
+    >>> np.interp(2.5, xp, fp)
+    1.0
+    >>> np.interp([0, 1, 1.5, 2.72, 3.14], xp, fp)
+    array([3.  , 3.  , 2.5 , 0.56, 0.  ])
+    >>> UNDEF = -99.0
+    >>> np.interp(3.14, xp, fp, right=UNDEF)
+    -99.0
+
+    Plot an interpolant to the sine function:
+
+    >>> x = np.linspace(0, 2*np.pi, 10)
+    >>> y = np.sin(x)
+    >>> xvals = np.linspace(0, 2*np.pi, 50)
+    >>> yinterp = np.interp(xvals, x, y)
+    >>> import matplotlib.pyplot as plt
+    >>> plt.plot(x, y, 'o')
+    [<matplotlib.lines.Line2D object at 0x...>]
+    >>> plt.plot(xvals, yinterp, '-x')
+    [<matplotlib.lines.Line2D object at 0x...>]
+    >>> plt.show()
+
+    Interpolation with periodic x-coordinates:
+
+    >>> x = [-180, -170, -185, 185, -10, -5, 0, 365]
+    >>> xp = [190, -190, 350, -350]
+    >>> fp = [5, 10, 3, 4]
+    >>> np.interp(x, xp, fp, period=360)
+    array([7.5 , 5.  , 8.75, 6.25, 3.  , 3.25, 3.5 , 3.75])
+
+    Complex interpolation:
+
+    >>> x = [1.5, 4.0]
+    >>> xp = [2,3,5]
+    >>> fp = [1.0j, 0, 2+3j]
+    >>> np.interp(x, xp, fp)
+    array([0.+1.j , 1.+1.5j])
+
+    """
+
+    fp = np.asarray(fp)
+
+    if np.iscomplexobj(fp):
+        interp_func = compiled_interp_complex
+        input_dtype = np.complex128
+    else:
+        interp_func = compiled_interp
+        input_dtype = np.float64
+
+    if period is not None:
+        if period == 0:
+            raise ValueError("period must be a non-zero value")
+        period = abs(period)
+        left = None
+        right = None
+
+        x = np.asarray(x, dtype=np.float64)
+        xp = np.asarray(xp, dtype=np.float64)
+        fp = np.asarray(fp, dtype=input_dtype)
+
+        if xp.ndim != 1 or fp.ndim != 1:
+            raise ValueError("Data points must be 1-D sequences")
+        if xp.shape[0] != fp.shape[0]:
+            raise ValueError("fp and xp are not of the same length")
+        # normalizing periodic boundaries
+        x = x % period
+        xp = xp % period
+        asort_xp = np.argsort(xp)
+        xp = xp[asort_xp]
+        fp = fp[asort_xp]
+        xp = np.concatenate((xp[-1:] - period, xp, xp[0:1] + period))
+        fp = np.concatenate((fp[-1:], fp, fp[0:1]))
+
+    return interp_func(x, xp, fp, left, right)
+
+
+def _angle_dispatcher(z, deg=None):
+    return (z,)
+
+
+@array_function_dispatch(_angle_dispatcher)
+def angle(z, deg=False):
+    """
+    Return the angle of the complex argument.
+
+    Parameters
+    ----------
+    z : array_like
+        A complex number or sequence of complex numbers.
+    deg : bool, optional
+        Return angle in degrees if True, radians if False (default).
+
+    Returns
+    -------
+    angle : ndarray or scalar
+        The counterclockwise angle from the positive real axis on the complex
+        plane in the range ``(-pi, pi]``, with dtype as numpy.float64.
+
+    See Also
+    --------
+    arctan2
+    absolute
+
+    Notes
+    -----
+    This function passes the imaginary and real parts of the argument to
+    `arctan2` to compute the result; consequently, it follows the convention
+    of `arctan2` when the magnitude of the argument is zero. See example.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.angle([1.0, 1.0j, 1+1j])               # in radians
+    array([ 0.        ,  1.57079633,  0.78539816]) # may vary
+    >>> np.angle(1+1j, deg=True)                  # in degrees
+    45.0
+    >>> np.angle([0., -0., complex(0., -0.), complex(-0., -0.)])  # convention
+    array([ 0.        ,  3.14159265, -0.        , -3.14159265])
+
+    """
+    z = asanyarray(z)
+    if issubclass(z.dtype.type, _nx.complexfloating):
+        zimag = z.imag
+        zreal = z.real
+    else:
+        zimag = 0
+        zreal = z
+
+    a = arctan2(zimag, zreal)
+    if deg:
+        a *= 180 / pi
+    return a
+
+
+def _unwrap_dispatcher(p, discont=None, axis=None, *, period=None):
+    return (p,)
+
+
+@array_function_dispatch(_unwrap_dispatcher)
+def unwrap(p, discont=None, axis=-1, *, period=2 * pi):
+    r"""
+    Unwrap by taking the complement of large deltas with respect to the period.
+
+    This unwraps a signal `p` by changing elements which have an absolute
+    difference from their predecessor of more than ``max(discont, period/2)``
+    to their `period`-complementary values.
+
+    For the default case where `period` is :math:`2\pi` and `discont` is
+    :math:`\pi`, this unwraps a radian phase `p` such that adjacent differences
+    are never greater than :math:`\pi` by adding :math:`2k\pi` for some
+    integer :math:`k`.
+
+    Parameters
+    ----------
+    p : array_like
+        Input array.
+    discont : float, optional
+        Maximum discontinuity between values, default is ``period/2``.
+        Values below ``period/2`` are treated as if they were ``period/2``.
+        To have an effect different from the default, `discont` should be
+        larger than ``period/2``.
+    axis : int, optional
+        Axis along which unwrap will operate, default is the last axis.
+    period : float, optional
+        Size of the range over which the input wraps. By default, it is
+        ``2 pi``.
+
+        .. versionadded:: 1.21.0
+
+    Returns
+    -------
+    out : ndarray
+        Output array.
+
+    See Also
+    --------
+    rad2deg, deg2rad
+
+    Notes
+    -----
+    If the discontinuity in `p` is smaller than ``period/2``,
+    but larger than `discont`, no unwrapping is done because taking
+    the complement would only make the discontinuity larger.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> phase = np.linspace(0, np.pi, num=5)
+    >>> phase[3:] += np.pi
+    >>> phase
+    array([ 0.        ,  0.78539816,  1.57079633,  5.49778714,  6.28318531]) # may vary
+    >>> np.unwrap(phase)
+    array([ 0.        ,  0.78539816,  1.57079633, -0.78539816,  0.        ]) # may vary
+    >>> np.unwrap([0, 1, 2, -1, 0], period=4)
+    array([0, 1, 2, 3, 4])
+    >>> np.unwrap([ 1, 2, 3, 4, 5, 6, 1, 2, 3], period=6)
+    array([1, 2, 3, 4, 5, 6, 7, 8, 9])
+    >>> np.unwrap([2, 3, 4, 5, 2, 3, 4, 5], period=4)
+    array([2, 3, 4, 5, 6, 7, 8, 9])
+    >>> phase_deg = np.mod(np.linspace(0 ,720, 19), 360) - 180
+    >>> np.unwrap(phase_deg, period=360)
+    array([-180., -140., -100.,  -60.,  -20.,   20.,   60.,  100.,  140.,
+            180.,  220.,  260.,  300.,  340.,  380.,  420.,  460.,  500.,
+            540.])
+
+    This example plots the unwrapping of the wrapped input signal `w`.
+    First generate `w`, then apply `unwrap` to get `u`.
+
+    >>> t = np.linspace(0, 25, 801)
+    >>> w = np.mod(1.5 * np.sin(1.1 * t + 0.26) * (1 - t / 6 + (t / 23) ** 3), 2.0) - 1
+    >>> u = np.unwrap(w, period=2.0)
+
+    Plot `w` and `u`.
+
+    >>> import matplotlib.pyplot as plt
+    >>> plt.plot(t, w, label='w (a signal wrapped to [-1, 1])')
+    >>> plt.plot(t, u, linewidth=2.5, alpha=0.5, label='unwrap(w, period=2)')
+    >>> plt.xlabel('t')
+    >>> plt.grid(alpha=0.6)
+    >>> plt.legend(framealpha=1, shadow=True)
+    >>> plt.show()
+    """
+    p = asarray(p)
+    nd = p.ndim
+    dd = diff(p, axis=axis)
+    if discont is None:
+        discont = period / 2
+    slice1 = [slice(None, None)] * nd     # full slices
+    slice1[axis] = slice(1, None)
+    slice1 = tuple(slice1)
+    dtype = np.result_type(dd, period)
+    if _nx.issubdtype(dtype, _nx.integer):
+        interval_high, rem = divmod(period, 2)
+        boundary_ambiguous = rem == 0
+    else:
+        interval_high = period / 2
+        boundary_ambiguous = True
+    interval_low = -interval_high
+    ddmod = mod(dd - interval_low, period) + interval_low
+    if boundary_ambiguous:
+        # for `mask = (abs(dd) == period/2)`, the above line made
+        # `ddmod[mask] == -period/2`. correct these such that
+        # `ddmod[mask] == sign(dd[mask])*period/2`.
+        _nx.copyto(ddmod, interval_high,
+                   where=(ddmod == interval_low) & (dd > 0))
+    ph_correct = ddmod - dd
+    _nx.copyto(ph_correct, 0, where=abs(dd) < discont)
+    up = array(p, copy=True, dtype=dtype)
+    up[slice1] = p[slice1] + ph_correct.cumsum(axis)
+    return up
+
+
+def _sort_complex(a):
+    return (a,)
+
+
+@array_function_dispatch(_sort_complex)
+def sort_complex(a):
+    """
+    Sort a complex array using the real part first, then the imaginary part.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array
+
+    Returns
+    -------
+    out : complex ndarray
+        Always returns a sorted complex array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.sort_complex([5, 3, 6, 2, 1])
+    array([1.+0.j, 2.+0.j, 3.+0.j, 5.+0.j, 6.+0.j])
+
+    >>> np.sort_complex([1 + 2j, 2 - 1j, 3 - 2j, 3 - 3j, 3 + 5j])
+    array([1.+2.j,  2.-1.j,  3.-3.j,  3.-2.j,  3.+5.j])
+
+    """
+    b = array(a, copy=True)
+    b.sort()
+    if not issubclass(b.dtype.type, _nx.complexfloating):
+        if b.dtype.char in 'bhBH':
+            return b.astype('F')
+        elif b.dtype.char == 'g':
+            return b.astype('G')
+        else:
+            return b.astype('D')
+    else:
+        return b
+
+
+def _arg_trim_zeros(filt):
+    """Return indices of the first and last non-zero element.
+
+    Parameters
+    ----------
+    filt : array_like
+        Input array.
+
+    Returns
+    -------
+    start, stop : ndarray
+        Two arrays containing the indices of the first and last non-zero
+        element in each dimension.
+
+    See also
+    --------
+    trim_zeros
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> _arg_trim_zeros(np.array([0, 0, 1, 1, 0]))
+    (array([2]), array([3]))
+    """
+    nonzero = (
+        np.argwhere(filt)
+        if filt.dtype != np.object_
+        # Historically, `trim_zeros` treats `None` in an object array
+        # as non-zero while argwhere doesn't, account for that
+        else np.argwhere(filt != 0)
+    )
+    if nonzero.size == 0:
+        start = stop = np.array([], dtype=np.intp)
+    else:
+        start = nonzero.min(axis=0)
+        stop = nonzero.max(axis=0)
+    return start, stop
+
+
+def _trim_zeros(filt, trim=None, axis=None):
+    return (filt,)
+
+
+@array_function_dispatch(_trim_zeros)
+def trim_zeros(filt, trim='fb', axis=None):
+    """Remove values along a dimension which are zero along all other.
+
+    Parameters
+    ----------
+    filt : array_like
+        Input array.
+    trim : {"fb", "f", "b"}, optional
+        A string with 'f' representing trim from front and 'b' to trim from
+        back. By default, zeros are trimmed on both sides.
+        Front and back refer to the edges of a dimension, with "front" referring
+        to the side with the lowest index 0, and "back" referring to the highest
+        index (or index -1).
+    axis : int or sequence, optional
+        If None, `filt` is cropped such that the smallest bounding box is
+        returned that still contains all values which are not zero.
+        If an axis is specified, `filt` will be sliced in that dimension only
+        on the sides specified by `trim`. The remaining area will be the
+        smallest that still contains all values wich are not zero.
+
+        .. versionadded:: 2.2.0
+
+    Returns
+    -------
+    trimmed : ndarray or sequence
+        The result of trimming the input. The number of dimensions and the
+        input data type are preserved.
+
+    Notes
+    -----
+    For all-zero arrays, the first axis is trimmed first.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array((0, 0, 0, 1, 2, 3, 0, 2, 1, 0))
+    >>> np.trim_zeros(a)
+    array([1, 2, 3, 0, 2, 1])
+
+    >>> np.trim_zeros(a, trim='b')
+    array([0, 0, 0, ..., 0, 2, 1])
+
+    Multiple dimensions are supported.
+
+    >>> b = np.array([[0, 0, 2, 3, 0, 0],
+    ...               [0, 1, 0, 3, 0, 0],
+    ...               [0, 0, 0, 0, 0, 0]])
+    >>> np.trim_zeros(b)
+    array([[0, 2, 3],
+           [1, 0, 3]])
+
+    >>> np.trim_zeros(b, axis=-1)
+    array([[0, 2, 3],
+           [1, 0, 3],
+           [0, 0, 0]])
+
+    The input data type is preserved, list/tuple in means list/tuple out.
+
+    >>> np.trim_zeros([0, 1, 2, 0])
+    [1, 2]
+
+    """
+    filt_ = np.asarray(filt)
+
+    trim = trim.lower()
+    if trim not in {"fb", "bf", "f", "b"}:
+        raise ValueError(f"unexpected character(s) in `trim`: {trim!r}")
+    if axis is None:
+        axis_tuple = tuple(range(filt_.ndim))
+    else:
+        axis_tuple = _nx.normalize_axis_tuple(axis, filt_.ndim, argname="axis")
+
+    if not axis_tuple:
+        # No trimming requested -> return input unmodified.
+        return filt
+
+    start, stop = _arg_trim_zeros(filt_)
+    stop += 1  # Adjust for slicing
+
+    if start.size == 0:
+        # filt is all-zero -> assign same values to start and stop so that
+        # resulting slice will be empty
+        start = stop = np.zeros(filt_.ndim, dtype=np.intp)
+    else:
+        if 'f' not in trim:
+            start = (None,) * filt_.ndim
+        if 'b' not in trim:
+            stop = (None,) * filt_.ndim
+
+    sl = tuple(slice(start[ax], stop[ax]) if ax in axis_tuple else slice(None)
+               for ax in range(filt_.ndim))
+    if len(sl) == 1:
+        # filt is 1D -> avoid multi-dimensional slicing to preserve
+        # non-array input types
+        return filt[sl[0]]
+    return filt[sl]
+
+
+def _extract_dispatcher(condition, arr):
+    return (condition, arr)
+
+
+@array_function_dispatch(_extract_dispatcher)
+def extract(condition, arr):
+    """
+    Return the elements of an array that satisfy some condition.
+
+    This is equivalent to ``np.compress(ravel(condition), ravel(arr))``.  If
+    `condition` is boolean ``np.extract`` is equivalent to ``arr[condition]``.
+
+    Note that `place` does the exact opposite of `extract`.
+
+    Parameters
+    ----------
+    condition : array_like
+        An array whose nonzero or True entries indicate the elements of `arr`
+        to extract.
+    arr : array_like
+        Input array of the same size as `condition`.
+
+    Returns
+    -------
+    extract : ndarray
+        Rank 1 array of values from `arr` where `condition` is True.
+
+    See Also
+    --------
+    take, put, copyto, compress, place
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.arange(12).reshape((3, 4))
+    >>> arr
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11]])
+    >>> condition = np.mod(arr, 3)==0
+    >>> condition
+    array([[ True, False, False,  True],
+           [False, False,  True, False],
+           [False,  True, False, False]])
+    >>> np.extract(condition, arr)
+    array([0, 3, 6, 9])
+
+
+    If `condition` is boolean:
+
+    >>> arr[condition]
+    array([0, 3, 6, 9])
+
+    """
+    return _nx.take(ravel(arr), nonzero(ravel(condition))[0])
+
+
+def _place_dispatcher(arr, mask, vals):
+    return (arr, mask, vals)
+
+
+@array_function_dispatch(_place_dispatcher)
+def place(arr, mask, vals):
+    """
+    Change elements of an array based on conditional and input values.
+
+    Similar to ``np.copyto(arr, vals, where=mask)``, the difference is that
+    `place` uses the first N elements of `vals`, where N is the number of
+    True values in `mask`, while `copyto` uses the elements where `mask`
+    is True.
+
+    Note that `extract` does the exact opposite of `place`.
+
+    Parameters
+    ----------
+    arr : ndarray
+        Array to put data into.
+    mask : array_like
+        Boolean mask array. Must have the same size as `a`.
+    vals : 1-D sequence
+        Values to put into `a`. Only the first N elements are used, where
+        N is the number of True values in `mask`. If `vals` is smaller
+        than N, it will be repeated, and if elements of `a` are to be masked,
+        this sequence must be non-empty.
+
+    See Also
+    --------
+    copyto, put, take, extract
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.arange(6).reshape(2, 3)
+    >>> np.place(arr, arr>2, [44, 55])
+    >>> arr
+    array([[ 0,  1,  2],
+           [44, 55, 44]])
+
+    """
+    return _place(arr, mask, vals)
+
+
+# See https://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html
+_DIMENSION_NAME = r'\w+'
+_CORE_DIMENSION_LIST = f'(?:{_DIMENSION_NAME}(?:,{_DIMENSION_NAME})*)?'
+_ARGUMENT = fr'\({_CORE_DIMENSION_LIST}\)'
+_ARGUMENT_LIST = f'{_ARGUMENT}(?:,{_ARGUMENT})*'
+_SIGNATURE = f'^{_ARGUMENT_LIST}->{_ARGUMENT_LIST}$'
+
+
+def _parse_gufunc_signature(signature):
+    """
+    Parse string signatures for a generalized universal function.
+
+    Arguments
+    ---------
+    signature : string
+        Generalized universal function signature, e.g., ``(m,n),(n,p)->(m,p)``
+        for ``np.matmul``.
+
+    Returns
+    -------
+    Tuple of input and output core dimensions parsed from the signature, each
+    of the form List[Tuple[str, ...]].
+    """
+    signature = re.sub(r'\s+', '', signature)
+
+    if not re.match(_SIGNATURE, signature):
+        raise ValueError(
+            f'not a valid gufunc signature: {signature}')
+    return tuple([tuple(re.findall(_DIMENSION_NAME, arg))
+                  for arg in re.findall(_ARGUMENT, arg_list)]
+                 for arg_list in signature.split('->'))
+
+
+def _update_dim_sizes(dim_sizes, arg, core_dims):
+    """
+    Incrementally check and update core dimension sizes for a single argument.
+
+    Arguments
+    ---------
+    dim_sizes : Dict[str, int]
+        Sizes of existing core dimensions. Will be updated in-place.
+    arg : ndarray
+        Argument to examine.
+    core_dims : Tuple[str, ...]
+        Core dimensions for this argument.
+    """
+    if not core_dims:
+        return
+
+    num_core_dims = len(core_dims)
+    if arg.ndim < num_core_dims:
+        raise ValueError(
+            '%d-dimensional argument does not have enough '
+            'dimensions for all core dimensions %r'
+            % (arg.ndim, core_dims))
+
+    core_shape = arg.shape[-num_core_dims:]
+    for dim, size in zip(core_dims, core_shape):
+        if dim in dim_sizes:
+            if size != dim_sizes[dim]:
+                raise ValueError(
+                    'inconsistent size for core dimension %r: %r vs %r'
+                    % (dim, size, dim_sizes[dim]))
+        else:
+            dim_sizes[dim] = size
+
+
+def _parse_input_dimensions(args, input_core_dims):
+    """
+    Parse broadcast and core dimensions for vectorize with a signature.
+
+    Arguments
+    ---------
+    args : Tuple[ndarray, ...]
+        Tuple of input arguments to examine.
+    input_core_dims : List[Tuple[str, ...]]
+        List of core dimensions corresponding to each input.
+
+    Returns
+    -------
+    broadcast_shape : Tuple[int, ...]
+        Common shape to broadcast all non-core dimensions to.
+    dim_sizes : Dict[str, int]
+        Common sizes for named core dimensions.
+    """
+    broadcast_args = []
+    dim_sizes = {}
+    for arg, core_dims in zip(args, input_core_dims):
+        _update_dim_sizes(dim_sizes, arg, core_dims)
+        ndim = arg.ndim - len(core_dims)
+        dummy_array = np.lib.stride_tricks.as_strided(0, arg.shape[:ndim])
+        broadcast_args.append(dummy_array)
+    broadcast_shape = np.lib._stride_tricks_impl._broadcast_shape(
+        *broadcast_args
+    )
+    return broadcast_shape, dim_sizes
+
+
+def _calculate_shapes(broadcast_shape, dim_sizes, list_of_core_dims):
+    """Helper for calculating broadcast shapes with core dimensions."""
+    return [broadcast_shape + tuple(dim_sizes[dim] for dim in core_dims)
+            for core_dims in list_of_core_dims]
+
+
+def _create_arrays(broadcast_shape, dim_sizes, list_of_core_dims, dtypes,
+                   results=None):
+    """Helper for creating output arrays in vectorize."""
+    shapes = _calculate_shapes(broadcast_shape, dim_sizes, list_of_core_dims)
+    if dtypes is None:
+        dtypes = [None] * len(shapes)
+    if results is None:
+        arrays = tuple(np.empty(shape=shape, dtype=dtype)
+                       for shape, dtype in zip(shapes, dtypes))
+    else:
+        arrays = tuple(np.empty_like(result, shape=shape, dtype=dtype)
+                       for result, shape, dtype
+                       in zip(results, shapes, dtypes))
+    return arrays
+
+
+def _get_vectorize_dtype(dtype):
+    if dtype.char in "SU":
+        return dtype.char
+    return dtype
+
+
+@set_module('numpy')
+class vectorize:
+    """
+    vectorize(pyfunc=np._NoValue, otypes=None, doc=None, excluded=None,
+    cache=False, signature=None)
+
+    Returns an object that acts like pyfunc, but takes arrays as input.
+
+    Define a vectorized function which takes a nested sequence of objects or
+    numpy arrays as inputs and returns a single numpy array or a tuple of numpy
+    arrays. The vectorized function evaluates `pyfunc` over successive tuples
+    of the input arrays like the python map function, except it uses the
+    broadcasting rules of numpy.
+
+    The data type of the output of `vectorized` is determined by calling
+    the function with the first element of the input.  This can be avoided
+    by specifying the `otypes` argument.
+
+    Parameters
+    ----------
+    pyfunc : callable, optional
+        A python function or method.
+        Can be omitted to produce a decorator with keyword arguments.
+    otypes : str or list of dtypes, optional
+        The output data type. It must be specified as either a string of
+        typecode characters or a list of data type specifiers. There should
+        be one data type specifier for each output.
+    doc : str, optional
+        The docstring for the function. If None, the docstring will be the
+        ``pyfunc.__doc__``.
+    excluded : set, optional
+        Set of strings or integers representing the positional or keyword
+        arguments for which the function will not be vectorized. These will be
+        passed directly to `pyfunc` unmodified.
+
+    cache : bool, optional
+        If neither `otypes` nor `signature` are provided, and `cache` is ``True``, then
+        cache the number of outputs.
+
+    signature : string, optional
+        Generalized universal function signature, e.g., ``(m,n),(n)->(m)`` for
+        vectorized matrix-vector multiplication. If provided, ``pyfunc`` will
+        be called with (and expected to return) arrays with shapes given by the
+        size of corresponding core dimensions. By default, ``pyfunc`` is
+        assumed to take scalars as input and output.
+
+    Returns
+    -------
+    out : callable
+        A vectorized function if ``pyfunc`` was provided,
+        a decorator otherwise.
+
+    See Also
+    --------
+    frompyfunc : Takes an arbitrary Python function and returns a ufunc
+
+    Notes
+    -----
+    The `vectorize` function is provided primarily for convenience, not for
+    performance. The implementation is essentially a for loop.
+
+    If neither `otypes` nor `signature` are specified, then a call to the function with
+    the first argument will be used to determine the number of outputs.  The results of
+    this call will be cached if `cache` is `True` to prevent calling the function
+    twice.  However, to implement the cache, the original function must be wrapped
+    which will slow down subsequent calls, so only do this if your function is
+    expensive.
+
+    The new keyword argument interface and `excluded` argument support
+    further degrades performance.
+
+    References
+    ----------
+    .. [1] :doc:`/reference/c-api/generalized-ufuncs`
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> def myfunc(a, b):
+    ...     "Return a-b if a>b, otherwise return a+b"
+    ...     if a > b:
+    ...         return a - b
+    ...     else:
+    ...         return a + b
+
+    >>> vfunc = np.vectorize(myfunc)
+    >>> vfunc([1, 2, 3, 4], 2)
+    array([3, 4, 1, 2])
+
+    The docstring is taken from the input function to `vectorize` unless it
+    is specified:
+
+    >>> vfunc.__doc__
+    'Return a-b if a>b, otherwise return a+b'
+    >>> vfunc = np.vectorize(myfunc, doc='Vectorized `myfunc`')
+    >>> vfunc.__doc__
+    'Vectorized `myfunc`'
+
+    The output type is determined by evaluating the first element of the input,
+    unless it is specified:
+
+    >>> out = vfunc([1, 2, 3, 4], 2)
+    >>> type(out[0])
+    <class 'numpy.int64'>
+    >>> vfunc = np.vectorize(myfunc, otypes=[float])
+    >>> out = vfunc([1, 2, 3, 4], 2)
+    >>> type(out[0])
+    <class 'numpy.float64'>
+
+    The `excluded` argument can be used to prevent vectorizing over certain
+    arguments.  This can be useful for array-like arguments of a fixed length
+    such as the coefficients for a polynomial as in `polyval`:
+
+    >>> def mypolyval(p, x):
+    ...     _p = list(p)
+    ...     res = _p.pop(0)
+    ...     while _p:
+    ...         res = res*x + _p.pop(0)
+    ...     return res
+
+    Here, we exclude the zeroth argument from vectorization whether it is
+    passed by position or keyword.
+
+    >>> vpolyval = np.vectorize(mypolyval, excluded={0, 'p'})
+    >>> vpolyval([1, 2, 3], x=[0, 1])
+    array([3, 6])
+    >>> vpolyval(p=[1, 2, 3], x=[0, 1])
+    array([3, 6])
+
+    The `signature` argument allows for vectorizing functions that act on
+    non-scalar arrays of fixed length. For example, you can use it for a
+    vectorized calculation of Pearson correlation coefficient and its p-value:
+
+    >>> import scipy.stats
+    >>> pearsonr = np.vectorize(scipy.stats.pearsonr,
+    ...                 signature='(n),(n)->(),()')
+    >>> pearsonr([[0, 1, 2, 3]], [[1, 2, 3, 4], [4, 3, 2, 1]])
+    (array([ 1., -1.]), array([ 0.,  0.]))
+
+    Or for a vectorized convolution:
+
+    >>> convolve = np.vectorize(np.convolve, signature='(n),(m)->(k)')
+    >>> convolve(np.eye(4), [1, 2, 1])
+    array([[1., 2., 1., 0., 0., 0.],
+           [0., 1., 2., 1., 0., 0.],
+           [0., 0., 1., 2., 1., 0.],
+           [0., 0., 0., 1., 2., 1.]])
+
+    Decorator syntax is supported.  The decorator can be called as
+    a function to provide keyword arguments:
+
+    >>> @np.vectorize
+    ... def identity(x):
+    ...     return x
+    ...
+    >>> identity([0, 1, 2])
+    array([0, 1, 2])
+    >>> @np.vectorize(otypes=[float])
+    ... def as_float(x):
+    ...     return x
+    ...
+    >>> as_float([0, 1, 2])
+    array([0., 1., 2.])
+    """
+    def __init__(self, pyfunc=np._NoValue, otypes=None, doc=None,
+                 excluded=None, cache=False, signature=None):
+
+        if (pyfunc != np._NoValue) and (not callable(pyfunc)):
+            # Splitting the error message to keep
+            # the length below 79 characters.
+            part1 = "When used as a decorator, "
+            part2 = "only accepts keyword arguments."
+            raise TypeError(part1 + part2)
+
+        self.pyfunc = pyfunc
+        self.cache = cache
+        self.signature = signature
+        if pyfunc != np._NoValue and hasattr(pyfunc, '__name__'):
+            self.__name__ = pyfunc.__name__
+
+        self._ufunc = {}    # Caching to improve default performance
+        self._doc = None
+        self.__doc__ = doc
+        if doc is None and hasattr(pyfunc, '__doc__'):
+            self.__doc__ = pyfunc.__doc__
+        else:
+            self._doc = doc
+
+        if isinstance(otypes, str):
+            for char in otypes:
+                if char not in typecodes['All']:
+                    raise ValueError(f"Invalid otype specified: {char}")
+        elif iterable(otypes):
+            otypes = [_get_vectorize_dtype(_nx.dtype(x)) for x in otypes]
+        elif otypes is not None:
+            raise ValueError("Invalid otype specification")
+        self.otypes = otypes
+
+        # Excluded variable support
+        if excluded is None:
+            excluded = set()
+        self.excluded = set(excluded)
+
+        if signature is not None:
+            self._in_and_out_core_dims = _parse_gufunc_signature(signature)
+        else:
+            self._in_and_out_core_dims = None
+
+    def _init_stage_2(self, pyfunc, *args, **kwargs):
+        self.__name__ = pyfunc.__name__
+        self.pyfunc = pyfunc
+        if self._doc is None:
+            self.__doc__ = pyfunc.__doc__
+        else:
+            self.__doc__ = self._doc
+
+    def _call_as_normal(self, *args, **kwargs):
+        """
+        Return arrays with the results of `pyfunc` broadcast (vectorized) over
+        `args` and `kwargs` not in `excluded`.
+        """
+        excluded = self.excluded
+        if not kwargs and not excluded:
+            func = self.pyfunc
+            vargs = args
+        else:
+            # The wrapper accepts only positional arguments: we use `names` and
+            # `inds` to mutate `the_args` and `kwargs` to pass to the original
+            # function.
+            nargs = len(args)
+
+            names = [_n for _n in kwargs if _n not in excluded]
+            inds = [_i for _i in range(nargs) if _i not in excluded]
+            the_args = list(args)
+
+            def func(*vargs):
+                for _n, _i in enumerate(inds):
+                    the_args[_i] = vargs[_n]
+                kwargs.update(zip(names, vargs[len(inds):]))
+                return self.pyfunc(*the_args, **kwargs)
+
+            vargs = [args[_i] for _i in inds]
+            vargs.extend([kwargs[_n] for _n in names])
+
+        return self._vectorize_call(func=func, args=vargs)
+
+    def __call__(self, *args, **kwargs):
+        if self.pyfunc is np._NoValue:
+            self._init_stage_2(*args, **kwargs)
+            return self
+
+        return self._call_as_normal(*args, **kwargs)
+
+    def _get_ufunc_and_otypes(self, func, args):
+        """Return (ufunc, otypes)."""
+        # frompyfunc will fail if args is empty
+        if not args:
+            raise ValueError('args can not be empty')
+
+        if self.otypes is not None:
+            otypes = self.otypes
+
+            # self._ufunc is a dictionary whose keys are the number of
+            # arguments (i.e. len(args)) and whose values are ufuncs created
+            # by frompyfunc. len(args) can be different for different calls if
+            # self.pyfunc has parameters with default values.  We only use the
+            # cache when func is self.pyfunc, which occurs when the call uses
+            # only positional arguments and no arguments are excluded.
+
+            nin = len(args)
+            nout = len(self.otypes)
+            if func is not self.pyfunc or nin not in self._ufunc:
+                ufunc = frompyfunc(func, nin, nout)
+            else:
+                ufunc = None  # We'll get it from self._ufunc
+            if func is self.pyfunc:
+                ufunc = self._ufunc.setdefault(nin, ufunc)
+        else:
+            # Get number of outputs and output types by calling the function on
+            # the first entries of args.  We also cache the result to prevent
+            # the subsequent call when the ufunc is evaluated.
+            # Assumes that ufunc first evaluates the 0th elements in the input
+            # arrays (the input values are not checked to ensure this)
+            args = [asarray(a) for a in args]
+            if builtins.any(arg.size == 0 for arg in args):
+                raise ValueError('cannot call `vectorize` on size 0 inputs '
+                                 'unless `otypes` is set')
+
+            inputs = [arg.flat[0] for arg in args]
+            outputs = func(*inputs)
+
+            # Performance note: profiling indicates that -- for simple
+            # functions at least -- this wrapping can almost double the
+            # execution time.
+            # Hence we make it optional.
+            if self.cache:
+                _cache = [outputs]
+
+                def _func(*vargs):
+                    if _cache:
+                        return _cache.pop()
+                    else:
+                        return func(*vargs)
+            else:
+                _func = func
+
+            if isinstance(outputs, tuple):
+                nout = len(outputs)
+            else:
+                nout = 1
+                outputs = (outputs,)
+
+            otypes = ''.join([asarray(outputs[_k]).dtype.char
+                              for _k in range(nout)])
+
+            # Performance note: profiling indicates that creating the ufunc is
+            # not a significant cost compared with wrapping so it seems not
+            # worth trying to cache this.
+            ufunc = frompyfunc(_func, len(args), nout)
+
+        return ufunc, otypes
+
+    def _vectorize_call(self, func, args):
+        """Vectorized call to `func` over positional `args`."""
+        if self.signature is not None:
+            res = self._vectorize_call_with_signature(func, args)
+        elif not args:
+            res = func()
+        else:
+            ufunc, otypes = self._get_ufunc_and_otypes(func=func, args=args)
+            # gh-29196: `dtype=object` should eventually be removed
+            args = [asanyarray(a, dtype=object) for a in args]
+            outputs = ufunc(*args, out=...)
+
+            if ufunc.nout == 1:
+                res = asanyarray(outputs, dtype=otypes[0])
+            else:
+                res = tuple(asanyarray(x, dtype=t)
+                            for x, t in zip(outputs, otypes))
+        return res
+
+    def _vectorize_call_with_signature(self, func, args):
+        """Vectorized call over positional arguments with a signature."""
+        input_core_dims, output_core_dims = self._in_and_out_core_dims
+
+        if len(args) != len(input_core_dims):
+            raise TypeError('wrong number of positional arguments: '
+                            'expected %r, got %r'
+                            % (len(input_core_dims), len(args)))
+        args = tuple(asanyarray(arg) for arg in args)
+
+        broadcast_shape, dim_sizes = _parse_input_dimensions(
+            args, input_core_dims)
+        input_shapes = _calculate_shapes(broadcast_shape, dim_sizes,
+                                         input_core_dims)
+        args = [np.broadcast_to(arg, shape, subok=True)
+                for arg, shape in zip(args, input_shapes)]
+
+        outputs = None
+        otypes = self.otypes
+        nout = len(output_core_dims)
+
+        for index in np.ndindex(*broadcast_shape):
+            results = func(*(arg[index] for arg in args))
+
+            n_results = len(results) if isinstance(results, tuple) else 1
+
+            if nout != n_results:
+                raise ValueError(
+                    'wrong number of outputs from pyfunc: expected %r, got %r'
+                    % (nout, n_results))
+
+            if nout == 1:
+                results = (results,)
+
+            if outputs is None:
+                for result, core_dims in zip(results, output_core_dims):
+                    _update_dim_sizes(dim_sizes, result, core_dims)
+
+                outputs = _create_arrays(broadcast_shape, dim_sizes,
+                                         output_core_dims, otypes, results)
+
+            for output, result in zip(outputs, results):
+                output[index] = result
+
+        if outputs is None:
+            # did not call the function even once
+            if otypes is None:
+                raise ValueError('cannot call `vectorize` on size 0 inputs '
+                                 'unless `otypes` is set')
+            if builtins.any(dim not in dim_sizes
+                            for dims in output_core_dims
+                            for dim in dims):
+                raise ValueError('cannot call `vectorize` with a signature '
+                                 'including new output dimensions on size 0 '
+                                 'inputs')
+            outputs = _create_arrays(broadcast_shape, dim_sizes,
+                                     output_core_dims, otypes)
+
+        return outputs[0] if nout == 1 else outputs
+
+
+def _cov_dispatcher(m, y=None, rowvar=None, bias=None, ddof=None,
+                    fweights=None, aweights=None, *, dtype=None):
+    return (m, y, fweights, aweights)
+
+
+@array_function_dispatch(_cov_dispatcher)
+def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
+        aweights=None, *, dtype=None):
+    """
+    Estimate a covariance matrix, given data and weights.
+
+    Covariance indicates the level to which two variables vary together.
+    If we examine N-dimensional samples, :math:`X = [x_1, x_2, ..., x_N]^T`,
+    then the covariance matrix element :math:`C_{ij}` is the covariance of
+    :math:`x_i` and :math:`x_j`. The element :math:`C_{ii}` is the variance
+    of :math:`x_i`.
+
+    See the notes for an outline of the algorithm.
+
+    Parameters
+    ----------
+    m : array_like
+        A 1-D or 2-D array containing multiple variables and observations.
+        Each row of `m` represents a variable, and each column a single
+        observation of all those variables. Also see `rowvar` below.
+    y : array_like, optional
+        An additional set of variables and observations. `y` has the same form
+        as that of `m`.
+    rowvar : bool, optional
+        If `rowvar` is True (default), then each row represents a
+        variable, with observations in the columns. Otherwise, the relationship
+        is transposed: each column represents a variable, while the rows
+        contain observations.
+    bias : bool, optional
+        Default normalization (False) is by ``(N - 1)``, where ``N`` is the
+        number of observations given (unbiased estimate). If `bias` is True,
+        then normalization is by ``N``. These values can be overridden by using
+        the keyword ``ddof`` in numpy versions >= 1.5.
+    ddof : int, optional
+        If not ``None`` the default value implied by `bias` is overridden.
+        Note that ``ddof=1`` will return the unbiased estimate, even if both
+        `fweights` and `aweights` are specified, and ``ddof=0`` will return
+        the simple average. See the notes for the details. The default value
+        is ``None``.
+    fweights : array_like, int, optional
+        1-D array of integer frequency weights; the number of times each
+        observation vector should be repeated.
+    aweights : array_like, optional
+        1-D array of observation vector weights. These relative weights are
+        typically large for observations considered "important" and smaller for
+        observations considered less "important". If ``ddof=0`` the array of
+        weights can be used to assign probabilities to observation vectors.
+    dtype : data-type, optional
+        Data-type of the result. By default, the return data-type will have
+        at least `numpy.float64` precision.
+
+        .. versionadded:: 1.20
+
+    Returns
+    -------
+    out : ndarray
+        The covariance matrix of the variables.
+
+    See Also
+    --------
+    corrcoef : Normalized covariance matrix
+
+    Notes
+    -----
+    Assume that the observations are in the columns of the observation
+    array `m` and let ``f = fweights`` and ``a = aweights`` for brevity. The
+    steps to compute the weighted covariance are as follows::
+
+        >>> m = np.arange(10, dtype=np.float64)
+        >>> f = np.arange(10) * 2
+        >>> a = np.arange(10) ** 2.
+        >>> ddof = 1
+        >>> w = f * a
+        >>> v1 = np.sum(w)
+        >>> v2 = np.sum(w * a)
+        >>> m -= np.sum(m * w, axis=None, keepdims=True) / v1
+        >>> cov = np.dot(m * w, m.T) * v1 / (v1**2 - ddof * v2)
+
+    Note that when ``a == 1``, the normalization factor
+    ``v1 / (v1**2 - ddof * v2)`` goes over to ``1 / (np.sum(f) - ddof)``
+    as it should.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Consider two variables, :math:`x_0` and :math:`x_1`, which
+    correlate perfectly, but in opposite directions:
+
+    >>> x = np.array([[0, 2], [1, 1], [2, 0]]).T
+    >>> x
+    array([[0, 1, 2],
+           [2, 1, 0]])
+
+    Note how :math:`x_0` increases while :math:`x_1` decreases. The covariance
+    matrix shows this clearly:
+
+    >>> np.cov(x)
+    array([[ 1., -1.],
+           [-1.,  1.]])
+
+    Note that element :math:`C_{0,1}`, which shows the correlation between
+    :math:`x_0` and :math:`x_1`, is negative.
+
+    Further, note how `x` and `y` are combined:
+
+    >>> x = [-2.1, -1,  4.3]
+    >>> y = [3,  1.1,  0.12]
+    >>> X = np.stack((x, y), axis=0)
+    >>> np.cov(X)
+    array([[11.71      , -4.286     ], # may vary
+           [-4.286     ,  2.144133]])
+    >>> np.cov(x, y)
+    array([[11.71      , -4.286     ], # may vary
+           [-4.286     ,  2.144133]])
+    >>> np.cov(x)
+    array(11.71)
+
+    """
+    # Check inputs
+    if ddof is not None and ddof != int(ddof):
+        raise ValueError(
+            "ddof must be integer")
+
+    # Handles complex arrays too
+    m = np.asarray(m)
+    if m.ndim > 2:
+        raise ValueError("m has more than 2 dimensions")
+
+    if y is not None:
+        y = np.asarray(y)
+        if y.ndim > 2:
+            raise ValueError("y has more than 2 dimensions")
+
+    if dtype is None:
+        if y is None:
+            dtype = np.result_type(m, np.float64)
+        else:
+            dtype = np.result_type(m, y, np.float64)
+
+    X = array(m, ndmin=2, dtype=dtype)
+    if not rowvar and m.ndim != 1:
+        X = X.T
+    if X.shape[0] == 0:
+        return np.array([]).reshape(0, 0)
+    if y is not None:
+        y = array(y, copy=None, ndmin=2, dtype=dtype)
+        if not rowvar and y.shape[0] != 1:
+            y = y.T
+        X = np.concatenate((X, y), axis=0)
+
+    if ddof is None:
+        if bias == 0:
+            ddof = 1
+        else:
+            ddof = 0
+
+    # Get the product of frequencies and weights
+    w = None
+    if fweights is not None:
+        fweights = np.asarray(fweights, dtype=float)
+        if not np.all(fweights == np.around(fweights)):
+            raise TypeError(
+                "fweights must be integer")
+        if fweights.ndim > 1:
+            raise RuntimeError(
+                "cannot handle multidimensional fweights")
+        if fweights.shape[0] != X.shape[1]:
+            raise RuntimeError(
+                "incompatible numbers of samples and fweights")
+        if any(fweights < 0):
+            raise ValueError(
+                "fweights cannot be negative")
+        w = fweights
+    if aweights is not None:
+        aweights = np.asarray(aweights, dtype=float)
+        if aweights.ndim > 1:
+            raise RuntimeError(
+                "cannot handle multidimensional aweights")
+        if aweights.shape[0] != X.shape[1]:
+            raise RuntimeError(
+                "incompatible numbers of samples and aweights")
+        if any(aweights < 0):
+            raise ValueError(
+                "aweights cannot be negative")
+        if w is None:
+            w = aweights
+        else:
+            w *= aweights
+
+    avg, w_sum = average(X, axis=1, weights=w, returned=True)
+    w_sum = w_sum[0]
+
+    # Determine the normalization
+    if w is None:
+        fact = X.shape[1] - ddof
+    elif ddof == 0:
+        fact = w_sum
+    elif aweights is None:
+        fact = w_sum - ddof
+    else:
+        fact = w_sum - ddof * sum(w * aweights) / w_sum
+
+    if fact <= 0:
+        warnings.warn("Degrees of freedom <= 0 for slice",
+                      RuntimeWarning, stacklevel=2)
+        fact = 0.0
+
+    X -= avg[:, None]
+    if w is None:
+        X_T = X.T
+    else:
+        X_T = (X * w).T
+    c = dot(X, X_T.conj())
+    c *= np.true_divide(1, fact)
+    return c.squeeze()
+
+
+def _corrcoef_dispatcher(x, y=None, rowvar=None, *,
+                         dtype=None):
+    return (x, y)
+
+
+@array_function_dispatch(_corrcoef_dispatcher)
+def corrcoef(x, y=None, rowvar=True, *,
+             dtype=None):
+    """
+    Return Pearson product-moment correlation coefficients.
+
+    Please refer to the documentation for `cov` for more detail.  The
+    relationship between the correlation coefficient matrix, `R`, and the
+    covariance matrix, `C`, is
+
+    .. math:: R_{ij} = \\frac{ C_{ij} } { \\sqrt{ C_{ii} C_{jj} } }
+
+    The values of `R` are between -1 and 1, inclusive.
+
+    Parameters
+    ----------
+    x : array_like
+        A 1-D or 2-D array containing multiple variables and observations.
+        Each row of `x` represents a variable, and each column a single
+        observation of all those variables. Also see `rowvar` below.
+    y : array_like, optional
+        An additional set of variables and observations. `y` has the same
+        shape as `x`.
+    rowvar : bool, optional
+        If `rowvar` is True (default), then each row represents a
+        variable, with observations in the columns. Otherwise, the relationship
+        is transposed: each column represents a variable, while the rows
+        contain observations.
+
+    dtype : data-type, optional
+        Data-type of the result. By default, the return data-type will have
+        at least `numpy.float64` precision.
+
+        .. versionadded:: 1.20
+
+    Returns
+    -------
+    R : ndarray
+        The correlation coefficient matrix of the variables.
+
+    See Also
+    --------
+    cov : Covariance matrix
+
+    Notes
+    -----
+    Due to floating point rounding the resulting array may not be Hermitian,
+    the diagonal elements may not be 1, and the elements may not satisfy the
+    inequality abs(a) <= 1. The real and imaginary parts are clipped to the
+    interval [-1,  1] in an attempt to improve on that situation but is not
+    much help in the complex case.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    In this example we generate two random arrays, ``xarr`` and ``yarr``, and
+    compute the row-wise and column-wise Pearson correlation coefficients,
+    ``R``. Since ``rowvar`` is  true by  default, we first find the row-wise
+    Pearson correlation coefficients between the variables of ``xarr``.
+
+    >>> import numpy as np
+    >>> rng = np.random.default_rng(seed=42)
+    >>> xarr = rng.random((3, 3))
+    >>> xarr
+    array([[0.77395605, 0.43887844, 0.85859792],
+           [0.69736803, 0.09417735, 0.97562235],
+           [0.7611397 , 0.78606431, 0.12811363]])
+    >>> R1 = np.corrcoef(xarr)
+    >>> R1
+    array([[ 1.        ,  0.99256089, -0.68080986],
+           [ 0.99256089,  1.        , -0.76492172],
+           [-0.68080986, -0.76492172,  1.        ]])
+
+    If we add another set of variables and observations ``yarr``, we can
+    compute the row-wise Pearson correlation coefficients between the
+    variables in ``xarr`` and ``yarr``.
+
+    >>> yarr = rng.random((3, 3))
+    >>> yarr
+    array([[0.45038594, 0.37079802, 0.92676499],
+           [0.64386512, 0.82276161, 0.4434142 ],
+           [0.22723872, 0.55458479, 0.06381726]])
+    >>> R2 = np.corrcoef(xarr, yarr)
+    >>> R2
+    array([[ 1.        ,  0.99256089, -0.68080986,  0.75008178, -0.934284  ,
+            -0.99004057],
+           [ 0.99256089,  1.        , -0.76492172,  0.82502011, -0.97074098,
+            -0.99981569],
+           [-0.68080986, -0.76492172,  1.        , -0.99507202,  0.89721355,
+             0.77714685],
+           [ 0.75008178,  0.82502011, -0.99507202,  1.        , -0.93657855,
+            -0.83571711],
+           [-0.934284  , -0.97074098,  0.89721355, -0.93657855,  1.        ,
+             0.97517215],
+           [-0.99004057, -0.99981569,  0.77714685, -0.83571711,  0.97517215,
+             1.        ]])
+
+    Finally if we use the option ``rowvar=False``, the columns are now
+    being treated as the variables and we will find the column-wise Pearson
+    correlation coefficients between variables in ``xarr`` and ``yarr``.
+
+    >>> R3 = np.corrcoef(xarr, yarr, rowvar=False)
+    >>> R3
+    array([[ 1.        ,  0.77598074, -0.47458546, -0.75078643, -0.9665554 ,
+             0.22423734],
+           [ 0.77598074,  1.        , -0.92346708, -0.99923895, -0.58826587,
+            -0.44069024],
+           [-0.47458546, -0.92346708,  1.        ,  0.93773029,  0.23297648,
+             0.75137473],
+           [-0.75078643, -0.99923895,  0.93773029,  1.        ,  0.55627469,
+             0.47536961],
+           [-0.9665554 , -0.58826587,  0.23297648,  0.55627469,  1.        ,
+            -0.46666491],
+           [ 0.22423734, -0.44069024,  0.75137473,  0.47536961, -0.46666491,
+             1.        ]])
+
+    """
+    c = cov(x, y, rowvar, dtype=dtype)
+    try:
+        d = diag(c)
+    except ValueError:
+        # scalar covariance
+        # nan if incorrect value (nan, inf, 0), 1 otherwise
+        return c / c
+    stddev = sqrt(d.real)
+    c /= stddev[:, None]
+    c /= stddev[None, :]
+
+    # Clip real and imaginary parts to [-1, 1].  This does not guarantee
+    # abs(a[i,j]) <= 1 for complex arrays, but is the best we can do without
+    # excessive work.
+    np.clip(c.real, -1, 1, out=c.real)
+    if np.iscomplexobj(c):
+        np.clip(c.imag, -1, 1, out=c.imag)
+
+    return c
+
+
+@set_module('numpy')
+def blackman(M):
+    """
+    Return the Blackman window.
+
+    The Blackman window is a taper formed by using the first three
+    terms of a summation of cosines. It was designed to have close to the
+    minimal leakage possible.  It is close to optimal, only slightly worse
+    than a Kaiser window.
+
+    Parameters
+    ----------
+    M : int
+        Number of points in the output window. If zero or less, an empty
+        array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        The window, with the maximum value normalized to one (the value one
+        appears only if the number of samples is odd).
+
+    See Also
+    --------
+    bartlett, hamming, hanning, kaiser
+
+    Notes
+    -----
+    The Blackman window is defined as
+
+    .. math::  w(n) = 0.42 - 0.5 \\cos(2\\pi n/M) + 0.08 \\cos(4\\pi n/M)
+
+    Most references to the Blackman window come from the signal processing
+    literature, where it is used as one of many windowing functions for
+    smoothing values.  It is also known as an apodization (which means
+    "removing the foot", i.e. smoothing discontinuities at the beginning
+    and end of the sampled signal) or tapering function. It is known as a
+    "near optimal" tapering function, almost as good (by some measures)
+    as the kaiser window.
+
+    References
+    ----------
+    Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra,
+    Dover Publications, New York.
+
+    Oppenheim, A.V., and R.W. Schafer. Discrete-Time Signal Processing.
+    Upper Saddle River, NJ: Prentice-Hall, 1999, pp. 468-471.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> np.blackman(12)
+    array([-1.38777878e-17,   3.26064346e-02,   1.59903635e-01, # may vary
+            4.14397981e-01,   7.36045180e-01,   9.67046769e-01,
+            9.67046769e-01,   7.36045180e-01,   4.14397981e-01,
+            1.59903635e-01,   3.26064346e-02,  -1.38777878e-17])
+
+    Plot the window and the frequency response.
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        from numpy.fft import fft, fftshift
+        window = np.blackman(51)
+        plt.plot(window)
+        plt.title("Blackman window")
+        plt.ylabel("Amplitude")
+        plt.xlabel("Sample")
+        plt.show()  # doctest: +SKIP
+
+        plt.figure()
+        A = fft(window, 2048) / 25.5
+        mag = np.abs(fftshift(A))
+        freq = np.linspace(-0.5, 0.5, len(A))
+        with np.errstate(divide='ignore', invalid='ignore'):
+            response = 20 * np.log10(mag)
+        response = np.clip(response, -100, 100)
+        plt.plot(freq, response)
+        plt.title("Frequency response of Blackman window")
+        plt.ylabel("Magnitude [dB]")
+        plt.xlabel("Normalized frequency [cycles per sample]")
+        plt.axis('tight')
+        plt.show()
+
+    """
+    # Ensures at least float64 via 0.0.  M should be an integer, but conversion
+    # to double is safe for a range.
+    values = np.array([0.0, M])
+    M = values[1]
+
+    if M < 1:
+        return array([], dtype=values.dtype)
+    if M == 1:
+        return ones(1, dtype=values.dtype)
+    n = arange(1 - M, M, 2)
+    return 0.42 + 0.5 * cos(pi * n / (M - 1)) + 0.08 * cos(2.0 * pi * n / (M - 1))
+
+
+@set_module('numpy')
+def bartlett(M):
+    """
+    Return the Bartlett window.
+
+    The Bartlett window is very similar to a triangular window, except
+    that the end points are at zero.  It is often used in signal
+    processing for tapering a signal, without generating too much
+    ripple in the frequency domain.
+
+    Parameters
+    ----------
+    M : int
+        Number of points in the output window. If zero or less, an
+        empty array is returned.
+
+    Returns
+    -------
+    out : array
+        The triangular window, with the maximum value normalized to one
+        (the value one appears only if the number of samples is odd), with
+        the first and last samples equal to zero.
+
+    See Also
+    --------
+    blackman, hamming, hanning, kaiser
+
+    Notes
+    -----
+    The Bartlett window is defined as
+
+    .. math:: w(n) = \\frac{2}{M-1} \\left(
+              \\frac{M-1}{2} - \\left|n - \\frac{M-1}{2}\\right|
+              \\right)
+
+    Most references to the Bartlett window come from the signal processing
+    literature, where it is used as one of many windowing functions for
+    smoothing values.  Note that convolution with this window produces linear
+    interpolation.  It is also known as an apodization (which means "removing
+    the foot", i.e. smoothing discontinuities at the beginning and end of the
+    sampled signal) or tapering function. The Fourier transform of the
+    Bartlett window is the product of two sinc functions. Note the excellent
+    discussion in Kanasewich [2]_.
+
+    References
+    ----------
+    .. [1] M.S. Bartlett, "Periodogram Analysis and Continuous Spectra",
+           Biometrika 37, 1-16, 1950.
+    .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
+           The University of Alberta Press, 1975, pp. 109-110.
+    .. [3] A.V. Oppenheim and R.W. Schafer, "Discrete-Time Signal
+           Processing", Prentice-Hall, 1999, pp. 468-471.
+    .. [4] Wikipedia, "Window function",
+           https://en.wikipedia.org/wiki/Window_function
+    .. [5] W.H. Press,  B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
+           "Numerical Recipes", Cambridge University Press, 1986, page 429.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> np.bartlett(12)
+    array([ 0.        ,  0.18181818,  0.36363636,  0.54545455,  0.72727273, # may vary
+            0.90909091,  0.90909091,  0.72727273,  0.54545455,  0.36363636,
+            0.18181818,  0.        ])
+
+    Plot the window and its frequency response (requires SciPy and matplotlib).
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        from numpy.fft import fft, fftshift
+        window = np.bartlett(51)
+        plt.plot(window)
+        plt.title("Bartlett window")
+        plt.ylabel("Amplitude")
+        plt.xlabel("Sample")
+        plt.show()
+        plt.figure()
+        A = fft(window, 2048) / 25.5
+        mag = np.abs(fftshift(A))
+        freq = np.linspace(-0.5, 0.5, len(A))
+        with np.errstate(divide='ignore', invalid='ignore'):
+            response = 20 * np.log10(mag)
+        response = np.clip(response, -100, 100)
+        plt.plot(freq, response)
+        plt.title("Frequency response of Bartlett window")
+        plt.ylabel("Magnitude [dB]")
+        plt.xlabel("Normalized frequency [cycles per sample]")
+        plt.axis('tight')
+        plt.show()
+
+    """
+    # Ensures at least float64 via 0.0.  M should be an integer, but conversion
+    # to double is safe for a range.
+    values = np.array([0.0, M])
+    M = values[1]
+
+    if M < 1:
+        return array([], dtype=values.dtype)
+    if M == 1:
+        return ones(1, dtype=values.dtype)
+    n = arange(1 - M, M, 2)
+    return where(less_equal(n, 0), 1 + n / (M - 1), 1 - n / (M - 1))
+
+
+@set_module('numpy')
+def hanning(M):
+    """
+    Return the Hanning window.
+
+    The Hanning window is a taper formed by using a weighted cosine.
+
+    Parameters
+    ----------
+    M : int
+        Number of points in the output window. If zero or less, an
+        empty array is returned.
+
+    Returns
+    -------
+    out : ndarray, shape(M,)
+        The window, with the maximum value normalized to one (the value
+        one appears only if `M` is odd).
+
+    See Also
+    --------
+    bartlett, blackman, hamming, kaiser
+
+    Notes
+    -----
+    The Hanning window is defined as
+
+    .. math::  w(n) = 0.5 - 0.5\\cos\\left(\\frac{2\\pi{n}}{M-1}\\right)
+               \\qquad 0 \\leq n \\leq M-1
+
+    The Hanning was named for Julius von Hann, an Austrian meteorologist.
+    It is also known as the Cosine Bell. Some authors prefer that it be
+    called a Hann window, to help avoid confusion with the very similar
+    Hamming window.
+
+    Most references to the Hanning window come from the signal processing
+    literature, where it is used as one of many windowing functions for
+    smoothing values.  It is also known as an apodization (which means
+    "removing the foot", i.e. smoothing discontinuities at the beginning
+    and end of the sampled signal) or tapering function.
+
+    References
+    ----------
+    .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
+           spectra, Dover Publications, New York.
+    .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
+           The University of Alberta Press, 1975, pp. 106-108.
+    .. [3] Wikipedia, "Window function",
+           https://en.wikipedia.org/wiki/Window_function
+    .. [4] W.H. Press,  B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
+           "Numerical Recipes", Cambridge University Press, 1986, page 425.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.hanning(12)
+    array([0.        , 0.07937323, 0.29229249, 0.57115742, 0.82743037,
+           0.97974649, 0.97974649, 0.82743037, 0.57115742, 0.29229249,
+           0.07937323, 0.        ])
+
+    Plot the window and its frequency response.
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        from numpy.fft import fft, fftshift
+        window = np.hanning(51)
+        plt.plot(window)
+        plt.title("Hann window")
+        plt.ylabel("Amplitude")
+        plt.xlabel("Sample")
+        plt.show()
+
+        plt.figure()
+        A = fft(window, 2048) / 25.5
+        mag = np.abs(fftshift(A))
+        freq = np.linspace(-0.5, 0.5, len(A))
+        with np.errstate(divide='ignore', invalid='ignore'):
+            response = 20 * np.log10(mag)
+        response = np.clip(response, -100, 100)
+        plt.plot(freq, response)
+        plt.title("Frequency response of the Hann window")
+        plt.ylabel("Magnitude [dB]")
+        plt.xlabel("Normalized frequency [cycles per sample]")
+        plt.axis('tight')
+        plt.show()
+
+    """
+    # Ensures at least float64 via 0.0.  M should be an integer, but conversion
+    # to double is safe for a range.
+    values = np.array([0.0, M])
+    M = values[1]
+
+    if M < 1:
+        return array([], dtype=values.dtype)
+    if M == 1:
+        return ones(1, dtype=values.dtype)
+    n = arange(1 - M, M, 2)
+    return 0.5 + 0.5 * cos(pi * n / (M - 1))
+
+
+@set_module('numpy')
+def hamming(M):
+    """
+    Return the Hamming window.
+
+    The Hamming window is a taper formed by using a weighted cosine.
+
+    Parameters
+    ----------
+    M : int
+        Number of points in the output window. If zero or less, an
+        empty array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        The window, with the maximum value normalized to one (the value
+        one appears only if the number of samples is odd).
+
+    See Also
+    --------
+    bartlett, blackman, hanning, kaiser
+
+    Notes
+    -----
+    The Hamming window is defined as
+
+    .. math::  w(n) = 0.54 - 0.46\\cos\\left(\\frac{2\\pi{n}}{M-1}\\right)
+               \\qquad 0 \\leq n \\leq M-1
+
+    The Hamming was named for R. W. Hamming, an associate of J. W. Tukey
+    and is described in Blackman and Tukey. It was recommended for
+    smoothing the truncated autocovariance function in the time domain.
+    Most references to the Hamming window come from the signal processing
+    literature, where it is used as one of many windowing functions for
+    smoothing values.  It is also known as an apodization (which means
+    "removing the foot", i.e. smoothing discontinuities at the beginning
+    and end of the sampled signal) or tapering function.
+
+    References
+    ----------
+    .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
+           spectra, Dover Publications, New York.
+    .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The
+           University of Alberta Press, 1975, pp. 109-110.
+    .. [3] Wikipedia, "Window function",
+           https://en.wikipedia.org/wiki/Window_function
+    .. [4] W.H. Press,  B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
+           "Numerical Recipes", Cambridge University Press, 1986, page 425.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.hamming(12)
+    array([ 0.08      ,  0.15302337,  0.34890909,  0.60546483,  0.84123594, # may vary
+            0.98136677,  0.98136677,  0.84123594,  0.60546483,  0.34890909,
+            0.15302337,  0.08      ])
+
+    Plot the window and the frequency response.
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        from numpy.fft import fft, fftshift
+        window = np.hamming(51)
+        plt.plot(window)
+        plt.title("Hamming window")
+        plt.ylabel("Amplitude")
+        plt.xlabel("Sample")
+        plt.show()
+
+        plt.figure()
+        A = fft(window, 2048) / 25.5
+        mag = np.abs(fftshift(A))
+        freq = np.linspace(-0.5, 0.5, len(A))
+        response = 20 * np.log10(mag)
+        response = np.clip(response, -100, 100)
+        plt.plot(freq, response)
+        plt.title("Frequency response of Hamming window")
+        plt.ylabel("Magnitude [dB]")
+        plt.xlabel("Normalized frequency [cycles per sample]")
+        plt.axis('tight')
+        plt.show()
+
+    """
+    # Ensures at least float64 via 0.0.  M should be an integer, but conversion
+    # to double is safe for a range.
+    values = np.array([0.0, M])
+    M = values[1]
+
+    if M < 1:
+        return array([], dtype=values.dtype)
+    if M == 1:
+        return ones(1, dtype=values.dtype)
+    n = arange(1 - M, M, 2)
+    return 0.54 + 0.46 * cos(pi * n / (M - 1))
+
+
+## Code from cephes for i0
+
+_i0A = [
+    -4.41534164647933937950E-18,
+    3.33079451882223809783E-17,
+    -2.43127984654795469359E-16,
+    1.71539128555513303061E-15,
+    -1.16853328779934516808E-14,
+    7.67618549860493561688E-14,
+    -4.85644678311192946090E-13,
+    2.95505266312963983461E-12,
+    -1.72682629144155570723E-11,
+    9.67580903537323691224E-11,
+    -5.18979560163526290666E-10,
+    2.65982372468238665035E-9,
+    -1.30002500998624804212E-8,
+    6.04699502254191894932E-8,
+    -2.67079385394061173391E-7,
+    1.11738753912010371815E-6,
+    -4.41673835845875056359E-6,
+    1.64484480707288970893E-5,
+    -5.75419501008210370398E-5,
+    1.88502885095841655729E-4,
+    -5.76375574538582365885E-4,
+    1.63947561694133579842E-3,
+    -4.32430999505057594430E-3,
+    1.05464603945949983183E-2,
+    -2.37374148058994688156E-2,
+    4.93052842396707084878E-2,
+    -9.49010970480476444210E-2,
+    1.71620901522208775349E-1,
+    -3.04682672343198398683E-1,
+    6.76795274409476084995E-1
+    ]
+
+_i0B = [
+    -7.23318048787475395456E-18,
+    -4.83050448594418207126E-18,
+    4.46562142029675999901E-17,
+    3.46122286769746109310E-17,
+    -2.82762398051658348494E-16,
+    -3.42548561967721913462E-16,
+    1.77256013305652638360E-15,
+    3.81168066935262242075E-15,
+    -9.55484669882830764870E-15,
+    -4.15056934728722208663E-14,
+    1.54008621752140982691E-14,
+    3.85277838274214270114E-13,
+    7.18012445138366623367E-13,
+    -1.79417853150680611778E-12,
+    -1.32158118404477131188E-11,
+    -3.14991652796324136454E-11,
+    1.18891471078464383424E-11,
+    4.94060238822496958910E-10,
+    3.39623202570838634515E-9,
+    2.26666899049817806459E-8,
+    2.04891858946906374183E-7,
+    2.89137052083475648297E-6,
+    6.88975834691682398426E-5,
+    3.36911647825569408990E-3,
+    8.04490411014108831608E-1
+    ]
+
+
+def _chbevl(x, vals):
+    b0 = vals[0]
+    b1 = 0.0
+
+    for i in range(1, len(vals)):
+        b2 = b1
+        b1 = b0
+        b0 = x * b1 - b2 + vals[i]
+
+    return 0.5 * (b0 - b2)
+
+
+def _i0_1(x):
+    return exp(x) * _chbevl(x / 2.0 - 2, _i0A)
+
+
+def _i0_2(x):
+    return exp(x) * _chbevl(32.0 / x - 2.0, _i0B) / sqrt(x)
+
+
+def _i0_dispatcher(x):
+    return (x,)
+
+
+@array_function_dispatch(_i0_dispatcher)
+def i0(x):
+    """
+    Modified Bessel function of the first kind, order 0.
+
+    Usually denoted :math:`I_0`.
+
+    Parameters
+    ----------
+    x : array_like of float
+        Argument of the Bessel function.
+
+    Returns
+    -------
+    out : ndarray, shape = x.shape, dtype = float
+        The modified Bessel function evaluated at each of the elements of `x`.
+
+    See Also
+    --------
+    scipy.special.i0, scipy.special.iv, scipy.special.ive
+
+    Notes
+    -----
+    The scipy implementation is recommended over this function: it is a
+    proper ufunc written in C, and more than an order of magnitude faster.
+
+    We use the algorithm published by Clenshaw [1]_ and referenced by
+    Abramowitz and Stegun [2]_, for which the function domain is
+    partitioned into the two intervals [0,8] and (8,inf), and Chebyshev
+    polynomial expansions are employed in each interval. Relative error on
+    the domain [0,30] using IEEE arithmetic is documented [3]_ as having a
+    peak of 5.8e-16 with an rms of 1.4e-16 (n = 30000).
+
+    References
+    ----------
+    .. [1] C. W. Clenshaw, "Chebyshev series for mathematical functions", in
+           *National Physical Laboratory Mathematical Tables*, vol. 5, London:
+           Her Majesty's Stationery Office, 1962.
+    .. [2] M. Abramowitz and I. A. Stegun, *Handbook of Mathematical
+           Functions*, 10th printing, New York: Dover, 1964, pp. 379.
+           https://personal.math.ubc.ca/~cbm/aands/page_379.htm
+    .. [3] https://metacpan.org/pod/distribution/Math-Cephes/lib/Math/Cephes.pod#i0:-Modified-Bessel-function-of-order-zero
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.i0(0.)
+    array(1.0)
+    >>> np.i0([0, 1, 2, 3])
+    array([1.        , 1.26606588, 2.2795853 , 4.88079259])
+
+    """
+    x = np.asanyarray(x)
+    if x.dtype.kind == 'c':
+        raise TypeError("i0 not supported for complex values")
+    if x.dtype.kind != 'f':
+        x = x.astype(float)
+    x = np.abs(x)
+    return piecewise(x, [x <= 8.0], [_i0_1, _i0_2])
+
+## End of cephes code for i0
+
+
+@set_module('numpy')
+def kaiser(M, beta):
+    """
+    Return the Kaiser window.
+
+    The Kaiser window is a taper formed by using a Bessel function.
+
+    Parameters
+    ----------
+    M : int
+        Number of points in the output window. If zero or less, an
+        empty array is returned.
+    beta : float
+        Shape parameter for window.
+
+    Returns
+    -------
+    out : array
+        The window, with the maximum value normalized to one (the value
+        one appears only if the number of samples is odd).
+
+    See Also
+    --------
+    bartlett, blackman, hamming, hanning
+
+    Notes
+    -----
+    The Kaiser window is defined as
+
+    .. math::  w(n) = I_0\\left( \\beta \\sqrt{1-\\frac{4n^2}{(M-1)^2}}
+               \\right)/I_0(\\beta)
+
+    with
+
+    .. math:: \\quad -\\frac{M-1}{2} \\leq n \\leq \\frac{M-1}{2},
+
+    where :math:`I_0` is the modified zeroth-order Bessel function.
+
+    The Kaiser was named for Jim Kaiser, who discovered a simple
+    approximation to the DPSS window based on Bessel functions.  The Kaiser
+    window is a very good approximation to the Digital Prolate Spheroidal
+    Sequence, or Slepian window, which is the transform which maximizes the
+    energy in the main lobe of the window relative to total energy.
+
+    The Kaiser can approximate many other windows by varying the beta
+    parameter.
+
+    ====  =======================
+    beta  Window shape
+    ====  =======================
+    0     Rectangular
+    5     Similar to a Hamming
+    6     Similar to a Hanning
+    8.6   Similar to a Blackman
+    ====  =======================
+
+    A beta value of 14 is probably a good starting point. Note that as beta
+    gets large, the window narrows, and so the number of samples needs to be
+    large enough to sample the increasingly narrow spike, otherwise NaNs will
+    get returned.
+
+    Most references to the Kaiser window come from the signal processing
+    literature, where it is used as one of many windowing functions for
+    smoothing values.  It is also known as an apodization (which means
+    "removing the foot", i.e. smoothing discontinuities at the beginning
+    and end of the sampled signal) or tapering function.
+
+    References
+    ----------
+    .. [1] J. F. Kaiser, "Digital Filters" - Ch 7 in "Systems analysis by
+           digital computer", Editors: F.F. Kuo and J.F. Kaiser, p 218-285.
+           John Wiley and Sons, New York, (1966).
+    .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The
+           University of Alberta Press, 1975, pp. 177-178.
+    .. [3] Wikipedia, "Window function",
+           https://en.wikipedia.org/wiki/Window_function
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> np.kaiser(12, 14)
+     array([7.72686684e-06, 3.46009194e-03, 4.65200189e-02, # may vary
+            2.29737120e-01, 5.99885316e-01, 9.45674898e-01,
+            9.45674898e-01, 5.99885316e-01, 2.29737120e-01,
+            4.65200189e-02, 3.46009194e-03, 7.72686684e-06])
+
+
+    Plot the window and the frequency response.
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        from numpy.fft import fft, fftshift
+        window = np.kaiser(51, 14)
+        plt.plot(window)
+        plt.title("Kaiser window")
+        plt.ylabel("Amplitude")
+        plt.xlabel("Sample")
+        plt.show()
+
+        plt.figure()
+        A = fft(window, 2048) / 25.5
+        mag = np.abs(fftshift(A))
+        freq = np.linspace(-0.5, 0.5, len(A))
+        response = 20 * np.log10(mag)
+        response = np.clip(response, -100, 100)
+        plt.plot(freq, response)
+        plt.title("Frequency response of Kaiser window")
+        plt.ylabel("Magnitude [dB]")
+        plt.xlabel("Normalized frequency [cycles per sample]")
+        plt.axis('tight')
+        plt.show()
+
+    """
+    # Ensures at least float64 via 0.0.  M should be an integer, but conversion
+    # to double is safe for a range.  (Simplified result_type with 0.0
+    # strongly typed.  result-type is not/less order sensitive, but that mainly
+    # matters for integers anyway.)
+    values = np.array([0.0, M, beta])
+    M = values[1]
+    beta = values[2]
+
+    if M == 1:
+        return np.ones(1, dtype=values.dtype)
+    n = arange(0, M)
+    alpha = (M - 1) / 2.0
+    return i0(beta * sqrt(1 - ((n - alpha) / alpha)**2.0)) / i0(beta)
+
+
+def _sinc_dispatcher(x):
+    return (x,)
+
+
+@array_function_dispatch(_sinc_dispatcher)
+def sinc(x):
+    r"""
+    Return the normalized sinc function.
+
+    The sinc function is equal to :math:`\sin(\pi x)/(\pi x)` for any argument
+    :math:`x\ne 0`. ``sinc(0)`` takes the limit value 1, making ``sinc`` not
+    only everywhere continuous but also infinitely differentiable.
+
+    .. note::
+
+        Note the normalization factor of ``pi`` used in the definition.
+        This is the most commonly used definition in signal processing.
+        Use ``sinc(x / np.pi)`` to obtain the unnormalized sinc function
+        :math:`\sin(x)/x` that is more common in mathematics.
+
+    Parameters
+    ----------
+    x : ndarray
+        Array (possibly multi-dimensional) of values for which to calculate
+        ``sinc(x)``.
+
+    Returns
+    -------
+    out : ndarray
+        ``sinc(x)``, which has the same shape as the input.
+
+    Notes
+    -----
+    The name sinc is short for "sine cardinal" or "sinus cardinalis".
+
+    The sinc function is used in various signal processing applications,
+    including in anti-aliasing, in the construction of a Lanczos resampling
+    filter, and in interpolation.
+
+    For bandlimited interpolation of discrete-time signals, the ideal
+    interpolation kernel is proportional to the sinc function.
+
+    References
+    ----------
+    .. [1] Weisstein, Eric W. "Sinc Function." From MathWorld--A Wolfram Web
+           Resource. https://mathworld.wolfram.com/SincFunction.html
+    .. [2] Wikipedia, "Sinc function",
+           https://en.wikipedia.org/wiki/Sinc_function
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import matplotlib.pyplot as plt
+    >>> x = np.linspace(-4, 4, 41)
+    >>> np.sinc(x)
+     array([-3.89804309e-17,  -4.92362781e-02,  -8.40918587e-02, # may vary
+            -8.90384387e-02,  -5.84680802e-02,   3.89804309e-17,
+            6.68206631e-02,   1.16434881e-01,   1.26137788e-01,
+            8.50444803e-02,  -3.89804309e-17,  -1.03943254e-01,
+            -1.89206682e-01,  -2.16236208e-01,  -1.55914881e-01,
+            3.89804309e-17,   2.33872321e-01,   5.04551152e-01,
+            7.56826729e-01,   9.35489284e-01,   1.00000000e+00,
+            9.35489284e-01,   7.56826729e-01,   5.04551152e-01,
+            2.33872321e-01,   3.89804309e-17,  -1.55914881e-01,
+           -2.16236208e-01,  -1.89206682e-01,  -1.03943254e-01,
+           -3.89804309e-17,   8.50444803e-02,   1.26137788e-01,
+            1.16434881e-01,   6.68206631e-02,   3.89804309e-17,
+            -5.84680802e-02,  -8.90384387e-02,  -8.40918587e-02,
+            -4.92362781e-02,  -3.89804309e-17])
+
+    >>> plt.plot(x, np.sinc(x))
+    [<matplotlib.lines.Line2D object at 0x...>]
+    >>> plt.title("Sinc Function")
+    Text(0.5, 1.0, 'Sinc Function')
+    >>> plt.ylabel("Amplitude")
+    Text(0, 0.5, 'Amplitude')
+    >>> plt.xlabel("X")
+    Text(0.5, 0, 'X')
+    >>> plt.show()
+
+    """
+    x = np.asanyarray(x)
+    x = pi * x
+    # Hope that 1e-20 is sufficient for objects...
+    eps = np.finfo(x.dtype).eps if x.dtype.kind == "f" else 1e-20
+    y = where(x, x, eps)
+    return sin(y) / y
+
+
+def _ureduce(a, func, keepdims=False, **kwargs):
+    """
+    Internal Function.
+    Call `func` with `a` as first argument swapping the axes to use extended
+    axis on functions that don't support it natively.
+
+    Returns result and a.shape with axis dims set to 1.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array.
+    func : callable
+        Reduction function capable of receiving a single axis argument.
+        It is called with `a` as first argument followed by `kwargs`.
+    kwargs : keyword arguments
+        additional keyword arguments to pass to `func`.
+
+    Returns
+    -------
+    result : tuple
+        Result of func(a, **kwargs) and a.shape with axis dims set to 1
+        which can be used to reshape the result to the same shape a ufunc with
+        keepdims=True would produce.
+
+    """
+    a = np.asanyarray(a)
+    axis = kwargs.get('axis')
+    out = kwargs.get('out')
+
+    if keepdims is np._NoValue:
+        keepdims = False
+
+    nd = a.ndim
+    if axis is not None:
+        axis = _nx.normalize_axis_tuple(axis, nd)
+
+        if keepdims and out is not None:
+            index_out = tuple(
+                0 if i in axis else slice(None) for i in range(nd))
+            kwargs['out'] = out[(Ellipsis, ) + index_out]
+
+        if len(axis) == 1:
+            kwargs['axis'] = axis[0]
+        else:
+            keep = sorted(set(range(nd)) - set(axis))
+            nkeep = len(keep)
+
+            def reshape_arr(a):
+                # move axis that should not be reduced to front
+                a = np.moveaxis(a, keep, range(nkeep))
+                # merge reduced axis
+                return a.reshape(a.shape[:nkeep] + (-1,))
+
+            a = reshape_arr(a)
+
+            weights = kwargs.get("weights")
+            if weights is not None:
+                kwargs["weights"] = reshape_arr(weights)
+
+            kwargs['axis'] = -1
+    elif keepdims and out is not None:
+        index_out = (0, ) * nd
+        kwargs['out'] = out[(Ellipsis, ) + index_out]
+
+    r = func(a, **kwargs)
+
+    if out is not None:
+        return out
+
+    if keepdims:
+        if axis is None:
+            index_r = (np.newaxis, ) * nd
+        else:
+            index_r = tuple(
+                np.newaxis if i in axis else slice(None)
+                for i in range(nd))
+        r = r[(Ellipsis, ) + index_r]
+
+    return r
+
+
+def _median_dispatcher(
+        a, axis=None, out=None, overwrite_input=None, keepdims=None):
+    return (a, out)
+
+
+@array_function_dispatch(_median_dispatcher)
+def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):
+    """
+    Compute the median along the specified axis.
+
+    Returns the median of the array elements.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array.
+    axis : {int, sequence of int, None}, optional
+        Axis or axes along which the medians are computed. The default,
+        axis=None, will compute the median along a flattened version of
+        the array. If a sequence of axes, the array is first flattened
+        along the given axes, then the median is computed along the
+        resulting flattened axis.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output,
+        but the type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+       If True, then allow use of memory of input array `a` for
+       calculations. The input array will be modified by the call to
+       `median`. This will save memory when you do not need to preserve
+       the contents of the input array. Treat the input as undefined,
+       but it will probably be fully or partially sorted. Default is
+       False. If `overwrite_input` is ``True`` and `a` is not already an
+       `ndarray`, an error will be raised.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `arr`.
+
+    Returns
+    -------
+    median : ndarray
+        A new array holding the result. If the input contains integers
+        or floats smaller than ``float64``, then the output data-type is
+        ``np.float64``.  Otherwise, the data-type of the output is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    mean, percentile
+
+    Notes
+    -----
+    Given a vector ``V`` of length ``N``, the median of ``V`` is the
+    middle value of a sorted copy of ``V``, ``V_sorted`` - i
+    e., ``V_sorted[(N-1)/2]``, when ``N`` is odd, and the average of the
+    two middle values of ``V_sorted`` when ``N`` is even.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10, 7, 4], [3, 2, 1]])
+    >>> a
+    array([[10,  7,  4],
+           [ 3,  2,  1]])
+    >>> np.median(a)
+    np.float64(3.5)
+    >>> np.median(a, axis=0)
+    array([6.5, 4.5, 2.5])
+    >>> np.median(a, axis=1)
+    array([7.,  2.])
+    >>> np.median(a, axis=(0, 1))
+    np.float64(3.5)
+    >>> m = np.median(a, axis=0)
+    >>> out = np.zeros_like(m)
+    >>> np.median(a, axis=0, out=m)
+    array([6.5,  4.5,  2.5])
+    >>> m
+    array([6.5,  4.5,  2.5])
+    >>> b = a.copy()
+    >>> np.median(b, axis=1, overwrite_input=True)
+    array([7.,  2.])
+    >>> assert not np.all(a==b)
+    >>> b = a.copy()
+    >>> np.median(b, axis=None, overwrite_input=True)
+    np.float64(3.5)
+    >>> assert not np.all(a==b)
+
+    """
+    return _ureduce(a, func=_median, keepdims=keepdims, axis=axis, out=out,
+                    overwrite_input=overwrite_input)
+
+
+def _median(a, axis=None, out=None, overwrite_input=False):
+    # can't be reasonably be implemented in terms of percentile as we have to
+    # call mean to not break astropy
+    a = np.asanyarray(a)
+
+    # Set the partition indexes
+    if axis is None:
+        sz = a.size
+    else:
+        sz = a.shape[axis]
+    if sz % 2 == 0:
+        szh = sz // 2
+        kth = [szh - 1, szh]
+    else:
+        kth = [(sz - 1) // 2]
+
+    # We have to check for NaNs (as of writing 'M' doesn't actually work).
+    supports_nans = np.issubdtype(a.dtype, np.inexact) or a.dtype.kind in 'Mm'
+    if supports_nans:
+        kth.append(-1)
+
+    if overwrite_input:
+        if axis is None:
+            part = a.ravel()
+            part.partition(kth)
+        else:
+            a.partition(kth, axis=axis)
+            part = a
+    else:
+        part = partition(a, kth, axis=axis)
+
+    if part.shape == ():
+        # make 0-D arrays work
+        return part.item()
+    if axis is None:
+        axis = 0
+
+    indexer = [slice(None)] * part.ndim
+    index = part.shape[axis] // 2
+    if part.shape[axis] % 2 == 1:
+        # index with slice to allow mean (below) to work
+        indexer[axis] = slice(index, index + 1)
+    else:
+        indexer[axis] = slice(index - 1, index + 1)
+    indexer = tuple(indexer)
+
+    # Use mean in both odd and even case to coerce data type,
+    # using out array if needed.
+    rout = mean(part[indexer], axis=axis, out=out)
+    if supports_nans and sz > 0:
+        # If nans are possible, warn and replace by nans like mean would.
+        rout = np.lib._utils_impl._median_nancheck(part, rout, axis)
+
+    return rout
+
+
+def _percentile_dispatcher(a, q, axis=None, out=None, overwrite_input=None,
+                           method=None, keepdims=None, *, weights=None):
+    return (a, q, out, weights)
+
+
+@array_function_dispatch(_percentile_dispatcher)
+def percentile(a,
+               q,
+               axis=None,
+               out=None,
+               overwrite_input=False,
+               method="linear",
+               keepdims=False,
+               *,
+               weights=None):
+    """
+    Compute the q-th percentile of the data along the specified axis.
+
+    Returns the q-th percentile(s) of the array elements.
+
+    Parameters
+    ----------
+    a : array_like of real numbers
+        Input array or object that can be converted to an array.
+    q : array_like of float
+        Percentage or sequence of percentages for the percentiles to compute.
+        Values must be between 0 and 100 inclusive.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the percentiles are computed. The
+        default is to compute the percentile(s) along a flattened
+        version of the array.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output,
+        but the type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+        If True, then allow the input array `a` to be modified by intermediate
+        calculations, to save memory. In this case, the contents of the input
+        `a` after this function completes is undefined.
+    method : str, optional
+        This parameter specifies the method to use for estimating the
+        percentile.  There are many different methods, some unique to NumPy.
+        See the notes for explanation.  The options sorted by their R type
+        as summarized in the H&F paper [1]_ are:
+
+        1. 'inverted_cdf'
+        2. 'averaged_inverted_cdf'
+        3. 'closest_observation'
+        4. 'interpolated_inverted_cdf'
+        5. 'hazen'
+        6. 'weibull'
+        7. 'linear'  (default)
+        8. 'median_unbiased'
+        9. 'normal_unbiased'
+
+        The first three methods are discontinuous.  NumPy further defines the
+        following discontinuous variations of the default 'linear' (7.) option:
+
+        * 'lower'
+        * 'higher',
+        * 'midpoint'
+        * 'nearest'
+
+        .. versionchanged:: 1.22.0
+            This argument was previously called "interpolation" and only
+            offered the "linear" default and last four options.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left in
+        the result as dimensions with size one. With this option, the
+        result will broadcast correctly against the original array `a`.
+
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the percentile according to its associated weight.
+        The weights array can either be 1-D (in which case its length must be
+        the size of `a` along the given axis) or of the same shape as `a`.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        Only `method="inverted_cdf"` supports weights.
+        See the notes for more details.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    percentile : scalar or ndarray
+        If `q` is a single percentile and `axis=None`, then the result
+        is a scalar. If multiple percentiles are given, first axis of
+        the result corresponds to the percentiles. The other axes are
+        the axes that remain after the reduction of `a`. If the input
+        contains integers or floats smaller than ``float64``, the output
+        data-type is ``float64``. Otherwise, the output data-type is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    mean
+    median : equivalent to ``percentile(..., 50)``
+    nanpercentile
+    quantile : equivalent to percentile, except q in the range [0, 1].
+
+    Notes
+    -----
+    The behavior of `numpy.percentile` with percentage `q` is
+    that of `numpy.quantile` with argument ``q/100``.
+    For more information, please see `numpy.quantile`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10, 7, 4], [3, 2, 1]])
+    >>> a
+    array([[10,  7,  4],
+           [ 3,  2,  1]])
+    >>> np.percentile(a, 50)
+    3.5
+    >>> np.percentile(a, 50, axis=0)
+    array([6.5, 4.5, 2.5])
+    >>> np.percentile(a, 50, axis=1)
+    array([7.,  2.])
+    >>> np.percentile(a, 50, axis=1, keepdims=True)
+    array([[7.],
+           [2.]])
+
+    >>> m = np.percentile(a, 50, axis=0)
+    >>> out = np.zeros_like(m)
+    >>> np.percentile(a, 50, axis=0, out=out)
+    array([6.5, 4.5, 2.5])
+    >>> m
+    array([6.5, 4.5, 2.5])
+
+    >>> b = a.copy()
+    >>> np.percentile(b, 50, axis=1, overwrite_input=True)
+    array([7.,  2.])
+    >>> assert not np.all(a == b)
+
+    The different methods can be visualized graphically:
+
+    .. plot::
+
+        import matplotlib.pyplot as plt
+
+        a = np.arange(4)
+        p = np.linspace(0, 100, 6001)
+        ax = plt.gca()
+        lines = [
+            ('linear', '-', 'C0'),
+            ('inverted_cdf', ':', 'C1'),
+            # Almost the same as `inverted_cdf`:
+            ('averaged_inverted_cdf', '-.', 'C1'),
+            ('closest_observation', ':', 'C2'),
+            ('interpolated_inverted_cdf', '--', 'C1'),
+            ('hazen', '--', 'C3'),
+            ('weibull', '-.', 'C4'),
+            ('median_unbiased', '--', 'C5'),
+            ('normal_unbiased', '-.', 'C6'),
+            ]
+        for method, style, color in lines:
+            ax.plot(
+                p, np.percentile(a, p, method=method),
+                label=method, linestyle=style, color=color)
+        ax.set(
+            title='Percentiles for different methods and data: ' + str(a),
+            xlabel='Percentile',
+            ylabel='Estimated percentile value',
+            yticks=a)
+        ax.legend(bbox_to_anchor=(1.03, 1))
+        plt.tight_layout()
+        plt.show()
+
+    References
+    ----------
+    .. [1] R. J. Hyndman and Y. Fan,
+       "Sample quantiles in statistical packages,"
+       The American Statistician, 50(4), pp. 361-365, 1996
+
+    """
+    a = np.asanyarray(a)
+    if a.dtype.kind == "c":
+        raise TypeError("a must be an array of real numbers")
+
+    weak_q = type(q) in (int, float)  # use weak promotion for final result type
+    q = np.true_divide(q, 100, out=...)
+    if not _quantile_is_valid(q):
+        raise ValueError("Percentiles must be in the range [0, 100]")
+
+    if weights is not None:
+        if method != "inverted_cdf":
+            msg = ("Only method 'inverted_cdf' supports weights. "
+                   f"Got: {method}.")
+            raise ValueError(msg)
+        if axis is not None:
+            axis = _nx.normalize_axis_tuple(axis, a.ndim, argname="axis")
+        weights = _weights_are_valid(weights=weights, a=a, axis=axis)
+        if np.any(weights < 0):
+            raise ValueError("Weights must be non-negative.")
+
+    return _quantile_unchecked(
+        a, q, axis, out, overwrite_input, method, keepdims, weights, weak_q)
+
+
+def _quantile_dispatcher(a, q, axis=None, out=None, overwrite_input=None,
+                         method=None, keepdims=None, *, weights=None):
+    return (a, q, out, weights)
+
+
+@array_function_dispatch(_quantile_dispatcher)
+def quantile(a,
+             q,
+             axis=None,
+             out=None,
+             overwrite_input=False,
+             method="linear",
+             keepdims=False,
+             *,
+             weights=None):
+    """
+    Compute the q-th quantile of the data along the specified axis.
+
+    Parameters
+    ----------
+    a : array_like of real numbers
+        Input array or object that can be converted to an array.
+    q : array_like of float
+        Probability or sequence of probabilities of the quantiles to compute.
+        Values must be between 0 and 1 inclusive.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the quantiles are computed. The default is
+        to compute the quantile(s) along a flattened version of the array.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must have
+        the same shape and buffer length as the expected output, but the
+        type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+        If True, then allow the input array `a` to be modified by
+        intermediate calculations, to save memory. In this case, the
+        contents of the input `a` after this function completes is
+        undefined.
+    method : str, optional
+        This parameter specifies the method to use for estimating the
+        quantile.  There are many different methods, some unique to NumPy.
+        The recommended options, numbered as they appear in [1]_, are:
+
+        1. 'inverted_cdf'
+        2. 'averaged_inverted_cdf'
+        3. 'closest_observation'
+        4. 'interpolated_inverted_cdf'
+        5. 'hazen'
+        6. 'weibull'
+        7. 'linear'  (default)
+        8. 'median_unbiased'
+        9. 'normal_unbiased'
+
+        The first three methods are discontinuous. For backward compatibility
+        with previous versions of NumPy, the following discontinuous variations
+        of the default 'linear' (7.) option are available:
+
+        * 'lower'
+        * 'higher',
+        * 'midpoint'
+        * 'nearest'
+
+        See Notes for details.
+
+        .. versionchanged:: 1.22.0
+            This argument was previously called "interpolation" and only
+            offered the "linear" default and last four options.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left in
+        the result as dimensions with size one. With this option, the
+        result will broadcast correctly against the original array `a`.
+
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the quantile according to its associated weight.
+        The weights array can either be 1-D (in which case its length must be
+        the size of `a` along the given axis) or of the same shape as `a`.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        Only `method="inverted_cdf"` supports weights.
+        See the notes for more details.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    quantile : scalar or ndarray
+        If `q` is a single probability and `axis=None`, then the result
+        is a scalar. If multiple probability levels are given, first axis
+        of the result corresponds to the quantiles. The other axes are
+        the axes that remain after the reduction of `a`. If the input
+        contains integers or floats smaller than ``float64``, the output
+        data-type is ``float64``. Otherwise, the output data-type is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    mean
+    percentile : equivalent to quantile, but with q in the range [0, 100].
+    median : equivalent to ``quantile(..., 0.5)``
+    nanquantile
+
+    Notes
+    -----
+    Given a sample `a` from an underlying distribution, `quantile` provides a
+    nonparametric estimate of the inverse cumulative distribution function.
+
+    By default, this is done by interpolating between adjacent elements in
+    ``y``, a sorted copy of `a`::
+
+        (1-g)*y[j] + g*y[j+1]
+
+    where the index ``j`` and coefficient ``g`` are the integral and
+    fractional components of ``q * (n-1)``, and ``n`` is the number of
+    elements in the sample.
+
+    This is a special case of Equation 1 of H&F [1]_. More generally,
+
+    - ``j = (q*n + m - 1) // 1``, and
+    - ``g = (q*n + m - 1) % 1``,
+
+    where ``m`` may be defined according to several different conventions.
+    The preferred convention may be selected using the ``method`` parameter:
+
+    =============================== =============== ===============
+    ``method``                      number in H&F   ``m``
+    =============================== =============== ===============
+    ``interpolated_inverted_cdf``   4               ``0``
+    ``hazen``                       5               ``1/2``
+    ``weibull``                     6               ``q``
+    ``linear`` (default)            7               ``1 - q``
+    ``median_unbiased``             8               ``q/3 + 1/3``
+    ``normal_unbiased``             9               ``q/4 + 3/8``
+    =============================== =============== ===============
+
+    Note that indices ``j`` and ``j + 1`` are clipped to the range ``0`` to
+    ``n - 1`` when the results of the formula would be outside the allowed
+    range of non-negative indices. The ``- 1`` in the formulas for ``j`` and
+    ``g`` accounts for Python's 0-based indexing.
+
+    The table above includes only the estimators from H&F that are continuous
+    functions of probability `q` (estimators 4-9). NumPy also provides the
+    three discontinuous estimators from H&F (estimators 1-3), where ``j`` is
+    defined as above, ``m`` is defined as follows, and ``g`` is a function
+    of the real-valued ``index = q*n + m - 1`` and ``j``.
+
+    1. ``inverted_cdf``: ``m = 0`` and ``g = int(index - j > 0)``
+    2. ``averaged_inverted_cdf``: ``m = 0`` and
+       ``g = (1 + int(index - j > 0)) / 2``
+    3. ``closest_observation``: ``m = -1/2`` and
+       ``g = 1 - int((index == j) & (j%2 == 1))``
+
+    For backward compatibility with previous versions of NumPy, `quantile`
+    provides four additional discontinuous estimators. Like
+    ``method='linear'``, all have ``m = 1 - q`` so that ``j = q*(n-1) // 1``,
+    but ``g`` is defined as follows.
+
+    - ``lower``: ``g = 0``
+    - ``midpoint``: ``g = 0.5``
+    - ``higher``: ``g = 1``
+    - ``nearest``: ``g = (q*(n-1) % 1) > 0.5``
+
+    **Weighted quantiles:**
+    More formally, the quantile at probability level :math:`q` of a cumulative
+    distribution function :math:`F(y)=P(Y \\leq y)` with probability measure
+    :math:`P` is defined as any number :math:`x` that fulfills the
+    *coverage conditions*
+
+    .. math:: P(Y < x) \\leq q \\quad\\text{and}\\quad P(Y \\leq x) \\geq q
+
+    with random variable :math:`Y\\sim P`.
+    Sample quantiles, the result of `quantile`, provide nonparametric
+    estimation of the underlying population counterparts, represented by the
+    unknown :math:`F`, given a data vector `a` of length ``n``.
+
+    Some of the estimators above arise when one considers :math:`F` as the
+    empirical distribution function of the data, i.e.
+    :math:`F(y) = \\frac{1}{n} \\sum_i 1_{a_i \\leq y}`.
+    Then, different methods correspond to different choices of :math:`x` that
+    fulfill the above coverage conditions. Methods that follow this approach
+    are ``inverted_cdf`` and ``averaged_inverted_cdf``.
+
+    For weighted quantiles, the coverage conditions still hold. The
+    empirical cumulative distribution is simply replaced by its weighted
+    version, i.e.
+    :math:`P(Y \\leq t) = \\frac{1}{\\sum_i w_i} \\sum_i w_i 1_{x_i \\leq t}`.
+    Only ``method="inverted_cdf"`` supports weights.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10, 7, 4], [3, 2, 1]])
+    >>> a
+    array([[10,  7,  4],
+           [ 3,  2,  1]])
+    >>> np.quantile(a, 0.5)
+    3.5
+    >>> np.quantile(a, 0.5, axis=0)
+    array([6.5, 4.5, 2.5])
+    >>> np.quantile(a, 0.5, axis=1)
+    array([7.,  2.])
+    >>> np.quantile(a, 0.5, axis=1, keepdims=True)
+    array([[7.],
+           [2.]])
+    >>> m = np.quantile(a, 0.5, axis=0)
+    >>> out = np.zeros_like(m)
+    >>> np.quantile(a, 0.5, axis=0, out=out)
+    array([6.5, 4.5, 2.5])
+    >>> m
+    array([6.5, 4.5, 2.5])
+    >>> b = a.copy()
+    >>> np.quantile(b, 0.5, axis=1, overwrite_input=True)
+    array([7.,  2.])
+    >>> assert not np.all(a == b)
+
+    See also `numpy.percentile` for a visualization of most methods.
+
+    References
+    ----------
+    .. [1] R. J. Hyndman and Y. Fan,
+       "Sample quantiles in statistical packages,"
+       The American Statistician, 50(4), pp. 361-365, 1996
+
+    """
+    a = np.asanyarray(a)
+    if a.dtype.kind == "c":
+        raise TypeError("a must be an array of real numbers")
+
+    weak_q = type(q) in (int, float)  # use weak promotion for final result type
+    q = np.asanyarray(q)
+
+    if not _quantile_is_valid(q):
+        raise ValueError("Quantiles must be in the range [0, 1]")
+
+    if weights is not None:
+        if method != "inverted_cdf":
+            msg = ("Only method 'inverted_cdf' supports weights. "
+                   f"Got: {method}.")
+            raise ValueError(msg)
+        if axis is not None:
+            axis = _nx.normalize_axis_tuple(axis, a.ndim, argname="axis")
+        weights = _weights_are_valid(weights=weights, a=a, axis=axis)
+        if np.any(weights < 0):
+            raise ValueError("Weights must be non-negative.")
+
+    return _quantile_unchecked(
+        a, q, axis, out, overwrite_input, method, keepdims, weights, weak_q)
+
+
+def _quantile_unchecked(a,
+                        q,
+                        axis=None,
+                        out=None,
+                        overwrite_input=False,
+                        method="linear",
+                        keepdims=False,
+                        weights=None,
+                        weak_q=False):
+    """Assumes that q is in [0, 1], and is an ndarray"""
+    return _ureduce(a,
+                    func=_quantile_ureduce_func,
+                    q=q,
+                    weights=weights,
+                    keepdims=keepdims,
+                    axis=axis,
+                    out=out,
+                    overwrite_input=overwrite_input,
+                    method=method,
+                    weak_q=weak_q)
+
+
+def _quantile_is_valid(q):
+    # avoid expensive reductions, relevant for arrays with < O(1000) elements
+    if q.ndim == 1 and q.size < 10:
+        for i in range(q.size):
+            if not (0.0 <= q[i] <= 1.0):
+                return False
+    elif not (q.min() >= 0 and q.max() <= 1):
+        return False
+    return True
+
+
+def _compute_virtual_index(n, quantiles, alpha: float, beta: float):
+    """
+    Compute the floating point indexes of an array for the linear
+    interpolation of quantiles.
+    n : array_like
+        The sample sizes.
+    quantiles : array_like
+        The quantiles values.
+    alpha : float
+        A constant used to correct the index computed.
+    beta : float
+        A constant used to correct the index computed.
+
+    alpha and beta values depend on the chosen method
+    (see quantile documentation)
+
+    Reference:
+    Hyndman&Fan paper "Sample Quantiles in Statistical Packages",
+    DOI: 10.1080/00031305.1996.10473566
+    """
+    return n * quantiles + (
+            alpha + quantiles * (1 - alpha - beta)
+    ) - 1
+
+
+def _get_gamma(virtual_indexes, previous_indexes, method):
+    """
+    Compute gamma (a.k.a 'm' or 'weight') for the linear interpolation
+    of quantiles.
+
+    virtual_indexes : array_like
+        The indexes where the percentile is supposed to be found in the sorted
+        sample.
+    previous_indexes : array_like
+        The floor values of virtual_indexes.
+    method : dict
+        The interpolation method chosen, which may have a specific rule
+        modifying gamma.
+
+    gamma is usually the fractional part of virtual_indexes but can be modified
+    by the interpolation method.
+    """
+    gamma = np.asanyarray(virtual_indexes - previous_indexes)
+    gamma = method["fix_gamma"](gamma, virtual_indexes)
+    # Ensure both that we have an array, and that we keep the dtype
+    # (which may have been matched to the input array).
+    return np.asanyarray(gamma, dtype=virtual_indexes.dtype)
+
+
+def _lerp(a, b, t, out=None):
+    """
+    Compute the linear interpolation weighted by gamma on each point of
+    two same shape array.
+
+    a : array_like
+        Left bound.
+    b : array_like
+        Right bound.
+    t : array_like
+        The interpolation weight.
+    out : array_like
+        Output array.
+    """
+    diff_b_a = b - a
+    lerp_interpolation = add(a, diff_b_a * t, out=... if out is None else out)
+    subtract(b, diff_b_a * (1 - t), out=lerp_interpolation, where=t >= 0.5,
+             casting='unsafe', dtype=type(lerp_interpolation.dtype))
+    if lerp_interpolation.ndim == 0 and out is None:
+        lerp_interpolation = lerp_interpolation[()]  # unpack 0d arrays
+    return lerp_interpolation
+
+
+def _get_gamma_mask(shape, default_value, conditioned_value, where):
+    out = np.full(shape, default_value)
+    np.copyto(out, conditioned_value, where=where, casting="unsafe")
+    return out
+
+
+def _discrete_interpolation_to_boundaries(index, gamma_condition_fun):
+    previous = np.floor(index)
+    next = previous + 1
+    gamma = index - previous
+    res = _get_gamma_mask(shape=index.shape,
+                          default_value=next,
+                          conditioned_value=previous,
+                          where=gamma_condition_fun(gamma, index)
+                          ).astype(np.intp)
+    # Some methods can lead to out-of-bound integers, clip them:
+    res[res < 0] = 0
+    return res
+
+
+def _closest_observation(n, quantiles):
+    # "choose the nearest even order statistic at g=0" (H&F (1996) pp. 362).
+    # Order is 1-based so for zero-based indexing round to nearest odd index.
+    gamma_fun = lambda gamma, index: (gamma == 0) & (np.floor(index) % 2 == 1)
+    return _discrete_interpolation_to_boundaries((n * quantiles) - 1 - 0.5,
+                                                 gamma_fun)
+
+
+def _inverted_cdf(n, quantiles):
+    gamma_fun = lambda gamma, _: (gamma == 0)
+    return _discrete_interpolation_to_boundaries((n * quantiles) - 1,
+                                                 gamma_fun)
+
+
+def _quantile_ureduce_func(
+    a: np.ndarray,
+    q: np.ndarray,
+    weights: np.ndarray | None,
+    axis: int | None = None,
+    out: np.ndarray | None = None,
+    overwrite_input: bool = False,
+    method: str = "linear",
+    weak_q: bool = False,
+) -> np.ndarray:
+    if q.ndim > 2:
+        # The code below works fine for nd, but it might not have useful
+        # semantics. For now, keep the supported dimensions the same as it was
+        # before.
+        raise ValueError("q must be a scalar or 1d")
+    if overwrite_input:
+        if axis is None:
+            axis = 0
+            arr = a.ravel()
+            wgt = None if weights is None else weights.ravel()
+        else:
+            arr = a
+            wgt = weights
+    elif axis is None:
+        axis = 0
+        arr = a.flatten()
+        wgt = None if weights is None else weights.flatten()
+    else:
+        arr = a.copy()
+        wgt = weights
+    result = _quantile(arr,
+                       quantiles=q,
+                       axis=axis,
+                       method=method,
+                       out=out,
+                       weights=wgt,
+                       weak_q=weak_q)
+    return result
+
+
+def _get_indexes(arr, virtual_indexes, valid_values_count):
+    """
+    Get the valid indexes of arr neighbouring virtual_indexes.
+    Note
+    This is a companion function to linear interpolation of
+    Quantiles
+
+    Returns
+    -------
+    (previous_indexes, next_indexes): Tuple
+        A Tuple of virtual_indexes neighbouring indexes
+    """
+    previous_indexes = floor(virtual_indexes, out=...)
+    next_indexes = add(previous_indexes, 1, out=...)
+    indexes_above_bounds = virtual_indexes >= valid_values_count - 1
+    # When indexes is above max index, take the max value of the array
+    if indexes_above_bounds.any():
+        previous_indexes[indexes_above_bounds] = -1
+        next_indexes[indexes_above_bounds] = -1
+    # When indexes is below min index, take the min value of the array
+    indexes_below_bounds = virtual_indexes < 0
+    if indexes_below_bounds.any():
+        previous_indexes[indexes_below_bounds] = 0
+        next_indexes[indexes_below_bounds] = 0
+    if np.issubdtype(arr.dtype, np.inexact):
+        # After the sort, slices having NaNs will have for last element a NaN
+        virtual_indexes_nans = np.isnan(virtual_indexes)
+        if virtual_indexes_nans.any():
+            previous_indexes[virtual_indexes_nans] = -1
+            next_indexes[virtual_indexes_nans] = -1
+    previous_indexes = previous_indexes.astype(np.intp)
+    next_indexes = next_indexes.astype(np.intp)
+    return previous_indexes, next_indexes
+
+
+def _quantile(
+    arr: "np.typing.ArrayLike",
+    quantiles: np.ndarray,
+    axis: int = -1,
+    method: str = "linear",
+    out: np.ndarray | None = None,
+    weights: "np.typing.ArrayLike | None" = None,
+    weak_q: bool = False,
+) -> np.ndarray:
+    """
+    Private function that doesn't support extended axis or keepdims.
+    These methods are extended to this function using _ureduce
+    See nanpercentile for parameter usage
+    It computes the quantiles of the array for the given axis.
+    A linear interpolation is performed based on the `method`.
+
+    By default, the method is "linear" where alpha == beta == 1 which
+    performs the 7th method of Hyndman&Fan.
+    With "median_unbiased" we get alpha == beta == 1/3
+    thus the 8th method of Hyndman&Fan.
+    """
+    # --- Setup
+    arr = np.asanyarray(arr)
+    values_count = arr.shape[axis]
+    # The dimensions of `q` are prepended to the output shape, so we need the
+    # axis being sampled from `arr` to be last.
+    if axis != 0:  # But moveaxis is slow, so only call it if necessary.
+        arr = np.moveaxis(arr, axis, destination=0)
+    supports_nans = (
+        np.issubdtype(arr.dtype, np.inexact) or arr.dtype.kind in 'Mm'
+    )
+
+    if weights is None:
+        # --- Computation of indexes
+        # Index where to find the value in the sorted array.
+        # Virtual because it is a floating point value, not a valid index.
+        # The nearest neighbours are used for interpolation
+        try:
+            method_props = _QuantileMethods[method]
+        except KeyError:
+            raise ValueError(
+                f"{method!r} is not a valid method. Use one of: "
+                f"{_QuantileMethods.keys()}") from None
+        virtual_indexes = method_props["get_virtual_index"](values_count,
+                                                            quantiles)
+        virtual_indexes = np.asanyarray(virtual_indexes)
+
+        if method_props["fix_gamma"] is None:
+            supports_integers = True
+        else:
+            int_virtual_indices = np.issubdtype(virtual_indexes.dtype,
+                                                np.integer)
+            supports_integers = method == 'linear' and int_virtual_indices
+
+        if supports_integers:
+            # No interpolation needed, take the points along axis
+            if supports_nans:
+                # may contain nan, which would sort to the end
+                arr.partition(
+                    concatenate((virtual_indexes.ravel(), [-1])), axis=0,
+                )
+                slices_having_nans = np.isnan(arr[-1, ...])
+            else:
+                # cannot contain nan
+                arr.partition(virtual_indexes.ravel(), axis=0)
+                slices_having_nans = np.array(False, dtype=bool)
+            result = take(arr, virtual_indexes, axis=0, out=out)
+        else:
+            previous_indexes, next_indexes = _get_indexes(arr,
+                                                          virtual_indexes,
+                                                          values_count)
+            # --- Sorting
+            arr.partition(
+                np.unique(np.concatenate(([0, -1],
+                                          previous_indexes.ravel(),
+                                          next_indexes.ravel(),
+                                          ))),
+                axis=0)
+            if supports_nans:
+                slices_having_nans = np.isnan(arr[-1, ...])
+            else:
+                slices_having_nans = None
+            # --- Get values from indexes
+            previous = arr[previous_indexes]
+            next = arr[next_indexes]
+            # --- Linear interpolation
+            gamma = _get_gamma(virtual_indexes, previous_indexes,
+                               method_props)
+            if weak_q:
+                gamma = float(gamma)
+            else:
+                result_shape = virtual_indexes.shape + (1,) * (arr.ndim - 1)
+                gamma = gamma.reshape(result_shape)
+            result = _lerp(previous,
+                        next,
+                        gamma,
+                        out=out)
+    else:
+        # Weighted case
+        # This implements method="inverted_cdf", the only supported weighted
+        # method, which needs to sort anyway.
+        weights = np.asanyarray(weights)
+        if axis != 0:
+            weights = np.moveaxis(weights, axis, destination=0)
+        index_array = np.argsort(arr, axis=0)
+
+        # arr = arr[index_array, ...]  # but this adds trailing dimensions of
+        # 1.
+        arr = np.take_along_axis(arr, index_array, axis=0)
+        if weights.shape == arr.shape:
+            weights = np.take_along_axis(weights, index_array, axis=0)
+        else:
+            # weights is 1d
+            weights = weights.reshape(-1)[index_array, ...]
+
+        if supports_nans:
+            # may contain nan, which would sort to the end
+            slices_having_nans = np.isnan(arr[-1, ...])
+        else:
+            # cannot contain nan
+            slices_having_nans = np.array(False, dtype=bool)
+
+        # We use the weights to calculate the empirical cumulative
+        # distribution function cdf
+        cdf = weights.cumsum(axis=0, dtype=np.float64)
+        cdf /= cdf[-1, ...]  # normalization to 1
+        if np.isnan(cdf[-1]).any():
+            # Above calculations should normally warn for the zero/inf case.
+            raise ValueError("Weights included NaN, inf or were all zero.")
+        # Search index i such that
+        #   sum(weights[j], j=0..i-1) < quantile <= sum(weights[j], j=0..i)
+        # is then equivalent to
+        #   cdf[i-1] < quantile <= cdf[i]
+        # Unfortunately, searchsorted only accepts 1-d arrays as first
+        # argument, so we will need to iterate over dimensions.
+
+        # Without the following cast, searchsorted can return surprising
+        # results, e.g.
+        #   np.searchsorted(np.array([0.2, 0.4, 0.6, 0.8, 1.]),
+        #                   np.array(0.4, dtype=np.float32), side="left")
+        # returns 2 instead of 1 because 0.4 is not binary representable.
+        if quantiles.dtype.kind == "f":
+            cdf = cdf.astype(quantiles.dtype)
+        # Weights must be non-negative, so we might have zero weights at the
+        # beginning leading to some leading zeros in cdf. The call to
+        # np.searchsorted for quantiles=0 will then pick the first element,
+        # but should pick the first one larger than zero. We
+        # therefore simply set 0 values in cdf to -1.
+        if np.any(cdf[0, ...] == 0):
+            cdf[cdf == 0] = -1
+
+        def find_cdf_1d(arr, cdf):
+            indices = np.searchsorted(cdf, quantiles, side="left")
+            # We might have reached the maximum with i = len(arr), e.g. for
+            # quantiles = 1, and need to cut it to len(arr) - 1.
+            indices = minimum(indices, values_count - 1)
+            result = take(arr, indices, axis=0)
+            return result
+
+        r_shape = arr.shape[1:]
+        if quantiles.ndim > 0:
+            r_shape = quantiles.shape + r_shape
+        if out is None:
+            result = np.empty_like(arr, shape=r_shape)
+        else:
+            if out.shape != r_shape:
+                msg = (f"Wrong shape of argument 'out', shape={r_shape} is "
+                       f"required; got shape={out.shape}.")
+                raise ValueError(msg)
+            result = out
+
+        # See apply_along_axis, which we do for axis=0. Note that Ni = (,)
+        # always, so we remove it here.
+        Nk = arr.shape[1:]
+        for kk in np.ndindex(Nk):
+            result[(...,) + kk] = find_cdf_1d(
+                arr[np.s_[:, ] + kk], cdf[np.s_[:, ] + kk]
+            )
+
+        # Make result the same as in unweighted inverted_cdf.
+        if result.shape == () and result.dtype == np.dtype("O"):
+            result = result.item()
+
+    if np.any(slices_having_nans):
+        if result.ndim == 0 and out is None:
+            # can't write to a scalar, but indexing will be correct
+            result = arr[-1]
+        else:
+            np.copyto(result, arr[-1, ...], where=slices_having_nans)
+    return result
+
+
+def _trapezoid_dispatcher(y, x=None, dx=None, axis=None):
+    return (y, x)
+
+
+@array_function_dispatch(_trapezoid_dispatcher)
+def trapezoid(y, x=None, dx=1.0, axis=-1):
+    r"""
+    Integrate along the given axis using the composite trapezoidal rule.
+
+    If `x` is provided, the integration happens in sequence along its
+    elements - they are not sorted.
+
+    Integrate `y` (`x`) along each 1d slice on the given axis, compute
+    :math:`\int y(x) dx`.
+    When `x` is specified, this integrates along the parametric curve,
+    computing :math:`\int_t y(t) dt =
+    \int_t y(t) \left.\frac{dx}{dt}\right|_{x=x(t)} dt`.
+
+    .. versionadded:: 2.0.0
+
+    Parameters
+    ----------
+    y : array_like
+        Input array to integrate.
+    x : array_like, optional
+        The sample points corresponding to the `y` values. If `x` is None,
+        the sample points are assumed to be evenly spaced `dx` apart. The
+        default is None.
+    dx : scalar, optional
+        The spacing between sample points when `x` is None. The default is 1.
+    axis : int, optional
+        The axis along which to integrate.
+
+    Returns
+    -------
+    trapezoid : float or ndarray
+        Definite integral of `y` = n-dimensional array as approximated along
+        a single axis by the trapezoidal rule. If `y` is a 1-dimensional array,
+        then the result is a float. If `n` is greater than 1, then the result
+        is an `n`-1 dimensional array.
+
+    See Also
+    --------
+    sum, cumsum
+
+    Notes
+    -----
+    Image [2]_ illustrates trapezoidal rule -- y-axis locations of points
+    will be taken from `y` array, by default x-axis distances between
+    points will be 1.0, alternatively they can be provided with `x` array
+    or with `dx` scalar.  Return value will be equal to combined area under
+    the red lines.
+
+
+    References
+    ----------
+    .. [1] Wikipedia page: https://en.wikipedia.org/wiki/Trapezoidal_rule
+
+    .. [2] Illustration image:
+           https://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Use the trapezoidal rule on evenly spaced points:
+
+    >>> np.trapezoid([1, 2, 3])
+    4.0
+
+    The spacing between sample points can be selected by either the
+    ``x`` or ``dx`` arguments:
+
+    >>> np.trapezoid([1, 2, 3], x=[4, 6, 8])
+    8.0
+    >>> np.trapezoid([1, 2, 3], dx=2)
+    8.0
+
+    Using a decreasing ``x`` corresponds to integrating in reverse:
+
+    >>> np.trapezoid([1, 2, 3], x=[8, 6, 4])
+    -8.0
+
+    More generally ``x`` is used to integrate along a parametric curve. We can
+    estimate the integral :math:`\int_0^1 x^2 = 1/3` using:
+
+    >>> x = np.linspace(0, 1, num=50)
+    >>> y = x**2
+    >>> np.trapezoid(y, x)
+    0.33340274885464394
+
+    Or estimate the area of a circle, noting we repeat the sample which closes
+    the curve:
+
+    >>> theta = np.linspace(0, 2 * np.pi, num=1000, endpoint=True)
+    >>> np.trapezoid(np.cos(theta), x=np.sin(theta))
+    3.141571941375841
+
+    ``np.trapezoid`` can be applied along a specified axis to do multiple
+    computations in one call:
+
+    >>> a = np.arange(6).reshape(2, 3)
+    >>> a
+    array([[0, 1, 2],
+           [3, 4, 5]])
+    >>> np.trapezoid(a, axis=0)
+    array([1.5, 2.5, 3.5])
+    >>> np.trapezoid(a, axis=1)
+    array([2.,  8.])
+    """
+
+    y = asanyarray(y)
+    if x is None:
+        d = dx
+    else:
+        x = asanyarray(x)
+        if x.ndim == 1:
+            d = diff(x)
+            # reshape to correct shape
+            shape = [1] * y.ndim
+            shape[axis] = d.shape[0]
+            d = d.reshape(shape)
+        else:
+            d = diff(x, axis=axis)
+    nd = y.ndim
+    slice1 = [slice(None)] * nd
+    slice2 = [slice(None)] * nd
+    slice1[axis] = slice(1, None)
+    slice2[axis] = slice(None, -1)
+    try:
+        ret = (d * (y[tuple(slice1)] + y[tuple(slice2)]) / 2.0).sum(axis)
+    except ValueError:
+        # Operations didn't work, cast to ndarray
+        d = np.asarray(d)
+        y = np.asarray(y)
+        ret = add.reduce(d * (y[tuple(slice1)] + y[tuple(slice2)]) / 2.0, axis)
+    return ret
+
+
+def _meshgrid_dispatcher(*xi, copy=None, sparse=None, indexing=None):
+    return xi
+
+
+# Based on scitools meshgrid
+@array_function_dispatch(_meshgrid_dispatcher)
+def meshgrid(*xi, copy=True, sparse=False, indexing='xy'):
+    """
+    Return a tuple of coordinate matrices from coordinate vectors.
+
+    Make N-D coordinate arrays for vectorized evaluations of
+    N-D scalar/vector fields over N-D grids, given
+    one-dimensional coordinate arrays x1, x2,..., xn.
+
+    Parameters
+    ----------
+    x1, x2,..., xn : array_like
+        1-D arrays representing the coordinates of a grid.
+    indexing : {'xy', 'ij'}, optional
+        Cartesian ('xy', default) or matrix ('ij') indexing of output.
+        See Notes for more details.
+    sparse : bool, optional
+        If True the shape of the returned coordinate array for dimension *i*
+        is reduced from ``(N1, ..., Ni, ... Nn)`` to
+        ``(1, ..., 1, Ni, 1, ..., 1)``.  These sparse coordinate grids are
+        intended to be used with :ref:`basics.broadcasting`.  When all
+        coordinates are used in an expression, broadcasting still leads to a
+        fully-dimensonal result array.
+
+        Default is False.
+
+    copy : bool, optional
+        If False, a view into the original arrays are returned in order to
+        conserve memory.  Default is True.  Please note that
+        ``sparse=False, copy=False`` will likely return non-contiguous
+        arrays.  Furthermore, more than one element of a broadcast array
+        may refer to a single memory location.  If you need to write to the
+        arrays, make copies first.
+
+    Returns
+    -------
+    X1, X2,..., XN : tuple of ndarrays
+        For vectors `x1`, `x2`,..., `xn` with lengths ``Ni=len(xi)``,
+        returns ``(N1, N2, N3,..., Nn)`` shaped arrays if indexing='ij'
+        or ``(N2, N1, N3,..., Nn)`` shaped arrays if indexing='xy'
+        with the elements of `xi` repeated to fill the matrix along
+        the first dimension for `x1`, the second for `x2` and so on.
+
+    Notes
+    -----
+    This function supports both indexing conventions through the indexing
+    keyword argument.  Giving the string 'ij' returns a meshgrid with
+    matrix indexing, while 'xy' returns a meshgrid with Cartesian indexing.
+    In the 2-D case with inputs of length M and N, the outputs are of shape
+    (N, M) for 'xy' indexing and (M, N) for 'ij' indexing.  In the 3-D case
+    with inputs of length M, N and P, outputs are of shape (N, M, P) for
+    'xy' indexing and (M, N, P) for 'ij' indexing.  The difference is
+    illustrated by the following code snippet::
+
+        xv, yv = np.meshgrid(x, y, indexing='ij')
+        for i in range(nx):
+            for j in range(ny):
+                # treat xv[i,j], yv[i,j]
+
+        xv, yv = np.meshgrid(x, y, indexing='xy')
+        for i in range(nx):
+            for j in range(ny):
+                # treat xv[j,i], yv[j,i]
+
+    In the 1-D and 0-D case, the indexing and sparse keywords have no effect.
+
+    See Also
+    --------
+    mgrid : Construct a multi-dimensional "meshgrid" using indexing notation.
+    ogrid : Construct an open multi-dimensional "meshgrid" using indexing
+            notation.
+    :ref:`how-to-index`
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> nx, ny = (3, 2)
+    >>> x = np.linspace(0, 1, nx)
+    >>> y = np.linspace(0, 1, ny)
+    >>> xv, yv = np.meshgrid(x, y)
+    >>> xv
+    array([[0. , 0.5, 1. ],
+           [0. , 0.5, 1. ]])
+    >>> yv
+    array([[0.,  0.,  0.],
+           [1.,  1.,  1.]])
+
+    The result of `meshgrid` is a coordinate grid:
+
+    >>> import matplotlib.pyplot as plt
+    >>> plt.plot(xv, yv, marker='o', color='k', linestyle='none')
+    >>> plt.show()
+
+    You can create sparse output arrays to save memory and computation time.
+
+    >>> xv, yv = np.meshgrid(x, y, sparse=True)
+    >>> xv
+    array([[0. ,  0.5,  1. ]])
+    >>> yv
+    array([[0.],
+           [1.]])
+
+    `meshgrid` is very useful to evaluate functions on a grid. If the
+    function depends on all coordinates, both dense and sparse outputs can be
+    used.
+
+    >>> x = np.linspace(-5, 5, 101)
+    >>> y = np.linspace(-5, 5, 101)
+    >>> # full coordinate arrays
+    >>> xx, yy = np.meshgrid(x, y)
+    >>> zz = np.sqrt(xx**2 + yy**2)
+    >>> xx.shape, yy.shape, zz.shape
+    ((101, 101), (101, 101), (101, 101))
+    >>> # sparse coordinate arrays
+    >>> xs, ys = np.meshgrid(x, y, sparse=True)
+    >>> zs = np.sqrt(xs**2 + ys**2)
+    >>> xs.shape, ys.shape, zs.shape
+    ((1, 101), (101, 1), (101, 101))
+    >>> np.array_equal(zz, zs)
+    True
+
+    >>> h = plt.contourf(x, y, zs)
+    >>> plt.axis('scaled')
+    >>> plt.colorbar()
+    >>> plt.show()
+    """
+    ndim = len(xi)
+
+    if indexing not in ['xy', 'ij']:
+        raise ValueError(
+            "Valid values for `indexing` are 'xy' and 'ij'.")
+
+    s0 = (1,) * ndim
+    output = [np.asanyarray(x).reshape(s0[:i] + (-1,) + s0[i + 1:])
+              for i, x in enumerate(xi)]
+
+    if indexing == 'xy' and ndim > 1:
+        # switch first and second axis
+        output[0].shape = (1, -1) + s0[2:]
+        output[1].shape = (-1, 1) + s0[2:]
+
+    if not sparse:
+        # Return the full N-D matrix (not only the 1-D vector)
+        output = np.broadcast_arrays(*output, subok=True)
+
+    if copy:
+        output = tuple(x.copy() for x in output)
+
+    return output
+
+
+def _delete_dispatcher(arr, obj, axis=None):
+    return (arr, obj)
+
+
+@array_function_dispatch(_delete_dispatcher)
+def delete(arr, obj, axis=None):
+    """
+    Return a new array with sub-arrays along an axis deleted. For a one
+    dimensional array, this returns those entries not returned by
+    `arr[obj]`.
+
+    Parameters
+    ----------
+    arr : array_like
+        Input array.
+    obj : slice, int, array-like of ints or bools
+        Indicate indices of sub-arrays to remove along the specified axis.
+
+        .. versionchanged:: 1.19.0
+            Boolean indices are now treated as a mask of elements to remove,
+            rather than being cast to the integers 0 and 1.
+
+    axis : int, optional
+        The axis along which to delete the subarray defined by `obj`.
+        If `axis` is None, `obj` is applied to the flattened array.
+
+    Returns
+    -------
+    out : ndarray
+        A copy of `arr` with the elements specified by `obj` removed. Note
+        that `delete` does not occur in-place. If `axis` is None, `out` is
+        a flattened array.
+
+    See Also
+    --------
+    insert : Insert elements into an array.
+    append : Append elements at the end of an array.
+
+    Notes
+    -----
+    Often it is preferable to use a boolean mask. For example:
+
+    >>> arr = np.arange(12) + 1
+    >>> mask = np.ones(len(arr), dtype=bool)
+    >>> mask[[0,2,4]] = False
+    >>> result = arr[mask,...]
+
+    Is equivalent to ``np.delete(arr, [0,2,4], axis=0)``, but allows further
+    use of `mask`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
+    >>> arr
+    array([[ 1,  2,  3,  4],
+           [ 5,  6,  7,  8],
+           [ 9, 10, 11, 12]])
+    >>> np.delete(arr, 1, 0)
+    array([[ 1,  2,  3,  4],
+           [ 9, 10, 11, 12]])
+
+    >>> np.delete(arr, np.s_[::2], 1)
+    array([[ 2,  4],
+           [ 6,  8],
+           [10, 12]])
+    >>> np.delete(arr, [1,3,5], None)
+    array([ 1,  3,  5,  7,  8,  9, 10, 11, 12])
+
+    """
+    conv = _array_converter(arr)
+    arr, = conv.as_arrays(subok=False)
+
+    ndim = arr.ndim
+    arrorder = 'F' if arr.flags.fnc else 'C'
+    if axis is None:
+        if ndim != 1:
+            arr = arr.ravel()
+        # needed for np.matrix, which is still not 1d after being ravelled
+        ndim = arr.ndim
+        axis = ndim - 1
+    else:
+        axis = normalize_axis_index(axis, ndim)
+
+    slobj = [slice(None)] * ndim
+    N = arr.shape[axis]
+    newshape = list(arr.shape)
+
+    if isinstance(obj, slice):
+        start, stop, step = obj.indices(N)
+        xr = range(start, stop, step)
+        numtodel = len(xr)
+
+        if numtodel <= 0:
+            return conv.wrap(arr.copy(order=arrorder), to_scalar=False)
+
+        # Invert if step is negative:
+        if step < 0:
+            step = -step
+            start = xr[-1]
+            stop = xr[0] + 1
+
+        newshape[axis] -= numtodel
+        new = empty(newshape, arr.dtype, arrorder)
+        # copy initial chunk
+        if start == 0:
+            pass
+        else:
+            slobj[axis] = slice(None, start)
+            new[tuple(slobj)] = arr[tuple(slobj)]
+        # copy end chunk
+        if stop == N:
+            pass
+        else:
+            slobj[axis] = slice(stop - numtodel, None)
+            slobj2 = [slice(None)] * ndim
+            slobj2[axis] = slice(stop, None)
+            new[tuple(slobj)] = arr[tuple(slobj2)]
+        # copy middle pieces
+        if step == 1:
+            pass
+        else:  # use array indexing.
+            keep = ones(stop - start, dtype=bool)
+            keep[:stop - start:step] = False
+            slobj[axis] = slice(start, stop - numtodel)
+            slobj2 = [slice(None)] * ndim
+            slobj2[axis] = slice(start, stop)
+            arr = arr[tuple(slobj2)]
+            slobj2[axis] = keep
+            new[tuple(slobj)] = arr[tuple(slobj2)]
+
+        return conv.wrap(new, to_scalar=False)
+
+    if isinstance(obj, (int, integer)) and not isinstance(obj, bool):
+        single_value = True
+    else:
+        single_value = False
+        _obj = obj
+        obj = np.asarray(obj)
+        # `size == 0` to allow empty lists similar to indexing, but (as there)
+        # is really too generic:
+        if obj.size == 0 and not isinstance(_obj, np.ndarray):
+            obj = obj.astype(intp)
+        elif obj.size == 1 and obj.dtype.kind in "ui":
+            # For a size 1 integer array we can use the single-value path
+            # (most dtypes, except boolean, should just fail later).
+            obj = obj.item()
+            single_value = True
+
+    if single_value:
+        # optimization for a single value
+        if (obj < -N or obj >= N):
+            raise IndexError(
+                f"index {obj} is out of bounds for axis {axis} with "
+                f"size {N}")
+        if (obj < 0):
+            obj += N
+        newshape[axis] -= 1
+        new = empty(newshape, arr.dtype, arrorder)
+        slobj[axis] = slice(None, obj)
+        new[tuple(slobj)] = arr[tuple(slobj)]
+        slobj[axis] = slice(obj, None)
+        slobj2 = [slice(None)] * ndim
+        slobj2[axis] = slice(obj + 1, None)
+        new[tuple(slobj)] = arr[tuple(slobj2)]
+    else:
+        if obj.dtype == bool:
+            if obj.shape != (N,):
+                raise ValueError('boolean array argument obj to delete '
+                                 'must be one dimensional and match the axis '
+                                 f'length of {N}')
+
+            # optimization, the other branch is slower
+            keep = ~obj
+        else:
+            keep = ones(N, dtype=bool)
+            keep[obj,] = False
+
+        slobj[axis] = keep
+        new = arr[tuple(slobj)]
+
+    return conv.wrap(new, to_scalar=False)
+
+
+def _insert_dispatcher(arr, obj, values, axis=None):
+    return (arr, obj, values)
+
+
+@array_function_dispatch(_insert_dispatcher)
+def insert(arr, obj, values, axis=None):
+    """
+    Insert values along the given axis before the given indices.
+
+    Parameters
+    ----------
+    arr : array_like
+        Input array.
+    obj : slice, int, array-like of ints or bools
+        Object that defines the index or indices before which `values` is
+        inserted.
+
+        .. versionchanged:: 2.1.2
+            Boolean indices are now treated as a mask of elements to insert,
+            rather than being cast to the integers 0 and 1.
+
+        Support for multiple insertions when `obj` is a single scalar or a
+        sequence with one element (similar to calling insert multiple
+        times).
+    values : array_like
+        Values to insert into `arr`. If the type of `values` is different
+        from that of `arr`, `values` is converted to the type of `arr`.
+        `values` should be shaped so that ``arr[...,obj,...] = values``
+        is legal.
+    axis : int, optional
+        Axis along which to insert `values`.  If `axis` is None then `arr`
+        is flattened first.
+
+    Returns
+    -------
+    out : ndarray
+        A copy of `arr` with `values` inserted.  Note that `insert`
+        does not occur in-place: a new array is returned. If
+        `axis` is None, `out` is a flattened array.
+
+    See Also
+    --------
+    append : Append elements at the end of an array.
+    concatenate : Join a sequence of arrays along an existing axis.
+    delete : Delete elements from an array.
+
+    Notes
+    -----
+    Note that for higher dimensional inserts ``obj=0`` behaves very different
+    from ``obj=[0]`` just like ``arr[:,0,:] = values`` is different from
+    ``arr[:,[0],:] = values``. This is because of the difference between basic
+    and advanced :ref:`indexing <basics.indexing>`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(6).reshape(3, 2)
+    >>> a
+    array([[0, 1],
+           [2, 3],
+           [4, 5]])
+    >>> np.insert(a, 1, 6)
+    array([0, 6, 1, 2, 3, 4, 5])
+    >>> np.insert(a, 1, 6, axis=1)
+    array([[0, 6, 1],
+           [2, 6, 3],
+           [4, 6, 5]])
+
+    Difference between sequence and scalars,
+    showing how ``obj=[1]`` behaves different from ``obj=1``:
+
+    >>> np.insert(a, [1], [[7],[8],[9]], axis=1)
+    array([[0, 7, 1],
+           [2, 8, 3],
+           [4, 9, 5]])
+    >>> np.insert(a, 1, [[7],[8],[9]], axis=1)
+    array([[0, 7, 8, 9, 1],
+           [2, 7, 8, 9, 3],
+           [4, 7, 8, 9, 5]])
+    >>> np.array_equal(np.insert(a, 1, [7, 8, 9], axis=1),
+    ...                np.insert(a, [1], [[7],[8],[9]], axis=1))
+    True
+
+    >>> b = a.flatten()
+    >>> b
+    array([0, 1, 2, 3, 4, 5])
+    >>> np.insert(b, [2, 2], [6, 7])
+    array([0, 1, 6, 7, 2, 3, 4, 5])
+
+    >>> np.insert(b, slice(2, 4), [7, 8])
+    array([0, 1, 7, 2, 8, 3, 4, 5])
+
+    >>> np.insert(b, [2, 2], [7.13, False]) # type casting
+    array([0, 1, 7, 0, 2, 3, 4, 5])
+
+    >>> x = np.arange(8).reshape(2, 4)
+    >>> idx = (1, 3)
+    >>> np.insert(x, idx, 999, axis=1)
+    array([[  0, 999,   1,   2, 999,   3],
+           [  4, 999,   5,   6, 999,   7]])
+
+    """
+    conv = _array_converter(arr)
+    arr, = conv.as_arrays(subok=False)
+
+    ndim = arr.ndim
+    arrorder = 'F' if arr.flags.fnc else 'C'
+    if axis is None:
+        if ndim != 1:
+            arr = arr.ravel()
+        # needed for np.matrix, which is still not 1d after being ravelled
+        ndim = arr.ndim
+        axis = ndim - 1
+    else:
+        axis = normalize_axis_index(axis, ndim)
+    slobj = [slice(None)] * ndim
+    N = arr.shape[axis]
+    newshape = list(arr.shape)
+
+    if isinstance(obj, slice):
+        # turn it into a range object
+        indices = arange(*obj.indices(N), dtype=intp)
+    else:
+        # need to copy obj, because indices will be changed in-place
+        indices = np.array(obj)
+        if indices.dtype == bool:
+            if obj.ndim != 1:
+                raise ValueError('boolean array argument obj to insert '
+                                'must be one dimensional')
+            indices = np.flatnonzero(obj)
+        elif indices.ndim > 1:
+            raise ValueError(
+                "index array argument obj to insert must be one dimensional "
+                "or scalar")
+    if indices.size == 1:
+        index = indices.item()
+        if index < -N or index > N:
+            raise IndexError(f"index {obj} is out of bounds for axis {axis} "
+                             f"with size {N}")
+        if (index < 0):
+            index += N
+
+        # There are some object array corner cases here, but we cannot avoid
+        # that:
+        values = array(values, copy=None, ndmin=arr.ndim, dtype=arr.dtype)
+        if indices.ndim == 0:
+            # broadcasting is very different here, since a[:,0,:] = ... behaves
+            # very different from a[:,[0],:] = ...! This changes values so that
+            # it works likes the second case. (here a[:,0:1,:])
+            values = np.moveaxis(values, 0, axis)
+        numnew = values.shape[axis]
+        newshape[axis] += numnew
+        new = empty(newshape, arr.dtype, arrorder)
+        slobj[axis] = slice(None, index)
+        new[tuple(slobj)] = arr[tuple(slobj)]
+        slobj[axis] = slice(index, index + numnew)
+        new[tuple(slobj)] = values
+        slobj[axis] = slice(index + numnew, None)
+        slobj2 = [slice(None)] * ndim
+        slobj2[axis] = slice(index, None)
+        new[tuple(slobj)] = arr[tuple(slobj2)]
+
+        return conv.wrap(new, to_scalar=False)
+
+    elif indices.size == 0 and not isinstance(obj, np.ndarray):
+        # Can safely cast the empty list to intp
+        indices = indices.astype(intp)
+
+    indices[indices < 0] += N
+
+    numnew = len(indices)
+    order = indices.argsort(kind='mergesort')   # stable sort
+    indices[order] += np.arange(numnew)
+
+    newshape[axis] += numnew
+    old_mask = ones(newshape[axis], dtype=bool)
+    old_mask[indices] = False
+
+    new = empty(newshape, arr.dtype, arrorder)
+    slobj2 = [slice(None)] * ndim
+    slobj[axis] = indices
+    slobj2[axis] = old_mask
+    new[tuple(slobj)] = values
+    new[tuple(slobj2)] = arr
+
+    return conv.wrap(new, to_scalar=False)
+
+
+def _append_dispatcher(arr, values, axis=None):
+    return (arr, values)
+
+
+@array_function_dispatch(_append_dispatcher)
+def append(arr, values, axis=None):
+    """
+    Append values to the end of an array.
+
+    Parameters
+    ----------
+    arr : array_like
+        Values are appended to a copy of this array.
+    values : array_like
+        These values are appended to a copy of `arr`.  It must be of the
+        correct shape (the same shape as `arr`, excluding `axis`).  If
+        `axis` is not specified, `values` can be any shape and will be
+        flattened before use.
+    axis : int, optional
+        The axis along which `values` are appended.  If `axis` is not
+        given, both `arr` and `values` are flattened before use.
+
+    Returns
+    -------
+    append : ndarray
+        A copy of `arr` with `values` appended to `axis`.  Note that
+        `append` does not occur in-place: a new array is allocated and
+        filled.  If `axis` is None, `out` is a flattened array.
+
+    See Also
+    --------
+    insert : Insert elements into an array.
+    delete : Delete elements from an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
+    array([1, 2, 3, ..., 7, 8, 9])
+
+    When `axis` is specified, `values` must have the correct shape.
+
+    >>> np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9]], axis=0)
+    array([[1, 2, 3],
+           [4, 5, 6],
+           [7, 8, 9]])
+
+    >>> np.append([[1, 2, 3], [4, 5, 6]], [7, 8, 9], axis=0)
+    Traceback (most recent call last):
+        ...
+    ValueError: all the input arrays must have same number of dimensions, but
+    the array at index 0 has 2 dimension(s) and the array at index 1 has 1
+    dimension(s)
+
+    >>> a = np.array([1, 2], dtype=int)
+    >>> c = np.append(a, [])
+    >>> c
+    array([1., 2.])
+    >>> c.dtype
+    float64
+
+    Default dtype for empty ndarrays is `float64` thus making the output of dtype
+    `float64` when appended with dtype `int64`
+
+    """
+    arr = asanyarray(arr)
+    if axis is None:
+        if arr.ndim != 1:
+            arr = arr.ravel()
+        values = ravel(values)
+        axis = arr.ndim - 1
+    return concatenate((arr, values), axis=axis)
+
+
+def _digitize_dispatcher(x, bins, right=None):
+    return (x, bins)
+
+
+@array_function_dispatch(_digitize_dispatcher)
+def digitize(x, bins, right=False):
+    """
+    Return the indices of the bins to which each value in input array belongs.
+
+    =========  =============  ============================
+    `right`    order of bins  returned index `i` satisfies
+    =========  =============  ============================
+    ``False``  increasing     ``bins[i-1] <= x < bins[i]``
+    ``True``   increasing     ``bins[i-1] < x <= bins[i]``
+    ``False``  decreasing     ``bins[i-1] > x >= bins[i]``
+    ``True``   decreasing     ``bins[i-1] >= x > bins[i]``
+    =========  =============  ============================
+
+    If values in `x` are beyond the bounds of `bins`, 0 or ``len(bins)`` is
+    returned as appropriate.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array to be binned. Prior to NumPy 1.10.0, this array had to
+        be 1-dimensional, but can now have any shape.
+    bins : array_like
+        Array of bins. It has to be 1-dimensional and monotonic.
+    right : bool, optional
+        Indicating whether the intervals include the right or the left bin
+        edge. Default behavior is (right==False) indicating that the interval
+        does not include the right edge. The left bin end is open in this
+        case, i.e., bins[i-1] <= x < bins[i] is the default behavior for
+        monotonically increasing bins.
+
+    Returns
+    -------
+    indices : ndarray of ints
+        Output array of indices, of same shape as `x`.
+
+    Raises
+    ------
+    ValueError
+        If `bins` is not monotonic.
+    TypeError
+        If the type of the input is complex.
+
+    See Also
+    --------
+    bincount, histogram, unique, searchsorted
+
+    Notes
+    -----
+    If values in `x` are such that they fall outside the bin range,
+    attempting to index `bins` with the indices that `digitize` returns
+    will result in an IndexError.
+
+    .. versionadded:: 1.10.0
+
+    `numpy.digitize` is  implemented in terms of `numpy.searchsorted`.
+    This means that a binary search is used to bin the values, which scales
+    much better for larger number of bins than the previous linear search.
+    It also removes the requirement for the input array to be 1-dimensional.
+
+    For monotonically *increasing* `bins`, the following are equivalent::
+
+        np.digitize(x, bins, right=True)
+        np.searchsorted(bins, x, side='left')
+
+    Note that as the order of the arguments are reversed, the side must be too.
+    The `searchsorted` call is marginally faster, as it does not do any
+    monotonicity checks. Perhaps more importantly, it supports all dtypes.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([0.2, 6.4, 3.0, 1.6])
+    >>> bins = np.array([0.0, 1.0, 2.5, 4.0, 10.0])
+    >>> inds = np.digitize(x, bins)
+    >>> inds
+    array([1, 4, 3, 2])
+    >>> for n in range(x.size):
+    ...   print(bins[inds[n]-1], "<=", x[n], "<", bins[inds[n]])
+    ...
+    0.0 <= 0.2 < 1.0
+    4.0 <= 6.4 < 10.0
+    2.5 <= 3.0 < 4.0
+    1.0 <= 1.6 < 2.5
+
+    >>> x = np.array([1.2, 10.0, 12.4, 15.5, 20.])
+    >>> bins = np.array([0, 5, 10, 15, 20])
+    >>> np.digitize(x,bins,right=True)
+    array([1, 2, 3, 4, 4])
+    >>> np.digitize(x,bins,right=False)
+    array([1, 3, 3, 4, 5])
+    """
+    x = _nx.asarray(x)
+    bins = _nx.asarray(bins)
+
+    # here for compatibility, searchsorted below is happy to take this
+    if np.issubdtype(x.dtype, _nx.complexfloating):
+        raise TypeError("x may not be complex")
+
+    mono = _monotonicity(bins)
+    if mono == 0:
+        raise ValueError("bins must be monotonically increasing or decreasing")
+
+    # this is backwards because the arguments below are swapped
+    side = 'left' if right else 'right'
+    if mono == -1:
+        # reverse the bins, and invert the results
+        return len(bins) - _nx.searchsorted(bins[::-1], x, side=side)
+    else:
+        return _nx.searchsorted(bins, x, side=side)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..0012dccf2ec0d3542d36f9ccf1f7686dcd549679
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_function_base_impl.pyi
@@ -0,0 +1,2324 @@
+from _typeshed import ConvertibleToInt, Incomplete
+from collections.abc import Callable, Iterable, Sequence
+from typing import (
+    Any,
+    Concatenate,
+    Literal as L,
+    Never,
+    ParamSpec,
+    Protocol,
+    SupportsIndex,
+    SupportsInt,
+    TypeAlias,
+    overload,
+    type_check_only,
+)
+from typing_extensions import TypeIs, TypeVar
+
+import numpy as np
+from numpy import _OrderKACF
+from numpy._core.multiarray import bincount
+from numpy._globals import _NoValueType
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ArrayLikeInt_co,
+    _ArrayLikeNumber_co,
+    _ArrayLikeObject_co,
+    _ComplexLike_co,
+    _DTypeLike,
+    _FloatLike_co,
+    _NestedSequence as _SeqND,
+    _NumberLike_co,
+    _ScalarLike_co,
+    _ShapeLike,
+    _SupportsArray,
+)
+
+__all__ = [
+    "select",
+    "piecewise",
+    "trim_zeros",
+    "copy",
+    "iterable",
+    "percentile",
+    "diff",
+    "gradient",
+    "angle",
+    "unwrap",
+    "sort_complex",
+    "flip",
+    "rot90",
+    "extract",
+    "place",
+    "vectorize",
+    "asarray_chkfinite",
+    "average",
+    "bincount",
+    "digitize",
+    "cov",
+    "corrcoef",
+    "median",
+    "sinc",
+    "hamming",
+    "hanning",
+    "bartlett",
+    "blackman",
+    "kaiser",
+    "trapezoid",
+    "i0",
+    "meshgrid",
+    "delete",
+    "insert",
+    "append",
+    "interp",
+    "quantile",
+]
+
+_T = TypeVar("_T")
+_T_co = TypeVar("_T_co", covariant=True)
+# The `{}ss` suffix refers to the PEP 695 (Python 3.12) `ParamSpec` syntax, `**P`.
+_Tss = ParamSpec("_Tss")
+
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ScalarT1 = TypeVar("_ScalarT1", bound=np.generic)
+_ScalarT2 = TypeVar("_ScalarT2", bound=np.generic)
+_FloatingT = TypeVar("_FloatingT", bound=np.floating)
+_InexactT = TypeVar("_InexactT", bound=np.inexact)
+_InexactTimeT = TypeVar("_InexactTimeT", bound=np.inexact | np.timedelta64)
+_InexactDateTimeT = TypeVar("_InexactDateTimeT", bound=np.inexact | np.timedelta64 | np.datetime64)
+_ScalarNumericT = TypeVar("_ScalarNumericT", bound=np.inexact | np.timedelta64 | np.object_)
+_AnyDoubleT = TypeVar("_AnyDoubleT", bound=np.float64 | np.longdouble | np.complex128 | np.clongdouble)
+
+_ArrayT = TypeVar("_ArrayT", bound=np.ndarray)
+_ArrayFloatingT = TypeVar("_ArrayFloatingT", bound=NDArray[np.floating])
+_ArrayFloatObjT = TypeVar("_ArrayFloatObjT", bound=NDArray[np.floating | np.object_])
+_ArrayComplexT = TypeVar("_ArrayComplexT", bound=NDArray[np.complexfloating])
+_ArrayInexactT = TypeVar("_ArrayInexactT", bound=NDArray[np.inexact])
+_ArrayNumericT = TypeVar("_ArrayNumericT", bound=NDArray[np.inexact | np.timedelta64 | np.object_])
+
+_ArrayLike1D: TypeAlias = _SupportsArray[np.dtype[_ScalarT]] | Sequence[_ScalarT]
+
+_ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
+
+_integer_co: TypeAlias = np.integer | np.bool
+_float64_co: TypeAlias = np.float64 | _integer_co
+_floating_co: TypeAlias = np.floating | _integer_co
+
+# non-trivial scalar-types that will become `complex128` in `sort_complex()`,
+# i.e. all numeric scalar types except for `[u]int{8,16} | longdouble`
+_SortsToComplex128: TypeAlias = (
+    np.bool
+    | np.int32
+    | np.uint32
+    | np.int64
+    | np.uint64
+    | np.float16
+    | np.float32
+    | np.float64
+    | np.timedelta64
+    | np.object_
+)
+
+_Array: TypeAlias = np.ndarray[_ShapeT, np.dtype[_ScalarT]]
+_Array0D: TypeAlias = np.ndarray[tuple[()], np.dtype[_ScalarT]]
+_Array1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]]
+_Array2D: TypeAlias = np.ndarray[tuple[int, int], np.dtype[_ScalarT]]
+_Array3D: TypeAlias = np.ndarray[tuple[int, int, int], np.dtype[_ScalarT]]
+_ArrayMax2D: TypeAlias = np.ndarray[tuple[int] | tuple[int, int], np.dtype[_ScalarT]]
+# workaround for mypy and pyright not following the typing spec for overloads
+_ArrayNoD: TypeAlias = np.ndarray[tuple[Never, Never, Never, Never], np.dtype[_ScalarT]]
+
+_Seq1D: TypeAlias = Sequence[_T]
+_Seq2D: TypeAlias = Sequence[Sequence[_T]]
+_Seq3D: TypeAlias = Sequence[Sequence[Sequence[_T]]]
+_ListSeqND: TypeAlias = list[_T] | _SeqND[list[_T]]
+
+_Tuple2: TypeAlias = tuple[_T, _T]
+_Tuple3: TypeAlias = tuple[_T, _T, _T]
+_Tuple4: TypeAlias = tuple[_T, _T, _T, _T]
+
+_Mesh1: TypeAlias = tuple[_Array1D[_ScalarT]]
+_Mesh2: TypeAlias = tuple[_Array2D[_ScalarT], _Array2D[_ScalarT1]]
+_Mesh3: TypeAlias = tuple[_Array3D[_ScalarT], _Array3D[_ScalarT1], _Array3D[_ScalarT2]]
+
+_IndexLike: TypeAlias = slice | _ArrayLikeInt_co
+
+_Indexing: TypeAlias = L["ij", "xy"]
+_InterpolationMethod = L[
+    "inverted_cdf",
+    "averaged_inverted_cdf",
+    "closest_observation",
+    "interpolated_inverted_cdf",
+    "hazen",
+    "weibull",
+    "linear",
+    "median_unbiased",
+    "normal_unbiased",
+    "lower",
+    "higher",
+    "midpoint",
+    "nearest",
+]
+
+# The resulting value will be used as `y[cond] = func(vals, *args, **kw)`, so in can
+# return any (usually 1d) array-like or scalar-like compatible with the input.
+_PiecewiseFunction: TypeAlias = Callable[Concatenate[NDArray[_ScalarT], _Tss], ArrayLike]
+_PiecewiseFunctions: TypeAlias = _SizedIterable[_PiecewiseFunction[_ScalarT, _Tss] | _ScalarLike_co]
+
+@type_check_only
+class _TrimZerosSequence(Protocol[_T_co]):
+    def __len__(self, /) -> int: ...
+    @overload
+    def __getitem__(self, key: int, /) -> object: ...
+    @overload
+    def __getitem__(self, key: slice, /) -> _T_co: ...
+
+@type_check_only
+class _SupportsRMulFloat(Protocol[_T_co]):
+    def __rmul__(self, other: float, /) -> _T_co: ...
+
+@type_check_only
+class _SizedIterable(Protocol[_T_co]):
+    def __iter__(self) -> Iterable[_T_co]: ...
+    def __len__(self) -> int: ...
+
+###
+
+class vectorize:
+    __doc__: str | None
+    __module__: L["numpy"] = "numpy"
+    pyfunc: Callable[..., Incomplete]
+    cache: bool
+    signature: str | None
+    otypes: str | None
+    excluded: set[int | str]
+
+    def __init__(
+        self,
+        /,
+        pyfunc: Callable[..., Incomplete] | _NoValueType = ...,  # = _NoValue
+        otypes: str | Iterable[DTypeLike] | None = None,
+        doc: str | None = None,
+        excluded: Iterable[int | str] | None = None,
+        cache: bool = False,
+        signature: str | None = None,
+    ) -> None: ...
+    def __call__(self, /, *args: Incomplete, **kwargs: Incomplete) -> Incomplete: ...
+
+@overload
+def rot90(m: _ArrayT, k: int = 1, axes: tuple[int, int] = (0, 1)) -> _ArrayT: ...
+@overload
+def rot90(m: _ArrayLike[_ScalarT], k: int = 1, axes: tuple[int, int] = (0, 1)) -> NDArray[_ScalarT]: ...
+@overload
+def rot90(m: ArrayLike, k: int = 1, axes: tuple[int, int] = (0, 1)) -> NDArray[Incomplete]: ...
+
+# NOTE: Technically `flip` also accept scalars, but that has no effect and complicates
+# the overloads significantly, so we ignore that case here.
+@overload
+def flip(m: _ArrayT, axis: int | tuple[int, ...] | None = None) -> _ArrayT: ...
+@overload
+def flip(m: _ArrayLike[_ScalarT], axis: int | tuple[int, ...] | None = None) -> NDArray[_ScalarT]: ...
+@overload
+def flip(m: ArrayLike, axis: int | tuple[int, ...] | None = None) -> NDArray[Incomplete]: ...
+
+#
+def iterable(y: object) -> TypeIs[Iterable[Any]]: ...
+
+# NOTE: This assumes that if `axis` is given the input is at least 2d, and will
+# therefore always return an array.
+# NOTE: This assumes that if `keepdims=True` the input is at least 1d, and will
+# therefore always return an array.
+@overload  # inexact array, keepdims=True
+def average(
+    a: _ArrayInexactT,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[True],
+) -> _ArrayInexactT: ...
+@overload  # inexact array, returned=True keepdims=True
+def average(
+    a: _ArrayInexactT,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[True],
+) -> _Tuple2[_ArrayInexactT]: ...
+@overload  # inexact array-like, axis=None
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> _InexactT: ...
+@overload  # inexact array-like, axis=<given>
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> NDArray[_InexactT]: ...
+@overload  # inexact array-like, keepdims=True
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[_InexactT]: ...
+@overload  # inexact array-like, axis=None, returned=True
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[_InexactT]: ...
+@overload  # inexact array-like, axis=<given>, returned=True
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[NDArray[_InexactT]]: ...
+@overload  # inexact array-like, returned=True, keepdims=True
+def average(
+    a: _ArrayLike[_InexactT],
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[True],
+) -> _Tuple2[NDArray[_InexactT]]: ...
+@overload  # bool or integer array-like, axis=None
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: None = None,
+    weights: _ArrayLikeFloat_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> np.float64: ...
+@overload  # bool or integer array-like, axis=<given>
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeFloat_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> NDArray[np.float64]: ...
+@overload  # bool or integer array-like, keepdims=True
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeFloat_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[np.float64]: ...
+@overload  # bool or integer array-like, axis=None, returned=True
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: None = None,
+    weights: _ArrayLikeFloat_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[np.float64]: ...
+@overload  # bool or integer array-like, axis=<given>, returned=True
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeFloat_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[NDArray[np.float64]]: ...
+@overload  # bool or integer array-like, returned=True, keepdims=True
+def average(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeFloat_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[True],
+) -> _Tuple2[NDArray[np.float64]]: ...
+@overload  # complex array-like, axis=None
+def average(
+    a: _ListSeqND[complex],
+    axis: None = None,
+    weights: _ArrayLikeComplex_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> np.complex128: ...
+@overload  # complex array-like, axis=<given>
+def average(
+    a: _ListSeqND[complex],
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeComplex_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> NDArray[np.complex128]: ...
+@overload  # complex array-like, keepdims=True
+def average(
+    a: _ListSeqND[complex],
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeComplex_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[np.complex128]: ...
+@overload  # complex array-like, axis=None, returned=True
+def average(
+    a: _ListSeqND[complex],
+    axis: None = None,
+    weights: _ArrayLikeComplex_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[np.complex128]: ...
+@overload  # complex array-like, axis=<given>, returned=True
+def average(
+    a: _ListSeqND[complex],
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeComplex_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[NDArray[np.complex128]]: ...
+@overload  # complex array-like, keepdims=True, returned=True
+def average(
+    a: _ListSeqND[complex],
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeComplex_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[True],
+) -> _Tuple2[NDArray[np.complex128]]: ...
+@overload  # unknown, axis=None
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> Any: ...
+@overload  # unknown, axis=<given>
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[False] | _NoValueType = ...,
+) -> np.ndarray: ...
+@overload  # unknown, keepdims=True
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    returned: L[False] = False,
+    *,
+    keepdims: L[True],
+) -> np.ndarray: ...
+@overload  # unknown, axis=None, returned=True
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[Any]: ...
+@overload  # unknown, axis=<given>, returned=True
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: int | tuple[int, ...],
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[False] | _NoValueType = ...,
+) -> _Tuple2[np.ndarray]: ...
+@overload  # unknown, returned=True, keepdims=True
+def average(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    axis: int | tuple[int, ...] | None = None,
+    weights: _ArrayLikeNumber_co | None = None,
+    *,
+    returned: L[True],
+    keepdims: L[True],
+) -> _Tuple2[np.ndarray]: ...
+
+#
+@overload
+def asarray_chkfinite(a: _ArrayT, dtype: None = None, order: _OrderKACF = None) -> _ArrayT: ...
+@overload
+def asarray_chkfinite(
+    a: np.ndarray[_ShapeT], dtype: _DTypeLike[_ScalarT], order: _OrderKACF = None
+) -> _Array[_ShapeT, _ScalarT]: ...
+@overload
+def asarray_chkfinite(a: _ArrayLike[_ScalarT], dtype: None = None, order: _OrderKACF = None) -> NDArray[_ScalarT]: ...
+@overload
+def asarray_chkfinite(a: object, dtype: _DTypeLike[_ScalarT], order: _OrderKACF = None) -> NDArray[_ScalarT]: ...
+@overload
+def asarray_chkfinite(a: object, dtype: DTypeLike | None = None, order: _OrderKACF = None) -> NDArray[Incomplete]: ...
+
+# NOTE: Contrary to the documentation, scalars are also accepted and treated as
+# `[condlist]`. And even though the documentation says these should be boolean, in
+# practice anything that `np.array(condlist, dtype=bool)` accepts will work, i.e. any
+# array-like.
+@overload
+def piecewise(
+    x: _Array[_ShapeT, _ScalarT],
+    condlist: ArrayLike,
+    funclist: _PiecewiseFunctions[Any, _Tss],
+    *args: _Tss.args,
+    **kw: _Tss.kwargs,
+) -> _Array[_ShapeT, _ScalarT]: ...
+@overload
+def piecewise(
+    x: _ArrayLike[_ScalarT],
+    condlist: ArrayLike,
+    funclist: _PiecewiseFunctions[Any, _Tss],
+    *args: _Tss.args,
+    **kw: _Tss.kwargs,
+) -> NDArray[_ScalarT]: ...
+@overload
+def piecewise(
+    x: ArrayLike,
+    condlist: ArrayLike,
+    funclist: _PiecewiseFunctions[_ScalarT, _Tss],
+    *args: _Tss.args,
+    **kw: _Tss.kwargs,
+) -> NDArray[_ScalarT]: ...
+
+# NOTE: condition is usually boolean, but anything with zero/non-zero semantics works
+@overload
+def extract(condition: ArrayLike, arr: _ArrayLike[_ScalarT]) -> _Array1D[_ScalarT]: ...
+@overload
+def extract(condition: ArrayLike, arr: _SeqND[bool]) -> _Array1D[np.bool]: ...
+@overload
+def extract(condition: ArrayLike, arr: _ListSeqND[int]) -> _Array1D[np.int_]: ...
+@overload
+def extract(condition: ArrayLike, arr: _ListSeqND[float]) -> _Array1D[np.float64]: ...
+@overload
+def extract(condition: ArrayLike, arr: _ListSeqND[complex]) -> _Array1D[np.complex128]: ...
+@overload
+def extract(condition: ArrayLike, arr: _SeqND[bytes]) -> _Array1D[np.bytes_]: ...
+@overload
+def extract(condition: ArrayLike, arr: _SeqND[str]) -> _Array1D[np.str_]: ...
+@overload
+def extract(condition: ArrayLike, arr: ArrayLike) -> _Array1D[Incomplete]: ...
+
+# NOTE: unlike `extract`, passing non-boolean conditions for `condlist` will raise an
+# error at runtime
+@overload
+def select(
+    condlist: _SizedIterable[_ArrayLikeBool_co],
+    choicelist: Sequence[_ArrayT],
+    default: ArrayLike = 0,
+) -> _ArrayT: ...
+@overload
+def select(
+    condlist: _SizedIterable[_ArrayLikeBool_co],
+    choicelist: Sequence[_ArrayLike[_ScalarT]] | NDArray[_ScalarT],
+    default: ArrayLike = 0,
+) -> NDArray[_ScalarT]: ...
+@overload
+def select(
+    condlist: _SizedIterable[_ArrayLikeBool_co],
+    choicelist: Sequence[ArrayLike],
+    default: ArrayLike = 0,
+) -> np.ndarray: ...
+
+# keep roughly in sync with `ma.core.copy`
+@overload
+def copy(a: _ArrayT, order: _OrderKACF, subok: L[True]) -> _ArrayT: ...
+@overload
+def copy(a: _ArrayT, order: _OrderKACF = "K", *, subok: L[True]) -> _ArrayT: ...
+@overload
+def copy(a: _ArrayLike[_ScalarT], order: _OrderKACF = "K", subok: L[False] = False) -> NDArray[_ScalarT]: ...
+@overload
+def copy(a: ArrayLike, order: _OrderKACF = "K", subok: L[False] = False) -> NDArray[Incomplete]: ...
+
+#
+@overload  # ?d, known inexact scalar-type
+def gradient(
+    f: _ArrayNoD[_InexactTimeT],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+    # `| Any` instead of ` | tuple` is returned to avoid several mypy_primer errors
+) -> _Array1D[_InexactTimeT] | Any: ...
+@overload  # 1d, known inexact scalar-type
+def gradient(
+    f: _Array1D[_InexactTimeT],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Array1D[_InexactTimeT]: ...
+@overload  # 2d, known inexact scalar-type
+def gradient(
+    f: _Array2D[_InexactTimeT],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh2[_InexactTimeT, _InexactTimeT]: ...
+@overload  # 3d, known inexact scalar-type
+def gradient(
+    f: _Array3D[_InexactTimeT],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh3[_InexactTimeT, _InexactTimeT, _InexactTimeT]: ...
+@overload  # ?d, datetime64 scalar-type
+def gradient(
+    f: _ArrayNoD[np.datetime64],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Array1D[np.timedelta64] | tuple[NDArray[np.timedelta64], ...]: ...
+@overload  # 1d, datetime64 scalar-type
+def gradient(
+    f: _Array1D[np.datetime64],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Array1D[np.timedelta64]: ...
+@overload  # 2d, datetime64 scalar-type
+def gradient(
+    f: _Array2D[np.datetime64],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh2[np.timedelta64, np.timedelta64]: ...
+@overload  # 3d, datetime64 scalar-type
+def gradient(
+    f: _Array3D[np.datetime64],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh3[np.timedelta64, np.timedelta64, np.timedelta64]: ...
+@overload  # 1d float-like
+def gradient(
+    f: _Seq1D[float],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Array1D[np.float64]: ...
+@overload  # 2d float-like
+def gradient(
+    f: _Seq2D[float],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh2[np.float64, np.float64]: ...
+@overload  # 3d float-like
+def gradient(
+    f: _Seq3D[float],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh3[np.float64, np.float64, np.float64]: ...
+@overload  # 1d complex-like  (the `list` avoids overlap with the float-like overload)
+def gradient(
+    f: list[complex],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Array1D[np.complex128]: ...
+@overload  # 2d float-like
+def gradient(
+    f: _Seq1D[list[complex]],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh2[np.complex128, np.complex128]: ...
+@overload  # 3d float-like
+def gradient(
+    f: _Seq2D[list[complex]],
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> _Mesh3[np.complex128, np.complex128, np.complex128]: ...
+@overload  # fallback
+def gradient(
+    f: ArrayLike,
+    *varargs: _ArrayLikeNumber_co,
+    axis: _ShapeLike | None = None,
+    edge_order: L[1, 2] = 1,
+) -> Incomplete: ...
+
+#
+@overload  # n == 0; return input unchanged
+def diff(
+    a: _T,
+    n: L[0],
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,  # = _NoValue
+    append: ArrayLike | _NoValueType = ...,  # = _NoValue
+) -> _T: ...
+@overload  # known array-type
+def diff(
+    a: _ArrayNumericT,
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _ArrayNumericT: ...
+@overload  # known shape, datetime64
+def diff(
+    a: _Array[_ShapeT, np.datetime64],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array[_ShapeT, np.timedelta64]: ...
+@overload  # unknown shape, known scalar-type
+def diff(
+    a: _ArrayLike[_ScalarNumericT],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> NDArray[_ScalarNumericT]: ...
+@overload  # unknown shape, datetime64
+def diff(
+    a: _ArrayLike[np.datetime64],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> NDArray[np.timedelta64]: ...
+@overload  # 1d int
+def diff(
+    a: _Seq1D[int],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array1D[np.int_]: ...
+@overload  # 2d int
+def diff(
+    a: _Seq2D[int],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array2D[np.int_]: ...
+@overload  # 1d float  (the `list` avoids overlap with the `int` overloads)
+def diff(
+    a: list[float],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array1D[np.float64]: ...
+@overload  # 2d float
+def diff(
+    a: _Seq1D[list[float]],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array2D[np.float64]: ...
+@overload  # 1d complex  (the `list` avoids overlap with the `int` overloads)
+def diff(
+    a: list[complex],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array1D[np.complex128]: ...
+@overload  # 2d complex
+def diff(
+    a: _Seq1D[list[complex]],
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> _Array2D[np.complex128]: ...
+@overload  # unknown shape, unknown scalar-type
+def diff(
+    a: ArrayLike,
+    n: int = 1,
+    axis: SupportsIndex = -1,
+    prepend: ArrayLike | _NoValueType = ...,
+    append: ArrayLike | _NoValueType = ...,
+) -> NDArray[Incomplete]: ...
+
+#
+@overload  # float scalar
+def interp(
+    x: _FloatLike_co,
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeFloat_co,
+    left: _FloatLike_co | None = None,
+    right: _FloatLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> np.float64: ...
+@overload  # complex scalar
+def interp(
+    x: _FloatLike_co,
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLike1D[np.complexfloating] | list[complex],
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> np.complex128: ...
+@overload  # float array
+def interp(
+    x: _Array[_ShapeT, _floating_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeFloat_co,
+    left: _FloatLike_co | None = None,
+    right: _FloatLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> _Array[_ShapeT, np.float64]: ...
+@overload  # complex array
+def interp(
+    x: _Array[_ShapeT, _floating_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLike1D[np.complexfloating] | list[complex],
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> _Array[_ShapeT, np.complex128]: ...
+@overload  # float sequence
+def interp(
+    x: _Seq1D[_FloatLike_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeFloat_co,
+    left: _FloatLike_co | None = None,
+    right: _FloatLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> _Array1D[np.float64]: ...
+@overload  # complex sequence
+def interp(
+    x: _Seq1D[_FloatLike_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLike1D[np.complexfloating] | list[complex],
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> _Array1D[np.complex128]: ...
+@overload  # float array-like
+def interp(
+    x: _SeqND[_FloatLike_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeFloat_co,
+    left: _FloatLike_co | None = None,
+    right: _FloatLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # complex array-like
+def interp(
+    x: _SeqND[_FloatLike_co],
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLike1D[np.complexfloating] | list[complex],
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # float scalar/array-like
+def interp(
+    x: _ArrayLikeFloat_co,
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeFloat_co,
+    left: _FloatLike_co | None = None,
+    right: _FloatLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> NDArray[np.float64] | np.float64: ...
+@overload  # complex scalar/array-like
+def interp(
+    x: _ArrayLikeFloat_co,
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLike1D[np.complexfloating],
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> NDArray[np.complex128] | np.complex128: ...
+@overload  # float/complex scalar/array-like
+def interp(
+    x: _ArrayLikeFloat_co,
+    xp: _ArrayLikeFloat_co,
+    fp: _ArrayLikeNumber_co,
+    left: _NumberLike_co | None = None,
+    right: _NumberLike_co | None = None,
+    period: _FloatLike_co | None = None,
+) -> NDArray[np.complex128 | np.float64] | np.complex128 | np.float64: ...
+
+#
+@overload  # 0d T: floating -> 0d T
+def angle(z: _FloatingT, deg: bool = False) -> _FloatingT: ...
+@overload  # 0d complex | float | ~integer -> 0d float64
+def angle(z: complex | _integer_co, deg: bool = False) -> np.float64: ...
+@overload  # 0d complex64 -> 0d float32
+def angle(z: np.complex64, deg: bool = False) -> np.float32: ...
+@overload  # 0d clongdouble -> 0d longdouble
+def angle(z: np.clongdouble, deg: bool = False) -> np.longdouble: ...
+@overload  # T: nd floating -> T
+def angle(z: _ArrayFloatingT, deg: bool = False) -> _ArrayFloatingT: ...
+@overload  # nd T: complex128 | ~integer -> nd float64
+def angle(z: _Array[_ShapeT, np.complex128 | _integer_co], deg: bool = False) -> _Array[_ShapeT, np.float64]: ...
+@overload  # nd T: complex64 -> nd float32
+def angle(z: _Array[_ShapeT, np.complex64], deg: bool = False) -> _Array[_ShapeT, np.float32]: ...
+@overload  # nd T: clongdouble -> nd longdouble
+def angle(z: _Array[_ShapeT, np.clongdouble], deg: bool = False) -> _Array[_ShapeT, np.longdouble]: ...
+@overload  # 1d complex -> 1d float64
+def angle(z: _Seq1D[complex], deg: bool = False) -> _Array1D[np.float64]: ...
+@overload  # 2d complex -> 2d float64
+def angle(z: _Seq2D[complex], deg: bool = False) -> _Array2D[np.float64]: ...
+@overload  # 3d complex -> 3d float64
+def angle(z: _Seq3D[complex], deg: bool = False) -> _Array3D[np.float64]: ...
+@overload  # fallback
+def angle(z: _ArrayLikeComplex_co, deg: bool = False) -> NDArray[np.floating] | Any: ...
+
+#
+@overload  # known array-type
+def unwrap(
+    p: _ArrayFloatObjT,
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> _ArrayFloatObjT: ...
+@overload  # known shape, float64
+def unwrap(
+    p: _Array[_ShapeT, _float64_co],
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> _Array[_ShapeT, np.float64]: ...
+@overload  # 1d float64-like
+def unwrap(
+    p: _Seq1D[float | _float64_co],
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> _Array1D[np.float64]: ...
+@overload  # 2d float64-like
+def unwrap(
+    p: _Seq2D[float | _float64_co],
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> _Array2D[np.float64]: ...
+@overload  # 3d float64-like
+def unwrap(
+    p: _Seq3D[float | _float64_co],
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> _Array3D[np.float64]: ...
+@overload  # ?d, float64
+def unwrap(
+    p: _SeqND[float] | _ArrayLike[_float64_co],
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> NDArray[np.float64]: ...
+@overload  # fallback
+def unwrap(
+    p: _ArrayLikeFloat_co | _ArrayLikeObject_co,
+    discont: float | None = None,
+    axis: int = -1,
+    *,
+    period: float = ...,  # = τ
+) -> np.ndarray: ...
+
+#
+@overload
+def sort_complex(a: _ArrayComplexT) -> _ArrayComplexT: ...
+@overload  # complex64, shape known
+def sort_complex(a: _Array[_ShapeT, np.int8 | np.uint8 | np.int16 | np.uint16]) -> _Array[_ShapeT, np.complex64]: ...
+@overload  # complex64, shape unknown
+def sort_complex(a: _ArrayLike[np.int8 | np.uint8 | np.int16 | np.uint16]) -> NDArray[np.complex64]: ...
+@overload  # complex128, shape known
+def sort_complex(a: _Array[_ShapeT, _SortsToComplex128]) -> _Array[_ShapeT, np.complex128]: ...
+@overload  # complex128, shape unknown
+def sort_complex(a: _ArrayLike[_SortsToComplex128]) -> NDArray[np.complex128]: ...
+@overload  # clongdouble, shape known
+def sort_complex(a: _Array[_ShapeT, np.longdouble]) -> _Array[_ShapeT, np.clongdouble]: ...
+@overload  # clongdouble, shape unknown
+def sort_complex(a: _ArrayLike[np.longdouble]) -> NDArray[np.clongdouble]: ...
+
+#
+def trim_zeros(filt: _TrimZerosSequence[_T], trim: L["f", "b", "fb", "bf"] = "fb", axis: _ShapeLike | None = None) -> _T: ...
+
+# NOTE: keep in sync with `corrcoef`
+@overload  # ?d, known inexact scalar-type >=64 precision, y=<given>.
+def cov(
+    m: _ArrayLike[_AnyDoubleT],
+    y: _ArrayLike[_AnyDoubleT],
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: None = None,
+) -> _Array2D[_AnyDoubleT]: ...
+@overload  # ?d, known inexact scalar-type >=64 precision, y=None -> 0d or 2d
+def cov(
+    m: _ArrayNoD[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> NDArray[_AnyDoubleT]: ...
+@overload  # 1d, known inexact scalar-type >=64 precision, y=None
+def cov(
+    m: _Array1D[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> _Array0D[_AnyDoubleT]: ...
+@overload  # nd, known inexact scalar-type >=64 precision, y=None -> 0d or 2d
+def cov(
+    m: _ArrayLike[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> NDArray[_AnyDoubleT]: ...
+@overload  # nd, casts to float64, y=<given>
+def cov(
+    m: NDArray[np.float32 | np.float16 | _integer_co] | _Seq1D[float] | _Seq2D[float],
+    y: NDArray[np.float32 | np.float16 | _integer_co] | _Seq1D[float] | _Seq2D[float],
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> _Array2D[np.float64]: ...
+@overload  # ?d or 2d, casts to float64, y=None -> 0d or 2d
+def cov(
+    m: _ArrayNoD[np.float32 | np.float16 | _integer_co] | _Seq2D[float],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # 1d, casts to float64, y=None
+def cov(
+    m:  _Array1D[np.float32 | np.float16 | _integer_co] | _Seq1D[float],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> _Array0D[np.float64]: ...
+@overload  # nd, casts to float64, y=None -> 0d or 2d
+def cov(
+    m:  _ArrayLike[np.float32 | np.float16 | _integer_co],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # 1d complex, y=<given>  (`list` avoids overlap with float overloads)
+def cov(
+    m: list[complex] | _Seq1D[list[complex]],
+    y: list[complex] | _Seq1D[list[complex]],
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> _Array2D[np.complex128]: ...
+@overload  # 1d complex, y=None
+def cov(
+    m: list[complex],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> _Array0D[np.complex128]: ...
+@overload  # 2d complex, y=None -> 0d or 2d
+def cov(
+    m: _Seq1D[list[complex]],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # 1d complex-like, y=None, dtype=<known>
+def cov(
+    m: _Seq1D[_ComplexLike_co],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> _Array0D[_ScalarT]: ...
+@overload  # nd complex-like, y=<given>, dtype=<known>
+def cov(
+    m: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> _Array2D[_ScalarT]: ...
+@overload  # nd complex-like, y=None, dtype=<known> -> 0d or 2d
+def cov(
+    m: _ArrayLikeComplex_co,
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> NDArray[_ScalarT]: ...
+@overload  # nd complex-like, y=<given>, dtype=?
+def cov(
+    m: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: DTypeLike | None = None,
+) -> _Array2D[Incomplete]: ...
+@overload  # 1d complex-like, y=None, dtype=?
+def cov(
+    m: _Seq1D[_ComplexLike_co],
+    y: None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: DTypeLike | None = None,
+) -> _Array0D[Incomplete]: ...
+@overload  # nd complex-like, dtype=?
+def cov(
+    m: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co | None = None,
+    rowvar: bool = True,
+    bias: bool = False,
+    ddof: SupportsIndex | SupportsInt | None = None,
+    fweights: _ArrayLikeInt_co | None = None,
+    aweights: _ArrayLikeFloat_co | None = None,
+    *,
+    dtype: DTypeLike | None = None,
+) -> NDArray[Incomplete]: ...
+
+# NOTE: If only `x` is given and the resulting array has shape (1,1), a bare scalar
+# is returned instead of a 2D array. When y is given, a 2D array is always returned.
+# This differs from `cov`, which returns 0-D arrays instead of scalars in such cases.
+# NOTE: keep in sync with `cov`
+@overload  # ?d, known inexact scalar-type >=64 precision, y=<given>.
+def corrcoef(
+    x: _ArrayLike[_AnyDoubleT],
+    y: _ArrayLike[_AnyDoubleT],
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> _Array2D[_AnyDoubleT]: ...
+@overload  # ?d, known inexact scalar-type >=64 precision, y=None
+def corrcoef(
+    x: _ArrayNoD[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> _Array2D[_AnyDoubleT] | _AnyDoubleT: ...
+@overload  # 1d, known inexact scalar-type >=64 precision, y=None
+def corrcoef(
+    x: _Array1D[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> _AnyDoubleT: ...
+@overload  # nd, known inexact scalar-type >=64 precision, y=None
+def corrcoef(
+    x: _ArrayLike[_AnyDoubleT],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_AnyDoubleT] | None = None,
+) -> _Array2D[_AnyDoubleT] | _AnyDoubleT: ...
+@overload  # nd, casts to float64, y=<given>
+def corrcoef(
+    x: NDArray[np.float32 | np.float16 | _integer_co] | _Seq1D[float] | _Seq2D[float],
+    y: NDArray[np.float32 | np.float16 | _integer_co] | _Seq1D[float] | _Seq2D[float],
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> _Array2D[np.float64]: ...
+@overload  # ?d or 2d, casts to float64, y=None
+def corrcoef(
+    x: _ArrayNoD[np.float32 | np.float16 | _integer_co] | _Seq2D[float],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> _Array2D[np.float64] | np.float64: ...
+@overload  # 1d, casts to float64, y=None
+def corrcoef(
+    x: _Array1D[np.float32 | np.float16 | _integer_co] | _Seq1D[float],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> np.float64: ...
+@overload  # nd, casts to float64, y=None
+def corrcoef(
+    x: _ArrayLike[np.float32 | np.float16 | _integer_co],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.float64] | None = None,
+) -> _Array2D[np.float64] | np.float64: ...
+@overload  # 1d complex, y=<given>  (`list` avoids overlap with float overloads)
+def corrcoef(
+    x: list[complex] | _Seq1D[list[complex]],
+    y: list[complex] | _Seq1D[list[complex]],
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> _Array2D[np.complex128]: ...
+@overload  # 1d complex, y=None
+def corrcoef(
+    x: list[complex],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> np.complex128: ...
+@overload  # 2d complex, y=None
+def corrcoef(
+    x: _Seq1D[list[complex]],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[np.complex128] | None = None,
+) -> _Array2D[np.complex128] | np.complex128: ...
+@overload  # 1d complex-like, y=None, dtype=<known>
+def corrcoef(
+    x: _Seq1D[_ComplexLike_co],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> _ScalarT: ...
+@overload  # nd complex-like, y=<given>, dtype=<known>
+def corrcoef(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> _Array2D[_ScalarT]: ...
+@overload  # nd complex-like, y=None, dtype=<known>
+def corrcoef(
+    x: _ArrayLikeComplex_co,
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+) -> _Array2D[_ScalarT] | _ScalarT: ...
+@overload  # nd complex-like, y=<given>, dtype=?
+def corrcoef(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    rowvar: bool = True,
+    *,
+    dtype: DTypeLike | None = None,
+) -> _Array2D[Incomplete]: ...
+@overload  # 1d complex-like, y=None, dtype=?
+def corrcoef(
+    x: _Seq1D[_ComplexLike_co],
+    y: None = None,
+    rowvar: bool = True,
+    *,
+    dtype: DTypeLike | None = None,
+) -> Incomplete: ...
+@overload  # nd complex-like, dtype=?
+def corrcoef(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co | None = None,
+    rowvar: bool = True,
+    *,
+    dtype: DTypeLike | None = None,
+) -> _Array2D[Incomplete] | Incomplete: ...
+
+# note that floating `M` are accepted, but their fractional part is ignored
+def blackman(M: _FloatLike_co) -> _Array1D[np.float64]: ...
+def bartlett(M: _FloatLike_co) -> _Array1D[np.float64]: ...
+def hanning(M: _FloatLike_co) -> _Array1D[np.float64]: ...
+def hamming(M: _FloatLike_co) -> _Array1D[np.float64]: ...
+def kaiser(M: _FloatLike_co, beta: _FloatLike_co) -> _Array1D[np.float64]: ...
+
+#
+@overload
+def i0(x: _Array[_ShapeT, np.floating | np.integer]) -> _Array[_ShapeT, np.float64]: ...
+@overload
+def i0(x: _FloatLike_co) -> _Array0D[np.float64]: ...
+@overload
+def i0(x: _Seq1D[_FloatLike_co]) -> _Array1D[np.float64]: ...
+@overload
+def i0(x: _Seq2D[_FloatLike_co]) -> _Array2D[np.float64]: ...
+@overload
+def i0(x: _Seq3D[_FloatLike_co]) -> _Array3D[np.float64]: ...
+@overload
+def i0(x: _ArrayLikeFloat_co) -> NDArray[np.float64]: ...
+
+#
+@overload
+def sinc(x: _InexactT) -> _InexactT: ...
+@overload
+def sinc(x: float | _float64_co) -> np.float64: ...
+@overload
+def sinc(x: complex) -> np.complex128 | Any: ...
+@overload
+def sinc(x: _ArrayInexactT) -> _ArrayInexactT: ...
+@overload
+def sinc(x: _Array[_ShapeT, _integer_co]) -> _Array[_ShapeT, np.float64]: ...
+@overload
+def sinc(x: _Seq1D[float]) -> _Array1D[np.float64]: ...
+@overload
+def sinc(x: _Seq2D[float]) -> _Array2D[np.float64]: ...
+@overload
+def sinc(x: _Seq3D[float]) -> _Array3D[np.float64]: ...
+@overload
+def sinc(x: _SeqND[float]) -> NDArray[np.float64]: ...
+@overload
+def sinc(x: list[complex]) -> _Array1D[np.complex128]: ...
+@overload
+def sinc(x: _Seq1D[list[complex]]) -> _Array2D[np.complex128]: ...
+@overload
+def sinc(x: _Seq2D[list[complex]]) -> _Array3D[np.complex128]: ...
+@overload
+def sinc(x: _ArrayLikeComplex_co) -> np.ndarray | Any: ...
+
+# NOTE: We assume that `axis` is only provided for >=1-D arrays because for <1-D arrays
+# it has no effect, and would complicate the overloads significantly.
+@overload  # known scalar-type, keepdims=False (default)
+def median(
+    a: _ArrayLike[_InexactTimeT],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: L[False] = False,
+) -> _InexactTimeT: ...
+@overload  # float array-like, keepdims=False (default)
+def median(
+    a: _ArrayLikeInt_co | _SeqND[float] | float,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: L[False] = False,
+) -> np.float64: ...
+@overload  # complex array-like, keepdims=False (default)
+def median(
+    a: _ListSeqND[complex],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: L[False] = False,
+) -> np.complex128: ...
+@overload  # complex scalar, keepdims=False (default)
+def median(
+    a: complex,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: L[False] = False,
+) -> np.complex128 | Any: ...
+@overload  # known array-type, keepdims=True
+def median(
+    a: _ArrayNumericT,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    *,
+    keepdims: L[True],
+) -> _ArrayNumericT: ...
+@overload  # known scalar-type, keepdims=True
+def median(
+    a: _ArrayLike[_ScalarNumericT],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[_ScalarNumericT]: ...
+@overload  # known scalar-type, axis=<given>
+def median(
+    a: _ArrayLike[_ScalarNumericT],
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> NDArray[_ScalarNumericT]: ...
+@overload  # float array-like, keepdims=True
+def median(
+    a: _SeqND[float],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[np.float64]: ...
+@overload  # float array-like, axis=<given>
+def median(
+    a: _SeqND[float],
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> NDArray[np.float64]: ...
+@overload  # complex array-like, keepdims=True
+def median(
+    a: _ListSeqND[complex],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    *,
+    keepdims: L[True],
+) -> NDArray[np.complex128]: ...
+@overload  # complex array-like, axis=<given>
+def median(
+    a: _ListSeqND[complex],
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> NDArray[np.complex128]: ...
+@overload  # out=<given> (keyword)
+def median(
+    a: _ArrayLikeComplex_co | _ArrayLike[np.timedelta64 | np.object_],
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> _ArrayT: ...
+@overload  # out=<given> (positional)
+def median(
+    a: _ArrayLikeComplex_co | _ArrayLike[np.timedelta64 | np.object_],
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> _ArrayT: ...
+@overload  # fallback
+def median(
+    a: _ArrayLikeComplex_co | _ArrayLike[np.timedelta64 | np.object_],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    keepdims: bool = False,
+) -> Incomplete: ...
+
+# NOTE: keep in sync with `quantile`
+@overload  # inexact, scalar, axis=None
+def percentile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _InexactDateTimeT: ...
+@overload  # inexact, scalar, axis=<given>
+def percentile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # inexact, scalar, keepdims=True
+def percentile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # inexact, array, axis=None
+def percentile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, _InexactDateTimeT]: ...
+@overload  # inexact, array-like
+def percentile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # float, scalar, axis=None
+def percentile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> np.float64: ...
+@overload  # float, scalar, axis=<given>
+def percentile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # float, scalar, keepdims=True
+def percentile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # float, array, axis=None
+def percentile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.float64]: ...
+@overload  # float, array-like
+def percentile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # complex, scalar, axis=None
+def percentile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> np.complex128: ...
+@overload  # complex, scalar, axis=<given>
+def percentile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # complex, scalar, keepdims=True
+def percentile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # complex, array, axis=None
+def percentile(
+    a: _ListSeqND[complex],
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.complex128]: ...
+@overload  # complex, array-like
+def percentile(
+    a: _ListSeqND[complex],
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # object_, scalar, axis=None
+def percentile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> Any: ...
+@overload  # object_, scalar, axis=<given>
+def percentile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # object_, scalar, keepdims=True
+def percentile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # object_, array, axis=None
+def percentile(
+    a: _ArrayLikeObject_co,
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.object_]: ...
+@overload  # object_, array-like
+def percentile(
+    a: _ArrayLikeObject_co,
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # out=<given> (keyword)
+def percentile(
+    a: ArrayLike,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _ArrayT: ...
+@overload  # out=<given> (positional)
+def percentile(
+    a: ArrayLike,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _ArrayT: ...
+@overload  # fallback
+def percentile(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> Incomplete: ...
+
+# NOTE: keep in sync with `percentile`
+@overload  # inexact, scalar, axis=None
+def quantile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _InexactDateTimeT: ...
+@overload  # inexact, scalar, axis=<given>
+def quantile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # inexact, scalar, keepdims=True
+def quantile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # inexact, array, axis=None
+def quantile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, _InexactDateTimeT]: ...
+@overload  # inexact, array-like
+def quantile(
+    a: _ArrayLike[_InexactDateTimeT],
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[_InexactDateTimeT]: ...
+@overload  # float, scalar, axis=None
+def quantile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> np.float64: ...
+@overload  # float, scalar, axis=<given>
+def quantile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # float, scalar, keepdims=True
+def quantile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # float, array, axis=None
+def quantile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.float64]: ...
+@overload  # float, array-like
+def quantile(
+    a: _SeqND[float] | _ArrayLikeInt_co,
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.float64]: ...
+@overload  # complex, scalar, axis=None
+def quantile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> np.complex128: ...
+@overload  # complex, scalar, axis=<given>
+def quantile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # complex, scalar, keepdims=True
+def quantile(
+    a: _ListSeqND[complex],
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # complex, array, axis=None
+def quantile(
+    a: _ListSeqND[complex],
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.complex128]: ...
+@overload  # complex, array-like
+def quantile(
+    a: _ListSeqND[complex],
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.complex128]: ...
+@overload  # object_, scalar, axis=None
+def quantile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> Any: ...
+@overload  # object_, scalar, axis=<given>
+def quantile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # object_, scalar, keepdims=True
+def quantile(
+    a: _ArrayLikeObject_co,
+    q: _FloatLike_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    *,
+    keepdims: L[True],
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # object_, array, axis=None
+def quantile(
+    a: _ArrayLikeObject_co,
+    q: _Array[_ShapeT, _floating_co],
+    axis: None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: L[False] = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _Array[_ShapeT, np.object_]: ...
+@overload  # object_, array-like
+def quantile(
+    a: _ArrayLikeObject_co,
+    q: NDArray[_floating_co] | _SeqND[_FloatLike_co],
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> NDArray[np.object_]: ...
+@overload  # out=<given> (keyword)
+def quantile(
+    a: ArrayLike,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _ArrayT: ...
+@overload  # out=<given> (positional)
+def quantile(
+    a: ArrayLike,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> _ArrayT: ...
+@overload  # fallback
+def quantile(
+    a: _ArrayLikeNumber_co | _ArrayLikeObject_co,
+    q: _ArrayLikeFloat_co,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    overwrite_input: bool = False,
+    method: _InterpolationMethod = "linear",
+    keepdims: bool = False,
+    *,
+    weights: _ArrayLikeFloat_co | None = None,
+) -> Incomplete: ...
+
+#
+@overload  # ?d, known inexact/timedelta64 scalar-type
+def trapezoid(
+    y: _ArrayNoD[_InexactTimeT],
+    x: _ArrayLike[_InexactTimeT] | _ArrayLikeFloat_co | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[_InexactTimeT] | _InexactTimeT: ...
+@overload  # ?d, casts to float64
+def trapezoid(
+    y: _ArrayNoD[_integer_co],
+    x: _ArrayLikeFloat_co | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[np.float64] | np.float64: ...
+@overload  # strict 1d, known inexact/timedelta64 scalar-type
+def trapezoid(
+    y: _Array1D[_InexactTimeT],
+    x: _Array1D[_InexactTimeT] | _Seq1D[float] | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> _InexactTimeT: ...
+@overload  # strict 1d, casts to float64
+def trapezoid(
+    y: _Array1D[_float64_co] | _Seq1D[float],
+    x: _Array1D[_float64_co] | _Seq1D[float] | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.float64: ...
+@overload  # strict 1d, casts to complex128 (`list` prevents overlapping overloads)
+def trapezoid(
+    y: list[complex],
+    x: _Seq1D[complex] | None = None,
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.complex128: ...
+@overload  # strict 1d, casts to complex128
+def trapezoid(
+    y: _Seq1D[complex],
+    x: list[complex],
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.complex128: ...
+@overload  # strict 2d, known inexact/timedelta64 scalar-type
+def trapezoid(
+    y: _Array2D[_InexactTimeT],
+    x: _ArrayMax2D[_InexactTimeT] | _Seq2D[float] | _Seq1D[float] | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> _InexactTimeT: ...
+@overload  # strict 2d, casts to float64
+def trapezoid(
+    y: _Array2D[_float64_co] | _Seq2D[float],
+    x: _ArrayMax2D[_float64_co] | _Seq2D[float] | _Seq1D[float] | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.float64: ...
+@overload  # strict 2d, casts to complex128 (`list` prevents overlapping overloads)
+def trapezoid(
+    y: _Seq1D[list[complex]],
+    x: _Seq2D[complex] | _Seq1D[complex] | None = None,
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.complex128: ...
+@overload  # strict 2d, casts to complex128
+def trapezoid(
+    y: _Seq2D[complex] | _Seq1D[complex],
+    x: _Seq1D[list[complex]],
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> np.complex128: ...
+@overload
+def trapezoid(
+    y: _ArrayLike[_InexactTimeT],
+    x: _ArrayLike[_InexactTimeT] | _ArrayLikeInt_co | None = None,
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[_InexactTimeT] | _InexactTimeT: ...
+@overload
+def trapezoid(
+    y: _ArrayLike[_float64_co],
+    x: _ArrayLikeFloat_co | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[np.float64] | np.float64: ...
+@overload
+def trapezoid(
+    y: _ArrayLike[np.complex128],
+    x: _ArrayLikeComplex_co | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[np.complex128] | np.complex128: ...
+@overload
+def trapezoid(
+    y: _ArrayLikeComplex_co,
+    x: _ArrayLike[np.complex128],
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[np.complex128] | np.complex128: ...
+@overload
+def trapezoid(
+    y: _ArrayLikeObject_co,
+    x: _ArrayLikeObject_co | _ArrayLikeFloat_co | None = None,
+    dx: float = 1.0,
+    axis: SupportsIndex = -1,
+) -> NDArray[np.object_] | Any: ...
+@overload
+def trapezoid(
+    y: _Seq1D[_SupportsRMulFloat[_T]],
+    x: _Seq1D[_SupportsRMulFloat[_T] | _T] | None = None,
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> _T: ...
+@overload
+def trapezoid(
+    y: _ArrayLikeComplex_co | _ArrayLike[np.timedelta64 | np.object_],
+    x: _ArrayLikeComplex_co | _ArrayLike[np.timedelta64 | np.object_] | None = None,
+    dx: complex = 1.0,
+    axis: SupportsIndex = -1,
+) -> Incomplete: ...
+
+#
+@overload  # 0d
+def meshgrid(*, copy: bool = True, sparse: bool = False, indexing: _Indexing = "xy") -> tuple[()]: ...
+@overload  # 1d, known scalar-type
+def meshgrid(
+    x1: _ArrayLike[_ScalarT],
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh1[_ScalarT]: ...
+@overload  # 1d, unknown scalar-type
+def meshgrid(
+    x1: ArrayLike,
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh1[Any]: ...
+@overload  # 2d, known scalar-types
+def meshgrid(
+    x1: _ArrayLike[_ScalarT],
+    x2: _ArrayLike[_ScalarT1],
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh2[_ScalarT, _ScalarT1]: ...
+@overload  # 2d, known/unknown scalar-types
+def meshgrid(
+    x1: _ArrayLike[_ScalarT],
+    x2: ArrayLike,
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh2[_ScalarT, Any]: ...
+@overload  # 2d, unknown/known scalar-types
+def meshgrid(
+    x1: ArrayLike,
+    x2: _ArrayLike[_ScalarT],
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh2[Any, _ScalarT]: ...
+@overload  # 2d, unknown scalar-types
+def meshgrid(
+    x1: ArrayLike,
+    x2: ArrayLike,
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh2[Any, Any]: ...
+@overload  # 3d, known scalar-types
+def meshgrid(
+    x1: _ArrayLike[_ScalarT],
+    x2: _ArrayLike[_ScalarT1],
+    x3: _ArrayLike[_ScalarT2],
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh3[_ScalarT, _ScalarT1, _ScalarT2]: ...
+@overload  # 3d, unknown scalar-types
+def meshgrid(
+    x1: ArrayLike,
+    x2: ArrayLike,
+    x3: ArrayLike,
+    /,
+    *,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> _Mesh3[Any, Any, Any]: ...
+@overload  # ?d, known scalar-types
+def meshgrid(
+    *xi: _ArrayLike[_ScalarT],
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> tuple[NDArray[_ScalarT], ...]: ...
+@overload  # ?d, unknown scalar-types
+def meshgrid(
+    *xi: ArrayLike,
+    copy: bool = True,
+    sparse: bool = False,
+    indexing: _Indexing = "xy",
+) -> tuple[NDArray[Any], ...]: ...
+
+#
+def place(arr: np.ndarray, mask: ConvertibleToInt | Sequence[ConvertibleToInt], vals: ArrayLike) -> None: ...
+
+# keep in sync with `insert`
+@overload  # known scalar-type, axis=None (default)
+def delete(arr: _ArrayLike[_ScalarT], obj: _IndexLike, axis: None = None) -> _Array1D[_ScalarT]: ...
+@overload  # known array-type, axis specified
+def delete(arr: _ArrayT, obj: _IndexLike, axis: SupportsIndex) -> _ArrayT: ...
+@overload  # known scalar-type, axis specified
+def delete(arr: _ArrayLike[_ScalarT], obj: _IndexLike, axis: SupportsIndex) -> NDArray[_ScalarT]: ...
+@overload  # known scalar-type, axis=None (default)
+def delete(arr: ArrayLike, obj: _IndexLike, axis: None = None) -> _Array1D[Any]: ...
+@overload  # unknown scalar-type, axis specified
+def delete(arr: ArrayLike, obj: _IndexLike, axis: SupportsIndex) -> NDArray[Any]: ...
+
+# keep in sync with `delete`
+@overload  # known scalar-type, axis=None (default)
+def insert(arr: _ArrayLike[_ScalarT], obj: _IndexLike, values: ArrayLike, axis: None = None) -> _Array1D[_ScalarT]: ...
+@overload  # known array-type, axis specified
+def insert(arr: _ArrayT, obj: _IndexLike, values: ArrayLike, axis: SupportsIndex) -> _ArrayT: ...
+@overload  # known scalar-type, axis specified
+def insert(arr: _ArrayLike[_ScalarT], obj: _IndexLike, values: ArrayLike, axis: SupportsIndex) -> NDArray[_ScalarT]: ...
+@overload  # known scalar-type, axis=None (default)
+def insert(arr: ArrayLike, obj: _IndexLike, values: ArrayLike, axis: None = None) -> _Array1D[Any]: ...
+@overload  # unknown scalar-type, axis specified
+def insert(arr: ArrayLike, obj: _IndexLike, values: ArrayLike, axis: SupportsIndex) -> NDArray[Any]: ...
+
+#
+@overload  # known array type, axis specified
+def append(arr: _ArrayT, values: _ArrayT, axis: SupportsIndex) -> _ArrayT: ...
+@overload  # 1d, known scalar type, axis specified
+def append(arr: _Seq1D[_ScalarT], values: _Seq1D[_ScalarT], axis: SupportsIndex) -> _Array1D[_ScalarT]: ...
+@overload  # 2d, known scalar type, axis specified
+def append(arr: _Seq2D[_ScalarT], values: _Seq2D[_ScalarT], axis: SupportsIndex) -> _Array2D[_ScalarT]: ...
+@overload  # 3d, known scalar type, axis specified
+def append(arr: _Seq3D[_ScalarT], values: _Seq3D[_ScalarT], axis: SupportsIndex) -> _Array3D[_ScalarT]: ...
+@overload  # ?d, known scalar type, axis specified
+def append(arr: _SeqND[_ScalarT], values: _SeqND[_ScalarT], axis: SupportsIndex) -> NDArray[_ScalarT]: ...
+@overload  # ?d, unknown scalar type, axis specified
+def append(arr: np.ndarray | _SeqND[_ScalarLike_co], values: _SeqND[_ScalarLike_co], axis: SupportsIndex) -> np.ndarray: ...
+@overload  # known scalar type, axis=None
+def append(arr: _ArrayLike[_ScalarT], values: _ArrayLike[_ScalarT], axis: None = None) -> _Array1D[_ScalarT]: ...
+@overload  # unknown scalar type, axis=None
+def append(arr: ArrayLike, values: ArrayLike, axis: None = None) -> _Array1D[Any]: ...
+
+#
+@overload
+def digitize(
+    x: _Array[_ShapeT, np.floating | np.integer], bins: _ArrayLikeFloat_co, right: bool = False
+) -> _Array[_ShapeT, np.int_]: ...
+@overload
+def digitize(x: _FloatLike_co, bins: _ArrayLikeFloat_co, right: bool = False) -> np.int_: ...
+@overload
+def digitize(x: _Seq1D[_FloatLike_co], bins: _ArrayLikeFloat_co, right: bool = False) -> _Array1D[np.int_]: ...
+@overload
+def digitize(x: _Seq2D[_FloatLike_co], bins: _ArrayLikeFloat_co, right: bool = False) -> _Array2D[np.int_]: ...
+@overload
+def digitize(x: _Seq3D[_FloatLike_co], bins: _ArrayLikeFloat_co, right: bool = False) -> _Array3D[np.int_]: ...
+@overload
+def digitize(x: _ArrayLikeFloat_co, bins: _ArrayLikeFloat_co, right: bool = False) -> NDArray[np.int_] | Any: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..6aa0aa9e64cc3877dd360187c5a555d6a9a77a36
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.py
@@ -0,0 +1,1085 @@
+"""
+Histogram-related functions
+"""
+import contextlib
+import functools
+import operator
+import warnings
+
+import numpy as np
+from numpy._core import overrides
+
+__all__ = ['histogram', 'histogramdd', 'histogram_bin_edges']
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+# range is a keyword argument to many functions, so save the builtin so they can
+# use it.
+_range = range
+
+
+def _ptp(x):
+    """Peak-to-peak value of x.
+
+    This implementation avoids the problem of signed integer arrays having a
+    peak-to-peak value that cannot be represented with the array's data type.
+    This function returns an unsigned value for signed integer arrays.
+    """
+    return _unsigned_subtract(x.max(), x.min())
+
+
+def _hist_bin_sqrt(x, range):
+    """
+    Square root histogram bin estimator.
+
+    Bin width is inversely proportional to the data size. Used by many
+    programs for its simplicity.
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    return _ptp(x) / np.sqrt(x.size)
+
+
+def _hist_bin_sturges(x, range):
+    """
+    Sturges histogram bin estimator.
+
+    A very simplistic estimator based on the assumption of normality of
+    the data. This estimator has poor performance for non-normal data,
+    which becomes especially obvious for large data sets. The estimate
+    depends only on size of the data.
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    return _ptp(x) / (np.log2(x.size) + 1.0)
+
+
+def _hist_bin_rice(x, range):
+    """
+    Rice histogram bin estimator.
+
+    Another simple estimator with no normality assumption. It has better
+    performance for large data than Sturges, but tends to overestimate
+    the number of bins. The number of bins is proportional to the cube
+    root of data size (asymptotically optimal). The estimate depends
+    only on size of the data.
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    return _ptp(x) / (2.0 * x.size ** (1.0 / 3))
+
+
+def _hist_bin_scott(x, range):
+    """
+    Scott histogram bin estimator.
+
+    The binwidth is proportional to the standard deviation of the data
+    and inversely proportional to the cube root of data size
+    (asymptotically optimal).
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    return (24.0 * np.pi**0.5 / x.size)**(1.0 / 3.0) * np.std(x)
+
+
+def _hist_bin_stone(x, range):
+    """
+    Histogram bin estimator based on minimizing the estimated integrated squared error (ISE).
+
+    The number of bins is chosen by minimizing the estimated ISE against the unknown
+    true distribution. The ISE is estimated using cross-validation and can be regarded
+    as a generalization of Scott's rule.
+    https://en.wikipedia.org/wiki/Histogram#Scott.27s_normal_reference_rule
+
+    This paper by Stone appears to be the origination of this rule.
+    https://digitalassets.lib.berkeley.edu/sdtr/ucb/text/34.pdf
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+    range : (float, float)
+        The lower and upper range of the bins.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """  # noqa: E501
+
+    n = x.size
+    ptp_x = _ptp(x)
+    if n <= 1 or ptp_x == 0:
+        return 0
+
+    def jhat(nbins):
+        hh = ptp_x / nbins
+        p_k = np.histogram(x, bins=nbins, range=range)[0] / n
+        return (2 - (n + 1) * p_k.dot(p_k)) / hh
+
+    nbins_upper_bound = max(100, int(np.sqrt(n)))
+    nbins = min(_range(1, nbins_upper_bound + 1), key=jhat)
+    if nbins == nbins_upper_bound:
+        warnings.warn("The number of bins estimated may be suboptimal.",
+                      RuntimeWarning, stacklevel=3)
+    return ptp_x / nbins
+
+
+def _hist_bin_doane(x, range):
+    """
+    Doane's histogram bin estimator.
+
+    Improved version of Sturges' formula which works better for
+    non-normal data. See
+    stats.stackexchange.com/questions/55134/doanes-formula-for-histogram-binning
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    if x.size > 2:
+        sg1 = np.sqrt(6.0 * (x.size - 2) / ((x.size + 1.0) * (x.size + 3)))
+        sigma = np.std(x)
+        if sigma > 0.0:
+            # These three operations add up to
+            # g1 = np.mean(((x - np.mean(x)) / sigma)**3)
+            # but use only one temp array instead of three
+            temp = x - np.mean(x)
+            np.true_divide(temp, sigma, temp)
+            np.power(temp, 3, temp)
+            g1 = np.mean(temp)
+            return _ptp(x) / (1.0 + np.log2(x.size) +
+                                    np.log2(1.0 + np.absolute(g1) / sg1))
+    return 0.0
+
+
+def _hist_bin_fd(x, range):
+    """
+    The Freedman-Diaconis histogram bin estimator.
+
+    The Freedman-Diaconis rule uses interquartile range (IQR) to
+    estimate binwidth. It is considered a variation of the Scott rule
+    with more robustness as the IQR is less affected by outliers than
+    the standard deviation. However, the IQR depends on fewer points
+    than the standard deviation, so it is less accurate, especially for
+    long tailed distributions.
+
+    If the IQR is 0, this function returns 0 for the bin width.
+    Binwidth is inversely proportional to the cube root of data size
+    (asymptotically optimal).
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+    """
+    del range  # unused
+    iqr = np.subtract(*np.percentile(x, [75, 25]))
+    return 2.0 * iqr * x.size ** (-1.0 / 3.0)
+
+
+def _hist_bin_auto(x, range):
+    """
+    Histogram bin estimator that uses the minimum width of a relaxed
+    Freedman-Diaconis and Sturges estimators if the FD bin width does
+    not result in a large number of bins. The relaxed Freedman-Diaconis estimator
+    limits the bin width to half the sqrt estimated to avoid small bins.
+
+    The FD estimator is usually the most robust method, but its width
+    estimate tends to be too large for small `x` and bad for data with limited
+    variance. The Sturges estimator is quite good for small (<1000) datasets
+    and is the default in the R language. This method gives good off-the-shelf
+    behaviour.
+
+
+    Parameters
+    ----------
+    x : array_like
+        Input data that is to be histogrammed, trimmed to range. May not
+        be empty.
+    range : Tuple with range for the histogram
+
+    Returns
+    -------
+    h : An estimate of the optimal bin width for the given data.
+
+    See Also
+    --------
+    _hist_bin_fd, _hist_bin_sturges
+    """
+    fd_bw = _hist_bin_fd(x, range)
+    sturges_bw = _hist_bin_sturges(x, range)
+    sqrt_bw = _hist_bin_sqrt(x, range)
+    # heuristic to limit the maximal number of bins
+    fd_bw_corrected = max(fd_bw, sqrt_bw / 2)
+    return min(fd_bw_corrected, sturges_bw)
+
+
+# Private dict initialized at module load time
+_hist_bin_selectors = {'stone': _hist_bin_stone,
+                       'auto': _hist_bin_auto,
+                       'doane': _hist_bin_doane,
+                       'fd': _hist_bin_fd,
+                       'rice': _hist_bin_rice,
+                       'scott': _hist_bin_scott,
+                       'sqrt': _hist_bin_sqrt,
+                       'sturges': _hist_bin_sturges}
+
+
+def _ravel_and_check_weights(a, weights):
+    """ Check a and weights have matching shapes, and ravel both """
+    a = np.asarray(a)
+
+    # Ensure that the array is a "subtractable" dtype
+    if a.dtype == np.bool:
+        msg = f"Converting input from {a.dtype} to {np.uint8} for compatibility."
+        warnings.warn(msg, RuntimeWarning, stacklevel=3)
+        a = a.astype(np.uint8)
+
+    if weights is not None:
+        weights = np.asarray(weights)
+        if weights.shape != a.shape:
+            raise ValueError(
+                'weights should have the same shape as a.')
+        weights = weights.ravel()
+    a = a.ravel()
+    return a, weights
+
+
+def _get_outer_edges(a, range):
+    """
+    Determine the outer bin edges to use, from either the data or the range
+    argument
+    """
+    if range is not None:
+        first_edge, last_edge = range
+        if first_edge > last_edge:
+            raise ValueError(
+                'max must be larger than min in range parameter.')
+        if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
+            raise ValueError(
+                f"supplied range of [{first_edge}, {last_edge}] is not finite")
+    elif a.size == 0:
+        # handle empty arrays. Can't determine range, so use 0-1.
+        first_edge, last_edge = 0, 1
+    else:
+        first_edge, last_edge = a.min(), a.max()
+        if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
+            raise ValueError(
+                f"autodetected range of [{first_edge}, {last_edge}] is not finite")
+
+    # expand empty range to avoid divide by zero
+    if first_edge == last_edge:
+        first_edge = first_edge - 0.5
+        last_edge = last_edge + 0.5
+
+    return first_edge, last_edge
+
+
+def _unsigned_subtract(a, b):
+    """
+    Subtract two values where a >= b, and produce an unsigned result
+
+    This is needed when finding the difference between the upper and lower
+    bound of an int16 histogram
+    """
+    # coerce to a single type
+    signed_to_unsigned = {
+        np.byte: np.ubyte,
+        np.short: np.ushort,
+        np.intc: np.uintc,
+        np.int_: np.uint,
+        np.longlong: np.ulonglong
+    }
+    dt = np.result_type(a, b)
+    try:
+        unsigned_dt = signed_to_unsigned[dt.type]
+    except KeyError:
+        return np.subtract(a, b, dtype=dt)
+    else:
+        # we know the inputs are integers, and we are deliberately casting
+        # signed to unsigned.  The input may be negative python integers so
+        # ensure we pass in arrays with the initial dtype (related to NEP 50).
+        return np.subtract(np.asarray(a, dtype=dt), np.asarray(b, dtype=dt),
+                           casting='unsafe', dtype=unsigned_dt)
+
+
+def _get_bin_edges(a, bins, range, weights):
+    """
+    Computes the bins used internally by `histogram`.
+
+    Parameters
+    ==========
+    a : ndarray
+        Ravelled data array
+    bins, range
+        Forwarded arguments from `histogram`.
+    weights : ndarray, optional
+        Ravelled weights array, or None
+
+    Returns
+    =======
+    bin_edges : ndarray
+        Array of bin edges
+    uniform_bins : (Number, Number, int):
+        The upper bound, lowerbound, and number of bins, used in the optimized
+        implementation of `histogram` that works on uniform bins.
+    """
+    # parse the overloaded bins argument
+    n_equal_bins = None
+    bin_edges = None
+
+    if isinstance(bins, str):
+        bin_name = bins
+        # if `bins` is a string for an automatic method,
+        # this will replace it with the number of bins calculated
+        if bin_name not in _hist_bin_selectors:
+            raise ValueError(
+                f"{bin_name!r} is not a valid estimator for `bins`")
+        if weights is not None:
+            raise TypeError("Automated estimation of the number of "
+                            "bins is not supported for weighted data")
+
+        first_edge, last_edge = _get_outer_edges(a, range)
+
+        # truncate the range if needed
+        if range is not None:
+            keep = (a >= first_edge)
+            keep &= (a <= last_edge)
+            if not np.logical_and.reduce(keep):
+                a = a[keep]
+
+        if a.size == 0:
+            n_equal_bins = 1
+        else:
+            # Do not call selectors on empty arrays
+            width = _hist_bin_selectors[bin_name](a, (first_edge, last_edge))
+            if width:
+                if np.issubdtype(a.dtype, np.integer) and width < 1:
+                    width = 1
+                delta = _unsigned_subtract(last_edge, first_edge)
+                n_equal_bins = int(np.ceil(delta / width))
+            else:
+                # Width can be zero for some estimators, e.g. FD when
+                # the IQR of the data is zero.
+                n_equal_bins = 1
+
+    elif np.ndim(bins) == 0:
+        try:
+            n_equal_bins = operator.index(bins)
+        except TypeError as e:
+            raise TypeError(
+                '`bins` must be an integer, a string, or an array') from e
+        if n_equal_bins < 1:
+            raise ValueError('`bins` must be positive, when an integer')
+
+        first_edge, last_edge = _get_outer_edges(a, range)
+
+    elif np.ndim(bins) == 1:
+        bin_edges = np.asarray(bins)
+        if np.any(bin_edges[:-1] > bin_edges[1:]):
+            raise ValueError(
+                '`bins` must increase monotonically, when an array')
+
+    else:
+        raise ValueError('`bins` must be 1d, when an array')
+
+    if n_equal_bins is not None:
+        # gh-10322 means that type resolution rules are dependent on array
+        # shapes. To avoid this causing problems, we pick a type now and stick
+        # with it throughout.
+        bin_type = np.result_type(first_edge, last_edge, a)
+        if np.issubdtype(bin_type, np.integer):
+            bin_type = np.result_type(bin_type, float)
+
+        # bin edges must be computed
+        bin_edges = np.linspace(
+            first_edge, last_edge, n_equal_bins + 1,
+            endpoint=True, dtype=bin_type)
+        if np.any(bin_edges[:-1] >= bin_edges[1:]):
+            raise ValueError(
+                f'Too many bins for data range. Cannot create {n_equal_bins} '
+                f'finite-sized bins.')
+        return bin_edges, (first_edge, last_edge, n_equal_bins)
+    else:
+        return bin_edges, None
+
+
+def _search_sorted_inclusive(a, v):
+    """
+    Like `searchsorted`, but where the last item in `v` is placed on the right.
+
+    In the context of a histogram, this makes the last bin edge inclusive
+    """
+    return np.concatenate((
+        a.searchsorted(v[:-1], 'left'),
+        a.searchsorted(v[-1:], 'right')
+    ))
+
+
+def _histogram_bin_edges_dispatcher(a, bins=None, range=None, weights=None):
+    return (a, bins, weights)
+
+
+@array_function_dispatch(_histogram_bin_edges_dispatcher)
+def histogram_bin_edges(a, bins=10, range=None, weights=None):
+    r"""
+    Function to calculate only the edges of the bins used by the `histogram`
+    function.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data. The histogram is computed over the flattened array.
+    bins : int or sequence of scalars or str, optional
+        If `bins` is an int, it defines the number of equal-width
+        bins in the given range (10, by default). If `bins` is a
+        sequence, it defines the bin edges, including the rightmost
+        edge, allowing for non-uniform bin widths.
+
+        If `bins` is a string from the list below, `histogram_bin_edges` will
+        use the method chosen to calculate the optimal bin width and
+        consequently the number of bins (see the Notes section for more detail
+        on the estimators) from the data that falls within the requested range.
+        While the bin width will be optimal for the actual data
+        in the range, the number of bins will be computed to fill the
+        entire range, including the empty portions. For visualisation,
+        using the 'auto' option is suggested. Weighted data is not
+        supported for automated bin size selection.
+
+        'auto'
+            Minimum bin width between the 'sturges' and 'fd' estimators.
+            Provides good all-around performance.
+
+        'fd' (Freedman Diaconis Estimator)
+            Robust (resilient to outliers) estimator that takes into
+            account data variability and data size.
+
+        'doane'
+            An improved version of Sturges' estimator that works better
+            with non-normal datasets.
+
+        'scott'
+            Less robust estimator that takes into account data variability
+            and data size.
+
+        'stone'
+            Estimator based on leave-one-out cross-validation estimate of
+            the integrated squared error. Can be regarded as a generalization
+            of Scott's rule.
+
+        'rice'
+            Estimator does not take variability into account, only data
+            size. Commonly overestimates number of bins required.
+
+        'sturges'
+            R's default method, only accounts for data size. Only
+            optimal for gaussian data and underestimates number of bins
+            for large non-gaussian datasets.
+
+        'sqrt'
+            Square root (of data size) estimator, used by Excel and
+            other programs for its speed and simplicity.
+
+    range : (float, float), optional
+        The lower and upper range of the bins.  If not provided, range
+        is simply ``(a.min(), a.max())``.  Values outside the range are
+        ignored. The first element of the range must be less than or
+        equal to the second. `range` affects the automatic bin
+        computation as well. While bin width is computed to be optimal
+        based on the actual data within `range`, the bin count will fill
+        the entire range including portions containing no data.
+
+    weights : array_like, optional
+        An array of weights, of the same shape as `a`.  Each value in
+        `a` only contributes its associated weight towards the bin count
+        (instead of 1). This is currently not used by any of the bin estimators,
+        but may be in the future.
+
+    Returns
+    -------
+    bin_edges : array of dtype float
+        The edges to pass into `histogram`
+
+    See Also
+    --------
+    histogram
+
+    Notes
+    -----
+    The methods to estimate the optimal number of bins are well founded
+    in literature, and are inspired by the choices R provides for
+    histogram visualisation. Note that having the number of bins
+    proportional to :math:`n^{1/3}` is asymptotically optimal, which is
+    why it appears in most estimators. These are simply plug-in methods
+    that give good starting points for number of bins. In the equations
+    below, :math:`h` is the binwidth and :math:`n_h` is the number of
+    bins. All estimators that compute bin counts are recast to bin width
+    using the `ptp` of the data. The final bin count is obtained from
+    ``np.round(np.ceil(range / h))``. The final bin width is often less
+    than what is returned by the estimators below.
+
+    'auto' (minimum bin width of the 'sturges' and 'fd' estimators)
+        A compromise to get a good value. For small datasets the Sturges
+        value will usually be chosen, while larger datasets will usually
+        default to FD.  Avoids the overly conservative behaviour of FD
+        and Sturges for small and large datasets respectively.
+        Switchover point is usually :math:`a.size \approx 1000`.
+
+    'fd' (Freedman Diaconis Estimator)
+        .. math:: h = 2 \frac{IQR}{n^{1/3}}
+
+        The binwidth is proportional to the interquartile range (IQR)
+        and inversely proportional to cube root of a.size. Can be too
+        conservative for small datasets, but is quite good for large
+        datasets. The IQR is very robust to outliers.
+
+    'scott'
+        .. math:: h = \sigma \sqrt[3]{\frac{24 \sqrt{\pi}}{n}}
+
+        The binwidth is proportional to the standard deviation of the
+        data and inversely proportional to cube root of ``x.size``. Can
+        be too conservative for small datasets, but is quite good for
+        large datasets. The standard deviation is not very robust to
+        outliers. Values are very similar to the Freedman-Diaconis
+        estimator in the absence of outliers.
+
+    'rice'
+        .. math:: n_h = 2n^{1/3}
+
+        The number of bins is only proportional to cube root of
+        ``a.size``. It tends to overestimate the number of bins and it
+        does not take into account data variability.
+
+    'sturges'
+        .. math:: n_h = \log _{2}(n) + 1
+
+        The number of bins is the base 2 log of ``a.size``.  This
+        estimator assumes normality of data and is too conservative for
+        larger, non-normal datasets. This is the default method in R's
+        ``hist`` method.
+
+    'doane'
+        .. math:: n_h = 1 + \log_{2}(n) +
+                        \log_{2}\left(1 + \frac{|g_1|}{\sigma_{g_1}}\right)
+
+            g_1 = mean\left[\left(\frac{x - \mu}{\sigma}\right)^3\right]
+
+            \sigma_{g_1} = \sqrt{\frac{6(n - 2)}{(n + 1)(n + 3)}}
+
+        An improved version of Sturges' formula that produces better
+        estimates for non-normal datasets. This estimator attempts to
+        account for the skew of the data.
+
+    'sqrt'
+        .. math:: n_h = \sqrt n
+
+        The simplest and fastest estimator. Only takes into account the
+        data size.
+
+    Additionally, if the data is of integer dtype, then the binwidth will never
+    be less than 1.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.array([0, 0, 0, 1, 2, 3, 3, 4, 5])
+    >>> np.histogram_bin_edges(arr, bins='auto', range=(0, 1))
+    array([0.  , 0.25, 0.5 , 0.75, 1.  ])
+    >>> np.histogram_bin_edges(arr, bins=2)
+    array([0. , 2.5, 5. ])
+
+    For consistency with histogram, an array of pre-computed bins is
+    passed through unmodified:
+
+    >>> np.histogram_bin_edges(arr, [1, 2])
+    array([1, 2])
+
+    This function allows one set of bins to be computed, and reused across
+    multiple histograms:
+
+    >>> shared_bins = np.histogram_bin_edges(arr, bins='auto')
+    >>> shared_bins
+    array([0., 1., 2., 3., 4., 5.])
+
+    >>> group_id = np.array([0, 1, 1, 0, 1, 1, 0, 1, 1])
+    >>> hist_0, _ = np.histogram(arr[group_id == 0], bins=shared_bins)
+    >>> hist_1, _ = np.histogram(arr[group_id == 1], bins=shared_bins)
+
+    >>> hist_0; hist_1
+    array([1, 1, 0, 1, 0])
+    array([2, 0, 1, 1, 2])
+
+    Which gives more easily comparable results than using separate bins for
+    each histogram:
+
+    >>> hist_0, bins_0 = np.histogram(arr[group_id == 0], bins='auto')
+    >>> hist_1, bins_1 = np.histogram(arr[group_id == 1], bins='auto')
+    >>> hist_0; hist_1
+    array([1, 1, 1])
+    array([2, 1, 1, 2])
+    >>> bins_0; bins_1
+    array([0., 1., 2., 3.])
+    array([0.  , 1.25, 2.5 , 3.75, 5.  ])
+
+    """
+    a, weights = _ravel_and_check_weights(a, weights)
+    bin_edges, _ = _get_bin_edges(a, bins, range, weights)
+    return bin_edges
+
+
+def _histogram_dispatcher(
+        a, bins=None, range=None, density=None, weights=None):
+    return (a, bins, weights)
+
+
+@array_function_dispatch(_histogram_dispatcher)
+def histogram(a, bins=10, range=None, density=None, weights=None):
+    r"""
+    Compute the histogram of a dataset.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data. The histogram is computed over the flattened array.
+    bins : int or sequence of scalars or str, optional
+        If `bins` is an int, it defines the number of equal-width
+        bins in the given range (10, by default). If `bins` is a
+        sequence, it defines a monotonically increasing array of bin edges,
+        including the rightmost edge, allowing for non-uniform bin widths.
+
+        If `bins` is a string, it defines the method used to calculate the
+        optimal bin width, as defined by `histogram_bin_edges`.
+
+    range : (float, float), optional
+        The lower and upper range of the bins.  If not provided, range
+        is simply ``(a.min(), a.max())``.  Values outside the range are
+        ignored. The first element of the range must be less than or
+        equal to the second. `range` affects the automatic bin
+        computation as well. While bin width is computed to be optimal
+        based on the actual data within `range`, the bin count will fill
+        the entire range including portions containing no data.
+    weights : array_like, optional
+        An array of weights, of the same shape as `a`.  Each value in
+        `a` only contributes its associated weight towards the bin count
+        (instead of 1). If `density` is True, the weights are
+        normalized, so that the integral of the density over the range
+        remains 1.
+        Please note that the ``dtype`` of `weights` will also become the
+        ``dtype`` of the returned accumulator (`hist`), so it must be
+        large enough to hold accumulated values as well.
+    density : bool, optional
+        If ``False``, the result will contain the number of samples in
+        each bin. If ``True``, the result is the value of the
+        probability *density* function at the bin, normalized such that
+        the *integral* over the range is 1. Note that the sum of the
+        histogram values will not be equal to 1 unless bins of unity
+        width are chosen; it is not a probability *mass* function.
+
+    Returns
+    -------
+    hist : array
+        The values of the histogram. See `density` and `weights` for a
+        description of the possible semantics.  If `weights` are given,
+        ``hist.dtype`` will be taken from `weights`.
+    bin_edges : array of dtype float
+        Return the bin edges ``(length(hist)+1)``.
+
+
+    See Also
+    --------
+    histogramdd, bincount, searchsorted, digitize, histogram_bin_edges
+
+    Notes
+    -----
+    All but the last (righthand-most) bin is half-open.  In other words,
+    if `bins` is::
+
+      [1, 2, 3, 4]
+
+    then the first bin is ``[1, 2)`` (including 1, but excluding 2) and
+    the second ``[2, 3)``.  The last bin, however, is ``[3, 4]``, which
+    *includes* 4.
+
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.histogram([1, 2, 1], bins=[0, 1, 2, 3])
+    (array([0, 2, 1]), array([0, 1, 2, 3]))
+    >>> np.histogram(np.arange(4), bins=np.arange(5), density=True)
+    (array([0.25, 0.25, 0.25, 0.25]), array([0, 1, 2, 3, 4]))
+    >>> np.histogram([[1, 2, 1], [1, 0, 1]], bins=[0,1,2,3])
+    (array([1, 4, 1]), array([0, 1, 2, 3]))
+
+    >>> a = np.arange(5)
+    >>> hist, bin_edges = np.histogram(a, density=True)
+    >>> hist
+    array([0.5, 0. , 0.5, 0. , 0. , 0.5, 0. , 0.5, 0. , 0.5])
+    >>> hist.sum()
+    2.4999999999999996
+    >>> np.sum(hist * np.diff(bin_edges))
+    1.0
+
+    Automated Bin Selection Methods example, using 2 peak random data
+    with 2000 points.
+
+    .. plot::
+        :include-source:
+
+        import matplotlib.pyplot as plt
+        import numpy as np
+
+        rng = np.random.RandomState(10)  # deterministic random data
+        a = np.hstack((rng.normal(size=1000),
+                       rng.normal(loc=5, scale=2, size=1000)))
+        plt.hist(a, bins='auto')  # arguments are passed to np.histogram
+        plt.title("Histogram with 'auto' bins")
+        plt.show()
+
+    """
+    a, weights = _ravel_and_check_weights(a, weights)
+
+    bin_edges, uniform_bins = _get_bin_edges(a, bins, range, weights)
+
+    # Histogram is an integer or a float array depending on the weights.
+    if weights is None:
+        ntype = np.dtype(np.intp)
+    else:
+        ntype = weights.dtype
+
+    # We set a block size, as this allows us to iterate over chunks when
+    # computing histograms, to minimize memory usage.
+    BLOCK = 65536
+
+    # The fast path uses bincount, but that only works for certain types
+    # of weight
+    simple_weights = (
+        weights is None or
+        np.can_cast(weights.dtype, np.double) or
+        np.can_cast(weights.dtype, complex)
+    )
+
+    if uniform_bins is not None and simple_weights:
+        # Fast algorithm for equal bins
+        # We now convert values of a to bin indices, under the assumption of
+        # equal bin widths (which is valid here).
+        first_edge, last_edge, n_equal_bins = uniform_bins
+
+        # Initialize empty histogram
+        n = np.zeros(n_equal_bins, ntype)
+
+        # Pre-compute histogram scaling factor
+        norm_numerator = n_equal_bins
+        norm_denom = _unsigned_subtract(last_edge, first_edge)
+
+        # We iterate over blocks here for two reasons: the first is that for
+        # large arrays, it is actually faster (for example for a 10^8 array it
+        # is 2x as fast) and it results in a memory footprint 3x lower in the
+        # limit of large arrays.
+        for i in _range(0, len(a), BLOCK):
+            tmp_a = a[i:i + BLOCK]
+            if weights is None:
+                tmp_w = None
+            else:
+                tmp_w = weights[i:i + BLOCK]
+
+            # Only include values in the right range
+            keep = (tmp_a >= first_edge)
+            keep &= (tmp_a <= last_edge)
+            if not np.logical_and.reduce(keep):
+                tmp_a = tmp_a[keep]
+                if tmp_w is not None:
+                    tmp_w = tmp_w[keep]
+
+            # This cast ensures no type promotions occur below, which gh-10322
+            # make unpredictable. Getting it wrong leads to precision errors
+            # like gh-8123.
+            tmp_a = tmp_a.astype(bin_edges.dtype, copy=False)
+
+            # Compute the bin indices, and for values that lie exactly on
+            # last_edge we need to subtract one
+            f_indices = ((_unsigned_subtract(tmp_a, first_edge) / norm_denom)
+                         * norm_numerator)
+            indices = f_indices.astype(np.intp)
+            indices[indices == n_equal_bins] -= 1
+
+            # The index computation is not guaranteed to give exactly
+            # consistent results within ~1 ULP of the bin edges.
+            decrement = tmp_a < bin_edges[indices]
+            indices[decrement] -= 1
+            # The last bin includes the right edge. The other bins do not.
+            increment = ((tmp_a >= bin_edges[indices + 1])
+                         & (indices != n_equal_bins - 1))
+            indices[increment] += 1
+
+            # We now compute the histogram using bincount
+            if ntype.kind == 'c':
+                n.real += np.bincount(indices, weights=tmp_w.real,
+                                      minlength=n_equal_bins)
+                n.imag += np.bincount(indices, weights=tmp_w.imag,
+                                      minlength=n_equal_bins)
+            else:
+                n += np.bincount(indices, weights=tmp_w,
+                                 minlength=n_equal_bins).astype(ntype)
+    else:
+        # Compute via cumulative histogram
+        cum_n = np.zeros(bin_edges.shape, ntype)
+        if weights is None:
+            for i in _range(0, len(a), BLOCK):
+                sa = np.sort(a[i:i + BLOCK])
+                cum_n += _search_sorted_inclusive(sa, bin_edges)
+        else:
+            zero = np.zeros(1, dtype=ntype)
+            for i in _range(0, len(a), BLOCK):
+                tmp_a = a[i:i + BLOCK]
+                tmp_w = weights[i:i + BLOCK]
+                sorting_index = np.argsort(tmp_a)
+                sa = tmp_a[sorting_index]
+                sw = tmp_w[sorting_index]
+                cw = np.concatenate((zero, sw.cumsum()))
+                bin_index = _search_sorted_inclusive(sa, bin_edges)
+                cum_n += cw[bin_index]
+
+        n = np.diff(cum_n)
+
+    if density:
+        db = np.array(np.diff(bin_edges), float)
+        return n / db / n.sum(), bin_edges
+
+    return n, bin_edges
+
+
+def _histogramdd_dispatcher(sample, bins=None, range=None, density=None,
+                            weights=None):
+    if hasattr(sample, 'shape'):  # same condition as used in histogramdd
+        yield sample
+    else:
+        yield from sample
+    with contextlib.suppress(TypeError):
+        yield from bins
+    yield weights
+
+
+@array_function_dispatch(_histogramdd_dispatcher)
+def histogramdd(sample, bins=10, range=None, density=None, weights=None):
+    """
+    Compute the multidimensional histogram of some data.
+
+    Parameters
+    ----------
+    sample : (N, D) array, or (N, D) array_like
+        The data to be histogrammed.
+
+        Note the unusual interpretation of sample when an array_like:
+
+        * When an array, each row is a coordinate in a D-dimensional space -
+          such as ``histogramdd(np.array([p1, p2, p3]))``.
+        * When an array_like, each element is the list of values for single
+          coordinate - such as ``histogramdd((X, Y, Z))``.
+
+        The first form should be preferred.
+
+    bins : sequence or int, optional
+        The bin specification:
+
+        * A sequence of arrays describing the monotonically increasing bin
+          edges along each dimension.
+        * The number of bins for each dimension (nx, ny, ... =bins)
+        * The number of bins for all dimensions (nx=ny=...=bins).
+
+    range : sequence, optional
+        A sequence of length D, each an optional (lower, upper) tuple giving
+        the outer bin edges to be used if the edges are not given explicitly in
+        `bins`.
+        An entry of None in the sequence results in the minimum and maximum
+        values being used for the corresponding dimension.
+        The default, None, is equivalent to passing a tuple of D None values.
+    density : bool, optional
+        If False, the default, returns the number of samples in each bin.
+        If True, returns the probability *density* function at the bin,
+        ``bin_count / sample_count / bin_volume``.
+    weights : (N,) array_like, optional
+        An array of values `w_i` weighing each sample `(x_i, y_i, z_i, ...)`.
+        Weights are normalized to 1 if density is True. If density is False,
+        the values of the returned histogram are equal to the sum of the
+        weights belonging to the samples falling into each bin.
+
+    Returns
+    -------
+    H : ndarray
+        The multidimensional histogram of sample x. See density and weights
+        for the different possible semantics.
+    edges : tuple of ndarrays
+        A tuple of D arrays describing the bin edges for each dimension.
+
+    See Also
+    --------
+    histogram: 1-D histogram
+    histogram2d: 2-D histogram
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> rng = np.random.default_rng()
+    >>> r = rng.normal(size=(100,3))
+    >>> H, edges = np.histogramdd(r, bins = (5, 8, 4))
+    >>> H.shape, edges[0].size, edges[1].size, edges[2].size
+    ((5, 8, 4), 6, 9, 5)
+
+    """
+
+    try:
+        # Sample is an ND-array.
+        N, D = sample.shape
+    except (AttributeError, ValueError):
+        # Sample is a sequence of 1D arrays.
+        sample = np.atleast_2d(sample).T
+        N, D = sample.shape
+
+    nbin = np.empty(D, np.intp)
+    edges = D * [None]
+    dedges = D * [None]
+    if weights is not None:
+        weights = np.asarray(weights)
+
+    try:
+        M = len(bins)
+        if M != D:
+            raise ValueError(
+                'The dimension of bins must be equal to the dimension of the '
+                'sample x.')
+    except TypeError:
+        # bins is an integer
+        bins = D * [bins]
+
+    # normalize the range argument
+    if range is None:
+        range = (None,) * D
+    elif len(range) != D:
+        raise ValueError('range argument must have one entry per dimension')
+
+    # Create edge arrays
+    for i in _range(D):
+        if np.ndim(bins[i]) == 0:
+            if bins[i] < 1:
+                raise ValueError(
+                    f'`bins[{i}]` must be positive, when an integer')
+            smin, smax = _get_outer_edges(sample[:, i], range[i])
+            try:
+                n = operator.index(bins[i])
+
+            except TypeError as e:
+                raise TypeError(
+                    f"`bins[{i}]` must be an integer, when a scalar"
+                ) from e
+
+            edges[i] = np.linspace(smin, smax, n + 1)
+        elif np.ndim(bins[i]) == 1:
+            edges[i] = np.asarray(bins[i])
+            if np.any(edges[i][:-1] > edges[i][1:]):
+                raise ValueError(
+                    f'`bins[{i}]` must be monotonically increasing, when an array')
+        else:
+            raise ValueError(
+                f'`bins[{i}]` must be a scalar or 1d array')
+
+        nbin[i] = len(edges[i]) + 1  # includes an outlier on each end
+        dedges[i] = np.diff(edges[i])
+
+    # Compute the bin number each sample falls into.
+    Ncount = tuple(
+        # avoid np.digitize to work around gh-11022
+        np.searchsorted(edges[i], sample[:, i], side='right')
+        for i in _range(D)
+    )
+
+    # Using digitize, values that fall on an edge are put in the right bin.
+    # For the rightmost bin, we want values equal to the right edge to be
+    # counted in the last bin, and not as an outlier.
+    for i in _range(D):
+        # Find which points are on the rightmost edge.
+        on_edge = (sample[:, i] == edges[i][-1])
+        # Shift these points one bin to the left.
+        Ncount[i][on_edge] -= 1
+
+    # Compute the sample indices in the flattened histogram matrix.
+    # This raises an error if the array is too large.
+    xy = np.ravel_multi_index(Ncount, nbin)
+
+    # Compute the number of repetitions in xy and assign it to the
+    # flattened histmat.
+    hist = np.bincount(xy, weights, minlength=nbin.prod())
+
+    # Shape into a proper matrix
+    hist = hist.reshape(nbin)
+
+    # This preserves the (bad) behavior observed in gh-7845, for now.
+    hist = hist.astype(float, casting='safe')
+
+    # Remove outliers (indices 0 and -1 for each dimension).
+    core = D * (slice(1, -1),)
+    hist = hist[core]
+
+    if density:
+        # calculate the probability density function
+        s = hist.sum()
+        for i in _range(D):
+            shape = np.ones(D, int)
+            shape[i] = nbin[i] - 2
+            hist = hist / dedges[i].reshape(shape)
+        hist /= s
+
+    if (hist.shape != nbin - 2).any():
+        raise RuntimeError(
+            "Internal Shape Error")
+    return hist, edges
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..b9fa4914234d9a019812ec74e68d4de88853a060
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_histograms_impl.pyi
@@ -0,0 +1,40 @@
+from collections.abc import Sequence
+from typing import Any, Literal as L, SupportsIndex, TypeAlias
+
+from numpy._typing import ArrayLike, NDArray
+
+__all__ = ["histogram", "histogramdd", "histogram_bin_edges"]
+
+_BinKind: TypeAlias = L[
+    "stone",
+    "auto",
+    "doane",
+    "fd",
+    "rice",
+    "scott",
+    "sqrt",
+    "sturges",
+]
+
+def histogram_bin_edges(
+    a: ArrayLike,
+    bins: _BinKind | SupportsIndex | ArrayLike = 10,
+    range: tuple[float, float] | None = None,
+    weights: ArrayLike | None = None,
+) -> NDArray[Any]: ...
+
+def histogram(
+    a: ArrayLike,
+    bins: _BinKind | SupportsIndex | ArrayLike = 10,
+    range: tuple[float, float] | None = None,
+    density: bool | None = None,
+    weights: ArrayLike | None = None,
+) -> tuple[NDArray[Any], NDArray[Any]]: ...
+
+def histogramdd(
+    sample: ArrayLike,
+    bins: SupportsIndex | ArrayLike = 10,
+    range: Sequence[tuple[float, float]] | None = None,
+    density: bool | None = None,
+    weights: ArrayLike | None = None,
+) -> tuple[NDArray[Any], tuple[NDArray[Any], ...]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc86430c2604162ad9f9d83e5ee50ae72d0a90dc
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.py
@@ -0,0 +1,1048 @@
+import functools
+import math
+import sys
+from itertools import product
+
+import numpy as np
+import numpy._core.numeric as _nx
+import numpy.matrixlib as matrixlib
+from numpy._core import linspace, overrides
+from numpy._core.multiarray import ravel_multi_index, unravel_index
+from numpy._core.numeric import ScalarType, array
+from numpy._core.numerictypes import issubdtype
+from numpy._utils import set_module
+from numpy.lib._function_base_impl import diff
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+__all__ = [
+    'ravel_multi_index', 'unravel_index', 'mgrid', 'ogrid', 'r_', 'c_',
+    's_', 'index_exp', 'ix_', 'ndenumerate', 'ndindex', 'fill_diagonal',
+    'diag_indices', 'diag_indices_from'
+]
+
+
+def _ix__dispatcher(*args):
+    return args
+
+
+@array_function_dispatch(_ix__dispatcher)
+def ix_(*args):
+    """
+    Construct an open mesh from multiple sequences.
+
+    This function takes N 1-D sequences and returns N outputs with N
+    dimensions each, such that the shape is 1 in all but one dimension
+    and the dimension with the non-unit shape value cycles through all
+    N dimensions.
+
+    Using `ix_` one can quickly construct index arrays that will index
+    the cross product. ``a[np.ix_([1,3],[2,5])]`` returns the array
+    ``[[a[1,2] a[1,5]], [a[3,2] a[3,5]]]``.
+
+    Parameters
+    ----------
+    args : 1-D sequences
+        Each sequence should be of integer or boolean type.
+        Boolean sequences will be interpreted as boolean masks for the
+        corresponding dimension (equivalent to passing in
+        ``np.nonzero(boolean_sequence)``).
+
+    Returns
+    -------
+    out : tuple of ndarrays
+        N arrays with N dimensions each, with N the number of input
+        sequences. Together these arrays form an open mesh.
+
+    See Also
+    --------
+    ogrid, mgrid, meshgrid
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(10).reshape(2, 5)
+    >>> a
+    array([[0, 1, 2, 3, 4],
+           [5, 6, 7, 8, 9]])
+    >>> ixgrid = np.ix_([0, 1], [2, 4])
+    >>> ixgrid
+    (array([[0],
+           [1]]), array([[2, 4]]))
+    >>> ixgrid[0].shape, ixgrid[1].shape
+    ((2, 1), (1, 2))
+    >>> a[ixgrid]
+    array([[2, 4],
+           [7, 9]])
+
+    >>> ixgrid = np.ix_([True, True], [2, 4])
+    >>> a[ixgrid]
+    array([[2, 4],
+           [7, 9]])
+    >>> ixgrid = np.ix_([True, True], [False, False, True, False, True])
+    >>> a[ixgrid]
+    array([[2, 4],
+           [7, 9]])
+
+    """
+    out = []
+    nd = len(args)
+    for k, new in enumerate(args):
+        if not isinstance(new, _nx.ndarray):
+            new = np.asarray(new)
+            if new.size == 0:
+                # Explicitly type empty arrays to avoid float default
+                new = new.astype(_nx.intp)
+        if new.ndim != 1:
+            raise ValueError("Cross index must be 1 dimensional")
+        if issubdtype(new.dtype, _nx.bool):
+            new, = new.nonzero()
+        new = new.reshape((1,) * k + (new.size,) + (1,) * (nd - k - 1))
+        out.append(new)
+    return tuple(out)
+
+
+class nd_grid:
+    """
+    Construct a multi-dimensional "meshgrid".
+
+    ``grid = nd_grid()`` creates an instance which will return a mesh-grid
+    when indexed.  The dimension and number of the output arrays are equal
+    to the number of indexing dimensions.  If the step length is not a
+    complex number, then the stop is not inclusive.
+
+    However, if the step length is a **complex number** (e.g. 5j), then the
+    integer part of its magnitude is interpreted as specifying the
+    number of points to create between the start and stop values, where
+    the stop value **is inclusive**.
+
+    If instantiated with an argument of ``sparse=True``, the mesh-grid is
+    open (or not fleshed out) so that only one-dimension of each returned
+    argument is greater than 1.
+
+    Parameters
+    ----------
+    sparse : bool, optional
+        Whether the grid is sparse or not. Default is False.
+
+    Notes
+    -----
+    Two instances of `nd_grid` are made available in the NumPy namespace,
+    `mgrid` and `ogrid`, approximately defined as::
+
+        mgrid = nd_grid(sparse=False)
+        ogrid = nd_grid(sparse=True)
+
+    Users should use these pre-defined instances instead of using `nd_grid`
+    directly.
+    """
+    __slots__ = ('sparse',)
+
+    def __init__(self, sparse=False):
+        self.sparse = sparse
+
+    def __getitem__(self, key):
+        try:
+            size = []
+            # Mimic the behavior of `np.arange` and use a data type
+            # which is at least as large as `np.int_`
+            num_list = [0]
+            for k in range(len(key)):
+                step = key[k].step
+                start = key[k].start
+                stop = key[k].stop
+                if start is None:
+                    start = 0
+                if step is None:
+                    step = 1
+                if isinstance(step, (_nx.complexfloating, complex)):
+                    step = abs(step)
+                    size.append(int(step))
+                else:
+                    size.append(
+                        math.ceil((stop - start) / step))
+                num_list += [start, stop, step]
+            typ = _nx.result_type(*num_list)
+            if self.sparse:
+                nn = [_nx.arange(_x, dtype=_t)
+                      for _x, _t in zip(size, (typ,) * len(size))]
+            else:
+                nn = _nx.indices(size, typ)
+            for k, kk in enumerate(key):
+                step = kk.step
+                start = kk.start
+                if start is None:
+                    start = 0
+                if step is None:
+                    step = 1
+                if isinstance(step, (_nx.complexfloating, complex)):
+                    step = int(abs(step))
+                    if step != 1:
+                        step = (kk.stop - start) / float(step - 1)
+                nn[k] = (nn[k] * step + start)
+            if self.sparse:
+                slobj = [_nx.newaxis] * len(size)
+                for k in range(len(size)):
+                    slobj[k] = slice(None, None)
+                    nn[k] = nn[k][tuple(slobj)]
+                    slobj[k] = _nx.newaxis
+                return tuple(nn)  # ogrid -> tuple of arrays
+            return nn  # mgrid -> ndarray
+        except (IndexError, TypeError):
+            step = key.step
+            stop = key.stop
+            start = key.start
+            if start is None:
+                start = 0
+            if isinstance(step, (_nx.complexfloating, complex)):
+                # Prevent the (potential) creation of integer arrays
+                step_float = abs(step)
+                step = length = int(step_float)
+                if step != 1:
+                    step = (key.stop - start) / float(step - 1)
+                typ = _nx.result_type(start, stop, step_float)
+                return _nx.arange(0, length, 1, dtype=typ) * step + start
+            else:
+                return _nx.arange(start, stop, step)
+
+
+class MGridClass(nd_grid):
+    """
+    An instance which returns a dense multi-dimensional "meshgrid".
+
+    An instance which returns a dense (or fleshed out) mesh-grid
+    when indexed, so that each returned argument has the same shape.
+    The dimensions and number of the output arrays are equal to the
+    number of indexing dimensions.  If the step length is not a complex
+    number, then the stop is not inclusive.
+
+    However, if the step length is a **complex number** (e.g. 5j), then
+    the integer part of its magnitude is interpreted as specifying the
+    number of points to create between the start and stop values, where
+    the stop value **is inclusive**.
+
+    Returns
+    -------
+    mesh-grid : ndarray
+        A single array, containing a set of `ndarray`\\ s all of the same
+        dimensions. stacked along the first axis.
+
+    See Also
+    --------
+    ogrid : like `mgrid` but returns open (not fleshed out) mesh grids
+    meshgrid: return coordinate matrices from coordinate vectors
+    r_ : array concatenator
+    :ref:`how-to-partition`
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.mgrid[0:5, 0:5]
+    array([[[0, 0, 0, 0, 0],
+            [1, 1, 1, 1, 1],
+            [2, 2, 2, 2, 2],
+            [3, 3, 3, 3, 3],
+            [4, 4, 4, 4, 4]],
+           [[0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4],
+            [0, 1, 2, 3, 4]]])
+    >>> np.mgrid[-1:1:5j]
+    array([-1. , -0.5,  0. ,  0.5,  1. ])
+
+    >>> np.mgrid[0:4].shape
+    (4,)
+    >>> np.mgrid[0:4, 0:5].shape
+    (2, 4, 5)
+    >>> np.mgrid[0:4, 0:5, 0:6].shape
+    (3, 4, 5, 6)
+
+    """
+    __slots__ = ()
+
+    def __init__(self):
+        super().__init__(sparse=False)
+
+
+mgrid = MGridClass()
+
+
+class OGridClass(nd_grid):
+    """
+    An instance which returns an open multi-dimensional "meshgrid".
+
+    An instance which returns an open (i.e. not fleshed out) mesh-grid
+    when indexed, so that only one dimension of each returned array is
+    greater than 1.  The dimension and number of the output arrays are
+    equal to the number of indexing dimensions.  If the step length is
+    not a complex number, then the stop is not inclusive.
+
+    However, if the step length is a **complex number** (e.g. 5j), then
+    the integer part of its magnitude is interpreted as specifying the
+    number of points to create between the start and stop values, where
+    the stop value **is inclusive**.
+
+    Returns
+    -------
+    mesh-grid : ndarray or tuple of ndarrays
+        If the input is a single slice, returns an array.
+        If the input is multiple slices, returns a tuple of arrays, with
+        only one dimension not equal to 1.
+
+    See Also
+    --------
+    mgrid : like `ogrid` but returns dense (or fleshed out) mesh grids
+    meshgrid: return coordinate matrices from coordinate vectors
+    r_ : array concatenator
+    :ref:`how-to-partition`
+
+    Examples
+    --------
+    >>> from numpy import ogrid
+    >>> ogrid[-1:1:5j]
+    array([-1. , -0.5,  0. ,  0.5,  1. ])
+    >>> ogrid[0:5, 0:5]
+    (array([[0],
+            [1],
+            [2],
+            [3],
+            [4]]),
+     array([[0, 1, 2, 3, 4]]))
+
+    """
+    __slots__ = ()
+
+    def __init__(self):
+        super().__init__(sparse=True)
+
+
+ogrid = OGridClass()
+
+
+class AxisConcatenator:
+    """
+    Translates slice objects to concatenation along an axis.
+
+    For detailed documentation on usage, see `r_`.
+    """
+    __slots__ = ('axis', 'matrix', 'ndmin', 'trans1d')
+
+    # allow ma.mr_ to override this
+    concatenate = staticmethod(_nx.concatenate)
+    makemat = staticmethod(matrixlib.matrix)
+
+    def __init__(self, axis=0, matrix=False, ndmin=1, trans1d=-1):
+        self.axis = axis
+        self.matrix = matrix
+        self.trans1d = trans1d
+        self.ndmin = ndmin
+
+    def __getitem__(self, key):
+        # handle matrix builder syntax
+        if isinstance(key, str):
+            frame = sys._getframe().f_back
+            mymat = matrixlib.bmat(key, frame.f_globals, frame.f_locals)
+            return mymat
+
+        if not isinstance(key, tuple):
+            key = (key,)
+
+        # copy attributes, since they can be overridden in the first argument
+        trans1d = self.trans1d
+        ndmin = self.ndmin
+        matrix = self.matrix
+        axis = self.axis
+
+        objs = []
+        # dtypes or scalars for weak scalar handling in result_type
+        result_type_objs = []
+
+        for k, item in enumerate(key):
+            scalar = False
+            if isinstance(item, slice):
+                step = item.step
+                start = item.start
+                stop = item.stop
+                if start is None:
+                    start = 0
+                if step is None:
+                    step = 1
+                if isinstance(step, (_nx.complexfloating, complex)):
+                    size = int(abs(step))
+                    newobj = linspace(start, stop, num=size)
+                else:
+                    newobj = _nx.arange(start, stop, step)
+                if ndmin > 1:
+                    newobj = array(newobj, copy=None, ndmin=ndmin)
+                    if trans1d != -1:
+                        newobj = newobj.swapaxes(-1, trans1d)
+            elif isinstance(item, str):
+                if k != 0:
+                    raise ValueError("special directives must be the "
+                                     "first entry.")
+                if item in ('r', 'c'):
+                    matrix = True
+                    col = (item == 'c')
+                    continue
+                if ',' in item:
+                    vec = item.split(',')
+                    try:
+                        axis, ndmin = [int(x) for x in vec[:2]]
+                        if len(vec) == 3:
+                            trans1d = int(vec[2])
+                        continue
+                    except Exception as e:
+                        raise ValueError(
+                            f"unknown special directive {item!r}"
+                        ) from e
+                try:
+                    axis = int(item)
+                    continue
+                except (ValueError, TypeError) as e:
+                    raise ValueError("unknown special directive") from e
+            elif type(item) in ScalarType:
+                scalar = True
+                newobj = item
+            else:
+                item_ndim = np.ndim(item)
+                newobj = array(item, copy=None, subok=True, ndmin=ndmin)
+                if trans1d != -1 and item_ndim < ndmin:
+                    k2 = ndmin - item_ndim
+                    k1 = trans1d
+                    if k1 < 0:
+                        k1 += k2 + 1
+                    defaxes = list(range(ndmin))
+                    axes = defaxes[:k1] + defaxes[k2:] + defaxes[k1:k2]
+                    newobj = newobj.transpose(axes)
+
+            objs.append(newobj)
+            if scalar:
+                result_type_objs.append(item)
+            else:
+                result_type_objs.append(newobj.dtype)
+
+        # Ensure that scalars won't up-cast unless warranted, for 0, drops
+        # through to error in concatenate.
+        if len(result_type_objs) != 0:
+            final_dtype = _nx.result_type(*result_type_objs)
+            # concatenate could do cast, but that can be overridden:
+            objs = [array(obj, copy=None, subok=True,
+                          ndmin=ndmin, dtype=final_dtype) for obj in objs]
+
+        res = self.concatenate(tuple(objs), axis=axis)
+
+        if matrix:
+            oldndim = res.ndim
+            res = self.makemat(res)
+            if oldndim == 1 and col:
+                res = res.T
+        return res
+
+    def __len__(self):
+        return 0
+
+# separate classes are used here instead of just making r_ = concatenator(0),
+# etc. because otherwise we couldn't get the doc string to come out right
+# in help(r_)
+
+
+class RClass(AxisConcatenator):
+    """
+    Translates slice objects to concatenation along the first axis.
+
+    This is a simple way to build up arrays quickly. There are two use cases.
+
+    1. If the index expression contains comma separated arrays, then stack
+       them along their first axis.
+    2. If the index expression contains slice notation or scalars then create
+       a 1-D array with a range indicated by the slice notation.
+
+    If slice notation is used, the syntax ``start:stop:step`` is equivalent
+    to ``np.arange(start, stop, step)`` inside of the brackets. However, if
+    ``step`` is an imaginary number (i.e. 100j) then its integer portion is
+    interpreted as a number-of-points desired and the start and stop are
+    inclusive. In other words ``start:stop:stepj`` is interpreted as
+    ``np.linspace(start, stop, step, endpoint=1)`` inside of the brackets.
+    After expansion of slice notation, all comma separated sequences are
+    concatenated together.
+
+    Optional character strings placed as the first element of the index
+    expression can be used to change the output. The strings 'r' or 'c' result
+    in matrix output. If the result is 1-D and 'r' is specified a 1 x N (row)
+    matrix is produced. If the result is 1-D and 'c' is specified, then
+    an N x 1 (column) matrix is produced.
+    If the result is 2-D then both provide the same matrix result.
+
+    A string integer specifies which axis to stack multiple comma separated
+    arrays along. A string of two comma-separated integers allows indication
+    of the minimum number of dimensions to force each entry into as the
+    second integer (the axis to concatenate along is still the first integer).
+
+    A string with three comma-separated integers allows specification of the
+    axis to concatenate along, the minimum number of dimensions to force the
+    entries to, and which axis should contain the start of the arrays which
+    are less than the specified number of dimensions. In other words the third
+    integer allows you to specify where the 1's should be placed in the shape
+    of the arrays that have their shapes upgraded. By default, they are placed
+    in the front of the shape tuple. The third argument allows you to specify
+    where the start of the array should be instead. Thus, a third argument of
+    '0' would place the 1's at the end of the array shape. Negative integers
+    specify where in the new shape tuple the last dimension of upgraded arrays
+    should be placed, so the default is '-1'.
+
+    Parameters
+    ----------
+    Not a function, so takes no parameters
+
+
+    Returns
+    -------
+    A concatenated ndarray or matrix.
+
+    See Also
+    --------
+    concatenate : Join a sequence of arrays along an existing axis.
+    c_ : Translates slice objects to concatenation along the second axis.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.r_[np.array([1,2,3]), 0, 0, np.array([4,5,6])]
+    array([1, 2, 3, ..., 4, 5, 6])
+    >>> np.r_[-1:1:6j, [0]*3, 5, 6]
+    array([-1. , -0.6, -0.2,  0.2,  0.6,  1. ,  0. ,  0. ,  0. ,  5. ,  6. ])
+
+    String integers specify the axis to concatenate along or the minimum
+    number of dimensions to force entries into.
+
+    >>> a = np.array([[0, 1, 2], [3, 4, 5]])
+    >>> np.r_['-1', a, a] # concatenate along last axis
+    array([[0, 1, 2, 0, 1, 2],
+           [3, 4, 5, 3, 4, 5]])
+    >>> np.r_['0,2', [1,2,3], [4,5,6]] # concatenate along first axis, dim>=2
+    array([[1, 2, 3],
+           [4, 5, 6]])
+
+    >>> np.r_['0,2,0', [1,2,3], [4,5,6]]
+    array([[1],
+           [2],
+           [3],
+           [4],
+           [5],
+           [6]])
+    >>> np.r_['1,2,0', [1,2,3], [4,5,6]]
+    array([[1, 4],
+           [2, 5],
+           [3, 6]])
+
+    Using 'r' or 'c' as a first string argument creates a matrix.
+
+    >>> np.r_['r',[1,2,3], [4,5,6]]
+    matrix([[1, 2, 3, 4, 5, 6]])
+
+    """
+    __slots__ = ()
+
+    def __init__(self):
+        AxisConcatenator.__init__(self, 0)
+
+
+r_ = RClass()
+
+
+class CClass(AxisConcatenator):
+    """
+    Translates slice objects to concatenation along the second axis.
+
+    This is short-hand for ``np.r_['-1,2,0', index expression]``, which is
+    useful because of its common occurrence. In particular, arrays will be
+    stacked along their last axis after being upgraded to at least 2-D with
+    1's post-pended to the shape (column vectors made out of 1-D arrays).
+
+    See Also
+    --------
+    column_stack : Stack 1-D arrays as columns into a 2-D array.
+    r_ : For more detailed documentation.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.c_[np.array([1,2,3]), np.array([4,5,6])]
+    array([[1, 4],
+           [2, 5],
+           [3, 6]])
+    >>> np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])]
+    array([[1, 2, 3, ..., 4, 5, 6]])
+
+    """
+    __slots__ = ()
+
+    def __init__(self):
+        AxisConcatenator.__init__(self, -1, ndmin=2, trans1d=0)
+
+
+c_ = CClass()
+
+
+@set_module('numpy')
+class ndenumerate:
+    """
+    Multidimensional index iterator.
+
+    Return an iterator yielding pairs of array coordinates and values.
+
+    Parameters
+    ----------
+    arr : ndarray
+      Input array.
+
+    See Also
+    --------
+    ndindex, flatiter
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> for index, x in np.ndenumerate(a):
+    ...     print(index, x)
+    (0, 0) 1
+    (0, 1) 2
+    (1, 0) 3
+    (1, 1) 4
+
+    """
+
+    def __init__(self, arr):
+        self.iter = np.asarray(arr).flat
+
+    def __next__(self):
+        """
+        Standard iterator method, returns the index tuple and array value.
+
+        Returns
+        -------
+        coords : tuple of ints
+            The indices of the current iteration.
+        val : scalar
+            The array element of the current iteration.
+
+        """
+        return self.iter.coords, next(self.iter)
+
+    def __iter__(self):
+        return self
+
+
+@set_module('numpy')
+class ndindex:
+    """
+    An N-dimensional iterator object to index arrays.
+
+    Given the shape of an array, an `ndindex` instance iterates over
+    the N-dimensional index of the array. At each iteration a tuple
+    of indices is returned, the last dimension is iterated over first.
+
+    Parameters
+    ----------
+    shape : ints, or a single tuple of ints
+        The size of each dimension of the array can be passed as
+        individual parameters or as the elements of a tuple.
+
+    See Also
+    --------
+    ndenumerate, flatiter
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Dimensions as individual arguments
+
+    >>> for index in np.ndindex(3, 2, 1):
+    ...     print(index)
+    (0, 0, 0)
+    (0, 1, 0)
+    (1, 0, 0)
+    (1, 1, 0)
+    (2, 0, 0)
+    (2, 1, 0)
+
+    Same dimensions - but in a tuple ``(3, 2, 1)``
+
+    >>> for index in np.ndindex((3, 2, 1)):
+    ...     print(index)
+    (0, 0, 0)
+    (0, 1, 0)
+    (1, 0, 0)
+    (1, 1, 0)
+    (2, 0, 0)
+    (2, 1, 0)
+
+    """
+
+    def __init__(self, *shape):
+        if len(shape) == 1 and isinstance(shape[0], tuple):
+            shape = shape[0]
+        if min(shape, default=0) < 0:
+            raise ValueError("negative dimensions are not allowed")
+        self._iter = product(*map(range, shape))
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        """
+        Standard iterator method, updates the index and returns the index
+        tuple.
+
+        Returns
+        -------
+        val : tuple of ints
+            Returns a tuple containing the indices of the current
+            iteration.
+
+        """
+        return next(self._iter)
+
+
+# You can do all this with slice() plus a few special objects,
+# but there's a lot to remember. This version is simpler because
+# it uses the standard array indexing syntax.
+#
+# Written by Konrad Hinsen <hinsen@cnrs-orleans.fr>
+# last revision: 1999-7-23
+#
+# Cosmetic changes by T. Oliphant 2001
+#
+#
+
+class IndexExpression:
+    """
+    A nicer way to build up index tuples for arrays.
+
+    .. note::
+       Use one of the two predefined instances ``index_exp`` or `s_`
+       rather than directly using `IndexExpression`.
+
+    For any index combination, including slicing and axis insertion,
+    ``a[indices]`` is the same as ``a[np.index_exp[indices]]`` for any
+    array `a`. However, ``np.index_exp[indices]`` can be used anywhere
+    in Python code and returns a tuple of slice objects that can be
+    used in the construction of complex index expressions.
+
+    Parameters
+    ----------
+    maketuple : bool
+        If True, always returns a tuple.
+
+    See Also
+    --------
+    s_ : Predefined instance without tuple conversion:
+       `s_ = IndexExpression(maketuple=False)`.
+       The ``index_exp`` is another predefined instance that
+       always returns a tuple:
+       `index_exp = IndexExpression(maketuple=True)`.
+
+    Notes
+    -----
+    You can do all this with :class:`slice` plus a few special objects,
+    but there's a lot to remember and this version is simpler because
+    it uses the standard array indexing syntax.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.s_[2::2]
+    slice(2, None, 2)
+    >>> np.index_exp[2::2]
+    (slice(2, None, 2),)
+
+    >>> np.array([0, 1, 2, 3, 4])[np.s_[2::2]]
+    array([2, 4])
+
+    """
+    __slots__ = ('maketuple',)
+
+    def __init__(self, maketuple):
+        self.maketuple = maketuple
+
+    def __getitem__(self, item):
+        if self.maketuple and not isinstance(item, tuple):
+            return (item,)
+        else:
+            return item
+
+
+index_exp = IndexExpression(maketuple=True)
+s_ = IndexExpression(maketuple=False)
+
+# End contribution from Konrad.
+
+
+# The following functions complement those in twodim_base, but are
+# applicable to N-dimensions.
+
+
+def _fill_diagonal_dispatcher(a, val, wrap=None):
+    return (a,)
+
+
+@array_function_dispatch(_fill_diagonal_dispatcher)
+def fill_diagonal(a, val, wrap=False):
+    """Fill the main diagonal of the given array of any dimensionality.
+
+    For an array `a` with ``a.ndim >= 2``, the diagonal is the list of
+    values ``a[i, ..., i]`` with indices ``i`` all identical.  This function
+    modifies the input array in-place without returning a value.
+
+    Parameters
+    ----------
+    a : array, at least 2-D.
+      Array whose diagonal is to be filled in-place.
+    val : scalar or array_like
+      Value(s) to write on the diagonal. If `val` is scalar, the value is
+      written along the diagonal. If array-like, the flattened `val` is
+      written along the diagonal, repeating if necessary to fill all
+      diagonal entries.
+
+    wrap : bool
+      For tall matrices in NumPy version up to 1.6.2, the
+      diagonal "wrapped" after N columns. You can have this behavior
+      with this option. This affects only tall matrices.
+
+    See also
+    --------
+    diag_indices, diag_indices_from
+
+    Notes
+    -----
+    This functionality can be obtained via `diag_indices`, but internally
+    this version uses a much faster implementation that never constructs the
+    indices and uses simple slicing.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.zeros((3, 3), int)
+    >>> np.fill_diagonal(a, 5)
+    >>> a
+    array([[5, 0, 0],
+           [0, 5, 0],
+           [0, 0, 5]])
+
+    The same function can operate on a 4-D array:
+
+    >>> a = np.zeros((3, 3, 3, 3), int)
+    >>> np.fill_diagonal(a, 4)
+
+    We only show a few blocks for clarity:
+
+    >>> a[0, 0]
+    array([[4, 0, 0],
+           [0, 0, 0],
+           [0, 0, 0]])
+    >>> a[1, 1]
+    array([[0, 0, 0],
+           [0, 4, 0],
+           [0, 0, 0]])
+    >>> a[2, 2]
+    array([[0, 0, 0],
+           [0, 0, 0],
+           [0, 0, 4]])
+
+    The wrap option affects only tall matrices:
+
+    >>> # tall matrices no wrap
+    >>> a = np.zeros((5, 3), int)
+    >>> np.fill_diagonal(a, 4)
+    >>> a
+    array([[4, 0, 0],
+           [0, 4, 0],
+           [0, 0, 4],
+           [0, 0, 0],
+           [0, 0, 0]])
+
+    >>> # tall matrices wrap
+    >>> a = np.zeros((5, 3), int)
+    >>> np.fill_diagonal(a, 4, wrap=True)
+    >>> a
+    array([[4, 0, 0],
+           [0, 4, 0],
+           [0, 0, 4],
+           [0, 0, 0],
+           [4, 0, 0]])
+
+    >>> # wide matrices
+    >>> a = np.zeros((3, 5), int)
+    >>> np.fill_diagonal(a, 4, wrap=True)
+    >>> a
+    array([[4, 0, 0, 0, 0],
+           [0, 4, 0, 0, 0],
+           [0, 0, 4, 0, 0]])
+
+    The anti-diagonal can be filled by reversing the order of elements
+    using either `numpy.flipud` or `numpy.fliplr`.
+
+    >>> a = np.zeros((3, 3), int);
+    >>> np.fill_diagonal(np.fliplr(a), [1,2,3])  # Horizontal flip
+    >>> a
+    array([[0, 0, 1],
+           [0, 2, 0],
+           [3, 0, 0]])
+    >>> np.fill_diagonal(np.flipud(a), [1,2,3])  # Vertical flip
+    >>> a
+    array([[0, 0, 3],
+           [0, 2, 0],
+           [1, 0, 0]])
+
+    Note that the order in which the diagonal is filled varies depending
+    on the flip function.
+    """
+    if a.ndim < 2:
+        raise ValueError("array must be at least 2-d")
+    end = None
+    if a.ndim == 2:
+        # Explicit, fast formula for the common case.  For 2-d arrays, we
+        # accept rectangular ones.
+        step = a.shape[1] + 1
+        # This is needed to don't have tall matrix have the diagonal wrap.
+        if not wrap:
+            end = a.shape[1] * a.shape[1]
+    else:
+        # For more than d=2, the strided formula is only valid for arrays with
+        # all dimensions equal, so we check first.
+        if not np.all(diff(a.shape) == 0):
+            raise ValueError("All dimensions of input must be of equal length")
+        step = 1 + (np.cumprod(a.shape[:-1])).sum()
+
+    # Write the value out into the diagonal.
+    a.flat[:end:step] = val
+
+
+@set_module('numpy')
+def diag_indices(n, ndim=2):
+    """
+    Return the indices to access the main diagonal of an array.
+
+    This returns a tuple of indices that can be used to access the main
+    diagonal of an array `a` with ``a.ndim >= 2`` dimensions and shape
+    (n, n, ..., n). For ``a.ndim = 2`` this is the usual diagonal, for
+    ``a.ndim > 2`` this is the set of indices to access ``a[i, i, ..., i]``
+    for ``i = [0..n-1]``.
+
+    Parameters
+    ----------
+    n : int
+      The size, along each dimension, of the arrays for which the returned
+      indices can be used.
+
+    ndim : int, optional
+      The number of dimensions.
+
+    See Also
+    --------
+    diag_indices_from
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create a set of indices to access the diagonal of a (4, 4) array:
+
+    >>> di = np.diag_indices(4)
+    >>> di
+    (array([0, 1, 2, 3]), array([0, 1, 2, 3]))
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+    >>> a[di] = 100
+    >>> a
+    array([[100,   1,   2,   3],
+           [  4, 100,   6,   7],
+           [  8,   9, 100,  11],
+           [ 12,  13,  14, 100]])
+
+    Now, we create indices to manipulate a 3-D array:
+
+    >>> d3 = np.diag_indices(2, 3)
+    >>> d3
+    (array([0, 1]), array([0, 1]), array([0, 1]))
+
+    And use it to set the diagonal of an array of zeros to 1:
+
+    >>> a = np.zeros((2, 2, 2), dtype=int)
+    >>> a[d3] = 1
+    >>> a
+    array([[[1, 0],
+            [0, 0]],
+           [[0, 0],
+            [0, 1]]])
+
+    """
+    idx = np.arange(n)
+    return (idx,) * ndim
+
+
+def _diag_indices_from(arr):
+    return (arr,)
+
+
+@array_function_dispatch(_diag_indices_from)
+def diag_indices_from(arr):
+    """
+    Return the indices to access the main diagonal of an n-dimensional array.
+
+    See `diag_indices` for full details.
+
+    Parameters
+    ----------
+    arr : array, at least 2-D
+
+    See Also
+    --------
+    diag_indices
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create a 4 by 4 array.
+
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+
+    Get the indices of the diagonal elements.
+
+    >>> di = np.diag_indices_from(a)
+    >>> di
+    (array([0, 1, 2, 3]), array([0, 1, 2, 3]))
+
+    >>> a[di]
+    array([ 0,  5, 10, 15])
+
+    This is simply syntactic sugar for diag_indices.
+
+    >>> np.diag_indices(a.shape[0])
+    (array([0, 1, 2, 3]), array([0, 1, 2, 3]))
+
+    """
+
+    if not arr.ndim >= 2:
+        raise ValueError("input array must be at least 2-d")
+    # For more than d=2, the strided formula is only valid for arrays with
+    # all dimensions equal, so we check first.
+    if not np.all(diff(arr.shape) == 0):
+        raise ValueError("All dimensions of input must be of equal length")
+
+    return diag_indices(arr.shape[0], arr.ndim)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..34d92476870616b33e2710ca032e7304484fedf9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_index_tricks_impl.pyi
@@ -0,0 +1,267 @@
+from _typeshed import Incomplete, SupportsLenAndGetItem
+from collections.abc import Sequence
+from typing import (
+    Any,
+    ClassVar,
+    Final,
+    Generic,
+    Literal as L,
+    Self,
+    SupportsIndex,
+    final,
+    overload,
+)
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy import _CastingKind
+from numpy._core.multiarray import ravel_multi_index, unravel_index
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _AnyShape,
+    _ArrayLike,
+    _DTypeLike,
+    _FiniteNestedSequence,
+    _HasDType,
+    _NestedSequence,
+    _SupportsArray,
+)
+
+__all__ = [  # noqa: RUF022
+    "ravel_multi_index",
+    "unravel_index",
+    "mgrid",
+    "ogrid",
+    "r_",
+    "c_",
+    "s_",
+    "index_exp",
+    "ix_",
+    "ndenumerate",
+    "ndindex",
+    "fill_diagonal",
+    "diag_indices",
+    "diag_indices_from",
+]
+
+###
+
+_T = TypeVar("_T")
+_TupleT = TypeVar("_TupleT", bound=tuple[Any, ...])
+_ArrayT = TypeVar("_ArrayT", bound=NDArray[Any])
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, default=Any, covariant=True)
+_BoolT_co = TypeVar("_BoolT_co", bound=bool, default=bool, covariant=True)
+
+_AxisT_co = TypeVar("_AxisT_co", bound=int, default=L[0], covariant=True)
+_MatrixT_co = TypeVar("_MatrixT_co", bound=bool, default=L[False], covariant=True)
+_NDMinT_co = TypeVar("_NDMinT_co", bound=int, default=L[1], covariant=True)
+_Trans1DT_co = TypeVar("_Trans1DT_co", bound=int, default=L[-1], covariant=True)
+
+###
+
+class ndenumerate(Generic[_ScalarT_co]):
+    @overload
+    def __init__(self: ndenumerate[_ScalarT], arr: _FiniteNestedSequence[_SupportsArray[np.dtype[_ScalarT]]]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.str_], arr: str | _NestedSequence[str]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.bytes_], arr: bytes | _NestedSequence[bytes]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.bool], arr: bool | _NestedSequence[bool]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.intp], arr: int | _NestedSequence[int]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.float64], arr: float | _NestedSequence[float]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[np.complex128], arr: complex | _NestedSequence[complex]) -> None: ...
+    @overload
+    def __init__(self: ndenumerate[Incomplete], arr: object) -> None: ...
+
+    # The first overload is a (semi-)workaround for a mypy bug (tested with v1.10 and v1.11)
+    @overload
+    def __next__(
+        self: ndenumerate[np.bool | np.number | np.flexible | np.datetime64 | np.timedelta64],
+        /,
+    ) -> tuple[_AnyShape, _ScalarT_co]: ...
+    @overload
+    def __next__(self: ndenumerate[np.object_], /) -> tuple[_AnyShape, Incomplete]: ...
+    @overload
+    def __next__(self, /) -> tuple[_AnyShape, _ScalarT_co]: ...
+
+    #
+    def __iter__(self) -> Self: ...
+
+class ndindex:
+    @overload
+    def __init__(self, shape: tuple[SupportsIndex, ...], /) -> None: ...
+    @overload
+    def __init__(self, /, *shape: SupportsIndex) -> None: ...
+
+    #
+    def __iter__(self) -> Self: ...
+    def __next__(self) -> _AnyShape: ...
+
+class nd_grid(Generic[_BoolT_co]):
+    __slots__ = ("sparse",)
+
+    sparse: _BoolT_co
+    def __init__(self, sparse: _BoolT_co = ...) -> None: ...  # stubdefaulter: ignore[missing-default]
+    @overload
+    def __getitem__(self: nd_grid[L[False]], key: slice | Sequence[slice]) -> NDArray[Incomplete]: ...
+    @overload
+    def __getitem__(self: nd_grid[L[True]], key: slice | Sequence[slice]) -> tuple[NDArray[Incomplete], ...]: ...
+
+@final
+class MGridClass(nd_grid[L[False]]):
+    __slots__ = ()
+
+    def __init__(self) -> None: ...
+
+@final
+class OGridClass(nd_grid[L[True]]):
+    __slots__ = ()
+
+    def __init__(self) -> None: ...
+
+class AxisConcatenator(Generic[_AxisT_co, _MatrixT_co, _NDMinT_co, _Trans1DT_co]):
+    __slots__ = "axis", "matrix", "ndmin", "trans1d"
+
+    makemat: ClassVar[type[np.matrix[tuple[int, int], np.dtype]]]
+
+    axis: _AxisT_co
+    matrix: _MatrixT_co
+    ndmin: _NDMinT_co
+    trans1d: _Trans1DT_co
+
+    # NOTE: mypy does not understand that these default values are the same as the
+    # TypeVar defaults. Since the workaround would require us to write 16 overloads,
+    # we ignore the assignment type errors here.
+    def __init__(
+        self,
+        /,
+        axis: _AxisT_co = 0,  # type: ignore[assignment]
+        matrix: _MatrixT_co = False,  # type: ignore[assignment]
+        ndmin: _NDMinT_co = 1,  # type: ignore[assignment]
+        trans1d: _Trans1DT_co = -1,  # type: ignore[assignment]
+    ) -> None: ...
+
+    # TODO(jorenham): annotate this
+    def __getitem__(self, key: Incomplete, /) -> Incomplete: ...
+    def __len__(self, /) -> L[0]: ...
+
+    # Keep in sync with _core.multiarray.concatenate
+    @staticmethod
+    @overload
+    def concatenate(
+        arrays: _ArrayLike[_ScalarT],
+        /,
+        axis: SupportsIndex | None = 0,
+        out: None = None,
+        *,
+        dtype: None = None,
+        casting: _CastingKind | None = "same_kind",
+    ) -> NDArray[_ScalarT]: ...
+    @staticmethod
+    @overload
+    def concatenate(
+        arrays: SupportsLenAndGetItem[ArrayLike],
+        /,
+        axis: SupportsIndex | None = 0,
+        out: None = None,
+        *,
+        dtype: _DTypeLike[_ScalarT],
+        casting: _CastingKind | None = "same_kind",
+    ) -> NDArray[_ScalarT]: ...
+    @staticmethod
+    @overload
+    def concatenate(
+        arrays: SupportsLenAndGetItem[ArrayLike],
+        /,
+        axis: SupportsIndex | None = 0,
+        out: None = None,
+        *,
+        dtype: DTypeLike | None = None,
+        casting: _CastingKind | None = "same_kind",
+    ) -> NDArray[Incomplete]: ...
+    @staticmethod
+    @overload
+    def concatenate(
+        arrays: SupportsLenAndGetItem[ArrayLike],
+        /,
+        axis: SupportsIndex | None = 0,
+        *,
+        out: _ArrayT,
+        dtype: DTypeLike | None = None,
+        casting: _CastingKind | None = "same_kind",
+    ) -> _ArrayT: ...
+    @staticmethod
+    @overload
+    def concatenate(
+        arrays: SupportsLenAndGetItem[ArrayLike],
+        /,
+        axis: SupportsIndex | None,
+        out: _ArrayT,
+        *,
+        dtype: DTypeLike | None = None,
+        casting: _CastingKind | None = "same_kind",
+    ) -> _ArrayT: ...
+
+@final
+class RClass(AxisConcatenator[L[0], L[False], L[1], L[-1]]):
+    __slots__ = ()
+
+    def __init__(self, /) -> None: ...
+
+@final
+class CClass(AxisConcatenator[L[-1], L[False], L[2], L[0]]):
+    __slots__ = ()
+
+    def __init__(self, /) -> None: ...
+
+class IndexExpression(Generic[_BoolT_co]):
+    __slots__ = ("maketuple",)
+
+    maketuple: _BoolT_co
+    def __init__(self, maketuple: _BoolT_co) -> None: ...
+    @overload
+    def __getitem__(self, item: _TupleT) -> _TupleT: ...
+    @overload
+    def __getitem__(self: IndexExpression[L[True]], item: _T) -> tuple[_T]: ...
+    @overload
+    def __getitem__(self: IndexExpression[L[False]], item: _T) -> _T: ...
+
+@overload
+def ix_(*args: _FiniteNestedSequence[_HasDType[_DTypeT]]) -> tuple[np.ndarray[_AnyShape, _DTypeT], ...]: ...
+@overload
+def ix_(*args: str | _NestedSequence[str]) -> tuple[NDArray[np.str_], ...]: ...
+@overload
+def ix_(*args: bytes | _NestedSequence[bytes]) -> tuple[NDArray[np.bytes_], ...]: ...
+@overload
+def ix_(*args: bool | _NestedSequence[bool]) -> tuple[NDArray[np.bool], ...]: ...
+@overload
+def ix_(*args: int | _NestedSequence[int]) -> tuple[NDArray[np.intp], ...]: ...
+@overload
+def ix_(*args: float | _NestedSequence[float]) -> tuple[NDArray[np.float64], ...]: ...
+@overload
+def ix_(*args: complex | _NestedSequence[complex]) -> tuple[NDArray[np.complex128], ...]: ...
+
+#
+def fill_diagonal(a: NDArray[Any], val: object, wrap: bool = False) -> None: ...
+
+#
+def diag_indices(n: int, ndim: int = 2) -> tuple[NDArray[np.intp], ...]: ...
+def diag_indices_from(arr: ArrayLike) -> tuple[NDArray[np.intp], ...]: ...
+
+#
+mgrid: Final[MGridClass] = ...
+ogrid: Final[OGridClass] = ...
+
+r_: Final[RClass] = ...
+c_: Final[CClass] = ...
+
+index_exp: Final[IndexExpression[L[True]]] = ...
+s_: Final[IndexExpression[L[False]]] = ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_iotools.py b/python/user_packages/Python313/site-packages/numpy/lib/_iotools.py
new file mode 100644
index 0000000000000000000000000000000000000000..5f41996bb79b160d9221eeab23fa9666916b60e5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_iotools.py
@@ -0,0 +1,900 @@
+"""A collection of functions designed to help I/O with ascii files.
+
+"""
+__docformat__ = "restructuredtext en"
+
+import itertools
+
+import numpy as np
+import numpy._core.numeric as nx
+from numpy._utils import asbytes, asunicode
+
+
+def _decode_line(line, encoding=None):
+    """Decode bytes from binary input streams.
+
+    Defaults to decoding from 'latin1'.
+
+    Parameters
+    ----------
+    line : str or bytes
+         Line to be decoded.
+    encoding : str
+         Encoding used to decode `line`.
+
+    Returns
+    -------
+    decoded_line : str
+
+    """
+    if type(line) is bytes:
+        if encoding is None:
+            encoding = "latin1"
+        line = line.decode(encoding)
+
+    return line
+
+
+def _is_string_like(obj):
+    """
+    Check whether obj behaves like a string.
+    """
+    try:
+        obj + ''
+    except (TypeError, ValueError):
+        return False
+    return True
+
+
+def _is_bytes_like(obj):
+    """
+    Check whether obj behaves like a bytes object.
+    """
+    try:
+        obj + b''
+    except (TypeError, ValueError):
+        return False
+    return True
+
+
+def has_nested_fields(ndtype):
+    """
+    Returns whether one or several fields of a dtype are nested.
+
+    Parameters
+    ----------
+    ndtype : dtype
+        Data-type of a structured array.
+
+    Raises
+    ------
+    AttributeError
+        If `ndtype` does not have a `names` attribute.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float)])
+    >>> np.lib._iotools.has_nested_fields(dt)
+    False
+
+    """
+    return any(ndtype[name].names is not None for name in ndtype.names or ())
+
+
+def flatten_dtype(ndtype, flatten_base=False):
+    """
+    Unpack a structured data-type by collapsing nested fields and/or fields
+    with a shape.
+
+    Note that the field names are lost.
+
+    Parameters
+    ----------
+    ndtype : dtype
+        The datatype to collapse
+    flatten_base : bool, optional
+       If True, transform a field with a shape into several fields. Default is
+       False.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
+    ...                ('block', int, (2, 3))])
+    >>> np.lib._iotools.flatten_dtype(dt)
+    [dtype('S4'), dtype('float64'), dtype('float64'), dtype('int64')]
+    >>> np.lib._iotools.flatten_dtype(dt, flatten_base=True)
+    [dtype('S4'),
+     dtype('float64'),
+     dtype('float64'),
+     dtype('int64'),
+     dtype('int64'),
+     dtype('int64'),
+     dtype('int64'),
+     dtype('int64'),
+     dtype('int64')]
+
+    """
+    names = ndtype.names
+    if names is None:
+        if flatten_base:
+            return [ndtype.base] * int(np.prod(ndtype.shape))
+        return [ndtype.base]
+    else:
+        types = []
+        for field in names:
+            info = ndtype.fields[field]
+            flat_dt = flatten_dtype(info[0], flatten_base)
+            types.extend(flat_dt)
+        return types
+
+
+class LineSplitter:
+    """
+    Object to split a string at a given delimiter or at given places.
+
+    Parameters
+    ----------
+    delimiter : str, int, or sequence of ints, optional
+        If a string, character used to delimit consecutive fields.
+        If an integer or a sequence of integers, width(s) of each field.
+    comments : str, optional
+        Character used to mark the beginning of a comment. Default is '#'.
+    autostrip : bool, optional
+        Whether to strip each individual field. Default is True.
+
+    """
+
+    def autostrip(self, method):
+        """
+        Wrapper to strip each member of the output of `method`.
+
+        Parameters
+        ----------
+        method : function
+            Function that takes a single argument and returns a sequence of
+            strings.
+
+        Returns
+        -------
+        wrapped : function
+            The result of wrapping `method`. `wrapped` takes a single input
+            argument and returns a list of strings that are stripped of
+            white-space.
+
+        """
+        return lambda input: [_.strip() for _ in method(input)]
+
+    def __init__(self, delimiter=None, comments='#', autostrip=True,
+                 encoding=None):
+        delimiter = _decode_line(delimiter)
+        comments = _decode_line(comments)
+
+        self.comments = comments
+
+        # Delimiter is a character
+        if (delimiter is None) or isinstance(delimiter, str):
+            delimiter = delimiter or None
+            _handyman = self._delimited_splitter
+        # Delimiter is a list of field widths
+        elif hasattr(delimiter, '__iter__'):
+            _handyman = self._variablewidth_splitter
+            idx = np.cumsum([0] + list(delimiter))
+            delimiter = [slice(i, j) for (i, j) in itertools.pairwise(idx)]
+        # Delimiter is a single integer
+        elif int(delimiter):
+            (_handyman, delimiter) = (
+                    self._fixedwidth_splitter, int(delimiter))
+        else:
+            (_handyman, delimiter) = (self._delimited_splitter, None)
+        self.delimiter = delimiter
+        if autostrip:
+            self._handyman = self.autostrip(_handyman)
+        else:
+            self._handyman = _handyman
+        self.encoding = encoding
+
+    def _delimited_splitter(self, line):
+        """Chop off comments, strip, and split at delimiter. """
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
+        line = line.strip(" \r\n")
+        if not line:
+            return []
+        return line.split(self.delimiter)
+
+    def _fixedwidth_splitter(self, line):
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
+        line = line.strip("\r\n")
+        if not line:
+            return []
+        fixed = self.delimiter
+        slices = [slice(i, i + fixed) for i in range(0, len(line), fixed)]
+        return [line[s] for s in slices]
+
+    def _variablewidth_splitter(self, line):
+        if self.comments is not None:
+            line = line.split(self.comments)[0]
+        if not line:
+            return []
+        slices = self.delimiter
+        return [line[s] for s in slices]
+
+    def __call__(self, line):
+        return self._handyman(_decode_line(line, self.encoding))
+
+
+class NameValidator:
+    """
+    Object to validate a list of strings to use as field names.
+
+    The strings are stripped of any non alphanumeric character, and spaces
+    are replaced by '_'. During instantiation, the user can define a list
+    of names to exclude, as well as a list of invalid characters. Names in
+    the exclusion list are appended a '_' character.
+
+    Once an instance has been created, it can be called with a list of
+    names, and a list of valid names will be created.  The `__call__`
+    method accepts an optional keyword "default" that sets the default name
+    in case of ambiguity. By default this is 'f', so that names will
+    default to `f0`, `f1`, etc.
+
+    Parameters
+    ----------
+    excludelist : sequence, optional
+        A list of names to exclude. This list is appended to the default
+        list ['return', 'file', 'print']. Excluded names are appended an
+        underscore: for example, `file` becomes `file_` if supplied.
+    deletechars : str, optional
+        A string combining invalid characters that must be deleted from the
+        names.
+    case_sensitive : {True, False, 'upper', 'lower'}, optional
+        * If True, field names are case-sensitive.
+        * If False or 'upper', field names are converted to upper case.
+        * If 'lower', field names are converted to lower case.
+
+        The default value is True.
+    replace_space : '_', optional
+        Character(s) used in replacement of white spaces.
+
+    Notes
+    -----
+    Calling an instance of `NameValidator` is the same as calling its
+    method `validate`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> validator = np.lib._iotools.NameValidator()
+    >>> validator(['file', 'field2', 'with space', 'CaSe'])
+    ('file_', 'field2', 'with_space', 'CaSe')
+
+    >>> validator = np.lib._iotools.NameValidator(excludelist=['excl'],
+    ...                                           deletechars='q',
+    ...                                           case_sensitive=False)
+    >>> validator(['excl', 'field2', 'no_q', 'with space', 'CaSe'])
+    ('EXCL', 'FIELD2', 'NO_Q', 'WITH_SPACE', 'CASE')
+
+    """
+
+    defaultexcludelist = 'return', 'file', 'print'
+    defaultdeletechars = frozenset(r"""~!@#$%^&*()-=+~\|]}[{';: /?.>,<""")
+
+    def __init__(self, excludelist=None, deletechars=None,
+                 case_sensitive=None, replace_space='_'):
+        # Process the exclusion list ..
+        if excludelist is None:
+            excludelist = []
+        excludelist.extend(self.defaultexcludelist)
+        self.excludelist = excludelist
+        # Process the list of characters to delete
+        if deletechars is None:
+            delete = set(self.defaultdeletechars)
+        else:
+            delete = set(deletechars)
+        delete.add('"')
+        self.deletechars = delete
+        # Process the case option .....
+        if (case_sensitive is None) or (case_sensitive is True):
+            self.case_converter = lambda x: x
+        elif (case_sensitive is False) or case_sensitive.startswith('u'):
+            self.case_converter = lambda x: x.upper()
+        elif case_sensitive.startswith('l'):
+            self.case_converter = lambda x: x.lower()
+        else:
+            msg = f'unrecognized case_sensitive value {case_sensitive}.'
+            raise ValueError(msg)
+
+        self.replace_space = replace_space
+
+    def validate(self, names, defaultfmt="f%i", nbfields=None):
+        """
+        Validate a list of strings as field names for a structured array.
+
+        Parameters
+        ----------
+        names : sequence of str
+            Strings to be validated.
+        defaultfmt : str, optional
+            Default format string, used if validating a given string
+            reduces its length to zero.
+        nbfields : integer, optional
+            Final number of validated names, used to expand or shrink the
+            initial list of names.
+
+        Returns
+        -------
+        validatednames : list of str
+            The list of validated field names.
+
+        Notes
+        -----
+        A `NameValidator` instance can be called directly, which is the
+        same as calling `validate`. For examples, see `NameValidator`.
+
+        """
+        # Initial checks ..............
+        if (names is None):
+            if (nbfields is None):
+                return None
+            names = []
+        if isinstance(names, str):
+            names = [names, ]
+        if nbfields is not None:
+            nbnames = len(names)
+            if (nbnames < nbfields):
+                names = list(names) + [''] * (nbfields - nbnames)
+            elif (nbnames > nbfields):
+                names = names[:nbfields]
+        # Set some shortcuts ...........
+        deletechars = self.deletechars
+        excludelist = self.excludelist
+        case_converter = self.case_converter
+        replace_space = self.replace_space
+        # Initializes some variables ...
+        validatednames = []
+        seen = {}
+        nbempty = 0
+
+        for item in names:
+            item = case_converter(item).strip()
+            if replace_space:
+                item = item.replace(' ', replace_space)
+            item = ''.join([c for c in item if c not in deletechars])
+            if item == '':
+                item = defaultfmt % nbempty
+                while item in names:
+                    nbempty += 1
+                    item = defaultfmt % nbempty
+                nbempty += 1
+            elif item in excludelist:
+                item += '_'
+            cnt = seen.get(item, 0)
+            if cnt > 0:
+                validatednames.append(item + '_%d' % cnt)
+            else:
+                validatednames.append(item)
+            seen[item] = cnt + 1
+        return tuple(validatednames)
+
+    def __call__(self, names, defaultfmt="f%i", nbfields=None):
+        return self.validate(names, defaultfmt=defaultfmt, nbfields=nbfields)
+
+
+def str2bool(value):
+    """
+    Tries to transform a string supposed to represent a boolean to a boolean.
+
+    Parameters
+    ----------
+    value : str
+        The string that is transformed to a boolean.
+
+    Returns
+    -------
+    boolval : bool
+        The boolean representation of `value`.
+
+    Raises
+    ------
+    ValueError
+        If the string is not 'True' or 'False' (case independent)
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.lib._iotools.str2bool('TRUE')
+    True
+    >>> np.lib._iotools.str2bool('false')
+    False
+
+    """
+    value = value.upper()
+    if value == 'TRUE':
+        return True
+    elif value == 'FALSE':
+        return False
+    else:
+        raise ValueError("Invalid boolean")
+
+
+class ConverterError(Exception):
+    """
+    Exception raised when an error occurs in a converter for string values.
+
+    """
+    pass
+
+
+class ConverterLockError(ConverterError):
+    """
+    Exception raised when an attempt is made to upgrade a locked converter.
+
+    """
+    pass
+
+
+class ConversionWarning(UserWarning):
+    """
+    Warning issued when a string converter has a problem.
+
+    Notes
+    -----
+    In `genfromtxt` a `ConversionWarning` is issued if raising exceptions
+    is explicitly suppressed with the "invalid_raise" keyword.
+
+    """
+    pass
+
+
+class StringConverter:
+    """
+    Factory class for function transforming a string into another object
+    (int, float).
+
+    After initialization, an instance can be called to transform a string
+    into another object. If the string is recognized as representing a
+    missing value, a default value is returned.
+
+    Attributes
+    ----------
+    func : function
+        Function used for the conversion.
+    default : any
+        Default value to return when the input corresponds to a missing
+        value.
+    type : type
+        Type of the output.
+    _status : int
+        Integer representing the order of the conversion.
+    _mapper : sequence of tuples
+        Sequence of tuples (dtype, function, default value) to evaluate in
+        order.
+    _locked : bool
+        Holds `locked` parameter.
+
+    Parameters
+    ----------
+    dtype_or_func : {None, dtype, function}, optional
+        If a `dtype`, specifies the input data type, used to define a basic
+        function and a default value for missing data. For example, when
+        `dtype` is float, the `func` attribute is set to `float` and the
+        default value to `np.nan`.  If a function, this function is used to
+        convert a string to another object. In this case, it is recommended
+        to give an associated default value as input.
+    default : any, optional
+        Value to return by default, that is, when the string to be
+        converted is flagged as missing. If not given, `StringConverter`
+        tries to supply a reasonable default value.
+    missing_values : {None, sequence of str}, optional
+        ``None`` or sequence of strings indicating a missing value. If ``None``
+        then missing values are indicated by empty entries. The default is
+        ``None``.
+    locked : bool, optional
+        Whether the StringConverter should be locked to prevent automatic
+        upgrade or not. Default is False.
+
+    """
+    _mapper = [(nx.bool, str2bool, False),
+               (nx.int_, int, -1),]
+
+    # On 32-bit systems, we need to make sure that we explicitly include
+    # nx.int64 since ns.int_ is nx.int32.
+    if nx.dtype(nx.int_).itemsize < nx.dtype(nx.int64).itemsize:
+        _mapper.append((nx.int64, int, -1))
+
+    _mapper.extend([(nx.float64, float, nx.nan),
+                    (nx.complex128, complex, nx.nan + 0j),
+                    (nx.longdouble, nx.longdouble, nx.nan),
+                    # If a non-default dtype is passed, fall back to generic
+                    # ones (should only be used for the converter)
+                    (nx.integer, int, -1),
+                    (nx.floating, float, nx.nan),
+                    (nx.complexfloating, complex, nx.nan + 0j),
+                    # Last, try with the string types (must be last, because
+                    # `_mapper[-1]` is used as default in some cases)
+                    (nx.str_, asunicode, '???'),
+                    (nx.bytes_, asbytes, '???'),
+                    ])
+
+    @classmethod
+    def _getdtype(cls, val):
+        """Returns the dtype of the input variable."""
+        return np.array(val).dtype
+
+    @classmethod
+    def _getsubdtype(cls, val):
+        """Returns the type of the dtype of the input variable."""
+        return np.array(val).dtype.type
+
+    @classmethod
+    def _dtypeortype(cls, dtype):
+        """Returns dtype for datetime64 and type of dtype otherwise."""
+
+        # This is a bit annoying. We want to return the "general" type in most
+        # cases (ie. "string" rather than "S10"), but we want to return the
+        # specific type for datetime64 (ie. "datetime64[us]" rather than
+        # "datetime64").
+        if dtype.type == np.datetime64:
+            return dtype
+        return dtype.type
+
+    @classmethod
+    def upgrade_mapper(cls, func, default=None):
+        """
+        Upgrade the mapper of a StringConverter by adding a new function and
+        its corresponding default.
+
+        The input function (or sequence of functions) and its associated
+        default value (if any) is inserted in penultimate position of the
+        mapper.  The corresponding type is estimated from the dtype of the
+        default value.
+
+        Parameters
+        ----------
+        func : var
+            Function, or sequence of functions
+
+        Examples
+        --------
+        >>> import dateutil.parser
+        >>> import datetime
+        >>> dateparser = dateutil.parser.parse
+        >>> defaultdate = datetime.date(2000, 1, 1)
+        >>> StringConverter.upgrade_mapper(dateparser, default=defaultdate)
+        """
+        # Func is a single functions
+        if callable(func):
+            cls._mapper.insert(-1, (cls._getsubdtype(default), func, default))
+            return
+        elif hasattr(func, '__iter__'):
+            if isinstance(func[0], (tuple, list)):
+                for _ in func:
+                    cls._mapper.insert(-1, _)
+                return
+            if default is None:
+                default = [None] * len(func)
+            else:
+                default = list(default)
+                default.append([None] * (len(func) - len(default)))
+            for fct, dft in zip(func, default):
+                cls._mapper.insert(-1, (cls._getsubdtype(dft), fct, dft))
+
+    @classmethod
+    def _find_map_entry(cls, dtype):
+        # if a converter for the specific dtype is available use that
+        for i, (deftype, func, default_def) in enumerate(cls._mapper):
+            if dtype.type == deftype:
+                return i, (deftype, func, default_def)
+
+        # otherwise find an inexact match
+        for i, (deftype, func, default_def) in enumerate(cls._mapper):
+            if np.issubdtype(dtype.type, deftype):
+                return i, (deftype, func, default_def)
+
+        raise LookupError
+
+    def __init__(self, dtype_or_func=None, default=None, missing_values=None,
+                 locked=False):
+        # Defines a lock for upgrade
+        self._locked = bool(locked)
+        # No input dtype: minimal initialization
+        if dtype_or_func is None:
+            self.func = str2bool
+            self._status = 0
+            self.default = default or False
+            dtype = np.dtype('bool')
+        else:
+            # Is the input a np.dtype ?
+            try:
+                self.func = None
+                dtype = np.dtype(dtype_or_func)
+            except TypeError:
+                # dtype_or_func must be a function, then
+                if not callable(dtype_or_func):
+                    errmsg = ("The input argument `dtype` is neither a"
+                              " function nor a dtype (got '%s' instead)")
+                    raise TypeError(errmsg % type(dtype_or_func))
+                # Set the function
+                self.func = dtype_or_func
+                # If we don't have a default, try to guess it or set it to
+                # None
+                if default is None:
+                    try:
+                        default = self.func('0')
+                    except ValueError:
+                        default = None
+                dtype = self._getdtype(default)
+
+            # find the best match in our mapper
+            try:
+                self._status, (_, func, default_def) = self._find_map_entry(dtype)
+            except LookupError:
+                # no match
+                self.default = default
+                _, func, _ = self._mapper[-1]
+                self._status = 0
+            else:
+                # use the found default only if we did not already have one
+                if default is None:
+                    self.default = default_def
+                else:
+                    self.default = default
+
+            # If the input was a dtype, set the function to the last we saw
+            if self.func is None:
+                self.func = func
+
+            # If the status is 1 (int), change the function to
+            # something more robust.
+            if self.func == self._mapper[1][1]:
+                if issubclass(dtype.type, np.uint64):
+                    self.func = np.uint64
+                elif issubclass(dtype.type, np.int64):
+                    self.func = np.int64
+                else:
+                    self.func = lambda x: int(float(x))
+        # Store the list of strings corresponding to missing values.
+        if missing_values is None:
+            self.missing_values = {''}
+        else:
+            if isinstance(missing_values, str):
+                missing_values = missing_values.split(",")
+            self.missing_values = set(list(missing_values) + [''])
+
+        self._callingfunction = self._strict_call
+        self.type = self._dtypeortype(dtype)
+        self._checked = False
+        self._initial_default = default
+
+    def _loose_call(self, value):
+        try:
+            return self.func(value)
+        except ValueError:
+            return self.default
+
+    def _strict_call(self, value):
+        try:
+
+            # We check if we can convert the value using the current function
+            new_value = self.func(value)
+
+            # In addition to having to check whether func can convert the
+            # value, we also have to make sure that we don't get overflow
+            # errors for integers.
+            if self.func is int:
+                try:
+                    np.array(value, dtype=self.type)
+                except OverflowError:
+                    raise ValueError
+
+            # We're still here so we can now return the new value
+            return new_value
+
+        except ValueError:
+            if value.strip() in self.missing_values:
+                if not self._status:
+                    self._checked = False
+                return self.default
+            raise ValueError(f"Cannot convert string '{value}'")
+
+    def __call__(self, value):
+        return self._callingfunction(value)
+
+    def _do_upgrade(self):
+        # Raise an exception if we locked the converter...
+        if self._locked:
+            errmsg = "Converter is locked and cannot be upgraded"
+            raise ConverterLockError(errmsg)
+        _statusmax = len(self._mapper)
+        # Complains if we try to upgrade by the maximum
+        _status = self._status
+        if _status == _statusmax:
+            errmsg = "Could not find a valid conversion function"
+            raise ConverterError(errmsg)
+        elif _status < _statusmax - 1:
+            _status += 1
+        self.type, self.func, default = self._mapper[_status]
+        self._status = _status
+        if self._initial_default is not None:
+            self.default = self._initial_default
+        else:
+            self.default = default
+
+    def upgrade(self, value):
+        """
+        Find the best converter for a given string, and return the result.
+
+        The supplied string `value` is converted by testing different
+        converters in order. First the `func` method of the
+        `StringConverter` instance is tried, if this fails other available
+        converters are tried.  The order in which these other converters
+        are tried is determined by the `_status` attribute of the instance.
+
+        Parameters
+        ----------
+        value : str
+            The string to convert.
+
+        Returns
+        -------
+        out : any
+            The result of converting `value` with the appropriate converter.
+
+        """
+        self._checked = True
+        try:
+            return self._strict_call(value)
+        except ValueError:
+            self._do_upgrade()
+            return self.upgrade(value)
+
+    def iterupgrade(self, value):
+        self._checked = True
+        if not hasattr(value, '__iter__'):
+            value = (value,)
+        _strict_call = self._strict_call
+        try:
+            for _m in value:
+                _strict_call(_m)
+        except ValueError:
+            self._do_upgrade()
+            self.iterupgrade(value)
+
+    def update(self, func, default=None, testing_value=None,
+               missing_values='', locked=False):
+        """
+        Set StringConverter attributes directly.
+
+        Parameters
+        ----------
+        func : function
+            Conversion function.
+        default : any, optional
+            Value to return by default, that is, when the string to be
+            converted is flagged as missing. If not given,
+            `StringConverter` tries to supply a reasonable default value.
+        testing_value : str, optional
+            A string representing a standard input value of the converter.
+            This string is used to help defining a reasonable default
+            value.
+        missing_values : {sequence of str, None}, optional
+            Sequence of strings indicating a missing value. If ``None``, then
+            the existing `missing_values` are cleared. The default is ``''``.
+        locked : bool, optional
+            Whether the StringConverter should be locked to prevent
+            automatic upgrade or not. Default is False.
+
+        Notes
+        -----
+        `update` takes the same parameters as the constructor of
+        `StringConverter`, except that `func` does not accept a `dtype`
+        whereas `dtype_or_func` in the constructor does.
+
+        """
+        self.func = func
+        self._locked = locked
+
+        # Don't reset the default to None if we can avoid it
+        if default is not None:
+            self.default = default
+            self.type = self._dtypeortype(self._getdtype(default))
+        else:
+            try:
+                tester = func(testing_value or '1')
+            except (TypeError, ValueError):
+                tester = None
+            self.type = self._dtypeortype(self._getdtype(tester))
+
+        # Add the missing values to the existing set or clear it.
+        if missing_values is None:
+            # Clear all missing values even though the ctor initializes it to
+            # set(['']) when the argument is None.
+            self.missing_values = set()
+        else:
+            if not np.iterable(missing_values):
+                missing_values = [missing_values]
+            if not all(isinstance(v, str) for v in missing_values):
+                raise TypeError("missing_values must be strings or unicode")
+            self.missing_values.update(missing_values)
+
+
+def easy_dtype(ndtype, names=None, defaultfmt="f%i", **validationargs):
+    """
+    Convenience function to create a `np.dtype` object.
+
+    The function processes the input `dtype` and matches it with the given
+    names.
+
+    Parameters
+    ----------
+    ndtype : var
+        Definition of the dtype. Can be any string or dictionary recognized
+        by the `np.dtype` function, or a sequence of types.
+    names : str or sequence, optional
+        Sequence of strings to use as field names for a structured dtype.
+        For convenience, `names` can be a string of a comma-separated list
+        of names.
+    defaultfmt : str, optional
+        Format string used to define missing names, such as ``"f%i"``
+        (default) or ``"fields_%02i"``.
+    validationargs : optional
+        A series of optional arguments used to initialize a
+        `NameValidator`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.lib._iotools.easy_dtype(float)
+    dtype('float64')
+    >>> np.lib._iotools.easy_dtype("i4, f8")
+    dtype([('f0', '<i4'), ('f1', '<f8')])
+    >>> np.lib._iotools.easy_dtype("i4, f8", defaultfmt="field_%03i")
+    dtype([('field_000', '<i4'), ('field_001', '<f8')])
+
+    >>> np.lib._iotools.easy_dtype((int, float, float), names="a,b,c")
+    dtype([('a', '<i8'), ('b', '<f8'), ('c', '<f8')])
+    >>> np.lib._iotools.easy_dtype(float, names="a,b,c")
+    dtype([('a', '<f8'), ('b', '<f8'), ('c', '<f8')])
+
+    """
+    try:
+        ndtype = np.dtype(ndtype)
+    except TypeError:
+        validate = NameValidator(**validationargs)
+        nbfields = len(ndtype)
+        if names is None:
+            names = [''] * len(ndtype)
+        elif isinstance(names, str):
+            names = names.split(",")
+        names = validate(names, nbfields=nbfields, defaultfmt=defaultfmt)
+        ndtype = np.dtype({"formats": ndtype, "names": names})
+    else:
+        # Explicit names
+        if names is not None:
+            validate = NameValidator(**validationargs)
+            if isinstance(names, str):
+                names = names.split(",")
+            # Simple dtype: repeat to match the nb of names
+            if ndtype.names is None:
+                formats = tuple([ndtype.type] * len(names))
+                names = validate(names, defaultfmt=defaultfmt)
+                ndtype = np.dtype(list(zip(names, formats)))
+            # Structured dtype: just validate the names as needed
+            else:
+                ndtype.names = validate(names, nbfields=len(ndtype.names),
+                                        defaultfmt=defaultfmt)
+        # No implicit names
+        elif ndtype.names is not None:
+            validate = NameValidator(**validationargs)
+            # Default initial names : should we change the format ?
+            numbered_names = tuple(f"f{i}" for i in range(len(ndtype.names)))
+            if ((ndtype.names == numbered_names) and (defaultfmt != "f%i")):
+                ndtype.names = validate([''] * len(ndtype.names),
+                                        defaultfmt=defaultfmt)
+            # Explicit initial names : just validate
+            else:
+                ndtype.names = validate(ndtype.names, defaultfmt=defaultfmt)
+    return ndtype
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_iotools.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_iotools.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..91d3d0f3a9e66b43b7e07d1e9711f81d2a3e3c6b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_iotools.pyi
@@ -0,0 +1,116 @@
+from collections.abc import Callable, Iterable, Sequence
+from typing import (
+    Any,
+    ClassVar,
+    Final,
+    Literal,
+    TypedDict,
+    TypeVar,
+    Unpack,
+    overload,
+    type_check_only,
+)
+
+import numpy as np
+import numpy.typing as npt
+from numpy._typing._dtype_like import _DTypeLikeNested
+
+_T = TypeVar("_T")
+
+@type_check_only
+class _NameValidatorKwargs(TypedDict, total=False):
+    excludelist: Iterable[str] | None
+    deletechars: Iterable[str] | None
+    case_sensitive: Literal["upper", "lower"] | bool | None
+    replace_space: str
+
+###
+
+__docformat__: Final = "restructuredtext en"
+
+class ConverterError(Exception): ...
+class ConverterLockError(ConverterError): ...
+class ConversionWarning(UserWarning): ...
+
+class LineSplitter:
+    delimiter: str | int | Iterable[int] | None
+    comments: str
+    encoding: str | None
+
+    def __init__(
+        self,
+        /,
+        delimiter: str | bytes | int | Iterable[int] | None = None,
+        comments: str | bytes = "#",
+        autostrip: bool = True,
+        encoding: str | None = None,
+    ) -> None: ...
+    def __call__(self, /, line: str | bytes) -> list[str]: ...
+    def autostrip(self, /, method: Callable[[_T], Iterable[str]]) -> Callable[[_T], list[str]]: ...
+
+class NameValidator:
+    defaultexcludelist: ClassVar[Sequence[str]] = ...
+    defaultdeletechars: ClassVar[frozenset[str]] = ...
+    excludelist: list[str]
+    deletechars: set[str]
+    case_converter: Callable[[str], str]
+    replace_space: str
+
+    def __init__(
+        self,
+        /,
+        excludelist: Iterable[str] | None = None,
+        deletechars: Iterable[str] | None = None,
+        case_sensitive: Literal["upper", "lower"] | bool | None = None,
+        replace_space: str = "_",
+    ) -> None: ...
+    def __call__(self, /, names: Iterable[str], defaultfmt: str = "f%i", nbfields: int | None = None) -> tuple[str, ...]: ...
+    def validate(self, /, names: Iterable[str], defaultfmt: str = "f%i", nbfields: int | None = None) -> tuple[str, ...]: ...
+
+class StringConverter:
+    func: Callable[[str], Any] | None
+    default: Any
+    missing_values: set[str]
+    type: np.dtype[np.datetime64] | np.generic
+
+    def __init__(
+        self,
+        /,
+        dtype_or_func: npt.DTypeLike | None = None,
+        default: None = None,
+        missing_values: Iterable[str] | None = None,
+        locked: bool = False,
+    ) -> None: ...
+    def update(
+        self,
+        /,
+        func: Callable[[str], Any],
+        default: object | None = None,
+        testing_value: str | None = None,
+        missing_values: str = "",
+        locked: bool = False,
+    ) -> None: ...
+    #
+    def __call__(self, /, value: str) -> Any: ...
+    def upgrade(self, /, value: str) -> Any: ...
+    def iterupgrade(self, /, value: Iterable[str] | str) -> None: ...
+
+    #
+    @classmethod
+    def upgrade_mapper(cls, func: Callable[[str], Any], default: object | None = None) -> None: ...
+
+def _decode_line(line: str | bytes, encoding: str | None = None) -> str: ...
+def _is_string_like(obj: object) -> bool: ...
+def _is_bytes_like(obj: object) -> bool: ...
+def has_nested_fields(ndtype: np.dtype[np.void]) -> bool: ...
+def flatten_dtype(ndtype: np.dtype[np.void], flatten_base: bool = False) -> type[np.dtype]: ...
+@overload
+def str2bool(value: Literal["false", "False", "FALSE"]) -> Literal[False]: ...
+@overload
+def str2bool(value: Literal["true", "True", "TRUE"]) -> Literal[True]: ...
+def easy_dtype(
+    ndtype: str | Sequence[_DTypeLikeNested],
+    names: str | Sequence[str] | None = None,
+    defaultfmt: str = "f%i",
+    **validationargs: Unpack[_NameValidatorKwargs],
+) -> np.dtype[np.void]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..b65e260bf9010408ca8d76ce5137e65145e6a87c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.py
@@ -0,0 +1,2006 @@
+"""
+Functions that ignore NaN.
+
+Functions
+---------
+
+- `nanmin` -- minimum non-NaN value
+- `nanmax` -- maximum non-NaN value
+- `nanargmin` -- index of minimum non-NaN value
+- `nanargmax` -- index of maximum non-NaN value
+- `nansum` -- sum of non-NaN values
+- `nanprod` -- product of non-NaN values
+- `nancumsum` -- cumulative sum of non-NaN values
+- `nancumprod` -- cumulative product of non-NaN values
+- `nanmean` -- mean of non-NaN values
+- `nanvar` -- variance of non-NaN values
+- `nanstd` -- standard deviation of non-NaN values
+- `nanmedian` -- median of non-NaN values
+- `nanquantile` -- qth quantile of non-NaN values
+- `nanpercentile` -- qth percentile of non-NaN values
+
+"""
+import functools
+import warnings
+
+import numpy as np
+import numpy._core.numeric as _nx
+from numpy._core import overrides
+from numpy.lib import _function_base_impl as fnb
+from numpy.lib._function_base_impl import _weights_are_valid
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+__all__ = [
+    'nansum', 'nanmax', 'nanmin', 'nanargmax', 'nanargmin', 'nanmean',
+    'nanmedian', 'nanpercentile', 'nanvar', 'nanstd', 'nanprod',
+    'nancumsum', 'nancumprod', 'nanquantile'
+    ]
+
+
+def _nan_mask(a, out=None):
+    """
+    Parameters
+    ----------
+    a : array-like
+        Input array with at least 1 dimension.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``; if provided, it must have the same shape as the
+        expected output and will prevent the allocation of a new array.
+
+    Returns
+    -------
+    y : bool ndarray or True
+        A bool array where ``np.nan`` positions are marked with ``False``
+        and other positions are marked with ``True``. If the type of ``a``
+        is such that it can't possibly contain ``np.nan``, returns ``True``.
+    """
+    # we assume that a is an array for this private function
+
+    if a.dtype.kind not in 'fc':
+        return True
+
+    y = np.isnan(a, out=out)
+    y = np.invert(y, out=y)
+    return y
+
+def _replace_nan(a, val):
+    """
+    If `a` is of inexact type, make a copy of `a`, replace NaNs with
+    the `val` value, and return the copy together with a boolean mask
+    marking the locations where NaNs were present. If `a` is not of
+    inexact type, do nothing and return `a` together with a mask of None.
+
+    Note that scalars will end up as array scalars, which is important
+    for using the result as the value of the out argument in some
+    operations.
+
+    Parameters
+    ----------
+    a : array-like
+        Input array.
+    val : float
+        NaN values are set to val before doing the operation.
+
+    Returns
+    -------
+    y : ndarray
+        If `a` is of inexact type, return a copy of `a` with the NaNs
+        replaced by the fill value, otherwise return `a`.
+    mask: {bool, None}
+        If `a` is of inexact type, return a boolean mask marking locations of
+        NaNs, otherwise return None.
+
+    """
+    a = np.asanyarray(a)
+
+    if a.dtype == np.object_:
+        # object arrays do not support `isnan` (gh-9009), so make a guess
+        mask = np.not_equal(a, a, dtype=bool)
+    elif issubclass(a.dtype.type, np.inexact):
+        mask = np.isnan(a)
+    else:
+        mask = None
+
+    if mask is not None:
+        a = np.array(a, subok=True, copy=True)
+        np.copyto(a, val, where=mask)
+
+    return a, mask
+
+
+def _copyto(a, val, mask):
+    """
+    Replace values in `a` with NaN where `mask` is True.  This differs from
+    copyto in that it will deal with the case where `a` is a numpy scalar.
+
+    Parameters
+    ----------
+    a : ndarray or numpy scalar
+        Array or numpy scalar some of whose values are to be replaced
+        by val.
+    val : numpy scalar
+        Value used a replacement.
+    mask : ndarray, scalar
+        Boolean array. Where True the corresponding element of `a` is
+        replaced by `val`. Broadcasts.
+
+    Returns
+    -------
+    res : ndarray, scalar
+        Array with elements replaced or scalar `val`.
+
+    """
+    if isinstance(a, np.ndarray):
+        np.copyto(a, val, where=mask, casting='unsafe')
+    else:
+        a = a.dtype.type(val)
+    return a
+
+
+def _remove_nan_1d(arr1d, second_arr1d=None, overwrite_input=False):
+    """
+    Equivalent to arr1d[~arr1d.isnan()], but in a different order
+
+    Presumably faster as it incurs fewer copies
+
+    Parameters
+    ----------
+    arr1d : ndarray
+        Array to remove nans from
+    second_arr1d : ndarray or None
+        A second array which will have the same positions removed as arr1d.
+    overwrite_input : bool
+        True if `arr1d` can be modified in place
+
+    Returns
+    -------
+    res : ndarray
+        Array with nan elements removed
+    second_res : ndarray or None
+        Second array with nan element positions of first array removed.
+    overwrite_input : bool
+        True if `res` can be modified in place, given the constraint on the
+        input
+    """
+    if arr1d.dtype == object:
+        # object arrays do not support `isnan` (gh-9009), so make a guess
+        c = np.not_equal(arr1d, arr1d, dtype=bool)
+    else:
+        c = np.isnan(arr1d)
+
+    s = np.nonzero(c)[0]
+    if s.size == arr1d.size:
+        warnings.warn("All-NaN slice encountered", RuntimeWarning,
+                      stacklevel=6)
+        if second_arr1d is None:
+            return arr1d[:0], None, True
+        else:
+            return arr1d[:0], second_arr1d[:0], True
+    elif s.size == 0:
+        return arr1d, second_arr1d, overwrite_input
+    else:
+        if not overwrite_input:
+            arr1d = arr1d.copy()
+        # select non-nans at end of array
+        enonan = arr1d[-s.size:][~c[-s.size:]]
+        # fill nans in beginning of array with non-nans of end
+        arr1d[s[:enonan.size]] = enonan
+
+        if second_arr1d is None:
+            return arr1d[:-s.size], None, True
+        else:
+            if not overwrite_input:
+                second_arr1d = second_arr1d.copy()
+            enonan = second_arr1d[-s.size:][~c[-s.size:]]
+            second_arr1d[s[:enonan.size]] = enonan
+
+            return arr1d[:-s.size], second_arr1d[:-s.size], True
+
+
+def _divide_by_count(a, b, out=None):
+    """
+    Compute a/b ignoring invalid results. If `a` is an array the division
+    is done in place. If `a` is a scalar, then its type is preserved in the
+    output. If out is None, then a is used instead so that the division
+    is in place. Note that this is only called with `a` an inexact type.
+
+    Parameters
+    ----------
+    a : {ndarray, numpy scalar}
+        Numerator. Expected to be of inexact type but not checked.
+    b : {ndarray, numpy scalar}
+        Denominator.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``; if provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary.
+
+    Returns
+    -------
+    ret : {ndarray, numpy scalar}
+        The return value is a/b. If `a` was an ndarray the division is done
+        in place. If `a` is a numpy scalar, the division preserves its type.
+
+    """
+    with np.errstate(invalid='ignore', divide='ignore'):
+        if isinstance(a, np.ndarray):
+            if out is None:
+                return np.divide(a, b, out=a, casting='unsafe')
+            else:
+                return np.divide(a, b, out=out, casting='unsafe')
+        elif out is None:
+            # Precaution against reduced object arrays
+            try:
+                return a.dtype.type(a / b)
+            except AttributeError:
+                return a / b
+        else:
+            # This is questionable, but currently a numpy scalar can
+            # be output to a zero dimensional array.
+            return np.divide(a, b, out=out, casting='unsafe')
+
+
+def _nanmin_dispatcher(a, axis=None, out=None, keepdims=None,
+                       initial=None, where=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanmin_dispatcher)
+def nanmin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
+           where=np._NoValue):
+    """
+    Return minimum of an array or minimum along an axis, ignoring any NaNs.
+    When all-NaN slices are encountered a ``RuntimeWarning`` is raised and
+    Nan is returned for that slice.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose minimum is desired. If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the minimum is computed. The default is to compute
+        the minimum of the flattened array.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``; if provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary. See
+        :ref:`ufuncs-output-type` for more details.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+
+        If the value is anything but the default, then
+        `keepdims` will be passed through to the `min` method
+        of sub-classes of `ndarray`.  If the sub-classes methods
+        does not implement `keepdims` any exceptions will be raised.
+    initial : scalar, optional
+        The maximum value of an output element. Must be present to allow
+        computation on empty slice. See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+    where : array_like of bool, optional
+        Elements to compare for the minimum. See `~numpy.ufunc.reduce`
+        for details.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    nanmin : ndarray
+        An array with the same shape as `a`, with the specified axis
+        removed.  If `a` is a 0-d array, or if axis is None, an ndarray
+        scalar is returned.  The same dtype as `a` is returned.
+
+    See Also
+    --------
+    nanmax :
+        The maximum value of an array along a given axis, ignoring any NaNs.
+    amin :
+        The minimum value of an array along a given axis, propagating any NaNs.
+    fmin :
+        Element-wise minimum of two arrays, ignoring any NaNs.
+    minimum :
+        Element-wise minimum of two arrays, propagating any NaNs.
+    isnan :
+        Shows which elements are Not a Number (NaN).
+    isfinite:
+        Shows which elements are neither NaN nor infinity.
+
+    amax, fmax, maximum
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+    Positive infinity is treated as a very large number and negative
+    infinity is treated as a very small (i.e. negative) number.
+
+    If the input has a integer type the function is equivalent to np.min.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, np.nan]])
+    >>> np.nanmin(a)
+    1.0
+    >>> np.nanmin(a, axis=0)
+    array([1.,  2.])
+    >>> np.nanmin(a, axis=1)
+    array([1.,  3.])
+
+    When positive infinity and negative infinity are present:
+
+    >>> np.nanmin([1, 2, np.nan, np.inf])
+    1.0
+    >>> np.nanmin([1, 2, np.nan, -np.inf])
+    -inf
+
+    """
+    kwargs = {}
+    if keepdims is not np._NoValue:
+        kwargs['keepdims'] = keepdims
+    if initial is not np._NoValue:
+        kwargs['initial'] = initial
+    if where is not np._NoValue:
+        kwargs['where'] = where
+
+    if (type(a) is np.ndarray or type(a) is np.memmap) and a.dtype != np.object_:
+        # Fast, but not safe for subclasses of ndarray, or object arrays,
+        # which do not implement isnan (gh-9009), or fmin correctly (gh-8975)
+        res = np.fmin.reduce(a, axis=axis, out=out, **kwargs)
+        if np.isnan(res).any():
+            warnings.warn("All-NaN slice encountered", RuntimeWarning,
+                          stacklevel=2)
+    else:
+        # Slow, but safe for subclasses of ndarray
+        a, mask = _replace_nan(a, +np.inf)
+        res = np.amin(a, axis=axis, out=out, **kwargs)
+        if mask is None:
+            return res
+
+        # Check for all-NaN axis
+        kwargs.pop("initial", None)
+        mask = np.all(mask, axis=axis, **kwargs)
+        if np.any(mask):
+            res = _copyto(res, np.nan, mask)
+            warnings.warn("All-NaN axis encountered", RuntimeWarning,
+                          stacklevel=2)
+    return res
+
+
+def _nanmax_dispatcher(a, axis=None, out=None, keepdims=None,
+                       initial=None, where=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanmax_dispatcher)
+def nanmax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
+           where=np._NoValue):
+    """
+    Return the maximum of an array or maximum along an axis, ignoring any
+    NaNs.  When all-NaN slices are encountered a ``RuntimeWarning`` is
+    raised and NaN is returned for that slice.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose maximum is desired. If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the maximum is computed. The default is to compute
+        the maximum of the flattened array.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``; if provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary. See
+        :ref:`ufuncs-output-type` for more details.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+        If the value is anything but the default, then
+        `keepdims` will be passed through to the `max` method
+        of sub-classes of `ndarray`.  If the sub-classes methods
+        does not implement `keepdims` any exceptions will be raised.
+    initial : scalar, optional
+        The minimum value of an output element. Must be present to allow
+        computation on empty slice. See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+    where : array_like of bool, optional
+        Elements to compare for the maximum. See `~numpy.ufunc.reduce`
+        for details.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    nanmax : ndarray
+        An array with the same shape as `a`, with the specified axis removed.
+        If `a` is a 0-d array, or if axis is None, an ndarray scalar is
+        returned.  The same dtype as `a` is returned.
+
+    See Also
+    --------
+    nanmin :
+        The minimum value of an array along a given axis, ignoring any NaNs.
+    amax :
+        The maximum value of an array along a given axis, propagating any NaNs.
+    fmax :
+        Element-wise maximum of two arrays, ignoring any NaNs.
+    maximum :
+        Element-wise maximum of two arrays, propagating any NaNs.
+    isnan :
+        Shows which elements are Not a Number (NaN).
+    isfinite:
+        Shows which elements are neither NaN nor infinity.
+
+    amin, fmin, minimum
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+    Positive infinity is treated as a very large number and negative
+    infinity is treated as a very small (i.e. negative) number.
+
+    If the input has a integer type the function is equivalent to np.max.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, np.nan]])
+    >>> np.nanmax(a)
+    3.0
+    >>> np.nanmax(a, axis=0)
+    array([3.,  2.])
+    >>> np.nanmax(a, axis=1)
+    array([2.,  3.])
+
+    When positive infinity and negative infinity are present:
+
+    >>> np.nanmax([1, 2, np.nan, -np.inf])
+    2.0
+    >>> np.nanmax([1, 2, np.nan, np.inf])
+    inf
+
+    """
+    kwargs = {}
+    if keepdims is not np._NoValue:
+        kwargs['keepdims'] = keepdims
+    if initial is not np._NoValue:
+        kwargs['initial'] = initial
+    if where is not np._NoValue:
+        kwargs['where'] = where
+
+    if (type(a) is np.ndarray or type(a) is np.memmap) and a.dtype != np.object_:
+        # Fast, but not safe for subclasses of ndarray, or object arrays,
+        # which do not implement isnan (gh-9009), or fmax correctly (gh-8975)
+        res = np.fmax.reduce(a, axis=axis, out=out, **kwargs)
+        if np.isnan(res).any():
+            warnings.warn("All-NaN slice encountered", RuntimeWarning,
+                          stacklevel=2)
+    else:
+        # Slow, but safe for subclasses of ndarray
+        a, mask = _replace_nan(a, -np.inf)
+        res = np.amax(a, axis=axis, out=out, **kwargs)
+        if mask is None:
+            return res
+
+        # Check for all-NaN axis
+        kwargs.pop("initial", None)
+        mask = np.all(mask, axis=axis, **kwargs)
+        if np.any(mask):
+            res = _copyto(res, np.nan, mask)
+            warnings.warn("All-NaN axis encountered", RuntimeWarning,
+                          stacklevel=2)
+    return res
+
+
+def _nanargmin_dispatcher(a, axis=None, out=None, *, keepdims=None):
+    return (a,)
+
+
+@array_function_dispatch(_nanargmin_dispatcher)
+def nanargmin(a, axis=None, out=None, *, keepdims=np._NoValue):
+    """
+    Return the indices of the minimum values in the specified axis ignoring
+    NaNs. For all-NaN slices ``ValueError`` is raised. Warning: the results
+    cannot be trusted if a slice contains only NaNs and Infs.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data.
+    axis : int, optional
+        Axis along which to operate.  By default flattened input is used.
+    out : array, optional
+        If provided, the result will be inserted into this array. It should
+        be of the appropriate shape and dtype.
+
+        .. versionadded:: 1.22.0
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the array.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    index_array : ndarray
+        An array of indices or a single index value.
+
+    See Also
+    --------
+    argmin, nanargmax
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[np.nan, 4], [2, 3]])
+    >>> np.argmin(a)
+    0
+    >>> np.nanargmin(a)
+    2
+    >>> np.nanargmin(a, axis=0)
+    array([1, 1])
+    >>> np.nanargmin(a, axis=1)
+    array([1, 0])
+
+    """
+    a, mask = _replace_nan(a, np.inf)
+    if mask is not None and mask.size:
+        mask = np.all(mask, axis=axis)
+        if np.any(mask):
+            raise ValueError("All-NaN slice encountered")
+    res = np.argmin(a, axis=axis, out=out, keepdims=keepdims)
+    return res
+
+
+def _nanargmax_dispatcher(a, axis=None, out=None, *, keepdims=None):
+    return (a,)
+
+
+@array_function_dispatch(_nanargmax_dispatcher)
+def nanargmax(a, axis=None, out=None, *, keepdims=np._NoValue):
+    """
+    Return the indices of the maximum values in the specified axis ignoring
+    NaNs. For all-NaN slices ``ValueError`` is raised. Warning: the
+    results cannot be trusted if a slice contains only NaNs and -Infs.
+
+
+    Parameters
+    ----------
+    a : array_like
+        Input data.
+    axis : int, optional
+        Axis along which to operate.  By default flattened input is used.
+    out : array, optional
+        If provided, the result will be inserted into this array. It should
+        be of the appropriate shape and dtype.
+
+        .. versionadded:: 1.22.0
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the array.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    index_array : ndarray
+        An array of indices or a single index value.
+
+    See Also
+    --------
+    argmax, nanargmin
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[np.nan, 4], [2, 3]])
+    >>> np.argmax(a)
+    0
+    >>> np.nanargmax(a)
+    1
+    >>> np.nanargmax(a, axis=0)
+    array([1, 0])
+    >>> np.nanargmax(a, axis=1)
+    array([1, 1])
+
+    """
+    a, mask = _replace_nan(a, -np.inf)
+    if mask is not None and mask.size:
+        mask = np.all(mask, axis=axis)
+        if np.any(mask):
+            raise ValueError("All-NaN slice encountered")
+    res = np.argmax(a, axis=axis, out=out, keepdims=keepdims)
+    return res
+
+
+def _nansum_dispatcher(a, axis=None, dtype=None, out=None, keepdims=None,
+                       initial=None, where=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nansum_dispatcher)
+def nansum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue,
+           initial=np._NoValue, where=np._NoValue):
+    """
+    Return the sum of array elements over a given axis treating Not a
+    Numbers (NaNs) as zero.
+
+    In NumPy versions <= 1.9.0 Nan is returned for slices that are all-NaN or
+    empty. In later versions zero is returned.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose sum is desired. If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the sum is computed. The default is to compute the
+        sum of the flattened array.
+    dtype : data-type, optional
+        The type of the returned array and of the accumulator in which the
+        elements are summed.  By default, the dtype of `a` is used.  An
+        exception is when `a` has an integer type with less precision than
+        the platform (u)intp. In that case, the default will be either
+        (u)int32 or (u)int64 depending on whether the platform is 32 or 64
+        bits. For inexact inputs, dtype must be inexact.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``. If provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary.  See
+        :ref:`ufuncs-output-type` for more details. The casting of NaN to integer
+        can yield unexpected results.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+
+        If the value is anything but the default, then
+        `keepdims` will be passed through to the `mean` or `sum` methods
+        of sub-classes of `ndarray`.  If the sub-classes methods
+        does not implement `keepdims` any exceptions will be raised.
+    initial : scalar, optional
+        Starting value for the sum. See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+    where : array_like of bool, optional
+        Elements to include in the sum. See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    nansum : ndarray.
+        A new array holding the result is returned unless `out` is
+        specified, in which it is returned. The result has the same
+        size as `a`, and the same shape as `a` if `axis` is not None
+        or `a` is a 1-d array.
+
+    See Also
+    --------
+    numpy.sum : Sum across array propagating NaNs.
+    isnan : Show which elements are NaN.
+    isfinite : Show which elements are not NaN or +/-inf.
+
+    Notes
+    -----
+    If both positive and negative infinity are present, the sum will be Not
+    A Number (NaN).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.nansum(1)
+    1
+    >>> np.nansum([1])
+    1
+    >>> np.nansum([1, np.nan])
+    1.0
+    >>> a = np.array([[1, 1], [1, np.nan]])
+    >>> np.nansum(a)
+    3.0
+    >>> np.nansum(a, axis=0)
+    array([2.,  1.])
+    >>> np.nansum([1, np.nan, np.inf])
+    inf
+    >>> np.nansum([1, np.nan, -np.inf])
+    -inf
+    >>> with np.errstate(invalid="ignore"):
+    ...     np.nansum([1, np.nan, np.inf, -np.inf]) # both +/- infinity present
+    np.float64(nan)
+
+    """
+    a, mask = _replace_nan(a, 0)
+    return np.sum(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims,
+                  initial=initial, where=where)
+
+
+def _nanprod_dispatcher(a, axis=None, dtype=None, out=None, keepdims=None,
+                        initial=None, where=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanprod_dispatcher)
+def nanprod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue,
+            initial=np._NoValue, where=np._NoValue):
+    """
+    Return the product of array elements over a given axis treating Not a
+    Numbers (NaNs) as ones.
+
+    One is returned for slices that are all-NaN or empty.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose product is desired. If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the product is computed. The default is to compute
+        the product of the flattened array.
+    dtype : data-type, optional
+        The type of the returned array and of the accumulator in which the
+        elements are summed.  By default, the dtype of `a` is used.  An
+        exception is when `a` has an integer type with less precision than
+        the platform (u)intp. In that case, the default will be either
+        (u)int32 or (u)int64 depending on whether the platform is 32 or 64
+        bits. For inexact inputs, dtype must be inexact.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``. If provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary. See
+        :ref:`ufuncs-output-type` for more details. The casting of NaN to integer
+        can yield unexpected results.
+    keepdims : bool, optional
+        If True, the axes which are reduced are left in the result as
+        dimensions with size one. With this option, the result will
+        broadcast correctly against the original `arr`.
+    initial : scalar, optional
+        The starting value for this product. See `~numpy.ufunc.reduce`
+        for details.
+
+        .. versionadded:: 1.22.0
+    where : array_like of bool, optional
+        Elements to include in the product. See `~numpy.ufunc.reduce`
+        for details.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    nanprod : ndarray
+        A new array holding the result is returned unless `out` is
+        specified, in which case it is returned.
+
+    See Also
+    --------
+    numpy.prod : Product across array propagating NaNs.
+    isnan : Show which elements are NaN.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.nanprod(1)
+    1
+    >>> np.nanprod([1])
+    1
+    >>> np.nanprod([1, np.nan])
+    1.0
+    >>> a = np.array([[1, 2], [3, np.nan]])
+    >>> np.nanprod(a)
+    6.0
+    >>> np.nanprod(a, axis=0)
+    array([3., 2.])
+
+    """
+    a, mask = _replace_nan(a, 1)
+    return np.prod(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims,
+                   initial=initial, where=where)
+
+
+def _nancumsum_dispatcher(a, axis=None, dtype=None, out=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nancumsum_dispatcher)
+def nancumsum(a, axis=None, dtype=None, out=None):
+    """
+    Return the cumulative sum of array elements over a given axis treating Not a
+    Numbers (NaNs) as zero.  The cumulative sum does not change when NaNs are
+    encountered and leading NaNs are replaced by zeros.
+
+    Zeros are returned for slices that are all-NaN or empty.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    axis : int, optional
+        Axis along which the cumulative sum is computed. The default
+        (None) is to compute the cumsum over the flattened array.
+    dtype : dtype, optional
+        Type of the returned array and of the accumulator in which the
+        elements are summed.  If `dtype` is not specified, it defaults
+        to the dtype of `a`, unless `a` has an integer dtype with a
+        precision less than that of the default platform integer.  In
+        that case, the default platform integer is used.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output
+        but the type will be cast if necessary. See :ref:`ufuncs-output-type` for
+        more details.
+
+    Returns
+    -------
+    nancumsum : ndarray.
+        A new array holding the result is returned unless `out` is
+        specified, in which it is returned. The result has the same
+        size as `a`, and the same shape as `a` if `axis` is not None
+        or `a` is a 1-d array.
+
+    See Also
+    --------
+    numpy.cumsum : Cumulative sum across array propagating NaNs.
+    isnan : Show which elements are NaN.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.nancumsum(1)
+    array([1])
+    >>> np.nancumsum([1])
+    array([1])
+    >>> np.nancumsum([1, np.nan])
+    array([1.,  1.])
+    >>> a = np.array([[1, 2], [3, np.nan]])
+    >>> np.nancumsum(a)
+    array([1.,  3.,  6.,  6.])
+    >>> np.nancumsum(a, axis=0)
+    array([[1.,  2.],
+           [4.,  2.]])
+    >>> np.nancumsum(a, axis=1)
+    array([[1.,  3.],
+           [3.,  3.]])
+
+    """
+    a, mask = _replace_nan(a, 0)
+    return np.cumsum(a, axis=axis, dtype=dtype, out=out)
+
+
+def _nancumprod_dispatcher(a, axis=None, dtype=None, out=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nancumprod_dispatcher)
+def nancumprod(a, axis=None, dtype=None, out=None):
+    """
+    Return the cumulative product of array elements over a given axis treating Not a
+    Numbers (NaNs) as one.  The cumulative product does not change when NaNs are
+    encountered and leading NaNs are replaced by ones.
+
+    Ones are returned for slices that are all-NaN or empty.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    axis : int, optional
+        Axis along which the cumulative product is computed.  By default
+        the input is flattened.
+    dtype : dtype, optional
+        Type of the returned array, as well as of the accumulator in which
+        the elements are multiplied.  If *dtype* is not specified, it
+        defaults to the dtype of `a`, unless `a` has an integer dtype with
+        a precision less than that of the default platform integer.  In
+        that case, the default platform integer is used instead.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output
+        but the type of the resulting values will be cast if necessary.
+
+    Returns
+    -------
+    nancumprod : ndarray
+        A new array holding the result is returned unless `out` is
+        specified, in which case it is returned.
+
+    See Also
+    --------
+    numpy.cumprod : Cumulative product across array propagating NaNs.
+    isnan : Show which elements are NaN.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.nancumprod(1)
+    array([1])
+    >>> np.nancumprod([1])
+    array([1])
+    >>> np.nancumprod([1, np.nan])
+    array([1.,  1.])
+    >>> a = np.array([[1, 2], [3, np.nan]])
+    >>> np.nancumprod(a)
+    array([1.,  2.,  6.,  6.])
+    >>> np.nancumprod(a, axis=0)
+    array([[1.,  2.],
+           [3.,  2.]])
+    >>> np.nancumprod(a, axis=1)
+    array([[1.,  2.],
+           [3.,  3.]])
+
+    """
+    a, mask = _replace_nan(a, 1)
+    return np.cumprod(a, axis=axis, dtype=dtype, out=out)
+
+
+def _nanmean_dispatcher(a, axis=None, dtype=None, out=None, keepdims=None,
+                        *, where=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanmean_dispatcher)
+def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue,
+            *, where=np._NoValue):
+    """
+    Compute the arithmetic mean along the specified axis, ignoring NaNs.
+
+    Returns the average of the array elements.  The average is taken over
+    the flattened array by default, otherwise over the specified axis.
+    `float64` intermediate and return values are used for integer inputs.
+
+    For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose mean is desired. If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the means are computed. The default is to compute
+        the mean of the flattened array.
+    dtype : data-type, optional
+        Type to use in computing the mean.  For integer inputs, the default
+        is `float64`; for inexact inputs, it is the same as the input
+        dtype.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  The default
+        is ``None``; if provided, it must have the same shape as the
+        expected output, but the type will be cast if necessary.
+        See :ref:`ufuncs-output-type` for more details.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+
+        If the value is anything but the default, then
+        `keepdims` will be passed through to the `mean` or `sum` methods
+        of sub-classes of `ndarray`.  If the sub-classes methods
+        does not implement `keepdims` any exceptions will be raised.
+    where : array_like of bool, optional
+        Elements to include in the mean. See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+
+    Returns
+    -------
+    m : ndarray, see dtype parameter above
+        If `out=None`, returns a new array containing the mean values,
+        otherwise a reference to the output array is returned. Nan is
+        returned for slices that contain only NaNs.
+
+    See Also
+    --------
+    average : Weighted average
+    mean : Arithmetic mean taken while not ignoring NaNs
+    var, nanvar
+
+    Notes
+    -----
+    The arithmetic mean is the sum of the non-NaN elements along the axis
+    divided by the number of non-NaN elements.
+
+    Note that for floating-point input, the mean is computed using the same
+    precision the input has.  Depending on the input data, this can cause
+    the results to be inaccurate, especially for `float32`.  Specifying a
+    higher-precision accumulator using the `dtype` keyword can alleviate
+    this issue.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, np.nan], [3, 4]])
+    >>> np.nanmean(a)
+    2.6666666666666665
+    >>> np.nanmean(a, axis=0)
+    array([2.,  4.])
+    >>> np.nanmean(a, axis=1)
+    array([1.,  3.5]) # may vary
+
+    """
+    arr, mask = _replace_nan(a, 0)
+    if mask is None:
+        return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims,
+                       where=where)
+
+    if dtype is not None:
+        dtype = np.dtype(dtype)
+    if dtype is not None and not issubclass(dtype.type, np.inexact):
+        raise TypeError("If a is inexact, then dtype must be inexact")
+    if out is not None and not issubclass(out.dtype.type, np.inexact):
+        raise TypeError("If a is inexact, then out must be inexact")
+
+    cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims,
+                 where=where)
+    tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims,
+                 where=where)
+    avg = _divide_by_count(tot, cnt, out=out)
+
+    isbad = (cnt == 0)
+    if isbad.any():
+        warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=2)
+        # NaN is the only possible bad value, so no further
+        # action is needed to handle bad results.
+    return avg
+
+
+def _nanmedian1d(arr1d, overwrite_input=False):
+    """
+    Private function for rank 1 arrays. Compute the median ignoring NaNs.
+    See nanmedian for parameter usage
+    """
+    arr1d_parsed, _, overwrite_input = _remove_nan_1d(
+        arr1d, overwrite_input=overwrite_input,
+    )
+
+    if arr1d_parsed.size == 0:
+        # Ensure that a nan-esque scalar of the appropriate type (and unit)
+        # is returned for `timedelta64` and `complexfloating`
+        return arr1d[-1]
+
+    return np.median(arr1d_parsed, overwrite_input=overwrite_input)
+
+
+def _nanmedian(a, axis=None, out=None, overwrite_input=False):
+    """
+    Private function that doesn't support extended axis or keepdims.
+    These methods are extended to this function using _ureduce
+    See nanmedian for parameter usage
+
+    """
+    if axis is None or a.ndim == 1:
+        part = a.ravel()
+        if out is None:
+            return _nanmedian1d(part, overwrite_input)
+        else:
+            out[...] = _nanmedian1d(part, overwrite_input)
+            return out
+    else:
+        # for small medians use sort + indexing which is still faster than
+        # apply_along_axis
+        # benchmarked with shuffled (50, 50, x) containing a few NaN
+        if a.shape[axis] < 600:
+            return _nanmedian_small(a, axis, out, overwrite_input)
+        result = np.apply_along_axis(_nanmedian1d, axis, a, overwrite_input)
+        if out is not None:
+            out[...] = result
+        return result
+
+
+def _nanmedian_small(a, axis=None, out=None, overwrite_input=False):
+    """
+    sort + indexing median, faster for small medians along multiple
+    dimensions due to the high overhead of apply_along_axis
+
+    see nanmedian for parameter usage
+    """
+    a = np.ma.masked_array(a, np.isnan(a))
+    m = np.ma.median(a, axis=axis, overwrite_input=overwrite_input)
+    for i in range(np.count_nonzero(m.mask.ravel())):
+        warnings.warn("All-NaN slice encountered", RuntimeWarning,
+                      stacklevel=5)
+
+    fill_value = np.timedelta64("NaT") if m.dtype.kind == "m" else np.nan
+    if out is not None:
+        out[...] = m.filled(fill_value)
+        return out
+    return m.filled(fill_value)
+
+
+def _nanmedian_dispatcher(
+        a, axis=None, out=None, overwrite_input=None, keepdims=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanmedian_dispatcher)
+def nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=np._NoValue):
+    """
+    Compute the median along the specified axis, while ignoring NaNs.
+
+    Returns the median of the array elements.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array.
+    axis : {int, sequence of int, None}, optional
+        Axis or axes along which the medians are computed. The default
+        is to compute the median along a flattened version of the array.
+        A sequence of axes is supported since version 1.9.0.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output,
+        but the type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+       If True, then allow use of memory of input array `a` for
+       calculations. The input array will be modified by the call to
+       `median`. This will save memory when you do not need to preserve
+       the contents of the input array. Treat the input as undefined,
+       but it will probably be fully or partially sorted. Default is
+       False. If `overwrite_input` is ``True`` and `a` is not already an
+       `ndarray`, an error will be raised.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+
+        If this is anything but the default value it will be passed
+        through (in the special case of an empty array) to the
+        `mean` function of the underlying array.  If the array is
+        a sub-class and `mean` does not have the kwarg `keepdims` this
+        will raise a RuntimeError.
+
+    Returns
+    -------
+    median : ndarray
+        A new array holding the result. If the input contains integers
+        or floats smaller than ``float64``, then the output data-type is
+        ``np.float64``.  Otherwise, the data-type of the output is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    mean, median, percentile
+
+    Notes
+    -----
+    Given a vector ``V`` of length ``N``, the median of ``V`` is the
+    middle value of a sorted copy of ``V``, ``V_sorted`` - i.e.,
+    ``V_sorted[(N-1)/2]``, when ``N`` is odd and the average of the two
+    middle values of ``V_sorted`` when ``N`` is even.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10.0, 7, 4], [3, 2, 1]])
+    >>> a[0, 1] = np.nan
+    >>> a
+    array([[10., nan,  4.],
+           [ 3.,  2.,  1.]])
+    >>> np.median(a)
+    np.float64(nan)
+    >>> np.nanmedian(a)
+    3.0
+    >>> np.nanmedian(a, axis=0)
+    array([6.5, 2. , 2.5])
+    >>> np.median(a, axis=1)
+    array([nan,  2.])
+    >>> b = a.copy()
+    >>> np.nanmedian(b, axis=1, overwrite_input=True)
+    array([7.,  2.])
+    >>> assert not np.all(a==b)
+    >>> b = a.copy()
+    >>> np.nanmedian(b, axis=None, overwrite_input=True)
+    3.0
+    >>> assert not np.all(a==b)
+
+    """
+    a = np.asanyarray(a)
+    # apply_along_axis in _nanmedian doesn't handle empty arrays well,
+    # so deal them upfront
+    if a.size == 0:
+        return np.nanmean(a, axis, out=out, keepdims=keepdims)
+
+    return fnb._ureduce(a, func=_nanmedian, keepdims=keepdims,
+                        axis=axis, out=out,
+                        overwrite_input=overwrite_input)
+
+
+def _nanpercentile_dispatcher(
+        a, q, axis=None, out=None, overwrite_input=None,
+        method=None, keepdims=None, *, weights=None):
+    return (a, q, out, weights)
+
+
+@array_function_dispatch(_nanpercentile_dispatcher)
+def nanpercentile(
+        a,
+        q,
+        axis=None,
+        out=None,
+        overwrite_input=False,
+        method="linear",
+        keepdims=np._NoValue,
+        *,
+        weights=None,
+):
+    """
+    Compute the qth percentile of the data along the specified axis,
+    while ignoring nan values.
+
+    Returns the qth percentile(s) of the array elements.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array, containing
+        nan values to be ignored.
+    q : array_like of float
+        Percentile or sequence of percentiles to compute, which must be
+        between 0 and 100 inclusive.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the percentiles are computed. The default
+        is to compute the percentile(s) along a flattened version of the
+        array.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must have
+        the same shape and buffer length as the expected output, but the
+        type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+        If True, then allow the input array `a` to be modified by
+        intermediate calculations, to save memory. In this case, the
+        contents of the input `a` after this function completes is
+        undefined.
+    method : str, optional
+        This parameter specifies the method to use for estimating the
+        percentile.  There are many different methods, some unique to NumPy.
+        See the notes for explanation.  The options sorted by their R type
+        as summarized in the H&F paper [1]_ are:
+
+        1. 'inverted_cdf'
+        2. 'averaged_inverted_cdf'
+        3. 'closest_observation'
+        4. 'interpolated_inverted_cdf'
+        5. 'hazen'
+        6. 'weibull'
+        7. 'linear'  (default)
+        8. 'median_unbiased'
+        9. 'normal_unbiased'
+
+        The first three methods are discontinuous.  NumPy further defines the
+        following discontinuous variations of the default 'linear' (7.) option:
+
+        * 'lower'
+        * 'higher',
+        * 'midpoint'
+        * 'nearest'
+
+        .. versionchanged:: 1.22.0
+            This argument was previously called "interpolation" and only
+            offered the "linear" default and last four options.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left in
+        the result as dimensions with size one. With this option, the
+        result will broadcast correctly against the original array `a`.
+
+        If this is anything but the default value it will be passed
+        through (in the special case of an empty array) to the
+        `mean` function of the underlying array.  If the array is
+        a sub-class and `mean` does not have the kwarg `keepdims` this
+        will raise a RuntimeError.
+
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the percentile according to its associated weight.
+        The weights array can either be 1-D (in which case its length must be
+        the size of `a` along the given axis) or of the same shape as `a`.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        Only `method="inverted_cdf"` supports weights.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    percentile : scalar or ndarray
+        If `q` is a single percentile and `axis=None`, then the result
+        is a scalar. If multiple percentiles are given, first axis of
+        the result corresponds to the percentiles. The other axes are
+        the axes that remain after the reduction of `a`. If the input
+        contains integers or floats smaller than ``float64``, the output
+        data-type is ``float64``. Otherwise, the output data-type is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    nanmean
+    nanmedian : equivalent to ``nanpercentile(..., 50)``
+    percentile, median, mean
+    nanquantile : equivalent to nanpercentile, except q in range [0, 1].
+
+    Notes
+    -----
+    The behavior of `numpy.nanpercentile` with percentage `q` is that of
+    `numpy.quantile` with argument ``q/100`` (ignoring nan values).
+    For more information, please see `numpy.quantile`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10., 7., 4.], [3., 2., 1.]])
+    >>> a[0][1] = np.nan
+    >>> a
+    array([[10.,  nan,   4.],
+          [ 3.,   2.,   1.]])
+    >>> np.percentile(a, 50)
+    np.float64(nan)
+    >>> np.nanpercentile(a, 50)
+    3.0
+    >>> np.nanpercentile(a, 50, axis=0)
+    array([6.5, 2. , 2.5])
+    >>> np.nanpercentile(a, 50, axis=1, keepdims=True)
+    array([[7.],
+           [2.]])
+    >>> m = np.nanpercentile(a, 50, axis=0)
+    >>> out = np.zeros_like(m)
+    >>> np.nanpercentile(a, 50, axis=0, out=out)
+    array([6.5, 2. , 2.5])
+    >>> m
+    array([6.5,  2. ,  2.5])
+
+    >>> b = a.copy()
+    >>> np.nanpercentile(b, 50, axis=1, overwrite_input=True)
+    array([7., 2.])
+    >>> assert not np.all(a==b)
+
+    References
+    ----------
+    .. [1] R. J. Hyndman and Y. Fan,
+       "Sample quantiles in statistical packages,"
+       The American Statistician, 50(4), pp. 361-365, 1996
+
+    """
+    a = np.asanyarray(a)
+    if a.dtype.kind == "c":
+        raise TypeError("a must be an array of real numbers")
+
+    weak_q = type(q) in (int, float)  # use weak promotion for final result type
+    q = np.true_divide(q, 100, out=...)
+    if not fnb._quantile_is_valid(q):
+        raise ValueError("Percentiles must be in the range [0, 100]")
+
+    if weights is not None:
+        if method != "inverted_cdf":
+            msg = ("Only method 'inverted_cdf' supports weights. "
+                   f"Got: {method}.")
+            raise ValueError(msg)
+        if axis is not None:
+            axis = _nx.normalize_axis_tuple(axis, a.ndim, argname="axis")
+        weights = _weights_are_valid(weights=weights, a=a, axis=axis)
+        if np.any(weights < 0):
+            raise ValueError("Weights must be non-negative.")
+
+    return _nanquantile_unchecked(
+        a, q, axis, out, overwrite_input, method, keepdims, weights, weak_q)
+
+
+def _nanquantile_dispatcher(a, q, axis=None, out=None, overwrite_input=None,
+                            method=None, keepdims=None, *, weights=None):
+    return (a, q, out, weights)
+
+
+@array_function_dispatch(_nanquantile_dispatcher)
+def nanquantile(
+        a,
+        q,
+        axis=None,
+        out=None,
+        overwrite_input=False,
+        method="linear",
+        keepdims=np._NoValue,
+        *,
+        weights=None,
+):
+    """
+    Compute the qth quantile of the data along the specified axis,
+    while ignoring nan values.
+    Returns the qth quantile(s) of the array elements.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array, containing
+        nan values to be ignored
+    q : array_like of float
+        Probability or sequence of probabilities for the quantiles to compute.
+        Values must be between 0 and 1 inclusive.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the quantiles are computed. The
+        default is to compute the quantile(s) along a flattened
+        version of the array.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output,
+        but the type (of the output) will be cast if necessary.
+    overwrite_input : bool, optional
+        If True, then allow the input array `a` to be modified by intermediate
+        calculations, to save memory. In this case, the contents of the input
+        `a` after this function completes is undefined.
+    method : str, optional
+        This parameter specifies the method to use for estimating the
+        quantile.  There are many different methods, some unique to NumPy.
+        See the notes for explanation.  The options sorted by their R type
+        as summarized in the H&F paper [1]_ are:
+
+        1. 'inverted_cdf'
+        2. 'averaged_inverted_cdf'
+        3. 'closest_observation'
+        4. 'interpolated_inverted_cdf'
+        5. 'hazen'
+        6. 'weibull'
+        7. 'linear'  (default)
+        8. 'median_unbiased'
+        9. 'normal_unbiased'
+
+        The first three methods are discontinuous.  NumPy further defines the
+        following discontinuous variations of the default 'linear' (7.) option:
+
+        * 'lower'
+        * 'higher',
+        * 'midpoint'
+        * 'nearest'
+
+        .. versionchanged:: 1.22.0
+            This argument was previously called "interpolation" and only
+            offered the "linear" default and last four options.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left in
+        the result as dimensions with size one. With this option, the
+        result will broadcast correctly against the original array `a`.
+
+        If this is anything but the default value it will be passed
+        through (in the special case of an empty array) to the
+        `mean` function of the underlying array.  If the array is
+        a sub-class and `mean` does not have the kwarg `keepdims` this
+        will raise a RuntimeError.
+
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the quantile according to its associated weight.
+        The weights array can either be 1-D (in which case its length must be
+        the size of `a` along the given axis) or of the same shape as `a`.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        Only `method="inverted_cdf"` supports weights.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    quantile : scalar or ndarray
+        If `q` is a single probability and `axis=None`, then the result
+        is a scalar. If multiple probability levels are given, first axis of
+        the result corresponds to the quantiles. The other axes are
+        the axes that remain after the reduction of `a`. If the input
+        contains integers or floats smaller than ``float64``, the output
+        data-type is ``float64``. Otherwise, the output data-type is the
+        same as that of the input. If `out` is specified, that array is
+        returned instead.
+
+    See Also
+    --------
+    quantile
+    nanmean, nanmedian
+    nanmedian : equivalent to ``nanquantile(..., 0.5)``
+    nanpercentile : same as nanquantile, but with q in the range [0, 100].
+
+    Notes
+    -----
+    The behavior of `numpy.nanquantile` is the same as that of
+    `numpy.quantile` (ignoring nan values).
+    For more information, please see `numpy.quantile`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[10., 7., 4.], [3., 2., 1.]])
+    >>> a[0][1] = np.nan
+    >>> a
+    array([[10.,  nan,   4.],
+          [ 3.,   2.,   1.]])
+    >>> np.quantile(a, 0.5)
+    np.float64(nan)
+    >>> np.nanquantile(a, 0.5)
+    3.0
+    >>> np.nanquantile(a, 0.5, axis=0)
+    array([6.5, 2. , 2.5])
+    >>> np.nanquantile(a, 0.5, axis=1, keepdims=True)
+    array([[7.],
+           [2.]])
+    >>> m = np.nanquantile(a, 0.5, axis=0)
+    >>> out = np.zeros_like(m)
+    >>> np.nanquantile(a, 0.5, axis=0, out=out)
+    array([6.5, 2. , 2.5])
+    >>> m
+    array([6.5,  2. ,  2.5])
+    >>> b = a.copy()
+    >>> np.nanquantile(b, 0.5, axis=1, overwrite_input=True)
+    array([7., 2.])
+    >>> assert not np.all(a==b)
+
+    References
+    ----------
+    .. [1] R. J. Hyndman and Y. Fan,
+       "Sample quantiles in statistical packages,"
+       The American Statistician, 50(4), pp. 361-365, 1996
+
+    """
+    a = np.asanyarray(a)
+    if a.dtype.kind == "c":
+        raise TypeError("a must be an array of real numbers")
+
+    weak_q = type(q) in (int, float)  # use weak promotion for final result type
+    q = np.asanyarray(q)
+
+    if not fnb._quantile_is_valid(q):
+        raise ValueError("Quantiles must be in the range [0, 1]")
+
+    if weights is not None:
+        if method != "inverted_cdf":
+            msg = ("Only method 'inverted_cdf' supports weights. "
+                   f"Got: {method}.")
+            raise ValueError(msg)
+        if axis is not None:
+            axis = _nx.normalize_axis_tuple(axis, a.ndim, argname="axis")
+        weights = _weights_are_valid(weights=weights, a=a, axis=axis)
+        if np.any(weights < 0):
+            raise ValueError("Weights must be non-negative.")
+
+    return _nanquantile_unchecked(
+        a, q, axis, out, overwrite_input, method, keepdims, weights, weak_q)
+
+
+def _nanquantile_unchecked(
+        a,
+        q,
+        axis=None,
+        out=None,
+        overwrite_input=False,
+        method="linear",
+        keepdims=np._NoValue,
+        weights=None,
+        weak_q=False,
+):
+    """Assumes that q is in [0, 1], and is an ndarray"""
+    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
+    # so deal them upfront
+    if a.size == 0:
+        return np.nanmean(a, axis, out=out, keepdims=keepdims)
+    return fnb._ureduce(a,
+                        func=_nanquantile_ureduce_func,
+                        q=q,
+                        weights=weights,
+                        keepdims=keepdims,
+                        axis=axis,
+                        out=out,
+                        overwrite_input=overwrite_input,
+                        method=method,
+                        weak_q=weak_q)
+
+
+def _nanquantile_ureduce_func(
+        a: np.array,
+        q: np.array,
+        weights: np.array,
+        axis: int | None = None,
+        out=None,
+        overwrite_input: bool = False,
+        method="linear",
+        weak_q=False,
+):
+    """
+    Private function that doesn't support extended axis or keepdims.
+    These methods are extended to this function using _ureduce
+    See nanpercentile for parameter usage
+    """
+    if axis is None or a.ndim == 1:
+        part = a.ravel()
+        wgt = None if weights is None else weights.ravel()
+        result = _nanquantile_1d(part, q, overwrite_input, method,
+                                 weights=wgt, weak_q=weak_q)
+    # Note that this code could try to fill in `out` right away
+    elif weights is None:
+        result = np.apply_along_axis(_nanquantile_1d, axis, a, q,
+                                     overwrite_input, method, weights, weak_q)
+        # apply_along_axis fills in collapsed axis with results.
+        # Move those axes to the beginning to match percentile's
+        # convention.
+        if q.ndim != 0:
+            from_ax = [axis + i for i in range(q.ndim)]
+            result = np.moveaxis(result, from_ax, list(range(q.ndim)))
+    else:
+        # We need to apply along axis over 2 arrays, a and weights.
+        # move operation axes to end for simplicity:
+        a = np.moveaxis(a, axis, -1)
+        if weights is not None:
+            weights = np.moveaxis(weights, axis, -1)
+        if out is not None:
+            result = out
+        else:
+            # weights are limited to `inverted_cdf` so the result dtype
+            # is known to be identical to that of `a` here:
+            result = np.empty_like(a, shape=q.shape + a.shape[:-1])
+
+        for ii in np.ndindex(a.shape[:-1]):
+            result[(...,) + ii] = _nanquantile_1d(
+                    a[ii], q, weights=weights[ii],
+                    overwrite_input=overwrite_input, method=method,
+                    weak_q=weak_q,
+            )
+        # This path dealt with `out` already...
+        return result
+
+    if out is not None:
+        out[...] = result
+    return result
+
+
+def _nanquantile_1d(
+    arr1d, q, overwrite_input=False, method="linear", weights=None,
+    weak_q=False,
+):
+    """
+    Private function for rank 1 arrays. Compute quantile ignoring NaNs.
+    See nanpercentile for parameter usage
+    """
+    # TODO: What to do when arr1d = [1, np.nan] and weights = [0, 1]?
+    arr1d, weights, overwrite_input = _remove_nan_1d(arr1d,
+        second_arr1d=weights, overwrite_input=overwrite_input)
+    if arr1d.size == 0:
+        # convert to scalar
+        return np.full(q.shape, np.nan, dtype=arr1d.dtype)[()]
+
+    return fnb._quantile_unchecked(
+        arr1d,
+        q,
+        overwrite_input=overwrite_input,
+        method=method,
+        weights=weights,
+        weak_q=weak_q,
+    )
+
+
+def _nanvar_dispatcher(a, axis=None, dtype=None, out=None, ddof=None,
+                       keepdims=None, *, where=None, mean=None,
+                       correction=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanvar_dispatcher)
+def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue,
+           *, where=np._NoValue, mean=np._NoValue, correction=np._NoValue):
+    """
+    Compute the variance along the specified axis, while ignoring NaNs.
+
+    Returns the variance of the array elements, a measure of the spread of
+    a distribution.  The variance is computed for the flattened array by
+    default, otherwise over the specified axis.
+
+    For all-NaN slices or slices with zero degrees of freedom, NaN is
+    returned and a `RuntimeWarning` is raised.
+
+    Parameters
+    ----------
+    a : array_like
+        Array containing numbers whose variance is desired.  If `a` is not an
+        array, a conversion is attempted.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the variance is computed.  The default is to compute
+        the variance of the flattened array.
+    dtype : data-type, optional
+        Type to use in computing the variance.  For arrays of integer type
+        the default is `float64`; for arrays of float types it is the same as
+        the array type.
+    out : ndarray, optional
+        Alternate output array in which to place the result.  It must have
+        the same shape as the expected output, but the type is cast if
+        necessary.
+    ddof : {int, float}, optional
+        "Delta Degrees of Freedom": the divisor used in the calculation is
+        ``N - ddof``, where ``N`` represents the number of non-NaN
+        elements. By default `ddof` is zero.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+    where : array_like of bool, optional
+        Elements to include in the variance. See `~numpy.ufunc.reduce` for
+        details.
+
+        .. versionadded:: 1.22.0
+
+    mean : array_like, optional
+        Provide the mean to prevent its recalculation. The mean should have
+        a shape as if it was calculated with ``keepdims=True``.
+        The axis for the calculation of the mean should be the same as used in
+        the call to this var function.
+
+        .. versionadded:: 2.0.0
+
+    correction : {int, float}, optional
+        Array API compatible name for the ``ddof`` parameter. Only one of them
+        can be provided at the same time.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    variance : ndarray, see dtype parameter above
+        If `out` is None, return a new array containing the variance,
+        otherwise return a reference to the output array. If ddof is >= the
+        number of non-NaN elements in a slice or the slice contains only
+        NaNs, then the result for that slice is NaN.
+
+    See Also
+    --------
+    std : Standard deviation
+    mean : Average
+    var : Variance while not ignoring NaNs
+    nanstd, nanmean
+    :ref:`ufuncs-output-type`
+
+    Notes
+    -----
+    The variance is the average of the squared deviations from the mean,
+    i.e.,  ``var = mean(abs(x - x.mean())**2)``.
+
+    The mean is normally calculated as ``x.sum() / N``, where ``N = len(x)``.
+    If, however, `ddof` is specified, the divisor ``N - ddof`` is used
+    instead.  In standard statistical practice, ``ddof=1`` provides an
+    unbiased estimator of the variance of a hypothetical infinite
+    population.  ``ddof=0`` provides a maximum likelihood estimate of the
+    variance for normally distributed variables.
+
+    Note that for complex numbers, the absolute value is taken before
+    squaring, so that the result is always real and nonnegative.
+
+    For floating-point input, the variance is computed using the same
+    precision the input has.  Depending on the input data, this can cause
+    the results to be inaccurate, especially for `float32` (see example
+    below).  Specifying a higher-accuracy accumulator using the ``dtype``
+    keyword can alleviate this issue.
+
+    For this function to work on sub-classes of ndarray, they must define
+    `sum` with the kwarg `keepdims`
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, np.nan], [3, 4]])
+    >>> np.nanvar(a)
+    1.5555555555555554
+    >>> np.nanvar(a, axis=0)
+    array([1.,  0.])
+    >>> np.nanvar(a, axis=1)
+    array([0.,  0.25])  # may vary
+
+    """
+    arr, mask = _replace_nan(a, 0)
+    if mask is None:
+        return np.var(arr, axis=axis, dtype=dtype, out=out, ddof=ddof,
+                      keepdims=keepdims, where=where, mean=mean,
+                      correction=correction)
+
+    if dtype is not None:
+        dtype = np.dtype(dtype)
+    if dtype is not None and not issubclass(dtype.type, np.inexact):
+        raise TypeError("If a is inexact, then dtype must be inexact")
+    if out is not None and not issubclass(out.dtype.type, np.inexact):
+        raise TypeError("If a is inexact, then out must be inexact")
+
+    if correction != np._NoValue:
+        if ddof != 0:
+            raise ValueError(
+                "ddof and correction can't be provided simultaneously."
+            )
+        else:
+            ddof = correction
+
+    # Compute mean
+    if type(arr) is np.matrix:
+        _keepdims = np._NoValue
+    else:
+        _keepdims = True
+
+    cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=_keepdims,
+                     where=where)
+
+    if mean is not np._NoValue:
+        avg = mean
+    else:
+        # we need to special case matrix for reverse compatibility
+        # in order for this to work, these sums need to be called with
+        # keepdims=True, however matrix now raises an error in this case, but
+        # the reason that it drops the keepdims kwarg is to force keepdims=True
+        # so this used to work by serendipity.
+        avg = np.sum(arr, axis=axis, dtype=dtype,
+                     keepdims=_keepdims, where=where)
+        avg = _divide_by_count(avg, cnt)
+
+    # Compute squared deviation from mean.
+    np.subtract(arr, avg, out=arr, casting='unsafe', where=where)
+    arr = _copyto(arr, 0, mask)
+    if issubclass(arr.dtype.type, np.complexfloating):
+        sqr = np.multiply(arr, arr.conj(), out=arr, where=where).real
+    else:
+        sqr = np.multiply(arr, arr, out=arr, where=where)
+
+    # Compute variance.
+    var = np.sum(sqr, axis=axis, dtype=dtype, out=out, keepdims=keepdims,
+                 where=where)
+
+    # Precaution against reduced object arrays
+    try:
+        var_ndim = var.ndim
+    except AttributeError:
+        var_ndim = np.ndim(var)
+    if var_ndim < cnt.ndim:
+        # Subclasses of ndarray may ignore keepdims, so check here.
+        cnt = cnt.squeeze(axis)
+    dof = cnt - ddof
+    var = _divide_by_count(var, dof)
+
+    isbad = (dof <= 0)
+    if np.any(isbad):
+        warnings.warn("Degrees of freedom <= 0 for slice.", RuntimeWarning,
+                      stacklevel=2)
+        # NaN, inf, or negative numbers are all possible bad
+        # values, so explicitly replace them with NaN.
+        var = _copyto(var, np.nan, isbad)
+    return var
+
+
+def _nanstd_dispatcher(a, axis=None, dtype=None, out=None, ddof=None,
+                       keepdims=None, *, where=None, mean=None,
+                       correction=None):
+    return (a, out)
+
+
+@array_function_dispatch(_nanstd_dispatcher)
+def nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue,
+           *, where=np._NoValue, mean=np._NoValue, correction=np._NoValue):
+    """
+    Compute the standard deviation along the specified axis, while
+    ignoring NaNs.
+
+    Returns the standard deviation, a measure of the spread of a
+    distribution, of the non-NaN array elements. The standard deviation is
+    computed for the flattened array by default, otherwise over the
+    specified axis.
+
+    For all-NaN slices or slices with zero degrees of freedom, NaN is
+    returned and a `RuntimeWarning` is raised.
+
+    Parameters
+    ----------
+    a : array_like
+        Calculate the standard deviation of the non-NaN values.
+    axis : {int, tuple of int, None}, optional
+        Axis or axes along which the standard deviation is computed. The default is
+        to compute the standard deviation of the flattened array.
+    dtype : dtype, optional
+        Type to use in computing the standard deviation. For arrays of
+        integer type the default is float64, for arrays of float types it
+        is the same as the array type.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must have
+        the same shape as the expected output but the type (of the
+        calculated values) will be cast if necessary.
+    ddof : {int, float}, optional
+        Means Delta Degrees of Freedom.  The divisor used in calculations
+        is ``N - ddof``, where ``N`` represents the number of non-NaN
+        elements.  By default `ddof` is zero.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+
+        If this value is anything but the default it is passed through
+        as-is to the relevant functions of the sub-classes.  If these
+        functions do not have a `keepdims` kwarg, a RuntimeError will
+        be raised.
+    where : array_like of bool, optional
+        Elements to include in the standard deviation.
+        See `~numpy.ufunc.reduce` for details.
+
+        .. versionadded:: 1.22.0
+
+    mean : array_like, optional
+        Provide the mean to prevent its recalculation. The mean should have
+        a shape as if it was calculated with ``keepdims=True``.
+        The axis for the calculation of the mean should be the same as used in
+        the call to this std function.
+
+        .. versionadded:: 2.0.0
+
+    correction : {int, float}, optional
+        Array API compatible name for the ``ddof`` parameter. Only one of them
+        can be provided at the same time.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    standard_deviation : ndarray, see dtype parameter above.
+        If `out` is None, return a new array containing the standard
+        deviation, otherwise return a reference to the output array. If
+        ddof is >= the number of non-NaN elements in a slice or the slice
+        contains only NaNs, then the result for that slice is NaN.
+
+    See Also
+    --------
+    var, mean, std
+    nanvar, nanmean
+    :ref:`ufuncs-output-type`
+
+    Notes
+    -----
+    The standard deviation is the square root of the average of the squared
+    deviations from the mean: ``std = sqrt(mean(abs(x - x.mean())**2))``.
+
+    The average squared deviation is normally calculated as
+    ``x.sum() / N``, where ``N = len(x)``.  If, however, `ddof` is
+    specified, the divisor ``N - ddof`` is used instead. In standard
+    statistical practice, ``ddof=1`` provides an unbiased estimator of the
+    variance of the infinite population. ``ddof=0`` provides a maximum
+    likelihood estimate of the variance for normally distributed variables.
+    The standard deviation computed in this function is the square root of
+    the estimated variance, so even with ``ddof=1``, it will not be an
+    unbiased estimate of the standard deviation per se.
+
+    Note that, for complex numbers, `std` takes the absolute value before
+    squaring, so that the result is always real and nonnegative.
+
+    For floating-point input, the *std* is computed using the same
+    precision the input has. Depending on the input data, this can cause
+    the results to be inaccurate, especially for float32 (see example
+    below).  Specifying a higher-accuracy accumulator using the `dtype`
+    keyword can alleviate this issue.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([[1, np.nan], [3, 4]])
+    >>> np.nanstd(a)
+    1.247219128924647
+    >>> np.nanstd(a, axis=0)
+    array([1., 0.])
+    >>> np.nanstd(a, axis=1)
+    array([0.,  0.5]) # may vary
+
+    """
+    var = nanvar(a, axis=axis, dtype=dtype, out=out, ddof=ddof,
+                 keepdims=keepdims, where=where, mean=mean,
+                 correction=correction)
+    if isinstance(var, np.ndarray):
+        std = np.sqrt(var, out=var)
+    elif hasattr(var, 'dtype'):
+        std = var.dtype.type(np.sqrt(var))
+    else:
+        std = np.sqrt(var)
+    return std
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..6a8831c33fa269ec7c50bd49b3d5c63215d6b981
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_nanfunctions_impl.pyi
@@ -0,0 +1,48 @@
+from numpy._core.fromnumeric import (
+    amax,
+    amin,
+    argmax,
+    argmin,
+    cumprod,
+    cumsum,
+    mean,
+    prod,
+    std,
+    sum,
+    var,
+)
+from numpy.lib._function_base_impl import median, percentile, quantile
+
+__all__ = [
+    "nansum",
+    "nanmax",
+    "nanmin",
+    "nanargmax",
+    "nanargmin",
+    "nanmean",
+    "nanmedian",
+    "nanpercentile",
+    "nanvar",
+    "nanstd",
+    "nanprod",
+    "nancumsum",
+    "nancumprod",
+    "nanquantile",
+]
+
+# NOTE: In reality these functions are not aliases but distinct functions
+# with identical signatures.
+nanmin = amin
+nanmax = amax
+nanargmin = argmin
+nanargmax = argmax
+nansum = sum
+nanprod = prod
+nancumsum = cumsum
+nancumprod = cumprod
+nanmean = mean
+nanvar = var
+nanstd = std
+nanmedian = median
+nanpercentile = percentile
+nanquantile = quantile
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..ce000967caa70b965cc300a5e728979502bf7ef0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.py
@@ -0,0 +1,2583 @@
+"""
+IO related functions.
+"""
+import contextlib
+import functools
+import itertools
+import operator
+import os
+import pickle
+import re
+import warnings
+import weakref
+from collections.abc import Mapping
+from operator import itemgetter
+
+import numpy as np
+from numpy._core import overrides
+from numpy._core._multiarray_umath import _load_from_filelike
+from numpy._core.multiarray import packbits, unpackbits
+from numpy._core.overrides import finalize_array_function_like, set_module
+from numpy._utils import asbytes, asunicode
+
+from . import format
+from ._datasource import DataSource  # noqa: F401
+from ._format_impl import _MAX_HEADER_SIZE
+from ._iotools import (
+    ConversionWarning,
+    ConverterError,
+    ConverterLockError,
+    LineSplitter,
+    NameValidator,
+    StringConverter,
+    _decode_line,
+    _is_string_like,
+    easy_dtype,
+    flatten_dtype,
+    has_nested_fields,
+)
+
+__all__ = [
+    'savetxt', 'loadtxt', 'genfromtxt', 'load', 'save', 'savez',
+    'savez_compressed', 'packbits', 'unpackbits', 'fromregex'
+    ]
+
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+class BagObj:
+    """
+    BagObj(obj)
+
+    Convert attribute look-ups to getitems on the object passed in.
+
+    Parameters
+    ----------
+    obj : class instance
+        Object on which attribute look-up is performed.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib._npyio_impl import BagObj as BO
+    >>> class BagDemo:
+    ...     def __getitem__(self, key): # An instance of BagObj(BagDemo)
+    ...                                 # will call this method when any
+    ...                                 # attribute look-up is required
+    ...         result = "Doesn't matter what you want, "
+    ...         return result + "you're gonna get this"
+    ...
+    >>> demo_obj = BagDemo()
+    >>> bagobj = BO(demo_obj)
+    >>> bagobj.hello_there
+    "Doesn't matter what you want, you're gonna get this"
+    >>> bagobj.I_can_be_anything
+    "Doesn't matter what you want, you're gonna get this"
+
+    """
+
+    def __init__(self, obj):
+        # Use weakref to make NpzFile objects collectable by refcount
+        self._obj = weakref.proxy(obj)
+
+    def __getattribute__(self, key):
+        try:
+            return object.__getattribute__(self, '_obj')[key]
+        except KeyError:
+            raise AttributeError(key) from None
+
+    def __dir__(self):
+        """
+        Enables dir(bagobj) to list the files in an NpzFile.
+
+        This also enables tab-completion in an interpreter or IPython.
+        """
+        return list(object.__getattribute__(self, '_obj').keys())
+
+
+def zipfile_factory(file, *args, **kwargs):
+    """
+    Create a ZipFile.
+
+    Allows for Zip64, and the `file` argument can accept file, str, or
+    pathlib.Path objects. `args` and `kwargs` are passed to the zipfile.ZipFile
+    constructor.
+    """
+    if not hasattr(file, 'read'):
+        file = os.fspath(file)
+    import zipfile
+    kwargs['allowZip64'] = True
+    return zipfile.ZipFile(file, *args, **kwargs)
+
+
+@set_module('numpy.lib.npyio')
+class NpzFile(Mapping):
+    """
+    NpzFile(fid)
+
+    A dictionary-like object with lazy-loading of files in the zipped
+    archive provided on construction.
+
+    `NpzFile` is used to load files in the NumPy ``.npz`` data archive
+    format. It assumes that files in the archive have a ``.npy`` extension,
+    other files are ignored.
+
+    The arrays and file strings are lazily loaded on either
+    getitem access using ``obj['key']`` or attribute lookup using
+    ``obj.f.key``. A list of all files (without ``.npy`` extensions) can
+    be obtained with ``obj.files`` and the ZipFile object itself using
+    ``obj.zip``.
+
+    Attributes
+    ----------
+    files : list of str
+        List of all files in the archive with a ``.npy`` extension.
+    zip : ZipFile instance
+        The ZipFile object initialized with the zipped archive.
+    f : BagObj instance
+        An object on which attribute can be performed as an alternative
+        to getitem access on the `NpzFile` instance itself.
+    allow_pickle : bool, optional
+        Allow loading pickled data. Default: False
+    pickle_kwargs : dict, optional
+        Additional keyword arguments to pass on to pickle.load.
+        These are only useful when loading object arrays saved on
+        Python 2.
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+        This option is ignored when `allow_pickle` is passed.  In that case
+        the file is by definition trusted and the limit is unnecessary.
+
+    Parameters
+    ----------
+    fid : file, str, or pathlib.Path
+        The zipped archive to open. This is either a file-like object
+        or a string containing the path to the archive.
+    own_fid : bool, optional
+        Whether NpzFile should close the file handle.
+        Requires that `fid` is a file-like object.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from tempfile import TemporaryFile
+    >>> outfile = TemporaryFile()
+    >>> x = np.arange(10)
+    >>> y = np.sin(x)
+    >>> np.savez(outfile, x=x, y=y)
+    >>> _ = outfile.seek(0)
+
+    >>> npz = np.load(outfile)
+    >>> isinstance(npz, np.lib.npyio.NpzFile)
+    True
+    >>> npz
+    NpzFile 'object' with keys: x, y
+    >>> sorted(npz.files)
+    ['x', 'y']
+    >>> npz['x']  # getitem access
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+    >>> npz.f.x  # attribute lookup
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+
+    """
+    # Make __exit__ safe if zipfile_factory raises an exception
+    zip = None
+    fid = None
+    _MAX_REPR_ARRAY_COUNT = 5
+
+    def __init__(self, fid, own_fid=False, allow_pickle=False,
+                 pickle_kwargs=None, *,
+                 max_header_size=_MAX_HEADER_SIZE):
+        # Import is postponed to here since zipfile depends on gzip, an
+        # optional component of the so-called standard library.
+        _zip = zipfile_factory(fid)
+        _files = _zip.namelist()
+        self.files = [name.removesuffix(".npy") for name in _files]
+        self._files = dict(zip(self.files, _files))
+        self._files.update(zip(_files, _files))
+        self.allow_pickle = allow_pickle
+        self.max_header_size = max_header_size
+        self.pickle_kwargs = pickle_kwargs
+        self.zip = _zip
+        self.f = BagObj(self)
+        if own_fid:
+            self.fid = fid
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        self.close()
+
+    def close(self):
+        """
+        Close the file.
+
+        """
+        if self.zip is not None:
+            self.zip.close()
+            self.zip = None
+        if self.fid is not None:
+            self.fid.close()
+            self.fid = None
+        self.f = None  # break reference cycle
+
+    def __del__(self):
+        self.close()
+
+    # Implement the Mapping ABC
+    def __iter__(self):
+        return iter(self.files)
+
+    def __len__(self):
+        return len(self.files)
+
+    def __getitem__(self, key):
+        try:
+            key = self._files[key]
+        except KeyError:
+            raise KeyError(f"{key} is not a file in the archive") from None
+        else:
+            with self.zip.open(key) as bytes:
+                magic = bytes.read(len(format.MAGIC_PREFIX))
+                bytes.seek(0)
+                if magic == format.MAGIC_PREFIX:
+                    # FIXME: This seems like it will copy strings around
+                    #   more than is strictly necessary.  The zipfile
+                    #   will read the string and then
+                    #   the format.read_array will copy the string
+                    #   to another place in memory.
+                    #   It would be better if the zipfile could read
+                    #   (or at least uncompress) the data
+                    #   directly into the array memory.
+                    return format.read_array(
+                        bytes,
+                        allow_pickle=self.allow_pickle,
+                        pickle_kwargs=self.pickle_kwargs,
+                        max_header_size=self.max_header_size
+                    )
+                else:
+                    return bytes.read()
+
+    def __contains__(self, key):
+        return (key in self._files)
+
+    def __repr__(self):
+        # Get filename or default to `object`
+        if isinstance(self.fid, str):
+            filename = self.fid
+        else:
+            filename = getattr(self.fid, "name", "object")
+
+        # Get the name of arrays
+        array_names = ', '.join(self.files[:self._MAX_REPR_ARRAY_COUNT])
+        if len(self.files) > self._MAX_REPR_ARRAY_COUNT:
+            array_names += "..."
+        return f"NpzFile {filename!r} with keys: {array_names}"
+
+    # Work around problems with the docstrings in the Mapping methods
+    # They contain a `->`, which confuses the type annotation interpretations
+    # of sphinx-docs. See gh-25964
+
+    def get(self, key, default=None, /):
+        """
+        D.get(k,[,d]) returns D[k] if k in D, else d.  d defaults to None.
+        """
+        return Mapping.get(self, key, default)
+
+    def items(self):
+        """
+        D.items() returns a set-like object providing a view on the items
+        """
+        return Mapping.items(self)
+
+    def keys(self):
+        """
+        D.keys() returns a set-like object providing a view on the keys
+        """
+        return Mapping.keys(self)
+
+    def values(self):
+        """
+        D.values() returns a set-like object providing a view on the values
+        """
+        return Mapping.values(self)
+
+
+@set_module('numpy')
+def load(file, mmap_mode=None, allow_pickle=False, fix_imports=True,
+         encoding='ASCII', *, max_header_size=_MAX_HEADER_SIZE):
+    """
+    Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
+
+    .. warning:: Loading files that contain object arrays uses the ``pickle``
+                 module, which is not secure against erroneous or maliciously
+                 constructed data. Consider passing ``allow_pickle=False`` to
+                 load data that is known not to contain object arrays for the
+                 safer handling of untrusted sources.
+
+    Parameters
+    ----------
+    file : file-like object, string, or pathlib.Path
+        The file to read. File-like objects must support the
+        ``seek()`` and ``read()`` methods and must always
+        be opened in binary mode.  Pickled files require that the
+        file-like object support the ``readline()`` method as well.
+    mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional
+        If not None, then memory-map the file, using the given mode (see
+        `numpy.memmap` for a detailed description of the modes).  A
+        memory-mapped array is kept on disk. However, it can be accessed
+        and sliced like any ndarray.  Memory mapping is especially useful
+        for accessing small fragments of large files without reading the
+        entire file into memory.
+    allow_pickle : bool, optional
+        Allow loading pickled object arrays stored in npy files. Reasons for
+        disallowing pickles include security, as loading pickled data can
+        execute arbitrary code. If pickles are disallowed, loading object
+        arrays will fail. Default: False
+    fix_imports : bool, optional
+        Only useful when loading Python 2 generated pickled files,
+        which includes npy/npz files containing object arrays. If `fix_imports`
+        is True, pickle will try to map the old Python 2 names to the new names
+        used in Python 3.
+    encoding : str, optional
+        What encoding to use when reading Python 2 strings. Only useful when
+        loading Python 2 generated pickled files, which includes
+        npy/npz files containing object arrays. Values other than 'latin1',
+        'ASCII', and 'bytes' are not allowed, as they can corrupt numerical
+        data. Default: 'ASCII'
+    max_header_size : int, optional
+        Maximum allowed size of the header.  Large headers may not be safe
+        to load securely and thus require explicitly passing a larger value.
+        See :py:func:`ast.literal_eval()` for details.
+        This option is ignored when `allow_pickle` is passed.  In that case
+        the file is by definition trusted and the limit is unnecessary.
+
+    Returns
+    -------
+    result : array, tuple, dict, etc.
+        Data stored in the file. For ``.npz`` files, the returned instance
+        of NpzFile class must be closed to avoid leaking file descriptors.
+
+    Raises
+    ------
+    OSError
+        If the input file does not exist or cannot be read.
+    UnpicklingError
+        If ``allow_pickle=True``, but the file cannot be loaded as a pickle.
+    ValueError
+        The file contains an object array, but ``allow_pickle=False`` given.
+    EOFError
+        When calling ``np.load`` multiple times on the same file handle,
+        if all data has already been read
+
+    See Also
+    --------
+    save, savez, savez_compressed, loadtxt
+    memmap : Create a memory-map to an array stored in a file on disk.
+    lib.format.open_memmap : Create or load a memory-mapped ``.npy`` file.
+
+    Notes
+    -----
+    - If the file contains pickle data, then whatever object is stored
+      in the pickle is returned.
+    - If the file is a ``.npy`` file, then a single array is returned.
+    - If the file is a ``.npz`` file, then a dictionary-like object is
+      returned, containing ``{filename: array}`` key-value pairs, one for
+      each file in the archive.
+    - If the file is a ``.npz`` file, the returned value supports the
+      context manager protocol in a similar fashion to the open function::
+
+        with load('foo.npz') as data:
+            a = data['a']
+
+      The underlying file descriptor is closed when exiting the 'with'
+      block.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Store data to disk, and load it again:
+
+    >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]]))
+    >>> np.load('/tmp/123.npy')
+    array([[1, 2, 3],
+           [4, 5, 6]])
+
+    Store compressed data to disk, and load it again:
+
+    >>> a=np.array([[1, 2, 3], [4, 5, 6]])
+    >>> b=np.array([1, 2])
+    >>> np.savez('/tmp/123.npz', a=a, b=b)
+    >>> data = np.load('/tmp/123.npz')
+    >>> data['a']
+    array([[1, 2, 3],
+           [4, 5, 6]])
+    >>> data['b']
+    array([1, 2])
+    >>> data.close()
+
+    Mem-map the stored array, and then access the second row
+    directly from disk:
+
+    >>> X = np.load('/tmp/123.npy', mmap_mode='r')
+    >>> X[1, :]
+    memmap([4, 5, 6])
+
+    """
+    if encoding not in ('ASCII', 'latin1', 'bytes'):
+        # The 'encoding' value for pickle also affects what encoding
+        # the serialized binary data of NumPy arrays is loaded
+        # in. Pickle does not pass on the encoding information to
+        # NumPy. The unpickling code in numpy._core.multiarray is
+        # written to assume that unicode data appearing where binary
+        # should be is in 'latin1'. 'bytes' is also safe, as is 'ASCII'.
+        #
+        # Other encoding values can corrupt binary data, and we
+        # purposefully disallow them. For the same reason, the errors=
+        # argument is not exposed, as values other than 'strict'
+        # result can similarly silently corrupt numerical data.
+        raise ValueError("encoding must be 'ASCII', 'latin1', or 'bytes'")
+
+    pickle_kwargs = {'encoding': encoding, 'fix_imports': fix_imports}
+
+    with contextlib.ExitStack() as stack:
+        if hasattr(file, 'read'):
+            fid = file
+            own_fid = False
+        else:
+            fid = stack.enter_context(open(os.fspath(file), "rb"))
+            own_fid = True
+
+        # Code to distinguish from NumPy binary files and pickles.
+        _ZIP_PREFIX = b'PK\x03\x04'
+        _ZIP_SUFFIX = b'PK\x05\x06'  # empty zip files start with this
+        N = len(format.MAGIC_PREFIX)
+        magic = fid.read(N)
+        if not magic:
+            raise EOFError("No data left in file")
+        # If the file size is less than N, we need to make sure not
+        # to seek past the beginning of the file
+        fid.seek(-min(N, len(magic)), 1)  # back-up
+        if magic.startswith((_ZIP_PREFIX, _ZIP_SUFFIX)):
+            # zip-file (assume .npz)
+            # Potentially transfer file ownership to NpzFile
+            stack.pop_all()
+            ret = NpzFile(fid, own_fid=own_fid, allow_pickle=allow_pickle,
+                          pickle_kwargs=pickle_kwargs,
+                          max_header_size=max_header_size)
+            return ret
+        elif magic == format.MAGIC_PREFIX:
+            # .npy file
+            if mmap_mode:
+                if allow_pickle:
+                    max_header_size = 2**64
+                return format.open_memmap(file, mode=mmap_mode,
+                                          max_header_size=max_header_size)
+            else:
+                return format.read_array(fid, allow_pickle=allow_pickle,
+                                         pickle_kwargs=pickle_kwargs,
+                                         max_header_size=max_header_size)
+        else:
+            # Try a pickle
+            if not allow_pickle:
+                raise ValueError(
+                    "This file contains pickled (object) data. If you trust "
+                    "the file you can load it unsafely using the "
+                    "`allow_pickle=` keyword argument or `pickle.load()`.")
+            try:
+                return pickle.load(fid, **pickle_kwargs)
+            except Exception as e:
+                raise pickle.UnpicklingError(
+                    f"Failed to interpret file {file!r} as a pickle") from e
+
+
+def _save_dispatcher(file, arr, allow_pickle=None):
+    return (arr,)
+
+
+@array_function_dispatch(_save_dispatcher)
+def save(file, arr, allow_pickle=True):
+    """
+    Save an array to a binary file in NumPy ``.npy`` format.
+
+    Parameters
+    ----------
+    file : file, str, or pathlib.Path
+        File or filename to which the data is saved. If file is a file-object,
+        then the filename is unchanged.  If file is a string or Path,
+        a ``.npy`` extension will be appended to the filename if it does not
+        already have one.
+    arr : array_like
+        Array data to be saved.
+    allow_pickle : bool, optional
+        Allow saving object arrays using Python pickles. Reasons for
+        disallowing pickles include security (loading pickled data can execute
+        arbitrary code) and portability (pickled objects may not be loadable
+        on different Python installations, for example if the stored objects
+        require libraries that are not available, and not all pickled data is
+        compatible between different versions of Python).
+        Default: True
+
+    See Also
+    --------
+    savez : Save several arrays into a ``.npz`` archive
+    savetxt, load
+
+    Notes
+    -----
+    For a description of the ``.npy`` format, see :py:mod:`numpy.lib.format`.
+
+    Any data saved to the file is appended to the end of the file.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from tempfile import TemporaryFile
+    >>> outfile = TemporaryFile()
+
+    >>> x = np.arange(10)
+    >>> np.save(outfile, x)
+
+    >>> _ = outfile.seek(0) # Only needed to simulate closing & reopening file
+    >>> np.load(outfile)
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+
+
+    >>> with open('test.npy', 'wb') as f:
+    ...     np.save(f, np.array([1, 2]))
+    ...     np.save(f, np.array([1, 3]))
+    >>> with open('test.npy', 'rb') as f:
+    ...     a = np.load(f)
+    ...     b = np.load(f)
+    >>> print(a, b)
+    # [1 2] [1 3]
+    """
+    if hasattr(file, 'write'):
+        file_ctx = contextlib.nullcontext(file)
+    else:
+        file = os.fspath(file)
+        if not file.endswith('.npy'):
+            file = file + '.npy'
+        file_ctx = open(file, "wb")
+
+    with file_ctx as fid:
+        arr = np.asanyarray(arr)
+        format.write_array(fid, arr, allow_pickle=allow_pickle)
+
+
+def _savez_dispatcher(file, *args, allow_pickle=True, **kwds):
+    yield from args
+    yield from kwds.values()
+
+
+@array_function_dispatch(_savez_dispatcher)
+def savez(file, *args, allow_pickle=True, **kwds):
+    """Save several arrays into a single file in uncompressed ``.npz`` format.
+
+    Provide arrays as keyword arguments to store them under the
+    corresponding name in the output file: ``savez(fn, x=x, y=y)``.
+
+    If arrays are specified as positional arguments, i.e., ``savez(fn,
+    x, y)``, their names will be `arr_0`, `arr_1`, etc.
+
+    Parameters
+    ----------
+    file : file, str, or pathlib.Path
+        Either the filename (string) or an open file (file-like object)
+        where the data will be saved. If file is a string or a Path, the
+        ``.npz`` extension will be appended to the filename if it is not
+        already there.
+    args : Arguments, optional
+        Arrays to save to the file. Please use keyword arguments (see
+        `kwds` below) to assign names to arrays.  Arrays specified as
+        args will be named "arr_0", "arr_1", and so on.
+    allow_pickle : bool, optional
+        Allow saving object arrays using Python pickles. Reasons for
+        disallowing pickles include security (loading pickled data can execute
+        arbitrary code) and portability (pickled objects may not be loadable
+        on different Python installations, for example if the stored objects
+        require libraries that are not available, and not all pickled data is
+        compatible between different versions of Python).
+        Default: True
+    kwds : Keyword arguments, optional
+        Arrays to save to the file. Each array will be saved to the
+        output file with its corresponding keyword name.
+
+    Returns
+    -------
+    None
+
+    See Also
+    --------
+    save : Save a single array to a binary file in NumPy format.
+    savetxt : Save an array to a file as plain text.
+    savez_compressed : Save several arrays into a compressed ``.npz`` archive
+
+    Notes
+    -----
+    The ``.npz`` file format is a zipped archive of files named after the
+    variables they contain.  The archive is not compressed and each file
+    in the archive contains one variable in ``.npy`` format. For a
+    description of the ``.npy`` format, see :py:mod:`numpy.lib.format`.
+
+    When opening the saved ``.npz`` file with `load` a `~lib.npyio.NpzFile`
+    object is returned. This is a dictionary-like object which can be queried
+    for its list of arrays (with the ``.files`` attribute), and for the arrays
+    themselves.
+
+    Keys passed in `kwds` are used as filenames inside the ZIP archive.
+    Therefore, keys should be valid filenames; e.g., avoid keys that begin with
+    ``/`` or contain ``.``.
+
+    When naming variables with keyword arguments, it is not possible to name a
+    variable ``file``, as this would cause the ``file`` argument to be defined
+    twice in the call to ``savez``.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from tempfile import TemporaryFile
+    >>> outfile = TemporaryFile()
+    >>> x = np.arange(10)
+    >>> y = np.sin(x)
+
+    Using `savez` with \\*args, the arrays are saved with default names.
+
+    >>> np.savez(outfile, x, y)
+    >>> _ = outfile.seek(0) # Only needed to simulate closing & reopening file
+    >>> npzfile = np.load(outfile)
+    >>> npzfile.files
+    ['arr_0', 'arr_1']
+    >>> npzfile['arr_0']
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+
+    Using `savez` with \\**kwds, the arrays are saved with the keyword names.
+
+    >>> outfile = TemporaryFile()
+    >>> np.savez(outfile, x=x, y=y)
+    >>> _ = outfile.seek(0)
+    >>> npzfile = np.load(outfile)
+    >>> sorted(npzfile.files)
+    ['x', 'y']
+    >>> npzfile['x']
+    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+
+    """
+    _savez(file, args, kwds, False, allow_pickle=allow_pickle)
+
+
+def _savez_compressed_dispatcher(file, *args, allow_pickle=True, **kwds):
+    yield from args
+    yield from kwds.values()
+
+
+@array_function_dispatch(_savez_compressed_dispatcher)
+def savez_compressed(file, *args, allow_pickle=True, **kwds):
+    """
+    Save several arrays into a single file in compressed ``.npz`` format.
+
+    Provide arrays as keyword arguments to store them under the
+    corresponding name in the output file: ``savez_compressed(fn, x=x, y=y)``.
+
+    If arrays are specified as positional arguments, i.e.,
+    ``savez_compressed(fn, x, y)``, their names will be `arr_0`, `arr_1`, etc.
+
+    Parameters
+    ----------
+    file : file, str, or pathlib.Path
+        Either the filename (string) or an open file (file-like object)
+        where the data will be saved. If file is a string or a Path, the
+        ``.npz`` extension will be appended to the filename if it is not
+        already there.
+    args : Arguments, optional
+        Arrays to save to the file. Please use keyword arguments (see
+        `kwds` below) to assign names to arrays.  Arrays specified as
+        args will be named "arr_0", "arr_1", and so on.
+    allow_pickle : bool, optional
+        Allow saving object arrays using Python pickles. Reasons for
+        disallowing pickles include security (loading pickled data can execute
+        arbitrary code) and portability (pickled objects may not be loadable
+        on different Python installations, for example if the stored objects
+        require libraries that are not available, and not all pickled data is
+        compatible between different versions of Python).
+        Default: True
+    kwds : Keyword arguments, optional
+        Arrays to save to the file. Each array will be saved to the
+        output file with its corresponding keyword name.
+
+    Returns
+    -------
+    None
+
+    See Also
+    --------
+    numpy.save : Save a single array to a binary file in NumPy format.
+    numpy.savetxt : Save an array to a file as plain text.
+    numpy.savez : Save several arrays into an uncompressed ``.npz`` file format
+    numpy.load : Load the files created by savez_compressed.
+
+    Notes
+    -----
+    The ``.npz`` file format is a zipped archive of files named after the
+    variables they contain.  The archive is compressed with
+    ``zipfile.ZIP_DEFLATED`` and each file in the archive contains one variable
+    in ``.npy`` format. For a description of the ``.npy`` format, see
+    :py:mod:`numpy.lib.format`.
+
+
+    When opening the saved ``.npz`` file with `load` a `~lib.npyio.NpzFile`
+    object is returned. This is a dictionary-like object which can be queried
+    for its list of arrays (with the ``.files`` attribute), and for the arrays
+    themselves.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> test_array = np.random.rand(3, 2)
+    >>> test_vector = np.random.rand(4)
+    >>> np.savez_compressed('/tmp/123', a=test_array, b=test_vector)
+    >>> loaded = np.load('/tmp/123.npz')
+    >>> print(np.array_equal(test_array, loaded['a']))
+    True
+    >>> print(np.array_equal(test_vector, loaded['b']))
+    True
+
+    """
+    _savez(file, args, kwds, True, allow_pickle=allow_pickle)
+
+
+def _savez(file, args, kwds, compress, allow_pickle=True, pickle_kwargs=None):
+    # Import is postponed to here since zipfile depends on gzip, an optional
+    # component of the so-called standard library.
+    import zipfile
+
+    if not hasattr(file, 'write'):
+        file = os.fspath(file)
+        if not file.endswith('.npz'):
+            file = file + '.npz'
+
+    namedict = kwds
+    for i, val in enumerate(args):
+        key = 'arr_%d' % i
+        if key in namedict.keys():
+            raise ValueError(
+                f"Cannot use un-named variables and keyword {key}")
+        namedict[key] = val
+
+    if compress:
+        compression = zipfile.ZIP_DEFLATED
+    else:
+        compression = zipfile.ZIP_STORED
+
+    zipf = zipfile_factory(file, mode="w", compression=compression)
+    try:
+        for key, val in namedict.items():
+            fname = key + '.npy'
+            val = np.asanyarray(val)
+            # always force zip64, gh-10776
+            with zipf.open(fname, 'w', force_zip64=True) as fid:
+                format.write_array(fid, val,
+                                   allow_pickle=allow_pickle,
+                                   pickle_kwargs=pickle_kwargs)
+    finally:
+        zipf.close()
+
+
+def _ensure_ndmin_ndarray_check_param(ndmin):
+    """Just checks if the param ndmin is supported on
+        _ensure_ndmin_ndarray. It is intended to be used as
+        verification before running anything expensive.
+        e.g. loadtxt, genfromtxt
+    """
+    # Check correctness of the values of `ndmin`
+    if ndmin not in [0, 1, 2]:
+        raise ValueError(f"Illegal value of ndmin keyword: {ndmin}")
+
+def _ensure_ndmin_ndarray(a, *, ndmin: int):
+    """This is a helper function of loadtxt and genfromtxt to ensure
+        proper minimum dimension as requested
+
+        ndim : int. Supported values 1, 2, 3
+                    ^^ whenever this changes, keep in sync with
+                       _ensure_ndmin_ndarray_check_param
+    """
+    # Verify that the array has at least dimensions `ndmin`.
+    # Tweak the size and shape of the arrays - remove extraneous dimensions
+    if a.ndim > ndmin:
+        a = np.squeeze(a)
+    # and ensure we have the minimum number of dimensions asked for
+    # - has to be in this order for the odd case ndmin=1, a.squeeze().ndim=0
+    if a.ndim < ndmin:
+        if ndmin == 1:
+            a = np.atleast_1d(a)
+        elif ndmin == 2:
+            a = np.atleast_2d(a).T
+
+    return a
+
+
+# amount of lines loadtxt reads in one chunk, can be overridden for testing
+_loadtxt_chunksize = 50000
+
+
+def _check_nonneg_int(value, name="argument"):
+    try:
+        operator.index(value)
+    except TypeError:
+        raise TypeError(f"{name} must be an integer") from None
+    if value < 0:
+        raise ValueError(f"{name} must be nonnegative")
+
+
+def _preprocess_comments(iterable, comments, encoding):
+    """
+    Generator that consumes a line iterated iterable and strips out the
+    multiple (or multi-character) comments from lines.
+    This is a pre-processing step to achieve feature parity with loadtxt
+    (we assume that this feature is a nieche feature).
+    """
+    for line in iterable:
+        if isinstance(line, bytes):
+            # Need to handle conversion here, or the splitting would fail
+            line = line.decode(encoding)
+
+        for c in comments:
+            line = line.split(c, 1)[0]
+
+        yield line
+
+
+# The number of rows we read in one go if confronted with a parametric dtype
+_loadtxt_chunksize = 50000
+
+
+def _read(fname, *, delimiter=',', comment='#', quote='"',
+          imaginary_unit='j', usecols=None, skiplines=0,
+          max_rows=None, converters=None, ndmin=None, unpack=False,
+          dtype=np.float64, encoding=None):
+    r"""
+    Read a NumPy array from a text file.
+    This is a helper function for loadtxt.
+
+    Parameters
+    ----------
+    fname : file, str, or pathlib.Path
+        The filename or the file to be read.
+    delimiter : str, optional
+        Field delimiter of the fields in line of the file.
+        Default is a comma, ','.  If None any sequence of whitespace is
+        considered a delimiter.
+    comment : str or sequence of str or None, optional
+        Character that begins a comment.  All text from the comment
+        character to the end of the line is ignored.
+        Multiple comments or multiple-character comment strings are supported,
+        but may be slower and `quote` must be empty if used.
+        Use None to disable all use of comments.
+    quote : str or None, optional
+        Character that is used to quote string fields. Default is '"'
+        (a double quote). Use None to disable quote support.
+    imaginary_unit : str, optional
+        Character that represent the imaginary unit `sqrt(-1)`.
+        Default is 'j'.
+    usecols : array_like, optional
+        A one-dimensional array of integer column numbers.  These are the
+        columns from the file to be included in the array.  If this value
+        is not given, all the columns are used.
+    skiplines : int, optional
+        Number of lines to skip before interpreting the data in the file.
+    max_rows : int, optional
+        Maximum number of rows of data to read.  Default is to read the
+        entire file.
+    converters : dict or callable, optional
+        A function to parse all columns strings into the desired value, or
+        a dictionary mapping column number to a parser function.
+        E.g. if column 0 is a date string: ``converters = {0: datestr2num}``.
+        Converters can also be used to provide a default value for missing
+        data, e.g. ``converters = lambda s: float(s.strip() or 0)`` will
+        convert empty fields to 0.
+        Default: None
+    ndmin : int, optional
+        Minimum dimension of the array returned.
+        Allowed values are 0, 1 or 2.  Default is 0.
+    unpack : bool, optional
+        If True, the returned array is transposed, so that arguments may be
+        unpacked using ``x, y, z = read(...)``.  When used with a structured
+        data-type, arrays are returned for each field.  Default is False.
+    dtype : numpy data type
+        A NumPy dtype instance, can be a structured dtype to map to the
+        columns of the file.
+    encoding : str, optional
+        Encoding used to decode the inputfile. The special value 'bytes'
+        (the default) enables backwards-compatible behavior for `converters`,
+        ensuring that inputs to the converter functions are encoded
+        bytes objects. The special value 'bytes' has no additional effect if
+        ``converters=None``. If encoding is ``'bytes'`` or ``None``, the
+        default system encoding is used.
+
+    Returns
+    -------
+    ndarray
+        NumPy array.
+    """
+    # Handle special 'bytes' keyword for encoding
+    byte_converters = False
+    if encoding == 'bytes':
+        encoding = None
+        byte_converters = True
+
+    if dtype is None:
+        raise TypeError("a dtype must be provided.")
+    dtype = np.dtype(dtype)
+
+    read_dtype_via_object_chunks = None
+    if dtype.kind in 'SUM' and dtype in {
+            np.dtype("S0"), np.dtype("U0"), np.dtype("M8"), np.dtype("m8")}:
+        # This is a legacy "flexible" dtype.  We do not truly support
+        # parametric dtypes currently (no dtype discovery step in the core),
+        # but have to support these for backward compatibility.
+        read_dtype_via_object_chunks = dtype
+        dtype = np.dtype(object)
+
+    if usecols is not None:
+        # Allow usecols to be a single int or a sequence of ints, the C-code
+        # handles the rest
+        try:
+            usecols = list(usecols)
+        except TypeError:
+            usecols = [usecols]
+
+    _ensure_ndmin_ndarray_check_param(ndmin)
+
+    if comment is None:
+        comments = None
+    else:
+        # assume comments are a sequence of strings
+        if "" in comment:
+            raise ValueError(
+                "comments cannot be an empty string. Use comments=None to "
+                "disable comments."
+            )
+        comments = tuple(comment)
+        comment = None
+        if len(comments) == 0:
+            comments = None  # No comments at all
+        elif len(comments) == 1:
+            # If there is only one comment, and that comment has one character,
+            # the normal parsing can deal with it just fine.
+            if isinstance(comments[0], str) and len(comments[0]) == 1:
+                comment = comments[0]
+                comments = None
+        # Input validation if there are multiple comment characters
+        elif delimiter in comments:
+            raise TypeError(
+                f"Comment characters '{comments}' cannot include the "
+                f"delimiter '{delimiter}'"
+            )
+
+    # comment is now either a 1 or 0 character string or a tuple:
+    if comments is not None:
+        # Note: An earlier version support two character comments (and could
+        #       have been extended to multiple characters, we assume this is
+        #       rare enough to not optimize for.
+        if quote is not None:
+            raise ValueError(
+                "when multiple comments or a multi-character comment is "
+                "given, quotes are not supported.  In this case quotechar "
+                "must be set to None.")
+
+    if len(imaginary_unit) != 1:
+        raise ValueError('len(imaginary_unit) must be 1.')
+
+    _check_nonneg_int(skiplines)
+    if max_rows is not None:
+        _check_nonneg_int(max_rows)
+    else:
+        # Passing -1 to the C code means "read the entire file".
+        max_rows = -1
+
+    fh_closing_ctx = contextlib.nullcontext()
+    filelike = False
+    try:
+        if isinstance(fname, os.PathLike):
+            fname = os.fspath(fname)
+        if isinstance(fname, str):
+            fh = np.lib._datasource.open(fname, 'rt', encoding=encoding)
+            if encoding is None:
+                encoding = getattr(fh, 'encoding', 'latin1')
+
+            fh_closing_ctx = contextlib.closing(fh)
+            data = fh
+            filelike = True
+        else:
+            if encoding is None:
+                encoding = getattr(fname, 'encoding', 'latin1')
+            data = iter(fname)
+    except TypeError as e:
+        raise ValueError(
+            f"fname must be a string, filehandle, list of strings,\n"
+            f"or generator. Got {type(fname)} instead.") from e
+
+    with fh_closing_ctx:
+        if comments is not None:
+            if filelike:
+                data = iter(data)
+                filelike = False
+            data = _preprocess_comments(data, comments, encoding)
+
+        if read_dtype_via_object_chunks is None:
+            arr = _load_from_filelike(
+                data, delimiter=delimiter, comment=comment, quote=quote,
+                imaginary_unit=imaginary_unit,
+                usecols=usecols, skiplines=skiplines, max_rows=max_rows,
+                converters=converters, dtype=dtype,
+                encoding=encoding, filelike=filelike,
+                byte_converters=byte_converters)
+
+        else:
+            # This branch reads the file into chunks of object arrays and then
+            # casts them to the desired actual dtype.  This ensures correct
+            # string-length and datetime-unit discovery (like `arr.astype()`).
+            # Due to chunking, certain error reports are less clear, currently.
+            if filelike:
+                data = iter(data)  # cannot chunk when reading from file
+                filelike = False
+
+            c_byte_converters = False
+            if read_dtype_via_object_chunks == "S":
+                c_byte_converters = True  # Use latin1 rather than ascii
+
+            chunks = []
+            while max_rows != 0:
+                if max_rows < 0:
+                    chunk_size = _loadtxt_chunksize
+                else:
+                    chunk_size = min(_loadtxt_chunksize, max_rows)
+
+                next_arr = _load_from_filelike(
+                    data, delimiter=delimiter, comment=comment, quote=quote,
+                    imaginary_unit=imaginary_unit,
+                    usecols=usecols, skiplines=skiplines, max_rows=chunk_size,
+                    converters=converters, dtype=dtype,
+                    encoding=encoding, filelike=filelike,
+                    byte_converters=byte_converters,
+                    c_byte_converters=c_byte_converters)
+                # Cast here already.  We hope that this is better even for
+                # large files because the storage is more compact.  It could
+                # be adapted (in principle the concatenate could cast).
+                chunks.append(next_arr.astype(read_dtype_via_object_chunks))
+
+                skiplines = 0  # Only have to skip for first chunk
+                if max_rows >= 0:
+                    max_rows -= chunk_size
+                if len(next_arr) < chunk_size:
+                    # There was less data than requested, so we are done.
+                    break
+
+            # Need at least one chunk, but if empty, the last one may have
+            # the wrong shape.
+            if len(chunks) > 1 and len(chunks[-1]) == 0:
+                del chunks[-1]
+            if len(chunks) == 1:
+                arr = chunks[0]
+            else:
+                arr = np.concatenate(chunks, axis=0)
+
+    # NOTE: ndmin works as advertised for structured dtypes, but normally
+    #       these would return a 1D result plus the structured dimension,
+    #       so ndmin=2 adds a third dimension even when no squeezing occurs.
+    #       A `squeeze=False` could be a better solution (pandas uses squeeze).
+    arr = _ensure_ndmin_ndarray(arr, ndmin=ndmin)
+
+    if arr.shape:
+        if arr.shape[0] == 0:
+            warnings.warn(
+                f'loadtxt: input contained no data: "{fname}"',
+                category=UserWarning,
+                stacklevel=3
+            )
+
+    if unpack:
+        # Unpack structured dtypes if requested:
+        dt = arr.dtype
+        if dt.names is not None:
+            # For structured arrays, return an array for each field.
+            return [arr[field] for field in dt.names]
+        else:
+            return arr.T
+    else:
+        return arr
+
+
+@finalize_array_function_like
+@set_module('numpy')
+def loadtxt(fname, dtype=float, comments='#', delimiter=None,
+            converters=None, skiprows=0, usecols=None, unpack=False,
+            ndmin=0, encoding=None, max_rows=None, *, quotechar=None,
+            like=None):
+    r"""
+    Load data from a text file.
+
+    Parameters
+    ----------
+    fname : file, str, pathlib.Path, list of str, generator
+        File, filename, list, or generator to read.  If the filename
+        extension is ``.gz`` or ``.bz2``, the file is first decompressed. Note
+        that generators must return bytes or strings. The strings
+        in a list or produced by a generator are treated as lines.
+    dtype : data-type, optional
+        Data-type of the resulting array; default: float.  If this is a
+        structured data-type, the resulting array will be 1-dimensional, and
+        each row will be interpreted as an element of the array.  In this
+        case, the number of columns used must match the number of fields in
+        the data-type.
+    comments : str or sequence of str or None, optional
+        The characters or list of characters used to indicate the start of a
+        comment. None implies no comments. For backwards compatibility, byte
+        strings will be decoded as 'latin1'. The default is '#'.
+    delimiter : str, optional
+        The character used to separate the values. For backwards compatibility,
+        byte strings will be decoded as 'latin1'. The default is whitespace.
+
+        .. versionchanged:: 1.23.0
+           Only single character delimiters are supported. Newline characters
+           cannot be used as the delimiter.
+
+    converters : dict or callable, optional
+        Converter functions to customize value parsing. If `converters` is
+        callable, the function is applied to all columns, else it must be a
+        dict that maps column number to a parser function.
+        See examples for further details.
+        Default: None.
+
+        .. versionchanged:: 1.23.0
+           The ability to pass a single callable to be applied to all columns
+           was added.
+
+    skiprows : int, optional
+        Skip the first `skiprows` lines, including comments; default: 0.
+    usecols : int or sequence, optional
+        Which columns to read, with 0 being the first. For example,
+        ``usecols = (1,4,5)`` will extract the 2nd, 5th and 6th columns.
+        The default, None, results in all columns being read.
+    unpack : bool, optional
+        If True, the returned array is transposed, so that arguments may be
+        unpacked using ``x, y, z = loadtxt(...)``.  When used with a
+        structured data-type, arrays are returned for each field.
+        Default is False.
+    ndmin : int, optional
+        The returned array will have at least `ndmin` dimensions.
+        Otherwise mono-dimensional axes will be squeezed.
+        Legal values: 0 (default), 1 or 2.
+    encoding : str, optional
+        Encoding used to decode the inputfile. Does not apply to input streams.
+        The special value 'bytes' enables backward compatibility workarounds
+        that ensures you receive byte arrays as results if possible and passes
+        'latin1' encoded strings to converters. Override this value to receive
+        unicode arrays and pass strings as input to converters.  If set to None
+        the system default is used. The default value is None.
+
+        .. versionchanged:: 2.0
+            Before NumPy 2, the default was ``'bytes'`` for Python 2
+            compatibility. The default is now ``None``.
+
+    max_rows : int, optional
+        Read `max_rows` rows of content after `skiprows` lines. The default is
+        to read all the rows. Note that empty rows containing no data such as
+        empty lines and comment lines are not counted towards `max_rows`,
+        while such lines are counted in `skiprows`.
+
+        .. versionchanged:: 1.23.0
+            Lines containing no data, including comment lines (e.g., lines
+            starting with '#' or as specified via `comments`) are not counted
+            towards `max_rows`.
+    quotechar : unicode character or None, optional
+        The character used to denote the start and end of a quoted item.
+        Occurrences of the delimiter or comment characters are ignored within
+        a quoted item. The default value is ``quotechar=None``, which means
+        quoting support is disabled.
+
+        If two consecutive instances of `quotechar` are found within a quoted
+        field, the first is treated as an escape character. See examples.
+
+        .. versionadded:: 1.23.0
+    ${ARRAY_FUNCTION_LIKE}
+
+        .. versionadded:: 1.20.0
+
+    Returns
+    -------
+    out : ndarray
+        Data read from the text file.
+
+    See Also
+    --------
+    load, fromstring, fromregex
+    genfromtxt : Load data with missing values handled as specified.
+    scipy.io.loadmat : reads MATLAB data files
+
+    Notes
+    -----
+    This function aims to be a fast reader for simply formatted files.  The
+    `genfromtxt` function provides more sophisticated handling of, e.g.,
+    lines with missing values.
+
+    Each row in the input text file must have the same number of values to be
+    able to read all values. If all rows do not have same number of values, a
+    subset of up to n columns (where n is the least number of values present
+    in all rows) can be read by specifying the columns via `usecols`.
+
+    The strings produced by the Python float.hex method can be used as
+    input for floats.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from io import StringIO   # StringIO behaves like a file object
+    >>> c = StringIO("0 1\n2 3")
+    >>> np.loadtxt(c)
+    array([[0., 1.],
+           [2., 3.]])
+
+    >>> d = StringIO("M 21 72\nF 35 58")
+    >>> np.loadtxt(d, dtype={'names': ('gender', 'age', 'weight'),
+    ...                      'formats': ('S1', 'i4', 'f4')})
+    array([(b'M', 21, 72.), (b'F', 35, 58.)],
+          dtype=[('gender', 'S1'), ('age', '<i4'), ('weight', '<f4')])
+
+    >>> c = StringIO("1,0,2\n3,0,4")
+    >>> x, y = np.loadtxt(c, delimiter=',', usecols=(0, 2), unpack=True)
+    >>> x
+    array([1., 3.])
+    >>> y
+    array([2., 4.])
+
+    The `converters` argument is used to specify functions to preprocess the
+    text prior to parsing. `converters` can be a dictionary that maps
+    preprocessing functions to each column:
+
+    >>> s = StringIO("1.618, 2.296\n3.141, 4.669\n")
+    >>> conv = {
+    ...     0: lambda x: np.floor(float(x)),  # conversion fn for column 0
+    ...     1: lambda x: np.ceil(float(x)),  # conversion fn for column 1
+    ... }
+    >>> np.loadtxt(s, delimiter=",", converters=conv)
+    array([[1., 3.],
+           [3., 5.]])
+
+    `converters` can be a callable instead of a dictionary, in which case it
+    is applied to all columns:
+
+    >>> s = StringIO("0xDE 0xAD\n0xC0 0xDE")
+    >>> import functools
+    >>> conv = functools.partial(int, base=16)
+    >>> np.loadtxt(s, converters=conv)
+    array([[222., 173.],
+           [192., 222.]])
+
+    This example shows how `converters` can be used to convert a field
+    with a trailing minus sign into a negative number.
+
+    >>> s = StringIO("10.01 31.25-\n19.22 64.31\n17.57- 63.94")
+    >>> def conv(fld):
+    ...     return -float(fld[:-1]) if fld.endswith("-") else float(fld)
+    ...
+    >>> np.loadtxt(s, converters=conv)
+    array([[ 10.01, -31.25],
+           [ 19.22,  64.31],
+           [-17.57,  63.94]])
+
+    Using a callable as the converter can be particularly useful for handling
+    values with different formatting, e.g. floats with underscores:
+
+    >>> s = StringIO("1 2.7 100_000")
+    >>> np.loadtxt(s, converters=float)
+    array([1.e+00, 2.7e+00, 1.e+05])
+
+    This idea can be extended to automatically handle values specified in
+    many different formats, such as hex values:
+
+    >>> def conv(val):
+    ...     try:
+    ...         return float(val)
+    ...     except ValueError:
+    ...         return float.fromhex(val)
+    >>> s = StringIO("1, 2.5, 3_000, 0b4, 0x1.4000000000000p+2")
+    >>> np.loadtxt(s, delimiter=",", converters=conv)
+    array([1.0e+00, 2.5e+00, 3.0e+03, 1.8e+02, 5.0e+00])
+
+    Or a format where the ``-`` sign comes after the number:
+
+    >>> s = StringIO("10.01 31.25-\n19.22 64.31\n17.57- 63.94")
+    >>> conv = lambda x: -float(x[:-1]) if x.endswith("-") else float(x)
+    >>> np.loadtxt(s, converters=conv)
+    array([[ 10.01, -31.25],
+           [ 19.22,  64.31],
+           [-17.57,  63.94]])
+
+    Support for quoted fields is enabled with the `quotechar` parameter.
+    Comment and delimiter characters are ignored when they appear within a
+    quoted item delineated by `quotechar`:
+
+    >>> s = StringIO('"alpha, #42", 10.0\n"beta, #64", 2.0\n')
+    >>> dtype = np.dtype([("label", "U12"), ("value", float)])
+    >>> np.loadtxt(s, dtype=dtype, delimiter=",", quotechar='"')
+    array([('alpha, #42', 10.), ('beta, #64',  2.)],
+          dtype=[('label', '<U12'), ('value', '<f8')])
+
+    Quoted fields can be separated by multiple whitespace characters:
+
+    >>> s = StringIO('"alpha, #42"       10.0\n"beta, #64" 2.0\n')
+    >>> dtype = np.dtype([("label", "U12"), ("value", float)])
+    >>> np.loadtxt(s, dtype=dtype, delimiter=None, quotechar='"')
+    array([('alpha, #42', 10.), ('beta, #64',  2.)],
+          dtype=[('label', '<U12'), ('value', '<f8')])
+
+    Two consecutive quote characters within a quoted field are treated as a
+    single escaped character:
+
+    >>> s = StringIO('"Hello, my name is ""Monty""!"')
+    >>> np.loadtxt(s, dtype="U", delimiter=",", quotechar='"')
+    array('Hello, my name is "Monty"!', dtype='<U26')
+
+    Read subset of columns when all rows do not contain equal number of values:
+
+    >>> d = StringIO("1 2\n2 4\n3 9 12\n4 16 20")
+    >>> np.loadtxt(d, usecols=(0, 1))
+    array([[ 1.,  2.],
+           [ 2.,  4.],
+           [ 3.,  9.],
+           [ 4., 16.]])
+
+    """
+
+    if like is not None:
+        return _loadtxt_with_like(
+            like, fname, dtype=dtype, comments=comments, delimiter=delimiter,
+            converters=converters, skiprows=skiprows, usecols=usecols,
+            unpack=unpack, ndmin=ndmin, encoding=encoding,
+            max_rows=max_rows
+        )
+
+    if isinstance(delimiter, bytes):
+        delimiter.decode("latin1")
+
+    if dtype is None:
+        dtype = np.float64
+
+    comment = comments
+    # Control character type conversions for Py3 convenience
+    if comment is not None:
+        if isinstance(comment, (str, bytes)):
+            comment = [comment]
+        comment = [
+            x.decode('latin1') if isinstance(x, bytes) else x for x in comment]
+    if isinstance(delimiter, bytes):
+        delimiter = delimiter.decode('latin1')
+
+    arr = _read(fname, dtype=dtype, comment=comment, delimiter=delimiter,
+                converters=converters, skiplines=skiprows, usecols=usecols,
+                unpack=unpack, ndmin=ndmin, encoding=encoding,
+                max_rows=max_rows, quote=quotechar)
+
+    return arr
+
+
+_loadtxt_with_like = array_function_dispatch()(loadtxt)
+
+
+def _savetxt_dispatcher(fname, X, fmt=None, delimiter=None, newline=None,
+                        header=None, footer=None, comments=None,
+                        encoding=None):
+    return (X,)
+
+
+@array_function_dispatch(_savetxt_dispatcher)
+def savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\n', header='',
+            footer='', comments='# ', encoding=None):
+    """
+    Save an array to a text file.
+
+    Parameters
+    ----------
+    fname : filename, file handle or pathlib.Path
+        If the filename ends in ``.gz``, the file is automatically saved in
+        compressed gzip format.  `loadtxt` understands gzipped files
+        transparently.
+    X : 1D or 2D array_like
+        Data to be saved to a text file.
+    fmt : str or sequence of strs, optional
+        A single format (%10.5f), a sequence of formats, or a
+        multi-format string, e.g. 'Iteration %d -- %10.5f', in which
+        case `delimiter` is ignored. For complex `X`, the legal options
+        for `fmt` are:
+
+        * a single specifier, ``fmt='%.4e'``, resulting in numbers formatted
+          like ``' (%s+%sj)' % (fmt, fmt)``
+        * a full string specifying every real and imaginary part, e.g.
+          ``' %.4e %+.4ej %.4e %+.4ej %.4e %+.4ej'`` for 3 columns
+        * a list of specifiers, one per column - in this case, the real
+          and imaginary part must have separate specifiers,
+          e.g. ``['%.3e + %.3ej', '(%.15e%+.15ej)']`` for 2 columns
+    delimiter : str, optional
+        String or character separating columns.
+    newline : str, optional
+        String or character separating lines.
+    header : str, optional
+        String that will be written at the beginning of the file.
+    footer : str, optional
+        String that will be written at the end of the file.
+    comments : str, optional
+        String that will be prepended to the ``header`` and ``footer`` strings,
+        to mark them as comments. Default: '# ',  as expected by e.g.
+        ``numpy.loadtxt``.
+    encoding : {None, str}, optional
+        Encoding used to encode the outputfile. Does not apply to output
+        streams. If the encoding is something other than 'bytes' or 'latin1'
+        you will not be able to load the file in NumPy versions < 1.14. Default
+        is 'latin1'.
+
+    See Also
+    --------
+    save : Save an array to a binary file in NumPy ``.npy`` format
+    savez : Save several arrays into an uncompressed ``.npz`` archive
+    savez_compressed : Save several arrays into a compressed ``.npz`` archive
+
+    Notes
+    -----
+    Further explanation of the `fmt` parameter
+    (``%[flag]width[.precision]specifier``):
+
+    flags:
+        ``-`` : left justify
+
+        ``+`` : Forces to precede result with + or -.
+
+        ``0`` : Left pad the number with zeros instead of space (see width).
+
+    width:
+        Minimum number of characters to be printed. The value is not truncated
+        if it has more characters.
+
+    precision:
+        - For integer specifiers (eg. ``d,i,o,x``), the minimum number of
+          digits.
+        - For ``e, E`` and ``f`` specifiers, the number of digits to print
+          after the decimal point.
+        - For ``g`` and ``G``, the maximum number of significant digits.
+        - For ``s``, the maximum number of characters.
+
+    specifiers:
+        ``c`` : character
+
+        ``d`` or ``i`` : signed decimal integer
+
+        ``e`` or ``E`` : scientific notation with ``e`` or ``E``.
+
+        ``f`` : decimal floating point
+
+        ``g,G`` : use the shorter of ``e,E`` or ``f``
+
+        ``o`` : signed octal
+
+        ``s`` : string of characters
+
+        ``u`` : unsigned decimal integer
+
+        ``x,X`` : unsigned hexadecimal integer
+
+    This explanation of ``fmt`` is not complete, for an exhaustive
+    specification see [1]_.
+
+    References
+    ----------
+    .. [1] `Format Specification Mini-Language
+           <https://docs.python.org/library/string.html#format-specification-mini-language>`_,
+           Python Documentation.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = y = z = np.arange(0.0,5.0,1.0)
+    >>> np.savetxt('test.out', x, delimiter=',')   # X is an array
+    >>> np.savetxt('test.out', (x,y,z))   # x,y,z equal sized 1D arrays
+    >>> np.savetxt('test.out', x, fmt='%1.4e')   # use exponential notation
+
+    """
+
+    class WriteWrap:
+        """Convert to bytes on bytestream inputs.
+
+        """
+        def __init__(self, fh, encoding):
+            self.fh = fh
+            self.encoding = encoding
+            self.do_write = self.first_write
+
+        def close(self):
+            self.fh.close()
+
+        def write(self, v):
+            self.do_write(v)
+
+        def write_bytes(self, v):
+            if isinstance(v, bytes):
+                self.fh.write(v)
+            else:
+                self.fh.write(v.encode(self.encoding))
+
+        def write_normal(self, v):
+            self.fh.write(asunicode(v))
+
+        def first_write(self, v):
+            try:
+                self.write_normal(v)
+                self.write = self.write_normal
+            except TypeError:
+                # input is probably a bytestream
+                self.write_bytes(v)
+                self.write = self.write_bytes
+
+    own_fh = False
+    if isinstance(fname, os.PathLike):
+        fname = os.fspath(fname)
+    if _is_string_like(fname):
+        # datasource doesn't support creating a new file ...
+        open(fname, 'wt').close()
+        fh = np.lib._datasource.open(fname, 'wt', encoding=encoding)
+        own_fh = True
+    elif hasattr(fname, 'write'):
+        # wrap to handle byte output streams
+        fh = WriteWrap(fname, encoding or 'latin1')
+    else:
+        raise ValueError('fname must be a string or file handle')
+
+    try:
+        X = np.asarray(X)
+
+        # Handle 1-dimensional arrays
+        if X.ndim == 0 or X.ndim > 2:
+            raise ValueError(
+                "Expected 1D or 2D array, got %dD array instead" % X.ndim)
+        elif X.ndim == 1:
+            # Common case -- 1d array of numbers
+            if X.dtype.names is None:
+                X = np.atleast_2d(X).T
+                ncol = 1
+
+            # Complex dtype -- each field indicates a separate column
+            else:
+                ncol = len(X.dtype.names)
+        else:
+            ncol = X.shape[1]
+
+        iscomplex_X = np.iscomplexobj(X)
+        # `fmt` can be a string with multiple insertion points or a
+        # list of formats.  E.g. '%10.5f\t%10d' or ('%10.5f', '$10d')
+        if type(fmt) in (list, tuple):
+            if len(fmt) != ncol:
+                raise AttributeError(f'fmt has wrong shape.  {str(fmt)}')
+            format = delimiter.join(fmt)
+        elif isinstance(fmt, str):
+            n_fmt_chars = fmt.count('%')
+            error = ValueError(f'fmt has wrong number of % formats:  {fmt}')
+            if n_fmt_chars == 1:
+                if iscomplex_X:
+                    fmt = [f' ({fmt}+{fmt}j)', ] * ncol
+                else:
+                    fmt = [fmt, ] * ncol
+                format = delimiter.join(fmt)
+            elif iscomplex_X and n_fmt_chars != (2 * ncol):
+                raise error
+            elif ((not iscomplex_X) and n_fmt_chars != ncol):
+                raise error
+            else:
+                format = fmt
+        else:
+            raise ValueError(f'invalid fmt: {fmt!r}')
+
+        if len(header) > 0:
+            header = header.replace('\n', '\n' + comments)
+            fh.write(comments + header + newline)
+        if iscomplex_X:
+            for row in X:
+                row2 = []
+                for number in row:
+                    row2.extend((number.real, number.imag))
+                s = format % tuple(row2) + newline
+                fh.write(s.replace('+-', '-'))
+        else:
+            for row in X:
+                try:
+                    v = format % tuple(row) + newline
+                except TypeError as e:
+                    raise TypeError("Mismatch between array dtype ('%s') and "
+                                    "format specifier ('%s')"
+                                    % (str(X.dtype), format)) from e
+                fh.write(v)
+
+        if len(footer) > 0:
+            footer = footer.replace('\n', '\n' + comments)
+            fh.write(comments + footer + newline)
+    finally:
+        if own_fh:
+            fh.close()
+
+
+@set_module('numpy')
+def fromregex(file, regexp, dtype, encoding=None):
+    r"""
+    Construct an array from a text file, using regular expression parsing.
+
+    The returned array is always a structured array, and is constructed from
+    all matches of the regular expression in the file. Groups in the regular
+    expression are converted to fields of the structured array.
+
+    Parameters
+    ----------
+    file : file, str, or pathlib.Path
+        Filename or file object to read.
+
+        .. versionchanged:: 1.22.0
+            Now accepts `os.PathLike` implementations.
+
+    regexp : str or regexp
+        Regular expression used to parse the file.
+        Groups in the regular expression correspond to fields in the dtype.
+    dtype : dtype or list of dtypes
+        Dtype for the structured array; must be a structured datatype.
+    encoding : str, optional
+        Encoding used to decode the inputfile. Does not apply to input streams.
+
+    Returns
+    -------
+    output : ndarray
+        The output array, containing the part of the content of `file` that
+        was matched by `regexp`. `output` is always a structured array.
+
+    Raises
+    ------
+    TypeError
+        When `dtype` is not a valid dtype for a structured array.
+
+    See Also
+    --------
+    fromstring, loadtxt
+
+    Notes
+    -----
+    Dtypes for structured arrays can be specified in several forms, but all
+    forms specify at least the data type and field name. For details see
+    `basics.rec`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from io import StringIO
+    >>> text = StringIO("1312 foo\n1534  bar\n444   qux")
+
+    >>> regexp = r"(\d+)\s+(...)"  # match [digits, whitespace, anything]
+    >>> output = np.fromregex(text, regexp,
+    ...                       [('num', np.int64), ('key', 'S3')])
+    >>> output
+    array([(1312, b'foo'), (1534, b'bar'), ( 444, b'qux')],
+          dtype=[('num', '<i8'), ('key', 'S3')])
+    >>> output['num']
+    array([1312, 1534,  444])
+
+    """
+    own_fh = False
+    if not hasattr(file, "read"):
+        file = os.fspath(file)
+        file = np.lib._datasource.open(file, 'rt', encoding=encoding)
+        own_fh = True
+
+    try:
+        if not isinstance(dtype, np.dtype):
+            dtype = np.dtype(dtype)
+        if dtype.names is None:
+            raise TypeError('dtype must be a structured datatype.')
+
+        content = file.read()
+        if isinstance(content, bytes) and isinstance(regexp, str):
+            regexp = asbytes(regexp)
+
+        if not hasattr(regexp, 'match'):
+            regexp = re.compile(regexp)
+        seq = regexp.findall(content)
+        if seq and not isinstance(seq[0], tuple):
+            # Only one group is in the regexp.
+            # Create the new array as a single data-type and then
+            #   re-interpret as a single-field structured array.
+            newdtype = np.dtype(dtype[dtype.names[0]])
+            output = np.array(seq, dtype=newdtype)
+            output = output.view(dtype)
+        else:
+            output = np.array(seq, dtype=dtype)
+
+        return output
+    finally:
+        if own_fh:
+            file.close()
+
+
+#####--------------------------------------------------------------------------
+#---- --- ASCII functions ---
+#####--------------------------------------------------------------------------
+
+
+@finalize_array_function_like
+@set_module('numpy')
+def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
+               skip_header=0, skip_footer=0, converters=None,
+               missing_values=None, filling_values=None, usecols=None,
+               names=None, excludelist=None,
+               deletechars=''.join(sorted(NameValidator.defaultdeletechars)),  # noqa: B008
+               replace_space='_', autostrip=False, case_sensitive=True,
+               defaultfmt="f%i", unpack=None, usemask=False, loose=True,
+               invalid_raise=True, max_rows=None, encoding=None,
+               *, ndmin=0, like=None):
+    """
+    Load data from a text file, with missing values handled as specified.
+
+    Each line past the first `skip_header` lines is split at the `delimiter`
+    character, and characters following the `comments` character are discarded.
+
+    Parameters
+    ----------
+    fname : file, str, pathlib.Path, list of str, generator
+        File, filename, list, or generator to read.  If the filename
+        extension is ``.gz`` or ``.bz2``, the file is first decompressed. Note
+        that generators must return bytes or strings. The strings
+        in a list or produced by a generator are treated as lines.
+    dtype : dtype, optional
+        Data type of the resulting array.
+        If None, the dtypes will be determined by the contents of each
+        column, individually.
+    comments : str, optional
+        The character used to indicate the start of a comment.
+        All the characters occurring on a line after a comment are discarded.
+    delimiter : str, int, or sequence, optional
+        The string used to separate values.  By default, any consecutive
+        whitespaces act as delimiter.  An integer or sequence of integers
+        can also be provided as width(s) of each field.
+    skiprows : int, optional
+        `skiprows` was removed in numpy 1.10. Please use `skip_header` instead.
+    skip_header : int, optional
+        The number of lines to skip at the beginning of the file.
+    skip_footer : int, optional
+        The number of lines to skip at the end of the file.
+    converters : variable, optional
+        The set of functions that convert the data of a column to a value.
+        The converters can also be used to provide a default value
+        for missing data: ``converters = {3: lambda s: float(s or 0)}``.
+    missing : variable, optional
+        `missing` was removed in numpy 1.10. Please use `missing_values`
+        instead.
+    missing_values : variable, optional
+        The set of strings corresponding to missing data.
+    filling_values : variable, optional
+        The set of values to be used as default when the data are missing.
+    usecols : sequence, optional
+        Which columns to read, with 0 being the first.  For example,
+        ``usecols = (1, 4, 5)`` will extract the 2nd, 5th and 6th columns.
+    names : {None, True, str, sequence}, optional
+        If `names` is True, the field names are read from the first line after
+        the first `skip_header` lines. This line can optionally be preceded
+        by a comment delimiter. Any content before the comment delimiter is
+        discarded. If `names` is a sequence or a single-string of
+        comma-separated names, the names will be used to define the field
+        names in a structured dtype. If `names` is None, the names of the
+        dtype fields will be used, if any.
+    excludelist : sequence, optional
+        A list of names to exclude. This list is appended to the default list
+        ['return','file','print']. Excluded names are appended with an
+        underscore: for example, `file` would become `file_`.
+    deletechars : str, optional
+        A string combining invalid characters that must be deleted from the
+        names.
+    defaultfmt : str, optional
+        A format used to define default field names, such as "f%i" or "f_%02i".
+    autostrip : bool, optional
+        Whether to automatically strip white spaces from the variables.
+    replace_space : char, optional
+        Character(s) used in replacement of white spaces in the variable
+        names. By default, use a '_'.
+    case_sensitive : {True, False, 'upper', 'lower'}, optional
+        If True, field names are case sensitive.
+        If False or 'upper', field names are converted to upper case.
+        If 'lower', field names are converted to lower case.
+    unpack : bool, optional
+        If True, the returned array is transposed, so that arguments may be
+        unpacked using ``x, y, z = genfromtxt(...)``.  When used with a
+        structured data-type, arrays are returned for each field.
+        Default is False.
+    usemask : bool, optional
+        If True, return a masked array.
+        If False, return a regular array.
+    loose : bool, optional
+        If True, do not raise errors for invalid values.
+    invalid_raise : bool, optional
+        If True, an exception is raised if an inconsistency is detected in the
+        number of columns.
+        If False, a warning is emitted and the offending lines are skipped.
+    max_rows : int,  optional
+        The maximum number of rows to read. Must not be used with skip_footer
+        at the same time.  If given, the value must be at least 1. Default is
+        to read the entire file.
+    encoding : str, optional
+        Encoding used to decode the inputfile. Does not apply when `fname`
+        is a file object. The special value 'bytes' enables backward
+        compatibility workarounds that ensure that you receive byte arrays
+        when possible and passes latin1 encoded strings to converters.
+        Override this value to receive unicode arrays and pass strings
+        as input to converters.  If set to None the system default is used.
+        The default value is 'bytes'.
+
+        .. versionchanged:: 2.0
+            Before NumPy 2, the default was ``'bytes'`` for Python 2
+            compatibility. The default is now ``None``.
+
+    ndmin : int, optional
+        Same parameter as `loadtxt`
+
+        .. versionadded:: 1.23.0
+    ${ARRAY_FUNCTION_LIKE}
+
+        .. versionadded:: 1.20.0
+
+    Returns
+    -------
+    out : ndarray
+        Data read from the text file. If `usemask` is True, this is a
+        masked array.
+
+    See Also
+    --------
+    numpy.loadtxt : equivalent function when no data is missing.
+
+    Notes
+    -----
+    * When spaces are used as delimiters, or when no delimiter has been given
+      as input, there should not be any missing data between two fields.
+    * When variables are named (either by a flexible dtype or with a `names`
+      sequence), there must not be any header in the file (else a ValueError
+      exception is raised).
+    * Individual values are not stripped of spaces by default.
+      When using a custom converter, make sure the function does remove spaces.
+    * Custom converters may receive unexpected values due to dtype
+      discovery.
+
+    References
+    ----------
+    .. [1] NumPy User Guide, section `I/O with NumPy
+           <https://docs.scipy.org/doc/numpy/user/basics.io.genfromtxt.html>`_.
+
+    Examples
+    --------
+    >>> from io import StringIO
+    >>> import numpy as np
+
+    Comma delimited file with mixed dtype
+
+    >>> s = StringIO("1,1.3,abcde")
+    >>> data = np.genfromtxt(s, dtype=[('myint','i8'),('myfloat','f8'),
+    ... ('mystring','S5')], delimiter=",")
+    >>> data
+    array((1, 1.3, b'abcde'),
+          dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', 'S5')])
+
+    Using dtype = None
+
+    >>> _ = s.seek(0) # needed for StringIO example only
+    >>> data = np.genfromtxt(s, dtype=None,
+    ... names = ['myint','myfloat','mystring'], delimiter=",")
+    >>> data
+    array((1, 1.3, 'abcde'),
+          dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', '<U5')])
+
+    Specifying dtype and names
+
+    >>> _ = s.seek(0)
+    >>> data = np.genfromtxt(s, dtype="i8,f8,S5",
+    ... names=['myint','myfloat','mystring'], delimiter=",")
+    >>> data
+    array((1, 1.3, b'abcde'),
+          dtype=[('myint', '<i8'), ('myfloat', '<f8'), ('mystring', 'S5')])
+
+    An example with fixed-width columns
+
+    >>> s = StringIO("11.3abcde")
+    >>> data = np.genfromtxt(s, dtype=None, names=['intvar','fltvar','strvar'],
+    ...     delimiter=[1,3,5])
+    >>> data
+    array((1, 1.3, 'abcde'),
+          dtype=[('intvar', '<i8'), ('fltvar', '<f8'), ('strvar', '<U5')])
+
+    An example to show comments
+
+    >>> f = StringIO('''
+    ... text,# of chars
+    ... hello world,11
+    ... numpy,5''')
+    >>> np.genfromtxt(f, dtype='S12,S12', delimiter=',')
+    array([(b'text', b''), (b'hello world', b'11'), (b'numpy', b'5')],
+      dtype=[('f0', 'S12'), ('f1', 'S12')])
+
+    """
+
+    if like is not None:
+        return _genfromtxt_with_like(
+            like, fname, dtype=dtype, comments=comments, delimiter=delimiter,
+            skip_header=skip_header, skip_footer=skip_footer,
+            converters=converters, missing_values=missing_values,
+            filling_values=filling_values, usecols=usecols, names=names,
+            excludelist=excludelist, deletechars=deletechars,
+            replace_space=replace_space, autostrip=autostrip,
+            case_sensitive=case_sensitive, defaultfmt=defaultfmt,
+            unpack=unpack, usemask=usemask, loose=loose,
+            invalid_raise=invalid_raise, max_rows=max_rows, encoding=encoding,
+            ndmin=ndmin,
+        )
+
+    _ensure_ndmin_ndarray_check_param(ndmin)
+
+    if max_rows is not None:
+        if skip_footer:
+            raise ValueError(
+                    "The keywords 'skip_footer' and 'max_rows' can not be "
+                    "specified at the same time.")
+        if max_rows < 1:
+            raise ValueError("'max_rows' must be at least 1.")
+
+    if usemask:
+        from numpy.ma import MaskedArray, make_mask_descr
+    # Check the input dictionary of converters
+    user_converters = converters or {}
+    if not isinstance(user_converters, dict):
+        raise TypeError(
+            "The input argument 'converter' should be a valid dictionary "
+            "(got '%s' instead)" % type(user_converters))
+
+    if encoding == 'bytes':
+        encoding = None
+        byte_converters = True
+    else:
+        byte_converters = False
+
+    # Initialize the filehandle, the LineSplitter and the NameValidator
+    if isinstance(fname, os.PathLike):
+        fname = os.fspath(fname)
+    if isinstance(fname, str):
+        fid = np.lib._datasource.open(fname, 'rt', encoding=encoding)
+        fid_ctx = contextlib.closing(fid)
+    else:
+        fid = fname
+        fid_ctx = contextlib.nullcontext(fid)
+    try:
+        fhd = iter(fid)
+    except TypeError as e:
+        raise TypeError(
+            "fname must be a string, a filehandle, a sequence of strings,\n"
+            f"or an iterator of strings. Got {type(fname)} instead."
+        ) from e
+    with fid_ctx:
+        split_line = LineSplitter(delimiter=delimiter, comments=comments,
+                                  autostrip=autostrip, encoding=encoding)
+        validate_names = NameValidator(excludelist=excludelist,
+                                       deletechars=deletechars,
+                                       case_sensitive=case_sensitive,
+                                       replace_space=replace_space)
+
+        # Skip the first `skip_header` rows
+        try:
+            for i in range(skip_header):
+                next(fhd)
+
+            # Keep on until we find the first valid values
+            first_values = None
+
+            while not first_values:
+                first_line = _decode_line(next(fhd), encoding)
+                if (names is True) and (comments is not None):
+                    if comments in first_line:
+                        first_line = (
+                            ''.join(first_line.split(comments)[1:]))
+                first_values = split_line(first_line)
+        except StopIteration:
+            # return an empty array if the datafile is empty
+            first_line = ''
+            first_values = []
+            warnings.warn(
+                f'genfromtxt: Empty input file: "{fname}"', stacklevel=2
+            )
+
+        # Should we take the first values as names ?
+        if names is True:
+            fval = first_values[0].strip()
+            if comments is not None:
+                if fval in comments:
+                    del first_values[0]
+
+        # Check the columns to use: make sure `usecols` is a list
+        if usecols is not None:
+            try:
+                usecols = [_.strip() for _ in usecols.split(",")]
+            except AttributeError:
+                try:
+                    usecols = list(usecols)
+                except TypeError:
+                    usecols = [usecols, ]
+        nbcols = len(usecols or first_values)
+
+        # Check the names and overwrite the dtype.names if needed
+        if names is True:
+            names = validate_names([str(_.strip()) for _ in first_values])
+            first_line = ''
+        elif _is_string_like(names):
+            names = validate_names([_.strip() for _ in names.split(',')])
+        elif names:
+            names = validate_names(names)
+        # Get the dtype
+        if dtype is not None:
+            dtype = easy_dtype(dtype, defaultfmt=defaultfmt, names=names,
+                               excludelist=excludelist,
+                               deletechars=deletechars,
+                               case_sensitive=case_sensitive,
+                               replace_space=replace_space)
+        # Make sure the names is a list (for 2.5)
+        if names is not None:
+            names = list(names)
+
+        if usecols:
+            for (i, current) in enumerate(usecols):
+                # if usecols is a list of names, convert to a list of indices
+                if _is_string_like(current):
+                    usecols[i] = names.index(current)
+                elif current < 0:
+                    usecols[i] = current + len(first_values)
+            # If the dtype is not None, make sure we update it
+            if (dtype is not None) and (len(dtype) > nbcols):
+                descr = dtype.descr
+                dtype = np.dtype([descr[_] for _ in usecols])
+                names = list(dtype.names)
+            # If `names` is not None, update the names
+            elif (names is not None) and (len(names) > nbcols):
+                names = [names[_] for _ in usecols]
+        elif (names is not None) and (dtype is not None):
+            names = list(dtype.names)
+
+        # Process the missing values ...............................
+        # Rename missing_values for convenience
+        user_missing_values = missing_values or ()
+        if isinstance(user_missing_values, bytes):
+            user_missing_values = user_missing_values.decode('latin1')
+
+        # Define the list of missing_values (one column: one list)
+        missing_values = [[''] for _ in range(nbcols)]
+
+        # We have a dictionary: process it field by field
+        if isinstance(user_missing_values, dict):
+            # Loop on the items
+            for (key, val) in user_missing_values.items():
+                # Is the key a string ?
+                if _is_string_like(key):
+                    try:
+                        # Transform it into an integer
+                        key = names.index(key)
+                    except ValueError:
+                        # We couldn't find it: the name must have been dropped
+                        continue
+                # Redefine the key as needed if it's a column number
+                if usecols:
+                    try:
+                        key = usecols.index(key)
+                    except ValueError:
+                        pass
+                # Transform the value as a list of string
+                if isinstance(val, (list, tuple)):
+                    val = [str(_) for _ in val]
+                else:
+                    val = [str(val), ]
+                # Add the value(s) to the current list of missing
+                if key is None:
+                    # None acts as default
+                    for miss in missing_values:
+                        miss.extend(val)
+                else:
+                    missing_values[key].extend(val)
+        # We have a sequence : each item matches a column
+        elif isinstance(user_missing_values, (list, tuple)):
+            for (value, entry) in zip(user_missing_values, missing_values):
+                value = str(value)
+                if value not in entry:
+                    entry.append(value)
+        # We have a string : apply it to all entries
+        elif isinstance(user_missing_values, str):
+            user_value = user_missing_values.split(",")
+            for entry in missing_values:
+                entry.extend(user_value)
+        # We have something else: apply it to all entries
+        else:
+            for entry in missing_values:
+                entry.extend([str(user_missing_values)])
+
+        # Process the filling_values ...............................
+        # Rename the input for convenience
+        user_filling_values = filling_values
+        if user_filling_values is None:
+            user_filling_values = []
+        # Define the default
+        filling_values = [None] * nbcols
+        # We have a dictionary : update each entry individually
+        if isinstance(user_filling_values, dict):
+            for (key, val) in user_filling_values.items():
+                if _is_string_like(key):
+                    try:
+                        # Transform it into an integer
+                        key = names.index(key)
+                    except ValueError:
+                        # We couldn't find it: the name must have been dropped
+                        continue
+                # Redefine the key if it's a column number
+                # and usecols is defined
+                if usecols:
+                    try:
+                        key = usecols.index(key)
+                    except ValueError:
+                        pass
+                # Add the value to the list
+                filling_values[key] = val
+        # We have a sequence : update on a one-to-one basis
+        elif isinstance(user_filling_values, (list, tuple)):
+            n = len(user_filling_values)
+            if (n <= nbcols):
+                filling_values[:n] = user_filling_values
+            else:
+                filling_values = user_filling_values[:nbcols]
+        # We have something else : use it for all entries
+        else:
+            filling_values = [user_filling_values] * nbcols
+
+        # Initialize the converters ................................
+        if dtype is None:
+            # Note: we can't use a [...]*nbcols, as we would have 3 times
+            # the same converter, instead of 3 different converters.
+            converters = [
+                StringConverter(None, missing_values=miss, default=fill)
+                for (miss, fill) in zip(missing_values, filling_values)
+            ]
+        else:
+            dtype_flat = flatten_dtype(dtype, flatten_base=True)
+            # Initialize the converters
+            if len(dtype_flat) > 1:
+                # Flexible type : get a converter from each dtype
+                zipit = zip(dtype_flat, missing_values, filling_values)
+                converters = [StringConverter(dt,
+                                              locked=True,
+                                              missing_values=miss,
+                                              default=fill)
+                              for (dt, miss, fill) in zipit]
+            else:
+                # Set to a default converter (but w/ different missing values)
+                zipit = zip(missing_values, filling_values)
+                converters = [StringConverter(dtype,
+                                              locked=True,
+                                              missing_values=miss,
+                                              default=fill)
+                              for (miss, fill) in zipit]
+        # Update the converters to use the user-defined ones
+        uc_update = []
+        for (j, conv) in user_converters.items():
+            # If the converter is specified by column names,
+            # use the index instead
+            if _is_string_like(j):
+                try:
+                    j = names.index(j)
+                    i = j
+                except ValueError:
+                    continue
+            elif usecols:
+                try:
+                    i = usecols.index(j)
+                except ValueError:
+                    # Unused converter specified
+                    continue
+            else:
+                i = j
+            # Find the value to test - first_line is not filtered by usecols:
+            if len(first_line):
+                testing_value = first_values[j]
+            else:
+                testing_value = None
+            if conv is bytes:
+                user_conv = asbytes
+            elif byte_converters:
+                # Converters may use decode to workaround numpy's old
+                # behavior, so encode the string again before passing
+                # to the user converter.
+                def tobytes_first(x, conv):
+                    if type(x) is bytes:
+                        return conv(x)
+                    return conv(x.encode("latin1"))
+                user_conv = functools.partial(tobytes_first, conv=conv)
+            else:
+                user_conv = conv
+            converters[i].update(user_conv, locked=True,
+                                 testing_value=testing_value,
+                                 default=filling_values[i],
+                                 missing_values=missing_values[i],)
+            uc_update.append((i, user_conv))
+        # Make sure we have the corrected keys in user_converters...
+        user_converters.update(uc_update)
+
+        # Fixme: possible error as following variable never used.
+        # miss_chars = [_.missing_values for _ in converters]
+
+        # Initialize the output lists ...
+        # ... rows
+        rows = []
+        append_to_rows = rows.append
+        # ... masks
+        if usemask:
+            masks = []
+            append_to_masks = masks.append
+        # ... invalid
+        invalid = []
+        append_to_invalid = invalid.append
+
+        # Parse each line
+        for (i, line) in enumerate(itertools.chain([first_line, ], fhd)):
+            values = split_line(line)
+            nbvalues = len(values)
+            # Skip an empty line
+            if nbvalues == 0:
+                continue
+            if usecols:
+                # Select only the columns we need
+                try:
+                    values = [values[_] for _ in usecols]
+                except IndexError:
+                    append_to_invalid((i + skip_header + 1, nbvalues))
+                    continue
+            elif nbvalues != nbcols:
+                append_to_invalid((i + skip_header + 1, nbvalues))
+                continue
+            # Store the values
+            append_to_rows(tuple(values))
+            if usemask:
+                append_to_masks(tuple(v.strip() in m
+                                       for (v, m) in zip(values,
+                                                         missing_values)))
+            if len(rows) == max_rows:
+                break
+
+    # Upgrade the converters (if needed)
+    if dtype is None:
+        for (i, converter) in enumerate(converters):
+            current_column = [itemgetter(i)(_m) for _m in rows]
+            try:
+                converter.iterupgrade(current_column)
+            except ConverterLockError:
+                errmsg = f"Converter #{i} is locked and cannot be upgraded: "
+                current_column = map(itemgetter(i), rows)
+                for (j, value) in enumerate(current_column):
+                    try:
+                        converter.upgrade(value)
+                    except (ConverterError, ValueError):
+                        line_number = j + 1 + skip_header
+                        errmsg += f"(occurred line #{line_number} for value '{value}')"
+                        raise ConverterError(errmsg)
+
+    # Check that we don't have invalid values
+    nbinvalid = len(invalid)
+    if nbinvalid > 0:
+        nbrows = len(rows) + nbinvalid - skip_footer
+        # Construct the error message
+        template = f"    Line #%i (got %i columns instead of {nbcols})"
+        if skip_footer > 0:
+            nbinvalid_skipped = len([_ for _ in invalid
+                                     if _[0] > nbrows + skip_header])
+            invalid = invalid[:nbinvalid - nbinvalid_skipped]
+            skip_footer -= nbinvalid_skipped
+#
+#            nbrows -= skip_footer
+#            errmsg = [template % (i, nb)
+#                      for (i, nb) in invalid if i < nbrows]
+#        else:
+        errmsg = [template % (i, nb)
+                  for (i, nb) in invalid]
+        if len(errmsg):
+            errmsg.insert(0, "Some errors were detected !")
+            errmsg = "\n".join(errmsg)
+            # Raise an exception ?
+            if invalid_raise:
+                raise ValueError(errmsg)
+            # Issue a warning ?
+            else:
+                warnings.warn(errmsg, ConversionWarning, stacklevel=2)
+
+    # Strip the last skip_footer data
+    if skip_footer > 0:
+        rows = rows[:-skip_footer]
+        if usemask:
+            masks = masks[:-skip_footer]
+
+    # Convert each value according to the converter:
+    # We want to modify the list in place to avoid creating a new one...
+    if loose:
+        rows = list(
+            zip(*[[conv._loose_call(_r) for _r in map(itemgetter(i), rows)]
+                  for (i, conv) in enumerate(converters)]))
+    else:
+        rows = list(
+            zip(*[[conv._strict_call(_r) for _r in map(itemgetter(i), rows)]
+                  for (i, conv) in enumerate(converters)]))
+
+    # Reset the dtype
+    data = rows
+    if dtype is None:
+        # Get the dtypes from the types of the converters
+        column_types = [conv.type for conv in converters]
+        # Find the columns with strings...
+        strcolidx = [i for (i, v) in enumerate(column_types)
+                     if v == np.str_]
+
+        if byte_converters and strcolidx:
+            # convert strings back to bytes for backward compatibility
+            warnings.warn(
+                "Reading unicode strings without specifying the encoding "
+                "argument is deprecated. Set the encoding, use None for the "
+                "system default.",
+                np.exceptions.VisibleDeprecationWarning, stacklevel=2)
+
+            def encode_unicode_cols(row_tup):
+                row = list(row_tup)
+                for i in strcolidx:
+                    row[i] = row[i].encode('latin1')
+                return tuple(row)
+
+            try:
+                data = [encode_unicode_cols(r) for r in data]
+            except UnicodeEncodeError:
+                pass
+            else:
+                for i in strcolidx:
+                    column_types[i] = np.bytes_
+
+        # Update string types to be the right length
+        sized_column_types = column_types.copy()
+        for i, col_type in enumerate(column_types):
+            if np.issubdtype(col_type, np.character):
+                n_chars = max(len(row[i]) for row in data)
+                sized_column_types[i] = (col_type, n_chars)
+
+        if names is None:
+            # If the dtype is uniform (before sizing strings)
+            base = {
+                c_type
+                for c, c_type in zip(converters, column_types)
+                if c._checked}
+            if len(base) == 1:
+                uniform_type, = base
+                (ddtype, mdtype) = (uniform_type, bool)
+            else:
+                ddtype = [(defaultfmt % i, dt)
+                          for (i, dt) in enumerate(sized_column_types)]
+                if usemask:
+                    mdtype = [(defaultfmt % i, bool)
+                              for (i, dt) in enumerate(sized_column_types)]
+        else:
+            ddtype = list(zip(names, sized_column_types))
+            mdtype = list(zip(names, [bool] * len(sized_column_types)))
+        output = np.array(data, dtype=ddtype)
+        if usemask:
+            outputmask = np.array(masks, dtype=mdtype)
+    else:
+        # Overwrite the initial dtype names if needed
+        if names and dtype.names is not None:
+            dtype.names = names
+        # Case 1. We have a structured type
+        if len(dtype_flat) > 1:
+            # Nested dtype, eg [('a', int), ('b', [('b0', int), ('b1', 'f4')])]
+            # First, create the array using a flattened dtype:
+            # [('a', int), ('b1', int), ('b2', float)]
+            # Then, view the array using the specified dtype.
+            if 'O' in (_.char for _ in dtype_flat):
+                if has_nested_fields(dtype):
+                    raise NotImplementedError(
+                        "Nested fields involving objects are not supported...")
+                else:
+                    output = np.array(data, dtype=dtype)
+            else:
+                rows = np.array(data, dtype=[('', _) for _ in dtype_flat])
+                output = rows.view(dtype)
+            # Now, process the rowmasks the same way
+            if usemask:
+                rowmasks = np.array(
+                    masks, dtype=np.dtype([('', bool) for t in dtype_flat]))
+                # Construct the new dtype
+                mdtype = make_mask_descr(dtype)
+                outputmask = rowmasks.view(mdtype)
+        # Case #2. We have a basic dtype
+        else:
+            # We used some user-defined converters
+            if user_converters:
+                ishomogeneous = True
+                descr = []
+                for i, ttype in enumerate([conv.type for conv in converters]):
+                    # Keep the dtype of the current converter
+                    if i in user_converters:
+                        ishomogeneous &= (ttype == dtype.type)
+                        if np.issubdtype(ttype, np.character):
+                            ttype = (ttype, max(len(row[i]) for row in data))
+                        descr.append(('', ttype))
+                    else:
+                        descr.append(('', dtype))
+                # So we changed the dtype ?
+                if not ishomogeneous:
+                    # We have more than one field
+                    if len(descr) > 1:
+                        dtype = np.dtype(descr)
+                    # We have only one field: drop the name if not needed.
+                    else:
+                        dtype = np.dtype(ttype)
+            #
+            output = np.array(data, dtype)
+            if usemask:
+                if dtype.names is not None:
+                    mdtype = [(_, bool) for _ in dtype.names]
+                else:
+                    mdtype = bool
+                outputmask = np.array(masks, dtype=mdtype)
+    # Try to take care of the missing data we missed
+    names = output.dtype.names
+    if usemask and names:
+        for (name, conv) in zip(names, converters):
+            missing_values = [conv(_) for _ in conv.missing_values
+                              if _ != '']
+            for mval in missing_values:
+                outputmask[name] |= (output[name] == mval)
+    # Construct the final array
+    if usemask:
+        output = output.view(MaskedArray)
+        output._mask = outputmask
+
+    output = _ensure_ndmin_ndarray(output, ndmin=ndmin)
+
+    if unpack:
+        if names is None:
+            return output.T
+        elif len(names) == 1:
+            # squeeze single-name dtypes too
+            return output[names[0]]
+        else:
+            # For structured arrays with multiple fields,
+            # return an array for each field.
+            return [output[field] for field in names]
+    return output
+
+
+_genfromtxt_with_like = array_function_dispatch()(genfromtxt)
+
+
+def recfromtxt(fname, **kwargs):
+    """
+    Load ASCII data from a file and return it in a record array.
+
+    If ``usemask=False`` a standard `recarray` is returned,
+    if ``usemask=True`` a MaskedRecords array is returned.
+
+    .. deprecated:: 2.0
+        Use `numpy.genfromtxt` instead.
+
+    Parameters
+    ----------
+    fname, kwargs : For a description of input parameters, see `genfromtxt`.
+
+    See Also
+    --------
+    numpy.genfromtxt : generic function
+
+    Notes
+    -----
+    By default, `dtype` is None, which means that the data-type of the output
+    array will be determined from the data.
+
+    """
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`recfromtxt` is deprecated, "
+        "use `numpy.genfromtxt` instead."
+        "(deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    kwargs.setdefault("dtype", None)
+    usemask = kwargs.get('usemask', False)
+    output = genfromtxt(fname, **kwargs)
+    if usemask:
+        from numpy.ma.mrecords import MaskedRecords
+        output = output.view(MaskedRecords)
+    else:
+        output = output.view(np.recarray)
+    return output
+
+
+def recfromcsv(fname, **kwargs):
+    """
+    Load ASCII data stored in a comma-separated file.
+
+    The returned array is a record array (if ``usemask=False``, see
+    `recarray`) or a masked record array (if ``usemask=True``,
+    see `ma.mrecords.MaskedRecords`).
+
+    .. deprecated:: 2.0
+        Use `numpy.genfromtxt` with comma as `delimiter` instead.
+
+    Parameters
+    ----------
+    fname, kwargs : For a description of input parameters, see `genfromtxt`.
+
+    See Also
+    --------
+    numpy.genfromtxt : generic function to load ASCII data.
+
+    Notes
+    -----
+    By default, `dtype` is None, which means that the data-type of the output
+    array will be determined from the data.
+
+    """
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`recfromcsv` is deprecated, "
+        "use `numpy.genfromtxt` with comma as `delimiter` instead. "
+        "(deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    # Set default kwargs for genfromtxt as relevant to csv import.
+    kwargs.setdefault("case_sensitive", "lower")
+    kwargs.setdefault("names", True)
+    kwargs.setdefault("delimiter", ",")
+    kwargs.setdefault("dtype", None)
+    output = genfromtxt(fname, **kwargs)
+
+    usemask = kwargs.get("usemask", False)
+    if usemask:
+        from numpy.ma.mrecords import MaskedRecords
+        output = output.view(MaskedRecords)
+    else:
+        output = output.view(np.recarray)
+    return output
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..d48691d6f36f0d5806b61f670db4c6afc743a622
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_npyio_impl.pyi
@@ -0,0 +1,299 @@
+import types
+import zipfile
+from _typeshed import (
+    StrOrBytesPath,
+    StrPath,
+    SupportsKeysAndGetItem,
+    SupportsRead,
+    SupportsWrite,
+)
+from collections.abc import Callable, Collection, Iterable, Iterator, Mapping, Sequence
+from re import Pattern
+from typing import (
+    IO,
+    Any,
+    ClassVar,
+    Generic,
+    Literal as L,
+    Protocol,
+    Self,
+    TypeAlias,
+    overload,
+    type_check_only,
+)
+from typing_extensions import TypeVar, override
+
+import numpy as np
+from numpy._core.multiarray import packbits, unpackbits
+from numpy._typing import ArrayLike, DTypeLike, NDArray, _DTypeLike, _SupportsArrayFunc
+from numpy.ma.mrecords import MaskedRecords
+
+from ._datasource import DataSource as DataSource
+
+__all__ = [
+    "fromregex",
+    "genfromtxt",
+    "load",
+    "loadtxt",
+    "packbits",
+    "save",
+    "savetxt",
+    "savez",
+    "savez_compressed",
+    "unpackbits",
+]
+
+_T = TypeVar("_T")
+_T_co = TypeVar("_T_co", covariant=True)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, default=Any, covariant=True)
+
+_FName: TypeAlias = StrPath | Iterable[str] | Iterable[bytes]
+_FNameRead: TypeAlias = StrPath | SupportsRead[str] | SupportsRead[bytes]
+_FNameWriteBytes: TypeAlias = StrPath | SupportsWrite[bytes]
+_FNameWrite: TypeAlias = _FNameWriteBytes | SupportsWrite[str]
+
+@type_check_only
+class _SupportsReadSeek(SupportsRead[_T_co], Protocol[_T_co]):
+    def seek(self, offset: int, whence: int, /) -> object: ...
+
+class BagObj(Generic[_T_co]):
+    def __init__(self, /, obj: SupportsKeysAndGetItem[str, _T_co]) -> None: ...
+    def __getattribute__(self, key: str, /) -> _T_co: ...
+    def __dir__(self) -> list[str]: ...
+
+class NpzFile(Mapping[str, NDArray[_ScalarT_co]]):
+    _MAX_REPR_ARRAY_COUNT: ClassVar[int] = 5
+
+    zip: zipfile.ZipFile | None = None
+    fid: IO[str] | None = None
+    files: list[str]
+    allow_pickle: bool
+    pickle_kwargs: Mapping[str, Any] | None
+    f: BagObj[NpzFile[_ScalarT_co]]
+
+    #
+    def __init__(
+        self,
+        /,
+        fid: IO[Any],
+        own_fid: bool = False,
+        allow_pickle: bool = False,
+        pickle_kwargs: Mapping[str, object] | None = None,
+        *,
+        max_header_size: int = 10_000,
+    ) -> None: ...
+    def __del__(self) -> None: ...
+    def __enter__(self) -> Self: ...
+    def __exit__(self, cls: type[BaseException] | None, e: BaseException | None, tb: types.TracebackType | None, /) -> None: ...
+    @override
+    def __len__(self) -> int: ...
+    @override
+    def __iter__(self) -> Iterator[str]: ...
+    @override
+    def __getitem__(self, key: str, /) -> NDArray[_ScalarT_co]: ...
+
+    #
+    @override
+    @overload
+    def get(self, key: str, default: None = None, /) -> NDArray[_ScalarT_co] | None: ...
+    @overload
+    def get(self, key: str, default: NDArray[_ScalarT_co] | _T, /) -> NDArray[_ScalarT_co] | _T: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    #
+    def close(self) -> None: ...
+
+# NOTE: Returns a `NpzFile` if file is a zip file;
+# returns an `ndarray`/`memmap` otherwise
+def load(
+    file: StrOrBytesPath | _SupportsReadSeek[bytes],
+    mmap_mode: L["r+", "r", "w+", "c"] | None = None,
+    allow_pickle: bool = False,
+    fix_imports: bool = True,
+    encoding: L["ASCII", "latin1", "bytes"] = "ASCII",
+    *,
+    max_header_size: int = 10_000,
+) -> Any: ...
+
+def save(file: _FNameWriteBytes, arr: ArrayLike, allow_pickle: bool = True) -> None: ...
+def savez(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ...
+def savez_compressed(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ...
+
+# File-like objects only have to implement `__iter__` and,
+# optionally, `encoding`
+@overload
+def loadtxt(
+    fname: _FName,
+    dtype: None = None,
+    comments: str | Sequence[str] | None = "#",
+    delimiter: str | None = None,
+    converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
+    skiprows: int = 0,
+    usecols: int | Sequence[int] | None = None,
+    unpack: bool = False,
+    ndmin: L[0, 1, 2] = 0,
+    encoding: str | None = None,
+    max_rows: int | None = None,
+    *,
+    quotechar: str | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[np.float64]: ...
+@overload
+def loadtxt(
+    fname: _FName,
+    dtype: _DTypeLike[_ScalarT],
+    comments: str | Sequence[str] | None = "#",
+    delimiter: str | None = None,
+    converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
+    skiprows: int = 0,
+    usecols: int | Sequence[int] | None = None,
+    unpack: bool = False,
+    ndmin: L[0, 1, 2] = 0,
+    encoding: str | None = None,
+    max_rows: int | None = None,
+    *,
+    quotechar: str | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[_ScalarT]: ...
+@overload
+def loadtxt(
+    fname: _FName,
+    dtype: DTypeLike | None,
+    comments: str | Sequence[str] | None = "#",
+    delimiter: str | None = None,
+    converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
+    skiprows: int = 0,
+    usecols: int | Sequence[int] | None = None,
+    unpack: bool = False,
+    ndmin: L[0, 1, 2] = 0,
+    encoding: str | None = None,
+    max_rows: int | None = None,
+    *,
+    quotechar: str | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[Any]: ...
+
+def savetxt(
+    fname: _FNameWrite,
+    X: ArrayLike,
+    fmt: str | Sequence[str] = "%.18e",
+    delimiter: str = " ",
+    newline: str = "\n",
+    header: str = "",
+    footer: str = "",
+    comments: str = "# ",
+    encoding: str | None = None,
+) -> None: ...
+
+@overload
+def fromregex(
+    file: _FNameRead,
+    regexp: str | bytes | Pattern[Any],
+    dtype: _DTypeLike[_ScalarT],
+    encoding: str | None = None,
+) -> NDArray[_ScalarT]: ...
+@overload
+def fromregex(
+    file: _FNameRead,
+    regexp: str | bytes | Pattern[Any],
+    dtype: DTypeLike | None,
+    encoding: str | None = None,
+) -> NDArray[Any]: ...
+
+@overload
+def genfromtxt(
+    fname: _FName,
+    dtype: None = None,
+    comments: str = "#",
+    delimiter: str | int | Iterable[int] | None = None,
+    skip_header: int = 0,
+    skip_footer: int = 0,
+    converters: Mapping[int | str, Callable[[str], Any]] | None = None,
+    missing_values: Any = None,
+    filling_values: Any = None,
+    usecols: Sequence[int] | None = None,
+    names: L[True] | str | Collection[str] | None = None,
+    excludelist: Sequence[str] | None = None,
+    deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~",
+    replace_space: str = "_",
+    autostrip: bool = False,
+    case_sensitive: bool | L["upper", "lower"] = True,
+    defaultfmt: str = "f%i",
+    unpack: bool | None = None,
+    usemask: bool = False,
+    loose: bool = True,
+    invalid_raise: bool = True,
+    max_rows: int | None = None,
+    encoding: str | None = None,
+    *,
+    ndmin: L[0, 1, 2] = 0,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[Any]: ...
+@overload
+def genfromtxt(
+    fname: _FName,
+    dtype: _DTypeLike[_ScalarT],
+    comments: str = "#",
+    delimiter: str | int | Iterable[int] | None = None,
+    skip_header: int = 0,
+    skip_footer: int = 0,
+    converters: Mapping[int | str, Callable[[str], Any]] | None = None,
+    missing_values: Any = None,
+    filling_values: Any = None,
+    usecols: Sequence[int] | None = None,
+    names: L[True] | str | Collection[str] | None = None,
+    excludelist: Sequence[str] | None = None,
+    deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~",
+    replace_space: str = "_",
+    autostrip: bool = False,
+    case_sensitive: bool | L["upper", "lower"] = True,
+    defaultfmt: str = "f%i",
+    unpack: bool | None = None,
+    usemask: bool = False,
+    loose: bool = True,
+    invalid_raise: bool = True,
+    max_rows: int | None = None,
+    encoding: str | None = None,
+    *,
+    ndmin: L[0, 1, 2] = 0,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[_ScalarT]: ...
+@overload
+def genfromtxt(
+    fname: _FName,
+    dtype: DTypeLike | None,
+    comments: str = "#",
+    delimiter: str | int | Iterable[int] | None = None,
+    skip_header: int = 0,
+    skip_footer: int = 0,
+    converters: Mapping[int | str, Callable[[str], Any]] | None = None,
+    missing_values: Any = None,
+    filling_values: Any = None,
+    usecols: Sequence[int] | None = None,
+    names: L[True] | str | Collection[str] | None = None,
+    excludelist: Sequence[str] | None = None,
+    deletechars: str = " !#$%&'()*+,-./:;<=>?@[\\]^{|}~",
+    replace_space: str = "_",
+    autostrip: bool = False,
+    case_sensitive: bool | L["upper", "lower"] = True,
+    defaultfmt: str = "f%i",
+    unpack: bool | None = None,
+    usemask: bool = False,
+    loose: bool = True,
+    invalid_raise: bool = True,
+    max_rows: int | None = None,
+    encoding: str | None = None,
+    *,
+    ndmin: L[0, 1, 2] = 0,
+    like: _SupportsArrayFunc | None = None,
+) -> NDArray[Any]: ...
+
+@overload
+def recfromtxt(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ...
+@overload
+def recfromtxt(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ...
+
+@overload
+def recfromcsv(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ...
+@overload
+def recfromcsv(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..1e42244ac5fc495d47b7d197b2f3b9f6c0c5646a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.py
@@ -0,0 +1,1465 @@
+"""
+Functions to operate on polynomials.
+
+"""
+__all__ = ['poly', 'roots', 'polyint', 'polyder', 'polyadd',
+           'polysub', 'polymul', 'polydiv', 'polyval', 'poly1d',
+           'polyfit']
+
+import functools
+import re
+import warnings
+
+import numpy._core.numeric as NX
+from numpy._core import (
+    abs,
+    array,
+    atleast_1d,
+    dot,
+    finfo,
+    hstack,
+    isscalar,
+    ones,
+    overrides,
+)
+from numpy._utils import set_module
+from numpy.exceptions import RankWarning
+from numpy.lib._function_base_impl import trim_zeros
+from numpy.lib._twodim_base_impl import diag, vander
+from numpy.lib._type_check_impl import imag, iscomplex, mintypecode, real
+from numpy.linalg import eigvals, inv, lstsq
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+def _poly_dispatcher(seq_of_zeros):
+    return seq_of_zeros
+
+
+@array_function_dispatch(_poly_dispatcher)
+def poly(seq_of_zeros):
+    """
+    Find the coefficients of a polynomial with the given sequence of roots.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Returns the coefficients of the polynomial whose leading coefficient
+    is one for the given sequence of zeros (multiple roots must be included
+    in the sequence as many times as their multiplicity; see Examples).
+    A square matrix (or array, which will be treated as a matrix) can also
+    be given, in which case the coefficients of the characteristic polynomial
+    of the matrix are returned.
+
+    Parameters
+    ----------
+    seq_of_zeros : array_like, shape (N,) or (N, N)
+        A sequence of polynomial roots, or a square array or matrix object.
+
+    Returns
+    -------
+    c : ndarray
+        1D array of polynomial coefficients from highest to lowest degree:
+
+        ``c[0] * x**(N) + c[1] * x**(N-1) + ... + c[N-1] * x + c[N]``
+        where c[0] always equals 1.
+
+    Raises
+    ------
+    ValueError
+        If input is the wrong shape (the input must be a 1-D or square
+        2-D array).
+
+    See Also
+    --------
+    polyval : Compute polynomial values.
+    roots : Return the roots of a polynomial.
+    polyfit : Least squares polynomial fit.
+    poly1d : A one-dimensional polynomial class.
+
+    Notes
+    -----
+    Specifying the roots of a polynomial still leaves one degree of
+    freedom, typically represented by an undetermined leading
+    coefficient. [1]_ In the case of this function, that coefficient -
+    the first one in the returned array - is always taken as one. (If
+    for some reason you have one other point, the only automatic way
+    presently to leverage that information is to use ``polyfit``.)
+
+    The characteristic polynomial, :math:`p_a(t)`, of an `n`-by-`n`
+    matrix **A** is given by
+
+    :math:`p_a(t) = \\mathrm{det}(t\\, \\mathbf{I} - \\mathbf{A})`,
+
+    where **I** is the `n`-by-`n` identity matrix. [2]_
+
+    References
+    ----------
+    .. [1] M. Sullivan and M. Sullivan, III, "Algebra and Trigonometry,
+       Enhanced With Graphing Utilities," Prentice-Hall, pg. 318, 1996.
+
+    .. [2] G. Strang, "Linear Algebra and Its Applications, 2nd Edition,"
+       Academic Press, pg. 182, 1980.
+
+    Examples
+    --------
+
+    Given a sequence of a polynomial's zeros:
+
+    >>> import numpy as np
+
+    >>> np.poly((0, 0, 0)) # Multiple root example
+    array([1., 0., 0., 0.])
+
+    The line above represents z**3 + 0*z**2 + 0*z + 0.
+
+    >>> np.poly((-1./2, 0, 1./2))
+    array([ 1.  ,  0.  , -0.25,  0.  ])
+
+    The line above represents z**3 - z/4
+
+    >>> np.poly((np.random.random(1)[0], 0, np.random.random(1)[0]))
+    array([ 1.        , -0.77086955,  0.08618131,  0.        ]) # random
+
+    Given a square array object:
+
+    >>> P = np.array([[0, 1./3], [-1./2, 0]])
+    >>> np.poly(P)
+    array([1.        , 0.        , 0.16666667])
+
+    Note how in all cases the leading coefficient is always 1.
+
+    """
+    seq_of_zeros = atleast_1d(seq_of_zeros)
+    sh = seq_of_zeros.shape
+
+    if len(sh) == 2 and sh[0] == sh[1] and sh[0] != 0:
+        seq_of_zeros = eigvals(seq_of_zeros)
+    elif len(sh) == 1:
+        dt = seq_of_zeros.dtype
+        # Let object arrays slip through, e.g. for arbitrary precision
+        if dt != object:
+            seq_of_zeros = seq_of_zeros.astype(mintypecode(dt.char))
+    else:
+        raise ValueError("input must be 1d or non-empty square 2d array.")
+
+    if len(seq_of_zeros) == 0:
+        return 1.0
+    dt = seq_of_zeros.dtype
+    a = ones((1,), dtype=dt)
+    for zero in seq_of_zeros:
+        a = NX.convolve(a, array([1, -zero], dtype=dt), mode='full')
+
+    if issubclass(a.dtype.type, NX.complexfloating):
+        # if complex roots are all complex conjugates, the roots are real.
+        roots = NX.asarray(seq_of_zeros, complex)
+        if NX.all(NX.sort(roots) == NX.sort(roots.conjugate())):
+            a = a.real.copy()
+
+    return a
+
+
+def _roots_dispatcher(p):
+    return p
+
+
+@array_function_dispatch(_roots_dispatcher)
+def roots(p):
+    """
+    Return the roots of a polynomial with coefficients given in p.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    The values in the rank-1 array `p` are coefficients of a polynomial.
+    If the length of `p` is n+1 then the polynomial is described by::
+
+      p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n]
+
+    Parameters
+    ----------
+    p : array_like
+        Rank-1 array of polynomial coefficients.
+
+    Returns
+    -------
+    out : ndarray
+        An array containing the roots of the polynomial.
+
+    Raises
+    ------
+    ValueError
+        When `p` cannot be converted to a rank-1 array.
+
+    See also
+    --------
+    poly : Find the coefficients of a polynomial with a given sequence
+           of roots.
+    polyval : Compute polynomial values.
+    polyfit : Least squares polynomial fit.
+    poly1d : A one-dimensional polynomial class.
+
+    Notes
+    -----
+    The algorithm relies on computing the eigenvalues of the
+    companion matrix [1]_.
+
+    References
+    ----------
+    .. [1] R. A. Horn & C. R. Johnson, *Matrix Analysis*.  Cambridge, UK:
+        Cambridge University Press, 1999, pp. 146-7.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> coeff = [3.2, 2, 1]
+    >>> np.roots(coeff)
+    array([-0.3125+0.46351241j, -0.3125-0.46351241j])
+
+    """
+    # If input is scalar, this makes it an array
+    p = atleast_1d(p)
+    if p.ndim != 1:
+        raise ValueError("Input must be a rank-1 array.")
+
+    # find non-zero array entries
+    non_zero = NX.nonzero(NX.ravel(p))[0]
+
+    # Return an empty array if polynomial is all zeros
+    if len(non_zero) == 0:
+        return NX.array([])
+
+    # find the number of trailing zeros -- this is the number of roots at 0.
+    trailing_zeros = len(p) - non_zero[-1] - 1
+
+    # strip leading and trailing zeros
+    p = p[int(non_zero[0]):int(non_zero[-1]) + 1]
+
+    # casting: if incoming array isn't floating point, make it floating point.
+    if not issubclass(p.dtype.type, (NX.floating, NX.complexfloating)):
+        p = p.astype(float)
+
+    N = len(p)
+    if N > 1:
+        # build companion matrix and find its eigenvalues (the roots)
+        A = diag(NX.ones((N - 2,), p.dtype), -1)
+        A[0, :] = -p[1:] / p[0]
+        roots = eigvals(A)
+    else:
+        roots = NX.array([])
+
+    # tack any zeros onto the back of the array
+    roots = hstack((roots, NX.zeros(trailing_zeros, roots.dtype)))
+    return roots
+
+
+def _polyint_dispatcher(p, m=None, k=None):
+    return (p,)
+
+
+@array_function_dispatch(_polyint_dispatcher)
+def polyint(p, m=1, k=None):
+    """
+    Return an antiderivative (indefinite integral) of a polynomial.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    The returned order `m` antiderivative `P` of polynomial `p` satisfies
+    :math:`\\frac{d^m}{dx^m}P(x) = p(x)` and is defined up to `m - 1`
+    integration constants `k`. The constants determine the low-order
+    polynomial part
+
+    .. math:: \\frac{k_{m-1}}{0!} x^0 + \\ldots + \\frac{k_0}{(m-1)!}x^{m-1}
+
+    of `P` so that :math:`P^{(j)}(0) = k_{m-j-1}`.
+
+    Parameters
+    ----------
+    p : array_like or poly1d
+        Polynomial to integrate.
+        A sequence is interpreted as polynomial coefficients, see `poly1d`.
+    m : int, optional
+        Order of the antiderivative. (Default: 1)
+    k : list of `m` scalars or scalar, optional
+        Integration constants. They are given in the order of integration:
+        those corresponding to highest-order terms come first.
+
+        If ``None`` (default), all constants are assumed to be zero.
+        If `m = 1`, a single scalar can be given instead of a list.
+
+    See Also
+    --------
+    polyder : derivative of a polynomial
+    poly1d.integ : equivalent method
+
+    Examples
+    --------
+
+    The defining property of the antiderivative:
+
+    >>> import numpy as np
+
+    >>> p = np.poly1d([1,1,1])
+    >>> P = np.polyint(p)
+    >>> P
+     poly1d([ 0.33333333,  0.5       ,  1.        ,  0.        ]) # may vary
+    >>> np.polyder(P) == p
+    True
+
+    The integration constants default to zero, but can be specified:
+
+    >>> P = np.polyint(p, 3)
+    >>> P(0)
+    0.0
+    >>> np.polyder(P)(0)
+    0.0
+    >>> np.polyder(P, 2)(0)
+    0.0
+    >>> P = np.polyint(p, 3, k=[6,5,3])
+    >>> P
+    poly1d([ 0.01666667,  0.04166667,  0.16666667,  3. ,  5. ,  3. ]) # may vary
+
+    Note that 3 = 6 / 2!, and that the constants are given in the order of
+    integrations. Constant of the highest-order polynomial term comes first:
+
+    >>> np.polyder(P, 2)(0)
+    6.0
+    >>> np.polyder(P, 1)(0)
+    5.0
+    >>> P(0)
+    3.0
+
+    """
+    m = int(m)
+    if m < 0:
+        raise ValueError("Order of integral must be positive (see polyder)")
+    if k is None:
+        k = NX.zeros(m, float)
+    k = atleast_1d(k)
+    if len(k) == 1 and m > 1:
+        k = k[0] * NX.ones(m, float)
+    if len(k) < m:
+        raise ValueError(
+              "k must be a scalar or a rank-1 array of length 1 or >m.")
+
+    truepoly = isinstance(p, poly1d)
+    p = NX.asarray(p)
+    if m == 0:
+        if truepoly:
+            return poly1d(p)
+        return p
+    else:
+        # Note: this must work also with object and integer arrays
+        y = NX.concatenate((p.__truediv__(NX.arange(len(p), 0, -1)), [k[0]]))
+        val = polyint(y, m - 1, k=k[1:])
+        if truepoly:
+            return poly1d(val)
+        return val
+
+
+def _polyder_dispatcher(p, m=None):
+    return (p,)
+
+
+@array_function_dispatch(_polyder_dispatcher)
+def polyder(p, m=1):
+    """
+    Return the derivative of the specified order of a polynomial.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Parameters
+    ----------
+    p : poly1d or sequence
+        Polynomial to differentiate.
+        A sequence is interpreted as polynomial coefficients, see `poly1d`.
+    m : int, optional
+        Order of differentiation (default: 1)
+
+    Returns
+    -------
+    der : poly1d
+        A new polynomial representing the derivative.
+
+    See Also
+    --------
+    polyint : Anti-derivative of a polynomial.
+    poly1d : Class for one-dimensional polynomials.
+
+    Examples
+    --------
+
+    The derivative of the polynomial :math:`x^3 + x^2 + x^1 + 1` is:
+
+    >>> import numpy as np
+
+    >>> p = np.poly1d([1,1,1,1])
+    >>> p2 = np.polyder(p)
+    >>> p2
+    poly1d([3, 2, 1])
+
+    which evaluates to:
+
+    >>> p2(2.)
+    17.0
+
+    We can verify this, approximating the derivative with
+    ``(f(x + h) - f(x))/h``:
+
+    >>> (p(2. + 0.001) - p(2.)) / 0.001
+    17.007000999997857
+
+    The fourth-order derivative of a 3rd-order polynomial is zero:
+
+    >>> np.polyder(p, 2)
+    poly1d([6, 2])
+    >>> np.polyder(p, 3)
+    poly1d([6])
+    >>> np.polyder(p, 4)
+    poly1d([0])
+
+    """
+    m = int(m)
+    if m < 0:
+        raise ValueError("Order of derivative must be positive (see polyint)")
+
+    truepoly = isinstance(p, poly1d)
+    p = NX.asarray(p)
+    n = len(p) - 1
+    y = p[:-1] * NX.arange(n, 0, -1)
+    if m == 0:
+        val = p
+    else:
+        val = polyder(y, m - 1)
+    if truepoly:
+        val = poly1d(val)
+    return val
+
+
+def _polyfit_dispatcher(x, y, deg, rcond=None, full=None, w=None, cov=None):
+    return (x, y, w)
+
+
+@array_function_dispatch(_polyfit_dispatcher)
+def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False):
+    """
+    Least squares polynomial fit.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Fit a polynomial ``p[0] * x**deg + ... + p[deg]`` of degree `deg`
+    to points `(x, y)`. Returns a vector of coefficients `p` that minimises
+    the squared error in the order `deg`, `deg-1`, ... `0`.
+
+    The `Polynomial.fit <numpy.polynomial.polynomial.Polynomial.fit>` class
+    method is recommended for new code as it is more stable numerically. See
+    the documentation of the method for more information.
+
+    Parameters
+    ----------
+    x : array_like, shape (M,)
+        x-coordinates of the M sample points ``(x[i], y[i])``.
+    y : array_like, shape (M,) or (M, K)
+        y-coordinates of the sample points. Several data sets of sample
+        points sharing the same x-coordinates can be fitted at once by
+        passing in a 2D-array that contains one dataset per column.
+    deg : int
+        Degree of the fitting polynomial
+    rcond : float, optional
+        Relative condition number of the fit. Singular values smaller than
+        this relative to the largest singular value will be ignored. The
+        default value is len(x)*eps, where eps is the relative precision of
+        the float type, about 2e-16 in most cases.
+    full : bool, optional
+        Switch determining nature of return value. When it is False (the
+        default) just the coefficients are returned, when True diagnostic
+        information from the singular value decomposition is also returned.
+    w : array_like, shape (M,), optional
+        Weights. If not None, the weight ``w[i]`` applies to the unsquared
+        residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are
+        chosen so that the errors of the products ``w[i]*y[i]`` all have the
+        same variance.  When using inverse-variance weighting, use
+        ``w[i] = 1/sigma(y[i])``.  The default value is None.
+    cov : bool or str, optional
+        If given and not `False`, return not just the estimate but also its
+        covariance matrix. By default, the covariance are scaled by
+        chi2/dof, where dof = M - (deg + 1), i.e., the weights are presumed
+        to be unreliable except in a relative sense and everything is scaled
+        such that the reduced chi2 is unity. This scaling is omitted if
+        ``cov='unscaled'``, as is relevant for the case that the weights are
+        w = 1/sigma, with sigma known to be a reliable estimate of the
+        uncertainty.
+
+    Returns
+    -------
+    p : ndarray, shape (deg + 1,) or (deg + 1, K)
+        Polynomial coefficients, highest power first.  If `y` was 2-D, the
+        coefficients for `k`-th data set are in ``p[:,k]``.
+
+    residuals, rank, singular_values, rcond
+        These values are only returned if ``full == True``
+
+        - residuals -- sum of squared residuals of the least squares fit
+        - rank -- the effective rank of the scaled Vandermonde
+          coefficient matrix
+        - singular_values -- singular values of the scaled Vandermonde
+          coefficient matrix
+        - rcond -- value of `rcond`.
+
+        For more details, see `numpy.linalg.lstsq`.
+
+    V : ndarray, shape (deg + 1, deg + 1) or (deg + 1, deg + 1, K)
+        Present only if ``full == False`` and ``cov == True``.  The covariance
+        matrix of the polynomial coefficient estimates.  The diagonal of
+        this matrix are the variance estimates for each coefficient.  If y
+        is a 2-D array, then the covariance matrix for the `k`-th data set
+        are in ``V[:,:,k]``
+
+
+    Warns
+    -----
+    RankWarning
+        The rank of the coefficient matrix in the least-squares fit is
+        deficient. The warning is only raised if ``full == False``.
+
+        The warnings can be turned off by
+
+        >>> import warnings
+        >>> warnings.simplefilter('ignore', np.exceptions.RankWarning)
+
+    See Also
+    --------
+    polyval : Compute polynomial values.
+    linalg.lstsq : Computes a least-squares fit.
+    scipy.interpolate.UnivariateSpline : Computes spline fits.
+
+    Notes
+    -----
+    The solution minimizes the squared error
+
+    .. math::
+        E = \\sum_{j=0}^k |p(x_j) - y_j|^2
+
+    in the equations::
+
+        x[0]**n * p[0] + ... + x[0] * p[n-1] + p[n] = y[0]
+        x[1]**n * p[0] + ... + x[1] * p[n-1] + p[n] = y[1]
+        ...
+        x[k]**n * p[0] + ... + x[k] * p[n-1] + p[n] = y[k]
+
+    The coefficient matrix of the coefficients `p` is a Vandermonde matrix.
+
+    `polyfit` issues a `~exceptions.RankWarning` when the least-squares fit is
+    badly conditioned. This implies that the best fit is not well-defined due
+    to numerical error. The results may be improved by lowering the polynomial
+    degree or by replacing `x` by `x` - `x`.mean(). The `rcond` parameter
+    can also be set to a value smaller than its default, but the resulting
+    fit may be spurious: including contributions from the small singular
+    values can add numerical noise to the result.
+
+    Note that fitting polynomial coefficients is inherently badly conditioned
+    when the degree of the polynomial is large or the interval of sample points
+    is badly centered. The quality of the fit should always be checked in these
+    cases. When polynomial fits are not satisfactory, splines may be a good
+    alternative.
+
+    References
+    ----------
+    .. [1] Wikipedia, "Curve fitting",
+           https://en.wikipedia.org/wiki/Curve_fitting
+    .. [2] Wikipedia, "Polynomial interpolation",
+           https://en.wikipedia.org/wiki/Polynomial_interpolation
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import warnings
+    >>> x = np.array([0.0, 1.0, 2.0, 3.0,  4.0,  5.0])
+    >>> y = np.array([0.0, 0.8, 0.9, 0.1, -0.8, -1.0])
+    >>> z = np.polyfit(x, y, 3)
+    >>> z
+    array([ 0.08703704, -0.81349206,  1.69312169, -0.03968254]) # may vary
+
+    It is convenient to use `poly1d` objects for dealing with polynomials:
+
+    >>> p = np.poly1d(z)
+    >>> p(0.5)
+    0.6143849206349179 # may vary
+    >>> p(3.5)
+    -0.34732142857143039 # may vary
+    >>> p(10)
+    22.579365079365115 # may vary
+
+    High-order polynomials may oscillate wildly:
+
+    >>> with warnings.catch_warnings():
+    ...     warnings.simplefilter('ignore', np.exceptions.RankWarning)
+    ...     p30 = np.poly1d(np.polyfit(x, y, 30))
+    ...
+    >>> p30(4)
+    -0.80000000000000204 # may vary
+    >>> p30(5)
+    -0.99999999999999445 # may vary
+    >>> p30(4.5)
+    -0.10547061179440398 # may vary
+
+    Illustration:
+
+    >>> import matplotlib.pyplot as plt
+    >>> xp = np.linspace(-2, 6, 100)
+    >>> _ = plt.plot(x, y, '.', xp, p(xp), '-', xp, p30(xp), '--')
+    >>> plt.ylim(-2,2)
+    (-2, 2)
+    >>> plt.show()
+
+    """
+    order = int(deg) + 1
+    x = NX.asarray(x) + 0.0
+    y = NX.asarray(y) + 0.0
+
+    # check arguments.
+    if deg < 0:
+        raise ValueError("expected deg >= 0")
+    if x.ndim != 1:
+        raise TypeError("expected 1D vector for x")
+    if x.size == 0:
+        raise TypeError("expected non-empty vector for x")
+    if y.ndim < 1 or y.ndim > 2:
+        raise TypeError("expected 1D or 2D array for y")
+    if x.shape[0] != y.shape[0]:
+        raise TypeError("expected x and y to have same length")
+
+    # set rcond
+    if rcond is None:
+        rcond = len(x) * finfo(x.dtype).eps
+
+    # set up least squares equation for powers of x
+    lhs = vander(x, order)
+    rhs = y
+
+    # apply weighting
+    if w is not None:
+        w = NX.asarray(w) + 0.0
+        if w.ndim != 1:
+            raise TypeError("expected a 1-d array for weights")
+        if w.shape[0] != y.shape[0]:
+            raise TypeError("expected w and y to have the same length")
+        lhs *= w[:, NX.newaxis]
+        if rhs.ndim == 2:
+            rhs *= w[:, NX.newaxis]
+        else:
+            rhs *= w
+
+    # scale lhs to improve condition number and solve
+    scale = NX.sqrt((lhs * lhs).sum(axis=0))
+    lhs /= scale
+    c, resids, rank, s = lstsq(lhs, rhs, rcond)
+    c = (c.T / scale).T  # broadcast scale coefficients
+
+    # warn on rank reduction, which indicates an ill conditioned matrix
+    if rank != order and not full:
+        msg = "Polyfit may be poorly conditioned"
+        warnings.warn(msg, RankWarning, stacklevel=2)
+
+    if full:
+        return c, resids, rank, s, rcond
+    elif cov:
+        Vbase = inv(dot(lhs.T, lhs))
+        Vbase /= NX.outer(scale, scale)
+        if cov == "unscaled":
+            fac = 1
+        else:
+            if len(x) <= order:
+                raise ValueError("the number of data points must exceed order "
+                                 "to scale the covariance matrix")
+            # note, this used to be: fac = resids / (len(x) - order - 2.0)
+            # it was decided that the "- 2" (originally justified by "Bayesian
+            # uncertainty analysis") is not what the user expects
+            # (see gh-11196 and gh-11197)
+            fac = resids / (len(x) - order)
+        if y.ndim == 1:
+            return c, Vbase * fac
+        else:
+            return c, Vbase[:, :, NX.newaxis] * fac
+    else:
+        return c
+
+
+def _polyval_dispatcher(p, x):
+    return (p, x)
+
+
+@array_function_dispatch(_polyval_dispatcher)
+def polyval(p, x):
+    """
+    Evaluate a polynomial at specific values.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    If `p` is of length N, this function returns the value::
+
+        p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]
+
+    If `x` is a sequence, then ``p(x)`` is returned for each element of ``x``.
+    If `x` is another polynomial then the composite polynomial ``p(x(t))``
+    is returned.
+
+    Parameters
+    ----------
+    p : array_like or poly1d object
+       1D array of polynomial coefficients (including coefficients equal
+       to zero) from highest degree to the constant term, or an
+       instance of poly1d.
+    x : array_like or poly1d object
+       A number, an array of numbers, or an instance of poly1d, at
+       which to evaluate `p`.
+
+    Returns
+    -------
+    values : ndarray or poly1d
+       If `x` is a poly1d instance, the result is the composition of the two
+       polynomials, i.e., `x` is "substituted" in `p` and the simplified
+       result is returned. In addition, the type of `x` - array_like or
+       poly1d - governs the type of the output: `x` array_like => `values`
+       array_like, `x` a poly1d object => `values` is also.
+
+    See Also
+    --------
+    poly1d: A polynomial class.
+
+    Notes
+    -----
+    Horner's scheme [1]_ is used to evaluate the polynomial. Even so,
+    for polynomials of high degree the values may be inaccurate due to
+    rounding errors. Use carefully.
+
+    If `x` is a subtype of `ndarray` the return value will be of the same type.
+
+    References
+    ----------
+    .. [1] I. N. Bronshtein, K. A. Semendyayev, and K. A. Hirsch (Eng.
+       trans. Ed.), *Handbook of Mathematics*, New York, Van Nostrand
+       Reinhold Co., 1985, pg. 720.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.polyval([3,0,1], 5)  # 3 * 5**2 + 0 * 5**1 + 1
+    76
+    >>> np.polyval([3,0,1], np.poly1d(5))
+    poly1d([76])
+    >>> np.polyval(np.poly1d([3,0,1]), 5)
+    76
+    >>> np.polyval(np.poly1d([3,0,1]), np.poly1d(5))
+    poly1d([76])
+
+    """
+    p = NX.asarray(p)
+    if isinstance(x, poly1d):
+        y = 0
+    else:
+        x = NX.asanyarray(x)
+        y = NX.zeros_like(x)
+    for pv in p:
+        y = y * x + pv
+    return y
+
+
+def _binary_op_dispatcher(a1, a2):
+    return (a1, a2)
+
+
+@array_function_dispatch(_binary_op_dispatcher)
+def polyadd(a1, a2):
+    """
+    Find the sum of two polynomials.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Returns the polynomial resulting from the sum of two input polynomials.
+    Each input must be either a poly1d object or a 1D sequence of polynomial
+    coefficients, from highest to lowest degree.
+
+    Parameters
+    ----------
+    a1, a2 : array_like or poly1d object
+        Input polynomials.
+
+    Returns
+    -------
+    out : ndarray or poly1d object
+        The sum of the inputs. If either input is a poly1d object, then the
+        output is also a poly1d object. Otherwise, it is a 1D array of
+        polynomial coefficients from highest to lowest degree.
+
+    See Also
+    --------
+    poly1d : A one-dimensional polynomial class.
+    poly, polyadd, polyder, polydiv, polyfit, polyint, polysub, polyval
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.polyadd([1, 2], [9, 5, 4])
+    array([9, 6, 6])
+
+    Using poly1d objects:
+
+    >>> p1 = np.poly1d([1, 2])
+    >>> p2 = np.poly1d([9, 5, 4])
+    >>> print(p1)
+    1 x + 2
+    >>> print(p2)
+       2
+    9 x + 5 x + 4
+    >>> print(np.polyadd(p1, p2))
+       2
+    9 x + 6 x + 6
+
+    """
+    truepoly = (isinstance(a1, poly1d) or isinstance(a2, poly1d))
+    a1 = atleast_1d(a1)
+    a2 = atleast_1d(a2)
+    diff = len(a2) - len(a1)
+    if diff == 0:
+        val = a1 + a2
+    elif diff > 0:
+        zr = NX.zeros(diff, a1.dtype)
+        val = NX.concatenate((zr, a1)) + a2
+    else:
+        zr = NX.zeros(abs(diff), a2.dtype)
+        val = a1 + NX.concatenate((zr, a2))
+    if truepoly:
+        val = poly1d(val)
+    return val
+
+
+@array_function_dispatch(_binary_op_dispatcher)
+def polysub(a1, a2):
+    """
+    Difference (subtraction) of two polynomials.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Given two polynomials `a1` and `a2`, returns ``a1 - a2``.
+    `a1` and `a2` can be either array_like sequences of the polynomials'
+    coefficients (including coefficients equal to zero), or `poly1d` objects.
+
+    Parameters
+    ----------
+    a1, a2 : array_like or poly1d
+        Minuend and subtrahend polynomials, respectively.
+
+    Returns
+    -------
+    out : ndarray or poly1d
+        Array or `poly1d` object of the difference polynomial's coefficients.
+
+    See Also
+    --------
+    polyval, polydiv, polymul, polyadd
+
+    Examples
+    --------
+
+    .. math:: (2 x^2 + 10 x - 2) - (3 x^2 + 10 x -4) = (-x^2 + 2)
+
+    >>> import numpy as np
+
+    >>> np.polysub([2, 10, -2], [3, 10, -4])
+    array([-1,  0,  2])
+
+    """
+    truepoly = (isinstance(a1, poly1d) or isinstance(a2, poly1d))
+    a1 = atleast_1d(a1)
+    a2 = atleast_1d(a2)
+    diff = len(a2) - len(a1)
+    if diff == 0:
+        val = a1 - a2
+    elif diff > 0:
+        zr = NX.zeros(diff, a1.dtype)
+        val = NX.concatenate((zr, a1)) - a2
+    else:
+        zr = NX.zeros(abs(diff), a2.dtype)
+        val = a1 - NX.concatenate((zr, a2))
+    if truepoly:
+        val = poly1d(val)
+    return val
+
+
+@array_function_dispatch(_binary_op_dispatcher)
+def polymul(a1, a2):
+    """
+    Find the product of two polynomials.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    Finds the polynomial resulting from the multiplication of the two input
+    polynomials. Each input must be either a poly1d object or a 1D sequence
+    of polynomial coefficients, from highest to lowest degree.
+
+    Parameters
+    ----------
+    a1, a2 : array_like or poly1d object
+        Input polynomials.
+
+    Returns
+    -------
+    out : ndarray or poly1d object
+        The polynomial resulting from the multiplication of the inputs. If
+        either inputs is a poly1d object, then the output is also a poly1d
+        object. Otherwise, it is a 1D array of polynomial coefficients from
+        highest to lowest degree.
+
+    See Also
+    --------
+    poly1d : A one-dimensional polynomial class.
+    poly, polyadd, polyder, polydiv, polyfit, polyint, polysub, polyval
+    convolve : Array convolution. Same output as polymul, but has parameter
+               for overlap mode.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.polymul([1, 2, 3], [9, 5, 1])
+    array([ 9, 23, 38, 17,  3])
+
+    Using poly1d objects:
+
+    >>> p1 = np.poly1d([1, 2, 3])
+    >>> p2 = np.poly1d([9, 5, 1])
+    >>> print(p1)
+       2
+    1 x + 2 x + 3
+    >>> print(p2)
+       2
+    9 x + 5 x + 1
+    >>> print(np.polymul(p1, p2))
+       4      3      2
+    9 x + 23 x + 38 x + 17 x + 3
+
+    """
+    truepoly = (isinstance(a1, poly1d) or isinstance(a2, poly1d))
+    a1, a2 = poly1d(a1), poly1d(a2)
+    val = NX.convolve(a1, a2)
+    if truepoly:
+        val = poly1d(val)
+    return val
+
+
+def _polydiv_dispatcher(u, v):
+    return (u, v)
+
+
+@array_function_dispatch(_polydiv_dispatcher)
+def polydiv(u, v):
+    """
+    Returns the quotient and remainder of polynomial division.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    The input arrays are the coefficients (including any coefficients
+    equal to zero) of the "numerator" (dividend) and "denominator"
+    (divisor) polynomials, respectively.
+
+    Parameters
+    ----------
+    u : array_like or poly1d
+        Dividend polynomial's coefficients.
+
+    v : array_like or poly1d
+        Divisor polynomial's coefficients.
+
+    Returns
+    -------
+    q : ndarray
+        Coefficients, including those equal to zero, of the quotient.
+    r : ndarray
+        Coefficients, including those equal to zero, of the remainder.
+
+    See Also
+    --------
+    poly, polyadd, polyder, polydiv, polyfit, polyint, polymul, polysub
+    polyval
+
+    Notes
+    -----
+    Both `u` and `v` must be 0-d or 1-d (ndim = 0 or 1), but `u.ndim` need
+    not equal `v.ndim`. In other words, all four possible combinations -
+    ``u.ndim = v.ndim = 0``, ``u.ndim = v.ndim = 1``,
+    ``u.ndim = 1, v.ndim = 0``, and ``u.ndim = 0, v.ndim = 1`` - work.
+
+    Examples
+    --------
+
+    .. math:: \\frac{3x^2 + 5x + 2}{2x + 1} = 1.5x + 1.75, remainder 0.25
+
+    >>> import numpy as np
+
+    >>> x = np.array([3.0, 5.0, 2.0])
+    >>> y = np.array([2.0, 1.0])
+    >>> np.polydiv(x, y)
+    (array([1.5 , 1.75]), array([0.25]))
+
+    """
+    truepoly = (isinstance(u, poly1d) or isinstance(v, poly1d))
+    u = atleast_1d(u) + 0.0
+    v = atleast_1d(v) + 0.0
+    # w has the common type
+    w = u[0] + v[0]
+    m = len(u) - 1
+    n = len(v) - 1
+    scale = 1. / v[0]
+    q = NX.zeros((max(m - n + 1, 1),), w.dtype)
+    r = u.astype(w.dtype)
+    for k in range(m - n + 1):
+        d = scale * r[k]
+        q[k] = d
+        r[k:k + n + 1] -= d * v
+    while NX.allclose(r[0], 0, rtol=1e-14) and (r.shape[-1] > 1):
+        r = r[1:]
+    if truepoly:
+        return poly1d(q), poly1d(r)
+    return q, r
+
+
+_poly_mat = re.compile(r"\*\*([0-9]*)")
+def _raise_power(astr, wrap=70):
+    n = 0
+    line1 = ''
+    line2 = ''
+    output = ' '
+    while True:
+        mat = _poly_mat.search(astr, n)
+        if mat is None:
+            break
+        span = mat.span()
+        power = mat.groups()[0]
+        partstr = astr[n:span[0]]
+        n = span[1]
+        toadd2 = partstr + ' ' * (len(power) - 1)
+        toadd1 = ' ' * (len(partstr) - 1) + power
+        if ((len(line2) + len(toadd2) > wrap) or
+                (len(line1) + len(toadd1) > wrap)):
+            output += line1 + "\n" + line2 + "\n "
+            line1 = toadd1
+            line2 = toadd2
+        else:
+            line2 += partstr + ' ' * (len(power) - 1)
+            line1 += ' ' * (len(partstr) - 1) + power
+    output += line1 + "\n" + line2
+    return output + astr[n:]
+
+
+@set_module('numpy')
+class poly1d:
+    """
+    A one-dimensional polynomial class.
+
+    .. note::
+       This forms part of the old polynomial API. Since version 1.4, the
+       new polynomial API defined in `numpy.polynomial` is preferred.
+       A summary of the differences can be found in the
+       :doc:`transition guide </reference/routines.polynomials>`.
+
+    A convenience class, used to encapsulate "natural" operations on
+    polynomials so that said operations may take on their customary
+    form in code (see Examples).
+
+    Parameters
+    ----------
+    c_or_r : array_like
+        The polynomial's coefficients, in decreasing powers, or if
+        the value of the second parameter is True, the polynomial's
+        roots (values where the polynomial evaluates to 0).  For example,
+        ``poly1d([1, 2, 3])`` returns an object that represents
+        :math:`x^2 + 2x + 3`, whereas ``poly1d([1, 2, 3], True)`` returns
+        one that represents :math:`(x-1)(x-2)(x-3) = x^3 - 6x^2 + 11x -6`.
+    r : bool, optional
+        If True, `c_or_r` specifies the polynomial's roots; the default
+        is False.
+    variable : str, optional
+        Changes the variable used when printing `p` from `x` to `variable`
+        (see Examples).
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Construct the polynomial :math:`x^2 + 2x + 3`:
+
+    >>> import numpy as np
+
+    >>> p = np.poly1d([1, 2, 3])
+    >>> print(np.poly1d(p))
+       2
+    1 x + 2 x + 3
+
+    Evaluate the polynomial at :math:`x = 0.5`:
+
+    >>> p(0.5)
+    4.25
+
+    Find the roots:
+
+    >>> p.r
+    array([-1.+1.41421356j, -1.-1.41421356j])
+    >>> p(p.r)
+    array([ -4.44089210e-16+0.j,  -4.44089210e-16+0.j]) # may vary
+
+    These numbers in the previous line represent (0, 0) to machine precision
+
+    Show the coefficients:
+
+    >>> p.c
+    array([1, 2, 3])
+
+    Display the order (the leading zero-coefficients are removed):
+
+    >>> p.order
+    2
+
+    Show the coefficient of the k-th power in the polynomial
+    (which is equivalent to ``p.c[-(i+1)]``):
+
+    >>> p[1]
+    2
+
+    Polynomials can be added, subtracted, multiplied, and divided
+    (returns quotient and remainder):
+
+    >>> p * p
+    poly1d([ 1,  4, 10, 12,  9])
+
+    >>> (p**3 + 4) / p
+    (poly1d([ 1.,  4., 10., 12.,  9.]), poly1d([4.]))
+
+    ``asarray(p)`` gives the coefficient array, so polynomials can be
+    used in all functions that accept arrays:
+
+    >>> p**2 # square of polynomial
+    poly1d([ 1,  4, 10, 12,  9])
+
+    >>> np.square(p) # square of individual coefficients
+    array([1, 4, 9])
+
+    The variable used in the string representation of `p` can be modified,
+    using the `variable` parameter:
+
+    >>> p = np.poly1d([1,2,3], variable='z')
+    >>> print(p)
+       2
+    1 z + 2 z + 3
+
+    Construct a polynomial from its roots:
+
+    >>> np.poly1d([1, 2], True)
+    poly1d([ 1., -3.,  2.])
+
+    This is the same polynomial as obtained by:
+
+    >>> np.poly1d([1, -1]) * np.poly1d([1, -2])
+    poly1d([ 1, -3,  2])
+
+    """
+    __hash__ = None
+
+    @property
+    def coeffs(self):
+        """ The polynomial coefficients """
+        return self._coeffs
+
+    @coeffs.setter
+    def coeffs(self, value):
+        # allowing this makes p.coeffs *= 2 legal
+        if value is not self._coeffs:
+            raise AttributeError("Cannot set attribute")
+
+    @property
+    def variable(self):
+        """ The name of the polynomial variable """
+        return self._variable
+
+    # calculated attributes
+    @property
+    def order(self):
+        """ The order or degree of the polynomial """
+        return len(self._coeffs) - 1
+
+    @property
+    def roots(self):
+        """ The roots of the polynomial, where self(x) == 0 """
+        return roots(self._coeffs)
+
+    # our internal _coeffs property need to be backed by __dict__['coeffs'] for
+    # scipy to work correctly.
+    @property
+    def _coeffs(self):
+        return self.__dict__['coeffs']
+
+    @_coeffs.setter
+    def _coeffs(self, coeffs):
+        self.__dict__['coeffs'] = coeffs
+
+    # alias attributes
+    r = roots
+    c = coef = coefficients = coeffs
+    o = order
+
+    def __init__(self, c_or_r, r=False, variable=None):
+        if isinstance(c_or_r, poly1d):
+            self._variable = c_or_r._variable
+            self._coeffs = c_or_r._coeffs
+
+            if set(c_or_r.__dict__) - set(self.__dict__):
+                msg = ("In the future extra properties will not be copied "
+                       "across when constructing one poly1d from another")
+                warnings.warn(msg, FutureWarning, stacklevel=2)
+                self.__dict__.update(c_or_r.__dict__)
+
+            if variable is not None:
+                self._variable = variable
+            return
+        if r:
+            c_or_r = poly(c_or_r)
+        c_or_r = atleast_1d(c_or_r)
+        if c_or_r.ndim > 1:
+            raise ValueError("Polynomial must be 1d only.")
+        c_or_r = trim_zeros(c_or_r, trim='f')
+        if len(c_or_r) == 0:
+            c_or_r = NX.array([0], dtype=c_or_r.dtype)
+        self._coeffs = c_or_r
+        if variable is None:
+            variable = 'x'
+        self._variable = variable
+
+    def __array__(self, t=None, copy=None):
+        if t:
+            return NX.asarray(self.coeffs, t, copy=copy)
+        else:
+            return NX.asarray(self.coeffs, copy=copy)
+
+    def __repr__(self):
+        vals = repr(self.coeffs)
+        vals = vals[6:-1]
+        return f"poly1d({vals})"
+
+    def __len__(self):
+        return self.order
+
+    def __str__(self):
+        thestr = "0"
+        var = self.variable
+
+        # Remove leading zeros
+        coeffs = self.coeffs[NX.logical_or.accumulate(self.coeffs != 0)]
+        N = len(coeffs) - 1
+
+        def fmt_float(q):
+            s = f'{q:.4g}'
+            s = s.removesuffix('.0000')
+            return s
+
+        for k, coeff in enumerate(coeffs):
+            if not iscomplex(coeff):
+                coefstr = fmt_float(real(coeff))
+            elif real(coeff) == 0:
+                coefstr = f'{fmt_float(imag(coeff))}j'
+            else:
+                coefstr = f'({fmt_float(real(coeff))} + {fmt_float(imag(coeff))}j)'
+
+            power = (N - k)
+            if power == 0:
+                if coefstr != '0':
+                    newstr = f'{coefstr}'
+                elif k == 0:
+                    newstr = '0'
+                else:
+                    newstr = ''
+            elif power == 1:
+                if coefstr == '0':
+                    newstr = ''
+                elif coefstr == 'b':
+                    newstr = var
+                else:
+                    newstr = f'{coefstr} {var}'
+            elif coefstr == '0':
+                newstr = ''
+            elif coefstr == 'b':
+                newstr = '%s**%d' % (var, power,)
+            else:
+                newstr = '%s %s**%d' % (coefstr, var, power)
+
+            if k > 0:
+                if newstr != '':
+                    if newstr.startswith('-'):
+                        thestr = f"{thestr} - {newstr[1:]}"
+                    else:
+                        thestr = f"{thestr} + {newstr}"
+            else:
+                thestr = newstr
+        return _raise_power(thestr)
+
+    def __call__(self, val):
+        return polyval(self.coeffs, val)
+
+    def __neg__(self):
+        return poly1d(-self.coeffs)
+
+    def __pos__(self):
+        return self
+
+    def __mul__(self, other):
+        if isscalar(other):
+            return poly1d(self.coeffs * other)
+        else:
+            other = poly1d(other)
+            return poly1d(polymul(self.coeffs, other.coeffs))
+
+    def __rmul__(self, other):
+        if isscalar(other):
+            return poly1d(other * self.coeffs)
+        else:
+            other = poly1d(other)
+            return poly1d(polymul(self.coeffs, other.coeffs))
+
+    def __add__(self, other):
+        other = poly1d(other)
+        return poly1d(polyadd(self.coeffs, other.coeffs))
+
+    def __radd__(self, other):
+        other = poly1d(other)
+        return poly1d(polyadd(self.coeffs, other.coeffs))
+
+    def __pow__(self, val):
+        if not isscalar(val) or int(val) != val or val < 0:
+            raise ValueError("Power to non-negative integers only.")
+        res = [1]
+        for _ in range(val):
+            res = polymul(self.coeffs, res)
+        return poly1d(res)
+
+    def __sub__(self, other):
+        other = poly1d(other)
+        return poly1d(polysub(self.coeffs, other.coeffs))
+
+    def __rsub__(self, other):
+        other = poly1d(other)
+        return poly1d(polysub(other.coeffs, self.coeffs))
+
+    def __truediv__(self, other):
+        if isscalar(other):
+            return poly1d(self.coeffs / other)
+        else:
+            other = poly1d(other)
+            return polydiv(self, other)
+
+    def __rtruediv__(self, other):
+        if isscalar(other):
+            return poly1d(other / self.coeffs)
+        else:
+            other = poly1d(other)
+            return polydiv(other, self)
+
+    def __eq__(self, other):
+        if not isinstance(other, poly1d):
+            return NotImplemented
+        if self.coeffs.shape != other.coeffs.shape:
+            return False
+        return (self.coeffs == other.coeffs).all()
+
+    def __ne__(self, other):
+        if not isinstance(other, poly1d):
+            return NotImplemented
+        return not self.__eq__(other)
+
+    def __getitem__(self, val):
+        ind = self.order - val
+        if val > self.order:
+            return self.coeffs.dtype.type(0)
+        if val < 0:
+            return self.coeffs.dtype.type(0)
+        return self.coeffs[ind]
+
+    def __setitem__(self, key, val):
+        ind = self.order - key
+        if key < 0:
+            raise ValueError("Does not support negative powers.")
+        if key > self.order:
+            zr = NX.zeros(key - self.order, self.coeffs.dtype)
+            self._coeffs = NX.concatenate((zr, self.coeffs))
+            ind = 0
+        self._coeffs[ind] = val
+
+    def __iter__(self):
+        return iter(self.coeffs)
+
+    def integ(self, m=1, k=0):
+        """
+        Return an antiderivative (indefinite integral) of this polynomial.
+
+        Refer to `polyint` for full documentation.
+
+        See Also
+        --------
+        polyint : equivalent function
+
+        """
+        return poly1d(polyint(self.coeffs, m=m, k=k))
+
+    def deriv(self, m=1):
+        """
+        Return a derivative of this polynomial.
+
+        Refer to `polyder` for full documentation.
+
+        See Also
+        --------
+        polyder : equivalent function
+
+        """
+        return poly1d(polyder(self.coeffs, m=m))
+
+# Stuff to do on module import
+
+
+warnings.simplefilter('always', RankWarning)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..2d8f2647ea6be904bc3aebdb070fbbe893655a18
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_polynomial_impl.pyi
@@ -0,0 +1,338 @@
+from typing import (
+    Any,
+    Literal as L,
+    NoReturn,
+    SupportsIndex,
+    SupportsInt,
+    TypeAlias,
+    TypeVar,
+    overload,
+)
+
+import numpy as np
+from numpy import (
+    complex128,
+    complexfloating,
+    float64,
+    floating,
+    int32,
+    int64,
+    object_,
+    poly1d,
+    signedinteger,
+    unsignedinteger,
+)
+from numpy._typing import (
+    ArrayLike,
+    NDArray,
+    _ArrayLikeBool_co,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ArrayLikeInt_co,
+    _ArrayLikeObject_co,
+    _ArrayLikeUInt_co,
+)
+
+_T = TypeVar("_T")
+
+_2Tup: TypeAlias = tuple[_T, _T]
+_5Tup: TypeAlias = tuple[
+    _T,
+    NDArray[float64],
+    NDArray[int32],
+    NDArray[float64],
+    NDArray[float64],
+]
+
+__all__ = [
+    "poly",
+    "roots",
+    "polyint",
+    "polyder",
+    "polyadd",
+    "polysub",
+    "polymul",
+    "polydiv",
+    "polyval",
+    "poly1d",
+    "polyfit",
+]
+
+def poly(seq_of_zeros: ArrayLike) -> NDArray[floating]: ...
+
+# Returns either a float or complex array depending on the input values.
+# See `np.linalg.eigvals`.
+def roots(p: ArrayLike) -> NDArray[complexfloating] | NDArray[floating]: ...
+
+@overload
+def polyint(
+    p: poly1d,
+    m: SupportsInt | SupportsIndex = 1,
+    k: _ArrayLikeComplex_co | _ArrayLikeObject_co | None = None,
+) -> poly1d: ...
+@overload
+def polyint(
+    p: _ArrayLikeFloat_co,
+    m: SupportsInt | SupportsIndex = 1,
+    k: _ArrayLikeFloat_co | None = None,
+) -> NDArray[floating]: ...
+@overload
+def polyint(
+    p: _ArrayLikeComplex_co,
+    m: SupportsInt | SupportsIndex = 1,
+    k: _ArrayLikeComplex_co | None = None,
+) -> NDArray[complexfloating]: ...
+@overload
+def polyint(
+    p: _ArrayLikeObject_co,
+    m: SupportsInt | SupportsIndex = 1,
+    k: _ArrayLikeObject_co | None = None,
+) -> NDArray[object_]: ...
+
+@overload
+def polyder(
+    p: poly1d,
+    m: SupportsInt | SupportsIndex = 1,
+) -> poly1d: ...
+@overload
+def polyder(
+    p: _ArrayLikeFloat_co,
+    m: SupportsInt | SupportsIndex = 1,
+) -> NDArray[floating]: ...
+@overload
+def polyder(
+    p: _ArrayLikeComplex_co,
+    m: SupportsInt | SupportsIndex = 1,
+) -> NDArray[complexfloating]: ...
+@overload
+def polyder(
+    p: _ArrayLikeObject_co,
+    m: SupportsInt | SupportsIndex = 1,
+) -> NDArray[object_]: ...
+
+@overload
+def polyfit(
+    x: _ArrayLikeFloat_co,
+    y: _ArrayLikeFloat_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    full: L[False] = False,
+    w: _ArrayLikeFloat_co | None = None,
+    cov: L[False] = False,
+) -> NDArray[float64]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    full: L[False] = False,
+    w: _ArrayLikeFloat_co | None = None,
+    cov: L[False] = False,
+) -> NDArray[complex128]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeFloat_co,
+    y: _ArrayLikeFloat_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    full: L[False] = False,
+    w: _ArrayLikeFloat_co | None = None,
+    *,
+    cov: L[True, "unscaled"],
+) -> _2Tup[NDArray[float64]]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    full: L[False] = False,
+    w: _ArrayLikeFloat_co | None = None,
+    *,
+    cov: L[True, "unscaled"],
+) -> _2Tup[NDArray[complex128]]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeFloat_co,
+    y: _ArrayLikeFloat_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None,
+    full: L[True],
+    w: _ArrayLikeFloat_co | None = None,
+    cov: bool | L["unscaled"] = False,
+) -> _5Tup[NDArray[float64]]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeFloat_co,
+    y: _ArrayLikeFloat_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    *,
+    full: L[True],
+    w: _ArrayLikeFloat_co | None = None,
+    cov: bool | L["unscaled"] = False,
+) -> _5Tup[NDArray[float64]]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None,
+    full: L[True],
+    w: _ArrayLikeFloat_co | None = None,
+    cov: bool | L["unscaled"] = False,
+) -> _5Tup[NDArray[complex128]]: ...
+@overload
+def polyfit(
+    x: _ArrayLikeComplex_co,
+    y: _ArrayLikeComplex_co,
+    deg: SupportsIndex | SupportsInt,
+    rcond: float | None = None,
+    *,
+    full: L[True],
+    w: _ArrayLikeFloat_co | None = None,
+    cov: bool | L["unscaled"] = False,
+) -> _5Tup[NDArray[complex128]]: ...
+
+@overload
+def polyval(
+    p: _ArrayLikeBool_co,
+    x: _ArrayLikeBool_co,
+) -> NDArray[int64]: ...
+@overload
+def polyval(
+    p: _ArrayLikeUInt_co,
+    x: _ArrayLikeUInt_co,
+) -> NDArray[unsignedinteger]: ...
+@overload
+def polyval(
+    p: _ArrayLikeInt_co,
+    x: _ArrayLikeInt_co,
+) -> NDArray[signedinteger]: ...
+@overload
+def polyval(
+    p: _ArrayLikeFloat_co,
+    x: _ArrayLikeFloat_co,
+) -> NDArray[floating]: ...
+@overload
+def polyval(
+    p: _ArrayLikeComplex_co,
+    x: _ArrayLikeComplex_co,
+) -> NDArray[complexfloating]: ...
+@overload
+def polyval(
+    p: _ArrayLikeObject_co,
+    x: _ArrayLikeObject_co,
+) -> NDArray[object_]: ...
+
+@overload
+def polyadd(
+    a1: poly1d,
+    a2: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+) -> poly1d: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+    a2: poly1d,
+) -> poly1d: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeBool_co,
+    a2: _ArrayLikeBool_co,
+) -> NDArray[np.bool]: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeUInt_co,
+    a2: _ArrayLikeUInt_co,
+) -> NDArray[unsignedinteger]: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeInt_co,
+    a2: _ArrayLikeInt_co,
+) -> NDArray[signedinteger]: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeFloat_co,
+    a2: _ArrayLikeFloat_co,
+) -> NDArray[floating]: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeComplex_co,
+    a2: _ArrayLikeComplex_co,
+) -> NDArray[complexfloating]: ...
+@overload
+def polyadd(
+    a1: _ArrayLikeObject_co,
+    a2: _ArrayLikeObject_co,
+) -> NDArray[object_]: ...
+
+@overload
+def polysub(
+    a1: poly1d,
+    a2: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+) -> poly1d: ...
+@overload
+def polysub(
+    a1: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+    a2: poly1d,
+) -> poly1d: ...
+@overload
+def polysub(
+    a1: _ArrayLikeBool_co,
+    a2: _ArrayLikeBool_co,
+) -> NoReturn: ...
+@overload
+def polysub(
+    a1: _ArrayLikeUInt_co,
+    a2: _ArrayLikeUInt_co,
+) -> NDArray[unsignedinteger]: ...
+@overload
+def polysub(
+    a1: _ArrayLikeInt_co,
+    a2: _ArrayLikeInt_co,
+) -> NDArray[signedinteger]: ...
+@overload
+def polysub(
+    a1: _ArrayLikeFloat_co,
+    a2: _ArrayLikeFloat_co,
+) -> NDArray[floating]: ...
+@overload
+def polysub(
+    a1: _ArrayLikeComplex_co,
+    a2: _ArrayLikeComplex_co,
+) -> NDArray[complexfloating]: ...
+@overload
+def polysub(
+    a1: _ArrayLikeObject_co,
+    a2: _ArrayLikeObject_co,
+) -> NDArray[object_]: ...
+
+# NOTE: Not an alias, but they do have the same signature (that we can reuse)
+polymul = polyadd
+
+@overload
+def polydiv(
+    u: poly1d,
+    v: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+) -> _2Tup[poly1d]: ...
+@overload
+def polydiv(
+    u: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+    v: poly1d,
+) -> _2Tup[poly1d]: ...
+@overload
+def polydiv(
+    u: _ArrayLikeFloat_co,
+    v: _ArrayLikeFloat_co,
+) -> _2Tup[NDArray[floating]]: ...
+@overload
+def polydiv(
+    u: _ArrayLikeComplex_co,
+    v: _ArrayLikeComplex_co,
+) -> _2Tup[NDArray[complexfloating]]: ...
+@overload
+def polydiv(
+    u: _ArrayLikeObject_co,
+    v: _ArrayLikeObject_co,
+) -> _2Tup[NDArray[Any]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..b90ce9a33dd8ec959c23c9c78aee480787a17412
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.py
@@ -0,0 +1,642 @@
+"""
+Wrapper functions to more user-friendly calling of certain math functions
+whose output data-type is different than the input data-type in certain
+domains of the input.
+
+For example, for functions like `log` with branch cuts, the versions in this
+module provide the mathematically valid answers in the complex plane::
+
+  >>> import math
+  >>> np.emath.log(-math.exp(1)) == (1+1j*math.pi)
+  True
+
+Similarly, `sqrt`, other base logarithms, `power` and trig functions are
+correctly handled.  See their respective docstrings for specific examples.
+
+"""
+import numpy._core.numeric as nx
+import numpy._core.numerictypes as nt
+from numpy._core.numeric import any, asarray
+from numpy._core.overrides import array_function_dispatch, set_module
+from numpy.lib._type_check_impl import isreal
+
+__all__ = [
+    'sqrt', 'log', 'log2', 'logn', 'log10', 'power', 'arccos', 'arcsin',
+    'arctanh'
+    ]
+
+
+_ln2 = nx.log(2.0)
+
+
+def _tocomplex(arr):
+    """Convert its input `arr` to a complex array.
+
+    The input is returned as a complex array of the smallest type that will fit
+    the original data: types like single, byte, short, etc. become csingle,
+    while others become cdouble.
+
+    A copy of the input is always made.
+
+    Parameters
+    ----------
+    arr : array
+
+    Returns
+    -------
+    array
+        An array with the same input data as the input but in complex form.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    First, consider an input of type short:
+
+    >>> a = np.array([1,2,3],np.short)
+
+    >>> ac = np.lib.scimath._tocomplex(a); ac
+    array([1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64)
+
+    >>> ac.dtype
+    dtype('complex64')
+
+    If the input is of type double, the output is correspondingly of the
+    complex double type as well:
+
+    >>> b = np.array([1,2,3],np.double)
+
+    >>> bc = np.lib.scimath._tocomplex(b); bc
+    array([1.+0.j, 2.+0.j, 3.+0.j])
+
+    >>> bc.dtype
+    dtype('complex128')
+
+    Note that even if the input was complex to begin with, a copy is still
+    made, since the astype() method always copies:
+
+    >>> c = np.array([1,2,3],np.csingle)
+
+    >>> cc = np.lib.scimath._tocomplex(c); cc
+    array([1.+0.j,  2.+0.j,  3.+0.j], dtype=complex64)
+
+    >>> c *= 2; c
+    array([2.+0.j,  4.+0.j,  6.+0.j], dtype=complex64)
+
+    >>> cc
+    array([1.+0.j,  2.+0.j,  3.+0.j], dtype=complex64)
+    """
+    if issubclass(arr.dtype.type, (nt.single, nt.byte, nt.short, nt.ubyte,
+                                   nt.ushort, nt.csingle)):
+        return arr.astype(nt.csingle)
+    else:
+        return arr.astype(nt.cdouble)
+
+
+def _fix_real_lt_zero(x):
+    """Convert `x` to complex if it has real, negative components.
+
+    Otherwise, output is just the array version of the input (via asarray).
+
+    Parameters
+    ----------
+    x : array_like
+
+    Returns
+    -------
+    array
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.lib.scimath._fix_real_lt_zero([1,2])
+    array([1, 2])
+
+    >>> np.lib.scimath._fix_real_lt_zero([-1,2])
+    array([-1.+0.j,  2.+0.j])
+
+    """
+    x = asarray(x)
+    if any(isreal(x) & (x < 0)):
+        x = _tocomplex(x)
+    return x
+
+
+def _fix_int_lt_zero(x):
+    """Convert `x` to double if it has real, negative components.
+
+    Otherwise, output is just the array version of the input (via asarray).
+
+    Parameters
+    ----------
+    x : array_like
+
+    Returns
+    -------
+    array
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.lib.scimath._fix_int_lt_zero([1,2])
+    array([1, 2])
+
+    >>> np.lib.scimath._fix_int_lt_zero([-1,2])
+    array([-1.,  2.])
+    """
+    x = asarray(x)
+    if any(isreal(x) & (x < 0)):
+        x = x * 1.0
+    return x
+
+
+def _fix_real_abs_gt_1(x):
+    """Convert `x` to complex if it has real components x_i with abs(x_i)>1.
+
+    Otherwise, output is just the array version of the input (via asarray).
+
+    Parameters
+    ----------
+    x : array_like
+
+    Returns
+    -------
+    array
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.lib.scimath._fix_real_abs_gt_1([0,1])
+    array([0, 1])
+
+    >>> np.lib.scimath._fix_real_abs_gt_1([0,2])
+    array([0.+0.j, 2.+0.j])
+    """
+    x = asarray(x)
+    if any(isreal(x) & (abs(x) > 1)):
+        x = _tocomplex(x)
+    return x
+
+
+def _unary_dispatcher(x):
+    return (x,)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def sqrt(x):
+    """
+    Compute the square root of x.
+
+    For negative input elements, a complex value is returned
+    (unlike `numpy.sqrt` which returns NaN).
+
+    Parameters
+    ----------
+    x : array_like
+       The input value(s).
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The square root of `x`. If `x` was a scalar, so is `out`,
+       otherwise an array is returned.
+
+    See Also
+    --------
+    numpy.sqrt
+
+    Examples
+    --------
+    For real, non-negative inputs this works just like `numpy.sqrt`:
+
+    >>> import numpy as np
+
+    >>> np.emath.sqrt(1)
+    1.0
+    >>> np.emath.sqrt([1, 4])
+    array([1.,  2.])
+
+    But it automatically handles negative inputs:
+
+    >>> np.emath.sqrt(-1)
+    1j
+    >>> np.emath.sqrt([-1,4])
+    array([0.+1.j, 2.+0.j])
+
+    Different results are expected because:
+    floating point 0.0 and -0.0 are distinct.
+
+    For more control, explicitly use complex() as follows:
+
+    >>> np.emath.sqrt(complex(-4.0, 0.0))
+    2j
+    >>> np.emath.sqrt(complex(-4.0, -0.0))
+    -2j
+    """
+    x = _fix_real_lt_zero(x)
+    return nx.sqrt(x)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def log(x):
+    """
+    Compute the natural logarithm of `x`.
+
+    Return the "principal value" (for a description of this, see `numpy.log`)
+    of :math:`log_e(x)`. For real `x > 0`, this is a real number (``log(0)``
+    returns ``-inf`` and ``log(np.inf)`` returns ``inf``). Otherwise, the
+    complex principle value is returned.
+
+    Parameters
+    ----------
+    x : array_like
+       The value(s) whose log is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The log of the `x` value(s). If `x` was a scalar, so is `out`,
+       otherwise an array is returned.
+
+    See Also
+    --------
+    numpy.log
+
+    Notes
+    -----
+    For a log() that returns ``NAN`` when real `x < 0`, use `numpy.log`
+    (note, however, that otherwise `numpy.log` and this `log` are identical,
+    i.e., both return ``-inf`` for `x = 0`, ``inf`` for `x = inf`, and,
+    notably, the complex principle value if ``x.imag != 0``).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.emath.log(np.exp(1))
+    1.0
+
+    Negative arguments are handled "correctly" (recall that
+    ``exp(log(x)) == x`` does *not* hold for real ``x < 0``):
+
+    >>> np.emath.log(-np.exp(1)) == (1 + np.pi * 1j)
+    True
+
+    """
+    x = _fix_real_lt_zero(x)
+    return nx.log(x)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def log10(x):
+    """
+    Compute the logarithm base 10 of `x`.
+
+    Return the "principal value" (for a description of this, see
+    `numpy.log10`) of :math:`log_{10}(x)`. For real `x > 0`, this
+    is a real number (``log10(0)`` returns ``-inf`` and ``log10(np.inf)``
+    returns ``inf``). Otherwise, the complex principle value is returned.
+
+    Parameters
+    ----------
+    x : array_like or scalar
+       The value(s) whose log base 10 is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The log base 10 of the `x` value(s). If `x` was a scalar, so is `out`,
+       otherwise an array object is returned.
+
+    See Also
+    --------
+    numpy.log10
+
+    Notes
+    -----
+    For a log10() that returns ``NAN`` when real `x < 0`, use `numpy.log10`
+    (note, however, that otherwise `numpy.log10` and this `log10` are
+    identical, i.e., both return ``-inf`` for `x = 0`, ``inf`` for `x = inf`,
+    and, notably, the complex principle value if ``x.imag != 0``).
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    (We set the printing precision so the example can be auto-tested)
+
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.log10(10**1)
+    1.0
+
+    >>> np.emath.log10([-10**1, -10**2, 10**2])
+    array([1.+1.3644j, 2.+1.3644j, 2.+0.j    ])
+
+    """
+    x = _fix_real_lt_zero(x)
+    return nx.log10(x)
+
+
+def _logn_dispatcher(n, x):
+    return (n, x,)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_logn_dispatcher)
+def logn(n, x):
+    """
+    Take log base n of x.
+
+    If `x` contains negative inputs, the answer is computed and returned in the
+    complex domain.
+
+    Parameters
+    ----------
+    n : array_like
+       The integer base(s) in which the log is taken.
+    x : array_like
+       The value(s) whose log base `n` is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The log base `n` of the `x` value(s). If `x` was a scalar, so is
+       `out`, otherwise an array is returned.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.logn(2, [4, 8])
+    array([2., 3.])
+    >>> np.emath.logn(2, [-4, -8, 8])
+    array([2.+4.5324j, 3.+4.5324j, 3.+0.j    ])
+
+    """
+    x = _fix_real_lt_zero(x)
+    n = _fix_real_lt_zero(n)
+    return nx.log(x) / nx.log(n)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def log2(x):
+    """
+    Compute the logarithm base 2 of `x`.
+
+    Return the "principal value" (for a description of this, see
+    `numpy.log2`) of :math:`log_2(x)`. For real `x > 0`, this is
+    a real number (``log2(0)`` returns ``-inf`` and ``log2(np.inf)`` returns
+    ``inf``). Otherwise, the complex principle value is returned.
+
+    Parameters
+    ----------
+    x : array_like
+       The value(s) whose log base 2 is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The log base 2 of the `x` value(s). If `x` was a scalar, so is `out`,
+       otherwise an array is returned.
+
+    See Also
+    --------
+    numpy.log2
+
+    Notes
+    -----
+    For a log2() that returns ``NAN`` when real `x < 0`, use `numpy.log2`
+    (note, however, that otherwise `numpy.log2` and this `log2` are
+    identical, i.e., both return ``-inf`` for `x = 0`, ``inf`` for `x = inf`,
+    and, notably, the complex principle value if ``x.imag != 0``).
+
+    Examples
+    --------
+
+    We set the printing precision so the example can be auto-tested:
+
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.log2(8)
+    3.0
+    >>> np.emath.log2([-4, -8, 8])
+    array([2.+4.5324j, 3.+4.5324j, 3.+0.j    ])
+
+    """
+    x = _fix_real_lt_zero(x)
+    return nx.log2(x)
+
+
+def _power_dispatcher(x, p):
+    return (x, p)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_power_dispatcher)
+def power(x, p):
+    """
+    Return x to the power p, (x**p).
+
+    If `x` contains negative values, the output is converted to the
+    complex domain.
+
+    Parameters
+    ----------
+    x : array_like
+        The input value(s).
+    p : array_like of ints
+        The power(s) to which `x` is raised. If `x` contains multiple values,
+        `p` has to either be a scalar, or contain the same number of values
+        as `x`. In the latter case, the result is
+        ``x[0]**p[0], x[1]**p[1], ...``.
+
+    Returns
+    -------
+    out : ndarray or scalar
+        The result of ``x**p``. If `x` and `p` are scalars, so is `out`,
+        otherwise an array is returned.
+
+    See Also
+    --------
+    numpy.power
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.power(2, 2)
+    4
+
+    >>> np.emath.power([2, 4], 2)
+    array([ 4, 16])
+
+    >>> np.emath.power([2, 4], -2)
+    array([0.25  ,  0.0625])
+
+    >>> np.emath.power([-2, 4], 2)
+    array([ 4.-0.j, 16.+0.j])
+
+    >>> np.emath.power([2, 4], [2, 4])
+    array([ 4, 256])
+
+    """
+    x = _fix_real_lt_zero(x)
+    p = _fix_int_lt_zero(p)
+    return nx.power(x, p)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def arccos(x):
+    """
+    Compute the inverse cosine of x.
+
+    Return the "principal value" (for a description of this, see
+    `numpy.arccos`) of the inverse cosine of `x`. For real `x` such that
+    `abs(x) <= 1`, this is a real number in the closed interval
+    :math:`[0, \\pi]`.  Otherwise, the complex principle value is returned.
+
+    Parameters
+    ----------
+    x : array_like or scalar
+       The value(s) whose arccos is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The inverse cosine(s) of the `x` value(s). If `x` was a scalar, so
+       is `out`, otherwise an array object is returned.
+
+    See Also
+    --------
+    numpy.arccos
+
+    Notes
+    -----
+    For an arccos() that returns ``NAN`` when real `x` is not in the
+    interval ``[-1,1]``, use `numpy.arccos`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.arccos(1) # a scalar is returned
+    0.0
+
+    >>> np.emath.arccos([1,2])
+    array([0.-0.j   , 0.-1.317j])
+
+    """
+    x = _fix_real_abs_gt_1(x)
+    return nx.arccos(x)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def arcsin(x):
+    """
+    Compute the inverse sine of x.
+
+    Return the "principal value" (for a description of this, see
+    `numpy.arcsin`) of the inverse sine of `x`. For real `x` such that
+    `abs(x) <= 1`, this is a real number in the closed interval
+    :math:`[-\\pi/2, \\pi/2]`.  Otherwise, the complex principle value is
+    returned.
+
+    Parameters
+    ----------
+    x : array_like or scalar
+       The value(s) whose arcsin is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The inverse sine(s) of the `x` value(s). If `x` was a scalar, so
+       is `out`, otherwise an array object is returned.
+
+    See Also
+    --------
+    numpy.arcsin
+
+    Notes
+    -----
+    For an arcsin() that returns ``NAN`` when real `x` is not in the
+    interval ``[-1,1]``, use `numpy.arcsin`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.arcsin(0)
+    0.0
+
+    >>> np.emath.arcsin([0,1])
+    array([0.    , 1.5708])
+
+    """
+    x = _fix_real_abs_gt_1(x)
+    return nx.arcsin(x)
+
+
+@set_module('numpy.lib.scimath')
+@array_function_dispatch(_unary_dispatcher)
+def arctanh(x):
+    """
+    Compute the inverse hyperbolic tangent of `x`.
+
+    Return the "principal value" (for a description of this, see
+    `numpy.arctanh`) of ``arctanh(x)``. For real `x` such that
+    ``abs(x) < 1``, this is a real number.  If `abs(x) > 1`, or if `x` is
+    complex, the result is complex. Finally, `x = 1` returns``inf`` and
+    ``x=-1`` returns ``-inf``.
+
+    Parameters
+    ----------
+    x : array_like
+       The value(s) whose arctanh is (are) required.
+
+    Returns
+    -------
+    out : ndarray or scalar
+       The inverse hyperbolic tangent(s) of the `x` value(s). If `x` was
+       a scalar so is `out`, otherwise an array is returned.
+
+
+    See Also
+    --------
+    numpy.arctanh
+
+    Notes
+    -----
+    For an arctanh() that returns ``NAN`` when real `x` is not in the
+    interval ``(-1,1)``, use `numpy.arctanh` (this latter, however, does
+    return +/-inf for ``x = +/-1``).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.set_printoptions(precision=4)
+
+    >>> np.emath.arctanh(0.5)
+    0.5493061443340549
+
+    >>> import warnings
+    >>> with warnings.catch_warnings():
+    ...     warnings.simplefilter('ignore', RuntimeWarning)
+    ...     np.emath.arctanh(np.eye(2))
+    array([[inf,  0.],
+           [ 0., inf]])
+    >>> np.emath.arctanh([1j])
+    array([0.+0.7854j])
+
+    """
+    x = _fix_real_abs_gt_1(x)
+    return nx.arctanh(x)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..80a1a4108ad5ed1141b19a78993ab8da3cee929b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_scimath_impl.pyi
@@ -0,0 +1,93 @@
+from typing import Any, overload
+
+from numpy import complexfloating
+from numpy._typing import (
+    NDArray,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ComplexLike_co,
+    _FloatLike_co,
+)
+
+__all__ = ["sqrt", "log", "log2", "logn", "log10", "power", "arccos", "arcsin", "arctanh"]
+
+@overload
+def sqrt(x: _FloatLike_co) -> Any: ...
+@overload
+def sqrt(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def sqrt(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def sqrt(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def log(x: _FloatLike_co) -> Any: ...
+@overload
+def log(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def log(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def log(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def log10(x: _FloatLike_co) -> Any: ...
+@overload
+def log10(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def log10(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def log10(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def log2(x: _FloatLike_co) -> Any: ...
+@overload
+def log2(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def log2(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def log2(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def logn(n: _FloatLike_co, x: _FloatLike_co) -> Any: ...
+@overload
+def logn(n: _ComplexLike_co, x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def logn(n: _ArrayLikeFloat_co, x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def logn(n: _ArrayLikeComplex_co, x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def power(x: _FloatLike_co, p: _FloatLike_co) -> Any: ...
+@overload
+def power(x: _ComplexLike_co, p: _ComplexLike_co) -> complexfloating: ...
+@overload
+def power(x: _ArrayLikeFloat_co, p: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def power(x: _ArrayLikeComplex_co, p: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def arccos(x: _FloatLike_co) -> Any: ...
+@overload
+def arccos(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def arccos(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def arccos(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def arcsin(x: _FloatLike_co) -> Any: ...
+@overload
+def arcsin(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def arcsin(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def arcsin(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def arctanh(x: _FloatLike_co) -> Any: ...
+@overload
+def arctanh(x: _ComplexLike_co) -> complexfloating: ...
+@overload
+def arctanh(x: _ArrayLikeFloat_co) -> NDArray[Any]: ...
+@overload
+def arctanh(x: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..861a938326006818a5614509bb5e2e01b3eac749
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.py
@@ -0,0 +1,1289 @@
+import functools
+import warnings
+
+import numpy as np
+import numpy._core.numeric as _nx
+from numpy._core import atleast_3d, overrides, vstack
+from numpy._core._multiarray_umath import _array_converter
+from numpy._core.fromnumeric import reshape, transpose
+from numpy._core.multiarray import normalize_axis_index
+from numpy._core.numeric import (
+    array,
+    asanyarray,
+    asarray,
+    normalize_axis_tuple,
+    zeros,
+    zeros_like,
+)
+from numpy._core.overrides import set_module
+from numpy._core.shape_base import _arrays_for_stack_dispatcher
+from numpy.lib._index_tricks_impl import ndindex
+from numpy.matrixlib.defmatrix import matrix  # this raises all the right alarm bells
+
+__all__ = [
+    'column_stack', 'row_stack', 'dstack', 'array_split', 'split',
+    'hsplit', 'vsplit', 'dsplit', 'apply_over_axes', 'expand_dims',
+    'apply_along_axis', 'kron', 'tile', 'take_along_axis',
+    'put_along_axis'
+    ]
+
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+def _make_along_axis_idx(arr_shape, indices, axis):
+    # compute dimensions to iterate over
+    if not _nx.issubdtype(indices.dtype, _nx.integer):
+        raise IndexError('`indices` must be an integer array')
+    if len(arr_shape) != indices.ndim:
+        raise ValueError(
+            "`indices` and `arr` must have the same number of dimensions")
+    shape_ones = (1,) * indices.ndim
+    dest_dims = list(range(axis)) + [None] + list(range(axis + 1, indices.ndim))
+
+    # build a fancy index, consisting of orthogonal aranges, with the
+    # requested index inserted at the right location
+    fancy_index = []
+    for dim, n in zip(dest_dims, arr_shape):
+        if dim is None:
+            fancy_index.append(indices)
+        else:
+            ind_shape = shape_ones[:dim] + (-1,) + shape_ones[dim + 1:]
+            fancy_index.append(_nx.arange(n).reshape(ind_shape))
+
+    return tuple(fancy_index)
+
+
+def _take_along_axis_dispatcher(arr, indices, axis=None):
+    return (arr, indices)
+
+
+@array_function_dispatch(_take_along_axis_dispatcher)
+def take_along_axis(arr, indices, axis=-1):
+    """
+    Take values from the input array by matching 1d index and data slices.
+
+    This iterates over matching 1d slices oriented along the specified axis in
+    the index and data arrays, and uses the former to look up values in the
+    latter. These slices can be different lengths.
+
+    Functions returning an index along an axis, like `argsort` and
+    `argpartition`, produce suitable indices for this function.
+
+    Parameters
+    ----------
+    arr : ndarray (Ni..., M, Nk...)
+        Source array
+    indices : ndarray (Ni..., J, Nk...)
+        Indices to take along each 1d slice of ``arr``. This must match the
+        dimension of ``arr``, but dimensions Ni and Nj only need to broadcast
+        against ``arr``.
+    axis : int or None, optional
+        The axis to take 1d slices along. If axis is None, the input array is
+        treated as if it had first been flattened to 1d, for consistency with
+        `sort` and `argsort`.
+
+        .. versionchanged:: 2.3
+            The default value is now ``-1``.
+
+    Returns
+    -------
+    out: ndarray (Ni..., J, Nk...)
+        The indexed result.
+
+    Notes
+    -----
+    This is equivalent to (but faster than) the following use of `ndindex` and
+    `s_`, which sets each of ``ii`` and ``kk`` to a tuple of indices::
+
+        Ni, M, Nk = a.shape[:axis], a.shape[axis], a.shape[axis+1:]
+        J = indices.shape[axis]  # Need not equal M
+        out = np.empty(Ni + (J,) + Nk)
+
+        for ii in ndindex(Ni):
+            for kk in ndindex(Nk):
+                a_1d       = a      [ii + s_[:,] + kk]
+                indices_1d = indices[ii + s_[:,] + kk]
+                out_1d     = out    [ii + s_[:,] + kk]
+                for j in range(J):
+                    out_1d[j] = a_1d[indices_1d[j]]
+
+    Equivalently, eliminating the inner loop, the last two lines would be::
+
+                out_1d[:] = a_1d[indices_1d]
+
+    See Also
+    --------
+    take : Take along an axis, using the same indices for every 1d slice
+    put_along_axis :
+        Put values into the destination array by matching 1d index and data slices
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    For this sample array
+
+    >>> a = np.array([[10, 30, 20], [60, 40, 50]])
+
+    We can sort either by using sort directly, or argsort and this function
+
+    >>> np.sort(a, axis=1)
+    array([[10, 20, 30],
+           [40, 50, 60]])
+    >>> ai = np.argsort(a, axis=1)
+    >>> ai
+    array([[0, 2, 1],
+           [1, 2, 0]])
+    >>> np.take_along_axis(a, ai, axis=1)
+    array([[10, 20, 30],
+           [40, 50, 60]])
+
+    The same works for max and min, if you maintain the trivial dimension
+    with ``keepdims``:
+
+    >>> np.max(a, axis=1, keepdims=True)
+    array([[30],
+           [60]])
+    >>> ai = np.argmax(a, axis=1, keepdims=True)
+    >>> ai
+    array([[1],
+           [0]])
+    >>> np.take_along_axis(a, ai, axis=1)
+    array([[30],
+           [60]])
+
+    If we want to get the max and min at the same time, we can stack the
+    indices first
+
+    >>> ai_min = np.argmin(a, axis=1, keepdims=True)
+    >>> ai_max = np.argmax(a, axis=1, keepdims=True)
+    >>> ai = np.concatenate([ai_min, ai_max], axis=1)
+    >>> ai
+    array([[0, 1],
+           [1, 0]])
+    >>> np.take_along_axis(a, ai, axis=1)
+    array([[10, 30],
+           [40, 60]])
+    """
+    # normalize inputs
+    if axis is None:
+        if indices.ndim != 1:
+            raise ValueError(
+                'when axis=None, `indices` must have a single dimension.')
+        arr = np.array(arr.flat)
+        axis = 0
+    else:
+        axis = normalize_axis_index(axis, arr.ndim)
+
+    # use the fancy index
+    return arr[_make_along_axis_idx(arr.shape, indices, axis)]
+
+
+def _put_along_axis_dispatcher(arr, indices, values, axis):
+    return (arr, indices, values)
+
+
+@array_function_dispatch(_put_along_axis_dispatcher)
+def put_along_axis(arr, indices, values, axis):
+    """
+    Put values into the destination array by matching 1d index and data slices.
+
+    This iterates over matching 1d slices oriented along the specified axis in
+    the index and data arrays, and uses the former to place values into the
+    latter. These slices can be different lengths.
+
+    Functions returning an index along an axis, like `argsort` and
+    `argpartition`, produce suitable indices for this function.
+
+    Parameters
+    ----------
+    arr : ndarray (Ni..., M, Nk...)
+        Destination array.
+    indices : ndarray (Ni..., J, Nk...)
+        Indices to change along each 1d slice of `arr`. This must match the
+        dimension of arr, but dimensions in Ni and Nj may be 1 to broadcast
+        against `arr`.
+    values : array_like (Ni..., J, Nk...)
+        values to insert at those indices. Its shape and dimension are
+        broadcast to match that of `indices`.
+    axis : int
+        The axis to take 1d slices along. If axis is None, the destination
+        array is treated as if a flattened 1d view had been created of it.
+
+    Notes
+    -----
+    This is equivalent to (but faster than) the following use of `ndindex` and
+    `s_`, which sets each of ``ii`` and ``kk`` to a tuple of indices::
+
+        Ni, M, Nk = a.shape[:axis], a.shape[axis], a.shape[axis+1:]
+        J = indices.shape[axis]  # Need not equal M
+
+        for ii in ndindex(Ni):
+            for kk in ndindex(Nk):
+                a_1d       = a      [ii + s_[:,] + kk]
+                indices_1d = indices[ii + s_[:,] + kk]
+                values_1d  = values [ii + s_[:,] + kk]
+                for j in range(J):
+                    a_1d[indices_1d[j]] = values_1d[j]
+
+    Equivalently, eliminating the inner loop, the last two lines would be::
+
+                a_1d[indices_1d] = values_1d
+
+    See Also
+    --------
+    take_along_axis :
+        Take values from the input array by matching 1d index and data slices
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    For this sample array
+
+    >>> a = np.array([[10, 30, 20], [60, 40, 50]])
+
+    We can replace the maximum values with:
+
+    >>> ai = np.argmax(a, axis=1, keepdims=True)
+    >>> ai
+    array([[1],
+           [0]])
+    >>> np.put_along_axis(a, ai, 99, axis=1)
+    >>> a
+    array([[10, 99, 20],
+           [99, 40, 50]])
+
+    """
+    # normalize inputs
+    if axis is None:
+        if indices.ndim != 1:
+            raise ValueError(
+                'when axis=None, `indices` must have a single dimension.')
+        arr = np.array(arr.flat)
+        axis = 0
+    else:
+        axis = normalize_axis_index(axis, arr.ndim)
+
+    # use the fancy index
+    arr[_make_along_axis_idx(arr.shape, indices, axis)] = values
+
+
+def _apply_along_axis_dispatcher(func1d, axis, arr, *args, **kwargs):
+    return (arr,)
+
+
+@array_function_dispatch(_apply_along_axis_dispatcher)
+def apply_along_axis(func1d, axis, arr, *args, **kwargs):
+    """
+    Apply a function to 1-D slices along the given axis.
+
+    Execute `func1d(a, *args, **kwargs)` where `func1d` operates on 1-D arrays
+    and `a` is a 1-D slice of `arr` along `axis`.
+
+    This is equivalent to (but faster than) the following use of `ndindex` and
+    `s_`, which sets each of ``ii``, ``jj``, and ``kk`` to a tuple of indices::
+
+        Ni, Nk = a.shape[:axis], a.shape[axis+1:]
+        for ii in ndindex(Ni):
+            for kk in ndindex(Nk):
+                f = func1d(arr[ii + s_[:,] + kk])
+                Nj = f.shape
+                for jj in ndindex(Nj):
+                    out[ii + jj + kk] = f[jj]
+
+    Equivalently, eliminating the inner loop, this can be expressed as::
+
+        Ni, Nk = a.shape[:axis], a.shape[axis+1:]
+        for ii in ndindex(Ni):
+            for kk in ndindex(Nk):
+                out[ii + s_[...,] + kk] = func1d(arr[ii + s_[:,] + kk])
+
+    Parameters
+    ----------
+    func1d : function (M,) -> (Nj...)
+        This function should accept 1-D arrays. It is applied to 1-D
+        slices of `arr` along the specified axis.
+    axis : integer
+        Axis along which `arr` is sliced.
+    arr : ndarray (Ni..., M, Nk...)
+        Input array.
+    args : any
+        Additional arguments to `func1d`.
+    kwargs : any
+        Additional named arguments to `func1d`.
+
+    Returns
+    -------
+    out : ndarray  (Ni..., Nj..., Nk...)
+        The output array. The shape of `out` is identical to the shape of
+        `arr`, except along the `axis` dimension. This axis is removed, and
+        replaced with new dimensions equal to the shape of the return value
+        of `func1d`. So if `func1d` returns a scalar `out` will have one
+        fewer dimensions than `arr`.
+
+    See Also
+    --------
+    apply_over_axes : Apply a function repeatedly over multiple axes.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> def my_func(a):
+    ...     \"\"\"Average first and last element of a 1-D array\"\"\"
+    ...     return (a[0] + a[-1]) * 0.5
+    >>> b = np.array([[1,2,3], [4,5,6], [7,8,9]])
+    >>> np.apply_along_axis(my_func, 0, b)
+    array([4., 5., 6.])
+    >>> np.apply_along_axis(my_func, 1, b)
+    array([2.,  5.,  8.])
+
+    For a function that returns a 1D array, the number of dimensions in
+    `outarr` is the same as `arr`.
+
+    >>> b = np.array([[8,1,7], [4,3,9], [5,2,6]])
+    >>> np.apply_along_axis(sorted, 1, b)
+    array([[1, 7, 8],
+           [3, 4, 9],
+           [2, 5, 6]])
+
+    For a function that returns a higher dimensional array, those dimensions
+    are inserted in place of the `axis` dimension.
+
+    >>> b = np.array([[1,2,3], [4,5,6], [7,8,9]])
+    >>> np.apply_along_axis(np.diag, -1, b)
+    array([[[1, 0, 0],
+            [0, 2, 0],
+            [0, 0, 3]],
+           [[4, 0, 0],
+            [0, 5, 0],
+            [0, 0, 6]],
+           [[7, 0, 0],
+            [0, 8, 0],
+            [0, 0, 9]]])
+    """
+    # handle negative axes
+    conv = _array_converter(arr)
+    arr = conv[0]
+
+    nd = arr.ndim
+    axis = normalize_axis_index(axis, nd)
+
+    # arr, with the iteration axis at the end
+    in_dims = list(range(nd))
+    inarr_view = transpose(arr, in_dims[:axis] + in_dims[axis + 1:] + [axis])
+
+    # compute indices for the iteration axes, and append a trailing ellipsis to
+    # prevent 0d arrays decaying to scalars, which fixes gh-8642
+    inds = ndindex(inarr_view.shape[:-1])
+    inds = (ind + (Ellipsis,) for ind in inds)
+
+    # invoke the function on the first item
+    try:
+        ind0 = next(inds)
+    except StopIteration:
+        raise ValueError(
+            'Cannot apply_along_axis when any iteration dimensions are 0'
+        ) from None
+    res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs))
+
+    # build a buffer for storing evaluations of func1d.
+    # remove the requested axis, and add the new ones on the end.
+    # laid out so that each write is contiguous.
+    # for a tuple index inds, buff[inds] = func1d(inarr_view[inds])
+    if not isinstance(res, matrix):
+        buff = zeros_like(res, shape=inarr_view.shape[:-1] + res.shape)
+    else:
+        # Matrices are nasty with reshaping, so do not preserve them here.
+        buff = zeros(inarr_view.shape[:-1] + res.shape, dtype=res.dtype)
+
+    # permutation of axes such that out = buff.transpose(buff_permute)
+    buff_dims = list(range(buff.ndim))
+    buff_permute = (
+        buff_dims[0 : axis] +
+        buff_dims[buff.ndim - res.ndim : buff.ndim] +
+        buff_dims[axis : buff.ndim - res.ndim]
+    )
+
+    # save the first result, then compute and save all remaining results
+    buff[ind0] = res
+    for ind in inds:
+        buff[ind] = asanyarray(func1d(inarr_view[ind], *args, **kwargs))
+
+    res = transpose(buff, buff_permute)
+    return conv.wrap(res)
+
+
+def _apply_over_axes_dispatcher(func, a, axes):
+    return (a,)
+
+
+@array_function_dispatch(_apply_over_axes_dispatcher)
+def apply_over_axes(func, a, axes):
+    """
+    Apply a function repeatedly over multiple axes.
+
+    `func` is called as `res = func(a, axis)`, where `axis` is the first
+    element of `axes`.  The result `res` of the function call must have
+    either the same dimensions as `a` or one less dimension.  If `res`
+    has one less dimension than `a`, a dimension is inserted before
+    `axis`.  The call to `func` is then repeated for each axis in `axes`,
+    with `res` as the first argument.
+
+    Parameters
+    ----------
+    func : function
+        This function must take two arguments, `func(a, axis)`.
+    a : array_like
+        Input array.
+    axes : array_like
+        Axes over which `func` is applied; the elements must be integers.
+
+    Returns
+    -------
+    apply_over_axis : ndarray
+        The output array.  The number of dimensions is the same as `a`,
+        but the shape can be different.  This depends on whether `func`
+        changes the shape of its output with respect to its input.
+
+    See Also
+    --------
+    apply_along_axis :
+        Apply a function to 1-D slices of an array along the given axis.
+
+    Notes
+    -----
+    This function is equivalent to tuple axis arguments to reorderable ufuncs
+    with keepdims=True. Tuple axis arguments to ufuncs have been available since
+    version 1.7.0.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(24).reshape(2,3,4)
+    >>> a
+    array([[[ 0,  1,  2,  3],
+            [ 4,  5,  6,  7],
+            [ 8,  9, 10, 11]],
+           [[12, 13, 14, 15],
+            [16, 17, 18, 19],
+            [20, 21, 22, 23]]])
+
+    Sum over axes 0 and 2. The result has same number of dimensions
+    as the original array:
+
+    >>> np.apply_over_axes(np.sum, a, [0,2])
+    array([[[ 60],
+            [ 92],
+            [124]]])
+
+    Tuple axis arguments to ufuncs are equivalent:
+
+    >>> np.sum(a, axis=(0,2), keepdims=True)
+    array([[[ 60],
+            [ 92],
+            [124]]])
+
+    """
+    val = asarray(a)
+    N = a.ndim
+    if array(axes).ndim == 0:
+        axes = (axes,)
+    for axis in axes:
+        if axis < 0:
+            axis = N + axis
+        args = (val, axis)
+        res = func(*args)
+        if res.ndim == val.ndim:
+            val = res
+        else:
+            res = expand_dims(res, axis)
+            if res.ndim == val.ndim:
+                val = res
+            else:
+                raise ValueError("function is not returning "
+                                 "an array of the correct shape")
+    return val
+
+
+def _expand_dims_dispatcher(a, axis):
+    return (a,)
+
+
+@array_function_dispatch(_expand_dims_dispatcher)
+def expand_dims(a, axis):
+    """
+    Expand the shape of an array.
+
+    Insert a new axis that will appear at the `axis` position in the expanded
+    array shape.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    axis : int or tuple of ints
+        Position in the expanded axes where the new axis (or axes) is placed.
+
+        .. deprecated:: 1.13.0
+            Passing an axis where ``axis > a.ndim`` will be treated as
+            ``axis == a.ndim``, and passing ``axis < -a.ndim - 1`` will
+            be treated as ``axis == 0``. This behavior is deprecated.
+
+    Returns
+    -------
+    result : ndarray
+        View of `a` with the number of dimensions increased.
+
+    See Also
+    --------
+    squeeze : The inverse operation, removing singleton dimensions
+    reshape : Insert, remove, and combine dimensions, and resize existing ones
+    atleast_1d, atleast_2d, atleast_3d
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([1, 2])
+    >>> x.shape
+    (2,)
+
+    The following is equivalent to ``x[np.newaxis, :]`` or ``x[np.newaxis]``:
+
+    >>> y = np.expand_dims(x, axis=0)
+    >>> y
+    array([[1, 2]])
+    >>> y.shape
+    (1, 2)
+
+    The following is equivalent to ``x[:, np.newaxis]``:
+
+    >>> y = np.expand_dims(x, axis=1)
+    >>> y
+    array([[1],
+           [2]])
+    >>> y.shape
+    (2, 1)
+
+    ``axis`` may also be a tuple:
+
+    >>> y = np.expand_dims(x, axis=(0, 1))
+    >>> y
+    array([[[1, 2]]])
+
+    >>> y = np.expand_dims(x, axis=(2, 0))
+    >>> y
+    array([[[1],
+            [2]]])
+
+    Note that some examples may use ``None`` instead of ``np.newaxis``.  These
+    are the same objects:
+
+    >>> np.newaxis is None
+    True
+
+    """
+    if isinstance(a, matrix):
+        a = asarray(a)
+    else:
+        a = asanyarray(a)
+
+    if not isinstance(axis, (tuple, list)):
+        axis = (axis,)
+
+    out_ndim = len(axis) + a.ndim
+    axis = normalize_axis_tuple(axis, out_ndim)
+
+    shape_it = iter(a.shape)
+    shape = [1 if ax in axis else next(shape_it) for ax in range(out_ndim)]
+
+    return a.reshape(shape)
+
+
+# NOTE: Remove once deprecation period passes
+@set_module("numpy")
+def row_stack(tup, *, dtype=None, casting="same_kind"):
+    # Deprecated in NumPy 2.0, 2023-08-18
+    warnings.warn(
+        "`row_stack` alias is deprecated. "
+        "Use `np.vstack` directly.",
+        DeprecationWarning,
+        stacklevel=2
+    )
+    return vstack(tup, dtype=dtype, casting=casting)
+
+
+row_stack.__doc__ = vstack.__doc__
+
+
+def _column_stack_dispatcher(tup):
+    return _arrays_for_stack_dispatcher(tup)
+
+
+@array_function_dispatch(_column_stack_dispatcher)
+def column_stack(tup):
+    """
+    Stack 1-D arrays as columns into a 2-D array.
+
+    Take a sequence of 1-D arrays and stack them as columns
+    to make a single 2-D array. 2-D arrays are stacked as-is,
+    just like with `hstack`.  1-D arrays are turned into 2-D columns
+    first.
+
+    Parameters
+    ----------
+    tup : sequence of 1-D or 2-D arrays.
+        Arrays to stack. All of them must have the same first dimension.
+
+    Returns
+    -------
+    stacked : 2-D array
+        The array formed by stacking the given arrays.
+
+    See Also
+    --------
+    stack, hstack, vstack, concatenate
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array((1,2,3))
+    >>> b = np.array((4,5,6))
+    >>> np.column_stack((a,b))
+    array([[1, 4],
+           [2, 5],
+           [3, 6]])
+
+    """
+    arrays = []
+    for v in tup:
+        arr = asanyarray(v)
+        if arr.ndim < 2:
+            arr = array(arr, copy=None, subok=True, ndmin=2).T
+        arrays.append(arr)
+    return _nx.concatenate(arrays, 1)
+
+
+def _dstack_dispatcher(tup):
+    return _arrays_for_stack_dispatcher(tup)
+
+
+@array_function_dispatch(_dstack_dispatcher)
+def dstack(tup):
+    """
+    Stack arrays in sequence depth wise (along third axis).
+
+    This is equivalent to concatenation along the third axis after 2-D arrays
+    of shape `(M,N)` have been reshaped to `(M,N,1)` and 1-D arrays of shape
+    `(N,)` have been reshaped to `(1,N,1)`. Rebuilds arrays divided by
+    `dsplit`.
+
+    This function makes most sense for arrays with up to 3 dimensions. For
+    instance, for pixel-data with a height (first axis), width (second axis),
+    and r/g/b channels (third axis). The functions `concatenate`, `stack` and
+    `block` provide more general stacking and concatenation operations.
+
+    Parameters
+    ----------
+    tup : sequence of arrays
+        The arrays must have the same shape along all but the third axis.
+        1-D or 2-D arrays must have the same shape.
+
+    Returns
+    -------
+    stacked : ndarray
+        The array formed by stacking the given arrays, will be at least 3-D.
+
+    See Also
+    --------
+    concatenate : Join a sequence of arrays along an existing axis.
+    stack : Join a sequence of arrays along a new axis.
+    block : Assemble an nd-array from nested lists of blocks.
+    vstack : Stack arrays in sequence vertically (row wise).
+    hstack : Stack arrays in sequence horizontally (column wise).
+    column_stack : Stack 1-D arrays as columns into a 2-D array.
+    dsplit : Split array along third axis.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array((1,2,3))
+    >>> b = np.array((4,5,6))
+    >>> np.dstack((a,b))
+    array([[[1, 4],
+            [2, 5],
+            [3, 6]]])
+
+    >>> a = np.array([[1],[2],[3]])
+    >>> b = np.array([[4],[5],[6]])
+    >>> np.dstack((a,b))
+    array([[[1, 4]],
+           [[2, 5]],
+           [[3, 6]]])
+
+    """
+    arrs = atleast_3d(*tup)
+    if not isinstance(arrs, tuple):
+        arrs = (arrs,)
+    return _nx.concatenate(arrs, 2)
+
+
+def _array_split_dispatcher(ary, indices_or_sections, axis=None):
+    return (ary, indices_or_sections)
+
+
+@array_function_dispatch(_array_split_dispatcher)
+def array_split(ary, indices_or_sections, axis=0):
+    """
+    Split an array into multiple sub-arrays.
+
+    Please refer to the ``split`` documentation.  The only difference
+    between these functions is that ``array_split`` allows
+    `indices_or_sections` to be an integer that does *not* equally
+    divide the axis. For an array of length l that should be split
+    into n sections, it returns l % n sub-arrays of size l//n + 1
+    and the rest of size l//n.
+
+    See Also
+    --------
+    split : Split array into multiple sub-arrays of equal size.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(8.0)
+    >>> np.array_split(x, 3)
+    [array([0.,  1.,  2.]), array([3.,  4.,  5.]), array([6.,  7.])]
+
+    >>> x = np.arange(9)
+    >>> np.array_split(x, 4)
+    [array([0, 1, 2]), array([3, 4]), array([5, 6]), array([7, 8])]
+
+    """
+    try:
+        Ntotal = ary.shape[axis]
+    except AttributeError:
+        Ntotal = len(ary)
+    try:
+        # handle array case.
+        Nsections = len(indices_or_sections) + 1
+        div_points = [0] + list(indices_or_sections) + [Ntotal]
+    except TypeError:
+        # indices_or_sections is a scalar, not an array.
+        Nsections = int(indices_or_sections)
+        if Nsections <= 0:
+            raise ValueError('number sections must be larger than 0.') from None
+        Neach_section, extras = divmod(Ntotal, Nsections)
+        section_sizes = ([0] +
+                         extras * [Neach_section + 1] +
+                         (Nsections - extras) * [Neach_section])
+        div_points = _nx.array(section_sizes, dtype=_nx.intp).cumsum()
+
+    sub_arys = []
+    sary = _nx.swapaxes(ary, axis, 0)
+    for i in range(Nsections):
+        st = div_points[i]
+        end = div_points[i + 1]
+        sub_arys.append(_nx.swapaxes(sary[st:end], axis, 0))
+
+    return sub_arys
+
+
+def _split_dispatcher(ary, indices_or_sections, axis=None):
+    return (ary, indices_or_sections)
+
+
+@array_function_dispatch(_split_dispatcher)
+def split(ary, indices_or_sections, axis=0):
+    """
+    Split an array into multiple sub-arrays as views into `ary`.
+
+    Parameters
+    ----------
+    ary : ndarray
+        Array to be divided into sub-arrays.
+    indices_or_sections : int or 1-D array
+        If `indices_or_sections` is an integer, N, the array will be divided
+        into N equal arrays along `axis`.  If such a split is not possible,
+        an error is raised.
+
+        If `indices_or_sections` is a 1-D array of sorted integers, the entries
+        indicate where along `axis` the array is split.  For example,
+        ``[2, 3]`` would, for ``axis=0``, result in
+
+        - ary[:2]
+        - ary[2:3]
+        - ary[3:]
+
+        If an index exceeds the dimension of the array along `axis`,
+        an empty sub-array is returned correspondingly.
+    axis : int, optional
+        The axis along which to split, default is 0.
+
+    Returns
+    -------
+    sub-arrays : list of ndarrays
+        A list of sub-arrays as views into `ary`.
+
+    Raises
+    ------
+    ValueError
+        If `indices_or_sections` is given as an integer, but
+        a split does not result in equal division.
+
+    See Also
+    --------
+    array_split : Split an array into multiple sub-arrays of equal or
+                  near-equal size.  Does not raise an exception if
+                  an equal division cannot be made.
+    hsplit : Split array into multiple sub-arrays horizontally (column-wise).
+    vsplit : Split array into multiple sub-arrays vertically (row wise).
+    dsplit : Split array into multiple sub-arrays along the 3rd axis (depth).
+    concatenate : Join a sequence of arrays along an existing axis.
+    stack : Join a sequence of arrays along a new axis.
+    hstack : Stack arrays in sequence horizontally (column wise).
+    vstack : Stack arrays in sequence vertically (row wise).
+    dstack : Stack arrays in sequence depth wise (along third dimension).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(9.0)
+    >>> np.split(x, 3)
+    [array([0.,  1.,  2.]), array([3.,  4.,  5.]), array([6.,  7.,  8.])]
+
+    >>> x = np.arange(8.0)
+    >>> np.split(x, [3, 5, 6, 10])
+    [array([0.,  1.,  2.]),
+     array([3.,  4.]),
+     array([5.]),
+     array([6.,  7.]),
+     array([], dtype=float64)]
+
+    """
+    try:
+        len(indices_or_sections)
+    except TypeError:
+        sections = indices_or_sections
+        N = ary.shape[axis]
+        if N % sections:
+            raise ValueError(
+                'array split does not result in an equal division') from None
+    return array_split(ary, indices_or_sections, axis)
+
+
+def _hvdsplit_dispatcher(ary, indices_or_sections):
+    return (ary, indices_or_sections)
+
+
+@array_function_dispatch(_hvdsplit_dispatcher)
+def hsplit(ary, indices_or_sections):
+    """
+    Split an array into multiple sub-arrays horizontally (column-wise).
+
+    Please refer to the `split` documentation.  `hsplit` is equivalent
+    to `split` with ``axis=1``, the array is always split along the second
+    axis except for 1-D arrays, where it is split at ``axis=0``.
+
+    See Also
+    --------
+    split : Split an array into multiple sub-arrays of equal size.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(16.0).reshape(4, 4)
+    >>> x
+    array([[ 0.,   1.,   2.,   3.],
+           [ 4.,   5.,   6.,   7.],
+           [ 8.,   9.,  10.,  11.],
+           [12.,  13.,  14.,  15.]])
+    >>> np.hsplit(x, 2)
+    [array([[  0.,   1.],
+           [  4.,   5.],
+           [  8.,   9.],
+           [12.,  13.]]),
+     array([[  2.,   3.],
+           [  6.,   7.],
+           [10.,  11.],
+           [14.,  15.]])]
+    >>> np.hsplit(x, np.array([3, 6]))
+    [array([[ 0.,   1.,   2.],
+           [ 4.,   5.,   6.],
+           [ 8.,   9.,  10.],
+           [12.,  13.,  14.]]),
+     array([[ 3.],
+           [ 7.],
+           [11.],
+           [15.]]),
+     array([], shape=(4, 0), dtype=float64)]
+
+    With a higher dimensional array the split is still along the second axis.
+
+    >>> x = np.arange(8.0).reshape(2, 2, 2)
+    >>> x
+    array([[[0.,  1.],
+            [2.,  3.]],
+           [[4.,  5.],
+            [6.,  7.]]])
+    >>> np.hsplit(x, 2)
+    [array([[[0.,  1.]],
+           [[4.,  5.]]]),
+     array([[[2.,  3.]],
+           [[6.,  7.]]])]
+
+    With a 1-D array, the split is along axis 0.
+
+    >>> x = np.array([0, 1, 2, 3, 4, 5])
+    >>> np.hsplit(x, 2)
+    [array([0, 1, 2]), array([3, 4, 5])]
+
+    """
+    if _nx.ndim(ary) == 0:
+        raise ValueError('hsplit only works on arrays of 1 or more dimensions')
+    if ary.ndim > 1:
+        return split(ary, indices_or_sections, 1)
+    else:
+        return split(ary, indices_or_sections, 0)
+
+
+@array_function_dispatch(_hvdsplit_dispatcher)
+def vsplit(ary, indices_or_sections):
+    """
+    Split an array into multiple sub-arrays vertically (row-wise).
+
+    Please refer to the ``split`` documentation.  ``vsplit`` is equivalent
+    to ``split`` with `axis=0` (default), the array is always split along the
+    first axis regardless of the array dimension.
+
+    See Also
+    --------
+    split : Split an array into multiple sub-arrays of equal size.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(16.0).reshape(4, 4)
+    >>> x
+    array([[ 0.,   1.,   2.,   3.],
+           [ 4.,   5.,   6.,   7.],
+           [ 8.,   9.,  10.,  11.],
+           [12.,  13.,  14.,  15.]])
+    >>> np.vsplit(x, 2)
+    [array([[0., 1., 2., 3.],
+            [4., 5., 6., 7.]]),
+     array([[ 8.,  9., 10., 11.],
+            [12., 13., 14., 15.]])]
+    >>> np.vsplit(x, np.array([3, 6]))
+    [array([[ 0.,  1.,  2.,  3.],
+            [ 4.,  5.,  6.,  7.],
+            [ 8.,  9., 10., 11.]]),
+     array([[12., 13., 14., 15.]]),
+     array([], shape=(0, 4), dtype=float64)]
+
+    With a higher dimensional array the split is still along the first axis.
+
+    >>> x = np.arange(8.0).reshape(2, 2, 2)
+    >>> x
+    array([[[0.,  1.],
+            [2.,  3.]],
+           [[4.,  5.],
+            [6.,  7.]]])
+    >>> np.vsplit(x, 2)
+    [array([[[0., 1.],
+             [2., 3.]]]),
+     array([[[4., 5.],
+             [6., 7.]]])]
+
+    """
+    if _nx.ndim(ary) < 2:
+        raise ValueError('vsplit only works on arrays of 2 or more dimensions')
+    return split(ary, indices_or_sections, 0)
+
+
+@array_function_dispatch(_hvdsplit_dispatcher)
+def dsplit(ary, indices_or_sections):
+    """
+    Split array into multiple sub-arrays along the 3rd axis (depth).
+
+    Please refer to the `split` documentation.  `dsplit` is equivalent
+    to `split` with ``axis=2``, the array is always split along the third
+    axis provided the array dimension is greater than or equal to 3.
+
+    See Also
+    --------
+    split : Split an array into multiple sub-arrays of equal size.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(16.0).reshape(2, 2, 4)
+    >>> x
+    array([[[ 0.,   1.,   2.,   3.],
+            [ 4.,   5.,   6.,   7.]],
+           [[ 8.,   9.,  10.,  11.],
+            [12.,  13.,  14.,  15.]]])
+    >>> np.dsplit(x, 2)
+    [array([[[ 0.,  1.],
+            [ 4.,  5.]],
+           [[ 8.,  9.],
+            [12., 13.]]]), array([[[ 2.,  3.],
+            [ 6.,  7.]],
+           [[10., 11.],
+            [14., 15.]]])]
+    >>> np.dsplit(x, np.array([3, 6]))
+    [array([[[ 0.,   1.,   2.],
+            [ 4.,   5.,   6.]],
+           [[ 8.,   9.,  10.],
+            [12.,  13.,  14.]]]),
+     array([[[ 3.],
+            [ 7.]],
+           [[11.],
+            [15.]]]),
+    array([], shape=(2, 2, 0), dtype=float64)]
+    """
+    if _nx.ndim(ary) < 3:
+        raise ValueError('dsplit only works on arrays of 3 or more dimensions')
+    return split(ary, indices_or_sections, 2)
+
+
+def get_array_wrap(*args):
+    """Find the wrapper for the array with the highest priority.
+
+    In case of ties, leftmost wins. If no wrapper is found, return None.
+
+    .. deprecated:: 2.0
+    """
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`get_array_wrap` is deprecated. "
+        "(deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    wrappers = sorted((getattr(x, '__array_priority__', 0), -i,
+                 x.__array_wrap__) for i, x in enumerate(args)
+                                   if hasattr(x, '__array_wrap__'))
+    if wrappers:
+        return wrappers[-1][-1]
+    return None
+
+
+def _kron_dispatcher(a, b):
+    return (a, b)
+
+
+@array_function_dispatch(_kron_dispatcher)
+def kron(a, b):
+    """
+    Kronecker product of two arrays.
+
+    Computes the Kronecker product, a composite array made of blocks of the
+    second array scaled by the first.
+
+    Parameters
+    ----------
+    a, b : array_like
+
+    Returns
+    -------
+    out : ndarray
+
+    See Also
+    --------
+    outer : The outer product
+
+    Notes
+    -----
+    The function assumes that the number of dimensions of `a` and `b`
+    are the same, if necessary prepending the smallest with ones.
+    If ``a.shape = (r0,r1,...,rN)`` and ``b.shape = (s0,s1,...,sN)``,
+    the Kronecker product has shape ``(r0*s0, r1*s1, ..., rN*SN)``.
+    The elements are products of elements from `a` and `b`, organized
+    explicitly by::
+
+        kron(a,b)[k0,k1,...,kN] = a[i0,i1,...,iN] * b[j0,j1,...,jN]
+
+    where::
+
+        kt = it * st + jt,  t = 0,...,N
+
+    In the common 2-D case (N=1), the block structure can be visualized::
+
+        [[ a[0,0]*b,   a[0,1]*b,  ... , a[0,-1]*b  ],
+         [  ...                              ...   ],
+         [ a[-1,0]*b,  a[-1,1]*b, ... , a[-1,-1]*b ]]
+
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.kron([1,10,100], [5,6,7])
+    array([  5,   6,   7, ..., 500, 600, 700])
+    >>> np.kron([5,6,7], [1,10,100])
+    array([  5,  50, 500, ...,   7,  70, 700])
+
+    >>> np.kron(np.eye(2), np.ones((2,2)))
+    array([[1.,  1.,  0.,  0.],
+           [1.,  1.,  0.,  0.],
+           [0.,  0.,  1.,  1.],
+           [0.,  0.,  1.,  1.]])
+
+    >>> a = np.arange(100).reshape((2,5,2,5))
+    >>> b = np.arange(24).reshape((2,3,4))
+    >>> c = np.kron(a,b)
+    >>> c.shape
+    (2, 10, 6, 20)
+    >>> I = (1,3,0,2)
+    >>> J = (0,2,1)
+    >>> J1 = (0,) + J             # extend to ndim=4
+    >>> S1 = (1,) + b.shape
+    >>> K = tuple(np.array(I) * np.array(S1) + np.array(J1))
+    >>> c[K] == a[I]*b[J]
+    True
+
+    """
+    # Working:
+    # 1. Equalise the shapes by prepending smaller array with 1s
+    # 2. Expand shapes of both the arrays by adding new axes at
+    #    odd positions for 1st array and even positions for 2nd
+    # 3. Compute the product of the modified array
+    # 4. The inner most array elements now contain the rows of
+    #    the Kronecker product
+    # 5. Reshape the result to kron's shape, which is same as
+    #    product of shapes of the two arrays.
+    b = asanyarray(b)
+    a = array(a, copy=None, subok=True, ndmin=b.ndim)
+    is_any_mat = isinstance(a, matrix) or isinstance(b, matrix)
+    ndb, nda = b.ndim, a.ndim
+    nd = max(ndb, nda)
+
+    if (nda == 0 or ndb == 0):
+        return _nx.multiply(a, b)
+
+    as_ = a.shape
+    bs = b.shape
+    if not a.flags.contiguous:
+        a = reshape(a, as_)
+    if not b.flags.contiguous:
+        b = reshape(b, bs)
+
+    # Equalise the shapes by prepending smaller one with 1s
+    as_ = (1,) * max(0, ndb - nda) + as_
+    bs = (1,) * max(0, nda - ndb) + bs
+
+    # Insert empty dimensions
+    a_arr = expand_dims(a, axis=tuple(range(ndb - nda)))
+    b_arr = expand_dims(b, axis=tuple(range(nda - ndb)))
+
+    # Compute the product
+    a_arr = expand_dims(a_arr, axis=tuple(range(1, nd * 2, 2)))
+    b_arr = expand_dims(b_arr, axis=tuple(range(0, nd * 2, 2)))
+    # In case of `mat`, convert result to `array`
+    result = _nx.multiply(a_arr, b_arr, subok=(not is_any_mat))
+
+    # Reshape back
+    result = result.reshape(_nx.multiply(as_, bs))
+
+    return result if not is_any_mat else matrix(result, copy=False)
+
+
+def _tile_dispatcher(A, reps):
+    return (A, reps)
+
+
+@array_function_dispatch(_tile_dispatcher)
+def tile(A, reps):
+    """
+    Construct an array by repeating A the number of times given by reps.
+
+    If `reps` has length ``d``, the result will have dimension of
+    ``max(d, A.ndim)``.
+
+    If ``A.ndim < d``, `A` is promoted to be d-dimensional by prepending new
+    axes. So a shape (3,) array is promoted to (1, 3) for 2-D replication,
+    or shape (1, 1, 3) for 3-D replication. If this is not the desired
+    behavior, promote `A` to d-dimensions manually before calling this
+    function.
+
+    If ``A.ndim > d``, `reps` is promoted to `A`.ndim by prepending 1's to it.
+    Thus for an `A` of shape (2, 3, 4, 5), a `reps` of (2, 2) is treated as
+    (1, 1, 2, 2).
+
+    Note : Although tile may be used for broadcasting, it is strongly
+    recommended to use numpy's broadcasting operations and functions.
+
+    Parameters
+    ----------
+    A : array_like
+        The input array.
+    reps : array_like
+        The number of repetitions of `A` along each axis.
+
+    Returns
+    -------
+    c : ndarray
+        The tiled output array.
+
+    See Also
+    --------
+    repeat : Repeat elements of an array.
+    broadcast_to : Broadcast an array to a new shape
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([0, 1, 2])
+    >>> np.tile(a, 2)
+    array([0, 1, 2, 0, 1, 2])
+    >>> np.tile(a, (2, 2))
+    array([[0, 1, 2, 0, 1, 2],
+           [0, 1, 2, 0, 1, 2]])
+    >>> np.tile(a, (2, 1, 2))
+    array([[[0, 1, 2, 0, 1, 2]],
+           [[0, 1, 2, 0, 1, 2]]])
+
+    >>> b = np.array([[1, 2], [3, 4]])
+    >>> np.tile(b, 2)
+    array([[1, 2, 1, 2],
+           [3, 4, 3, 4]])
+    >>> np.tile(b, (2, 1))
+    array([[1, 2],
+           [3, 4],
+           [1, 2],
+           [3, 4]])
+
+    >>> c = np.array([1,2,3,4])
+    >>> np.tile(c,(4,1))
+    array([[1, 2, 3, 4],
+           [1, 2, 3, 4],
+           [1, 2, 3, 4],
+           [1, 2, 3, 4]])
+    """
+    try:
+        tup = tuple(reps)
+    except TypeError:
+        tup = (reps,)
+    d = len(tup)
+    if all(x == 1 for x in tup) and isinstance(A, _nx.ndarray):
+        # Fixes the problem that the function does not make a copy if A is a
+        # numpy array and the repetitions are 1 in all dimensions
+        return _nx.array(A, copy=True, subok=True, ndmin=d)
+    else:
+        # Note that no copy of zero-sized arrays is made. However since they
+        # have no data there is no risk of an inadvertent overwrite.
+        c = _nx.array(A, copy=None, subok=True, ndmin=d)
+    if (d < c.ndim):
+        tup = (1,) * (c.ndim - d) + tup
+    shape_out = tuple(s * t for s, t in zip(c.shape, tup))
+    n = c.size
+    if n > 0:
+        for dim_in, nrep in zip(c.shape, tup):
+            if nrep != 1:
+                c = c.reshape(-1, n).repeat(nrep, 0)
+            n //= dim_in
+    return c.reshape(shape_out)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..aab222346486be54e8c074943b70eb47322fb779
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_shape_base_impl.pyi
@@ -0,0 +1,236 @@
+from collections.abc import Callable, Sequence
+from typing import (
+    Any,
+    Concatenate,
+    ParamSpec,
+    Protocol,
+    SupportsIndex,
+    TypeVar,
+    overload,
+    type_check_only,
+)
+from typing_extensions import deprecated
+
+import numpy as np
+from numpy import (
+    _CastingKind,
+    complexfloating,
+    floating,
+    generic,
+    integer,
+    object_,
+    signedinteger,
+    ufunc,
+    unsignedinteger,
+)
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ArrayLikeInt_co,
+    _ArrayLikeObject_co,
+    _ArrayLikeUInt_co,
+    _ShapeLike,
+)
+
+__all__ = [
+    "column_stack",
+    "row_stack",
+    "dstack",
+    "array_split",
+    "split",
+    "hsplit",
+    "vsplit",
+    "dsplit",
+    "apply_over_axes",
+    "expand_dims",
+    "apply_along_axis",
+    "kron",
+    "tile",
+    "take_along_axis",
+    "put_along_axis",
+]
+
+_P = ParamSpec("_P")
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+
+# Signature of `__array_wrap__`
+@type_check_only
+class _ArrayWrap(Protocol):
+    def __call__(
+        self,
+        array: NDArray[Any],
+        context: tuple[ufunc, tuple[Any, ...], int] | None = ...,
+        return_scalar: bool = ...,
+        /,
+    ) -> Any: ...
+
+@type_check_only
+class _SupportsArrayWrap(Protocol):
+    @property
+    def __array_wrap__(self) -> _ArrayWrap: ...
+
+###
+
+def take_along_axis(
+    arr: _ScalarT | NDArray[_ScalarT],
+    indices: NDArray[integer],
+    axis: int | None = -1,
+) -> NDArray[_ScalarT]: ...
+
+def put_along_axis(
+    arr: NDArray[_ScalarT],
+    indices: NDArray[integer],
+    values: ArrayLike,
+    axis: int | None,
+) -> None: ...
+
+@overload
+def apply_along_axis(
+    func1d: Callable[Concatenate[NDArray[Any], _P], _ArrayLike[_ScalarT]],
+    axis: SupportsIndex,
+    arr: ArrayLike,
+    *args: _P.args,
+    **kwargs: _P.kwargs,
+) -> NDArray[_ScalarT]: ...
+@overload
+def apply_along_axis(
+    func1d: Callable[Concatenate[NDArray[Any], _P], Any],
+    axis: SupportsIndex,
+    arr: ArrayLike,
+    *args: _P.args,
+    **kwargs: _P.kwargs,
+) -> NDArray[Any]: ...
+
+def apply_over_axes(
+    func: Callable[[NDArray[Any], int], NDArray[_ScalarT]],
+    a: ArrayLike,
+    axes: int | Sequence[int],
+) -> NDArray[_ScalarT]: ...
+
+@overload
+def expand_dims(
+    a: _ArrayLike[_ScalarT],
+    axis: _ShapeLike,
+) -> NDArray[_ScalarT]: ...
+@overload
+def expand_dims(
+    a: ArrayLike,
+    axis: _ShapeLike,
+) -> NDArray[Any]: ...
+
+# Deprecated in NumPy 2.0, 2023-08-18
+@deprecated("`row_stack` alias is deprecated. Use `np.vstack` directly.")
+def row_stack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind",
+) -> NDArray[Any]: ...
+
+# keep in sync with `numpy.ma.extras.column_stack`
+@overload
+def column_stack(tup: Sequence[_ArrayLike[_ScalarT]]) -> NDArray[_ScalarT]: ...
+@overload
+def column_stack(tup: Sequence[ArrayLike]) -> NDArray[Any]: ...
+
+# keep in sync with `numpy.ma.extras.dstack`
+@overload
+def dstack(tup: Sequence[_ArrayLike[_ScalarT]]) -> NDArray[_ScalarT]: ...
+@overload
+def dstack(tup: Sequence[ArrayLike]) -> NDArray[Any]: ...
+
+@overload
+def array_split(
+    ary: _ArrayLike[_ScalarT],
+    indices_or_sections: _ShapeLike,
+    axis: SupportsIndex = 0,
+) -> list[NDArray[_ScalarT]]: ...
+@overload
+def array_split(
+    ary: ArrayLike,
+    indices_or_sections: _ShapeLike,
+    axis: SupportsIndex = 0,
+) -> list[NDArray[Any]]: ...
+
+@overload
+def split(
+    ary: _ArrayLike[_ScalarT],
+    indices_or_sections: _ShapeLike,
+    axis: SupportsIndex = 0,
+) -> list[NDArray[_ScalarT]]: ...
+@overload
+def split(
+    ary: ArrayLike,
+    indices_or_sections: _ShapeLike,
+    axis: SupportsIndex = 0,
+) -> list[NDArray[Any]]: ...
+
+# keep in sync with `numpy.ma.extras.hsplit`
+@overload
+def hsplit(
+    ary: _ArrayLike[_ScalarT],
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[_ScalarT]]: ...
+@overload
+def hsplit(
+    ary: ArrayLike,
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[Any]]: ...
+
+@overload
+def vsplit(
+    ary: _ArrayLike[_ScalarT],
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[_ScalarT]]: ...
+@overload
+def vsplit(
+    ary: ArrayLike,
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[Any]]: ...
+
+@overload
+def dsplit(
+    ary: _ArrayLike[_ScalarT],
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[_ScalarT]]: ...
+@overload
+def dsplit(
+    ary: ArrayLike,
+    indices_or_sections: _ShapeLike,
+) -> list[NDArray[Any]]: ...
+
+@overload
+def get_array_wrap(*args: _SupportsArrayWrap) -> _ArrayWrap: ...
+@overload
+def get_array_wrap(*args: object) -> _ArrayWrap | None: ...
+
+@overload
+def kron(a: _ArrayLikeBool_co, b: _ArrayLikeBool_co) -> NDArray[np.bool]: ...  # type: ignore[misc]
+@overload
+def kron(a: _ArrayLikeUInt_co, b: _ArrayLikeUInt_co) -> NDArray[unsignedinteger]: ...  # type: ignore[misc]
+@overload
+def kron(a: _ArrayLikeInt_co, b: _ArrayLikeInt_co) -> NDArray[signedinteger]: ...  # type: ignore[misc]
+@overload
+def kron(a: _ArrayLikeFloat_co, b: _ArrayLikeFloat_co) -> NDArray[floating]: ...  # type: ignore[misc]
+@overload
+def kron(a: _ArrayLikeComplex_co, b: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+@overload
+def kron(a: _ArrayLikeObject_co, b: Any) -> NDArray[object_]: ...
+@overload
+def kron(a: Any, b: _ArrayLikeObject_co) -> NDArray[object_]: ...
+
+@overload
+def tile(
+    A: _ArrayLike[_ScalarT],
+    reps: int | Sequence[int],
+) -> NDArray[_ScalarT]: ...
+@overload
+def tile(
+    A: ArrayLike,
+    reps: int | Sequence[int],
+) -> NDArray[Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..0545dfa9d1a9dad3b62afba0c542be428ac2141a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.py
@@ -0,0 +1,582 @@
+"""
+Utilities that manipulate strides to achieve desirable effects.
+
+An explanation of strides can be found in the :ref:`arrays.ndarray`.
+
+"""
+import numpy as np
+from numpy._core.numeric import normalize_axis_tuple
+from numpy._core.overrides import array_function_dispatch, set_module
+
+__all__ = ['broadcast_to', 'broadcast_arrays', 'broadcast_shapes']
+
+
+class DummyArray:
+    """Dummy object that just exists to hang __array_interface__ dictionaries
+    and possibly keep alive a reference to a base array.
+    """
+
+    def __init__(self, interface, base=None):
+        self.__array_interface__ = interface
+        self.base = base
+
+
+def _maybe_view_as_subclass(original_array, new_array):
+    if type(original_array) is not type(new_array):
+        # if input was an ndarray subclass and subclasses were OK,
+        # then view the result as that subclass.
+        new_array = new_array.view(type=type(original_array))
+        # Since we have done something akin to a view from original_array, we
+        # should let the subclass finalize (if it has it implemented, i.e., is
+        # not None).
+        if new_array.__array_finalize__:
+            new_array.__array_finalize__(original_array)
+    return new_array
+
+
+@set_module("numpy.lib.stride_tricks")
+def as_strided(x, shape=None, strides=None, subok=False, writeable=True):
+    """
+    Create a view into the array with the given shape and strides.
+
+    .. warning:: This function has to be used with extreme care, see notes.
+
+    Parameters
+    ----------
+    x : ndarray
+        Array to create a new.
+    shape : sequence of int, optional
+        The shape of the new array. Defaults to ``x.shape``.
+    strides : sequence of int, optional
+        The strides of the new array. Defaults to ``x.strides``.
+    subok : bool, optional
+        If True, subclasses are preserved.
+    writeable : bool, optional
+        If set to False, the returned array will always be readonly.
+        Otherwise it will be writable if the original array was. It
+        is advisable to set this to False if possible (see Notes).
+
+    Returns
+    -------
+    view : ndarray
+
+    See also
+    --------
+    broadcast_to : broadcast an array to a given shape.
+    reshape : reshape an array.
+    lib.stride_tricks.sliding_window_view :
+        userfriendly and safe function for a creation of sliding window views.
+
+    Notes
+    -----
+    ``as_strided`` creates a view into the array given the exact strides
+    and shape. This means it manipulates the internal data structure of
+    ndarray and, if done incorrectly, the array elements can point to
+    invalid memory and can corrupt results or crash your program.
+    It is advisable to always use the original ``x.strides`` when
+    calculating new strides to avoid reliance on a contiguous memory
+    layout.
+
+    Furthermore, arrays created with this function often contain self
+    overlapping memory, so that two elements are identical.
+    Vectorized write operations on such arrays will typically be
+    unpredictable. They may even give different results for small, large,
+    or transposed arrays.
+
+    Since writing to these arrays has to be tested and done with great
+    care, you may want to use ``writeable=False`` to avoid accidental write
+    operations.
+
+    For these reasons it is advisable to avoid ``as_strided`` when
+    possible.
+    """
+    # first convert input to array, possibly keeping subclass
+    x = np.array(x, copy=None, subok=subok)
+    interface = dict(x.__array_interface__)
+    if shape is not None:
+        interface['shape'] = tuple(shape)
+    if strides is not None:
+        interface['strides'] = tuple(strides)
+
+    array = np.asarray(DummyArray(interface, base=x))
+    # The route via `__interface__` does not preserve structured
+    # dtypes. Since dtype should remain unchanged, we set it explicitly.
+    array.dtype = x.dtype
+
+    view = _maybe_view_as_subclass(x, array)
+
+    if view.flags.writeable and not writeable:
+        view.flags.writeable = False
+
+    return view
+
+
+def _sliding_window_view_dispatcher(x, window_shape, axis=None, *,
+                                    subok=None, writeable=None):
+    return (x,)
+
+
+@array_function_dispatch(
+    _sliding_window_view_dispatcher, module="numpy.lib.stride_tricks"
+)
+def sliding_window_view(x, window_shape, axis=None, *,
+                        subok=False, writeable=False):
+    """
+    Create a sliding window view into the array with the given window shape.
+
+    Also known as rolling or moving window, the window slides across all
+    dimensions of the array and extracts subsets of the array at all window
+    positions.
+
+    .. versionadded:: 1.20.0
+
+    Parameters
+    ----------
+    x : array_like
+        Array to create the sliding window view from.
+    window_shape : int or tuple of int
+        Size of window over each axis that takes part in the sliding window.
+        If `axis` is not present, must have same length as the number of input
+        array dimensions. Single integers `i` are treated as if they were the
+        tuple `(i,)`.
+    axis : int or tuple of int, optional
+        Axis or axes along which the sliding window is applied.
+        By default, the sliding window is applied to all axes and
+        `window_shape[i]` will refer to axis `i` of `x`.
+        If `axis` is given as a `tuple of int`, `window_shape[i]` will refer to
+        the axis `axis[i]` of `x`.
+        Single integers `i` are treated as if they were the tuple `(i,)`.
+    subok : bool, optional
+        If True, sub-classes will be passed-through, otherwise the returned
+        array will be forced to be a base-class array (default).
+    writeable : bool, optional
+        When true, allow writing to the returned view. The default is false,
+        as this should be used with caution: the returned view contains the
+        same memory location multiple times, so writing to one location will
+        cause others to change.
+
+    Returns
+    -------
+    view : ndarray
+        Sliding window view of the array. The sliding window dimensions are
+        inserted at the end, and the original dimensions are trimmed as
+        required by the size of the sliding window.
+        That is, ``view.shape = x_shape_trimmed + window_shape``, where
+        ``x_shape_trimmed`` is ``x.shape`` with every entry reduced by one less
+        than the corresponding window size.
+
+    See Also
+    --------
+    lib.stride_tricks.as_strided: A lower-level and less safe routine for
+        creating arbitrary views from custom shape and strides.
+    broadcast_to: broadcast an array to a given shape.
+
+    Notes
+    -----
+    .. warning::
+
+       This function creates views with overlapping memory. When
+       ``writeable=True``, writing to the view will modify the original array
+       and may affect multiple view positions. See the examples below and
+       :doc:`this guide </user/basics.copies>`
+       about the difference between copies and views.
+
+    For many applications using a sliding window view can be convenient, but
+    potentially very slow. Often specialized solutions exist, for example:
+
+    - `scipy.signal.fftconvolve`
+
+    - filtering functions in `scipy.ndimage`
+
+    - moving window functions provided by
+      `bottleneck <https://github.com/pydata/bottleneck>`_.
+
+    As a rough estimate, a sliding window approach with an input size of `N`
+    and a window size of `W` will scale as `O(N*W)` where frequently a special
+    algorithm can achieve `O(N)`. That means that the sliding window variant
+    for a window size of 100 can be a 100 times slower than a more specialized
+    version.
+
+    Nevertheless, for small window sizes, when no custom algorithm exists, or
+    as a prototyping and developing tool, this function can be a good solution.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib.stride_tricks import sliding_window_view
+    >>> x = np.arange(6)
+    >>> x.shape
+    (6,)
+    >>> v = sliding_window_view(x, 3)
+    >>> v.shape
+    (4, 3)
+    >>> v
+    array([[0, 1, 2],
+           [1, 2, 3],
+           [2, 3, 4],
+           [3, 4, 5]])
+
+    This also works in more dimensions, e.g.
+
+    >>> i, j = np.ogrid[:3, :4]
+    >>> x = 10*i + j
+    >>> x.shape
+    (3, 4)
+    >>> x
+    array([[ 0,  1,  2,  3],
+           [10, 11, 12, 13],
+           [20, 21, 22, 23]])
+    >>> shape = (2,2)
+    >>> v = sliding_window_view(x, shape)
+    >>> v.shape
+    (2, 3, 2, 2)
+    >>> v
+    array([[[[ 0,  1],
+             [10, 11]],
+            [[ 1,  2],
+             [11, 12]],
+            [[ 2,  3],
+             [12, 13]]],
+           [[[10, 11],
+             [20, 21]],
+            [[11, 12],
+             [21, 22]],
+            [[12, 13],
+             [22, 23]]]])
+
+    The axis can be specified explicitly:
+
+    >>> v = sliding_window_view(x, 3, 0)
+    >>> v.shape
+    (1, 4, 3)
+    >>> v
+    array([[[ 0, 10, 20],
+            [ 1, 11, 21],
+            [ 2, 12, 22],
+            [ 3, 13, 23]]])
+
+    The same axis can be used several times. In that case, every use reduces
+    the corresponding original dimension:
+
+    >>> v = sliding_window_view(x, (2, 3), (1, 1))
+    >>> v.shape
+    (3, 1, 2, 3)
+    >>> v
+    array([[[[ 0,  1,  2],
+             [ 1,  2,  3]]],
+           [[[10, 11, 12],
+             [11, 12, 13]]],
+           [[[20, 21, 22],
+             [21, 22, 23]]]])
+
+    Combining with stepped slicing (`::step`), this can be used to take sliding
+    views which skip elements:
+
+    >>> x = np.arange(7)
+    >>> sliding_window_view(x, 5)[:, ::2]
+    array([[0, 2, 4],
+           [1, 3, 5],
+           [2, 4, 6]])
+
+    or views which move by multiple elements
+
+    >>> x = np.arange(7)
+    >>> sliding_window_view(x, 3)[::2, :]
+    array([[0, 1, 2],
+           [2, 3, 4],
+           [4, 5, 6]])
+
+    A common application of `sliding_window_view` is the calculation of running
+    statistics. The simplest example is the
+    `moving average <https://en.wikipedia.org/wiki/Moving_average>`_:
+
+    >>> x = np.arange(6)
+    >>> x.shape
+    (6,)
+    >>> v = sliding_window_view(x, 3)
+    >>> v.shape
+    (4, 3)
+    >>> v
+    array([[0, 1, 2],
+           [1, 2, 3],
+           [2, 3, 4],
+           [3, 4, 5]])
+    >>> moving_average = v.mean(axis=-1)
+    >>> moving_average
+    array([1., 2., 3., 4.])
+
+    The two examples below demonstrate the effect of ``writeable=True``.
+
+    Creating a view with the default ``writeable=False`` and then writing to
+    it raises an error.
+
+    >>> v = sliding_window_view(x, 3)
+    >>> v[0,1] = 10
+    Traceback (most recent call last):
+    ...
+    ValueError: assignment destination is read-only
+
+    Creating a view with ``writeable=True`` and then writing to it changes
+    the original array and multiple view positions.
+
+    >>> x = np.arange(6)  # reset x for the second example
+    >>> v = sliding_window_view(x, 3, writeable=True)
+    >>> v[0,1] = 10
+    >>> x
+    array([ 0, 10,  2,  3,  4,  5])
+    >>> v
+    array([[ 0, 10,  2],
+           [10,  2,  3],
+           [ 2,  3,  4],
+           [ 3,  4,  5]])
+
+    Note that a sliding window approach is often **not** optimal (see Notes).
+    """
+    window_shape = (tuple(window_shape)
+                    if np.iterable(window_shape)
+                    else (window_shape,))
+    # first convert input to array, possibly keeping subclass
+    x = np.array(x, copy=None, subok=subok)
+
+    window_shape_array = np.array(window_shape)
+    if np.any(window_shape_array < 0):
+        raise ValueError('`window_shape` cannot contain negative values')
+
+    if axis is None:
+        axis = tuple(range(x.ndim))
+        if len(window_shape) != len(axis):
+            raise ValueError(f'Since axis is `None`, must provide '
+                             f'window_shape for all dimensions of `x`; '
+                             f'got {len(window_shape)} window_shape elements '
+                             f'and `x.ndim` is {x.ndim}.')
+    else:
+        axis = normalize_axis_tuple(axis, x.ndim, allow_duplicate=True)
+        if len(window_shape) != len(axis):
+            raise ValueError(f'Must provide matching length window_shape and '
+                             f'axis; got {len(window_shape)} window_shape '
+                             f'elements and {len(axis)} axes elements.')
+
+    out_strides = x.strides + tuple(x.strides[ax] for ax in axis)
+
+    # note: same axis can be windowed repeatedly
+    x_shape_trimmed = list(x.shape)
+    for ax, dim in zip(axis, window_shape):
+        if x_shape_trimmed[ax] < dim:
+            raise ValueError(
+                'window shape cannot be larger than input array shape')
+        x_shape_trimmed[ax] -= dim - 1
+    out_shape = tuple(x_shape_trimmed) + window_shape
+    return as_strided(x, strides=out_strides, shape=out_shape,
+                      subok=subok, writeable=writeable)
+
+
+def _broadcast_to(array, shape, subok, readonly):
+    shape = tuple(shape) if np.iterable(shape) else (shape,)
+    array = np.array(array, copy=None, subok=subok)
+    if not shape and array.shape:
+        raise ValueError('cannot broadcast a non-scalar to a scalar array')
+    if any(size < 0 for size in shape):
+        raise ValueError('all elements of broadcast shape must be non-'
+                         'negative')
+    extras = []
+    it = np.nditer(
+        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
+        op_flags=['readonly'], itershape=shape, order='C')
+    with it:
+        # never really has writebackifcopy semantics
+        broadcast = it.itviews[0]
+    result = _maybe_view_as_subclass(array, broadcast)
+    # In a future version this will go away
+    if not readonly and array.flags._writeable_no_warn:
+        result.flags.writeable = True
+        result.flags._warn_on_write = True
+    return result
+
+
+def _broadcast_to_dispatcher(array, shape, subok=None):
+    return (array,)
+
+
+@array_function_dispatch(_broadcast_to_dispatcher, module='numpy')
+def broadcast_to(array, shape, subok=False):
+    """Broadcast an array to a new shape.
+
+    Parameters
+    ----------
+    array : array_like
+        The array to broadcast.
+    shape : tuple or int
+        The shape of the desired array. A single integer ``i`` is interpreted
+        as ``(i,)``.
+    subok : bool, optional
+        If True, then sub-classes will be passed-through, otherwise
+        the returned array will be forced to be a base-class array (default).
+
+    Returns
+    -------
+    broadcast : array
+        A readonly view on the original array with the given shape. It is
+        typically not contiguous. Furthermore, more than one element of a
+        broadcasted array may refer to a single memory location.
+
+    Raises
+    ------
+    ValueError
+        If the array is not compatible with the new shape according to NumPy's
+        broadcasting rules.
+
+    See Also
+    --------
+    broadcast
+    broadcast_arrays
+    broadcast_shapes
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([1, 2, 3])
+    >>> np.broadcast_to(x, (3, 3))
+    array([[1, 2, 3],
+           [1, 2, 3],
+           [1, 2, 3]])
+    """
+    return _broadcast_to(array, shape, subok=subok, readonly=True)
+
+
+def _broadcast_shape(*args):
+    """Returns the shape of the arrays that would result from broadcasting the
+    supplied arrays against each other.
+    """
+    # use the old-iterator because np.nditer does not handle size 0 arrays
+    # consistently
+    b = np.broadcast(*args[:64])
+    # unfortunately, it cannot handle 64 or more arguments directly
+    for pos in range(64, len(args), 63):
+        # ironically, np.broadcast does not properly handle np.broadcast
+        # objects (it treats them as scalars)
+        # use broadcasting to avoid allocating the full array
+        b = broadcast_to(0, b.shape)
+        b = np.broadcast(b, *args[pos:(pos + 63)])
+    return b.shape
+
+
+_size0_dtype = np.dtype([])
+
+
+@set_module('numpy')
+def broadcast_shapes(*args):
+    """
+    Broadcast the input shapes into a single shape.
+
+    :ref:`Learn more about broadcasting here <basics.broadcasting>`.
+
+    .. versionadded:: 1.20.0
+
+    Parameters
+    ----------
+    *args : tuples of ints, or ints
+        The shapes to be broadcast against each other.
+
+    Returns
+    -------
+    tuple
+        Broadcasted shape.
+
+    Raises
+    ------
+    ValueError
+        If the shapes are not compatible and cannot be broadcast according
+        to NumPy's broadcasting rules.
+
+    See Also
+    --------
+    broadcast
+    broadcast_arrays
+    broadcast_to
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.broadcast_shapes((1, 2), (3, 1), (3, 2))
+    (3, 2)
+
+    >>> np.broadcast_shapes((6, 7), (5, 6, 1), (7,), (5, 1, 7))
+    (5, 6, 7)
+    """
+    arrays = [np.empty(x, dtype=_size0_dtype) for x in args]
+    return _broadcast_shape(*arrays)
+
+
+def _broadcast_arrays_dispatcher(*args, subok=None):
+    return args
+
+
+@array_function_dispatch(_broadcast_arrays_dispatcher, module='numpy')
+def broadcast_arrays(*args, subok=False):
+    """
+    Broadcast any number of arrays against each other.
+
+    Parameters
+    ----------
+    *args : array_likes
+        The arrays to broadcast.
+
+    subok : bool, optional
+        If True, then sub-classes will be passed-through, otherwise
+        the returned arrays will be forced to be a base-class array (default).
+
+    Returns
+    -------
+    broadcasted : tuple of arrays
+        These arrays are views on the original arrays.  They are typically
+        not contiguous.  Furthermore, more than one element of a
+        broadcasted array may refer to a single memory location. If you need
+        to write to the arrays, make copies first. While you can set the
+        ``writable`` flag True, writing to a single output value may end up
+        changing more than one location in the output array.
+
+        .. deprecated:: 1.17
+            The output is currently marked so that if written to, a deprecation
+            warning will be emitted. A future version will set the
+            ``writable`` flag False so writing to it will raise an error.
+
+    See Also
+    --------
+    broadcast
+    broadcast_to
+    broadcast_shapes
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([[1,2,3]])
+    >>> y = np.array([[4],[5]])
+    >>> np.broadcast_arrays(x, y)
+    (array([[1, 2, 3],
+            [1, 2, 3]]),
+     array([[4, 4, 4],
+            [5, 5, 5]]))
+
+    Here is a useful idiom for getting contiguous copies instead of
+    non-contiguous views.
+
+    >>> [np.array(a) for a in np.broadcast_arrays(x, y)]
+    [array([[1, 2, 3],
+            [1, 2, 3]]),
+     array([[4, 4, 4],
+            [5, 5, 5]])]
+
+    """
+    # nditer is not used here to avoid the limit of 64 arrays.
+    # Otherwise, something like the following one-liner would suffice:
+    # return np.nditer(args, flags=['multi_index', 'zerosize_ok'],
+    #                  order='C').itviews
+
+    args = [np.array(_m, copy=None, subok=subok) for _m in args]
+
+    shape = _broadcast_shape(*args)
+
+    result = [array if array.shape == shape
+              else _broadcast_to(array, shape, subok=subok, readonly=False)
+                              for array in args]
+    return tuple(result)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..b71840820d13897fc06f5d26b816ab9e37838b5a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_stride_tricks_impl.pyi
@@ -0,0 +1,73 @@
+from collections.abc import Iterable
+from typing import Any, SupportsIndex, TypeVar, overload
+
+from numpy import generic
+from numpy._typing import ArrayLike, NDArray, _AnyShape, _ArrayLike, _ShapeLike
+
+__all__ = ["broadcast_to", "broadcast_arrays", "broadcast_shapes"]
+
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+
+class DummyArray:
+    __array_interface__: dict[str, Any]
+    base: NDArray[Any] | None
+    def __init__(
+        self,
+        interface: dict[str, Any],
+        base: NDArray[Any] | None = None,
+    ) -> None: ...
+
+@overload
+def as_strided(
+    x: _ArrayLike[_ScalarT],
+    shape: Iterable[int] | None = None,
+    strides: Iterable[int] | None = None,
+    subok: bool = False,
+    writeable: bool = True,
+) -> NDArray[_ScalarT]: ...
+@overload
+def as_strided(
+    x: ArrayLike,
+    shape: Iterable[int] | None = None,
+    strides: Iterable[int] | None = None,
+    subok: bool = False,
+    writeable: bool = True,
+) -> NDArray[Any]: ...
+
+@overload
+def sliding_window_view(
+    x: _ArrayLike[_ScalarT],
+    window_shape: int | Iterable[int],
+    axis: SupportsIndex | None = None,
+    *,
+    subok: bool = False,
+    writeable: bool = False,
+) -> NDArray[_ScalarT]: ...
+@overload
+def sliding_window_view(
+    x: ArrayLike,
+    window_shape: int | Iterable[int],
+    axis: SupportsIndex | None = None,
+    *,
+    subok: bool = False,
+    writeable: bool = False,
+) -> NDArray[Any]: ...
+
+@overload
+def broadcast_to(
+    array: _ArrayLike[_ScalarT],
+    shape: int | Iterable[int],
+    subok: bool = False,
+) -> NDArray[_ScalarT]: ...
+@overload
+def broadcast_to(
+    array: ArrayLike,
+    shape: int | Iterable[int],
+    subok: bool = False,
+) -> NDArray[Any]: ...
+
+def broadcast_shapes(*args: _ShapeLike) -> _AnyShape: ...
+def broadcast_arrays(*args: ArrayLike, subok: bool = False) -> tuple[NDArray[Any], ...]: ...
+
+# used internally by `lib._function_base_impl._parse_input_dimensions`
+def _broadcast_shape(*args: ArrayLike) -> _AnyShape: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..dc1ee89cbc8b9468b3cb228d3569d9c5c2e20508
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.py
@@ -0,0 +1,1201 @@
+""" Basic functions for manipulating 2d arrays
+
+"""
+import functools
+import operator
+
+from numpy._core import iinfo, overrides
+from numpy._core._multiarray_umath import _array_converter
+from numpy._core.numeric import (
+    arange,
+    asanyarray,
+    asarray,
+    diagonal,
+    empty,
+    greater_equal,
+    indices,
+    int8,
+    int16,
+    int32,
+    int64,
+    intp,
+    multiply,
+    nonzero,
+    ones,
+    promote_types,
+    where,
+    zeros,
+)
+from numpy._core.overrides import finalize_array_function_like, set_module
+from numpy.lib._stride_tricks_impl import broadcast_to
+
+__all__ = [
+    'diag', 'diagflat', 'eye', 'fliplr', 'flipud', 'tri', 'triu',
+    'tril', 'vander', 'histogram2d', 'mask_indices', 'tril_indices',
+    'tril_indices_from', 'triu_indices', 'triu_indices_from', ]
+
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+i1 = iinfo(int8)
+i2 = iinfo(int16)
+i4 = iinfo(int32)
+
+
+def _min_int(low, high):
+    """ get small int that fits the range """
+    if high <= i1.max and low >= i1.min:
+        return int8
+    if high <= i2.max and low >= i2.min:
+        return int16
+    if high <= i4.max and low >= i4.min:
+        return int32
+    return int64
+
+
+def _flip_dispatcher(m):
+    return (m,)
+
+
+@array_function_dispatch(_flip_dispatcher)
+def fliplr(m):
+    """
+    Reverse the order of elements along axis 1 (left/right).
+
+    For a 2-D array, this flips the entries in each row in the left/right
+    direction. Columns are preserved, but appear in a different order than
+    before.
+
+    Parameters
+    ----------
+    m : array_like
+        Input array, must be at least 2-D.
+
+    Returns
+    -------
+    f : ndarray
+        A view of `m` with the columns reversed.  Since a view
+        is returned, this operation is :math:`\\mathcal O(1)`.
+
+    See Also
+    --------
+    flipud : Flip array in the up/down direction.
+    flip : Flip array in one or more dimensions.
+    rot90 : Rotate array counterclockwise.
+
+    Notes
+    -----
+    Equivalent to ``m[:,::-1]`` or ``np.flip(m, axis=1)``.
+    Requires the array to be at least 2-D.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> A = np.diag([1.,2.,3.])
+    >>> A
+    array([[1.,  0.,  0.],
+           [0.,  2.,  0.],
+           [0.,  0.,  3.]])
+    >>> np.fliplr(A)
+    array([[0.,  0.,  1.],
+           [0.,  2.,  0.],
+           [3.,  0.,  0.]])
+
+    >>> rng = np.random.default_rng()
+    >>> A = rng.normal(size=(2,3,5))
+    >>> np.all(np.fliplr(A) == A[:,::-1,...])
+    True
+
+    """
+    m = asanyarray(m)
+    if m.ndim < 2:
+        raise ValueError("Input must be >= 2-d.")
+    return m[:, ::-1]
+
+
+@array_function_dispatch(_flip_dispatcher)
+def flipud(m):
+    """
+    Reverse the order of elements along axis 0 (up/down).
+
+    For a 2-D array, this flips the entries in each column in the up/down
+    direction. Rows are preserved, but appear in a different order than before.
+
+    Parameters
+    ----------
+    m : array_like
+        Input array.
+
+    Returns
+    -------
+    out : array_like
+        A view of `m` with the rows reversed.  Since a view is
+        returned, this operation is :math:`\\mathcal O(1)`.
+
+    See Also
+    --------
+    fliplr : Flip array in the left/right direction.
+    flip : Flip array in one or more dimensions.
+    rot90 : Rotate array counterclockwise.
+
+    Notes
+    -----
+    Equivalent to ``m[::-1, ...]`` or ``np.flip(m, axis=0)``.
+    Requires the array to be at least 1-D.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> A = np.diag([1.0, 2, 3])
+    >>> A
+    array([[1.,  0.,  0.],
+           [0.,  2.,  0.],
+           [0.,  0.,  3.]])
+    >>> np.flipud(A)
+    array([[0.,  0.,  3.],
+           [0.,  2.,  0.],
+           [1.,  0.,  0.]])
+
+    >>> rng = np.random.default_rng()
+    >>> A = rng.normal(size=(2,3,5))
+    >>> np.all(np.flipud(A) == A[::-1,...])
+    True
+
+    >>> np.flipud([1,2])
+    array([2, 1])
+
+    """
+    m = asanyarray(m)
+    if m.ndim < 1:
+        raise ValueError("Input must be >= 1-d.")
+    return m[::-1, ...]
+
+
+@finalize_array_function_like
+@set_module('numpy')
+def eye(N, M=None, k=0, dtype=float, order='C', *, device=None, like=None):
+    """
+    Return a 2-D array with ones on the diagonal and zeros elsewhere.
+
+    Parameters
+    ----------
+    N : int
+      Number of rows in the output.
+    M : int, optional
+      Number of columns in the output. If None, defaults to `N`.
+    k : int, optional
+      Index of the diagonal: 0 (the default) refers to the main diagonal,
+      a positive value refers to an upper diagonal, and a negative value
+      to a lower diagonal.
+    dtype : data-type, optional
+      Data-type of the returned array.
+    order : {'C', 'F'}, optional
+        Whether the output should be stored in row-major (C-style) or
+        column-major (Fortran-style) order in memory.
+    device : str, optional
+        The device on which to place the created array. Default: None.
+        For Array-API interoperability only, so must be ``"cpu"`` if passed.
+
+        .. versionadded:: 2.0.0
+    ${ARRAY_FUNCTION_LIKE}
+
+        .. versionadded:: 1.20.0
+
+    Returns
+    -------
+    I : ndarray of shape (N,M)
+      An array where all elements are equal to zero, except for the `k`-th
+      diagonal, whose values are equal to one.
+
+    See Also
+    --------
+    identity : (almost) equivalent function
+    diag : diagonal 2-D array from a 1-D array specified by the user.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.eye(2, dtype=int)
+    array([[1, 0],
+           [0, 1]])
+    >>> np.eye(3, k=1)
+    array([[0.,  1.,  0.],
+           [0.,  0.,  1.],
+           [0.,  0.,  0.]])
+
+    """
+    if like is not None:
+        return _eye_with_like(
+            like, N, M=M, k=k, dtype=dtype, order=order, device=device
+        )
+    if M is None:
+        M = N
+    m = zeros((N, M), dtype=dtype, order=order, device=device)
+    if k >= M:
+        return m
+    # Ensure M and k are integers, so we don't get any surprise casting
+    # results in the expressions `M-k` and `M+1` used below.  This avoids
+    # a problem with inputs with type (for example) np.uint64.
+    M = operator.index(M)
+    k = operator.index(k)
+    if k >= 0:
+        i = k
+    else:
+        i = (-k) * M
+    m[:M - k].flat[i::M + 1] = 1
+    return m
+
+
+_eye_with_like = array_function_dispatch()(eye)
+
+
+def _diag_dispatcher(v, k=None):
+    return (v,)
+
+
+@array_function_dispatch(_diag_dispatcher)
+def diag(v, k=0):
+    """
+    Extract a diagonal or construct a diagonal array.
+
+    See the more detailed documentation for ``numpy.diagonal`` if you use this
+    function to extract a diagonal and wish to write to the resulting array;
+    whether it returns a copy or a view depends on what version of numpy you
+    are using.
+
+    Parameters
+    ----------
+    v : array_like
+        If `v` is a 2-D array, return a copy of its `k`-th diagonal.
+        If `v` is a 1-D array, return a 2-D array with `v` on the `k`-th
+        diagonal.
+    k : int, optional
+        Diagonal in question. The default is 0. Use `k>0` for diagonals
+        above the main diagonal, and `k<0` for diagonals below the main
+        diagonal.
+
+    Returns
+    -------
+    out : ndarray
+        The extracted diagonal or constructed diagonal array.
+
+    See Also
+    --------
+    diagonal : Return specified diagonals.
+    diagflat : Create a 2-D array with the flattened input as a diagonal.
+    trace : Sum along diagonals.
+    triu : Upper triangle of an array.
+    tril : Lower triangle of an array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(9).reshape((3,3))
+    >>> x
+    array([[0, 1, 2],
+           [3, 4, 5],
+           [6, 7, 8]])
+
+    >>> np.diag(x)
+    array([0, 4, 8])
+    >>> np.diag(x, k=1)
+    array([1, 5])
+    >>> np.diag(x, k=-1)
+    array([3, 7])
+
+    >>> np.diag(np.diag(x))
+    array([[0, 0, 0],
+           [0, 4, 0],
+           [0, 0, 8]])
+
+    """
+    v = asanyarray(v)
+    s = v.shape
+    if len(s) == 1:
+        n = s[0] + abs(k)
+        res = zeros((n, n), v.dtype)
+        if k >= 0:
+            i = k
+        else:
+            i = (-k) * n
+        res[:n - k].flat[i::n + 1] = v
+        return res
+    elif len(s) == 2:
+        return diagonal(v, k)
+    else:
+        raise ValueError("Input must be 1- or 2-d.")
+
+
+@array_function_dispatch(_diag_dispatcher)
+def diagflat(v, k=0):
+    """
+    Create a two-dimensional array with the flattened input as a diagonal.
+
+    Parameters
+    ----------
+    v : array_like
+        Input data, which is flattened and set as the `k`-th
+        diagonal of the output.
+    k : int, optional
+        Diagonal to set; 0, the default, corresponds to the "main" diagonal,
+        a positive (negative) `k` giving the number of the diagonal above
+        (below) the main.
+
+    Returns
+    -------
+    out : ndarray
+        The 2-D output array.
+
+    See Also
+    --------
+    diag : MATLAB work-alike for 1-D and 2-D arrays.
+    diagonal : Return specified diagonals.
+    trace : Sum along diagonals.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.diagflat([[1,2], [3,4]])
+    array([[1, 0, 0, 0],
+           [0, 2, 0, 0],
+           [0, 0, 3, 0],
+           [0, 0, 0, 4]])
+
+    >>> np.diagflat([1,2], 1)
+    array([[0, 1, 0],
+           [0, 0, 2],
+           [0, 0, 0]])
+
+    """
+    conv = _array_converter(v)
+    v, = conv.as_arrays(subok=False)
+    v = v.ravel()
+    s = len(v)
+    n = s + abs(k)
+    res = zeros((n, n), v.dtype)
+    if (k >= 0):
+        i = arange(0, n - k, dtype=intp)
+        fi = i + k + i * n
+    else:
+        i = arange(0, n + k, dtype=intp)
+        fi = i + (i - k) * n
+    res.flat[fi] = v
+
+    return conv.wrap(res)
+
+
+@finalize_array_function_like
+@set_module('numpy')
+def tri(N, M=None, k=0, dtype=float, *, like=None):
+    """
+    An array with ones at and below the given diagonal and zeros elsewhere.
+
+    Parameters
+    ----------
+    N : int
+        Number of rows in the array.
+    M : int, optional
+        Number of columns in the array.
+        By default, `M` is taken equal to `N`.
+    k : int, optional
+        The sub-diagonal at and below which the array is filled.
+        `k` = 0 is the main diagonal, while `k` < 0 is below it,
+        and `k` > 0 is above.  The default is 0.
+    dtype : dtype, optional
+        Data type of the returned array.  The default is float.
+    ${ARRAY_FUNCTION_LIKE}
+
+        .. versionadded:: 1.20.0
+
+    Returns
+    -------
+    tri : ndarray of shape (N, M)
+        Array with its lower triangle filled with ones and zero elsewhere;
+        in other words ``T[i,j] == 1`` for ``j <= i + k``, 0 otherwise.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.tri(3, 5, 2, dtype=int)
+    array([[1, 1, 1, 0, 0],
+           [1, 1, 1, 1, 0],
+           [1, 1, 1, 1, 1]])
+
+    >>> np.tri(3, 5, -1)
+    array([[0.,  0.,  0.,  0.,  0.],
+           [1.,  0.,  0.,  0.,  0.],
+           [1.,  1.,  0.,  0.,  0.]])
+
+    """
+    if like is not None:
+        return _tri_with_like(like, N, M=M, k=k, dtype=dtype)
+
+    if M is None:
+        M = N
+
+    m = greater_equal.outer(arange(N, dtype=_min_int(0, N)),
+                            arange(-k, M - k, dtype=_min_int(-k, M - k)))
+
+    # Avoid making a copy if the requested type is already bool
+    m = m.astype(dtype, copy=False)
+
+    return m
+
+
+_tri_with_like = array_function_dispatch()(tri)
+
+
+def _trilu_dispatcher(m, k=None):
+    return (m,)
+
+
+@array_function_dispatch(_trilu_dispatcher)
+def tril(m, k=0):
+    """
+    Lower triangle of an array.
+
+    Return a copy of an array with elements above the `k`-th diagonal zeroed.
+    For arrays with ``ndim`` exceeding 2, `tril` will apply to the final two
+    axes.
+
+    Parameters
+    ----------
+    m : array_like, shape (..., M, N)
+        Input array.
+    k : int, optional
+        Diagonal above which to zero elements.  `k = 0` (the default) is the
+        main diagonal, `k < 0` is below it and `k > 0` is above.
+
+    Returns
+    -------
+    tril : ndarray, shape (..., M, N)
+        Lower triangle of `m`, of same shape and data-type as `m`.
+
+    See Also
+    --------
+    triu : same thing, only for the upper triangle
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.tril([[1,2,3],[4,5,6],[7,8,9],[10,11,12]], -1)
+    array([[ 0,  0,  0],
+           [ 4,  0,  0],
+           [ 7,  8,  0],
+           [10, 11, 12]])
+
+    >>> np.tril(np.arange(3*4*5).reshape(3, 4, 5))
+    array([[[ 0,  0,  0,  0,  0],
+            [ 5,  6,  0,  0,  0],
+            [10, 11, 12,  0,  0],
+            [15, 16, 17, 18,  0]],
+           [[20,  0,  0,  0,  0],
+            [25, 26,  0,  0,  0],
+            [30, 31, 32,  0,  0],
+            [35, 36, 37, 38,  0]],
+           [[40,  0,  0,  0,  0],
+            [45, 46,  0,  0,  0],
+            [50, 51, 52,  0,  0],
+            [55, 56, 57, 58,  0]]])
+
+    """
+    m = asanyarray(m)
+    mask = tri(*m.shape[-2:], k=k, dtype=bool)
+
+    return where(mask, m, zeros(1, m.dtype))
+
+
+@array_function_dispatch(_trilu_dispatcher)
+def triu(m, k=0):
+    """
+    Upper triangle of an array.
+
+    Return a copy of an array with the elements below the `k`-th diagonal
+    zeroed. For arrays with ``ndim`` exceeding 2, `triu` will apply to the
+    final two axes.
+
+    Please refer to the documentation for `tril` for further details.
+
+    See Also
+    --------
+    tril : lower triangle of an array
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.triu([[1,2,3],[4,5,6],[7,8,9],[10,11,12]], -1)
+    array([[ 1,  2,  3],
+           [ 4,  5,  6],
+           [ 0,  8,  9],
+           [ 0,  0, 12]])
+
+    >>> np.triu(np.arange(3*4*5).reshape(3, 4, 5))
+    array([[[ 0,  1,  2,  3,  4],
+            [ 0,  6,  7,  8,  9],
+            [ 0,  0, 12, 13, 14],
+            [ 0,  0,  0, 18, 19]],
+           [[20, 21, 22, 23, 24],
+            [ 0, 26, 27, 28, 29],
+            [ 0,  0, 32, 33, 34],
+            [ 0,  0,  0, 38, 39]],
+           [[40, 41, 42, 43, 44],
+            [ 0, 46, 47, 48, 49],
+            [ 0,  0, 52, 53, 54],
+            [ 0,  0,  0, 58, 59]]])
+
+    """
+    m = asanyarray(m)
+    mask = tri(*m.shape[-2:], k=k - 1, dtype=bool)
+
+    return where(mask, zeros(1, m.dtype), m)
+
+
+def _vander_dispatcher(x, N=None, increasing=None):
+    return (x,)
+
+
+# Originally borrowed from John Hunter and matplotlib
+@array_function_dispatch(_vander_dispatcher)
+def vander(x, N=None, increasing=False):
+    """
+    Generate a Vandermonde matrix.
+
+    The columns of the output matrix are powers of the input vector. The
+    order of the powers is determined by the `increasing` boolean argument.
+    Specifically, when `increasing` is False, the `i`-th output column is
+    the input vector raised element-wise to the power of ``N - i - 1``. Such
+    a matrix with a geometric progression in each row is named for Alexandre-
+    Theophile Vandermonde.
+
+    Parameters
+    ----------
+    x : array_like
+        1-D input array.
+    N : int, optional
+        Number of columns in the output.  If `N` is not specified, a square
+        array is returned (``N = len(x)``).
+    increasing : bool, optional
+        Order of the powers of the columns.  If True, the powers increase
+        from left to right, if False (the default) they are reversed.
+
+    Returns
+    -------
+    out : ndarray
+        Vandermonde matrix.  If `increasing` is False, the first column is
+        ``x^(N-1)``, the second ``x^(N-2)`` and so forth. If `increasing` is
+        True, the columns are ``x^0, x^1, ..., x^(N-1)``.
+
+    See Also
+    --------
+    polynomial.polynomial.polyvander
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([1, 2, 3, 5])
+    >>> N = 3
+    >>> np.vander(x, N)
+    array([[ 1,  1,  1],
+           [ 4,  2,  1],
+           [ 9,  3,  1],
+           [25,  5,  1]])
+
+    >>> np.column_stack([x**(N-1-i) for i in range(N)])
+    array([[ 1,  1,  1],
+           [ 4,  2,  1],
+           [ 9,  3,  1],
+           [25,  5,  1]])
+
+    >>> x = np.array([1, 2, 3, 5])
+    >>> np.vander(x)
+    array([[  1,   1,   1,   1],
+           [  8,   4,   2,   1],
+           [ 27,   9,   3,   1],
+           [125,  25,   5,   1]])
+    >>> np.vander(x, increasing=True)
+    array([[  1,   1,   1,   1],
+           [  1,   2,   4,   8],
+           [  1,   3,   9,  27],
+           [  1,   5,  25, 125]])
+
+    The determinant of a square Vandermonde matrix is the product
+    of the differences between the values of the input vector:
+
+    >>> np.linalg.det(np.vander(x))
+    48.000000000000043 # may vary
+    >>> (5-3)*(5-2)*(5-1)*(3-2)*(3-1)*(2-1)
+    48
+
+    """
+    x = asarray(x)
+    if x.ndim != 1:
+        raise ValueError("x must be a one-dimensional array or sequence.")
+    if N is None:
+        N = len(x)
+
+    v = empty((len(x), N), dtype=promote_types(x.dtype, int))
+    tmp = v[:, ::-1] if not increasing else v
+
+    if N > 0:
+        tmp[:, 0] = 1
+    if N > 1:
+        tmp[:, 1:] = x[:, None]
+        multiply.accumulate(tmp[:, 1:], out=tmp[:, 1:], axis=1)
+
+    return v
+
+
+def _histogram2d_dispatcher(x, y, bins=None, range=None, density=None,
+                            weights=None):
+    yield x
+    yield y
+
+    # This terrible logic is adapted from the checks in histogram2d
+    try:
+        N = len(bins)
+    except TypeError:
+        N = 1
+    if N == 2:
+        yield from bins  # bins=[x, y]
+    else:
+        yield bins
+
+    yield weights
+
+
+@array_function_dispatch(_histogram2d_dispatcher)
+def histogram2d(x, y, bins=10, range=None, density=None, weights=None):
+    """
+    Compute the bi-dimensional histogram of two data samples.
+
+    Parameters
+    ----------
+    x : array_like, shape (N,)
+        An array containing the x coordinates of the points to be
+        histogrammed.
+    y : array_like, shape (N,)
+        An array containing the y coordinates of the points to be
+        histogrammed.
+    bins : int or array_like or [int, int] or [array, array], optional
+        The bin specification:
+
+        * If int, the number of bins for the two dimensions (nx=ny=bins).
+        * If array_like, the bin edges for the two dimensions
+          (x_edges=y_edges=bins).
+        * If [int, int], the number of bins in each dimension
+          (nx, ny = bins).
+        * If [array, array], the bin edges in each dimension
+          (x_edges, y_edges = bins).
+        * A combination [int, array] or [array, int], where int
+          is the number of bins and array is the bin edges.
+
+    range : array_like, shape(2,2), optional
+        The leftmost and rightmost edges of the bins along each dimension
+        (if not specified explicitly in the `bins` parameters):
+        ``[[xmin, xmax], [ymin, ymax]]``. All values outside of this range
+        will be considered outliers and not tallied in the histogram.
+    density : bool, optional
+        If False, the default, returns the number of samples in each bin.
+        If True, returns the probability *density* function at the bin,
+        ``bin_count / sample_count / bin_area``.
+    weights : array_like, shape(N,), optional
+        An array of values ``w_i`` weighing each sample ``(x_i, y_i)``.
+        Weights are normalized to 1 if `density` is True. If `density` is
+        False, the values of the returned histogram are equal to the sum of
+        the weights belonging to the samples falling into each bin.
+
+    Returns
+    -------
+    H : ndarray, shape(nx, ny)
+        The bi-dimensional histogram of samples `x` and `y`. Values in `x`
+        are histogrammed along the first dimension and values in `y` are
+        histogrammed along the second dimension.
+    xedges : ndarray, shape(nx+1,)
+        The bin edges along the first dimension.
+    yedges : ndarray, shape(ny+1,)
+        The bin edges along the second dimension.
+
+    See Also
+    --------
+    histogram : 1D histogram
+    histogramdd : Multidimensional histogram
+
+    Notes
+    -----
+    When `density` is True, then the returned histogram is the sample
+    density, defined such that the sum over bins of the product
+    ``bin_value * bin_area`` is 1.
+
+    Please note that the histogram does not follow the Cartesian convention
+    where `x` values are on the abscissa and `y` values on the ordinate
+    axis.  Rather, `x` is histogrammed along the first dimension of the
+    array (vertical), and `y` along the second dimension of the array
+    (horizontal).  This ensures compatibility with `histogramdd`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from matplotlib.image import NonUniformImage
+    >>> import matplotlib.pyplot as plt
+
+    Construct a 2-D histogram with variable bin width. First define the bin
+    edges:
+
+    >>> xedges = [0, 1, 3, 5]
+    >>> yedges = [0, 2, 3, 4, 6]
+
+    Next we create a histogram H with random bin content:
+
+    >>> x = np.random.normal(2, 1, 100)
+    >>> y = np.random.normal(1, 1, 100)
+    >>> H, xedges, yedges = np.histogram2d(x, y, bins=(xedges, yedges))
+    >>> # Histogram does not follow Cartesian convention (see Notes),
+    >>> # therefore transpose H for visualization purposes.
+    >>> H = H.T
+
+    :func:`imshow <matplotlib.pyplot.imshow>` can only display square bins:
+
+    >>> fig = plt.figure(figsize=(7, 3))
+    >>> ax = fig.add_subplot(131, title='imshow: square bins')
+    >>> plt.imshow(H, interpolation='nearest', origin='lower',
+    ...         extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]])
+    <matplotlib.image.AxesImage object at 0x...>
+
+    :func:`pcolormesh <matplotlib.pyplot.pcolormesh>` can display actual edges:
+
+    >>> ax = fig.add_subplot(132, title='pcolormesh: actual edges',
+    ...         aspect='equal')
+    >>> X, Y = np.meshgrid(xedges, yedges)
+    >>> ax.pcolormesh(X, Y, H)
+    <matplotlib.collections.QuadMesh object at 0x...>
+
+    :class:`NonUniformImage <matplotlib.image.NonUniformImage>` can be used to
+    display actual bin edges with interpolation:
+
+    >>> ax = fig.add_subplot(133, title='NonUniformImage: interpolated',
+    ...         aspect='equal', xlim=xedges[[0, -1]], ylim=yedges[[0, -1]])
+    >>> im = NonUniformImage(ax, interpolation='bilinear')
+    >>> xcenters = (xedges[:-1] + xedges[1:]) / 2
+    >>> ycenters = (yedges[:-1] + yedges[1:]) / 2
+    >>> im.set_data(xcenters, ycenters, H)
+    >>> ax.add_image(im)
+    >>> plt.show()
+
+    It is also possible to construct a 2-D histogram without specifying bin
+    edges:
+
+    >>> # Generate non-symmetric test data
+    >>> n = 10000
+    >>> x = np.linspace(1, 100, n)
+    >>> y = 2*np.log(x) + np.random.rand(n) - 0.5
+    >>> # Compute 2d histogram. Note the order of x/y and xedges/yedges
+    >>> H, yedges, xedges = np.histogram2d(y, x, bins=20)
+
+    Now we can plot the histogram using
+    :func:`pcolormesh <matplotlib.pyplot.pcolormesh>`, and a
+    :func:`hexbin <matplotlib.pyplot.hexbin>` for comparison.
+
+    >>> # Plot histogram using pcolormesh
+    >>> fig, (ax1, ax2) = plt.subplots(ncols=2, sharey=True)
+    >>> ax1.pcolormesh(xedges, yedges, H, cmap='rainbow')
+    >>> ax1.plot(x, 2*np.log(x), 'k-')
+    >>> ax1.set_xlim(x.min(), x.max())
+    >>> ax1.set_ylim(y.min(), y.max())
+    >>> ax1.set_xlabel('x')
+    >>> ax1.set_ylabel('y')
+    >>> ax1.set_title('histogram2d')
+    >>> ax1.grid()
+
+    >>> # Create hexbin plot for comparison
+    >>> ax2.hexbin(x, y, gridsize=20, cmap='rainbow')
+    >>> ax2.plot(x, 2*np.log(x), 'k-')
+    >>> ax2.set_title('hexbin')
+    >>> ax2.set_xlim(x.min(), x.max())
+    >>> ax2.set_xlabel('x')
+    >>> ax2.grid()
+
+    >>> plt.show()
+    """
+    from numpy import histogramdd
+
+    if len(x) != len(y):
+        raise ValueError('x and y must have the same length.')
+
+    try:
+        N = len(bins)
+    except TypeError:
+        N = 1
+
+    if N not in {1, 2}:
+        xedges = yedges = asarray(bins)
+        bins = [xedges, yedges]
+    hist, edges = histogramdd([x, y], bins, range, density, weights)
+    return hist, edges[0], edges[1]
+
+
+@set_module('numpy')
+def mask_indices(n, mask_func, k=0):
+    """
+    Return the indices to access (n, n) arrays, given a masking function.
+
+    Assume `mask_func` is a function that, for a square array a of size
+    ``(n, n)`` with a possible offset argument `k`, when called as
+    ``mask_func(a, k)`` returns a new array with zeros in certain locations
+    (functions like `triu` or `tril` do precisely this). Then this function
+    returns the indices where the non-zero values would be located.
+
+    Parameters
+    ----------
+    n : int
+        The returned indices will be valid to access arrays of shape (n, n).
+    mask_func : callable
+        A function whose call signature is similar to that of `triu`, `tril`.
+        That is, ``mask_func(x, k)`` returns a boolean array, shaped like `x`.
+        `k` is an optional argument to the function.
+    k : scalar
+        An optional argument which is passed through to `mask_func`. Functions
+        like `triu`, `tril` take a second argument that is interpreted as an
+        offset.
+
+    Returns
+    -------
+    indices : tuple of arrays.
+        The `n` arrays of indices corresponding to the locations where
+        ``mask_func(np.ones((n, n)), k)`` is True.
+
+    See Also
+    --------
+    triu, tril, triu_indices, tril_indices
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    These are the indices that would allow you to access the upper triangular
+    part of any 3x3 array:
+
+    >>> iu = np.mask_indices(3, np.triu)
+
+    For example, if `a` is a 3x3 array:
+
+    >>> a = np.arange(9).reshape(3, 3)
+    >>> a
+    array([[0, 1, 2],
+           [3, 4, 5],
+           [6, 7, 8]])
+    >>> a[iu]
+    array([0, 1, 2, 4, 5, 8])
+
+    An offset can be passed also to the masking function.  This gets us the
+    indices starting on the first diagonal right of the main one:
+
+    >>> iu1 = np.mask_indices(3, np.triu, 1)
+
+    with which we now extract only three elements:
+
+    >>> a[iu1]
+    array([1, 2, 5])
+
+    """
+    m = ones((n, n), int)
+    a = mask_func(m, k)
+    return nonzero(a != 0)
+
+
+@set_module('numpy')
+def tril_indices(n, k=0, m=None):
+    """
+    Return the indices for the lower-triangle of an (n, m) array.
+
+    Parameters
+    ----------
+    n : int
+        The row dimension of the arrays for which the returned
+        indices will be valid.
+    k : int, optional
+        Diagonal offset (see `tril` for details).
+    m : int, optional
+        The column dimension of the arrays for which the returned
+        arrays will be valid.
+        By default `m` is taken equal to `n`.
+
+
+    Returns
+    -------
+    inds : tuple of arrays
+        The row and column indices, respectively. The row indices are sorted
+        in non-decreasing order, and the corresponding column indices are
+        strictly increasing for each row.
+
+    See also
+    --------
+    triu_indices : similar function, for upper-triangular.
+    mask_indices : generic function accepting an arbitrary mask function.
+    tril, triu
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Compute two different sets of indices to access 4x4 arrays, one for the
+    lower triangular part starting at the main diagonal, and one starting two
+    diagonals further right:
+
+    >>> il1 = np.tril_indices(4)
+    >>> il1
+    (array([0, 1, 1, 2, 2, 2, 3, 3, 3, 3]), array([0, 0, 1, 0, 1, 2, 0, 1, 2, 3]))
+
+    Note that row indices (first array) are non-decreasing, and the corresponding
+    column indices (second array) are strictly increasing for each row.
+    Here is how they can be used with a sample array:
+
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+
+    Both for indexing:
+
+    >>> a[il1]
+    array([ 0,  4,  5, ..., 13, 14, 15])
+
+    And for assigning values:
+
+    >>> a[il1] = -1
+    >>> a
+    array([[-1,  1,  2,  3],
+           [-1, -1,  6,  7],
+           [-1, -1, -1, 11],
+           [-1, -1, -1, -1]])
+
+    These cover almost the whole array (two diagonals right of the main one):
+
+    >>> il2 = np.tril_indices(4, 2)
+    >>> a[il2] = -10
+    >>> a
+    array([[-10, -10, -10,   3],
+           [-10, -10, -10, -10],
+           [-10, -10, -10, -10],
+           [-10, -10, -10, -10]])
+
+    """
+    tri_ = tri(n, m, k=k, dtype=bool)
+
+    return tuple(broadcast_to(inds, tri_.shape)[tri_]
+                 for inds in indices(tri_.shape, sparse=True))
+
+
+def _trilu_indices_form_dispatcher(arr, k=None):
+    return (arr,)
+
+
+@array_function_dispatch(_trilu_indices_form_dispatcher)
+def tril_indices_from(arr, k=0):
+    """
+    Return the indices for the lower-triangle of arr.
+
+    See `tril_indices` for full details.
+
+    Parameters
+    ----------
+    arr : array_like
+        The indices will be valid for square arrays whose dimensions are
+        the same as arr.
+    k : int, optional
+        Diagonal offset (see `tril` for details).
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create a 4 by 4 array
+
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+
+    Pass the array to get the indices of the lower triangular elements.
+
+    >>> trili = np.tril_indices_from(a)
+    >>> trili
+    (array([0, 1, 1, 2, 2, 2, 3, 3, 3, 3]), array([0, 0, 1, 0, 1, 2, 0, 1, 2, 3]))
+
+    >>> a[trili]
+    array([ 0,  4,  5,  8,  9, 10, 12, 13, 14, 15])
+
+    This is syntactic sugar for tril_indices().
+
+    >>> np.tril_indices(a.shape[0])
+    (array([0, 1, 1, 2, 2, 2, 3, 3, 3, 3]), array([0, 0, 1, 0, 1, 2, 0, 1, 2, 3]))
+
+    Use the `k` parameter to return the indices for the lower triangular array
+    up to the k-th diagonal.
+
+    >>> trili1 = np.tril_indices_from(a, k=1)
+    >>> a[trili1]
+    array([ 0,  1,  4,  5,  6,  8,  9, 10, 11, 12, 13, 14, 15])
+
+    See Also
+    --------
+    tril_indices, tril, triu_indices_from
+    """
+    if arr.ndim != 2:
+        raise ValueError("input array must be 2-d")
+    return tril_indices(arr.shape[-2], k=k, m=arr.shape[-1])
+
+
+@set_module('numpy')
+def triu_indices(n, k=0, m=None):
+    """
+    Return the indices for the upper-triangle of an (n, m) array.
+
+    Parameters
+    ----------
+    n : int
+        The size of the arrays for which the returned indices will
+        be valid.
+    k : int, optional
+        Diagonal offset (see `triu` for details).
+    m : int, optional
+        The column dimension of the arrays for which the returned
+        arrays will be valid.
+        By default `m` is taken equal to `n`.
+
+
+    Returns
+    -------
+    inds : tuple, shape(2) of ndarrays, shape(`n`)
+        The row and column indices, respectively. The row indices are sorted
+        in non-decreasing order, and the corresponding column indices are
+        strictly increasing for each row.
+
+    See also
+    --------
+    tril_indices : similar function, for lower-triangular.
+    mask_indices : generic function accepting an arbitrary mask function.
+    triu, tril
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Compute two different sets of indices to access 4x4 arrays, one for the
+    upper triangular part starting at the main diagonal, and one starting two
+    diagonals further right:
+
+    >>> iu1 = np.triu_indices(4)
+    >>> iu1
+    (array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]), array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))
+
+    Note that row indices (first array) are non-decreasing, and the corresponding
+    column indices (second array) are strictly increasing for each row.
+
+    Here is how they can be used with a sample array:
+
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+
+    Both for indexing:
+
+    >>> a[iu1]
+    array([ 0,  1,  2, ..., 10, 11, 15])
+
+    And for assigning values:
+
+    >>> a[iu1] = -1
+    >>> a
+    array([[-1, -1, -1, -1],
+           [ 4, -1, -1, -1],
+           [ 8,  9, -1, -1],
+           [12, 13, 14, -1]])
+
+    These cover only a small part of the whole array (two diagonals right
+    of the main one):
+
+    >>> iu2 = np.triu_indices(4, 2)
+    >>> a[iu2] = -10
+    >>> a
+    array([[ -1,  -1, -10, -10],
+           [  4,  -1,  -1, -10],
+           [  8,   9,  -1,  -1],
+           [ 12,  13,  14,  -1]])
+
+    """
+    tri_ = ~tri(n, m, k=k - 1, dtype=bool)
+
+    return tuple(broadcast_to(inds, tri_.shape)[tri_]
+                 for inds in indices(tri_.shape, sparse=True))
+
+
+@array_function_dispatch(_trilu_indices_form_dispatcher)
+def triu_indices_from(arr, k=0):
+    """
+    Return the indices for the upper-triangle of arr.
+
+    See `triu_indices` for full details.
+
+    Parameters
+    ----------
+    arr : ndarray, shape(N, N)
+        The indices will be valid for square arrays.
+    k : int, optional
+        Diagonal offset (see `triu` for details).
+
+    Returns
+    -------
+    triu_indices_from : tuple, shape(2) of ndarray, shape(N)
+        Indices for the upper-triangle of `arr`.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create a 4 by 4 array
+
+    >>> a = np.arange(16).reshape(4, 4)
+    >>> a
+    array([[ 0,  1,  2,  3],
+           [ 4,  5,  6,  7],
+           [ 8,  9, 10, 11],
+           [12, 13, 14, 15]])
+
+    Pass the array to get the indices of the upper triangular elements.
+
+    >>> triui = np.triu_indices_from(a)
+    >>> triui
+    (array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]), array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))
+
+    >>> a[triui]
+    array([ 0,  1,  2,  3,  5,  6,  7, 10, 11, 15])
+
+    This is syntactic sugar for triu_indices().
+
+    >>> np.triu_indices(a.shape[0])
+    (array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]), array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))
+
+    Use the `k` parameter to return the indices for the upper triangular array
+    from the k-th diagonal.
+
+    >>> triuim1 = np.triu_indices_from(a, k=1)
+    >>> a[triuim1]
+    array([ 1,  2,  3,  6,  7, 11])
+
+
+    See Also
+    --------
+    triu_indices, triu, tril_indices_from
+    """
+    if arr.ndim != 2:
+        raise ValueError("input array must be 2-d")
+    return triu_indices(arr.shape[-2], k=k, m=arr.shape[-1])
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..901d0d84999496abe7ccbd0f8347f0971317ef73
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_twodim_base_impl.pyi
@@ -0,0 +1,408 @@
+from _typeshed import Incomplete
+from collections.abc import Callable, Sequence
+from typing import (
+    Any,
+    Literal as L,
+    Never,
+    Protocol,
+    TypeAlias,
+    TypeVar,
+    overload,
+    type_check_only,
+)
+
+import numpy as np
+from numpy import _OrderCF
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _ArrayLike,
+    _DTypeLike,
+    _NumberLike_co,
+    _ScalarLike_co,
+    _SupportsArray,
+    _SupportsArrayFunc,
+)
+
+__all__ = [
+    "diag",
+    "diagflat",
+    "eye",
+    "fliplr",
+    "flipud",
+    "tri",
+    "triu",
+    "tril",
+    "vander",
+    "histogram2d",
+    "mask_indices",
+    "tril_indices",
+    "tril_indices_from",
+    "triu_indices",
+    "triu_indices_from",
+]
+
+###
+
+_T = TypeVar("_T")
+_ArrayT = TypeVar("_ArrayT", bound=np.ndarray)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ComplexT = TypeVar("_ComplexT", bound=np.complexfloating)
+_InexactT = TypeVar("_InexactT", bound=np.inexact)
+_NumberT = TypeVar("_NumberT", bound=np.number)
+_NumberObjectT = TypeVar("_NumberObjectT", bound=np.number | np.object_)
+_NumberCoT = TypeVar("_NumberCoT", bound=_Number_co)
+
+_Int_co: TypeAlias = np.integer | np.bool
+_Float_co: TypeAlias = np.floating | _Int_co
+_Number_co: TypeAlias = np.number | np.bool
+
+_Array1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]]
+_Array2D: TypeAlias = np.ndarray[tuple[int, int], np.dtype[_ScalarT]]
+# Workaround for mypy's and pyright's lack of compliance with the typing spec for
+# overloads for gradual types. This works because only `Any` and `Never` are assignable
+# to `Never`.
+_ArrayNoD: TypeAlias = np.ndarray[tuple[Never] | tuple[Never, Never], np.dtype[_ScalarT]]
+
+_ArrayLike1D: TypeAlias = _SupportsArray[np.dtype[_ScalarT]] | Sequence[_ScalarT]
+_ArrayLike1DInt_co: TypeAlias = _SupportsArray[np.dtype[_Int_co]] | Sequence[int | _Int_co]
+_ArrayLike1DFloat_co: TypeAlias = _SupportsArray[np.dtype[_Float_co]] | Sequence[float | _Float_co]
+_ArrayLike2DFloat_co: TypeAlias = _SupportsArray[np.dtype[_Float_co]] | Sequence[_ArrayLike1DFloat_co]
+_ArrayLike1DNumber_co: TypeAlias = _SupportsArray[np.dtype[_Number_co]] | Sequence[complex | _Number_co]
+
+# The returned arrays dtype must be compatible with `np.equal`
+_MaskFunc: TypeAlias = Callable[[NDArray[np.int_], _T], NDArray[_Number_co | np.timedelta64 | np.datetime64 | np.object_]]
+
+_Indices2D: TypeAlias = tuple[_Array1D[np.intp], _Array1D[np.intp]]
+_Histogram2D: TypeAlias = tuple[_Array2D[np.float64], _Array1D[_ScalarT], _Array1D[_ScalarT]]
+
+@type_check_only
+class _HasShapeAndNDim(Protocol):
+    @property  # TODO: require 2d shape once shape-typing has matured
+    def shape(self) -> tuple[int, ...]: ...
+    @property
+    def ndim(self) -> int: ...
+
+###
+
+# keep in sync with `flipud`
+@overload
+def fliplr(m: _ArrayT) -> _ArrayT: ...
+@overload
+def fliplr(m: _ArrayLike[_ScalarT]) -> NDArray[_ScalarT]: ...
+@overload
+def fliplr(m: ArrayLike) -> NDArray[Any]: ...
+
+# keep in sync with `fliplr`
+@overload
+def flipud(m: _ArrayT) -> _ArrayT: ...
+@overload
+def flipud(m: _ArrayLike[_ScalarT]) -> NDArray[_ScalarT]: ...
+@overload
+def flipud(m: ArrayLike) -> NDArray[Any]: ...
+
+#
+@overload
+def eye(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    dtype: None = ...,  # = float  # stubdefaulter: ignore[missing-default]
+    order: _OrderCF = "C",
+    *,
+    device: L["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> _Array2D[np.float64]: ...
+@overload
+def eye(
+    N: int,
+    M: int | None,
+    k: int,
+    dtype: _DTypeLike[_ScalarT],
+    order: _OrderCF = "C",
+    *,
+    device: L["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> _Array2D[_ScalarT]: ...
+@overload
+def eye(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+    order: _OrderCF = "C",
+    device: L["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> _Array2D[_ScalarT]: ...
+@overload
+def eye(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    dtype: DTypeLike | None = ...,  # = float
+    order: _OrderCF = "C",
+    *,
+    device: L["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+) -> _Array2D[Incomplete]: ...
+
+#
+@overload
+def diag(v: _ArrayNoD[_ScalarT] | Sequence[Sequence[_ScalarT]], k: int = 0) -> NDArray[_ScalarT]: ...
+@overload
+def diag(v: _Array2D[_ScalarT] | Sequence[Sequence[_ScalarT]], k: int = 0) -> _Array1D[_ScalarT]: ...
+@overload
+def diag(v: _Array1D[_ScalarT] | Sequence[_ScalarT], k: int = 0) -> _Array2D[_ScalarT]: ...
+@overload
+def diag(v: Sequence[Sequence[_ScalarLike_co]], k: int = 0) -> _Array1D[Incomplete]: ...
+@overload
+def diag(v: Sequence[_ScalarLike_co], k: int = 0) -> _Array2D[Incomplete]: ...
+@overload
+def diag(v: _ArrayLike[_ScalarT], k: int = 0) -> NDArray[_ScalarT]: ...
+@overload
+def diag(v: ArrayLike, k: int = 0) -> NDArray[Incomplete]: ...
+
+# keep in sync with `numpy.ma.extras.diagflat`
+@overload
+def diagflat(v: _ArrayLike[_ScalarT], k: int = 0) -> _Array2D[_ScalarT]: ...
+@overload
+def diagflat(v: ArrayLike, k: int = 0) -> _Array2D[Incomplete]: ...
+
+#
+@overload
+def tri(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    dtype: None = ...,  # = float  # stubdefaulter: ignore[missing-default]
+    *,
+    like: _SupportsArrayFunc | None = None
+) -> _Array2D[np.float64]: ...
+@overload
+def tri(
+    N: int,
+    M: int | None,
+    k: int,
+    dtype: _DTypeLike[_ScalarT],
+    *,
+    like: _SupportsArrayFunc | None = None
+) -> _Array2D[_ScalarT]: ...
+@overload
+def tri(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+    like: _SupportsArrayFunc | None = None
+) -> _Array2D[_ScalarT]: ...
+@overload
+def tri(
+    N: int,
+    M: int | None = None,
+    k: int = 0,
+    dtype: DTypeLike | None = ...,  # = float
+    *,
+    like: _SupportsArrayFunc | None = None
+) -> _Array2D[Any]: ...
+
+# keep in sync with `triu`
+@overload
+def tril(m: _ArrayT, k: int = 0) -> _ArrayT: ...
+@overload
+def tril(m: _ArrayLike[_ScalarT], k: int = 0) -> NDArray[_ScalarT]: ...
+@overload
+def tril(m: ArrayLike, k: int = 0) -> NDArray[Any]: ...
+
+# keep in sync with `tril`
+@overload
+def triu(m: _ArrayT, k: int = 0) -> _ArrayT: ...
+@overload
+def triu(m: _ArrayLike[_ScalarT], k: int = 0) -> NDArray[_ScalarT]: ...
+@overload
+def triu(m: ArrayLike, k: int = 0) -> NDArray[Any]: ...
+
+# we use `list` (invariant) instead of `Sequence` (covariant) to avoid overlap
+@overload
+def vander(x: _ArrayLike1D[_NumberObjectT], N: int | None = None, increasing: bool = False) -> _Array2D[_NumberObjectT]: ...
+@overload
+def vander(x: _ArrayLike1D[np.bool] | list[int], N: int | None = None, increasing: bool = False) -> _Array2D[np.int_]: ...
+@overload
+def vander(x: list[float], N: int | None = None, increasing: bool = False) -> _Array2D[np.float64]: ...
+@overload
+def vander(x: list[complex], N: int | None = None, increasing: bool = False) -> _Array2D[np.complex128]: ...
+@overload  # fallback
+def vander(x: Sequence[_NumberLike_co], N: int | None = None, increasing: bool = False) -> _Array2D[Any]: ...
+
+#
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_ComplexT],
+    y: _ArrayLike1D[_ComplexT | _Float_co],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_ComplexT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_ComplexT | _Float_co],
+    y: _ArrayLike1D[_ComplexT],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_ComplexT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_InexactT],
+    y: _ArrayLike1D[_InexactT | _Int_co],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_InexactT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_InexactT | _Int_co],
+    y: _ArrayLike1D[_InexactT],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_InexactT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DInt_co | Sequence[float],
+    y: _ArrayLike1DInt_co | Sequence[float],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.float64]: ...
+@overload
+def histogram2d(
+    x: Sequence[complex],
+    y: Sequence[complex],
+    bins: int | Sequence[int] = 10,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.complex128 | Any]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DNumber_co,
+    y: _ArrayLike1DNumber_co,
+    bins: _ArrayLike1D[_NumberCoT] | Sequence[_ArrayLike1D[_NumberCoT]],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_NumberCoT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_InexactT],
+    y: _ArrayLike1D[_InexactT],
+    bins: Sequence[_ArrayLike1D[_NumberCoT] | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_InexactT | _NumberCoT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1D[_InexactT],
+    y: _ArrayLike1D[_InexactT],
+    bins: Sequence[_ArrayLike1DNumber_co | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[_InexactT | Any]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DInt_co | Sequence[float],
+    y: _ArrayLike1DInt_co | Sequence[float],
+    bins: Sequence[_ArrayLike1D[_NumberCoT] | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.float64 | _NumberCoT]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DInt_co | Sequence[float],
+    y: _ArrayLike1DInt_co | Sequence[float],
+    bins: Sequence[_ArrayLike1DNumber_co | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.float64 | Any]: ...
+@overload
+def histogram2d(
+    x: Sequence[complex],
+    y: Sequence[complex],
+    bins: Sequence[_ArrayLike1D[_NumberCoT] | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.complex128 | _NumberCoT]: ...
+@overload
+def histogram2d(
+    x: Sequence[complex],
+    y: Sequence[complex],
+    bins: Sequence[_ArrayLike1DNumber_co | int],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.complex128 | Any]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DNumber_co,
+    y: _ArrayLike1DNumber_co,
+    bins: Sequence[Sequence[int]],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.int_]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DNumber_co,
+    y: _ArrayLike1DNumber_co,
+    bins: Sequence[Sequence[float]],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.float64 | Any]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DNumber_co,
+    y: _ArrayLike1DNumber_co,
+    bins: Sequence[Sequence[complex]],
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[np.complex128 | Any]: ...
+@overload
+def histogram2d(
+    x: _ArrayLike1DNumber_co,
+    y: _ArrayLike1DNumber_co,
+    bins: Sequence[_ArrayLike1DNumber_co | int] | int,
+    range: _ArrayLike2DFloat_co | None = None,
+    density: bool | None = None,
+    weights: _ArrayLike1DFloat_co | None = None,
+) -> _Histogram2D[Any]: ...
+
+# NOTE: we're assuming/demanding here the `mask_func` returns
+# an ndarray of shape `(n, n)`; otherwise there is the possibility
+# of the output tuple having more or less than 2 elements
+@overload
+def mask_indices(n: int, mask_func: _MaskFunc[int], k: int = 0) -> _Indices2D: ...
+@overload
+def mask_indices(n: int, mask_func: _MaskFunc[_T], k: _T) -> _Indices2D: ...
+
+#
+def tril_indices(n: int, k: int = 0, m: int | None = None) -> _Indices2D: ...
+def triu_indices(n: int, k: int = 0, m: int | None = None) -> _Indices2D: ...
+
+# these will accept anything with `shape: tuple[int, int]` and `ndim: int` attributes
+def tril_indices_from(arr: _HasShapeAndNDim, k: int = 0) -> _Indices2D: ...
+def triu_indices_from(arr: _HasShapeAndNDim, k: int = 0) -> _Indices2D: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..5d52f3d2f29c2713f0d262114647af001bfa8e3a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.py
@@ -0,0 +1,710 @@
+"""Automatically adapted for numpy Sep 19, 2005 by convertcode.py
+
+"""
+import functools
+
+__all__ = ['iscomplexobj', 'isrealobj', 'imag', 'iscomplex',
+           'isreal', 'nan_to_num', 'real', 'real_if_close',
+           'typename', 'mintypecode',
+           'common_type']
+
+import numpy._core.numeric as _nx
+from numpy._core import getlimits, overrides
+from numpy._core.numeric import asanyarray, asarray, isnan, zeros
+from numpy._utils import set_module
+
+from ._ufunclike_impl import isneginf, isposinf
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy')
+
+
+_typecodes_by_elsize = 'GDFgdfQqLlIiHhBb?'
+
+
+@set_module('numpy')
+def mintypecode(typechars, typeset='GDFgdf', default='d'):
+    """
+    Return the character for the minimum-size type to which given types can
+    be safely cast.
+
+    The returned type character must represent the smallest size dtype such
+    that an array of the returned type can handle the data from an array of
+    all types in `typechars` (or if `typechars` is an array, then its
+    dtype.char).
+
+    Parameters
+    ----------
+    typechars : list of str or array_like
+        If a list of strings, each string should represent a dtype.
+        If array_like, the character representation of the array dtype is used.
+    typeset : str or list of str, optional
+        The set of characters that the returned character is chosen from.
+        The default set is 'GDFgdf'.
+    default : str, optional
+        The default character, this is returned if none of the characters in
+        `typechars` matches a character in `typeset`.
+
+    Returns
+    -------
+    typechar : str
+        The character representing the minimum-size type that was found.
+
+    See Also
+    --------
+    dtype
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.mintypecode(['d', 'f', 'S'])
+    'd'
+    >>> x = np.array([1.1, 2-3.j])
+    >>> np.mintypecode(x)
+    'D'
+
+    >>> np.mintypecode('abceh', default='G')
+    'G'
+
+    """
+    typecodes = ((isinstance(t, str) and t) or asarray(t).dtype.char
+                 for t in typechars)
+    intersection = {t for t in typecodes if t in typeset}
+    if not intersection:
+        return default
+    if 'F' in intersection and 'd' in intersection:
+        return 'D'
+    return min(intersection, key=_typecodes_by_elsize.index)
+
+
+def _real_dispatcher(val):
+    return (val,)
+
+
+@array_function_dispatch(_real_dispatcher)
+def real(val):
+    """
+    Return the real part of the complex argument.
+
+    Parameters
+    ----------
+    val : array_like
+        Input array.
+
+    Returns
+    -------
+    out : ndarray or scalar
+        The real component of the complex argument. If `val` is real, the type
+        of `val` is used for the output.  If `val` has complex elements, the
+        returned type is float.
+
+    See Also
+    --------
+    real_if_close, imag, angle
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1+2j, 3+4j, 5+6j])
+    >>> a.real
+    array([1.,  3.,  5.])
+    >>> a.real = 9
+    >>> a
+    array([9.+2.j,  9.+4.j,  9.+6.j])
+    >>> a.real = np.array([9, 8, 7])
+    >>> a
+    array([9.+2.j,  8.+4.j,  7.+6.j])
+    >>> np.real(1 + 1j)
+    1.0
+
+    """
+    try:
+        return val.real
+    except AttributeError:
+        return asanyarray(val).real
+
+
+def _imag_dispatcher(val):
+    return (val,)
+
+
+@array_function_dispatch(_imag_dispatcher)
+def imag(val):
+    """
+    Return the imaginary part of the complex argument.
+
+    Parameters
+    ----------
+    val : array_like
+        Input array.
+
+    Returns
+    -------
+    out : ndarray or scalar
+        The imaginary component of the complex argument. If `val` is real,
+        the type of `val` is used for the output.  If `val` has complex
+        elements, the returned type is float.
+
+    See Also
+    --------
+    real, angle, real_if_close
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1+2j, 3+4j, 5+6j])
+    >>> a.imag
+    array([2.,  4.,  6.])
+    >>> a.imag = np.array([8, 10, 12])
+    >>> a
+    array([1. +8.j,  3.+10.j,  5.+12.j])
+    >>> np.imag(1 + 1j)
+    1.0
+
+    """
+    try:
+        return val.imag
+    except AttributeError:
+        return asanyarray(val).imag
+
+
+def _is_type_dispatcher(x):
+    return (x,)
+
+
+@array_function_dispatch(_is_type_dispatcher)
+def iscomplex(x):
+    """
+    Returns a bool array, where True if input element is complex.
+
+    What is tested is whether the input has a non-zero imaginary part, not if
+    the input type is complex.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.
+
+    Returns
+    -------
+    out : ndarray of bools
+        Output array.
+
+    See Also
+    --------
+    isreal
+    iscomplexobj : Return True if x is a complex type or an array of complex
+                   numbers.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.iscomplex([1+1j, 1+0j, 4.5, 3, 2, 2j])
+    array([ True, False, False, False, False,  True])
+
+    """
+    ax = asanyarray(x)
+    if issubclass(ax.dtype.type, _nx.complexfloating):
+        return ax.imag != 0
+    res = zeros(ax.shape, bool)
+    return res[()]   # convert to scalar if needed
+
+
+@array_function_dispatch(_is_type_dispatcher)
+def isreal(x):
+    """
+    Returns a bool array, where True if input element is real.
+
+    If element has complex type with zero imaginary part, the return value
+    for that element is True.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.
+
+    Returns
+    -------
+    out : ndarray, bool
+        Boolean array of same shape as `x`.
+
+    Notes
+    -----
+    `isreal` may behave unexpectedly for string or object arrays (see examples)
+
+    See Also
+    --------
+    iscomplex
+    isrealobj : Return True if x is not a complex type.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1+1j, 1+0j, 4.5, 3, 2, 2j], dtype=complex)
+    >>> np.isreal(a)
+    array([False,  True,  True,  True,  True, False])
+
+    The function does not work on string arrays.
+
+    >>> a = np.array([2j, "a"], dtype="U")
+    >>> np.isreal(a)  # Warns about non-elementwise comparison
+    False
+
+    Returns True for all elements in input array of ``dtype=object`` even if
+    any of the elements is complex.
+
+    >>> a = np.array([1, "2", 3+4j], dtype=object)
+    >>> np.isreal(a)
+    array([ True,  True,  True])
+
+    isreal should not be used with object arrays
+
+    >>> a = np.array([1+2j, 2+1j], dtype=object)
+    >>> np.isreal(a)
+    array([ True,  True])
+
+    """
+    return imag(x) == 0
+
+
+@array_function_dispatch(_is_type_dispatcher)
+def iscomplexobj(x):
+    """
+    Check for a complex type or an array of complex numbers.
+
+    The type of the input is checked, not the value. Even if the input
+    has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
+
+    Parameters
+    ----------
+    x : any
+        The input can be of any type and shape.
+
+    Returns
+    -------
+    iscomplexobj : bool
+        The return value, True if `x` is of a complex type or has at least
+        one complex element.
+
+    See Also
+    --------
+    isrealobj, iscomplex
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.iscomplexobj(1)
+    False
+    >>> np.iscomplexobj(1+0j)
+    True
+    >>> np.iscomplexobj([3, 1+0j, True])
+    True
+
+    """
+    try:
+        dtype = x.dtype
+        type_ = dtype.type
+    except AttributeError:
+        type_ = asarray(x).dtype.type
+    return issubclass(type_, _nx.complexfloating)
+
+
+@array_function_dispatch(_is_type_dispatcher)
+def isrealobj(x):
+    """
+    Return True if x is a not complex type or an array of complex numbers.
+
+    The type of the input is checked, not the value. So even if the input
+    has an imaginary part equal to zero, `isrealobj` evaluates to False
+    if the data type is complex.
+
+    Parameters
+    ----------
+    x : any
+        The input can be of any type and shape.
+
+    Returns
+    -------
+    y : bool
+        The return value, False if `x` is of a complex type.
+
+    See Also
+    --------
+    iscomplexobj, isreal
+
+    Notes
+    -----
+    The function is only meant for arrays with numerical values but it
+    accepts all other objects. Since it assumes array input, the return
+    value of other objects may be True.
+
+    >>> np.isrealobj('A string')
+    True
+    >>> np.isrealobj(False)
+    True
+    >>> np.isrealobj(None)
+    True
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.isrealobj(1)
+    True
+    >>> np.isrealobj(1+0j)
+    False
+    >>> np.isrealobj([3, 1+0j, True])
+    False
+
+    """
+    return not iscomplexobj(x)
+
+#-----------------------------------------------------------------------------
+
+def _getmaxmin(t):
+    from numpy._core import getlimits
+    f = getlimits.finfo(t)
+    return f.max, f.min
+
+
+def _nan_to_num_dispatcher(x, copy=None, nan=None, posinf=None, neginf=None):
+    return (x,)
+
+
+@array_function_dispatch(_nan_to_num_dispatcher)
+def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):
+    """
+    Replace NaN with zero and infinity with large finite numbers (default
+    behaviour) or with the numbers defined by the user using the `nan`,
+    `posinf` and/or `neginf` keywords.
+
+    If `x` is inexact, NaN is replaced by zero or by the user defined value in
+    `nan` keyword, infinity is replaced by the largest finite floating point
+    values representable by ``x.dtype`` or by the user defined value in
+    `posinf` keyword and -infinity is replaced by the most negative finite
+    floating point values representable by ``x.dtype`` or by the user defined
+    value in `neginf` keyword.
+
+    For complex dtypes, the above is applied to each of the real and
+    imaginary components of `x` separately.
+
+    If `x` is not inexact, then no replacements are made.
+
+    Parameters
+    ----------
+    x : scalar or array_like
+        Input data.
+    copy : bool, optional
+        Whether to create a copy of `x` (True) or to replace values
+        in-place (False). The in-place operation only occurs if
+        casting to an array does not require a copy.
+        Default is True.
+    nan : int, float, or bool or array_like of int, float, or bool, optional
+        Values to be used to fill NaN values. If no values are passed
+        then NaN values will be replaced with 0.0.
+    posinf : int, float, or bool or array_like of int, float, or bool, optional
+        Values to be used to fill positive infinity values. If no values are
+        passed then positive infinity values will be replaced with a very
+        large number.
+    neginf : int, float, or bool or array_like of int, float, or bool, optional
+        Values to be used to fill negative infinity values. If no values are
+        passed then negative infinity values will be replaced with a very
+        small (or negative) number.
+
+    Returns
+    -------
+    out : ndarray
+        `x`, with the non-finite values replaced. If `copy` is False, this may
+        be `x` itself.
+
+    See Also
+    --------
+    isinf : Shows which elements are positive or negative infinity.
+    isneginf : Shows which elements are negative infinity.
+    isposinf : Shows which elements are positive infinity.
+    isnan : Shows which elements are Not a Number (NaN).
+    isfinite : Shows which elements are finite (not NaN, not infinity)
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.nan_to_num(np.inf)
+    1.7976931348623157e+308
+    >>> np.nan_to_num(-np.inf)
+    -1.7976931348623157e+308
+    >>> np.nan_to_num(np.nan)
+    0.0
+    >>> x = np.array([np.inf, -np.inf, np.nan, -128, 128])
+    >>> np.nan_to_num(x)
+    array([ 1.79769313e+308, -1.79769313e+308,  0.00000000e+000, # may vary
+           -1.28000000e+002,  1.28000000e+002])
+    >>> np.nan_to_num(x, nan=-9999, posinf=33333333, neginf=33333333)
+    array([ 3.3333333e+07,  3.3333333e+07, -9.9990000e+03,
+           -1.2800000e+02,  1.2800000e+02])
+    >>> nan = np.array([11, 12, -9999, 13, 14])
+    >>> posinf = np.array([33333333, 11, 12, 13, 14])
+    >>> neginf = np.array([11, 33333333, 12, 13, 14])
+    >>> np.nan_to_num(x, nan=nan, posinf=posinf, neginf=neginf)
+    array([ 3.3333333e+07,  3.3333333e+07, -9.9990000e+03, -1.2800000e+02,
+            1.2800000e+02])
+    >>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)])
+    array([  1.79769313e+308,  -1.79769313e+308,   0.00000000e+000, # may vary
+         -1.28000000e+002,   1.28000000e+002])
+    >>> np.nan_to_num(y)
+    array([  1.79769313e+308 +0.00000000e+000j, # may vary
+             0.00000000e+000 +0.00000000e+000j,
+             0.00000000e+000 +1.79769313e+308j])
+    >>> np.nan_to_num(y, nan=111111, posinf=222222)
+    array([222222.+111111.j, 111111.     +0.j, 111111.+222222.j])
+    >>> nan = np.array([11, 12, 13])
+    >>> posinf = np.array([21, 22, 23])
+    >>> neginf = np.array([31, 32, 33])
+    >>> np.nan_to_num(y, nan=nan, posinf=posinf, neginf=neginf)
+    array([21.+11.j, 12. +0.j, 13.+23.j])
+    """
+    x = _nx.array(x, subok=True, copy=copy)
+    xtype = x.dtype.type
+
+    isscalar = (x.ndim == 0)
+
+    if not issubclass(xtype, _nx.inexact):
+        return x[()] if isscalar else x
+
+    iscomplex = issubclass(xtype, _nx.complexfloating)
+
+    dest = (x.real, x.imag) if iscomplex else (x,)
+    maxf, minf = _getmaxmin(x.real.dtype)
+    if posinf is not None:
+        maxf = posinf
+    if neginf is not None:
+        minf = neginf
+    for d in dest:
+        idx_nan = isnan(d)
+        idx_posinf = isposinf(d)
+        idx_neginf = isneginf(d)
+        _nx.copyto(d, nan, where=idx_nan)
+        _nx.copyto(d, maxf, where=idx_posinf)
+        _nx.copyto(d, minf, where=idx_neginf)
+    return x[()] if isscalar else x
+
+#-----------------------------------------------------------------------------
+
+def _real_if_close_dispatcher(a, tol=None):
+    return (a,)
+
+
+@array_function_dispatch(_real_if_close_dispatcher)
+def real_if_close(a, tol=100):
+    """
+    If input is complex with all imaginary parts close to zero, return
+    real parts.
+
+    "Close to zero" is defined as `tol` * (machine epsilon of the type for
+    `a`).
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    tol : float
+        Tolerance in machine epsilons for the complex part of the elements
+        in the array. If the tolerance is <=1, then the absolute tolerance
+        is used.
+
+    Returns
+    -------
+    out : ndarray
+        If `a` is real, the type of `a` is used for the output.  If `a`
+        has complex elements, the returned type is float.
+
+    See Also
+    --------
+    real, imag, angle
+
+    Notes
+    -----
+    Machine epsilon varies from machine to machine and between data types
+    but Python floats on most platforms have a machine epsilon equal to
+    2.2204460492503131e-16.  You can use 'np.finfo(float).eps' to print
+    out the machine epsilon for floats.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.finfo(float).eps
+    2.2204460492503131e-16 # may vary
+
+    >>> np.real_if_close([2.1 + 4e-14j, 5.2 + 3e-15j], tol=1000)
+    array([2.1, 5.2])
+    >>> np.real_if_close([2.1 + 4e-13j, 5.2 + 3e-15j], tol=1000)
+    array([2.1+4.e-13j, 5.2 + 3e-15j])
+
+    """
+    a = asanyarray(a)
+    type_ = a.dtype.type
+    if not issubclass(type_, _nx.complexfloating):
+        return a
+    if tol > 1:
+        f = getlimits.finfo(type_)
+        tol = f.eps * tol
+    if _nx.all(_nx.absolute(a.imag) < tol):
+        a = a.real
+    return a
+
+
+#-----------------------------------------------------------------------------
+
+_namefromtype = {'S1': 'character',
+                 '?': 'bool',
+                 'b': 'signed char',
+                 'B': 'unsigned char',
+                 'h': 'short',
+                 'H': 'unsigned short',
+                 'i': 'integer',
+                 'I': 'unsigned integer',
+                 'l': 'long integer',
+                 'L': 'unsigned long integer',
+                 'q': 'long long integer',
+                 'Q': 'unsigned long long integer',
+                 'f': 'single precision',
+                 'd': 'double precision',
+                 'g': 'long precision',
+                 'F': 'complex single precision',
+                 'D': 'complex double precision',
+                 'G': 'complex long double precision',
+                 'S': 'string',
+                 'U': 'unicode',
+                 'V': 'void',
+                 'O': 'object'
+                 }
+
+@set_module('numpy')
+def typename(char):
+    """
+    Return a description for the given data type code.
+
+    Parameters
+    ----------
+    char : str
+        Data type code.
+
+    Returns
+    -------
+    out : str
+        Description of the input data type code.
+
+    See Also
+    --------
+    dtype
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> typechars = ['S1', '?', 'B', 'D', 'G', 'F', 'I', 'H', 'L', 'O', 'Q',
+    ...              'S', 'U', 'V', 'b', 'd', 'g', 'f', 'i', 'h', 'l', 'q']
+    >>> for typechar in typechars:
+    ...     print(typechar, ' : ', np.typename(typechar))
+    ...
+    S1  :  character
+    ?  :  bool
+    B  :  unsigned char
+    D  :  complex double precision
+    G  :  complex long double precision
+    F  :  complex single precision
+    I  :  unsigned integer
+    H  :  unsigned short
+    L  :  unsigned long integer
+    O  :  object
+    Q  :  unsigned long long integer
+    S  :  string
+    U  :  unicode
+    V  :  void
+    b  :  signed char
+    d  :  double precision
+    g  :  long precision
+    f  :  single precision
+    i  :  integer
+    h  :  short
+    l  :  long integer
+    q  :  long long integer
+
+    """
+    return _namefromtype[char]
+
+#-----------------------------------------------------------------------------
+
+
+#determine the "minimum common type" for a group of arrays.
+array_type = [[_nx.float16, _nx.float32, _nx.float64, _nx.longdouble],
+              [None, _nx.complex64, _nx.complex128, _nx.clongdouble]]
+array_precision = {_nx.float16: 0,
+                   _nx.float32: 1,
+                   _nx.float64: 2,
+                   _nx.longdouble: 3,
+                   _nx.complex64: 1,
+                   _nx.complex128: 2,
+                   _nx.clongdouble: 3}
+
+
+def _common_type_dispatcher(*arrays):
+    return arrays
+
+
+@array_function_dispatch(_common_type_dispatcher)
+def common_type(*arrays):
+    """
+    Return a scalar type which is common to the input arrays.
+
+    The return type will always be an inexact (i.e. floating point) scalar
+    type, even if all the arrays are integer arrays. If one of the inputs is
+    an integer array, the minimum precision type that is returned is a
+    64-bit floating point dtype.
+
+    All input arrays except int64 and uint64 can be safely cast to the
+    returned dtype without loss of information.
+
+    Parameters
+    ----------
+    array1, array2, ... : ndarrays
+        Input arrays.
+
+    Returns
+    -------
+    out : data type code
+        Data type code.
+
+    See Also
+    --------
+    dtype, mintypecode
+
+    Examples
+    --------
+    >>> np.common_type(np.arange(2, dtype=np.float32))
+    <class 'numpy.float32'>
+    >>> np.common_type(np.arange(2, dtype=np.float32), np.arange(2))
+    <class 'numpy.float64'>
+    >>> np.common_type(np.arange(4), np.array([45, 6.j]), np.array([45.0]))
+    <class 'numpy.complex128'>
+
+    """
+    is_complex = False
+    precision = 0
+    for a in arrays:
+        t = a.dtype.type
+        if iscomplexobj(a):
+            is_complex = True
+        if issubclass(t, _nx.integer):
+            p = 2  # array_precision[_nx.double]
+        else:
+            p = array_precision.get(t)
+            if p is None:
+                raise TypeError("can't get common type for non-numeric array")
+        precision = max(precision, p)
+    if is_complex:
+        return array_type[1][precision]
+    else:
+        return array_type[0][precision]
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..eeffc8c487abc45880256a20d14a9f044557572f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_type_check_impl.pyi
@@ -0,0 +1,348 @@
+from _typeshed import Incomplete
+from collections.abc import Container, Iterable
+from typing import Any, Literal as L, Protocol, TypeAlias, overload, type_check_only
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy._typing import (
+    ArrayLike,
+    NDArray,
+    _16Bit,
+    _32Bit,
+    _64Bit,
+    _ArrayLike,
+    _NestedSequence,
+    _ScalarLike_co,
+    _SupportsArray,
+)
+
+__all__ = [
+    "common_type",
+    "imag",
+    "iscomplex",
+    "iscomplexobj",
+    "isreal",
+    "isrealobj",
+    "mintypecode",
+    "nan_to_num",
+    "real",
+    "real_if_close",
+    "typename",
+]
+
+_T = TypeVar("_T")
+_T_co = TypeVar("_T_co", covariant=True)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True)
+_RealT = TypeVar("_RealT", bound=np.floating | np.integer | np.bool)
+
+_FloatMax32: TypeAlias = np.float32 | np.float16
+_ComplexMax128: TypeAlias = np.complex128 | np.complex64
+_RealMax64: TypeAlias = np.float64 | np.float32 | np.float16 | np.integer
+_Real: TypeAlias = np.floating | np.integer
+_InexactMax32: TypeAlias = np.inexact[_32Bit] | np.float16
+_NumberMax64: TypeAlias = np.number[_64Bit] | np.number[_32Bit] | np.number[_16Bit] | np.integer
+
+@type_check_only
+class _HasReal(Protocol[_T_co]):
+    @property
+    def real(self, /) -> _T_co: ...
+
+@type_check_only
+class _HasImag(Protocol[_T_co]):
+    @property
+    def imag(self, /) -> _T_co: ...
+
+@type_check_only
+class _HasDType(Protocol[_ScalarT_co]):
+    @property
+    def dtype(self, /) -> np.dtype[_ScalarT_co]: ...
+
+###
+
+def mintypecode(typechars: Iterable[str | ArrayLike], typeset: str | Container[str] = "GDFgdf", default: str = "d") -> str: ...
+
+#
+@overload
+def real(val: _HasReal[_T]) -> _T: ...  # type: ignore[overload-overlap]
+@overload
+def real(val: _ArrayLike[_RealT]) -> NDArray[_RealT]: ...
+@overload
+def real(val: ArrayLike) -> NDArray[Any]: ...
+
+#
+@overload
+def imag(val: _HasImag[_T]) -> _T: ...  # type: ignore[overload-overlap]
+@overload
+def imag(val: _ArrayLike[_RealT]) -> NDArray[_RealT]: ...
+@overload
+def imag(val: ArrayLike) -> NDArray[Any]: ...
+
+#
+@overload
+def iscomplex(x: _ScalarLike_co) -> np.bool: ...
+@overload
+def iscomplex(x: NDArray[Any] | _NestedSequence[ArrayLike]) -> NDArray[np.bool]: ...
+@overload
+def iscomplex(x: ArrayLike) -> np.bool | NDArray[np.bool]: ...
+
+#
+@overload
+def isreal(x: _ScalarLike_co) -> np.bool: ...
+@overload
+def isreal(x: NDArray[Any] | _NestedSequence[ArrayLike]) -> NDArray[np.bool]: ...
+@overload
+def isreal(x: ArrayLike) -> np.bool | NDArray[np.bool]: ...
+
+#
+def iscomplexobj(x: _HasDType[Any] | ArrayLike) -> bool: ...
+def isrealobj(x: _HasDType[Any] | ArrayLike) -> bool: ...
+
+#
+@overload
+def nan_to_num(
+    x: _ScalarT,
+    copy: bool = True,
+    nan: float = 0.0,
+    posinf: float | None = None,
+    neginf: float | None = None,
+) -> _ScalarT: ...
+@overload
+def nan_to_num(
+    x: NDArray[_ScalarT] | _NestedSequence[_ArrayLike[_ScalarT]],
+    copy: bool = True,
+    nan: float = 0.0,
+    posinf: float | None = None,
+    neginf: float | None = None,
+) -> NDArray[_ScalarT]: ...
+@overload
+def nan_to_num(
+    x: _SupportsArray[np.dtype[_ScalarT]],
+    copy: bool = True,
+    nan: float = 0.0,
+    posinf: float | None = None,
+    neginf: float | None = None,
+) -> _ScalarT | NDArray[_ScalarT]: ...
+@overload
+def nan_to_num(
+    x: _NestedSequence[ArrayLike],
+    copy: bool = True,
+    nan: float = 0.0,
+    posinf: float | None = None,
+    neginf: float | None = None,
+) -> NDArray[Incomplete]: ...
+@overload
+def nan_to_num(
+    x: ArrayLike,
+    copy: bool = True,
+    nan: float = 0.0,
+    posinf: float | None = None,
+    neginf: float | None = None,
+) -> Incomplete: ...
+
+# NOTE: The [overload-overlap] mypy error is a false positive
+@overload
+def real_if_close(a: _ArrayLike[np.complex64], tol: float = 100) -> NDArray[np.float32 | np.complex64]: ...  # type: ignore[overload-overlap]
+@overload
+def real_if_close(a: _ArrayLike[np.complex128], tol: float = 100) -> NDArray[np.float64 | np.complex128]: ...
+@overload
+def real_if_close(a: _ArrayLike[np.clongdouble], tol: float = 100) -> NDArray[np.longdouble | np.clongdouble]: ...
+@overload
+def real_if_close(a: _ArrayLike[_RealT], tol: float = 100) -> NDArray[_RealT]: ...
+@overload
+def real_if_close(a: ArrayLike, tol: float = 100) -> NDArray[Any]: ...
+
+#
+@overload
+def typename(char: L["S1"]) -> L["character"]: ...
+@overload
+def typename(char: L["?"]) -> L["bool"]: ...
+@overload
+def typename(char: L["b"]) -> L["signed char"]: ...
+@overload
+def typename(char: L["B"]) -> L["unsigned char"]: ...
+@overload
+def typename(char: L["h"]) -> L["short"]: ...
+@overload
+def typename(char: L["H"]) -> L["unsigned short"]: ...
+@overload
+def typename(char: L["i"]) -> L["integer"]: ...
+@overload
+def typename(char: L["I"]) -> L["unsigned integer"]: ...
+@overload
+def typename(char: L["l"]) -> L["long integer"]: ...
+@overload
+def typename(char: L["L"]) -> L["unsigned long integer"]: ...
+@overload
+def typename(char: L["q"]) -> L["long long integer"]: ...
+@overload
+def typename(char: L["Q"]) -> L["unsigned long long integer"]: ...
+@overload
+def typename(char: L["f"]) -> L["single precision"]: ...
+@overload
+def typename(char: L["d"]) -> L["double precision"]: ...
+@overload
+def typename(char: L["g"]) -> L["long precision"]: ...
+@overload
+def typename(char: L["F"]) -> L["complex single precision"]: ...
+@overload
+def typename(char: L["D"]) -> L["complex double precision"]: ...
+@overload
+def typename(char: L["G"]) -> L["complex long double precision"]: ...
+@overload
+def typename(char: L["S"]) -> L["string"]: ...
+@overload
+def typename(char: L["U"]) -> L["unicode"]: ...
+@overload
+def typename(char: L["V"]) -> L["void"]: ...
+@overload
+def typename(char: L["O"]) -> L["object"]: ...
+
+# NOTE: The [overload-overlap] mypy errors are false positives
+@overload
+def common_type() -> type[np.float16]: ...
+@overload
+def common_type(a0: _HasDType[np.float16], /, *ai: _HasDType[np.float16]) -> type[np.float16]: ...  # type: ignore[overload-overlap]
+@overload
+def common_type(a0: _HasDType[np.float32], /, *ai: _HasDType[_FloatMax32]) -> type[np.float32]: ...  # type: ignore[overload-overlap]
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[np.float64 | np.integer],
+    /,
+    *ai: _HasDType[_RealMax64],
+) -> type[np.float64]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[np.longdouble],
+    /,
+    *ai: _HasDType[_Real],
+) -> type[np.longdouble]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[np.complex64],
+    /,
+    *ai: _HasDType[_InexactMax32],
+) -> type[np.complex64]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[np.complex128],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[np.clongdouble],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.clongdouble]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[_FloatMax32],
+    array1: _HasDType[np.float32],
+    /,
+    *ai: _HasDType[_FloatMax32],
+) -> type[np.float32]: ...
+@overload
+def common_type(
+    a0: _HasDType[_RealMax64],
+    array1: _HasDType[np.float64 | np.integer],
+    /,
+    *ai: _HasDType[_RealMax64],
+) -> type[np.float64]: ...
+@overload
+def common_type(
+    a0: _HasDType[_Real],
+    array1: _HasDType[np.longdouble],
+    /,
+    *ai: _HasDType[_Real],
+) -> type[np.longdouble]: ...
+@overload
+def common_type(  # type: ignore[overload-overlap]
+    a0: _HasDType[_InexactMax32],
+    array1: _HasDType[np.complex64],
+    /,
+    *ai: _HasDType[_InexactMax32],
+) -> type[np.complex64]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.float64],
+    array1: _HasDType[_ComplexMax128],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(
+    a0: _HasDType[_ComplexMax128],
+    array1: _HasDType[np.float64],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(
+    a0: _HasDType[_NumberMax64],
+    array1: _HasDType[np.complex128],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(
+    a0: _HasDType[_ComplexMax128],
+    array1: _HasDType[np.complex128 | np.integer],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.complex128 | np.integer],
+    array1: _HasDType[_ComplexMax128],
+    /,
+    *ai: _HasDType[_NumberMax64],
+) -> type[np.complex128]: ...
+@overload
+def common_type(
+    a0: _HasDType[_Real],
+    /,
+    *ai: _HasDType[_Real],
+) -> type[np.floating]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.number],
+    array1: _HasDType[np.clongdouble],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.clongdouble]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.longdouble],
+    array1: _HasDType[np.complexfloating],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.clongdouble]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.complexfloating],
+    array1: _HasDType[np.longdouble],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.clongdouble]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.complexfloating],
+    array1: _HasDType[np.number],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.complexfloating]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.number],
+    array1: _HasDType[np.complexfloating],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[np.complexfloating]: ...
+@overload
+def common_type(
+    a0: _HasDType[np.number],
+    array1: _HasDType[np.number],
+    /,
+    *ai: _HasDType[np.number],
+) -> type[Any]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd9990ac308dcfd70b1be74b7fd7e4a0a3d47e07
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.py
@@ -0,0 +1,199 @@
+"""
+Module of functions that are like ufuncs in acting on arrays and optionally
+storing results in an output array.
+
+"""
+__all__ = ['fix', 'isneginf', 'isposinf']
+
+import numpy._core.numeric as nx
+from numpy._core.overrides import array_function_dispatch
+
+
+def _dispatcher(x, out=None):
+    return (x, out)
+
+
+@array_function_dispatch(_dispatcher, verify=False, module='numpy')
+def fix(x, out=None):
+    """
+    Round to nearest integer towards zero.
+
+    Round an array of floats element-wise to nearest integer towards zero.
+    The rounded values have the same data-type as the input.
+
+    Parameters
+    ----------
+    x : array_like
+        An array to be rounded
+    out : ndarray, optional
+        A location into which the result is stored. If provided, it must have
+        a shape that the input broadcasts to. If not provided or None, a
+        freshly-allocated array is returned.
+
+    Returns
+    -------
+    out : ndarray of floats
+        An array with the same dimensions and data-type as the input.
+        If second argument is not supplied then a new array is returned
+        with the rounded values.
+
+        If a second argument is supplied the result is stored there.
+        The return value ``out`` is then a reference to that array.
+
+    See Also
+    --------
+    rint, trunc, floor, ceil
+    around : Round to given number of decimals
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.fix(3.14)
+    3.0
+    >>> np.fix(3)
+    3
+    >>> np.fix([2.1, 2.9, -2.1, -2.9])
+    array([ 2.,  2., -2., -2.])
+
+    """
+    return nx.trunc(x, out=out)
+
+
+@array_function_dispatch(_dispatcher, verify=False, module='numpy')
+def isposinf(x, out=None):
+    """
+    Test element-wise for positive infinity, return result as bool array.
+
+    Parameters
+    ----------
+    x : array_like
+        The input array.
+    out : array_like, optional
+        A location into which the result is stored. If provided, it must have a
+        shape that the input broadcasts to. If not provided or None, a
+        freshly-allocated boolean array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        A boolean array with the same dimensions as the input.
+        If second argument is not supplied then a boolean array is returned
+        with values True where the corresponding element of the input is
+        positive infinity and values False where the element of the input is
+        not positive infinity.
+
+        If a second argument is supplied the result is stored there. If the
+        type of that array is a numeric type the result is represented as zeros
+        and ones, if the type is boolean then as False and True.
+        The return value `out` is then a reference to that array.
+
+    See Also
+    --------
+    isinf, isneginf, isfinite, isnan
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754).
+
+    Errors result if the second argument is also supplied when x is a scalar
+    input, if first and second arguments have different shapes, or if the
+    first argument has complex values
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.isposinf(np.inf)
+    True
+    >>> np.isposinf(-np.inf)
+    False
+    >>> np.isposinf([-np.inf, 0., np.inf])
+    array([False, False,  True])
+
+    >>> x = np.array([-np.inf, 0., np.inf])
+    >>> y = np.array([2, 2, 2])
+    >>> np.isposinf(x, y)
+    array([0, 0, 1])
+    >>> y
+    array([0, 0, 1])
+
+    """
+    is_inf = nx.isinf(x)
+    try:
+        signbit = ~nx.signbit(x)
+    except TypeError as e:
+        dtype = nx.asanyarray(x).dtype
+        raise TypeError(f'This operation is not supported for {dtype} values '
+                        'because it would be ambiguous.') from e
+    else:
+        return nx.logical_and(is_inf, signbit, out)
+
+
+@array_function_dispatch(_dispatcher, verify=False, module='numpy')
+def isneginf(x, out=None):
+    """
+    Test element-wise for negative infinity, return result as bool array.
+
+    Parameters
+    ----------
+    x : array_like
+        The input array.
+    out : array_like, optional
+        A location into which the result is stored. If provided, it must have a
+        shape that the input broadcasts to. If not provided or None, a
+        freshly-allocated boolean array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        A boolean array with the same dimensions as the input.
+        If second argument is not supplied then a numpy boolean array is
+        returned with values True where the corresponding element of the
+        input is negative infinity and values False where the element of
+        the input is not negative infinity.
+
+        If a second argument is supplied the result is stored there. If the
+        type of that array is a numeric type the result is represented as
+        zeros and ones, if the type is boolean then as False and True. The
+        return value `out` is then a reference to that array.
+
+    See Also
+    --------
+    isinf, isposinf, isnan, isfinite
+
+    Notes
+    -----
+    NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754).
+
+    Errors result if the second argument is also supplied when x is a scalar
+    input, if first and second arguments have different shapes, or if the
+    first argument has complex values.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.isneginf(-np.inf)
+    True
+    >>> np.isneginf(np.inf)
+    False
+    >>> np.isneginf([-np.inf, 0., np.inf])
+    array([ True, False, False])
+
+    >>> x = np.array([-np.inf, 0., np.inf])
+    >>> y = np.array([2, 2, 2])
+    >>> np.isneginf(x, y)
+    array([1, 0, 0])
+    >>> y
+    array([1, 0, 0])
+
+    """
+    is_inf = nx.isinf(x)
+    try:
+        signbit = nx.signbit(x)
+    except TypeError as e:
+        dtype = nx.asanyarray(x).dtype
+        raise TypeError(f'This operation is not supported for {dtype} values '
+                        'because it would be ambiguous.') from e
+    else:
+        return nx.logical_and(is_inf, signbit, out)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..ad5426e8d277bc66e5dbddab76009ffbc9d05de6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_ufunclike_impl.pyi
@@ -0,0 +1,60 @@
+from typing import Any, TypeVar, overload
+from typing_extensions import deprecated
+
+import numpy as np
+from numpy import floating, object_
+from numpy._typing import (
+    NDArray,
+    _ArrayLikeFloat_co,
+    _ArrayLikeObject_co,
+    _FloatLike_co,
+)
+
+__all__ = ["fix", "isneginf", "isposinf"]
+
+_ArrayT = TypeVar("_ArrayT", bound=NDArray[Any])
+
+@overload
+@deprecated("np.fix will be deprecated in NumPy 2.5 in favor of np.trunc", category=PendingDeprecationWarning)
+def fix(x: _FloatLike_co, out: None = None) -> floating: ...
+@overload
+@deprecated("np.fix will be deprecated in NumPy 2.5 in favor of np.trunc", category=PendingDeprecationWarning)
+def fix(x: _ArrayLikeFloat_co, out: None = None) -> NDArray[floating]: ...
+@overload
+@deprecated("np.fix will be deprecated in NumPy 2.5 in favor of np.trunc", category=PendingDeprecationWarning)
+def fix(x: _ArrayLikeObject_co, out: None = None) -> NDArray[object_]: ...
+@overload
+@deprecated("np.fix will be deprecated in NumPy 2.5 in favor of np.trunc", category=PendingDeprecationWarning)
+def fix(x: _ArrayLikeFloat_co | _ArrayLikeObject_co, out: _ArrayT) -> _ArrayT: ...
+
+@overload
+def isposinf(  # type: ignore[misc]
+    x: _FloatLike_co,
+    out: None = None,
+) -> np.bool: ...
+@overload
+def isposinf(
+    x: _ArrayLikeFloat_co,
+    out: None = None,
+) -> NDArray[np.bool]: ...
+@overload
+def isposinf(
+    x: _ArrayLikeFloat_co,
+    out: _ArrayT,
+) -> _ArrayT: ...
+
+@overload
+def isneginf(  # type: ignore[misc]
+    x: _FloatLike_co,
+    out: None = None,
+) -> np.bool: ...
+@overload
+def isneginf(
+    x: _ArrayLikeFloat_co,
+    out: None = None,
+) -> NDArray[np.bool]: ...
+@overload
+def isneginf(
+    x: _ArrayLikeFloat_co,
+    out: _ArrayT,
+) -> _ArrayT: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..3a4b7f4ae90120eb1196397e15084d6a0cc87f95
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.py
@@ -0,0 +1,310 @@
+"""
+Container class for backward compatibility with NumArray.
+
+The user_array.container class exists for backward compatibility with NumArray
+and is not meant to be used in new code. If you need to create an array
+container class, we recommend either creating a class that wraps an ndarray
+or subclasses ndarray.
+
+"""
+from numpy._core import (
+    absolute,
+    add,
+    arange,
+    array,
+    asarray,
+    bitwise_and,
+    bitwise_or,
+    bitwise_xor,
+    divide,
+    equal,
+    greater,
+    greater_equal,
+    invert,
+    left_shift,
+    less,
+    less_equal,
+    multiply,
+    not_equal,
+    power,
+    remainder,
+    reshape,
+    right_shift,
+    shape,
+    sin,
+    sqrt,
+    subtract,
+    transpose,
+)
+from numpy._core.overrides import set_module
+
+
+@set_module("numpy.lib.user_array")
+class container:
+    """
+    container(data, dtype=None, copy=True)
+
+    Standard container-class for easy multiple-inheritance.
+
+    Methods
+    -------
+    copy
+    byteswap
+    astype
+
+    """
+    def __init_subclass__(cls) -> None:
+        # Deprecated in NumPy 2.4, 2025-11-24
+        import warnings
+
+        warnings.warn(
+            "The numpy.lib.user_array.container class is deprecated and will be "
+            "removed in a future version.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+
+    def __init__(self, data, dtype=None, copy=True):
+        self.array = array(data, dtype, copy=copy)
+
+    def __repr__(self):
+        if self.ndim > 0:
+            return self.__class__.__name__ + repr(self.array)[len("array"):]
+        else:
+            return self.__class__.__name__ + "(" + repr(self.array) + ")"
+
+    def __array__(self, t=None):
+        if t:
+            return self.array.astype(t)
+        return self.array
+
+    # Array as sequence
+    def __len__(self):
+        return len(self.array)
+
+    def __getitem__(self, index):
+        return self._rc(self.array[index])
+
+    def __setitem__(self, index, value):
+        self.array[index] = asarray(value, self.dtype)
+
+    def __abs__(self):
+        return self._rc(absolute(self.array))
+
+    def __neg__(self):
+        return self._rc(-self.array)
+
+    def __add__(self, other):
+        return self._rc(self.array + asarray(other))
+
+    __radd__ = __add__
+
+    def __iadd__(self, other):
+        add(self.array, other, self.array)
+        return self
+
+    def __sub__(self, other):
+        return self._rc(self.array - asarray(other))
+
+    def __rsub__(self, other):
+        return self._rc(asarray(other) - self.array)
+
+    def __isub__(self, other):
+        subtract(self.array, other, self.array)
+        return self
+
+    def __mul__(self, other):
+        return self._rc(multiply(self.array, asarray(other)))
+
+    __rmul__ = __mul__
+
+    def __imul__(self, other):
+        multiply(self.array, other, self.array)
+        return self
+
+    def __mod__(self, other):
+        return self._rc(remainder(self.array, other))
+
+    def __rmod__(self, other):
+        return self._rc(remainder(other, self.array))
+
+    def __imod__(self, other):
+        remainder(self.array, other, self.array)
+        return self
+
+    def __divmod__(self, other):
+        return (self._rc(divide(self.array, other)),
+                self._rc(remainder(self.array, other)))
+
+    def __rdivmod__(self, other):
+        return (self._rc(divide(other, self.array)),
+                self._rc(remainder(other, self.array)))
+
+    def __pow__(self, other):
+        return self._rc(power(self.array, asarray(other)))
+
+    def __rpow__(self, other):
+        return self._rc(power(asarray(other), self.array))
+
+    def __ipow__(self, other):
+        power(self.array, other, self.array)
+        return self
+
+    def __lshift__(self, other):
+        return self._rc(left_shift(self.array, other))
+
+    def __rshift__(self, other):
+        return self._rc(right_shift(self.array, other))
+
+    def __rlshift__(self, other):
+        return self._rc(left_shift(other, self.array))
+
+    def __rrshift__(self, other):
+        return self._rc(right_shift(other, self.array))
+
+    def __ilshift__(self, other):
+        left_shift(self.array, other, self.array)
+        return self
+
+    def __irshift__(self, other):
+        right_shift(self.array, other, self.array)
+        return self
+
+    def __and__(self, other):
+        return self._rc(bitwise_and(self.array, other))
+
+    def __rand__(self, other):
+        return self._rc(bitwise_and(other, self.array))
+
+    def __iand__(self, other):
+        bitwise_and(self.array, other, self.array)
+        return self
+
+    def __xor__(self, other):
+        return self._rc(bitwise_xor(self.array, other))
+
+    def __rxor__(self, other):
+        return self._rc(bitwise_xor(other, self.array))
+
+    def __ixor__(self, other):
+        bitwise_xor(self.array, other, self.array)
+        return self
+
+    def __or__(self, other):
+        return self._rc(bitwise_or(self.array, other))
+
+    def __ror__(self, other):
+        return self._rc(bitwise_or(other, self.array))
+
+    def __ior__(self, other):
+        bitwise_or(self.array, other, self.array)
+        return self
+
+    def __pos__(self):
+        return self._rc(self.array)
+
+    def __invert__(self):
+        return self._rc(invert(self.array))
+
+    def _scalarfunc(self, func):
+        if self.ndim == 0:
+            return func(self[0])
+        else:
+            raise TypeError(
+                "only rank-0 arrays can be converted to Python scalars.")
+
+    def __complex__(self):
+        return self._scalarfunc(complex)
+
+    def __float__(self):
+        return self._scalarfunc(float)
+
+    def __int__(self):
+        return self._scalarfunc(int)
+
+    def __hex__(self):
+        return self._scalarfunc(hex)
+
+    def __oct__(self):
+        return self._scalarfunc(oct)
+
+    def __lt__(self, other):
+        return self._rc(less(self.array, other))
+
+    def __le__(self, other):
+        return self._rc(less_equal(self.array, other))
+
+    def __eq__(self, other):
+        return self._rc(equal(self.array, other))
+
+    def __ne__(self, other):
+        return self._rc(not_equal(self.array, other))
+
+    def __gt__(self, other):
+        return self._rc(greater(self.array, other))
+
+    def __ge__(self, other):
+        return self._rc(greater_equal(self.array, other))
+
+    def copy(self):
+        ""
+        return self._rc(self.array.copy())
+
+    def tobytes(self):
+        ""
+        return self.array.tobytes()
+
+    def byteswap(self):
+        ""
+        return self._rc(self.array.byteswap())
+
+    def astype(self, typecode):
+        ""
+        return self._rc(self.array.astype(typecode))
+
+    def _rc(self, a):
+        if len(shape(a)) == 0:
+            return a
+        else:
+            return self.__class__(a)
+
+    def __array_wrap__(self, *args):
+        return self.__class__(args[0])
+
+    def __setattr__(self, attr, value):
+        if attr == 'array':
+            object.__setattr__(self, attr, value)
+            return
+        try:
+            self.array.__setattr__(attr, value)
+        except AttributeError:
+            object.__setattr__(self, attr, value)
+
+    # Only called after other approaches fail.
+    def __getattr__(self, attr):
+        if (attr == 'array'):
+            return object.__getattribute__(self, attr)
+        return self.array.__getattribute__(attr)
+
+
+#############################################################
+# Test of class container
+#############################################################
+if __name__ == '__main__':
+    temp = reshape(arange(10000), (100, 100))
+
+    ua = container(temp)
+    # new object created begin test
+    print(dir(ua))
+    print(shape(ua), ua.shape)  # I have changed Numeric.py
+
+    ua_small = ua[:3, :5]
+    print(ua_small)
+    # this did not change ua[0,0], which is not normal behavior
+    ua_small[0, 0] = 10
+    print(ua_small[0, 0], ua[0, 0])
+    print(sin(ua_small) / 3. * 6. + sqrt(ua_small ** 2))
+    print(less(ua_small, 103), type(less(ua_small, 103)))
+    print(type(ua_small * reshape(arange(15), shape(ua_small))))
+    print(reshape(ua_small, (5, 3)))
+    print(transpose(ua_small))
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..1e21f1246b77a841c395c9a41ee395f7171f9622
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_user_array_impl.pyi
@@ -0,0 +1,226 @@
+from _typeshed import Incomplete
+from types import EllipsisType
+from typing import Any, Generic, Self, SupportsIndex, TypeAlias, overload
+from typing_extensions import TypeVar, deprecated, override
+
+import numpy as np
+import numpy.typing as npt
+from numpy._typing import (
+    _AnyShape,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeInt_co,
+    _DTypeLike,
+)
+
+###
+
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
+_ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=_AnyShape, covariant=True)
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
+
+_BoolArrayT = TypeVar("_BoolArrayT", bound=container[Any, np.dtype[np.bool]])
+_IntegralArrayT = TypeVar("_IntegralArrayT", bound=container[Any, np.dtype[np.bool | np.integer | np.object_]])
+_RealContainerT = TypeVar(
+    "_RealContainerT",
+    bound=container[Any, np.dtype[np.bool | np.integer | np.floating | np.timedelta64 | np.object_]],
+)
+_NumericContainerT = TypeVar("_NumericContainerT", bound=container[Any, np.dtype[np.number | np.timedelta64 | np.object_]])
+
+_ArrayInt_co: TypeAlias = npt.NDArray[np.integer | np.bool]
+
+_ToIndexSlice: TypeAlias = slice | EllipsisType | _ArrayInt_co | None
+_ToIndexSlices: TypeAlias = _ToIndexSlice | tuple[_ToIndexSlice, ...]
+_ToIndex: TypeAlias = SupportsIndex | _ToIndexSlice
+_ToIndices: TypeAlias = _ToIndex | tuple[_ToIndex, ...]
+
+###
+# pyright: reportDeprecated = false
+
+@deprecated("The numpy.lib.user_array.container class is deprecated and will be removed in a future version.")
+class container(Generic[_ShapeT_co, _DTypeT_co]):
+    array: np.ndarray[_ShapeT_co, _DTypeT_co]
+
+    @overload
+    def __init__(
+        self,
+        /,
+        data: container[_ShapeT_co, _DTypeT_co] | np.ndarray[_ShapeT_co, _DTypeT_co],
+        dtype: None = None,
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: container[Any, np.dtype[_ScalarT]],
+        /,
+        data: _ArrayLike[_ScalarT],
+        dtype: None = None,
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: container[Any, np.dtype[_ScalarT]],
+        /,
+        data: npt.ArrayLike,
+        dtype: _DTypeLike[_ScalarT],
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(self, /, data: npt.ArrayLike, dtype: npt.DTypeLike | None = None, copy: bool = True) -> None: ...
+
+    #
+    def __complex__(self, /) -> complex: ...
+    def __float__(self, /) -> float: ...
+    def __int__(self, /) -> int: ...
+    def __hex__(self, /) -> str: ...
+    def __oct__(self, /) -> str: ...
+
+    #
+    @override
+    def __eq__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    @override
+    def __ne__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    #
+    def __lt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __le__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __gt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __ge__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+
+    #
+    def __len__(self, /) -> int: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __getitem__(self, key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> container[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, key: _ToIndexSlices, /) -> container[_AnyShape, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, key: _ToIndices, /) -> Any: ...
+    @overload
+    def __getitem__(self: container[Any, np.dtype[np.void]], key: list[str], /) -> container[_ShapeT_co, np.dtype[np.void]]: ...
+    @overload
+    def __getitem__(self: container[Any, np.dtype[np.void]], key: str, /) -> container[_ShapeT_co, np.dtype]: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __setitem__(self, index: _ToIndices, value: object, /) -> None: ...
+    @overload
+    def __setitem__(self: container[Any, np.dtype[np.void]], key: str | list[str], value: object, /) -> None: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex64]], /) -> container[_ShapeT, np.dtype[np.float32]]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex128]], /) -> container[_ShapeT, np.dtype[np.float64]]: ...
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex192]], /) -> container[_ShapeT, np.dtype[np.float96]]: ...
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex256]], /) -> container[_ShapeT, np.dtype[np.float128]]: ...
+    @overload
+    def __abs__(self: _RealContainerT, /) -> _RealContainerT: ...
+
+    #
+    def __neg__(self: _NumericContainerT, /) -> _NumericContainerT: ...  # noqa: PYI019
+    def __pos__(self: _NumericContainerT, /) -> _NumericContainerT: ...  # noqa: PYI019
+    def __invert__(self: _IntegralArrayT, /) -> _IntegralArrayT: ...  # noqa: PYI019
+
+    # TODO(jorenham): complete these binary ops
+
+    #
+    def __add__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __radd__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __iadd__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __sub__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rsub__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __isub__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __mul__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rmul__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __imul__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __mod__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rmod__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __imod__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __divmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ...
+    def __rdivmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ...
+
+    #
+    def __pow__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rpow__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __ipow__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __lshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ...
+    def __rlshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ...
+    def __ilshift__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    def __rshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ...
+    def __rrshift__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.integer]]: ...
+    def __irshift__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __and__(
+        self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /
+    ) -> container[_AnyShape, np.dtype[np.bool]]: ...
+    @overload
+    def __and__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ...
+    __rand__ = __and__
+    @overload
+    def __iand__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __iand__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __xor__(
+        self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /
+    ) -> container[_AnyShape, np.dtype[np.bool]]: ...
+    @overload
+    def __xor__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ...
+    __rxor__ = __xor__
+    @overload
+    def __ixor__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __ixor__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __or__(
+        self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /
+    ) -> container[_AnyShape, np.dtype[np.bool]]: ...
+    @overload
+    def __or__(self, other: _ArrayLikeInt_co, /) -> container[_AnyShape, np.dtype[np.bool | np.integer]]: ...
+    __ror__ = __or__
+    @overload
+    def __ior__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __ior__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __array__(self, /, t: None = None) -> np.ndarray[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __array__(self, /, t: _DTypeT) -> np.ndarray[_ShapeT_co, _DTypeT]: ...
+
+    #
+    @overload
+    def __array_wrap__(self, arg0: npt.ArrayLike, /) -> container[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __array_wrap__(self, a: np.ndarray[_ShapeT, _DTypeT], c: Any = ..., s: Any = ..., /) -> container[_ShapeT, _DTypeT]: ...
+
+    #
+    def copy(self, /) -> Self: ...
+    def tobytes(self, /) -> bytes: ...
+    def byteswap(self, /) -> Self: ...
+    def astype(self, /, typecode: _DTypeLike[_ScalarT]) -> container[_ShapeT_co, np.dtype[_ScalarT]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.py b/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb30000a9451d8f92dd1f3e55f5525ba35dd3313
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.py
@@ -0,0 +1,784 @@
+import functools
+import os
+import platform
+import sys
+import textwrap
+import types
+import warnings
+
+import numpy as np
+from numpy._core import ndarray
+from numpy._utils import set_module
+
+__all__ = [
+    'get_include', 'info', 'show_runtime'
+]
+
+
+@set_module('numpy')
+def show_runtime():
+    """
+    Print information about various resources in the system
+    including available intrinsic support and BLAS/LAPACK library
+    in use
+
+    .. versionadded:: 1.24.0
+
+    See Also
+    --------
+    show_config : Show libraries in the system on which NumPy was built.
+
+    Notes
+    -----
+    1. Information is derived with the help of `threadpoolctl <https://pypi.org/project/threadpoolctl/>`_
+       library if available.
+    2. SIMD related information is derived from ``__cpu_features__``,
+       ``__cpu_baseline__`` and ``__cpu_dispatch__``
+
+    """
+    from pprint import pprint
+
+    from numpy._core._multiarray_umath import (
+        __cpu_baseline__,
+        __cpu_dispatch__,
+        __cpu_features__,
+    )
+    config_found = [{
+        "numpy_version": np.__version__,
+        "python": sys.version,
+        "uname": platform.uname(),
+        }]
+    features_found, features_not_found = [], []
+    for feature in __cpu_dispatch__:
+        if __cpu_features__[feature]:
+            features_found.append(feature)
+        else:
+            features_not_found.append(feature)
+    config_found.append({
+        "simd_extensions": {
+            "baseline": __cpu_baseline__,
+            "found": features_found,
+            "not_found": features_not_found
+        }
+    })
+    config_found.append({
+        "ignore_floating_point_errors_in_matmul":
+            not np._core._multiarray_umath._blas_supports_fpe(None),
+    })
+
+    try:
+        from threadpoolctl import threadpool_info
+        config_found.extend(threadpool_info())
+    except ImportError:
+        print("WARNING: `threadpoolctl` not found in system!"
+              " Install it by `pip install threadpoolctl`."
+              " Once installed, try `np.show_runtime` again"
+              " for more detailed build information")
+    pprint(config_found)
+
+
+@set_module('numpy')
+def get_include():
+    """
+    Return the directory that contains the NumPy \\*.h header files.
+
+    Extension modules that need to compile against NumPy may need to use this
+    function to locate the appropriate include directory.
+
+    Notes
+    -----
+    When using ``setuptools``, for example in ``setup.py``::
+
+        import numpy as np
+        ...
+        Extension('extension_name', ...
+                  include_dirs=[np.get_include()])
+        ...
+
+    Note that a CLI tool ``numpy-config`` was introduced in NumPy 2.0, using
+    that is likely preferred for build systems other than ``setuptools``::
+
+        $ numpy-config --cflags
+        -I/path/to/site-packages/numpy/_core/include
+
+        # Or rely on pkg-config:
+        $ export PKG_CONFIG_PATH=$(numpy-config --pkgconfigdir)
+        $ pkg-config --cflags
+        -I/path/to/site-packages/numpy/_core/include
+
+    Examples
+    --------
+    >>> np.get_include()
+    '.../site-packages/numpy/core/include'  # may vary
+
+    """
+    import numpy
+    if numpy.show_config is None:
+        # running from numpy source directory
+        d = os.path.join(os.path.dirname(numpy.__file__), '_core', 'include')
+    else:
+        # using installed numpy core headers
+        import numpy._core as _core
+        d = os.path.join(os.path.dirname(_core.__file__), 'include')
+    return d
+
+
+class _Deprecate:
+    """
+    Decorator class to deprecate old functions.
+
+    Refer to `deprecate` for details.
+
+    See Also
+    --------
+    deprecate
+
+    """
+
+    def __init__(self, old_name=None, new_name=None, message=None):
+        self.old_name = old_name
+        self.new_name = new_name
+        self.message = message
+
+    def __call__(self, func, *args, **kwargs):
+        """
+        Decorator call.  Refer to ``decorate``.
+
+        """
+        old_name = self.old_name
+        new_name = self.new_name
+        message = self.message
+
+        if old_name is None:
+            old_name = func.__name__
+        if new_name is None:
+            depdoc = f"`{old_name}` is deprecated!"
+        else:
+            depdoc = f"`{old_name}` is deprecated, use `{new_name}` instead!"
+
+        if message is not None:
+            depdoc += "\n" + message
+
+        @functools.wraps(func)
+        def newfunc(*args, **kwds):
+            warnings.warn(depdoc, DeprecationWarning, stacklevel=2)
+            return func(*args, **kwds)
+
+        newfunc.__name__ = old_name
+        doc = func.__doc__
+        if doc is None:
+            doc = depdoc
+        else:
+            lines = doc.expandtabs().split('\n')
+            indent = _get_indent(lines[1:])
+            if lines[0].lstrip():
+                # Indent the original first line to let inspect.cleandoc()
+                # dedent the docstring despite the deprecation notice.
+                doc = indent * ' ' + doc
+            else:
+                # Remove the same leading blank lines as cleandoc() would.
+                skip = len(lines[0]) + 1
+                for line in lines[1:]:
+                    if len(line) > indent:
+                        break
+                    skip += len(line) + 1
+                doc = doc[skip:]
+            depdoc = textwrap.indent(depdoc, ' ' * indent)
+            doc = f'{depdoc}\n\n{doc}'
+        newfunc.__doc__ = doc
+
+        return newfunc
+
+
+def _get_indent(lines):
+    """
+    Determines the leading whitespace that could be removed from all the lines.
+    """
+    indent = sys.maxsize
+    for line in lines:
+        content = len(line.lstrip())
+        if content:
+            indent = min(indent, len(line) - content)
+    if indent == sys.maxsize:
+        indent = 0
+    return indent
+
+
+def deprecate(*args, **kwargs):
+    """
+    Issues a DeprecationWarning, adds warning to `old_name`'s
+    docstring, rebinds ``old_name.__name__`` and returns the new
+    function object.
+
+    This function may also be used as a decorator.
+
+    .. deprecated:: 2.0
+        Use `~warnings.warn` with :exc:`DeprecationWarning` instead.
+
+    Parameters
+    ----------
+    func : function
+        The function to be deprecated.
+    old_name : str, optional
+        The name of the function to be deprecated. Default is None, in
+        which case the name of `func` is used.
+    new_name : str, optional
+        The new name for the function. Default is None, in which case the
+        deprecation message is that `old_name` is deprecated. If given, the
+        deprecation message is that `old_name` is deprecated and `new_name`
+        should be used instead.
+    message : str, optional
+        Additional explanation of the deprecation.  Displayed in the
+        docstring after the warning.
+
+    Returns
+    -------
+    old_func : function
+        The deprecated function.
+
+    Examples
+    --------
+    Note that ``olduint`` returns a value after printing Deprecation
+    Warning:
+
+    >>> olduint = np.lib.utils.deprecate(np.uint)
+    DeprecationWarning: `uint64` is deprecated! # may vary
+    >>> olduint(6)
+    6
+
+    """
+    # Deprecate may be run as a function or as a decorator
+    # If run as a function, we initialise the decorator class
+    # and execute its __call__ method.
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`deprecate` is deprecated, "
+        "use `warn` with `DeprecationWarning` instead. "
+        "(deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    if args:
+        fn = args[0]
+        args = args[1:]
+
+        return _Deprecate(*args, **kwargs)(fn)
+    else:
+        return _Deprecate(*args, **kwargs)
+
+
+def deprecate_with_doc(msg):
+    """
+    Deprecates a function and includes the deprecation in its docstring.
+
+    .. deprecated:: 2.0
+        Use `~warnings.warn` with :exc:`DeprecationWarning` instead.
+
+    This function is used as a decorator. It returns an object that can be
+    used to issue a DeprecationWarning, by passing the to-be decorated
+    function as argument, this adds warning to the to-be decorated function's
+    docstring and returns the new function object.
+
+    See Also
+    --------
+    deprecate : Decorate a function such that it issues a
+                :exc:`DeprecationWarning`
+
+    Parameters
+    ----------
+    msg : str
+        Additional explanation of the deprecation. Displayed in the
+        docstring after the warning.
+
+    Returns
+    -------
+    obj : object
+
+    """
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`deprecate` is deprecated, "
+        "use `warn` with `DeprecationWarning` instead. "
+        "(deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    return _Deprecate(message=msg)
+
+
+#-----------------------------------------------------------------------------
+
+
+# NOTE:  pydoc defines a help function which works similarly to this
+#  except it uses a pager to take over the screen.
+
+# combine name and arguments and split to multiple lines of width
+# characters.  End lines on a comma and begin argument list indented with
+# the rest of the arguments.
+def _split_line(name, arguments, width):
+    firstwidth = len(name)
+    k = firstwidth
+    newstr = name
+    sepstr = ", "
+    arglist = arguments.split(sepstr)
+    for argument in arglist:
+        if k == firstwidth:
+            addstr = ""
+        else:
+            addstr = sepstr
+        k = k + len(argument) + len(addstr)
+        if k > width:
+            k = firstwidth + 1 + len(argument)
+            newstr = newstr + ",\n" + " " * (firstwidth + 2) + argument
+        else:
+            newstr = newstr + addstr + argument
+    return newstr
+
+
+_namedict = None
+_dictlist = None
+
+# Traverse all module directories underneath globals
+# to see if something is defined
+def _makenamedict(module='numpy'):
+    module = __import__(module, globals(), locals(), [])
+    thedict = {module.__name__: module.__dict__}
+    dictlist = [module.__name__]
+    totraverse = [module.__dict__]
+    while True:
+        if len(totraverse) == 0:
+            break
+        thisdict = totraverse.pop(0)
+        for x in thisdict.keys():
+            if isinstance(thisdict[x], types.ModuleType):
+                modname = thisdict[x].__name__
+                if modname not in dictlist:
+                    moddict = thisdict[x].__dict__
+                    dictlist.append(modname)
+                    totraverse.append(moddict)
+                    thedict[modname] = moddict
+    return thedict, dictlist
+
+
+def _info(obj, output=None):
+    """Provide information about ndarray obj.
+
+    Parameters
+    ----------
+    obj : ndarray
+        Must be ndarray, not checked.
+    output
+        Where printed output goes.
+
+    Notes
+    -----
+    Copied over from the numarray module prior to its removal.
+    Adapted somewhat as only numpy is an option now.
+
+    Called by info.
+
+    """
+    extra = ""
+    tic = ""
+    bp = lambda x: x
+    cls = getattr(obj, '__class__', type(obj))
+    nm = getattr(cls, '__name__', cls)
+    strides = obj.strides
+    endian = obj.dtype.byteorder
+
+    if output is None:
+        output = sys.stdout
+
+    print("class: ", nm, file=output)
+    print("shape: ", obj.shape, file=output)
+    print("strides: ", strides, file=output)
+    print("itemsize: ", obj.itemsize, file=output)
+    print("aligned: ", bp(obj.flags.aligned), file=output)
+    print("contiguous: ", bp(obj.flags.contiguous), file=output)
+    print("fortran: ", obj.flags.fortran, file=output)
+    print(
+        f"data pointer: {hex(obj.ctypes._as_parameter_.value)}{extra}",
+        file=output
+        )
+    print("byteorder: ", end=' ', file=output)
+    if endian in ['|', '=']:
+        print(f"{tic}{sys.byteorder}{tic}", file=output)
+        byteswap = False
+    elif endian == '>':
+        print(f"{tic}big{tic}", file=output)
+        byteswap = sys.byteorder != "big"
+    else:
+        print(f"{tic}little{tic}", file=output)
+        byteswap = sys.byteorder != "little"
+    print("byteswap: ", bp(byteswap), file=output)
+    print(f"type: {obj.dtype}", file=output)
+
+
+@set_module('numpy')
+def info(object=None, maxwidth=76, output=None, toplevel='numpy'):
+    """
+    Get help information for an array, function, class, or module.
+
+    Parameters
+    ----------
+    object : object or str, optional
+        Input object or name to get information about. If `object` is
+        an `ndarray` instance, information about the array is printed.
+        If `object` is a numpy object, its docstring is given. If it is
+        a string, available modules are searched for matching objects.
+        If None, information about `info` itself is returned.
+    maxwidth : int, optional
+        Printing width.
+    output : file like object, optional
+        File like object that the output is written to, default is
+        ``None``, in which case ``sys.stdout`` will be used.
+        The object has to be opened in 'w' or 'a' mode.
+    toplevel : str, optional
+        Start search at this level.
+
+    Notes
+    -----
+    When used interactively with an object, ``np.info(obj)`` is equivalent
+    to ``help(obj)`` on the Python prompt or ``obj?`` on the IPython
+    prompt.
+
+    Examples
+    --------
+    >>> np.info(np.polyval) # doctest: +SKIP
+       polyval(p, x)
+         Evaluate the polynomial p at x.
+         ...
+
+    When using a string for `object` it is possible to get multiple results.
+
+    >>> np.info('fft') # doctest: +SKIP
+         *** Found in numpy ***
+    Core FFT routines
+    ...
+         *** Found in numpy.fft ***
+     fft(a, n=None, axis=-1)
+    ...
+         *** Repeat reference found in numpy.fft.fftpack ***
+         *** Total of 3 references found. ***
+
+    When the argument is an array, information about the array is printed.
+
+    >>> a = np.array([[1 + 2j, 3, -4], [-5j, 6, 0]], dtype=np.complex64)
+    >>> np.info(a)
+    class:  ndarray
+    shape:  (2, 3)
+    strides:  (24, 8)
+    itemsize:  8
+    aligned:  True
+    contiguous:  True
+    fortran:  False
+    data pointer: 0x562b6e0d2860  # may vary
+    byteorder:  little
+    byteswap:  False
+    type: complex64
+
+    """
+    global _namedict, _dictlist
+    # Local import to speed up numpy's import time.
+    import inspect
+    import pydoc
+
+    if (hasattr(object, '_ppimport_importer') or
+           hasattr(object, '_ppimport_module')):
+        object = object._ppimport_module
+    elif hasattr(object, '_ppimport_attr'):
+        object = object._ppimport_attr
+
+    if output is None:
+        output = sys.stdout
+
+    if object is None:
+        info(info)
+    elif isinstance(object, ndarray):
+        _info(object, output=output)
+    elif isinstance(object, str):
+        if _namedict is None:
+            _namedict, _dictlist = _makenamedict(toplevel)
+        numfound = 0
+        objlist = []
+        for namestr in _dictlist:
+            try:
+                obj = _namedict[namestr][object]
+                if id(obj) in objlist:
+                    print(f"\n     *** Repeat reference found in {namestr} *** ",
+                          file=output
+                          )
+                else:
+                    objlist.append(id(obj))
+                    print(f"     *** Found in {namestr} ***", file=output)
+                    info(obj)
+                    print("-" * maxwidth, file=output)
+                numfound += 1
+            except KeyError:
+                pass
+        if numfound == 0:
+            print(f"Help for {object} not found.", file=output)
+        else:
+            print("\n     "
+                  "*** Total of %d references found. ***" % numfound,
+                  file=output
+                  )
+
+    elif inspect.isfunction(object) or inspect.ismethod(object):
+        name = object.__name__
+        try:
+            arguments = str(inspect.signature(object))
+        except Exception:
+            arguments = "()"
+
+        if len(name + arguments) > maxwidth:
+            argstr = _split_line(name, arguments, maxwidth)
+        else:
+            argstr = name + arguments
+
+        print(" " + argstr + "\n", file=output)
+        print(inspect.getdoc(object), file=output)
+
+    elif inspect.isclass(object):
+        name = object.__name__
+        try:
+            arguments = str(inspect.signature(object))
+        except Exception:
+            arguments = "()"
+
+        if len(name + arguments) > maxwidth:
+            argstr = _split_line(name, arguments, maxwidth)
+        else:
+            argstr = name + arguments
+
+        print(" " + argstr + "\n", file=output)
+        doc1 = inspect.getdoc(object)
+        if doc1 is None:
+            if hasattr(object, '__init__'):
+                print(inspect.getdoc(object.__init__), file=output)
+        else:
+            print(inspect.getdoc(object), file=output)
+
+        methods = pydoc.allmethods(object)
+
+        public_methods = [meth for meth in methods if meth[0] != '_']
+        if public_methods:
+            print("\n\nMethods:\n", file=output)
+            for meth in public_methods:
+                thisobj = getattr(object, meth, None)
+                if thisobj is not None:
+                    methstr, other = pydoc.splitdoc(
+                            inspect.getdoc(thisobj) or "None"
+                            )
+                print(f"  {meth}  --  {methstr}", file=output)
+
+    elif hasattr(object, '__doc__'):
+        print(inspect.getdoc(object), file=output)
+
+
+def safe_eval(source):
+    """
+    Protected string evaluation.
+
+    .. deprecated:: 2.0
+        Use `ast.literal_eval` instead.
+
+    Evaluate a string containing a Python literal expression without
+    allowing the execution of arbitrary non-literal code.
+
+    .. warning::
+
+        This function is identical to :py:meth:`ast.literal_eval` and
+        has the same security implications.  It may not always be safe
+        to evaluate large input strings.
+
+    Parameters
+    ----------
+    source : str
+        The string to evaluate.
+
+    Returns
+    -------
+    obj : object
+       The result of evaluating `source`.
+
+    Raises
+    ------
+    SyntaxError
+        If the code has invalid Python syntax, or if it contains
+        non-literal code.
+
+    Examples
+    --------
+    >>> np.safe_eval('1')
+    1
+    >>> np.safe_eval('[1, 2, 3]')
+    [1, 2, 3]
+    >>> np.safe_eval('{"foo": ("bar", 10.0)}')
+    {'foo': ('bar', 10.0)}
+
+    >>> np.safe_eval('import os')
+    Traceback (most recent call last):
+      ...
+    SyntaxError: invalid syntax
+
+    >>> np.safe_eval('open("/home/user/.ssh/id_dsa").read()')
+    Traceback (most recent call last):
+      ...
+    ValueError: malformed node or string: <_ast.Call object at 0x...>
+
+    """
+
+    # Deprecated in NumPy 2.0, 2023-07-11
+    warnings.warn(
+        "`safe_eval` is deprecated. Use `ast.literal_eval` instead. "
+        "Be aware of security implications, such as memory exhaustion "
+        "based attacks (deprecated in NumPy 2.0)",
+        DeprecationWarning,
+        stacklevel=2
+    )
+
+    # Local import to speed up numpy's import time.
+    import ast
+    return ast.literal_eval(source)
+
+
+def _median_nancheck(data, result, axis):
+    """
+    Utility function to check median result from data for NaN values at the end
+    and return NaN in that case. Input result can also be a MaskedArray.
+
+    Parameters
+    ----------
+    data : array
+        Sorted input data to median function
+    result : Array or MaskedArray
+        Result of median function.
+    axis : int
+        Axis along which the median was computed.
+
+    Returns
+    -------
+    result : scalar or ndarray
+        Median or NaN in axes which contained NaN in the input.  If the input
+        was an array, NaN will be inserted in-place.  If a scalar, either the
+        input itself or a scalar NaN.
+    """
+    if data.size == 0:
+        return result
+    potential_nans = data.take(-1, axis=axis)
+    n = np.isnan(potential_nans)
+    # masked NaN values are ok, although for masked the copyto may fail for
+    # unmasked ones (this was always broken) when the result is a scalar.
+    if np.ma.isMaskedArray(n):
+        n = n.filled(False)
+
+    if not n.any():
+        return result
+
+    # Without given output, it is possible that the current result is a
+    # numpy scalar, which is not writeable.  If so, just return nan.
+    if isinstance(result, np.generic):
+        return potential_nans
+
+    # Otherwise copy NaNs (if there are any)
+    np.copyto(result, potential_nans, where=n)
+    return result
+
+def _opt_info():
+    """
+    Returns a string containing the CPU features supported
+    by the current build.
+
+    The format of the string can be explained as follows:
+        - Dispatched features supported by the running machine end with `*`.
+        - Dispatched features not supported by the running machine
+          end with `?`.
+        - Remaining features represent the baseline.
+
+    Returns:
+        str: A formatted string indicating the supported CPU features.
+    """
+    from numpy._core._multiarray_umath import (
+        __cpu_baseline__,
+        __cpu_dispatch__,
+        __cpu_features__,
+    )
+
+    if len(__cpu_baseline__) == 0 and len(__cpu_dispatch__) == 0:
+        return ''
+
+    enabled_features = ' '.join(__cpu_baseline__)
+    for feature in __cpu_dispatch__:
+        if __cpu_features__[feature]:
+            enabled_features += f" {feature}*"
+        else:
+            enabled_features += f" {feature}?"
+
+    return enabled_features
+
+def drop_metadata(dtype, /):
+    """
+    Returns the dtype unchanged if it contained no metadata or a copy of the
+    dtype if it (or any of its structure dtypes) contained metadata.
+
+    This utility is used by `np.save` and `np.savez` to drop metadata before
+    saving.
+
+    .. note::
+
+        Due to its limitation this function may move to a more appropriate
+        home or change in the future and is considered semi-public API only.
+
+    .. warning::
+
+        This function does not preserve more strange things like record dtypes
+        and user dtypes may simply return the wrong thing.  If you need to be
+        sure about the latter, check the result with:
+        ``np.can_cast(new_dtype, dtype, casting="no")``.
+
+    """
+    if dtype.fields is not None:
+        found_metadata = dtype.metadata is not None
+
+        names = []
+        formats = []
+        offsets = []
+        titles = []
+        for name, field in dtype.fields.items():
+            field_dt = drop_metadata(field[0])
+            if field_dt is not field[0]:
+                found_metadata = True
+
+            names.append(name)
+            formats.append(field_dt)
+            offsets.append(field[1])
+            titles.append(None if len(field) < 3 else field[2])
+
+        if not found_metadata:
+            return dtype
+
+        structure = {
+            'names': names, 'formats': formats, 'offsets': offsets, 'titles': titles,
+            'itemsize': dtype.itemsize}
+
+        # NOTE: Could pass (dtype.type, structure) to preserve record dtypes...
+        return np.dtype(structure, align=dtype.isalignedstruct)
+    elif dtype.subdtype is not None:
+        # subarray dtype
+        subdtype, shape = dtype.subdtype
+        new_subdtype = drop_metadata(subdtype)
+        if dtype.metadata is None and new_subdtype is subdtype:
+            return dtype
+
+        return np.dtype((new_subdtype, shape))
+    else:
+        # Normal unstructured dtype
+        if dtype.metadata is None:
+            return dtype
+        # Note that `dt.str` doesn't round-trip e.g. for user-dtypes.
+        return np.dtype(dtype.str)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..985237718961dd7abecef593f95fad806ce7983c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_utils_impl.pyi
@@ -0,0 +1,22 @@
+from _typeshed import SupportsWrite
+from typing import LiteralString
+from typing_extensions import TypeVar
+
+import numpy as np
+
+__all__ = ["get_include", "info", "show_runtime"]
+
+_ScalarOrArrayT = TypeVar("_ScalarOrArrayT", bound=np.generic | np.ndarray)
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype)
+
+###
+
+def get_include() -> LiteralString: ...
+def show_runtime() -> None: ...
+def info(
+    object: object = None, maxwidth: int = 76, output: SupportsWrite[str] | None = None, toplevel: str = "numpy"
+) -> None: ...
+def drop_metadata(dtype: _DTypeT, /) -> _DTypeT: ...
+
+# used internally by `lib._function_base_impl._median`
+def _median_nancheck(data: np.ndarray, result: _ScalarOrArrayT, axis: int) -> _ScalarOrArrayT: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_version.py b/python/user_packages/Python313/site-packages/numpy/lib/_version.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8b2eb3b600f5b17b702c81e3f3dd1d39abad69a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_version.py
@@ -0,0 +1,153 @@
+"""Utility to compare (NumPy) version strings.
+
+The NumpyVersion class allows properly comparing numpy version strings.
+The LooseVersion and StrictVersion classes that distutils provides don't
+work; they don't recognize anything like alpha/beta/rc/dev versions.
+
+"""
+import re
+
+__all__ = ['NumpyVersion']
+
+
+class NumpyVersion:
+    """Parse and compare numpy version strings.
+
+    NumPy has the following versioning scheme (numbers given are examples; they
+    can be > 9 in principle):
+
+    - Released version: '1.8.0', '1.8.1', etc.
+    - Alpha: '1.8.0a1', '1.8.0a2', etc.
+    - Beta: '1.8.0b1', '1.8.0b2', etc.
+    - Release candidates: '1.8.0rc1', '1.8.0rc2', etc.
+    - Development versions: '1.8.0.dev-f1234afa' (git commit hash appended)
+    - Development versions after a1: '1.8.0a1.dev-f1234afa',
+      '1.8.0b2.dev-f1234afa', '1.8.1rc1.dev-f1234afa', etc.
+    - Development versions (no git hash available): '1.8.0.dev-Unknown'
+
+    Comparing needs to be done against a valid version string or other
+    `NumpyVersion` instance. Note that all development versions of the same
+    (pre-)release compare equal.
+
+    Parameters
+    ----------
+    vstring : str
+        NumPy version string (``np.__version__``).
+
+    Examples
+    --------
+    >>> from numpy.lib import NumpyVersion
+    >>> if NumpyVersion(np.__version__) < '1.7.0':
+    ...     print('skip')
+    >>> # skip
+
+    >>> NumpyVersion('1.7')  # raises ValueError, add ".0"
+    Traceback (most recent call last):
+        ...
+    ValueError: Not a valid numpy version string
+
+    """
+
+    __module__ = "numpy.lib"
+
+    def __init__(self, vstring):
+        self.vstring = vstring
+        ver_main = re.match(r'\d+\.\d+\.\d+', vstring)
+        if not ver_main:
+            raise ValueError("Not a valid numpy version string")
+
+        self.version = ver_main.group()
+        self.major, self.minor, self.bugfix = [int(x) for x in
+            self.version.split('.')]
+        if len(vstring) == ver_main.end():
+            self.pre_release = 'final'
+        else:
+            alpha = re.match(r'a\d', vstring[ver_main.end():])
+            beta = re.match(r'b\d', vstring[ver_main.end():])
+            rc = re.match(r'rc\d', vstring[ver_main.end():])
+            pre_rel = [m for m in [alpha, beta, rc] if m is not None]
+            if pre_rel:
+                self.pre_release = pre_rel[0].group()
+            else:
+                self.pre_release = ''
+
+        self.is_devversion = bool(re.search(r'.dev', vstring))
+
+    def _compare_version(self, other):
+        """Compare major.minor.bugfix"""
+        if self.major == other.major:
+            if self.minor == other.minor:
+                if self.bugfix == other.bugfix:
+                    vercmp = 0
+                elif self.bugfix > other.bugfix:
+                    vercmp = 1
+                else:
+                    vercmp = -1
+            elif self.minor > other.minor:
+                vercmp = 1
+            else:
+                vercmp = -1
+        elif self.major > other.major:
+            vercmp = 1
+        else:
+            vercmp = -1
+
+        return vercmp
+
+    def _compare_pre_release(self, other):
+        """Compare alpha/beta/rc/final."""
+        if self.pre_release == other.pre_release:
+            vercmp = 0
+        elif self.pre_release == 'final':
+            vercmp = 1
+        elif other.pre_release == 'final':
+            vercmp = -1
+        elif self.pre_release > other.pre_release:
+            vercmp = 1
+        else:
+            vercmp = -1
+
+        return vercmp
+
+    def _compare(self, other):
+        if not isinstance(other, (str, NumpyVersion)):
+            raise ValueError("Invalid object to compare with NumpyVersion.")
+
+        if isinstance(other, str):
+            other = NumpyVersion(other)
+
+        vercmp = self._compare_version(other)
+        if vercmp == 0:
+            # Same x.y.z version, check for alpha/beta/rc
+            vercmp = self._compare_pre_release(other)
+            if vercmp == 0:
+                # Same version and same pre-release, check if dev version
+                if self.is_devversion is other.is_devversion:
+                    vercmp = 0
+                elif self.is_devversion:
+                    vercmp = -1
+                else:
+                    vercmp = 1
+
+        return vercmp
+
+    def __lt__(self, other):
+        return self._compare(other) < 0
+
+    def __le__(self, other):
+        return self._compare(other) <= 0
+
+    def __eq__(self, other):
+        return self._compare(other) == 0
+
+    def __ne__(self, other):
+        return self._compare(other) != 0
+
+    def __gt__(self, other):
+        return self._compare(other) > 0
+
+    def __ge__(self, other):
+        return self._compare(other) >= 0
+
+    def __repr__(self):
+        return f"NumpyVersion({self.vstring})"
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/_version.pyi b/python/user_packages/Python313/site-packages/numpy/lib/_version.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..4e30cf332a868efaf70993f58b7d0f82b5154d7d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/_version.pyi
@@ -0,0 +1,17 @@
+__all__ = ["NumpyVersion"]
+
+class NumpyVersion:
+    vstring: str
+    version: str
+    major: int
+    minor: int
+    bugfix: int
+    pre_release: str
+    is_devversion: bool
+    def __init__(self, vstring: str) -> None: ...
+    def __lt__(self, other: str | NumpyVersion) -> bool: ...
+    def __le__(self, other: str | NumpyVersion) -> bool: ...
+    def __eq__(self, other: str | NumpyVersion) -> bool: ...  # type: ignore[override]
+    def __ne__(self, other: str | NumpyVersion) -> bool: ...  # type: ignore[override]
+    def __gt__(self, other: str | NumpyVersion) -> bool: ...
+    def __ge__(self, other: str | NumpyVersion) -> bool: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/array_utils.py b/python/user_packages/Python313/site-packages/numpy/lib/array_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..19866b8734a395c691510d7a10bc964ec2959741
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/array_utils.py
@@ -0,0 +1,7 @@
+from ._array_utils_impl import (  # noqa: F401
+    __all__,
+    __doc__,
+    byte_bounds,
+    normalize_axis_index,
+    normalize_axis_tuple,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/array_utils.pyi b/python/user_packages/Python313/site-packages/numpy/lib/array_utils.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..231398e0035145a72010d1dc724f931c86f8d047
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/array_utils.pyi
@@ -0,0 +1,6 @@
+from ._array_utils_impl import (
+    __all__ as __all__,
+    byte_bounds as byte_bounds,
+    normalize_axis_index as normalize_axis_index,
+    normalize_axis_tuple as normalize_axis_tuple,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/format.py b/python/user_packages/Python313/site-packages/numpy/lib/format.py
new file mode 100644
index 0000000000000000000000000000000000000000..d69d1f8a4ea73afd20440baff186101957c73d8c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/format.py
@@ -0,0 +1,24 @@
+from ._format_impl import (  # noqa: F401
+    ARRAY_ALIGN,
+    BUFFER_SIZE,
+    EXPECTED_KEYS,
+    GROWTH_AXIS_MAX_DIGITS,
+    MAGIC_LEN,
+    MAGIC_PREFIX,
+    __all__,
+    __doc__,
+    descr_to_dtype,
+    drop_metadata,
+    dtype_to_descr,
+    header_data_from_array_1_0,
+    isfileobj,
+    magic,
+    open_memmap,
+    read_array,
+    read_array_header_1_0,
+    read_array_header_2_0,
+    read_magic,
+    write_array,
+    write_array_header_1_0,
+    write_array_header_2_0,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/format.pyi b/python/user_packages/Python313/site-packages/numpy/lib/format.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..d218b27dc119e3e873f06d088c57a2ea7485c4f5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/format.pyi
@@ -0,0 +1,24 @@
+from ._format_impl import (
+    ARRAY_ALIGN as ARRAY_ALIGN,
+    BUFFER_SIZE as BUFFER_SIZE,
+    EXPECTED_KEYS as EXPECTED_KEYS,
+    GROWTH_AXIS_MAX_DIGITS as GROWTH_AXIS_MAX_DIGITS,
+    MAGIC_LEN as MAGIC_LEN,
+    MAGIC_PREFIX as MAGIC_PREFIX,
+    __all__ as __all__,
+    __doc__ as __doc__,
+    descr_to_dtype as descr_to_dtype,
+    drop_metadata as drop_metadata,
+    dtype_to_descr as dtype_to_descr,
+    header_data_from_array_1_0 as header_data_from_array_1_0,
+    isfileobj as isfileobj,
+    magic as magic,
+    open_memmap as open_memmap,
+    read_array as read_array,
+    read_array_header_1_0 as read_array_header_1_0,
+    read_array_header_2_0 as read_array_header_2_0,
+    read_magic as read_magic,
+    write_array as write_array,
+    write_array_header_1_0 as write_array_header_1_0,
+    write_array_header_2_0 as write_array_header_2_0,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/introspect.py b/python/user_packages/Python313/site-packages/numpy/lib/introspect.py
new file mode 100644
index 0000000000000000000000000000000000000000..4fd58590370de1fad35a893b3533863c8b3d13af
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/introspect.py
@@ -0,0 +1,94 @@
+"""
+Introspection helper functions.
+"""
+
+__all__ = ['opt_func_info']
+
+
+def opt_func_info(func_name=None, signature=None):
+    """
+    Returns a dictionary containing the currently supported CPU dispatched
+    features for all optimized functions.
+
+    Parameters
+    ----------
+    func_name : str (optional)
+        Regular expression to filter by function name.
+
+    signature : str (optional)
+        Regular expression to filter by data type.
+
+    Returns
+    -------
+    dict
+        A dictionary where keys are optimized function names and values are
+        nested dictionaries indicating supported targets based on data types.
+
+    Examples
+    --------
+    Retrieve dispatch information for functions named 'add' or 'sub' and
+    data types 'float64' or 'float32':
+
+    >>> import numpy as np
+    >>> dict = np.lib.introspect.opt_func_info(
+    ...     func_name="add|abs", signature="float64|complex64"
+    ... )
+    >>> import json
+    >>> print(json.dumps(dict, indent=2))   # may vary (architecture)
+        {
+          "absolute": {
+            "dd": {
+              "current": "SSE41",
+              "available": "SSE41 baseline(SSE SSE2 SSE3)"
+            },
+            "Ff": {
+              "current": "FMA3__AVX2",
+              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
+            },
+            "Dd": {
+              "current": "FMA3__AVX2",
+              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"
+            }
+          },
+          "add": {
+            "ddd": {
+              "current": "FMA3__AVX2",
+              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
+            },
+            "FFF": {
+              "current": "FMA3__AVX2",
+              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"
+            }
+          }
+        }
+
+    """
+    import re
+
+    from numpy._core._multiarray_umath import __cpu_targets_info__ as targets, dtype
+
+    if func_name is not None:
+        func_pattern = re.compile(func_name)
+        matching_funcs = {
+            k: v for k, v in targets.items()
+            if func_pattern.search(k)
+        }
+    else:
+        matching_funcs = targets
+
+    if signature is not None:
+        sig_pattern = re.compile(signature)
+        matching_sigs = {}
+        for k, v in matching_funcs.items():
+            matching_chars = {}
+            for chars, targets in v.items():
+                if any(
+                    sig_pattern.search(c) or sig_pattern.search(dtype(c).name)
+                    for c in chars
+                ):
+                    matching_chars[chars] = targets  # noqa: PERF403
+            if matching_chars:
+                matching_sigs[k] = matching_chars
+    else:
+        matching_sigs = matching_funcs
+    return matching_sigs
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/introspect.pyi b/python/user_packages/Python313/site-packages/numpy/lib/introspect.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..52c3fbb3940447f911594fa2f834fa3a63e053cb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/introspect.pyi
@@ -0,0 +1,3 @@
+__all__ = ["opt_func_info"]
+
+def opt_func_info(func_name: str | None = None, signature: str | None = None) -> dict[str, dict[str, dict[str, str]]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/mixins.py b/python/user_packages/Python313/site-packages/numpy/lib/mixins.py
new file mode 100644
index 0000000000000000000000000000000000000000..830a617f275dbb9cf4bcec0c8f5167acd751ecad
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/mixins.py
@@ -0,0 +1,180 @@
+"""
+Mixin classes for custom array types that don't inherit from ndarray.
+"""
+from numpy._core import umath as um
+
+__all__ = ['NDArrayOperatorsMixin']
+
+
+def _disables_array_ufunc(obj):
+    """True when __array_ufunc__ is set to None."""
+    try:
+        return obj.__array_ufunc__ is None
+    except AttributeError:
+        return False
+
+
+def _binary_method(ufunc, name):
+    """Implement a forward binary method with a ufunc, e.g., __add__."""
+    def func(self, other):
+        if _disables_array_ufunc(other):
+            return NotImplemented
+        return ufunc(self, other)
+    func.__name__ = f'__{name}__'
+    return func
+
+
+def _reflected_binary_method(ufunc, name):
+    """Implement a reflected binary method with a ufunc, e.g., __radd__."""
+    def func(self, other):
+        if _disables_array_ufunc(other):
+            return NotImplemented
+        return ufunc(other, self)
+    func.__name__ = f'__r{name}__'
+    return func
+
+
+def _inplace_binary_method(ufunc, name):
+    """Implement an in-place binary method with a ufunc, e.g., __iadd__."""
+    def func(self, other):
+        return ufunc(self, other, out=(self,))
+    func.__name__ = f'__i{name}__'
+    return func
+
+
+def _numeric_methods(ufunc, name):
+    """Implement forward, reflected and inplace binary methods with a ufunc."""
+    return (_binary_method(ufunc, name),
+            _reflected_binary_method(ufunc, name),
+            _inplace_binary_method(ufunc, name))
+
+
+def _unary_method(ufunc, name):
+    """Implement a unary special method with a ufunc."""
+    def func(self):
+        return ufunc(self)
+    func.__name__ = f'__{name}__'
+    return func
+
+
+class NDArrayOperatorsMixin:
+    """Mixin defining all operator special methods using __array_ufunc__.
+
+    This class implements the special methods for almost all of Python's
+    builtin operators defined in the `operator` module, including comparisons
+    (``==``, ``>``, etc.) and arithmetic (``+``, ``*``, ``-``, etc.), by
+    deferring to the ``__array_ufunc__`` method, which subclasses must
+    implement.
+
+    It is useful for writing classes that do not inherit from `numpy.ndarray`,
+    but that should support arithmetic and numpy universal functions like
+    arrays as described in :external+neps:doc:`nep-0013-ufunc-overrides`.
+
+    As a trivial example, consider this implementation of an ``ArrayLike``
+    class that simply wraps a NumPy array and ensures that the result of any
+    arithmetic operation is also an ``ArrayLike`` object:
+
+        >>> import numbers
+        >>> class ArrayLike(np.lib.mixins.NDArrayOperatorsMixin):
+        ...     def __init__(self, value):
+        ...         self.value = np.asarray(value)
+        ...
+        ...     # One might also consider adding the built-in list type to this
+        ...     # list, to support operations like np.add(array_like, list)
+        ...     _HANDLED_TYPES = (np.ndarray, numbers.Number)
+        ...
+        ...     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
+        ...         out = kwargs.get('out', ())
+        ...         for x in inputs + out:
+        ...             # Only support operations with instances of
+        ...             # _HANDLED_TYPES. Use ArrayLike instead of type(self)
+        ...             # for isinstance to allow subclasses that don't
+        ...             # override __array_ufunc__ to handle ArrayLike objects.
+        ...             if not isinstance(
+        ...                 x, self._HANDLED_TYPES + (ArrayLike,)
+        ...             ):
+        ...                 return NotImplemented
+        ...
+        ...         # Defer to the implementation of the ufunc
+        ...         # on unwrapped values.
+        ...         inputs = tuple(x.value if isinstance(x, ArrayLike) else x
+        ...                     for x in inputs)
+        ...         if out:
+        ...             kwargs['out'] = tuple(
+        ...                 x.value if isinstance(x, ArrayLike) else x
+        ...                 for x in out)
+        ...         result = getattr(ufunc, method)(*inputs, **kwargs)
+        ...
+        ...         if type(result) is tuple:
+        ...             # multiple return values
+        ...             return tuple(type(self)(x) for x in result)
+        ...         elif method == 'at':
+        ...             # no return value
+        ...             return None
+        ...         else:
+        ...             # one return value
+        ...             return type(self)(result)
+        ...
+        ...     def __repr__(self):
+        ...         return '%s(%r)' % (type(self).__name__, self.value)
+
+    In interactions between ``ArrayLike`` objects and numbers or numpy arrays,
+    the result is always another ``ArrayLike``:
+
+        >>> x = ArrayLike([1, 2, 3])
+        >>> x - 1
+        ArrayLike(array([0, 1, 2]))
+        >>> 1 - x
+        ArrayLike(array([ 0, -1, -2]))
+        >>> np.arange(3) - x
+        ArrayLike(array([-1, -1, -1]))
+        >>> x - np.arange(3)
+        ArrayLike(array([1, 1, 1]))
+
+    Note that unlike ``numpy.ndarray``, ``ArrayLike`` does not allow operations
+    with arbitrary, unrecognized types. This ensures that interactions with
+    ArrayLike preserve a well-defined casting hierarchy.
+
+    """
+
+    __slots__ = ()
+    # Like np.ndarray, this mixin class implements "Option 1" from the ufunc
+    # overrides NEP.
+
+    # comparisons don't have reflected and in-place versions
+    __lt__ = _binary_method(um.less, 'lt')
+    __le__ = _binary_method(um.less_equal, 'le')
+    __eq__ = _binary_method(um.equal, 'eq')
+    __ne__ = _binary_method(um.not_equal, 'ne')
+    __gt__ = _binary_method(um.greater, 'gt')
+    __ge__ = _binary_method(um.greater_equal, 'ge')
+
+    # numeric methods
+    __add__, __radd__, __iadd__ = _numeric_methods(um.add, 'add')
+    __sub__, __rsub__, __isub__ = _numeric_methods(um.subtract, 'sub')
+    __mul__, __rmul__, __imul__ = _numeric_methods(um.multiply, 'mul')
+    __matmul__, __rmatmul__, __imatmul__ = _numeric_methods(
+        um.matmul, 'matmul')
+    __truediv__, __rtruediv__, __itruediv__ = _numeric_methods(
+        um.true_divide, 'truediv')
+    __floordiv__, __rfloordiv__, __ifloordiv__ = _numeric_methods(
+        um.floor_divide, 'floordiv')
+    __mod__, __rmod__, __imod__ = _numeric_methods(um.remainder, 'mod')
+    __divmod__ = _binary_method(um.divmod, 'divmod')
+    __rdivmod__ = _reflected_binary_method(um.divmod, 'divmod')
+    # __idivmod__ does not exist
+    # TODO: handle the optional third argument for __pow__?
+    __pow__, __rpow__, __ipow__ = _numeric_methods(um.power, 'pow')
+    __lshift__, __rlshift__, __ilshift__ = _numeric_methods(
+        um.left_shift, 'lshift')
+    __rshift__, __rrshift__, __irshift__ = _numeric_methods(
+        um.right_shift, 'rshift')
+    __and__, __rand__, __iand__ = _numeric_methods(um.bitwise_and, 'and')
+    __xor__, __rxor__, __ixor__ = _numeric_methods(um.bitwise_xor, 'xor')
+    __or__, __ror__, __ior__ = _numeric_methods(um.bitwise_or, 'or')
+
+    # unary methods
+    __neg__ = _unary_method(um.negative, 'neg')
+    __pos__ = _unary_method(um.positive, 'pos')
+    __abs__ = _unary_method(um.absolute, 'abs')
+    __invert__ = _unary_method(um.invert, 'invert')
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/mixins.pyi b/python/user_packages/Python313/site-packages/numpy/lib/mixins.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..6facb24c570c1f94af20ad926afdfee6ccc7c3d5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/mixins.pyi
@@ -0,0 +1,78 @@
+from abc import ABC, abstractmethod
+from typing import Any, Literal as L, type_check_only
+
+from numpy import ufunc
+
+__all__ = ["NDArrayOperatorsMixin"]
+
+# NOTE: `NDArrayOperatorsMixin` is not formally an abstract baseclass,
+# even though it's reliant on subclasses implementing `__array_ufunc__`
+
+# NOTE: The accepted input- and output-types of the various dunders are
+# completely dependent on how `__array_ufunc__` is implemented.
+# As such, only little type safety can be provided here.
+
+class NDArrayOperatorsMixin(ABC):
+    __slots__ = ()
+
+    @type_check_only
+    @abstractmethod
+    def __array_ufunc__(
+        self,
+        ufunc: ufunc,
+        method: L["__call__", "reduce", "reduceat", "accumulate", "outer", "at"],
+        /,
+        *inputs: Any,
+        **kwargs: Any,
+    ) -> Any: ...
+    def __lt__(self, other: Any) -> Any: ...
+    def __le__(self, other: Any) -> Any: ...
+    def __eq__(self, other: Any) -> Any: ...
+    def __ne__(self, other: Any) -> Any: ...
+    def __gt__(self, other: Any) -> Any: ...
+    def __ge__(self, other: Any) -> Any: ...
+    def __add__(self, other: Any) -> Any: ...
+    def __radd__(self, other: Any) -> Any: ...
+    def __iadd__(self, other: Any) -> Any: ...
+    def __sub__(self, other: Any) -> Any: ...
+    def __rsub__(self, other: Any) -> Any: ...
+    def __isub__(self, other: Any) -> Any: ...
+    def __mul__(self, other: Any) -> Any: ...
+    def __rmul__(self, other: Any) -> Any: ...
+    def __imul__(self, other: Any) -> Any: ...
+    def __matmul__(self, other: Any) -> Any: ...
+    def __rmatmul__(self, other: Any) -> Any: ...
+    def __imatmul__(self, other: Any) -> Any: ...
+    def __truediv__(self, other: Any) -> Any: ...
+    def __rtruediv__(self, other: Any) -> Any: ...
+    def __itruediv__(self, other: Any) -> Any: ...
+    def __floordiv__(self, other: Any) -> Any: ...
+    def __rfloordiv__(self, other: Any) -> Any: ...
+    def __ifloordiv__(self, other: Any) -> Any: ...
+    def __mod__(self, other: Any) -> Any: ...
+    def __rmod__(self, other: Any) -> Any: ...
+    def __imod__(self, other: Any) -> Any: ...
+    def __divmod__(self, other: Any) -> Any: ...
+    def __rdivmod__(self, other: Any) -> Any: ...
+    def __pow__(self, other: Any) -> Any: ...
+    def __rpow__(self, other: Any) -> Any: ...
+    def __ipow__(self, other: Any) -> Any: ...
+    def __lshift__(self, other: Any) -> Any: ...
+    def __rlshift__(self, other: Any) -> Any: ...
+    def __ilshift__(self, other: Any) -> Any: ...
+    def __rshift__(self, other: Any) -> Any: ...
+    def __rrshift__(self, other: Any) -> Any: ...
+    def __irshift__(self, other: Any) -> Any: ...
+    def __and__(self, other: Any) -> Any: ...
+    def __rand__(self, other: Any) -> Any: ...
+    def __iand__(self, other: Any) -> Any: ...
+    def __xor__(self, other: Any) -> Any: ...
+    def __rxor__(self, other: Any) -> Any: ...
+    def __ixor__(self, other: Any) -> Any: ...
+    def __or__(self, other: Any) -> Any: ...
+    def __ror__(self, other: Any) -> Any: ...
+    def __ior__(self, other: Any) -> Any: ...
+    def __neg__(self) -> Any: ...
+    def __pos__(self) -> Any: ...
+    def __abs__(self) -> Any: ...
+    def __invert__(self) -> Any: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/npyio.py b/python/user_packages/Python313/site-packages/numpy/lib/npyio.py
new file mode 100644
index 0000000000000000000000000000000000000000..6c36a6f07e5d813b212a05ea6ed2e24a16ac892e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/npyio.py
@@ -0,0 +1 @@
+from ._npyio_impl import DataSource, NpzFile, __doc__  # noqa: F401
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/npyio.pyi b/python/user_packages/Python313/site-packages/numpy/lib/npyio.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..218664db23d9ccbc110585d57465f55d28cd297c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/npyio.pyi
@@ -0,0 +1,5 @@
+from numpy.lib._npyio_impl import (
+    DataSource as DataSource,
+    NpzFile as NpzFile,
+    __doc__ as __doc__,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.py b/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.py
new file mode 100644
index 0000000000000000000000000000000000000000..933468e11eb906eeed54c6b4f64269ed32336a9b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.py
@@ -0,0 +1,1681 @@
+"""
+Collection of utilities to manipulate structured arrays.
+
+Most of these functions were initially implemented by John Hunter for
+matplotlib.  They have been rewritten and extended for convenience.
+
+"""
+import itertools
+
+import numpy as np
+import numpy.ma as ma
+import numpy.ma.mrecords as mrec
+from numpy._core.overrides import array_function_dispatch
+from numpy.lib._iotools import _is_string_like
+
+__all__ = [
+    'append_fields', 'apply_along_fields', 'assign_fields_by_name',
+    'drop_fields', 'find_duplicates', 'flatten_descr',
+    'get_fieldstructure', 'get_names', 'get_names_flat',
+    'join_by', 'merge_arrays', 'rec_append_fields',
+    'rec_drop_fields', 'rec_join', 'recursive_fill_fields',
+    'rename_fields', 'repack_fields', 'require_fields',
+    'stack_arrays', 'structured_to_unstructured', 'unstructured_to_structured',
+    ]
+
+
+def _recursive_fill_fields_dispatcher(input, output):
+    return (input, output)
+
+
+@array_function_dispatch(_recursive_fill_fields_dispatcher)
+def recursive_fill_fields(input, output):
+    """
+    Fills fields from output with fields from input,
+    with support for nested structures.
+
+    Parameters
+    ----------
+    input : ndarray
+        Input array.
+    output : ndarray
+        Output array.
+
+    Notes
+    -----
+    * `output` should be at least the same size as `input`
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> a = np.array([(1, 10.), (2, 20.)], dtype=[('A', np.int64), ('B', np.float64)])
+    >>> b = np.zeros((3,), dtype=a.dtype)
+    >>> rfn.recursive_fill_fields(a, b)
+    array([(1, 10.), (2, 20.), (0,  0.)], dtype=[('A', '<i8'), ('B', '<f8')])
+
+    """
+    newdtype = output.dtype
+    for field in newdtype.names:
+        try:
+            current = input[field]
+        except ValueError:
+            continue
+        if current.dtype.names is not None:
+            recursive_fill_fields(current, output[field])
+        else:
+            output[field][:len(current)] = current
+    return output
+
+
+def _get_fieldspec(dtype):
+    """
+    Produce a list of name/dtype pairs corresponding to the dtype fields
+
+    Similar to dtype.descr, but the second item of each tuple is a dtype, not a
+    string. As a result, this handles subarray dtypes
+
+    Can be passed to the dtype constructor to reconstruct the dtype, noting that
+    this (deliberately) discards field offsets.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> dt = np.dtype([(('a', 'A'), np.int64), ('b', np.double, 3)])
+    >>> dt.descr
+    [(('a', 'A'), '<i8'), ('b', '<f8', (3,))]
+    >>> _get_fieldspec(dt)
+    [(('a', 'A'), dtype('int64')), ('b', dtype(('<f8', (3,))))]
+
+    """
+    if dtype.names is None:
+        # .descr returns a nameless field, so we should too
+        return [('', dtype)]
+    else:
+        fields = ((name, dtype.fields[name]) for name in dtype.names)
+        # keep any titles, if present
+        return [
+            (name if len(f) == 2 else (f[2], name), f[0])
+            for name, f in fields
+        ]
+
+
+def get_names(adtype):
+    """
+    Returns the field names of the input datatype as a tuple. Input datatype
+    must have fields otherwise error is raised.
+
+    Parameters
+    ----------
+    adtype : dtype
+        Input datatype
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.get_names(np.empty((1,), dtype=[('A', int)]).dtype)
+    ('A',)
+    >>> rfn.get_names(np.empty((1,), dtype=[('A',int), ('B', float)]).dtype)
+    ('A', 'B')
+    >>> adtype = np.dtype([('a', int), ('b', [('ba', int), ('bb', int)])])
+    >>> rfn.get_names(adtype)
+    ('a', ('b', ('ba', 'bb')))
+    """
+    listnames = []
+    names = adtype.names
+    for name in names:
+        current = adtype[name]
+        if current.names is not None:
+            listnames.append((name, tuple(get_names(current))))
+        else:
+            listnames.append(name)
+    return tuple(listnames)
+
+
+def get_names_flat(adtype):
+    """
+    Returns the field names of the input datatype as a tuple. Input datatype
+    must have fields otherwise error is raised.
+    Nested structure are flattened beforehand.
+
+    Parameters
+    ----------
+    adtype : dtype
+        Input datatype
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.get_names_flat(np.empty((1,), dtype=[('A', int)]).dtype) is None
+    False
+    >>> rfn.get_names_flat(np.empty((1,), dtype=[('A',int), ('B', str)]).dtype)
+    ('A', 'B')
+    >>> adtype = np.dtype([('a', int), ('b', [('ba', int), ('bb', int)])])
+    >>> rfn.get_names_flat(adtype)
+    ('a', 'b', 'ba', 'bb')
+    """
+    listnames = []
+    names = adtype.names
+    for name in names:
+        listnames.append(name)
+        current = adtype[name]
+        if current.names is not None:
+            listnames.extend(get_names_flat(current))
+    return tuple(listnames)
+
+
+def flatten_descr(ndtype):
+    """
+    Flatten a structured data-type description.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> ndtype = np.dtype([('a', '<i4'), ('b', [('ba', '<f8'), ('bb', '<i4')])])
+    >>> rfn.flatten_descr(ndtype)
+    (('a', dtype('int32')), ('ba', dtype('float64')), ('bb', dtype('int32')))
+
+    """
+    names = ndtype.names
+    if names is None:
+        return (('', ndtype),)
+    else:
+        descr = []
+        for field in names:
+            (typ, _) = ndtype.fields[field]
+            if typ.names is not None:
+                descr.extend(flatten_descr(typ))
+            else:
+                descr.append((field, typ))
+        return tuple(descr)
+
+
+def _zip_dtype(seqarrays, flatten=False):
+    newdtype = []
+    if flatten:
+        for a in seqarrays:
+            newdtype.extend(flatten_descr(a.dtype))
+    else:
+        for a in seqarrays:
+            current = a.dtype
+            if current.names is not None and len(current.names) == 1:
+                # special case - dtypes of 1 field are flattened
+                newdtype.extend(_get_fieldspec(current))
+            else:
+                newdtype.append(('', current))
+    return np.dtype(newdtype)
+
+
+def _zip_descr(seqarrays, flatten=False):
+    """
+    Combine the dtype description of a series of arrays.
+
+    Parameters
+    ----------
+    seqarrays : sequence of arrays
+        Sequence of arrays
+    flatten : {boolean}, optional
+        Whether to collapse nested descriptions.
+    """
+    return _zip_dtype(seqarrays, flatten=flatten).descr
+
+
+def get_fieldstructure(adtype, lastname=None, parents=None,):
+    """
+    Returns a dictionary with fields indexing lists of their parent fields.
+
+    This function is used to simplify access to fields nested in other fields.
+
+    Parameters
+    ----------
+    adtype : np.dtype
+        Input datatype
+    lastname : optional
+        Last processed field name (used internally during recursion).
+    parents : dictionary
+        Dictionary of parent fields (used internally during recursion).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> ndtype =  np.dtype([('A', int),
+    ...                     ('B', [('BA', int),
+    ...                            ('BB', [('BBA', int), ('BBB', int)])])])
+    >>> rfn.get_fieldstructure(ndtype)
+    ... # XXX: possible regression, order of BBA and BBB is swapped
+    {'A': [], 'B': [], 'BA': ['B'], 'BB': ['B'], 'BBA': ['B', 'BB'], 'BBB': ['B', 'BB']}
+
+    """
+    if parents is None:
+        parents = {}
+    names = adtype.names
+    for name in names:
+        current = adtype[name]
+        if current.names is not None:
+            if lastname:
+                parents[name] = [lastname, ]
+            else:
+                parents[name] = []
+            parents.update(get_fieldstructure(current, name, parents))
+        else:
+            lastparent = list(parents.get(lastname, []) or [])
+            if lastparent:
+                lastparent.append(lastname)
+            elif lastname:
+                lastparent = [lastname, ]
+            parents[name] = lastparent or []
+    return parents
+
+
+def _izip_fields_flat(iterable):
+    """
+    Returns an iterator of concatenated fields from a sequence of arrays,
+    collapsing any nested structure.
+
+    """
+    for element in iterable:
+        if isinstance(element, np.void):
+            yield from _izip_fields_flat(tuple(element))
+        else:
+            yield element
+
+
+def _izip_fields(iterable):
+    """
+    Returns an iterator of concatenated fields from a sequence of arrays.
+
+    """
+    for element in iterable:
+        if (hasattr(element, '__iter__') and
+                not isinstance(element, str)):
+            yield from _izip_fields(element)
+        elif isinstance(element, np.void) and len(tuple(element)) == 1:
+            # this statement is the same from the previous expression
+            yield from _izip_fields(element)
+        else:
+            yield element
+
+
+def _izip_records(seqarrays, fill_value=None, flatten=True):
+    """
+    Returns an iterator of concatenated items from a sequence of arrays.
+
+    Parameters
+    ----------
+    seqarrays : sequence of arrays
+        Sequence of arrays.
+    fill_value : {None, integer}
+        Value used to pad shorter iterables.
+    flatten : {True, False},
+        Whether to
+    """
+
+    # Should we flatten the items, or just use a nested approach
+    if flatten:
+        zipfunc = _izip_fields_flat
+    else:
+        zipfunc = _izip_fields
+
+    for tup in itertools.zip_longest(*seqarrays, fillvalue=fill_value):
+        yield tuple(zipfunc(tup))
+
+
+def _fix_output(output, usemask=True, asrecarray=False):
+    """
+    Private function: return a recarray, a ndarray, a MaskedArray
+    or a MaskedRecords depending on the input parameters
+    """
+    if not isinstance(output, ma.MaskedArray):
+        usemask = False
+    if usemask:
+        if asrecarray:
+            output = output.view(mrec.MaskedRecords)
+    else:
+        output = ma.filled(output)
+        if asrecarray:
+            output = output.view(np.recarray)
+    return output
+
+
+def _fix_defaults(output, defaults=None):
+    """
+    Update the fill_value and masked data of `output`
+    from the default given in a dictionary defaults.
+    """
+    names = output.dtype.names
+    (data, mask, fill_value) = (output.data, output.mask, output.fill_value)
+    for (k, v) in (defaults or {}).items():
+        if k in names:
+            fill_value[k] = v
+            data[k][mask[k]] = v
+    return output
+
+
+def _merge_arrays_dispatcher(seqarrays, fill_value=None, flatten=None,
+                             usemask=None, asrecarray=None):
+    return seqarrays
+
+
+@array_function_dispatch(_merge_arrays_dispatcher)
+def merge_arrays(seqarrays, fill_value=-1, flatten=False,
+                 usemask=False, asrecarray=False):
+    """
+    Merge arrays field by field.
+
+    Parameters
+    ----------
+    seqarrays : sequence of ndarrays
+        Sequence of arrays
+    fill_value : {float}, optional
+        Filling value used to pad missing data on the shorter arrays.
+    flatten : {False, True}, optional
+        Whether to collapse nested fields.
+    usemask : {False, True}, optional
+        Whether to return a masked array or not.
+    asrecarray : {False, True}, optional
+        Whether to return a recarray (MaskedRecords) or not.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> rfn.merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])))
+    array([( 1, 10.), ( 2, 20.), (-1, 30.)],
+          dtype=[('f0', '<i8'), ('f1', '<f8')])
+
+    >>> rfn.merge_arrays((np.array([1, 2], dtype=np.int64),
+    ...         np.array([10., 20., 30.])), usemask=False)
+     array([(1, 10.0), (2, 20.0), (-1, 30.0)],
+             dtype=[('f0', '<i8'), ('f1', '<f8')])
+    >>> rfn.merge_arrays((np.array([1, 2]).view([('a', np.int64)]),
+    ...               np.array([10., 20., 30.])),
+    ...              usemask=False, asrecarray=True)
+    rec.array([( 1, 10.), ( 2, 20.), (-1, 30.)],
+              dtype=[('a', '<i8'), ('f1', '<f8')])
+
+    Notes
+    -----
+    * Without a mask, the missing value will be filled with something,
+      depending on what its corresponding type:
+
+      * ``-1``      for integers
+      * ``-1.0``    for floating point numbers
+      * ``'-'``     for characters
+      * ``'-1'``    for strings
+      * ``True``    for boolean values
+    * XXX: I just obtained these values empirically
+    """
+    # Only one item in the input sequence ?
+    if (len(seqarrays) == 1):
+        seqarrays = np.asanyarray(seqarrays[0])
+    # Do we have a single ndarray as input ?
+    if isinstance(seqarrays, (np.ndarray, np.void)):
+        seqdtype = seqarrays.dtype
+        # Make sure we have named fields
+        if seqdtype.names is None:
+            seqdtype = np.dtype([('', seqdtype)])
+        if not flatten or _zip_dtype((seqarrays,), flatten=True) == seqdtype:
+            # Minimal processing needed: just make sure everything's a-ok
+            seqarrays = seqarrays.ravel()
+            # Find what type of array we must return
+            if usemask:
+                if asrecarray:
+                    seqtype = mrec.MaskedRecords
+                else:
+                    seqtype = ma.MaskedArray
+            elif asrecarray:
+                seqtype = np.recarray
+            else:
+                seqtype = np.ndarray
+            return seqarrays.view(dtype=seqdtype, type=seqtype)
+        else:
+            seqarrays = (seqarrays,)
+    else:
+        # Make sure we have arrays in the input sequence
+        seqarrays = [np.asanyarray(_m) for _m in seqarrays]
+    # Find the sizes of the inputs and their maximum
+    sizes = tuple(a.size for a in seqarrays)
+    maxlength = max(sizes)
+    # Get the dtype of the output (flattening if needed)
+    newdtype = _zip_dtype(seqarrays, flatten=flatten)
+    # Initialize the sequences for data and mask
+    seqdata = []
+    seqmask = []
+    # If we expect some kind of MaskedArray, make a special loop.
+    if usemask:
+        for (a, n) in zip(seqarrays, sizes):
+            nbmissing = (maxlength - n)
+            # Get the data and mask
+            data = a.ravel().__array__()
+            mask = ma.getmaskarray(a).ravel()
+            # Get the filling value (if needed)
+            if nbmissing:
+                fval = mrec._check_fill_value(fill_value, a.dtype)
+                if isinstance(fval, (np.ndarray, np.void)):
+                    if len(fval.dtype) == 1:
+                        fval = fval.item()[0]
+                        fmsk = True
+                    else:
+                        fval = np.array(fval, dtype=a.dtype, ndmin=1)
+                        fmsk = np.ones((1,), dtype=mask.dtype)
+            else:
+                fval = None
+                fmsk = True
+            # Store an iterator padding the input to the expected length
+            seqdata.append(itertools.chain(data, [fval] * nbmissing))
+            seqmask.append(itertools.chain(mask, [fmsk] * nbmissing))
+        # Create an iterator for the data
+        data = tuple(_izip_records(seqdata, flatten=flatten))
+        output = ma.array(np.fromiter(data, dtype=newdtype, count=maxlength),
+                          mask=list(_izip_records(seqmask, flatten=flatten)))
+        if asrecarray:
+            output = output.view(mrec.MaskedRecords)
+    else:
+        # Same as before, without the mask we don't need...
+        for (a, n) in zip(seqarrays, sizes):
+            nbmissing = (maxlength - n)
+            data = a.ravel().__array__()
+            if nbmissing:
+                fval = mrec._check_fill_value(fill_value, a.dtype)
+                if isinstance(fval, (np.ndarray, np.void)):
+                    if len(fval.dtype) == 1:
+                        fval = fval.item()[0]
+                    else:
+                        fval = np.array(fval, dtype=a.dtype, ndmin=1)
+            else:
+                fval = None
+            seqdata.append(itertools.chain(data, [fval] * nbmissing))
+        output = np.fromiter(tuple(_izip_records(seqdata, flatten=flatten)),
+                             dtype=newdtype, count=maxlength)
+        if asrecarray:
+            output = output.view(np.recarray)
+    # And we're done...
+    return output
+
+
+def _drop_fields_dispatcher(base, drop_names, usemask=None, asrecarray=None):
+    return (base,)
+
+
+@array_function_dispatch(_drop_fields_dispatcher)
+def drop_fields(base, drop_names, usemask=True, asrecarray=False):
+    """
+    Return a new array with fields in `drop_names` dropped.
+
+    Nested fields are supported.
+
+    Parameters
+    ----------
+    base : array
+        Input array
+    drop_names : string or sequence
+        String or sequence of strings corresponding to the names of the
+        fields to drop.
+    usemask : {False, True}, optional
+        Whether to return a masked array or not.
+    asrecarray : string or sequence, optional
+        Whether to return a recarray or a mrecarray (`asrecarray=True`) or
+        a plain ndarray or masked array with flexible dtype. The default
+        is False.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> a = np.array([(1, (2, 3.0)), (4, (5, 6.0))],
+    ...   dtype=[('a', np.int64), ('b', [('ba', np.double), ('bb', np.int64)])])
+    >>> rfn.drop_fields(a, 'a')
+    array([((2., 3),), ((5., 6),)],
+          dtype=[('b', [('ba', '<f8'), ('bb', '<i8')])])
+    >>> rfn.drop_fields(a, 'ba')
+    array([(1, (3,)), (4, (6,))], dtype=[('a', '<i8'), ('b', [('bb', '<i8')])])
+    >>> rfn.drop_fields(a, ['ba', 'bb'])
+    array([(1,), (4,)], dtype=[('a', '<i8')])
+    """
+    if _is_string_like(drop_names):
+        drop_names = [drop_names]
+    else:
+        drop_names = set(drop_names)
+
+    def _drop_descr(ndtype, drop_names):
+        names = ndtype.names
+        newdtype = []
+        for name in names:
+            current = ndtype[name]
+            if name in drop_names:
+                continue
+            if current.names is not None:
+                descr = _drop_descr(current, drop_names)
+                if descr:
+                    newdtype.append((name, descr))
+            else:
+                newdtype.append((name, current))
+        return newdtype
+
+    newdtype = _drop_descr(base.dtype, drop_names)
+
+    output = np.empty(base.shape, dtype=newdtype)
+    output = recursive_fill_fields(base, output)
+    return _fix_output(output, usemask=usemask, asrecarray=asrecarray)
+
+
+def _keep_fields(base, keep_names, usemask=True, asrecarray=False):
+    """
+    Return a new array keeping only the fields in `keep_names`,
+    and preserving the order of those fields.
+
+    Parameters
+    ----------
+    base : array
+        Input array
+    keep_names : string or sequence
+        String or sequence of strings corresponding to the names of the
+        fields to keep. Order of the names will be preserved.
+    usemask : {False, True}, optional
+        Whether to return a masked array or not.
+    asrecarray : string or sequence, optional
+        Whether to return a recarray or a mrecarray (`asrecarray=True`) or
+        a plain ndarray or masked array with flexible dtype. The default
+        is False.
+    """
+    newdtype = [(n, base.dtype[n]) for n in keep_names]
+    output = np.empty(base.shape, dtype=newdtype)
+    output = recursive_fill_fields(base, output)
+    return _fix_output(output, usemask=usemask, asrecarray=asrecarray)
+
+
+def _rec_drop_fields_dispatcher(base, drop_names):
+    return (base,)
+
+
+@array_function_dispatch(_rec_drop_fields_dispatcher)
+def rec_drop_fields(base, drop_names):
+    """
+    Returns a new numpy.recarray with fields in `drop_names` dropped.
+    """
+    return drop_fields(base, drop_names, usemask=False, asrecarray=True)
+
+
+def _rename_fields_dispatcher(base, namemapper):
+    return (base,)
+
+
+@array_function_dispatch(_rename_fields_dispatcher)
+def rename_fields(base, namemapper):
+    """
+    Rename the fields from a flexible-datatype ndarray or recarray.
+
+    Nested fields are supported.
+
+    Parameters
+    ----------
+    base : ndarray
+        Input array whose fields must be modified.
+    namemapper : dictionary
+        Dictionary mapping old field names to their new version.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> a = np.array([(1, (2, [3.0, 30.])), (4, (5, [6.0, 60.]))],
+    ...   dtype=[('a', int),('b', [('ba', float), ('bb', (float, 2))])])
+    >>> rfn.rename_fields(a, {'a':'A', 'bb':'BB'})
+    array([(1, (2., [ 3., 30.])), (4, (5., [ 6., 60.]))],
+          dtype=[('A', '<i8'), ('b', [('ba', '<f8'), ('BB', '<f8', (2,))])])
+
+    """
+    def _recursive_rename_fields(ndtype, namemapper):
+        newdtype = []
+        for name in ndtype.names:
+            newname = namemapper.get(name, name)
+            current = ndtype[name]
+            if current.names is not None:
+                newdtype.append(
+                    (newname, _recursive_rename_fields(current, namemapper))
+                    )
+            else:
+                newdtype.append((newname, current))
+        return newdtype
+    newdtype = _recursive_rename_fields(base.dtype, namemapper)
+    return base.view(newdtype)
+
+
+def _append_fields_dispatcher(base, names, data, dtypes=None,
+                              fill_value=None, usemask=None, asrecarray=None):
+    yield base
+    yield from data
+
+
+@array_function_dispatch(_append_fields_dispatcher)
+def append_fields(base, names, data, dtypes=None,
+                  fill_value=-1, usemask=True, asrecarray=False):
+    """
+    Add new fields to an existing array.
+
+    The names of the fields are given with the `names` arguments,
+    the corresponding values with the `data` arguments.
+    If a single field is appended, `names`, `data` and `dtypes` do not have
+    to be lists but just values.
+
+    Parameters
+    ----------
+    base : array
+        Input array to extend.
+    names : string, sequence
+        String or sequence of strings corresponding to the names
+        of the new fields.
+    data : array or sequence of arrays
+        Array or sequence of arrays storing the fields to add to the base.
+    dtypes : sequence of datatypes, optional
+        Datatype or sequence of datatypes.
+        If None, the datatypes are estimated from the `data`.
+    fill_value : {float}, optional
+        Filling value used to pad missing data on the shorter arrays.
+    usemask : {False, True}, optional
+        Whether to return a masked array or not.
+    asrecarray : {False, True}, optional
+        Whether to return a recarray (MaskedRecords) or not.
+
+    """
+    # Check the names
+    if isinstance(names, (tuple, list)):
+        if len(names) != len(data):
+            msg = "The number of arrays does not match the number of names"
+            raise ValueError(msg)
+    elif isinstance(names, str):
+        names = [names, ]
+        data = [data, ]
+    #
+    if dtypes is None:
+        data = [np.array(a, copy=None, subok=True) for a in data]
+        data = [a.view([(name, a.dtype)]) for (name, a) in zip(names, data)]
+    else:
+        if not isinstance(dtypes, (tuple, list)):
+            dtypes = [dtypes, ]
+        if len(data) != len(dtypes):
+            if len(dtypes) == 1:
+                dtypes = dtypes * len(data)
+            else:
+                msg = "The dtypes argument must be None, a dtype, or a list."
+                raise ValueError(msg)
+        data = [np.array(a, copy=None, subok=True, dtype=d).view([(n, d)])
+                for (a, n, d) in zip(data, names, dtypes)]
+    #
+    base = merge_arrays(base, usemask=usemask, fill_value=fill_value)
+    if len(data) > 1:
+        data = merge_arrays(data, flatten=True, usemask=usemask,
+                            fill_value=fill_value)
+    else:
+        data = data.pop()
+    #
+    output = ma.masked_all(
+        max(len(base), len(data)),
+        dtype=_get_fieldspec(base.dtype) + _get_fieldspec(data.dtype))
+    output = recursive_fill_fields(base, output)
+    output = recursive_fill_fields(data, output)
+    #
+    return _fix_output(output, usemask=usemask, asrecarray=asrecarray)
+
+
+def _rec_append_fields_dispatcher(base, names, data, dtypes=None):
+    yield base
+    yield from data
+
+
+@array_function_dispatch(_rec_append_fields_dispatcher)
+def rec_append_fields(base, names, data, dtypes=None):
+    """
+    Add new fields to an existing array.
+
+    The names of the fields are given with the `names` arguments,
+    the corresponding values with the `data` arguments.
+    If a single field is appended, `names`, `data` and `dtypes` do not have
+    to be lists but just values.
+
+    Parameters
+    ----------
+    base : array
+        Input array to extend.
+    names : string, sequence
+        String or sequence of strings corresponding to the names
+        of the new fields.
+    data : array or sequence of arrays
+        Array or sequence of arrays storing the fields to add to the base.
+    dtypes : sequence of datatypes, optional
+        Datatype or sequence of datatypes.
+        If None, the datatypes are estimated from the `data`.
+
+    See Also
+    --------
+    append_fields
+
+    Returns
+    -------
+    appended_array : np.recarray
+    """
+    return append_fields(base, names, data=data, dtypes=dtypes,
+                         asrecarray=True, usemask=False)
+
+
+def _repack_fields_dispatcher(a, align=None, recurse=None):
+    return (a,)
+
+
+@array_function_dispatch(_repack_fields_dispatcher)
+def repack_fields(a, align=False, recurse=False):
+    """
+    Re-pack the fields of a structured array or dtype in memory.
+
+    The memory layout of structured datatypes allows fields at arbitrary
+    byte offsets. This means the fields can be separated by padding bytes,
+    their offsets can be non-monotonically increasing, and they can overlap.
+
+    This method removes any overlaps and reorders the fields in memory so they
+    have increasing byte offsets, and adds or removes padding bytes depending
+    on the `align` option, which behaves like the `align` option to
+    `numpy.dtype`.
+
+    If `align=False`, this method produces a "packed" memory layout in which
+    each field starts at the byte the previous field ended, and any padding
+    bytes are removed.
+
+    If `align=True`, this methods produces an "aligned" memory layout in which
+    each field's offset is a multiple of its alignment, and the total itemsize
+    is a multiple of the largest alignment, by adding padding bytes as needed.
+
+    Parameters
+    ----------
+    a : ndarray or dtype
+       array or dtype for which to repack the fields.
+    align : boolean
+       If true, use an "aligned" memory layout, otherwise use a "packed" layout.
+    recurse : boolean
+       If True, also repack nested structures.
+
+    Returns
+    -------
+    repacked : ndarray or dtype
+       Copy of `a` with fields repacked, or `a` itself if no repacking was
+       needed.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from numpy.lib import recfunctions as rfn
+    >>> def print_offsets(d):
+    ...     print("offsets:", [d.fields[name][1] for name in d.names])
+    ...     print("itemsize:", d.itemsize)
+    ...
+    >>> dt = np.dtype('u1, <i8, <f8', align=True)
+    >>> dt
+    dtype({'names': ['f0', 'f1', 'f2'], 'formats': ['u1', '<i8', '<f8'], \
+'offsets': [0, 8, 16], 'itemsize': 24}, align=True)
+    >>> print_offsets(dt)
+    offsets: [0, 8, 16]
+    itemsize: 24
+    >>> packed_dt = rfn.repack_fields(dt)
+    >>> packed_dt
+    dtype([('f0', 'u1'), ('f1', '<i8'), ('f2', '<f8')])
+    >>> print_offsets(packed_dt)
+    offsets: [0, 1, 9]
+    itemsize: 17
+
+    """
+    if not isinstance(a, np.dtype):
+        dt = repack_fields(a.dtype, align=align, recurse=recurse)
+        return a.astype(dt, copy=False)
+
+    if a.names is None:
+        return a
+
+    fieldinfo = []
+    for name in a.names:
+        tup = a.fields[name]
+        if recurse:
+            fmt = repack_fields(tup[0], align=align, recurse=True)
+        else:
+            fmt = tup[0]
+
+        if len(tup) == 3:
+            name = (tup[2], name)
+
+        fieldinfo.append((name, fmt))
+
+    dt = np.dtype(fieldinfo, align=align)
+    return np.dtype((a.type, dt))
+
+def _get_fields_and_offsets(dt, offset=0):
+    """
+    Returns a flat list of (dtype, count, offset) tuples of all the
+    scalar fields in the dtype "dt", including nested fields, in left
+    to right order.
+    """
+
+    # counts up elements in subarrays, including nested subarrays, and returns
+    # base dtype and count
+    def count_elem(dt):
+        count = 1
+        while dt.shape != ():
+            for size in dt.shape:
+                count *= size
+            dt = dt.base
+        return dt, count
+
+    fields = []
+    for name in dt.names:
+        field = dt.fields[name]
+        f_dt, f_offset = field[0], field[1]
+        f_dt, n = count_elem(f_dt)
+
+        if f_dt.names is None:
+            fields.append((np.dtype((f_dt, (n,))), n, f_offset + offset))
+        else:
+            subfields = _get_fields_and_offsets(f_dt, f_offset + offset)
+            size = f_dt.itemsize
+
+            for i in range(n):
+                if i == 0:
+                    # optimization: avoid list comprehension if no subarray
+                    fields.extend(subfields)
+                else:
+                    fields.extend([(d, c, o + i * size) for d, c, o in subfields])
+    return fields
+
+def _common_stride(offsets, counts, itemsize):
+    """
+    Returns the stride between the fields, or None if the stride is not
+    constant. The values in "counts" designate the lengths of
+    subarrays. Subarrays are treated as many contiguous fields, with
+    always positive stride.
+    """
+    if len(offsets) <= 1:
+        return itemsize
+
+    negative = offsets[1] < offsets[0]  # negative stride
+    if negative:
+        # reverse, so offsets will be ascending
+        it = zip(reversed(offsets), reversed(counts))
+    else:
+        it = zip(offsets, counts)
+
+    prev_offset = None
+    stride = None
+    for offset, count in it:
+        if count != 1:  # subarray: always c-contiguous
+            if negative:
+                return None  # subarrays can never have a negative stride
+            if stride is None:
+                stride = itemsize
+            if stride != itemsize:
+                return None
+            end_offset = offset + (count - 1) * itemsize
+        else:
+            end_offset = offset
+
+        if prev_offset is not None:
+            new_stride = offset - prev_offset
+            if stride is None:
+                stride = new_stride
+            if stride != new_stride:
+                return None
+
+        prev_offset = end_offset
+
+    if negative:
+        return -stride
+    return stride
+
+
+def _structured_to_unstructured_dispatcher(arr, dtype=None, copy=None,
+                                           casting=None):
+    return (arr,)
+
+@array_function_dispatch(_structured_to_unstructured_dispatcher)
+def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'):
+    """
+    Converts an n-D structured array into an (n+1)-D unstructured array.
+
+    The new array will have a new last dimension equal in size to the
+    number of field-elements of the input array. If not supplied, the output
+    datatype is determined from the numpy type promotion rules applied to all
+    the field datatypes.
+
+    Nested fields, as well as each element of any subarray fields, all count
+    as a single field-elements.
+
+    Parameters
+    ----------
+    arr : ndarray
+       Structured array or dtype to convert. Cannot contain object datatype.
+    dtype : dtype, optional
+       The dtype of the output unstructured array.
+    copy : bool, optional
+        If true, always return a copy. If false, a view is returned if
+        possible, such as when the `dtype` and strides of the fields are
+        suitable and the array subtype is one of `numpy.ndarray`,
+        `numpy.recarray` or `numpy.memmap`.
+
+        .. versionchanged:: 1.25.0
+            A view can now be returned if the fields are separated by a
+            uniform stride.
+
+    casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
+        See casting argument of `numpy.ndarray.astype`. Controls what kind of
+        data casting may occur.
+
+    Returns
+    -------
+    unstructured : ndarray
+       Unstructured array with one more dimension.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from numpy.lib import recfunctions as rfn
+    >>> a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
+    >>> a
+    array([(0, (0., 0), [0., 0.]), (0, (0., 0), [0., 0.]),
+           (0, (0., 0), [0., 0.]), (0, (0., 0), [0., 0.])],
+          dtype=[('a', '<i4'), ('b', [('f0', '<f4'), ('f1', '<u2')]), ('c', '<f4', (2,))])
+    >>> rfn.structured_to_unstructured(a)
+    array([[0., 0., 0., 0., 0.],
+           [0., 0., 0., 0., 0.],
+           [0., 0., 0., 0., 0.],
+           [0., 0., 0., 0., 0.]])
+
+    >>> b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
+    ...              dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
+    >>> np.mean(rfn.structured_to_unstructured(b[['x', 'z']]), axis=-1)
+    array([ 3. ,  5.5,  9. , 11. ])
+
+    """  # noqa: E501
+    if arr.dtype.names is None:
+        raise ValueError('arr must be a structured array')
+
+    fields = _get_fields_and_offsets(arr.dtype)
+    n_fields = len(fields)
+    if n_fields == 0 and dtype is None:
+        raise ValueError("arr has no fields. Unable to guess dtype")
+    elif n_fields == 0:
+        # too many bugs elsewhere for this to work now
+        raise NotImplementedError("arr with no fields is not supported")
+
+    dts, counts, offsets = zip(*fields)
+    names = [f'f{n}' for n in range(n_fields)]
+
+    if dtype is None:
+        out_dtype = np.result_type(*[dt.base for dt in dts])
+    else:
+        out_dtype = np.dtype(dtype)
+
+    # Use a series of views and casts to convert to an unstructured array:
+
+    # first view using flattened fields (doesn't work for object arrays)
+    # Note: dts may include a shape for subarrays
+    flattened_fields = np.dtype({'names': names,
+                                 'formats': dts,
+                                 'offsets': offsets,
+                                 'itemsize': arr.dtype.itemsize})
+    arr = arr.view(flattened_fields)
+
+    # we only allow a few types to be unstructured by manipulating the
+    # strides, because we know it won't work with, for example, np.matrix nor
+    # np.ma.MaskedArray.
+    can_view = type(arr) in (np.ndarray, np.recarray, np.memmap)
+    if (not copy) and can_view and all(dt.base == out_dtype for dt in dts):
+        # all elements have the right dtype already; if they have a common
+        # stride, we can just return a view
+        common_stride = _common_stride(offsets, counts, out_dtype.itemsize)
+        if common_stride is not None:
+            wrap = arr.__array_wrap__
+
+            new_shape = arr.shape + (sum(counts), out_dtype.itemsize)
+            new_strides = arr.strides + (abs(common_stride), 1)
+
+            arr = arr[..., np.newaxis].view(np.uint8)  # view as bytes
+            arr = arr[..., min(offsets):]  # remove the leading unused data
+            arr = np.lib.stride_tricks.as_strided(arr,
+                                                  new_shape,
+                                                  new_strides,
+                                                  subok=True)
+
+            # cast and drop the last dimension again
+            arr = arr.view(out_dtype)[..., 0]
+
+            if common_stride < 0:
+                arr = arr[..., ::-1]  # reverse, if the stride was negative
+            if type(arr) is not type(wrap.__self__):
+                # Some types (e.g. recarray) turn into an ndarray along the
+                # way, so we have to wrap it again in order to match the
+                # behavior with copy=True.
+                arr = wrap(arr)
+            return arr
+
+    # next cast to a packed format with all fields converted to new dtype
+    packed_fields = np.dtype({'names': names,
+                              'formats': [(out_dtype, dt.shape) for dt in dts]})
+    arr = arr.astype(packed_fields, copy=copy, casting=casting)
+
+    # finally is it safe to view the packed fields as the unstructured type
+    return arr.view((out_dtype, (sum(counts),)))
+
+
+def _unstructured_to_structured_dispatcher(arr, dtype=None, names=None,
+                                           align=None, copy=None, casting=None):
+    return (arr,)
+
+@array_function_dispatch(_unstructured_to_structured_dispatcher)
+def unstructured_to_structured(arr, dtype=None, names=None, align=False,
+                               copy=False, casting='unsafe'):
+    """
+    Converts an n-D unstructured array into an (n-1)-D structured array.
+
+    The last dimension of the input array is converted into a structure, with
+    number of field-elements equal to the size of the last dimension of the
+    input array. By default all output fields have the input array's dtype, but
+    an output structured dtype with an equal number of fields-elements can be
+    supplied instead.
+
+    Nested fields, as well as each element of any subarray fields, all count
+    towards the number of field-elements.
+
+    Parameters
+    ----------
+    arr : ndarray
+       Unstructured array or dtype to convert.
+    dtype : dtype, optional
+       The structured dtype of the output array
+    names : list of strings, optional
+       If dtype is not supplied, this specifies the field names for the output
+       dtype, in order. The field dtypes will be the same as the input array.
+    align : boolean, optional
+       Whether to create an aligned memory layout.
+    copy : bool, optional
+        See copy argument to `numpy.ndarray.astype`. If true, always return a
+        copy. If false, and `dtype` requirements are satisfied, a view is
+        returned.
+    casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
+        See casting argument of `numpy.ndarray.astype`. Controls what kind of
+        data casting may occur.
+
+    Returns
+    -------
+    structured : ndarray
+       Structured array with fewer dimensions.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from numpy.lib import recfunctions as rfn
+    >>> dt = np.dtype([('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
+    >>> a = np.arange(20).reshape((4,5))
+    >>> a
+    array([[ 0,  1,  2,  3,  4],
+           [ 5,  6,  7,  8,  9],
+           [10, 11, 12, 13, 14],
+           [15, 16, 17, 18, 19]])
+    >>> rfn.unstructured_to_structured(a, dt)
+    array([( 0, ( 1.,  2), [ 3.,  4.]), ( 5, ( 6.,  7), [ 8.,  9.]),
+           (10, (11., 12), [13., 14.]), (15, (16., 17), [18., 19.])],
+          dtype=[('a', '<i4'), ('b', [('f0', '<f4'), ('f1', '<u2')]), ('c', '<f4', (2,))])
+
+    """  # noqa: E501
+    if arr.shape == ():
+        raise ValueError('arr must have at least one dimension')
+    n_elem = arr.shape[-1]
+    if n_elem == 0:
+        # too many bugs elsewhere for this to work now
+        raise NotImplementedError("last axis with size 0 is not supported")
+
+    if dtype is None:
+        if names is None:
+            names = [f'f{n}' for n in range(n_elem)]
+        out_dtype = np.dtype([(n, arr.dtype) for n in names], align=align)
+        fields = _get_fields_and_offsets(out_dtype)
+        dts, counts, offsets = zip(*fields)
+    else:
+        if names is not None:
+            raise ValueError("don't supply both dtype and names")
+        # if dtype is the args of np.dtype, construct it
+        dtype = np.dtype(dtype)
+        # sanity check of the input dtype
+        fields = _get_fields_and_offsets(dtype)
+        if len(fields) == 0:
+            dts, counts, offsets = [], [], []
+        else:
+            dts, counts, offsets = zip(*fields)
+
+        if n_elem != sum(counts):
+            raise ValueError('The length of the last dimension of arr must '
+                             'be equal to the number of fields in dtype')
+        out_dtype = dtype
+        if align and not out_dtype.isalignedstruct:
+            raise ValueError("align was True but dtype is not aligned")
+
+    names = [f'f{n}' for n in range(len(fields))]
+
+    # Use a series of views and casts to convert to a structured array:
+
+    # first view as a packed structured array of one dtype
+    packed_fields = np.dtype({'names': names,
+                              'formats': [(arr.dtype, dt.shape) for dt in dts]})
+    arr = np.ascontiguousarray(arr).view(packed_fields)
+
+    # next cast to an unpacked but flattened format with varied dtypes
+    flattened_fields = np.dtype({'names': names,
+                                 'formats': dts,
+                                 'offsets': offsets,
+                                 'itemsize': out_dtype.itemsize})
+    arr = arr.astype(flattened_fields, copy=copy, casting=casting)
+
+    # finally view as the final nested dtype and remove the last axis
+    return arr.view(out_dtype)[..., 0]
+
+def _apply_along_fields_dispatcher(func, arr):
+    return (arr,)
+
+@array_function_dispatch(_apply_along_fields_dispatcher)
+def apply_along_fields(func, arr):
+    """
+    Apply function 'func' as a reduction across fields of a structured array.
+
+    This is similar to `numpy.apply_along_axis`, but treats the fields of a
+    structured array as an extra axis. The fields are all first cast to a
+    common type following the type-promotion rules from `numpy.result_type`
+    applied to the field's dtypes.
+
+    Parameters
+    ----------
+    func : function
+       Function to apply on the "field" dimension. This function must
+       support an `axis` argument, like `numpy.mean`, `numpy.sum`, etc.
+    arr : ndarray
+       Structured array for which to apply func.
+
+    Returns
+    -------
+    out : ndarray
+       Result of the reduction operation
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from numpy.lib import recfunctions as rfn
+    >>> b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)],
+    ...              dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')])
+    >>> rfn.apply_along_fields(np.mean, b)
+    array([ 2.66666667,  5.33333333,  8.66666667, 11.        ])
+    >>> rfn.apply_along_fields(np.mean, b[['x', 'z']])
+    array([ 3. ,  5.5,  9. , 11. ])
+
+    """
+    if arr.dtype.names is None:
+        raise ValueError('arr must be a structured array')
+
+    uarr = structured_to_unstructured(arr)
+    return func(uarr, axis=-1)
+    # works and avoids axis requirement, but very, very slow:
+    #return np.apply_along_axis(func, -1, uarr)
+
+def _assign_fields_by_name_dispatcher(dst, src, zero_unassigned=None):
+    return dst, src
+
+@array_function_dispatch(_assign_fields_by_name_dispatcher)
+def assign_fields_by_name(dst, src, zero_unassigned=True):
+    """
+    Assigns values from one structured array to another by field name.
+
+    Normally in numpy >= 1.14, assignment of one structured array to another
+    copies fields "by position", meaning that the first field from the src is
+    copied to the first field of the dst, and so on, regardless of field name.
+
+    This function instead copies "by field name", such that fields in the dst
+    are assigned from the identically named field in the src. This applies
+    recursively for nested structures. This is how structure assignment worked
+    in numpy >= 1.6 to <= 1.13.
+
+    Parameters
+    ----------
+    dst : ndarray
+    src : ndarray
+        The source and destination arrays during assignment.
+    zero_unassigned : bool, optional
+        If True, fields in the dst for which there was no matching
+        field in the src are filled with the value 0 (zero). This
+        was the behavior of numpy <= 1.13. If False, those fields
+        are not modified.
+    """
+
+    if dst.dtype.names is None:
+        dst[...] = src
+        return
+
+    for name in dst.dtype.names:
+        if name not in src.dtype.names:
+            if zero_unassigned:
+                dst[name] = 0
+        else:
+            assign_fields_by_name(dst[name], src[name],
+                                  zero_unassigned)
+
+def _require_fields_dispatcher(array, required_dtype):
+    return (array,)
+
+@array_function_dispatch(_require_fields_dispatcher)
+def require_fields(array, required_dtype):
+    """
+    Casts a structured array to a new dtype using assignment by field-name.
+
+    This function assigns from the old to the new array by name, so the
+    value of a field in the output array is the value of the field with the
+    same name in the source array. This has the effect of creating a new
+    ndarray containing only the fields "required" by the required_dtype.
+
+    If a field name in the required_dtype does not exist in the
+    input array, that field is created and set to 0 in the output array.
+
+    Parameters
+    ----------
+    a : ndarray
+       array to cast
+    required_dtype : dtype
+       datatype for output array
+
+    Returns
+    -------
+    out : ndarray
+        array with the new dtype, with field values copied from the fields in
+        the input array with the same name
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    >>> from numpy.lib import recfunctions as rfn
+    >>> a = np.ones(4, dtype=[('a', 'i4'), ('b', 'f8'), ('c', 'u1')])
+    >>> rfn.require_fields(a, [('b', 'f4'), ('c', 'u1')])
+    array([(1., 1), (1., 1), (1., 1), (1., 1)],
+      dtype=[('b', '<f4'), ('c', 'u1')])
+    >>> rfn.require_fields(a, [('b', 'f4'), ('newf', 'u1')])
+    array([(1., 0), (1., 0), (1., 0), (1., 0)],
+      dtype=[('b', '<f4'), ('newf', 'u1')])
+
+    """
+    out = np.empty(array.shape, dtype=required_dtype)
+    assign_fields_by_name(out, array)
+    return out
+
+
+def _stack_arrays_dispatcher(arrays, defaults=None, usemask=None,
+                             asrecarray=None, autoconvert=None):
+    return arrays
+
+
+@array_function_dispatch(_stack_arrays_dispatcher)
+def stack_arrays(arrays, defaults=None, usemask=True, asrecarray=False,
+                 autoconvert=False):
+    """
+    Superposes arrays fields by fields
+
+    Parameters
+    ----------
+    arrays : array or sequence
+        Sequence of input arrays.
+    defaults : dictionary, optional
+        Dictionary mapping field names to the corresponding default values.
+    usemask : {True, False}, optional
+        Whether to return a MaskedArray (or MaskedRecords is
+        `asrecarray==True`) or a ndarray.
+    asrecarray : {False, True}, optional
+        Whether to return a recarray (or MaskedRecords if `usemask==True`)
+        or just a flexible-type ndarray.
+    autoconvert : {False, True}, optional
+        Whether automatically cast the type of the field to the maximum.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> x = np.array([1, 2,])
+    >>> rfn.stack_arrays(x) is x
+    True
+    >>> z = np.array([('A', 1), ('B', 2)], dtype=[('A', '|S3'), ('B', float)])
+    >>> zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)],
+    ...   dtype=[('A', '|S3'), ('B', np.double), ('C', np.double)])
+    >>> test = rfn.stack_arrays((z,zz))
+    >>> test
+    masked_array(data=[(b'A', 1.0, --), (b'B', 2.0, --), (b'a', 10.0, 100.0),
+                       (b'b', 20.0, 200.0), (b'c', 30.0, 300.0)],
+                 mask=[(False, False,  True), (False, False,  True),
+                       (False, False, False), (False, False, False),
+                       (False, False, False)],
+           fill_value=(b'N/A', 1e+20, 1e+20),
+                dtype=[('A', 'S3'), ('B', '<f8'), ('C', '<f8')])
+
+    """
+    if isinstance(arrays, np.ndarray):
+        return arrays
+    elif len(arrays) == 1:
+        return arrays[0]
+    seqarrays = [np.asanyarray(a).ravel() for a in arrays]
+    nrecords = [len(a) for a in seqarrays]
+    ndtype = [a.dtype for a in seqarrays]
+    fldnames = [d.names for d in ndtype]
+    #
+    dtype_l = ndtype[0]
+    newdescr = _get_fieldspec(dtype_l)
+    names = [n for n, d in newdescr]
+    for dtype_n in ndtype[1:]:
+        for fname, fdtype in _get_fieldspec(dtype_n):
+            if fname not in names:
+                newdescr.append((fname, fdtype))
+                names.append(fname)
+            else:
+                nameidx = names.index(fname)
+                _, cdtype = newdescr[nameidx]
+                if autoconvert:
+                    newdescr[nameidx] = (fname, max(fdtype, cdtype))
+                elif fdtype != cdtype:
+                    raise TypeError(f"Incompatible type '{cdtype}' <> '{fdtype}'")
+    # Only one field: use concatenate
+    if len(newdescr) == 1:
+        output = ma.concatenate(seqarrays)
+    else:
+        #
+        output = ma.masked_all((np.sum(nrecords),), newdescr)
+        offset = np.cumsum(np.r_[0, nrecords])
+        seen = []
+        for (a, n, i, j) in zip(seqarrays, fldnames, offset[:-1], offset[1:]):
+            names = a.dtype.names
+            if names is None:
+                output[f'f{len(seen)}'][i:j] = a
+            else:
+                for name in n:
+                    output[name][i:j] = a[name]
+                    if name not in seen:
+                        seen.append(name)
+    #
+    return _fix_output(_fix_defaults(output, defaults),
+                       usemask=usemask, asrecarray=asrecarray)
+
+
+def _find_duplicates_dispatcher(
+        a, key=None, ignoremask=None, return_index=None):
+    return (a,)
+
+
+@array_function_dispatch(_find_duplicates_dispatcher)
+def find_duplicates(a, key=None, ignoremask=True, return_index=False):
+    """
+    Find the duplicates in a structured array along a given key
+
+    Parameters
+    ----------
+    a : array-like
+        Input array
+    key : {string, None}, optional
+        Name of the fields along which to check the duplicates.
+        If None, the search is performed by records
+    ignoremask : {True, False}, optional
+        Whether masked data should be discarded or considered as duplicates.
+    return_index : {False, True}, optional
+        Whether to return the indices of the duplicated values.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.lib import recfunctions as rfn
+    >>> ndtype = [('a', int)]
+    >>> a = np.ma.array([1, 1, 1, 2, 2, 3, 3],
+    ...         mask=[0, 0, 1, 0, 0, 0, 1]).view(ndtype)
+    >>> rfn.find_duplicates(a, ignoremask=True, return_index=True)
+    (masked_array(data=[(1,), (1,), (2,), (2,)],
+                 mask=[(False,), (False,), (False,), (False,)],
+           fill_value=(999999,),
+                dtype=[('a', '<i8')]), array([0, 1, 3, 4]))
+    """
+    a = np.asanyarray(a).ravel()
+    # Get a dictionary of fields
+    fields = get_fieldstructure(a.dtype)
+    # Get the sorting data (by selecting the corresponding field)
+    base = a
+    if key:
+        for f in fields[key]:
+            base = base[f]
+        base = base[key]
+    # Get the sorting indices and the sorted data
+    sortidx = base.argsort()
+    sortedbase = base[sortidx]
+    sorteddata = sortedbase.filled()
+    # Compare the sorting data
+    flag = (sorteddata[:-1] == sorteddata[1:])
+    # If masked data must be ignored, set the flag to false where needed
+    if ignoremask:
+        sortedmask = sortedbase.recordmask
+        flag[sortedmask[1:]] = False
+    flag = np.concatenate(([False], flag))
+    # We need to take the point on the left as well (else we're missing it)
+    flag[:-1] = flag[:-1] + flag[1:]
+    duplicates = a[sortidx][flag]
+    if return_index:
+        return (duplicates, sortidx[flag])
+    else:
+        return duplicates
+
+
+def _join_by_dispatcher(
+        key, r1, r2, jointype=None, r1postfix=None, r2postfix=None,
+        defaults=None, usemask=None, asrecarray=None):
+    return (r1, r2)
+
+
+@array_function_dispatch(_join_by_dispatcher)
+def join_by(key, r1, r2, jointype='inner', r1postfix='1', r2postfix='2',
+            defaults=None, usemask=True, asrecarray=False):
+    """
+    Join arrays `r1` and `r2` on key `key`.
+
+    The key should be either a string or a sequence of string corresponding
+    to the fields used to join the array.  An exception is raised if the
+    `key` field cannot be found in the two input arrays.  Neither `r1` nor
+    `r2` should have any duplicates along `key`: the presence of duplicates
+    will make the output quite unreliable. Note that duplicates are not
+    looked for by the algorithm.
+
+    Parameters
+    ----------
+    key : {string, sequence}
+        A string or a sequence of strings corresponding to the fields used
+        for comparison.
+    r1, r2 : arrays
+        Structured arrays.
+    jointype : {'inner', 'outer', 'leftouter'}, optional
+        If 'inner', returns the elements common to both r1 and r2.
+        If 'outer', returns the common elements as well as the elements of
+        r1 not in r2 and the elements of not in r2.
+        If 'leftouter', returns the common elements and the elements of r1
+        not in r2.
+    r1postfix : string, optional
+        String appended to the names of the fields of r1 that are present
+        in r2 but absent of the key.
+    r2postfix : string, optional
+        String appended to the names of the fields of r2 that are present
+        in r1 but absent of the key.
+    defaults : {dictionary}, optional
+        Dictionary mapping field names to the corresponding default values.
+    usemask : {True, False}, optional
+        Whether to return a MaskedArray (or MaskedRecords is
+        `asrecarray==True`) or a ndarray.
+    asrecarray : {False, True}, optional
+        Whether to return a recarray (or MaskedRecords if `usemask==True`)
+        or just a flexible-type ndarray.
+
+    Notes
+    -----
+    * The output is sorted along the key.
+    * A temporary array is formed by dropping the fields not in the key for
+      the two arrays and concatenating the result. This array is then
+      sorted, and the common entries selected. The output is constructed by
+      filling the fields with the selected entries. Matching is not
+      preserved if there are some duplicates...
+
+    """
+    # Check jointype
+    if jointype not in ('inner', 'outer', 'leftouter'):
+        raise ValueError(
+                "The 'jointype' argument should be in 'inner', "
+                "'outer' or 'leftouter' (got '%s' instead)" % jointype
+                )
+    # If we have a single key, put it in a tuple
+    if isinstance(key, str):
+        key = (key,)
+
+    # Check the keys
+    if len(set(key)) != len(key):
+        dup = next(x for n, x in enumerate(key) if x in key[n + 1:])
+        raise ValueError(f"duplicate join key {dup!r}")
+    for name in key:
+        if name not in r1.dtype.names:
+            raise ValueError(f'r1 does not have key field {name!r}')
+        if name not in r2.dtype.names:
+            raise ValueError(f'r2 does not have key field {name!r}')
+
+    # Make sure we work with ravelled arrays
+    r1 = r1.ravel()
+    r2 = r2.ravel()
+    (nb1, nb2) = (len(r1), len(r2))
+    (r1names, r2names) = (r1.dtype.names, r2.dtype.names)
+
+    # Check the names for collision
+    collisions = (set(r1names) & set(r2names)) - set(key)
+    if collisions and not (r1postfix or r2postfix):
+        msg = "r1 and r2 contain common names, r1postfix and r2postfix "
+        msg += "can't both be empty"
+        raise ValueError(msg)
+
+    # Make temporary arrays of just the keys
+    #  (use order of keys in `r1` for back-compatibility)
+    key1 = [n for n in r1names if n in key]
+    r1k = _keep_fields(r1, key1)
+    r2k = _keep_fields(r2, key1)
+
+    # Concatenate the two arrays for comparison
+    aux = ma.concatenate((r1k, r2k))
+    idx_sort = aux.argsort(order=key)
+    aux = aux[idx_sort]
+    #
+    # Get the common keys
+    flag_in = ma.concatenate(([False], aux[1:] == aux[:-1]))
+    flag_in[:-1] = flag_in[1:] + flag_in[:-1]
+    idx_in = idx_sort[flag_in]
+    idx_1 = idx_in[(idx_in < nb1)]
+    idx_2 = idx_in[(idx_in >= nb1)] - nb1
+    (r1cmn, r2cmn) = (len(idx_1), len(idx_2))
+    if jointype == 'inner':
+        (r1spc, r2spc) = (0, 0)
+    elif jointype == 'outer':
+        idx_out = idx_sort[~flag_in]
+        idx_1 = np.concatenate((idx_1, idx_out[(idx_out < nb1)]))
+        idx_2 = np.concatenate((idx_2, idx_out[(idx_out >= nb1)] - nb1))
+        (r1spc, r2spc) = (len(idx_1) - r1cmn, len(idx_2) - r2cmn)
+    elif jointype == 'leftouter':
+        idx_out = idx_sort[~flag_in]
+        idx_1 = np.concatenate((idx_1, idx_out[(idx_out < nb1)]))
+        (r1spc, r2spc) = (len(idx_1) - r1cmn, 0)
+    # Select the entries from each input
+    (s1, s2) = (r1[idx_1], r2[idx_2])
+    #
+    # Build the new description of the output array .......
+    # Start with the key fields
+    ndtype = _get_fieldspec(r1k.dtype)
+
+    # Add the fields from r1
+    for fname, fdtype in _get_fieldspec(r1.dtype):
+        if fname not in key:
+            ndtype.append((fname, fdtype))
+
+    # Add the fields from r2
+    for fname, fdtype in _get_fieldspec(r2.dtype):
+        # Have we seen the current name already ?
+        # we need to rebuild this list every time
+        names = [name for name, dtype in ndtype]
+        try:
+            nameidx = names.index(fname)
+        except ValueError:
+            #... we haven't: just add the description to the current list
+            ndtype.append((fname, fdtype))
+        else:
+            # collision
+            _, cdtype = ndtype[nameidx]
+            if fname in key:
+                # The current field is part of the key: take the largest dtype
+                ndtype[nameidx] = (fname, max(fdtype, cdtype))
+            else:
+                # The current field is not part of the key: add the suffixes,
+                # and place the new field adjacent to the old one
+                ndtype[nameidx:nameidx + 1] = [
+                    (fname + r1postfix, cdtype),
+                    (fname + r2postfix, fdtype)
+                ]
+    # Rebuild a dtype from the new fields
+    ndtype = np.dtype(ndtype)
+    # Find the largest nb of common fields :
+    # r1cmn and r2cmn should be equal, but...
+    cmn = max(r1cmn, r2cmn)
+    # Construct an empty array
+    output = ma.masked_all((cmn + r1spc + r2spc,), dtype=ndtype)
+    names = output.dtype.names
+    for f in r1names:
+        selected = s1[f]
+        if f not in names or (f in r2names and not r2postfix and f not in key):
+            f += r1postfix
+        current = output[f]
+        current[:r1cmn] = selected[:r1cmn]
+        if jointype in ('outer', 'leftouter'):
+            current[cmn:cmn + r1spc] = selected[r1cmn:]
+    for f in r2names:
+        selected = s2[f]
+        if f not in names or (f in r1names and not r1postfix and f not in key):
+            f += r2postfix
+        current = output[f]
+        current[:r2cmn] = selected[:r2cmn]
+        if (jointype == 'outer') and r2spc:
+            current[-r2spc:] = selected[r2cmn:]
+    # Sort and finalize the output
+    output.sort(order=key)
+    kwargs = {'usemask': usemask, 'asrecarray': asrecarray}
+    return _fix_output(_fix_defaults(output, defaults), **kwargs)
+
+
+def _rec_join_dispatcher(
+        key, r1, r2, jointype=None, r1postfix=None, r2postfix=None,
+        defaults=None):
+    return (r1, r2)
+
+
+@array_function_dispatch(_rec_join_dispatcher)
+def rec_join(key, r1, r2, jointype='inner', r1postfix='1', r2postfix='2',
+             defaults=None):
+    """
+    Join arrays `r1` and `r2` on keys.
+    Alternative to join_by, that always returns a np.recarray.
+
+    See Also
+    --------
+    join_by : equivalent function
+    """
+    kwargs = {'jointype': jointype, 'r1postfix': r1postfix, 'r2postfix': r2postfix,
+                  'defaults': defaults, 'usemask': False, 'asrecarray': True}
+    return join_by(key, r1, r2, **kwargs)
+
+
+del array_function_dispatch
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.pyi b/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..fe1a2ae10209330bb6c85a3044b6c57f4aeaf1f4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/recfunctions.pyi
@@ -0,0 +1,444 @@
+from _typeshed import Incomplete
+from collections.abc import Callable, Iterable, Mapping, Sequence
+from typing import Any, Literal, TypeAlias, overload
+from typing_extensions import TypeVar
+
+import numpy as np
+import numpy.typing as npt
+from numpy._typing import _AnyShape, _DTypeLike, _DTypeLikeVoid
+from numpy.ma.mrecords import MaskedRecords
+
+__all__ = [
+    "append_fields",
+    "apply_along_fields",
+    "assign_fields_by_name",
+    "drop_fields",
+    "find_duplicates",
+    "flatten_descr",
+    "get_fieldstructure",
+    "get_names",
+    "get_names_flat",
+    "join_by",
+    "merge_arrays",
+    "rec_append_fields",
+    "rec_drop_fields",
+    "rec_join",
+    "recursive_fill_fields",
+    "rename_fields",
+    "repack_fields",
+    "require_fields",
+    "stack_arrays",
+    "structured_to_unstructured",
+    "unstructured_to_structured",
+]
+
+_T = TypeVar("_T")
+_ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype)
+_ArrayT = TypeVar("_ArrayT", bound=npt.NDArray[Any])
+_VoidArrayT = TypeVar("_VoidArrayT", bound=npt.NDArray[np.void])
+_NonVoidDTypeT = TypeVar("_NonVoidDTypeT", bound=_NonVoidDType)
+
+_OneOrMany: TypeAlias = _T | Iterable[_T]
+_BuiltinSequence: TypeAlias = tuple[_T, ...] | list[_T]
+
+_NestedNames: TypeAlias = tuple[str | _NestedNames, ...]
+_NonVoid: TypeAlias = np.bool | np.number | np.character | np.datetime64 | np.timedelta64 | np.object_
+_NonVoidDType: TypeAlias = np.dtype[_NonVoid] | np.dtypes.StringDType
+
+_JoinType: TypeAlias = Literal["inner", "outer", "leftouter"]
+
+###
+
+def recursive_fill_fields(input: npt.NDArray[np.void], output: _VoidArrayT) -> _VoidArrayT: ...
+
+#
+def get_names(adtype: np.dtype[np.void]) -> _NestedNames: ...
+def get_names_flat(adtype: np.dtype[np.void]) -> tuple[str, ...]: ...
+
+#
+@overload
+def flatten_descr(ndtype: _NonVoidDTypeT) -> tuple[tuple[Literal[""], _NonVoidDTypeT]]: ...
+@overload
+def flatten_descr(ndtype: np.dtype[np.void]) -> tuple[tuple[str, np.dtype]]: ...
+
+#
+def get_fieldstructure(
+    adtype: np.dtype[np.void],
+    lastname: str | None = None,
+    parents: dict[str, list[str]] | None = None,
+) -> dict[str, list[str]]: ...
+
+#
+@overload
+def merge_arrays(
+    seqarrays: Sequence[np.ndarray[_ShapeT, np.dtype]] | np.ndarray[_ShapeT, np.dtype],
+    fill_value: float = -1,
+    flatten: bool = False,
+    usemask: bool = False,
+    asrecarray: bool = False,
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def merge_arrays(
+    seqarrays: Sequence[npt.ArrayLike] | np.void,
+    fill_value: float = -1,
+    flatten: bool = False,
+    usemask: bool = False,
+    asrecarray: bool = False,
+) -> np.recarray[_AnyShape, np.dtype[np.void]]: ...
+
+#
+@overload
+def drop_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    drop_names: str | Iterable[str],
+    usemask: bool = True,
+    asrecarray: Literal[False] = False,
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def drop_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    drop_names: str | Iterable[str],
+    usemask: bool,
+    asrecarray: Literal[True],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def drop_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    drop_names: str | Iterable[str],
+    usemask: bool = True,
+    *,
+    asrecarray: Literal[True],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+
+#
+@overload
+def rename_fields(
+    base: MaskedRecords[_ShapeT, np.dtype[np.void]],
+    namemapper: Mapping[str, str],
+) -> MaskedRecords[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def rename_fields(
+    base: np.ma.MaskedArray[_ShapeT, np.dtype[np.void]],
+    namemapper: Mapping[str, str],
+) -> np.ma.MaskedArray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def rename_fields(
+    base: np.recarray[_ShapeT, np.dtype[np.void]],
+    namemapper: Mapping[str, str],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def rename_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    namemapper: Mapping[str, str],
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+
+#
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None,
+    fill_value: int,
+    usemask: Literal[False],
+    asrecarray: Literal[False] = False,
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None = None,
+    fill_value: int = -1,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[False] = False,
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None,
+    fill_value: int,
+    usemask: Literal[False],
+    asrecarray: Literal[True],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None = None,
+    fill_value: int = -1,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[True],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None = None,
+    fill_value: int = -1,
+    usemask: Literal[True] = True,
+    asrecarray: Literal[False] = False,
+) -> np.ma.MaskedArray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None,
+    fill_value: int,
+    usemask: Literal[True],
+    asrecarray: Literal[True],
+) -> MaskedRecords[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None = None,
+    fill_value: int = -1,
+    usemask: Literal[True] = True,
+    *,
+    asrecarray: Literal[True],
+) -> MaskedRecords[_ShapeT, np.dtype[np.void]]: ...
+
+#
+def rec_drop_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    drop_names: str | Iterable[str],
+) -> np.recarray[_ShapeT, np.dtype[np.void]]: ...
+
+#
+def rec_append_fields(
+    base: np.ndarray[_ShapeT, np.dtype[np.void]],
+    names: _OneOrMany[str],
+    data: _OneOrMany[npt.NDArray[Any]],
+    dtypes: _BuiltinSequence[np.dtype] | None = None,
+) -> np.ma.MaskedArray[_ShapeT, np.dtype[np.void]]: ...
+
+# TODO(jorenham): Stop passing `void` directly once structured dtypes are implemented,
+# e.g. using a `TypeVar` with constraints.
+# https://github.com/numpy/numtype/issues/92
+@overload
+def repack_fields(a: _DTypeT, align: bool = False, recurse: bool = False) -> _DTypeT: ...
+@overload
+def repack_fields(a: _ScalarT, align: bool = False, recurse: bool = False) -> _ScalarT: ...
+@overload
+def repack_fields(a: _ArrayT, align: bool = False, recurse: bool = False) -> _ArrayT: ...
+
+# TODO(jorenham): Attempt shape-typing (return type has ndim == arr.ndim + 1)
+@overload
+def structured_to_unstructured(
+    arr: npt.NDArray[np.void],
+    dtype: _DTypeLike[_ScalarT],
+    copy: bool = False,
+    casting: np._CastingKind = "unsafe",
+) -> npt.NDArray[_ScalarT]: ...
+@overload
+def structured_to_unstructured(
+    arr: npt.NDArray[np.void],
+    dtype: npt.DTypeLike | None = None,
+    copy: bool = False,
+    casting: np._CastingKind = "unsafe",
+) -> npt.NDArray[Any]: ...
+
+#
+@overload
+def unstructured_to_structured(
+    arr: npt.NDArray[Any],
+    dtype: npt.DTypeLike,
+    names: None = None,
+    align: bool = False,
+    copy: bool = False,
+    casting: str = "unsafe",
+) -> npt.NDArray[np.void]: ...
+@overload
+def unstructured_to_structured(
+    arr: npt.NDArray[Any],
+    dtype: None,
+    names: _OneOrMany[str],
+    align: bool = False,
+    copy: bool = False,
+    casting: str = "unsafe",
+) -> npt.NDArray[np.void]: ...
+@overload
+def unstructured_to_structured(
+    arr: npt.NDArray[Any],
+    dtype: None = None,
+    *,
+    names: _OneOrMany[str],
+    align: bool = False,
+    copy: bool = False,
+    casting: str = "unsafe",
+) -> npt.NDArray[np.void]: ...
+
+#
+def apply_along_fields(
+    func: Callable[[np.ndarray[_ShapeT, Any]], npt.NDArray[Any]],
+    arr: np.ndarray[_ShapeT, np.dtype[np.void]],
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+
+#
+def assign_fields_by_name(dst: npt.NDArray[np.void], src: npt.NDArray[np.void], zero_unassigned: bool = True) -> None: ...
+
+#
+def require_fields(
+    array: np.ndarray[_ShapeT, np.dtype[np.void]],
+    required_dtype: _DTypeLikeVoid,
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+
+# TODO(jorenham): Attempt shape-typing
+@overload
+def stack_arrays(
+    arrays: _ArrayT,
+    defaults: Mapping[str, object] | None = None,
+    usemask: bool = True,
+    asrecarray: bool = False,
+    autoconvert: bool = False,
+) -> _ArrayT: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None,
+    usemask: Literal[False],
+    asrecarray: Literal[False] = False,
+    autoconvert: bool = False,
+) -> npt.NDArray[np.void]: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None = None,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[False] = False,
+    autoconvert: bool = False,
+) -> npt.NDArray[np.void]: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None = None,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[True],
+    autoconvert: bool = False,
+) -> np.recarray[_AnyShape, np.dtype[np.void]]: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None = None,
+    usemask: Literal[True] = True,
+    asrecarray: Literal[False] = False,
+    autoconvert: bool = False,
+) -> np.ma.MaskedArray[_AnyShape, np.dtype[np.void]]: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None,
+    usemask: Literal[True],
+    asrecarray: Literal[True],
+    autoconvert: bool = False,
+) -> MaskedRecords[_AnyShape, np.dtype[np.void]]: ...
+@overload
+def stack_arrays(
+    arrays: Sequence[npt.NDArray[Any]],
+    defaults: Mapping[str, Incomplete] | None = None,
+    usemask: Literal[True] = True,
+    *,
+    asrecarray: Literal[True],
+    autoconvert: bool = False,
+) -> MaskedRecords[_AnyShape, np.dtype[np.void]]: ...
+
+#
+@overload
+def find_duplicates(
+    a: np.ma.MaskedArray[_ShapeT, np.dtype[np.void]],
+    key: str | None = None,
+    ignoremask: bool = True,
+    return_index: Literal[False] = False,
+) -> np.ma.MaskedArray[_ShapeT, np.dtype[np.void]]: ...
+@overload
+def find_duplicates(
+    a: np.ma.MaskedArray[_ShapeT, np.dtype[np.void]],
+    key: str | None,
+    ignoremask: bool,
+    return_index: Literal[True],
+) -> tuple[np.ma.MaskedArray[_ShapeT, np.dtype[np.void]], np.ndarray[_ShapeT, np.dtype[np.int_]]]: ...
+@overload
+def find_duplicates(
+    a: np.ma.MaskedArray[_ShapeT, np.dtype[np.void]],
+    key: str | None = None,
+    ignoremask: bool = True,
+    *,
+    return_index: Literal[True],
+) -> tuple[np.ma.MaskedArray[_ShapeT, np.dtype[np.void]], np.ndarray[_ShapeT, np.dtype[np.int_]]]: ...
+
+#
+@overload
+def join_by(
+    key: str | Sequence[str],
+    r1: npt.NDArray[np.void],
+    r2: npt.NDArray[np.void],
+    jointype: _JoinType = "inner",
+    r1postfix: str = "1",
+    r2postfix: str = "2",
+    defaults: Mapping[str, object] | None = None,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[False] = False,
+) -> np.ndarray[tuple[int], np.dtype[np.void]]: ...
+@overload
+def join_by(
+    key: str | Sequence[str],
+    r1: npt.NDArray[np.void],
+    r2: npt.NDArray[np.void],
+    jointype: _JoinType = "inner",
+    r1postfix: str = "1",
+    r2postfix: str = "2",
+    defaults: Mapping[str, object] | None = None,
+    *,
+    usemask: Literal[False],
+    asrecarray: Literal[True],
+) -> np.recarray[tuple[int], np.dtype[np.void]]: ...
+@overload
+def join_by(
+    key: str | Sequence[str],
+    r1: npt.NDArray[np.void],
+    r2: npt.NDArray[np.void],
+    jointype: _JoinType = "inner",
+    r1postfix: str = "1",
+    r2postfix: str = "2",
+    defaults: Mapping[str, object] | None = None,
+    usemask: Literal[True] = True,
+    asrecarray: Literal[False] = False,
+) -> np.ma.MaskedArray[tuple[int], np.dtype[np.void]]: ...
+@overload
+def join_by(
+    key: str | Sequence[str],
+    r1: npt.NDArray[np.void],
+    r2: npt.NDArray[np.void],
+    jointype: _JoinType = "inner",
+    r1postfix: str = "1",
+    r2postfix: str = "2",
+    defaults: Mapping[str, object] | None = None,
+    usemask: Literal[True] = True,
+    *,
+    asrecarray: Literal[True],
+) -> MaskedRecords[tuple[int], np.dtype[np.void]]: ...
+
+#
+def rec_join(
+    key: str | Sequence[str],
+    r1: npt.NDArray[np.void],
+    r2: npt.NDArray[np.void],
+    jointype: _JoinType = "inner",
+    r1postfix: str = "1",
+    r2postfix: str = "2",
+    defaults: Mapping[str, object] | None = None,
+) -> np.recarray[tuple[int], np.dtype[np.void]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/scimath.py b/python/user_packages/Python313/site-packages/numpy/lib/scimath.py
new file mode 100644
index 0000000000000000000000000000000000000000..94175e1c800019a7b8954a6ad480c93ca210f5b6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/scimath.py
@@ -0,0 +1,13 @@
+from ._scimath_impl import (  # noqa: F401
+    __all__,
+    __doc__,
+    arccos,
+    arcsin,
+    arctanh,
+    log,
+    log2,
+    log10,
+    logn,
+    power,
+    sqrt,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/scimath.pyi b/python/user_packages/Python313/site-packages/numpy/lib/scimath.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..e45a10220c9bd0aae30aa270c84058c42f546dc4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/scimath.pyi
@@ -0,0 +1,12 @@
+from ._scimath_impl import (
+    __all__ as __all__,
+    arccos as arccos,
+    arcsin as arcsin,
+    arctanh as arctanh,
+    log as log,
+    log2 as log2,
+    log10 as log10,
+    logn as logn,
+    power as power,
+    sqrt as sqrt,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.py b/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.py
new file mode 100644
index 0000000000000000000000000000000000000000..36d7e507577860e159a27e6d1583a13a7c3f7133
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.py
@@ -0,0 +1 @@
+from ._stride_tricks_impl import __doc__, as_strided, sliding_window_view  # noqa: F401
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.pyi b/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..0f83c9b10d4d8c7bbfce0faae6488860921a8ded
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/stride_tricks.pyi
@@ -0,0 +1,4 @@
+from numpy.lib._stride_tricks_impl import (
+    as_strided as as_strided,
+    sliding_window_view as sliding_window_view,
+)
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/user_array.py b/python/user_packages/Python313/site-packages/numpy/lib/user_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..297a3b98eb65888807ba7da7a04467d0d8b060b7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/user_array.py
@@ -0,0 +1 @@
+from ._user_array_impl import __doc__, container  # noqa: F401
diff --git a/python/user_packages/Python313/site-packages/numpy/lib/user_array.pyi b/python/user_packages/Python313/site-packages/numpy/lib/user_array.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..1236b799bd411775484ca1ca308f457d0032797c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/lib/user_array.pyi
@@ -0,0 +1 @@
+from ._user_array_impl import container as container
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/__init__.py b/python/user_packages/Python313/site-packages/numpy/linalg/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..922989ace5dfc60cf9c067eb381ace0b1a28c227
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/__init__.py
@@ -0,0 +1,95 @@
+"""
+``numpy.linalg``
+================
+
+The NumPy linear algebra functions rely on BLAS and LAPACK to provide efficient
+low level implementations of standard linear algebra algorithms. Those
+libraries may be provided by NumPy itself using C versions of a subset of their
+reference implementations but, when possible, highly optimized libraries that
+take advantage of specialized processor functionality are preferred. Examples
+of such libraries are OpenBLAS, MKL (TM), and ATLAS. Because those libraries
+are multithreaded and processor dependent, environmental variables and external
+packages such as threadpoolctl may be needed to control the number of threads
+or specify the processor architecture.
+
+- OpenBLAS: https://www.openblas.net/
+- threadpoolctl: https://github.com/joblib/threadpoolctl
+
+Please note that the most-used linear algebra functions in NumPy are present in
+the main ``numpy`` namespace rather than in ``numpy.linalg``.  There are:
+``dot``, ``vdot``, ``inner``, ``outer``, ``matmul``, ``tensordot``, ``einsum``,
+``einsum_path`` and ``kron``.
+
+Functions present in numpy.linalg are listed below.
+
+
+Matrix and vector products
+--------------------------
+
+   cross
+   multi_dot
+   matrix_power
+   tensordot
+   matmul
+
+Decompositions
+--------------
+
+   cholesky
+   outer
+   qr
+   svd
+   svdvals
+
+Matrix eigenvalues
+------------------
+
+   eig
+   eigh
+   eigvals
+   eigvalsh
+
+Norms and other numbers
+-----------------------
+
+   norm
+   matrix_norm
+   vector_norm
+   cond
+   det
+   matrix_rank
+   slogdet
+   trace (Array API compatible)
+
+Solving equations and inverting matrices
+----------------------------------------
+
+   solve
+   tensorsolve
+   lstsq
+   inv
+   pinv
+   tensorinv
+
+Other matrix operations
+-----------------------
+
+   diagonal (Array API compatible)
+   matrix_transpose (Array API compatible)
+
+Exceptions
+----------
+
+   LinAlgError
+
+"""
+# To get sub-modules
+from . import _linalg
+from ._linalg import *
+
+__all__ = _linalg.__all__.copy()  # noqa: PLE0605
+
+from numpy._pytesttester import PytestTester
+
+test = PytestTester(__name__)
+del PytestTester
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/linalg/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..6e031b4232c42323eeb2620464bb8e7fade91f1d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/__init__.pyi
@@ -0,0 +1,71 @@
+from . import _linalg as _linalg, _umath_linalg as _umath_linalg
+from ._linalg import (
+    cholesky,
+    cond,
+    cross,
+    det,
+    diagonal,
+    eig,
+    eigh,
+    eigvals,
+    eigvalsh,
+    inv,
+    lstsq,
+    matmul,
+    matrix_norm,
+    matrix_power,
+    matrix_rank,
+    matrix_transpose,
+    multi_dot,
+    norm,
+    outer,
+    pinv,
+    qr,
+    slogdet,
+    solve,
+    svd,
+    svdvals,
+    tensordot,
+    tensorinv,
+    tensorsolve,
+    trace,
+    vecdot,
+    vector_norm,
+)
+
+__all__ = [
+    "LinAlgError",
+    "cholesky",
+    "cond",
+    "cross",
+    "det",
+    "diagonal",
+    "eig",
+    "eigh",
+    "eigvals",
+    "eigvalsh",
+    "inv",
+    "lstsq",
+    "matmul",
+    "matrix_norm",
+    "matrix_power",
+    "matrix_rank",
+    "matrix_transpose",
+    "multi_dot",
+    "norm",
+    "outer",
+    "pinv",
+    "qr",
+    "slogdet",
+    "solve",
+    "svd",
+    "svdvals",
+    "tensordot",
+    "tensorinv",
+    "tensorsolve",
+    "trace",
+    "vecdot",
+    "vector_norm",
+]
+
+class LinAlgError(ValueError): ...
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.py b/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.py
new file mode 100644
index 0000000000000000000000000000000000000000..937473721492c6195bc222a25aa9c5adc3f77967
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.py
@@ -0,0 +1,3657 @@
+"""Lite version of scipy.linalg.
+
+Notes
+-----
+This module is a lite version of the linalg.py module in SciPy which
+contains high-level Python interface to the LAPACK library.  The lite
+version only accesses the following LAPACK functions: dgesv, zgesv,
+dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetrf,
+zgetrf, dpotrf, zpotrf, dgeqrf, zgeqrf, zungqr, dorgqr.
+"""
+
+__all__ = ['matrix_power', 'solve', 'tensorsolve', 'tensorinv', 'inv',
+           'cholesky', 'eigvals', 'eigvalsh', 'pinv', 'slogdet', 'det',
+           'svd', 'svdvals', 'eig', 'eigh', 'lstsq', 'norm', 'qr', 'cond',
+           'matrix_rank', 'LinAlgError', 'multi_dot', 'trace', 'diagonal',
+           'cross', 'outer', 'tensordot', 'matmul', 'matrix_transpose',
+           'matrix_norm', 'vector_norm', 'vecdot']
+
+import functools
+import operator
+import warnings
+from typing import Any, NamedTuple
+
+from numpy._core import (
+    abs,
+    add,
+    all,
+    amax,
+    amin,
+    argsort,
+    array,
+    asanyarray,
+    asarray,
+    atleast_2d,
+    cdouble,
+    complexfloating,
+    count_nonzero,
+    cross as _core_cross,
+    csingle,
+    diagonal as _core_diagonal,
+    divide,
+    dot,
+    double,
+    empty,
+    empty_like,
+    errstate,
+    finfo,
+    inexact,
+    inf,
+    intc,
+    intp,
+    isfinite,
+    isnan,
+    matmul as _core_matmul,
+    matrix_transpose as _core_matrix_transpose,
+    moveaxis,
+    multiply,
+    newaxis,
+    object_,
+    outer as _core_outer,
+    overrides,
+    prod,
+    reciprocal,
+    sign,
+    single,
+    sort,
+    sqrt,
+    sum,
+    swapaxes,
+    tensordot as _core_tensordot,
+    trace as _core_trace,
+    transpose as _core_transpose,
+    vecdot as _core_vecdot,
+    zeros,
+)
+from numpy._globals import _NoValue
+from numpy._typing import NDArray
+from numpy._utils import set_module
+from numpy.lib._twodim_base_impl import eye, triu
+from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+from numpy.linalg import _umath_linalg
+
+
+class EigResult(NamedTuple):
+    eigenvalues: NDArray[Any]
+    eigenvectors: NDArray[Any]
+
+class EighResult(NamedTuple):
+    eigenvalues: NDArray[Any]
+    eigenvectors: NDArray[Any]
+
+class QRResult(NamedTuple):
+    Q: NDArray[Any]
+    R: NDArray[Any]
+
+class SlogdetResult(NamedTuple):
+    sign: NDArray[Any]
+    logabsdet: NDArray[Any]
+
+class SVDResult(NamedTuple):
+    U: NDArray[Any]
+    S: NDArray[Any]
+    Vh: NDArray[Any]
+
+
+array_function_dispatch = functools.partial(
+    overrides.array_function_dispatch, module='numpy.linalg'
+)
+
+
+fortran_int = intc
+
+
+@set_module('numpy.linalg')
+class LinAlgError(ValueError):
+    """
+    Generic Python-exception-derived object raised by linalg functions.
+
+    General purpose exception class, derived from Python's ValueError
+    class, programmatically raised in linalg functions when a Linear
+    Algebra-related condition would prevent further correct execution of the
+    function.
+
+    Parameters
+    ----------
+    None
+
+    Examples
+    --------
+    >>> from numpy import linalg as LA
+    >>> LA.inv(np.zeros((2,2)))
+    Traceback (most recent call last):
+      File "<stdin>", line 1, in <module>
+      File "...linalg.py", line 350,
+        in inv return wrap(solve(a, identity(a.shape[0], dtype=a.dtype)))
+      File "...linalg.py", line 249,
+        in solve
+        raise LinAlgError('Singular matrix')
+    numpy.linalg.LinAlgError: Singular matrix
+
+    """
+
+
+def _raise_linalgerror_singular(err, flag):
+    raise LinAlgError("Singular matrix")
+
+def _raise_linalgerror_nonposdef(err, flag):
+    raise LinAlgError("Matrix is not positive definite")
+
+def _raise_linalgerror_eigenvalues_nonconvergence(err, flag):
+    raise LinAlgError("Eigenvalues did not converge")
+
+def _raise_linalgerror_svd_nonconvergence(err, flag):
+    raise LinAlgError("SVD did not converge")
+
+def _raise_linalgerror_lstsq(err, flag):
+    raise LinAlgError("SVD did not converge in Linear Least Squares")
+
+def _raise_linalgerror_qr(err, flag):
+    raise LinAlgError("Incorrect argument found while performing "
+                      "QR factorization")
+
+
+def _makearray(a):
+    new = asarray(a)
+    wrap = getattr(a, "__array_wrap__", new.__array_wrap__)
+    return new, wrap
+
+def isComplexType(t):
+    return issubclass(t, complexfloating)
+
+
+_real_types_map = {single: single,
+                   double: double,
+                   csingle: single,
+                   cdouble: double}
+
+_complex_types_map = {single: csingle,
+                      double: cdouble,
+                      csingle: csingle,
+                      cdouble: cdouble}
+
+def _realType(t, default=double):
+    return _real_types_map.get(t, default)
+
+def _complexType(t, default=cdouble):
+    return _complex_types_map.get(t, default)
+
+def _commonType(*arrays):
+    # in lite version, use higher precision (always double or cdouble)
+    result_type = single
+    is_complex = False
+    for a in arrays:
+        type_ = a.dtype.type
+        if issubclass(type_, inexact):
+            if isComplexType(type_):
+                is_complex = True
+            rt = _realType(type_, default=None)
+            if rt is double:
+                result_type = double
+            elif rt is None:
+                # unsupported inexact scalar
+                raise TypeError(f"array type {a.dtype.name} is unsupported in linalg")
+        else:
+            result_type = double
+    if is_complex:
+        result_type = _complex_types_map[result_type]
+        return cdouble, result_type
+    else:
+        return double, result_type
+
+
+def _to_native_byte_order(*arrays):
+    ret = []
+    for arr in arrays:
+        if arr.dtype.byteorder not in ('=', '|'):
+            ret.append(asarray(arr, dtype=arr.dtype.newbyteorder('=')))
+        else:
+            ret.append(arr)
+    if len(ret) == 1:
+        return ret[0]
+    else:
+        return ret
+
+
+def _assert_2d(*arrays):
+    for a in arrays:
+        if a.ndim != 2:
+            raise LinAlgError('%d-dimensional array given. Array must be '
+                    'two-dimensional' % a.ndim)
+
+def _assert_stacked_2d(*arrays):
+    for a in arrays:
+        if a.ndim < 2:
+            raise LinAlgError('%d-dimensional array given. Array must be '
+                    'at least two-dimensional' % a.ndim)
+
+def _assert_stacked_square(*arrays):
+    for a in arrays:
+        try:
+            m, n = a.shape[-2:]
+        except ValueError:
+            raise LinAlgError('%d-dimensional array given. Array must be '
+                    'at least two-dimensional' % a.ndim)
+        if m != n:
+            raise LinAlgError('Last 2 dimensions of the array must be square')
+
+def _assert_finite(*arrays):
+    for a in arrays:
+        if not isfinite(a).all():
+            raise LinAlgError("Array must not contain infs or NaNs")
+
+def _is_empty_2d(arr):
+    # check size first for efficiency
+    return arr.size == 0 and prod(arr.shape[-2:]) == 0
+
+
+def transpose(a):
+    """
+    Transpose each matrix in a stack of matrices.
+
+    Unlike np.transpose, this only swaps the last two axes, rather than all of
+    them
+
+    Parameters
+    ----------
+    a : (...,M,N) array_like
+
+    Returns
+    -------
+    aT : (...,N,M) ndarray
+    """
+    return swapaxes(a, -1, -2)
+
+# Linear equations
+
+def _tensorsolve_dispatcher(a, b, axes=None):
+    return (a, b)
+
+
+@array_function_dispatch(_tensorsolve_dispatcher)
+def tensorsolve(a, b, axes=None):
+    """
+    Solve the tensor equation ``a x = b`` for x.
+
+    It is assumed that all indices of `x` are summed over in the product,
+    together with the rightmost indices of `a`, as is done in, for example,
+    ``tensordot(a, x, axes=x.ndim)``.
+
+    Parameters
+    ----------
+    a : array_like
+        Coefficient tensor, of shape ``b.shape + Q``. `Q`, a tuple, equals
+        the shape of that sub-tensor of `a` consisting of the appropriate
+        number of its rightmost indices, and must be such that
+        ``prod(Q) == prod(b.shape)`` (in which sense `a` is said to be
+        'square').
+    b : array_like
+        Right-hand tensor, which can be of any shape.
+    axes : tuple of ints, optional
+        Axes in `a` to reorder to the right, before inversion.
+        If None (default), no reordering is done.
+
+    Returns
+    -------
+    x : ndarray, shape Q
+
+    Raises
+    ------
+    LinAlgError
+        If `a` is singular or not 'square' (in the above sense).
+
+    See Also
+    --------
+    numpy.tensordot, tensorinv, numpy.einsum
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.eye(2*3*4).reshape((2*3, 4, 2, 3, 4))
+    >>> rng = np.random.default_rng()
+    >>> b = rng.normal(size=(2*3, 4))
+    >>> x = np.linalg.tensorsolve(a, b)
+    >>> x.shape
+    (2, 3, 4)
+    >>> np.allclose(np.tensordot(a, x, axes=3), b)
+    True
+
+    """
+    a, wrap = _makearray(a)
+    b = asarray(b)
+    an = a.ndim
+
+    if axes is not None:
+        allaxes = list(range(an))
+        for k in axes:
+            allaxes.remove(k)
+            allaxes.insert(an, k)
+        a = a.transpose(allaxes)
+
+    oldshape = a.shape[-(an - b.ndim):]
+    prod = 1
+    for k in oldshape:
+        prod *= k
+
+    if a.size != prod ** 2:
+        raise LinAlgError(
+            "Input arrays must satisfy the requirement \
+            prod(a.shape[b.ndim:]) == prod(a.shape[:b.ndim])"
+        )
+
+    a = a.reshape(prod, prod)
+    b = b.ravel()
+    res = wrap(solve(a, b))
+    res.shape = oldshape
+    return res
+
+
+def _solve_dispatcher(a, b):
+    return (a, b)
+
+
+@array_function_dispatch(_solve_dispatcher)
+def solve(a, b):
+    """
+    Solve a linear matrix equation, or system of linear scalar equations.
+
+    Computes the "exact" solution, `x`, of the well-determined, i.e., full
+    rank, linear matrix equation `ax = b`.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Coefficient matrix.
+    b : {(M,), (..., M, K)}, array_like
+        Ordinate or "dependent variable" values.
+
+    Returns
+    -------
+    x : {(..., M,), (..., M, K)} ndarray
+        Solution to the system a x = b.  Returned shape is (..., M) if b is
+        shape (M,) and (..., M, K) if b is (..., M, K), where the "..." part is
+        broadcasted between a and b.
+
+    Raises
+    ------
+    LinAlgError
+        If `a` is singular or not square.
+
+    See Also
+    --------
+    scipy.linalg.solve : Similar function in SciPy.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The solutions are computed using LAPACK routine ``_gesv``.
+
+    `a` must be square and of full-rank, i.e., all rows (or, equivalently,
+    columns) must be linearly independent; if either is not true, use
+    `lstsq` for the least-squares best "solution" of the
+    system/equation.
+
+    .. versionchanged:: 2.0
+
+       The b array is only treated as a shape (M,) column vector if it is
+       exactly 1-dimensional. In all other instances it is treated as a stack
+       of (M, K) matrices. Previously b would be treated as a stack of (M,)
+       vectors if b.ndim was equal to a.ndim - 1.
+
+    References
+    ----------
+    .. [1] G. Strang, *Linear Algebra and Its Applications*, 2nd Ed., Orlando,
+           FL, Academic Press, Inc., 1980, pg. 22.
+
+    Examples
+    --------
+    Solve the system of equations:
+    ``x0 + 2 * x1 = 1`` and
+    ``3 * x0 + 5 * x1 = 2``:
+
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, 5]])
+    >>> b = np.array([1, 2])
+    >>> x = np.linalg.solve(a, b)
+    >>> x
+    array([-1.,  1.])
+
+    Check that the solution is correct:
+
+    >>> np.allclose(np.dot(a, x), b)
+    True
+
+    """
+    a, _ = _makearray(a)
+    _assert_stacked_square(a)
+    b, wrap = _makearray(b)
+    t, result_t = _commonType(a, b)
+
+    # We use the b = (..., M,) logic, only if the number of extra dimensions
+    # match exactly
+    if b.ndim == 1:
+        gufunc = _umath_linalg.solve1
+    else:
+        gufunc = _umath_linalg.solve
+
+    signature = 'DD->D' if isComplexType(t) else 'dd->d'
+    with errstate(call=_raise_linalgerror_singular, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        r = gufunc(a, b, signature=signature)
+
+    return wrap(r.astype(result_t, copy=False))
+
+
+def _tensorinv_dispatcher(a, ind=None):
+    return (a,)
+
+
+@array_function_dispatch(_tensorinv_dispatcher)
+def tensorinv(a, ind=2):
+    """
+    Compute the 'inverse' of an N-dimensional array.
+
+    The result is an inverse for `a` relative to the tensordot operation
+    ``tensordot(a, b, ind)``, i. e., up to floating-point accuracy,
+    ``tensordot(tensorinv(a), a, ind)`` is the "identity" tensor for the
+    tensordot operation.
+
+    Parameters
+    ----------
+    a : array_like
+        Tensor to 'invert'. Its shape must be 'square', i. e.,
+        ``prod(a.shape[:ind]) == prod(a.shape[ind:])``.
+    ind : int, optional
+        Number of first indices that are involved in the inverse sum.
+        Must be a positive integer, default is 2.
+
+    Returns
+    -------
+    b : ndarray
+        `a`'s tensordot inverse, shape ``a.shape[ind:] + a.shape[:ind]``.
+
+    Raises
+    ------
+    LinAlgError
+        If `a` is singular or not 'square' (in the above sense).
+
+    See Also
+    --------
+    numpy.tensordot, tensorsolve
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.eye(4*6).reshape((4, 6, 8, 3))
+    >>> ainv = np.linalg.tensorinv(a, ind=2)
+    >>> ainv.shape
+    (8, 3, 4, 6)
+    >>> rng = np.random.default_rng()
+    >>> b = rng.normal(size=(4, 6))
+    >>> np.allclose(np.tensordot(ainv, b), np.linalg.tensorsolve(a, b))
+    True
+
+    >>> a = np.eye(4*6).reshape((24, 8, 3))
+    >>> ainv = np.linalg.tensorinv(a, ind=1)
+    >>> ainv.shape
+    (8, 3, 24)
+    >>> rng = np.random.default_rng()
+    >>> b = rng.normal(size=24)
+    >>> np.allclose(np.tensordot(ainv, b, 1), np.linalg.tensorsolve(a, b))
+    True
+
+    """
+    a = asarray(a)
+    oldshape = a.shape
+    prod = 1
+    if ind > 0:
+        invshape = oldshape[ind:] + oldshape[:ind]
+        for k in oldshape[ind:]:
+            prod *= k
+    else:
+        raise ValueError("Invalid ind argument.")
+    a = a.reshape(prod, -1)
+    ia = inv(a)
+    return ia.reshape(*invshape)
+
+
+# Matrix inversion
+
+def _unary_dispatcher(a):
+    return (a,)
+
+
+@array_function_dispatch(_unary_dispatcher)
+def inv(a):
+    """
+    Compute the inverse of a matrix.
+
+    Given a square matrix `a`, return the matrix `ainv` satisfying
+    ``a @ ainv = ainv @ a = eye(a.shape[0])``.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Matrix to be inverted.
+
+    Returns
+    -------
+    ainv : (..., M, M) ndarray or matrix
+        Inverse of the matrix `a`.
+
+    Raises
+    ------
+    LinAlgError
+        If `a` is not square or inversion fails.
+
+    See Also
+    --------
+    scipy.linalg.inv : Similar function in SciPy.
+    numpy.linalg.cond : Compute the condition number of a matrix.
+    numpy.linalg.svd : Compute the singular value decomposition of a matrix.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    If `a` is detected to be singular, a `LinAlgError` is raised. If `a` is
+    ill-conditioned, a `LinAlgError` may or may not be raised, and results may
+    be inaccurate due to floating-point errors.
+
+    References
+    ----------
+    .. [1] Wikipedia, "Condition number",
+           https://en.wikipedia.org/wiki/Condition_number
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.linalg import inv
+    >>> a = np.array([[1., 2.], [3., 4.]])
+    >>> ainv = inv(a)
+    >>> np.allclose(a @ ainv, np.eye(2))
+    True
+    >>> np.allclose(ainv @ a, np.eye(2))
+    True
+
+    If a is a matrix object, then the return value is a matrix as well:
+
+    >>> ainv = inv(np.matrix(a))
+    >>> ainv
+    matrix([[-2. ,  1. ],
+            [ 1.5, -0.5]])
+
+    Inverses of several matrices can be computed at once:
+
+    >>> a = np.array([[[1., 2.], [3., 4.]], [[1, 3], [3, 5]]])
+    >>> inv(a)
+    array([[[-2.  ,  1.  ],
+            [ 1.5 , -0.5 ]],
+           [[-1.25,  0.75],
+            [ 0.75, -0.25]]])
+
+    If a matrix is close to singular, the computed inverse may not satisfy
+    ``a @ ainv = ainv @ a = eye(a.shape[0])`` even if a `LinAlgError`
+    is not raised:
+
+    >>> a = np.array([[2,4,6],[2,0,2],[6,8,14]])
+    >>> inv(a)  # No errors raised
+    array([[-1.12589991e+15, -5.62949953e+14,  5.62949953e+14],
+       [-1.12589991e+15, -5.62949953e+14,  5.62949953e+14],
+       [ 1.12589991e+15,  5.62949953e+14, -5.62949953e+14]])
+    >>> a @ inv(a)
+    array([[ 0.   , -0.5  ,  0.   ],  # may vary
+           [-0.5  ,  0.625,  0.25 ],
+           [ 0.   ,  0.   ,  1.   ]])
+
+    To detect ill-conditioned matrices, you can use `numpy.linalg.cond` to
+    compute its *condition number* [1]_. The larger the condition number, the
+    more ill-conditioned the matrix is. As a rule of thumb, if the condition
+    number ``cond(a) = 10**k``, then you may lose up to ``k`` digits of
+    accuracy on top of what would be lost to the numerical method due to loss
+    of precision from arithmetic methods.
+
+    >>> from numpy.linalg import cond
+    >>> cond(a)
+    np.float64(8.659885634118668e+17)  # may vary
+
+    It is also possible to detect ill-conditioning by inspecting the matrix's
+    singular values directly. The ratio between the largest and the smallest
+    singular value is the condition number:
+
+    >>> from numpy.linalg import svd
+    >>> sigma = svd(a, compute_uv=False)  # Do not compute singular vectors
+    >>> sigma.max()/sigma.min()
+    8.659885634118668e+17  # may vary
+
+    """
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    with errstate(call=_raise_linalgerror_singular, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        ainv = _umath_linalg.inv(a, signature=signature)
+    return wrap(ainv.astype(result_t, copy=False))
+
+
+def _matrix_power_dispatcher(a, n):
+    return (a,)
+
+
+@array_function_dispatch(_matrix_power_dispatcher)
+def matrix_power(a, n):
+    """
+    Raise a square matrix to the (integer) power `n`.
+
+    For positive integers `n`, the power is computed by repeated matrix
+    squarings and matrix multiplications. If ``n == 0``, the identity matrix
+    of the same shape as M is returned. If ``n < 0``, the inverse
+    is computed and then raised to the ``abs(n)``.
+
+    .. note:: Stacks of object matrices are not currently supported.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Matrix to be "powered".
+    n : int
+        The exponent can be any integer or long integer, positive,
+        negative, or zero.
+
+    Returns
+    -------
+    a**n : (..., M, M) ndarray or matrix object
+        The return value is the same shape and type as `M`;
+        if the exponent is positive or zero then the type of the
+        elements is the same as those of `M`. If the exponent is
+        negative the elements are floating-point.
+
+    Raises
+    ------
+    LinAlgError
+        For matrices that are not square or that (for negative powers) cannot
+        be inverted numerically.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.linalg import matrix_power
+    >>> i = np.array([[0, 1], [-1, 0]]) # matrix equiv. of the imaginary unit
+    >>> matrix_power(i, 3) # should = -i
+    array([[ 0, -1],
+           [ 1,  0]])
+    >>> matrix_power(i, 0)
+    array([[1, 0],
+           [0, 1]])
+    >>> matrix_power(i, -3) # should = 1/(-i) = i, but w/ f.p. elements
+    array([[ 0.,  1.],
+           [-1.,  0.]])
+
+    Somewhat more sophisticated example
+
+    >>> q = np.zeros((4, 4))
+    >>> q[0:2, 0:2] = -i
+    >>> q[2:4, 2:4] = i
+    >>> q # one of the three quaternion units not equal to 1
+    array([[ 0., -1.,  0.,  0.],
+           [ 1.,  0.,  0.,  0.],
+           [ 0.,  0.,  0.,  1.],
+           [ 0.,  0., -1.,  0.]])
+    >>> matrix_power(q, 2) # = -np.eye(4)
+    array([[-1.,  0.,  0.,  0.],
+           [ 0., -1.,  0.,  0.],
+           [ 0.,  0., -1.,  0.],
+           [ 0.,  0.,  0., -1.]])
+
+    """
+    a = asanyarray(a)
+    _assert_stacked_square(a)
+
+    try:
+        n = operator.index(n)
+    except TypeError as e:
+        raise TypeError("exponent must be an integer") from e
+
+    # Fall back on dot for object arrays. Object arrays are not supported by
+    # the current implementation of matmul using einsum
+    if a.dtype != object:
+        fmatmul = matmul
+    elif a.ndim == 2:
+        fmatmul = dot
+    else:
+        raise NotImplementedError(
+            "matrix_power not supported for stacks of object arrays")
+
+    if n == 0:
+        a = empty_like(a)
+        a[...] = eye(a.shape[-2], dtype=a.dtype)
+        return a
+
+    elif n < 0:
+        a = inv(a)
+        n = abs(n)
+
+    # short-cuts.
+    if n == 1:
+        return a
+
+    elif n == 2:
+        return fmatmul(a, a)
+
+    elif n == 3:
+        return fmatmul(fmatmul(a, a), a)
+
+    # Use binary decomposition to reduce the number of matrix multiplications.
+    # Here, we iterate over the bits of n, from LSB to MSB, raise `a` to
+    # increasing powers of 2, and multiply into the result as needed.
+    z = result = None
+    while n > 0:
+        z = a if z is None else fmatmul(z, z)
+        n, bit = divmod(n, 2)
+        if bit:
+            result = z if result is None else fmatmul(result, z)
+
+    return result
+
+
+# Cholesky decomposition
+
+def _cholesky_dispatcher(a, /, *, upper=None):
+    return (a,)
+
+
+@array_function_dispatch(_cholesky_dispatcher)
+def cholesky(a, /, *, upper=False):
+    """
+    Cholesky decomposition.
+
+    Return the lower or upper Cholesky decomposition, ``L * L.H`` or
+    ``U.H * U``, of the square matrix ``a``, where ``L`` is lower-triangular,
+    ``U`` is upper-triangular, and ``.H`` is the conjugate transpose operator
+    (which is the ordinary transpose if ``a`` is real-valued). ``a`` must be
+    Hermitian (symmetric if real-valued) and positive-definite. No checking is
+    performed to verify whether ``a`` is Hermitian or not. In addition, only
+    the lower or upper-triangular and diagonal elements of ``a`` are used.
+    Only ``L`` or ``U`` is actually returned.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Hermitian (symmetric if all elements are real), positive-definite
+        input matrix.
+    upper : bool
+        If ``True``, the result must be the upper-triangular Cholesky factor.
+        If ``False``, the result must be the lower-triangular Cholesky factor.
+        Default: ``False``.
+
+    Returns
+    -------
+    L : (..., M, M) array_like
+        Lower or upper-triangular Cholesky factor of `a`. Returns a matrix
+        object if `a` is a matrix object.
+
+    Raises
+    ------
+    LinAlgError
+       If the decomposition fails, for example, if `a` is not
+       positive-definite.
+
+    See Also
+    --------
+    scipy.linalg.cholesky : Similar function in SciPy.
+    scipy.linalg.cholesky_banded : Cholesky decompose a banded Hermitian
+                                   positive-definite matrix.
+    scipy.linalg.cho_factor : Cholesky decomposition of a matrix, to use in
+                              `scipy.linalg.cho_solve`.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The Cholesky decomposition is often used as a fast way of solving
+
+    .. math:: A \\mathbf{x} = \\mathbf{b}
+
+    (when `A` is both Hermitian/symmetric and positive-definite).
+
+    First, we solve for :math:`\\mathbf{y}` in
+
+    .. math:: L \\mathbf{y} = \\mathbf{b},
+
+    and then for :math:`\\mathbf{x}` in
+
+    .. math:: L^{H} \\mathbf{x} = \\mathbf{y}.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> A = np.array([[1,-2j],[2j,5]])
+    >>> A
+    array([[ 1.+0.j, -0.-2.j],
+           [ 0.+2.j,  5.+0.j]])
+    >>> L = np.linalg.cholesky(A)
+    >>> L
+    array([[1.+0.j, 0.+0.j],
+           [0.+2.j, 1.+0.j]])
+    >>> np.dot(L, L.T.conj()) # verify that L * L.H = A
+    array([[1.+0.j, 0.-2.j],
+           [0.+2.j, 5.+0.j]])
+    >>> A = [[1,-2j],[2j,5]] # what happens if A is only array_like?
+    >>> np.linalg.cholesky(A) # an ndarray object is returned
+    array([[1.+0.j, 0.+0.j],
+           [0.+2.j, 1.+0.j]])
+    >>> # But a matrix object is returned if A is a matrix object
+    >>> np.linalg.cholesky(np.matrix(A))
+    matrix([[ 1.+0.j,  0.+0.j],
+            [ 0.+2.j,  1.+0.j]])
+    >>> # The upper-triangular Cholesky factor can also be obtained.
+    >>> np.linalg.cholesky(A, upper=True)
+    array([[1.-0.j, 0.-2.j],
+           [0.-0.j, 1.-0.j]])
+
+    """
+    gufunc = _umath_linalg.cholesky_up if upper else _umath_linalg.cholesky_lo
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    with errstate(call=_raise_linalgerror_nonposdef, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        r = gufunc(a, signature=signature)
+    return wrap(r.astype(result_t, copy=False))
+
+
+# outer product
+
+
+def _outer_dispatcher(x1, x2):
+    return (x1, x2)
+
+
+@array_function_dispatch(_outer_dispatcher)
+def outer(x1, x2, /):
+    """
+    Compute the outer product of two vectors.
+
+    This function is Array API compatible. Compared to ``np.outer``
+    it accepts 1-dimensional inputs only.
+
+    Parameters
+    ----------
+    x1 : (M,) array_like
+        One-dimensional input array of size ``N``.
+        Must have a numeric data type.
+    x2 : (N,) array_like
+        One-dimensional input array of size ``M``.
+        Must have a numeric data type.
+
+    Returns
+    -------
+    out : (M, N) ndarray
+        ``out[i, j] = a[i] * b[j]``
+
+    See also
+    --------
+    outer
+
+    Examples
+    --------
+    Make a (*very* coarse) grid for computing a Mandelbrot set:
+
+    >>> rl = np.linalg.outer(np.ones((5,)), np.linspace(-2, 2, 5))
+    >>> rl
+    array([[-2., -1.,  0.,  1.,  2.],
+           [-2., -1.,  0.,  1.,  2.],
+           [-2., -1.,  0.,  1.,  2.],
+           [-2., -1.,  0.,  1.,  2.],
+           [-2., -1.,  0.,  1.,  2.]])
+    >>> im = np.linalg.outer(1j*np.linspace(2, -2, 5), np.ones((5,)))
+    >>> im
+    array([[0.+2.j, 0.+2.j, 0.+2.j, 0.+2.j, 0.+2.j],
+           [0.+1.j, 0.+1.j, 0.+1.j, 0.+1.j, 0.+1.j],
+           [0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
+           [0.-1.j, 0.-1.j, 0.-1.j, 0.-1.j, 0.-1.j],
+           [0.-2.j, 0.-2.j, 0.-2.j, 0.-2.j, 0.-2.j]])
+    >>> grid = rl + im
+    >>> grid
+    array([[-2.+2.j, -1.+2.j,  0.+2.j,  1.+2.j,  2.+2.j],
+           [-2.+1.j, -1.+1.j,  0.+1.j,  1.+1.j,  2.+1.j],
+           [-2.+0.j, -1.+0.j,  0.+0.j,  1.+0.j,  2.+0.j],
+           [-2.-1.j, -1.-1.j,  0.-1.j,  1.-1.j,  2.-1.j],
+           [-2.-2.j, -1.-2.j,  0.-2.j,  1.-2.j,  2.-2.j]])
+
+    An example using a "vector" of letters:
+
+    >>> x = np.array(['a', 'b', 'c'], dtype=object)
+    >>> np.linalg.outer(x, [1, 2, 3])
+    array([['a', 'aa', 'aaa'],
+           ['b', 'bb', 'bbb'],
+           ['c', 'cc', 'ccc']], dtype=object)
+
+    """
+    x1 = asanyarray(x1)
+    x2 = asanyarray(x2)
+    if x1.ndim != 1 or x2.ndim != 1:
+        raise ValueError(
+            "Input arrays must be one-dimensional, but they are "
+            f"{x1.ndim=} and {x2.ndim=}."
+        )
+    return _core_outer(x1, x2, out=None)
+
+
+# QR decomposition
+
+
+def _qr_dispatcher(a, mode=None):
+    return (a,)
+
+
+@array_function_dispatch(_qr_dispatcher)
+def qr(a, mode='reduced'):
+    """
+    Compute the qr factorization of a matrix.
+
+    Factor the matrix `a` as *qr*, where `q` is orthonormal and `r` is
+    upper-triangular.
+
+    Parameters
+    ----------
+    a : array_like, shape (..., M, N)
+        An array-like object with the dimensionality of at least 2.
+    mode : {'reduced', 'complete', 'r', 'raw'}, optional, default: 'reduced'
+        If K = min(M, N), then
+
+        * 'reduced'  : returns Q, R with dimensions (..., M, K), (..., K, N)
+        * 'complete' : returns Q, R with dimensions (..., M, M), (..., M, N)
+        * 'r'        : returns R only with dimensions (..., K, N)
+        * 'raw'      : returns h, tau with dimensions (..., N, M), (..., K,)
+
+        The options 'reduced', 'complete, and 'raw' are new in numpy 1.8,
+        see the notes for more information. The default is 'reduced', and to
+        maintain backward compatibility with earlier versions of numpy both
+        it and the old default 'full' can be omitted. Note that array h
+        returned in 'raw' mode is transposed for calling Fortran. The
+        'economic' mode is deprecated.  The modes 'full' and 'economic' may
+        be passed using only the first letter for backwards compatibility,
+        but all others must be spelled out. See the Notes for more
+        explanation.
+
+
+    Returns
+    -------
+    Q : ndarray of float or complex, optional
+        A matrix with orthonormal columns. When mode = 'complete' the
+        result is an orthogonal/unitary matrix depending on whether or not
+        a is real/complex. The determinant may be either +/- 1 in that
+        case. In case the number of dimensions in the input array is
+        greater than 2 then a stack of the matrices with above properties
+        is returned.
+    R : ndarray of float or complex, optional
+        The upper-triangular matrix or a stack of upper-triangular
+        matrices if the number of dimensions in the input array is greater
+        than 2.
+    (h, tau) : ndarrays of np.double or np.cdouble, optional
+        The array h contains the Householder reflectors that generate q
+        along with r. The tau array contains scaling factors for the
+        reflectors. In the deprecated  'economic' mode only h is returned.
+
+    Raises
+    ------
+    LinAlgError
+        If factoring fails.
+
+    See Also
+    --------
+    scipy.linalg.qr : Similar function in SciPy.
+    scipy.linalg.rq : Compute RQ decomposition of a matrix.
+
+    Notes
+    -----
+    When mode is 'reduced' or 'complete', the result will be a namedtuple with
+    the attributes ``Q`` and ``R``.
+
+    This is an interface to the LAPACK routines ``dgeqrf``, ``zgeqrf``,
+    ``dorgqr``, and ``zungqr``.
+
+    For more information on the qr factorization, see for example:
+    https://en.wikipedia.org/wiki/QR_factorization
+
+    Subclasses of `ndarray` are preserved except for the 'raw' mode. So if
+    `a` is of type `matrix`, all the return values will be matrices too.
+
+    New 'reduced', 'complete', and 'raw' options for mode were added in
+    NumPy 1.8.0 and the old option 'full' was made an alias of 'reduced'.  In
+    addition the options 'full' and 'economic' were deprecated.  Because
+    'full' was the previous default and 'reduced' is the new default,
+    backward compatibility can be maintained by letting `mode` default.
+    The 'raw' option was added so that LAPACK routines that can multiply
+    arrays by q using the Householder reflectors can be used. Note that in
+    this case the returned arrays are of type np.double or np.cdouble and
+    the h array is transposed to be FORTRAN compatible.  No routines using
+    the 'raw' return are currently exposed by numpy, but some are available
+    in lapack_lite and just await the necessary work.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> rng = np.random.default_rng()
+    >>> a = rng.normal(size=(9, 6))
+    >>> Q, R = np.linalg.qr(a)
+    >>> np.allclose(a, np.dot(Q, R))  # a does equal QR
+    True
+    >>> R2 = np.linalg.qr(a, mode='r')
+    >>> np.allclose(R, R2)  # mode='r' returns the same R as mode='full'
+    True
+    >>> a = np.random.normal(size=(3, 2, 2)) # Stack of 2 x 2 matrices as input
+    >>> Q, R = np.linalg.qr(a)
+    >>> Q.shape
+    (3, 2, 2)
+    >>> R.shape
+    (3, 2, 2)
+    >>> np.allclose(a, np.matmul(Q, R))
+    True
+
+    Example illustrating a common use of `qr`: solving of least squares
+    problems
+
+    What are the least-squares-best `m` and `y0` in ``y = y0 + mx`` for
+    the following data: {(0,1), (1,0), (1,2), (2,1)}. (Graph the points
+    and you'll see that it should be y0 = 0, m = 1.)  The answer is provided
+    by solving the over-determined matrix equation ``Ax = b``, where::
+
+      A = array([[0, 1], [1, 1], [1, 1], [2, 1]])
+      x = array([[y0], [m]])
+      b = array([[1], [0], [2], [1]])
+
+    If A = QR such that Q is orthonormal (which is always possible via
+    Gram-Schmidt), then ``x = inv(R) * (Q.T) * b``.  (In numpy practice,
+    however, we simply use `lstsq`.)
+
+    >>> A = np.array([[0, 1], [1, 1], [1, 1], [2, 1]])
+    >>> A
+    array([[0, 1],
+           [1, 1],
+           [1, 1],
+           [2, 1]])
+    >>> b = np.array([1, 2, 2, 3])
+    >>> Q, R = np.linalg.qr(A)
+    >>> p = np.dot(Q.T, b)
+    >>> np.dot(np.linalg.inv(R), p)
+    array([  1.,   1.])
+
+    """
+    if mode not in ('reduced', 'complete', 'r', 'raw'):
+        if mode in ('f', 'full'):
+            # 2013-04-01, 1.8
+            msg = (
+                "The 'full' option is deprecated in favor of 'reduced'.\n"
+                "For backward compatibility let mode default."
+            )
+            warnings.warn(msg, DeprecationWarning, stacklevel=2)
+            mode = 'reduced'
+        elif mode in ('e', 'economic'):
+            # 2013-04-01, 1.8
+            msg = "The 'economic' option is deprecated."
+            warnings.warn(msg, DeprecationWarning, stacklevel=2)
+            mode = 'economic'
+        else:
+            raise ValueError(f"Unrecognized mode '{mode}'")
+
+    a, wrap = _makearray(a)
+    _assert_stacked_2d(a)
+    m, n = a.shape[-2:]
+    t, result_t = _commonType(a)
+    a = a.astype(t, copy=True)
+    a = _to_native_byte_order(a)
+    mn = min(m, n)
+
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    with errstate(call=_raise_linalgerror_qr, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        tau = _umath_linalg.qr_r_raw(a, signature=signature)
+
+    # handle modes that don't return q
+    if mode == 'r':
+        r = triu(a[..., :mn, :])
+        r = r.astype(result_t, copy=False)
+        return wrap(r)
+
+    if mode == 'raw':
+        q = transpose(a)
+        q = q.astype(result_t, copy=False)
+        tau = tau.astype(result_t, copy=False)
+        return wrap(q), tau
+
+    if mode == 'economic':
+        a = a.astype(result_t, copy=False)
+        return wrap(a)
+
+    # mc is the number of columns in the resulting q
+    # matrix. If the mode is complete then it is
+    # same as number of rows, and if the mode is reduced,
+    # then it is the minimum of number of rows and columns.
+    if mode == 'complete' and m > n:
+        mc = m
+        gufunc = _umath_linalg.qr_complete
+    else:
+        mc = mn
+        gufunc = _umath_linalg.qr_reduced
+
+    signature = 'DD->D' if isComplexType(t) else 'dd->d'
+    with errstate(call=_raise_linalgerror_qr, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        q = gufunc(a, tau, signature=signature)
+    r = triu(a[..., :mc, :])
+
+    q = q.astype(result_t, copy=False)
+    r = r.astype(result_t, copy=False)
+
+    return QRResult(wrap(q), wrap(r))
+
+# Eigenvalues
+
+
+@array_function_dispatch(_unary_dispatcher)
+def eigvals(a):
+    """
+    Compute the eigenvalues of a general matrix.
+
+    Main difference between `eigvals` and `eig`: the eigenvectors aren't
+    returned.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        A complex- or real-valued matrix whose eigenvalues will be computed.
+
+    Returns
+    -------
+    w : (..., M,) ndarray
+        The eigenvalues, each repeated according to its multiplicity.
+        They are not necessarily ordered, nor are they necessarily
+        real for real matrices.
+
+    Raises
+    ------
+    LinAlgError
+        If the eigenvalue computation does not converge.
+
+    See Also
+    --------
+    eig : eigenvalues and right eigenvectors of general arrays
+    eigvalsh : eigenvalues of real symmetric or complex Hermitian
+               (conjugate symmetric) arrays.
+    eigh : eigenvalues and eigenvectors of real symmetric or complex
+           Hermitian (conjugate symmetric) arrays.
+    scipy.linalg.eigvals : Similar function in SciPy.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    This is implemented using the ``_geev`` LAPACK routines which compute
+    the eigenvalues and eigenvectors of general square arrays.
+
+    Examples
+    --------
+    Illustration, using the fact that the eigenvalues of a diagonal matrix
+    are its diagonal elements, that multiplying a matrix on the left
+    by an orthogonal matrix, `Q`, and on the right by `Q.T` (the transpose
+    of `Q`), preserves the eigenvalues of the "middle" matrix. In other words,
+    if `Q` is orthogonal, then ``Q * A * Q.T`` has the same eigenvalues as
+    ``A``:
+
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+    >>> x = np.random.random()
+    >>> Q = np.array([[np.cos(x), -np.sin(x)], [np.sin(x), np.cos(x)]])
+    >>> LA.norm(Q[0, :]), LA.norm(Q[1, :]), np.dot(Q[0, :],Q[1, :])
+    (1.0, 1.0, 0.0)
+
+    Now multiply a diagonal matrix by ``Q`` on one side and
+    by ``Q.T`` on the other:
+
+    >>> D = np.diag((-1,1))
+    >>> LA.eigvals(D)
+    array([-1.,  1.])
+    >>> A = np.dot(Q, D)
+    >>> A = np.dot(A, Q.T)
+    >>> LA.eigvals(A)
+    array([ 1., -1.]) # random
+
+    """
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    _assert_finite(a)
+    t, result_t = _commonType(a)
+
+    signature = 'D->D' if isComplexType(t) else 'd->D'
+    with errstate(call=_raise_linalgerror_eigenvalues_nonconvergence,
+                  invalid='call', over='ignore', divide='ignore',
+                  under='ignore'):
+        w = _umath_linalg.eigvals(a, signature=signature)
+
+    if not isComplexType(t):
+        if all(w.imag == 0):
+            w = w.real
+            result_t = _realType(result_t)
+        else:
+            result_t = _complexType(result_t)
+
+    return w.astype(result_t, copy=False)
+
+
+def _eigvalsh_dispatcher(a, UPLO=None):
+    return (a,)
+
+
+@array_function_dispatch(_eigvalsh_dispatcher)
+def eigvalsh(a, UPLO='L'):
+    """
+    Compute the eigenvalues of a complex Hermitian or real symmetric matrix.
+
+    Main difference from eigh: the eigenvectors are not computed.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        A complex- or real-valued matrix whose eigenvalues are to be
+        computed.
+    UPLO : {'L', 'U'}, optional
+        Specifies whether the calculation is done with the lower triangular
+        part of `a` ('L', default) or the upper triangular part ('U').
+        Irrespective of this value only the real parts of the diagonal will
+        be considered in the computation to preserve the notion of a Hermitian
+        matrix. It therefore follows that the imaginary part of the diagonal
+        will always be treated as zero.
+
+    Returns
+    -------
+    w : (..., M,) ndarray
+        The eigenvalues in ascending order, each repeated according to
+        its multiplicity.
+
+    Raises
+    ------
+    LinAlgError
+        If the eigenvalue computation does not converge.
+
+    See Also
+    --------
+    eigh : eigenvalues and eigenvectors of real symmetric or complex Hermitian
+           (conjugate symmetric) arrays.
+    eigvals : eigenvalues of general real or complex arrays.
+    eig : eigenvalues and right eigenvectors of general real or complex
+          arrays.
+    scipy.linalg.eigvalsh : Similar function in SciPy.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The eigenvalues are computed using LAPACK routines ``_syevd``, ``_heevd``.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+    >>> a = np.array([[1, -2j], [2j, 5]])
+    >>> LA.eigvalsh(a)
+    array([ 0.17157288,  5.82842712]) # may vary
+
+    >>> # demonstrate the treatment of the imaginary part of the diagonal
+    >>> a = np.array([[5+2j, 9-2j], [0+2j, 2-1j]])
+    >>> a
+    array([[5.+2.j, 9.-2.j],
+           [0.+2.j, 2.-1.j]])
+    >>> # with UPLO='L' this is numerically equivalent to using LA.eigvals()
+    >>> # with:
+    >>> b = np.array([[5.+0.j, 0.-2.j], [0.+2.j, 2.-0.j]])
+    >>> b
+    array([[5.+0.j, 0.-2.j],
+           [0.+2.j, 2.+0.j]])
+    >>> wa = LA.eigvalsh(a)
+    >>> wb = LA.eigvals(b)
+    >>> wa
+    array([1., 6.])
+    >>> wb
+    array([6.+0.j, 1.+0.j])
+
+    """
+    UPLO = UPLO.upper()
+    if UPLO not in ('L', 'U'):
+        raise ValueError("UPLO argument must be 'L' or 'U'")
+
+    if UPLO == 'L':
+        gufunc = _umath_linalg.eigvalsh_lo
+    else:
+        gufunc = _umath_linalg.eigvalsh_up
+
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+    signature = 'D->d' if isComplexType(t) else 'd->d'
+    with errstate(call=_raise_linalgerror_eigenvalues_nonconvergence,
+                  invalid='call', over='ignore', divide='ignore',
+                  under='ignore'):
+        w = gufunc(a, signature=signature)
+    return w.astype(_realType(result_t), copy=False)
+
+
+# Eigenvectors
+
+
+@array_function_dispatch(_unary_dispatcher)
+def eig(a):
+    """
+    Compute the eigenvalues and right eigenvectors of a square array.
+
+    Parameters
+    ----------
+    a : (..., M, M) array
+        Matrices for which the eigenvalues and right eigenvectors will
+        be computed
+
+    Returns
+    -------
+    A namedtuple with the following attributes:
+
+    eigenvalues : (..., M) array
+        The eigenvalues, each repeated according to its multiplicity.
+        The eigenvalues are not necessarily ordered. The resulting
+        array will be of complex type, unless the imaginary part is
+        zero in which case it will be cast to a real type. When `a`
+        is real the resulting eigenvalues will be real (0 imaginary
+        part) or occur in conjugate pairs
+
+    eigenvectors : (..., M, M) array
+        The normalized (unit "length") eigenvectors, such that the
+        column ``eigenvectors[:,i]`` is the eigenvector corresponding to the
+        eigenvalue ``eigenvalues[i]``.
+
+    Raises
+    ------
+    LinAlgError
+        If the eigenvalue computation does not converge.
+
+    See Also
+    --------
+    eigvals : eigenvalues of a non-symmetric array.
+    eigh : eigenvalues and eigenvectors of a real symmetric or complex
+           Hermitian (conjugate symmetric) array.
+    eigvalsh : eigenvalues of a real symmetric or complex Hermitian
+               (conjugate symmetric) array.
+    scipy.linalg.eig : Similar function in SciPy that also solves the
+                       generalized eigenvalue problem.
+    scipy.linalg.schur : Best choice for unitary and other non-Hermitian
+                         normal matrices.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    This is implemented using the ``_geev`` LAPACK routines which compute
+    the eigenvalues and eigenvectors of general square arrays.
+
+    The number `w` is an eigenvalue of `a` if there exists a vector `v` such
+    that ``a @ v = w * v``. Thus, the arrays `a`, `eigenvalues`, and
+    `eigenvectors` satisfy the equations ``a @ eigenvectors[:,i] =
+    eigenvalues[i] * eigenvectors[:,i]`` for :math:`i \\in \\{0,...,M-1\\}`.
+
+    The array `eigenvectors` may not be of maximum rank, that is, some of the
+    columns may be linearly dependent, although round-off error may obscure
+    that fact. If the eigenvalues are all different, then theoretically the
+    eigenvectors are linearly independent and `a` can be diagonalized by a
+    similarity transformation using `eigenvectors`, i.e, ``inv(eigenvectors) @
+    a @ eigenvectors`` is diagonal.
+
+    For non-Hermitian normal matrices the SciPy function `scipy.linalg.schur`
+    is preferred because the matrix `eigenvectors` is guaranteed to be
+    unitary, which is not the case when using `eig`. The Schur factorization
+    produces an upper triangular matrix rather than a diagonal matrix, but for
+    normal matrices only the diagonal of the upper triangular matrix is
+    needed, the rest is roundoff error.
+
+    Finally, it is emphasized that `eigenvectors` consists of the *right* (as
+    in right-hand side) eigenvectors of `a`. A vector `y` satisfying ``y.T @ a
+    = z * y.T`` for some number `z` is called a *left* eigenvector of `a`,
+    and, in general, the left and right eigenvectors of a matrix are not
+    necessarily the (perhaps conjugate) transposes of each other.
+
+    References
+    ----------
+    G. Strang, *Linear Algebra and Its Applications*, 2nd Ed., Orlando, FL,
+    Academic Press, Inc., 1980, Various pp.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+
+    (Almost) trivial example with real eigenvalues and eigenvectors.
+
+    >>> eigenvalues, eigenvectors = LA.eig(np.diag((1, 2, 3)))
+    >>> eigenvalues
+    array([1., 2., 3.])
+    >>> eigenvectors
+    array([[1., 0., 0.],
+           [0., 1., 0.],
+           [0., 0., 1.]])
+
+    Real matrix possessing complex eigenvalues and eigenvectors;
+    note that the eigenvalues are complex conjugates of each other.
+
+    >>> eigenvalues, eigenvectors = LA.eig(np.array([[1, -1], [1, 1]]))
+    >>> eigenvalues
+    array([1.+1.j, 1.-1.j])
+    >>> eigenvectors
+    array([[0.70710678+0.j        , 0.70710678-0.j        ],
+           [0.        -0.70710678j, 0.        +0.70710678j]])
+
+    Complex-valued matrix with real eigenvalues (but complex-valued
+    eigenvectors); note that ``a.conj().T == a``, i.e., `a` is Hermitian.
+
+    >>> a = np.array([[1, 1j], [-1j, 1]])
+    >>> eigenvalues, eigenvectors = LA.eig(a)
+    >>> eigenvalues
+    array([2.+0.j, 0.+0.j])
+    >>> eigenvectors
+    array([[ 0.        +0.70710678j,  0.70710678+0.j        ], # may vary
+           [ 0.70710678+0.j        , -0.        +0.70710678j]])
+
+    Be careful about round-off error!
+
+    >>> a = np.array([[1 + 1e-9, 0], [0, 1 - 1e-9]])
+    >>> # Theor. eigenvalues are 1 +/- 1e-9
+    >>> eigenvalues, eigenvectors = LA.eig(a)
+    >>> eigenvalues
+    array([1., 1.])
+    >>> eigenvectors
+    array([[1., 0.],
+           [0., 1.]])
+
+    """
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    _assert_finite(a)
+    t, result_t = _commonType(a)
+
+    signature = 'D->DD' if isComplexType(t) else 'd->DD'
+    with errstate(call=_raise_linalgerror_eigenvalues_nonconvergence,
+                  invalid='call', over='ignore', divide='ignore',
+                  under='ignore'):
+        w, vt = _umath_linalg.eig(a, signature=signature)
+
+    if not isComplexType(t) and all(w.imag == 0.0):
+        w = w.real
+        vt = vt.real
+        result_t = _realType(result_t)
+    else:
+        result_t = _complexType(result_t)
+
+    vt = vt.astype(result_t, copy=False)
+    return EigResult(w.astype(result_t, copy=False), wrap(vt))
+
+
+@array_function_dispatch(_eigvalsh_dispatcher)
+def eigh(a, UPLO='L'):
+    """
+    Return the eigenvalues and eigenvectors of a complex Hermitian
+    (conjugate symmetric) or a real symmetric matrix.
+
+    Returns two objects, a 1-D array containing the eigenvalues of `a`, and
+    a 2-D square array or matrix (depending on the input type) of the
+    corresponding eigenvectors (in columns).
+
+    Parameters
+    ----------
+    a : (..., M, M) array
+        Hermitian or real symmetric matrices whose eigenvalues and
+        eigenvectors are to be computed.
+    UPLO : {'L', 'U'}, optional
+        Specifies whether the calculation is done with the lower triangular
+        part of `a` ('L', default) or the upper triangular part ('U').
+        Irrespective of this value only the real parts of the diagonal will
+        be considered in the computation to preserve the notion of a Hermitian
+        matrix. It therefore follows that the imaginary part of the diagonal
+        will always be treated as zero.
+
+    Returns
+    -------
+    A namedtuple with the following attributes:
+
+    eigenvalues : (..., M) ndarray
+        The eigenvalues in ascending order, each repeated according to
+        its multiplicity.
+    eigenvectors : {(..., M, M) ndarray, (..., M, M) matrix}
+        The column ``eigenvectors[:, i]`` is the normalized eigenvector
+        corresponding to the eigenvalue ``eigenvalues[i]``.  Will return a
+        matrix object if `a` is a matrix object.
+
+    Raises
+    ------
+    LinAlgError
+        If the eigenvalue computation does not converge.
+
+    See Also
+    --------
+    eigvalsh : eigenvalues of real symmetric or complex Hermitian
+               (conjugate symmetric) arrays.
+    eig : eigenvalues and right eigenvectors for non-symmetric arrays.
+    eigvals : eigenvalues of non-symmetric arrays.
+    scipy.linalg.eigh : Similar function in SciPy (but also solves the
+                        generalized eigenvalue problem).
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The eigenvalues/eigenvectors are computed using LAPACK routines ``_syevd``,
+    ``_heevd``.
+
+    The eigenvalues of real symmetric or complex Hermitian matrices are always
+    real. [1]_ The array `eigenvalues` of (column) eigenvectors is unitary and
+    `a`, `eigenvalues`, and `eigenvectors` satisfy the equations ``dot(a,
+    eigenvectors[:, i]) = eigenvalues[i] * eigenvectors[:, i]``.
+
+    References
+    ----------
+    .. [1] G. Strang, *Linear Algebra and Its Applications*, 2nd Ed., Orlando,
+           FL, Academic Press, Inc., 1980, pg. 222.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+    >>> a = np.array([[1, -2j], [2j, 5]])
+    >>> a
+    array([[ 1.+0.j, -0.-2.j],
+           [ 0.+2.j,  5.+0.j]])
+    >>> eigenvalues, eigenvectors = LA.eigh(a)
+    >>> eigenvalues
+    array([0.17157288, 5.82842712])
+    >>> eigenvectors
+    array([[-0.92387953+0.j        , -0.38268343+0.j        ], # may vary
+           [ 0.        +0.38268343j,  0.        -0.92387953j]])
+
+    >>> (np.dot(a, eigenvectors[:, 0]) -
+    ... eigenvalues[0] * eigenvectors[:, 0])  # verify 1st eigenval/vec pair
+    array([5.55111512e-17+0.0000000e+00j, 0.00000000e+00+1.2490009e-16j])
+    >>> (np.dot(a, eigenvectors[:, 1]) -
+    ... eigenvalues[1] * eigenvectors[:, 1])  # verify 2nd eigenval/vec pair
+    array([0.+0.j, 0.+0.j])
+
+    >>> A = np.matrix(a) # what happens if input is a matrix object
+    >>> A
+    matrix([[ 1.+0.j, -0.-2.j],
+            [ 0.+2.j,  5.+0.j]])
+    >>> eigenvalues, eigenvectors = LA.eigh(A)
+    >>> eigenvalues
+    array([0.17157288, 5.82842712])
+    >>> eigenvectors
+    matrix([[-0.92387953+0.j        , -0.38268343+0.j        ], # may vary
+            [ 0.        +0.38268343j,  0.        -0.92387953j]])
+
+    >>> # demonstrate the treatment of the imaginary part of the diagonal
+    >>> a = np.array([[5+2j, 9-2j], [0+2j, 2-1j]])
+    >>> a
+    array([[5.+2.j, 9.-2.j],
+           [0.+2.j, 2.-1.j]])
+    >>> # with UPLO='L' this is numerically equivalent to using LA.eig() with:
+    >>> b = np.array([[5.+0.j, 0.-2.j], [0.+2.j, 2.-0.j]])
+    >>> b
+    array([[5.+0.j, 0.-2.j],
+           [0.+2.j, 2.+0.j]])
+    >>> wa, va = LA.eigh(a)
+    >>> wb, vb = LA.eig(b)
+    >>> wa
+    array([1., 6.])
+    >>> wb
+    array([6.+0.j, 1.+0.j])
+    >>> va
+    array([[-0.4472136 +0.j        , -0.89442719+0.j        ], # may vary
+           [ 0.        +0.89442719j,  0.        -0.4472136j ]])
+    >>> vb
+    array([[ 0.89442719+0.j       , -0.        +0.4472136j],
+           [-0.        +0.4472136j,  0.89442719+0.j       ]])
+
+    """
+    UPLO = UPLO.upper()
+    if UPLO not in ('L', 'U'):
+        raise ValueError("UPLO argument must be 'L' or 'U'")
+
+    a, wrap = _makearray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+
+    if UPLO == 'L':
+        gufunc = _umath_linalg.eigh_lo
+    else:
+        gufunc = _umath_linalg.eigh_up
+
+    signature = 'D->dD' if isComplexType(t) else 'd->dd'
+    with errstate(call=_raise_linalgerror_eigenvalues_nonconvergence,
+                  invalid='call', over='ignore', divide='ignore',
+                  under='ignore'):
+        w, vt = gufunc(a, signature=signature)
+    w = w.astype(_realType(result_t), copy=False)
+    vt = vt.astype(result_t, copy=False)
+    return EighResult(w, wrap(vt))
+
+
+# Singular value decomposition
+
+def _svd_dispatcher(a, full_matrices=None, compute_uv=None, hermitian=None):
+    return (a,)
+
+
+@array_function_dispatch(_svd_dispatcher)
+def svd(a, full_matrices=True, compute_uv=True, hermitian=False):
+    """
+    Singular Value Decomposition.
+
+    When `a` is a 2D array, and ``full_matrices=False``, then it is
+    factorized as ``u @ np.diag(s) @ vh = (u * s) @ vh``, where
+    `u` and the Hermitian transpose of `vh` are 2D arrays with
+    orthonormal columns and `s` is a 1D array of `a`'s singular
+    values. When `a` is higher-dimensional, SVD is applied in
+    stacked mode as explained below.
+
+    Parameters
+    ----------
+    a : (..., M, N) array_like
+        A real or complex array with ``a.ndim >= 2``.
+    full_matrices : bool, optional
+        If True (default), `u` and `vh` have the shapes ``(..., M, M)`` and
+        ``(..., N, N)``, respectively.  Otherwise, the shapes are
+        ``(..., M, K)`` and ``(..., K, N)``, respectively, where
+        ``K = min(M, N)``.
+    compute_uv : bool, optional
+        Whether or not to compute `u` and `vh` in addition to `s`.  True
+        by default.
+    hermitian : bool, optional
+        If True, `a` is assumed to be Hermitian (symmetric if real-valued),
+        enabling a more efficient method for finding singular values.
+        Defaults to False.
+
+    Returns
+    -------
+    U : { (..., M, M), (..., M, K) } array
+        Unitary array(s). The first ``a.ndim - 2`` dimensions have the same
+        size as those of the input `a`. The size of the last two dimensions
+        depends on the value of `full_matrices`. Only returned when
+        `compute_uv` is True.
+    S : (..., K) array
+        Vector(s) with the singular values, within each vector sorted in
+        descending order. The first ``a.ndim - 2`` dimensions have the same
+        size as those of the input `a`.
+    Vh : { (..., N, N), (..., K, N) } array
+        Unitary array(s). The first ``a.ndim - 2`` dimensions have the same
+        size as those of the input `a`. The size of the last two dimensions
+        depends on the value of `full_matrices`. Only returned when
+        `compute_uv` is True.
+
+    Raises
+    ------
+    LinAlgError
+        If SVD computation does not converge.
+
+    See Also
+    --------
+    scipy.linalg.svd : Similar function in SciPy.
+    scipy.linalg.svdvals : Compute singular values of a matrix.
+
+    Notes
+    -----
+    When `compute_uv` is True, the result is a namedtuple with the following
+    attribute names: `U`, `S`, and `Vh`.
+
+    The decomposition is performed using LAPACK routine ``_gesdd``.
+
+    SVD is usually described for the factorization of a 2D matrix :math:`A`.
+    The higher-dimensional case will be discussed below. In the 2D case, SVD is
+    written as :math:`A = U S V^H`, where :math:`A = a`, :math:`U= u`,
+    :math:`S= \\mathtt{np.diag}(s)` and :math:`V^H = vh`. The 1D array `s`
+    contains the singular values of `a` and `u` and `vh` are unitary. The rows
+    of `vh` are the eigenvectors of :math:`A^H A` and the columns of `u` are
+    the eigenvectors of :math:`A A^H`. In both cases the corresponding
+    (possibly non-zero) eigenvalues are given by ``s**2``.
+
+    If `a` has more than two dimensions, then broadcasting rules apply, as
+    explained in :ref:`routines.linalg-broadcasting`. This means that SVD is
+    working in "stacked" mode: it iterates over all indices of the first
+    ``a.ndim - 2`` dimensions and for each combination SVD is applied to the
+    last two indices. The matrix `a` can be reconstructed from the
+    decomposition with either ``(u * s[..., None, :]) @ vh`` or
+    ``u @ (s[..., None] * vh)``. (The ``@`` operator can be replaced by the
+    function ``np.matmul`` for python versions below 3.5.)
+
+    If `a` is a ``matrix`` object (as opposed to an ``ndarray``), then so are
+    all the return values.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> rng = np.random.default_rng()
+    >>> a = rng.normal(size=(9, 6)) + 1j*rng.normal(size=(9, 6))
+    >>> b = rng.normal(size=(2, 7, 8, 3)) + 1j*rng.normal(size=(2, 7, 8, 3))
+
+
+    Reconstruction based on full SVD, 2D case:
+
+    >>> U, S, Vh = np.linalg.svd(a, full_matrices=True)
+    >>> U.shape, S.shape, Vh.shape
+    ((9, 9), (6,), (6, 6))
+    >>> np.allclose(a, np.dot(U[:, :6] * S, Vh))
+    True
+    >>> smat = np.zeros((9, 6), dtype=complex)
+    >>> smat[:6, :6] = np.diag(S)
+    >>> np.allclose(a, np.dot(U, np.dot(smat, Vh)))
+    True
+
+    Reconstruction based on reduced SVD, 2D case:
+
+    >>> U, S, Vh = np.linalg.svd(a, full_matrices=False)
+    >>> U.shape, S.shape, Vh.shape
+    ((9, 6), (6,), (6, 6))
+    >>> np.allclose(a, np.dot(U * S, Vh))
+    True
+    >>> smat = np.diag(S)
+    >>> np.allclose(a, np.dot(U, np.dot(smat, Vh)))
+    True
+
+    Reconstruction based on full SVD, 4D case:
+
+    >>> U, S, Vh = np.linalg.svd(b, full_matrices=True)
+    >>> U.shape, S.shape, Vh.shape
+    ((2, 7, 8, 8), (2, 7, 3), (2, 7, 3, 3))
+    >>> np.allclose(b, np.matmul(U[..., :3] * S[..., None, :], Vh))
+    True
+    >>> np.allclose(b, np.matmul(U[..., :3], S[..., None] * Vh))
+    True
+
+    Reconstruction based on reduced SVD, 4D case:
+
+    >>> U, S, Vh = np.linalg.svd(b, full_matrices=False)
+    >>> U.shape, S.shape, Vh.shape
+    ((2, 7, 8, 3), (2, 7, 3), (2, 7, 3, 3))
+    >>> np.allclose(b, np.matmul(U * S[..., None, :], Vh))
+    True
+    >>> np.allclose(b, np.matmul(U, S[..., None] * Vh))
+    True
+
+    """
+    import numpy as np
+    a, wrap = _makearray(a)
+
+    if hermitian:
+        # note: lapack svd returns eigenvalues with s ** 2 sorted descending,
+        # but eig returns s sorted ascending, so we re-order the eigenvalues
+        # and related arrays to have the correct order
+        if compute_uv:
+            s, u = eigh(a)
+            sgn = sign(s)
+            s = abs(s)
+            sidx = argsort(s)[..., ::-1]
+            sgn = np.take_along_axis(sgn, sidx, axis=-1)
+            s = np.take_along_axis(s, sidx, axis=-1)
+            u = np.take_along_axis(u, sidx[..., None, :], axis=-1)
+            # singular values are unsigned, move the sign into v
+            vt = transpose(u * sgn[..., None, :]).conjugate()
+            return SVDResult(wrap(u), s, wrap(vt))
+        else:
+            s = eigvalsh(a)
+            s = abs(s)
+            return sort(s)[..., ::-1]
+
+    _assert_stacked_2d(a)
+    t, result_t = _commonType(a)
+
+    m, n = a.shape[-2:]
+    if compute_uv:
+        if full_matrices:
+            gufunc = _umath_linalg.svd_f
+        else:
+            gufunc = _umath_linalg.svd_s
+
+        signature = 'D->DdD' if isComplexType(t) else 'd->ddd'
+        with errstate(call=_raise_linalgerror_svd_nonconvergence,
+                      invalid='call', over='ignore', divide='ignore',
+                      under='ignore'):
+            u, s, vh = gufunc(a, signature=signature)
+        u = u.astype(result_t, copy=False)
+        s = s.astype(_realType(result_t), copy=False)
+        vh = vh.astype(result_t, copy=False)
+        return SVDResult(wrap(u), s, wrap(vh))
+    else:
+        signature = 'D->d' if isComplexType(t) else 'd->d'
+        with errstate(call=_raise_linalgerror_svd_nonconvergence,
+                      invalid='call', over='ignore', divide='ignore',
+                      under='ignore'):
+            s = _umath_linalg.svd(a, signature=signature)
+        s = s.astype(_realType(result_t), copy=False)
+        return s
+
+
+def _svdvals_dispatcher(x):
+    return (x,)
+
+
+@array_function_dispatch(_svdvals_dispatcher)
+def svdvals(x, /):
+    """
+    Returns the singular values of a matrix (or a stack of matrices) ``x``.
+    When x is a stack of matrices, the function will compute the singular
+    values for each matrix in the stack.
+
+    This function is Array API compatible.
+
+    Calling ``np.svdvals(x)`` to get singular values is the same as
+    ``np.svd(x, compute_uv=False, hermitian=False)``.
+
+    Parameters
+    ----------
+    x : (..., M, N) array_like
+        Input array having shape (..., M, N) and whose last two
+        dimensions form matrices on which to perform singular value
+        decomposition. Should have a floating-point data type.
+
+    Returns
+    -------
+    out : ndarray
+        An array with shape (..., K) that contains the vector(s)
+        of singular values of length K, where K = min(M, N).
+
+    See Also
+    --------
+    scipy.linalg.svdvals : Compute singular values of a matrix.
+
+    Examples
+    --------
+
+    >>> np.linalg.svdvals([[1, 2, 3, 4, 5],
+    ...                    [1, 4, 9, 16, 25],
+    ...                    [1, 8, 27, 64, 125]])
+    array([146.68862757,   5.57510612,   0.60393245])
+
+    Determine the rank of a matrix using singular values:
+
+    >>> s = np.linalg.svdvals([[1, 2, 3],
+    ...                        [2, 4, 6],
+    ...                        [-1, 1, -1]]); s
+    array([8.38434191e+00, 1.64402274e+00, 2.31534378e-16])
+    >>> np.count_nonzero(s > 1e-10)  # Matrix of rank 2
+    2
+
+    """
+    return svd(x, compute_uv=False, hermitian=False)
+
+
+def _cond_dispatcher(x, p=None):
+    return (x,)
+
+
+@array_function_dispatch(_cond_dispatcher)
+def cond(x, p=None):
+    """
+    Compute the condition number of a matrix.
+
+    This function is capable of returning the condition number using
+    one of seven different norms, depending on the value of `p` (see
+    Parameters below).
+
+    Parameters
+    ----------
+    x : (..., M, N) array_like
+        The matrix whose condition number is sought.
+    p : {None, 1, -1, 2, -2, inf, -inf, 'fro'}, optional
+        Order of the norm used in the condition number computation:
+
+        =====  ============================
+        p      norm for matrices
+        =====  ============================
+        None   2-norm, computed directly using the ``SVD``
+        'fro'  Frobenius norm
+        inf    max(sum(abs(x), axis=1))
+        -inf   min(sum(abs(x), axis=1))
+        1      max(sum(abs(x), axis=0))
+        -1     min(sum(abs(x), axis=0))
+        2      2-norm (largest sing. value)
+        -2     smallest singular value
+        =====  ============================
+
+        inf means the `numpy.inf` object, and the Frobenius norm is
+        the root-of-sum-of-squares norm.
+
+    Returns
+    -------
+    c : {float, inf}
+        The condition number of the matrix. May be infinite.
+
+    See Also
+    --------
+    numpy.linalg.norm
+
+    Notes
+    -----
+    The condition number of `x` is defined as the norm of `x` times the
+    norm of the inverse of `x` [1]_; the norm can be the usual L2-norm
+    (root-of-sum-of-squares) or one of a number of other matrix norms.
+
+    References
+    ----------
+    .. [1] G. Strang, *Linear Algebra and Its Applications*, Orlando, FL,
+           Academic Press, Inc., 1980, pg. 285.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+    >>> a = np.array([[1, 0, -1], [0, 1, 0], [1, 0, 1]])
+    >>> a
+    array([[ 1,  0, -1],
+           [ 0,  1,  0],
+           [ 1,  0,  1]])
+    >>> LA.cond(a)
+    1.4142135623730951
+    >>> LA.cond(a, 'fro')
+    3.1622776601683795
+    >>> LA.cond(a, np.inf)
+    2.0
+    >>> LA.cond(a, -np.inf)
+    1.0
+    >>> LA.cond(a, 1)
+    2.0
+    >>> LA.cond(a, -1)
+    1.0
+    >>> LA.cond(a, 2)
+    1.4142135623730951
+    >>> LA.cond(a, -2)
+    0.70710678118654746 # may vary
+    >>> (min(LA.svd(a, compute_uv=False)) *
+    ... min(LA.svd(LA.inv(a), compute_uv=False)))
+    0.70710678118654746 # may vary
+
+    """
+    x = asarray(x)  # in case we have a matrix
+    if _is_empty_2d(x):
+        raise LinAlgError("cond is not defined on empty arrays")
+    if p is None or p in {2, -2}:
+        s = svd(x, compute_uv=False)
+        with errstate(all='ignore'):
+            if p == -2:
+                r = s[..., -1] / s[..., 0]
+            else:
+                r = s[..., 0] / s[..., -1]
+    else:
+        # Call inv(x) ignoring errors. The result array will
+        # contain nans in the entries where inversion failed.
+        _assert_stacked_square(x)
+        t, result_t = _commonType(x)
+        result_t = _realType(result_t)  # condition number is always real
+        signature = 'D->D' if isComplexType(t) else 'd->d'
+        with errstate(all='ignore'):
+            invx = _umath_linalg.inv(x, signature=signature)
+            r = norm(x, p, axis=(-2, -1)) * norm(invx, p, axis=(-2, -1))
+        r = r.astype(result_t, copy=False)
+
+    # Convert nans to infs unless the original array had nan entries
+    nan_mask = isnan(r)
+    if nan_mask.any():
+        nan_mask &= ~isnan(x).any(axis=(-2, -1))
+        if r.ndim > 0:
+            r[nan_mask] = inf
+        elif nan_mask:
+            # Convention is to return scalars instead of 0d arrays.
+            r = r.dtype.type(inf)
+
+    return r
+
+
+def _matrix_rank_dispatcher(A, tol=None, hermitian=None, *, rtol=None):
+    return (A,)
+
+
+@array_function_dispatch(_matrix_rank_dispatcher)
+def matrix_rank(A, tol=None, hermitian=False, *, rtol=None):
+    """
+    Return matrix rank of array using SVD method
+
+    Rank of the array is the number of singular values of the array that are
+    greater than `tol`.
+
+    Parameters
+    ----------
+    A : {(M,), (..., M, N)} array_like
+        Input vector or stack of matrices.
+    tol : (...) array_like, float, optional
+        Threshold below which SVD values are considered zero. If `tol` is
+        None, and ``S`` is an array with singular values for `M`, and
+        ``eps`` is the epsilon value for datatype of ``S``, then `tol` is
+        set to ``S.max() * max(M, N) * eps``.
+    hermitian : bool, optional
+        If True, `A` is assumed to be Hermitian (symmetric if real-valued),
+        enabling a more efficient method for finding singular values.
+        Defaults to False.
+    rtol : (...) array_like, float, optional
+        Parameter for the relative tolerance component. Only ``tol`` or
+        ``rtol`` can be set at a time. Defaults to ``max(M, N) * eps``.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    rank : (...) array_like
+        Rank of A.
+
+    Notes
+    -----
+    The default threshold to detect rank deficiency is a test on the magnitude
+    of the singular values of `A`.  By default, we identify singular values
+    less than ``S.max() * max(M, N) * eps`` as indicating rank deficiency
+    (with the symbols defined above). This is the algorithm MATLAB uses [1]_.
+    It also appears in *Numerical recipes* in the discussion of SVD solutions
+    for linear least squares [2]_.
+
+    This default threshold is designed to detect rank deficiency accounting
+    for the numerical errors of the SVD computation. Imagine that there
+    is a column in `A` that is an exact (in floating point) linear combination
+    of other columns in `A`. Computing the SVD on `A` will not produce
+    a singular value exactly equal to 0 in general: any difference of
+    the smallest SVD value from 0 will be caused by numerical imprecision
+    in the calculation of the SVD. Our threshold for small SVD values takes
+    this numerical imprecision into account, and the default threshold will
+    detect such numerical rank deficiency. The threshold may declare a matrix
+    `A` rank deficient even if the linear combination of some columns of `A`
+    is not exactly equal to another column of `A` but only numerically very
+    close to another column of `A`.
+
+    We chose our default threshold because it is in wide use. Other thresholds
+    are possible.  For example, elsewhere in the 2007 edition of *Numerical
+    recipes* there is an alternative threshold of ``S.max() *
+    np.finfo(A.dtype).eps / 2. * np.sqrt(m + n + 1.)``. The authors describe
+    this threshold as being based on "expected roundoff error" (p 71).
+
+    The thresholds above deal with floating point roundoff error in the
+    calculation of the SVD.  However, you may have more information about
+    the sources of error in `A` that would make you consider other tolerance
+    values to detect *effective* rank deficiency. The most useful measure
+    of the tolerance depends on the operations you intend to use on your
+    matrix. For example, if your data come from uncertain measurements with
+    uncertainties greater than floating point epsilon, choosing a tolerance
+    near that uncertainty may be preferable. The tolerance may be absolute
+    if the uncertainties are absolute rather than relative.
+
+    References
+    ----------
+    .. [1] MATLAB reference documentation, "Rank"
+           https://www.mathworks.com/help/techdoc/ref/rank.html
+    .. [2] W. H. Press, S. A. Teukolsky, W. T. Vetterling and B. P. Flannery,
+           "Numerical Recipes (3rd edition)", Cambridge University Press, 2007,
+           page 795.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from numpy.linalg import matrix_rank
+    >>> matrix_rank(np.eye(4)) # Full rank matrix
+    4
+    >>> I=np.eye(4); I[-1,-1] = 0. # rank deficient matrix
+    >>> matrix_rank(I)
+    3
+    >>> matrix_rank(np.ones((4,))) # 1 dimension - rank 1 unless all 0
+    1
+    >>> matrix_rank(np.zeros((4,)))
+    0
+    """
+    if rtol is not None and tol is not None:
+        raise ValueError("`tol` and `rtol` can't be both set.")
+
+    A = asarray(A)
+    if A.ndim < 2:
+        return int(not all(A == 0))
+    S = svd(A, compute_uv=False, hermitian=hermitian)
+
+    if tol is None:
+        if rtol is None:
+            rtol = max(A.shape[-2:]) * finfo(S.dtype).eps
+        else:
+            rtol = asarray(rtol)[..., newaxis]
+        tol = S.max(axis=-1, keepdims=True) * rtol
+    else:
+        tol = asarray(tol)[..., newaxis]
+
+    return count_nonzero(S > tol, axis=-1)
+
+
+# Generalized inverse
+
+def _pinv_dispatcher(a, rcond=None, hermitian=None, *, rtol=None):
+    return (a,)
+
+
+@array_function_dispatch(_pinv_dispatcher)
+def pinv(a, rcond=None, hermitian=False, *, rtol=_NoValue):
+    """
+    Compute the (Moore-Penrose) pseudo-inverse of a matrix.
+
+    Calculate the generalized inverse of a matrix using its
+    singular-value decomposition (SVD) and including all
+    *large* singular values.
+
+    Parameters
+    ----------
+    a : (..., M, N) array_like
+        Matrix or stack of matrices to be pseudo-inverted.
+    rcond : (...) array_like of float, optional
+        Cutoff for small singular values.
+        Singular values less than or equal to
+        ``rcond * largest_singular_value`` are set to zero.
+        Broadcasts against the stack of matrices. Default: ``1e-15``.
+    hermitian : bool, optional
+        If True, `a` is assumed to be Hermitian (symmetric if real-valued),
+        enabling a more efficient method for finding singular values.
+        Defaults to False.
+    rtol : (...) array_like of float, optional
+        Same as `rcond`, but it's an Array API compatible parameter name.
+        Only `rcond` or `rtol` can be set at a time. If none of them are
+        provided then NumPy's ``1e-15`` default is used. If ``rtol=None``
+        is passed then the API standard default is used.
+
+        .. versionadded:: 2.0.0
+
+    Returns
+    -------
+    B : (..., N, M) ndarray
+        The pseudo-inverse of `a`. If `a` is a `matrix` instance, then so
+        is `B`.
+
+    Raises
+    ------
+    LinAlgError
+        If the SVD computation does not converge.
+
+    See Also
+    --------
+    scipy.linalg.pinv : Similar function in SciPy.
+    scipy.linalg.pinvh : Compute the (Moore-Penrose) pseudo-inverse of a
+                         Hermitian matrix.
+
+    Notes
+    -----
+    The pseudo-inverse of a matrix A, denoted :math:`A^+`, is
+    defined as: "the matrix that 'solves' [the least-squares problem]
+    :math:`Ax = b`," i.e., if :math:`\\bar{x}` is said solution, then
+    :math:`A^+` is that matrix such that :math:`\\bar{x} = A^+b`.
+
+    It can be shown that if :math:`Q_1 \\Sigma Q_2^T = A` is the singular
+    value decomposition of A, then
+    :math:`A^+ = Q_2 \\Sigma^+ Q_1^T`, where :math:`Q_{1,2}` are
+    orthogonal matrices, :math:`\\Sigma` is a diagonal matrix consisting
+    of A's so-called singular values, (followed, typically, by
+    zeros), and then :math:`\\Sigma^+` is simply the diagonal matrix
+    consisting of the reciprocals of A's singular values
+    (again, followed by zeros). [1]_
+
+    References
+    ----------
+    .. [1] G. Strang, *Linear Algebra and Its Applications*, 2nd Ed., Orlando,
+           FL, Academic Press, Inc., 1980, pp. 139-142.
+
+    Examples
+    --------
+    The following example checks that ``a * a+ * a == a`` and
+    ``a+ * a * a+ == a+``:
+
+    >>> import numpy as np
+    >>> rng = np.random.default_rng()
+    >>> a = rng.normal(size=(9, 6))
+    >>> B = np.linalg.pinv(a)
+    >>> np.allclose(a, np.dot(a, np.dot(B, a)))
+    True
+    >>> np.allclose(B, np.dot(B, np.dot(a, B)))
+    True
+
+    """
+    a, wrap = _makearray(a)
+    if rcond is None:
+        if rtol is _NoValue:
+            rcond = 1e-15
+        elif rtol is None:
+            rcond = max(a.shape[-2:]) * finfo(a.dtype).eps
+        else:
+            rcond = rtol
+    elif rtol is not _NoValue:
+        raise ValueError("`rtol` and `rcond` can't be both set.")
+    else:
+        # NOTE: Deprecate `rcond` in a few versions.
+        pass
+
+    rcond = asarray(rcond)
+    if _is_empty_2d(a):
+        m, n = a.shape[-2:]
+        res = empty(a.shape[:-2] + (n, m), dtype=a.dtype)
+        return wrap(res)
+    a = a.conjugate()
+    u, s, vt = svd(a, full_matrices=False, hermitian=hermitian)
+
+    # discard small singular values
+    cutoff = rcond[..., newaxis] * amax(s, axis=-1, keepdims=True)
+    large = s > cutoff
+    s = divide(1, s, where=large, out=s)
+    s[~large] = 0
+
+    res = matmul(transpose(vt), multiply(s[..., newaxis], transpose(u)))
+    return wrap(res)
+
+
+# Determinant
+
+
+@array_function_dispatch(_unary_dispatcher)
+def slogdet(a):
+    """
+    Compute the sign and (natural) logarithm of the determinant of an array.
+
+    If an array has a very small or very large determinant, then a call to
+    `det` may overflow or underflow. This routine is more robust against such
+    issues, because it computes the logarithm of the determinant rather than
+    the determinant itself.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Input array, has to be a square 2-D array.
+
+    Returns
+    -------
+    A namedtuple with the following attributes:
+
+    sign : (...) array_like
+        A number representing the sign of the determinant. For a real matrix,
+        this is 1, 0, or -1. For a complex matrix, this is a complex number
+        with absolute value 1 (i.e., it is on the unit circle), or else 0.
+    logabsdet : (...) array_like
+        The natural log of the absolute value of the determinant.
+
+    If the determinant is zero, then `sign` will be 0 and `logabsdet`
+    will be -inf. In all cases, the determinant is equal to
+    ``sign * np.exp(logabsdet)``.
+
+    See Also
+    --------
+    det
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The determinant is computed via LU factorization using the LAPACK
+    routine ``z/dgetrf``.
+
+    Examples
+    --------
+    The determinant of a 2-D array ``[[a, b], [c, d]]`` is ``ad - bc``:
+
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> (sign, logabsdet) = np.linalg.slogdet(a)
+    >>> (sign, logabsdet)
+    (-1, 0.69314718055994529) # may vary
+    >>> sign * np.exp(logabsdet)
+    -2.0
+
+    Computing log-determinants for a stack of matrices:
+
+    >>> a = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
+    >>> a.shape
+    (3, 2, 2)
+    >>> sign, logabsdet = np.linalg.slogdet(a)
+    >>> (sign, logabsdet)
+    (array([-1., -1., -1.]), array([ 0.69314718,  1.09861229,  2.07944154]))
+    >>> sign * np.exp(logabsdet)
+    array([-2., -3., -8.])
+
+    This routine succeeds where ordinary `det` does not:
+
+    >>> np.linalg.det(np.eye(500) * 0.1)
+    0.0
+    >>> np.linalg.slogdet(np.eye(500) * 0.1)
+    (1, -1151.2925464970228)
+
+    """
+    a = asarray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+    real_t = _realType(result_t)
+    signature = 'D->Dd' if isComplexType(t) else 'd->dd'
+    sign, logdet = _umath_linalg.slogdet(a, signature=signature)
+    sign = sign.astype(result_t, copy=False)
+    logdet = logdet.astype(real_t, copy=False)
+    return SlogdetResult(sign, logdet)
+
+
+@array_function_dispatch(_unary_dispatcher)
+def det(a):
+    """
+    Compute the determinant of an array.
+
+    Parameters
+    ----------
+    a : (..., M, M) array_like
+        Input array to compute determinants for.
+
+    Returns
+    -------
+    det : (...) array_like
+        Determinant of `a`.
+
+    See Also
+    --------
+    slogdet : Another way to represent the determinant, more suitable
+      for large matrices where underflow/overflow may occur.
+    scipy.linalg.det : Similar function in SciPy.
+
+    Notes
+    -----
+    Broadcasting rules apply, see the `numpy.linalg` documentation for
+    details.
+
+    The determinant is computed via LU factorization using the LAPACK
+    routine ``z/dgetrf``.
+
+    Examples
+    --------
+    The determinant of a 2-D array [[a, b], [c, d]] is ad - bc:
+
+    >>> import numpy as np
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> np.linalg.det(a)
+    -2.0 # may vary
+
+    Computing determinants for a stack of matrices:
+
+    >>> a = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
+    >>> a.shape
+    (3, 2, 2)
+    >>> np.linalg.det(a)
+    array([-2., -3., -8.])
+
+    """
+    a = asarray(a)
+    _assert_stacked_square(a)
+    t, result_t = _commonType(a)
+    signature = 'D->D' if isComplexType(t) else 'd->d'
+    r = _umath_linalg.det(a, signature=signature)
+    r = r.astype(result_t, copy=False)
+    return r
+
+
+# Linear Least Squares
+
+def _lstsq_dispatcher(a, b, rcond=None):
+    return (a, b)
+
+
+@array_function_dispatch(_lstsq_dispatcher)
+def lstsq(a, b, rcond=None):
+    r"""
+    Return the least-squares solution to a linear matrix equation.
+
+    Computes the vector `x` that approximately solves the equation
+    ``a @ x = b``. The equation may be under-, well-, or over-determined
+    (i.e., the number of linearly independent rows of `a` can be less than,
+    equal to, or greater than its number of linearly independent columns).
+    If `a` is square and of full rank, then `x` (but for round-off error)
+    is the "exact" solution of the equation. Else, `x` minimizes the
+    Euclidean 2-norm :math:`||b - ax||`. If there are multiple minimizing
+    solutions, the one with the smallest 2-norm :math:`||x||` is returned.
+
+    Parameters
+    ----------
+    a : (M, N) array_like
+        "Coefficient" matrix.
+    b : {(M,), (M, K)} array_like
+        Ordinate or "dependent variable" values. If `b` is two-dimensional,
+        the least-squares solution is calculated for each of the `K` columns
+        of `b`.
+    rcond : float, optional
+        Cut-off ratio for small singular values of `a`.
+        For the purposes of rank determination, singular values are treated
+        as zero if they are smaller than `rcond` times the largest singular
+        value of `a`.
+        The default uses the machine precision times ``max(M, N)``.  Passing
+        ``-1`` will use machine precision.
+
+        .. versionchanged:: 2.0
+            Previously, the default was ``-1``, but a warning was given that
+            this would change.
+
+    Returns
+    -------
+    x : {(N,), (N, K)} ndarray
+        Least-squares solution. If `b` is two-dimensional,
+        the solutions are in the `K` columns of `x`.
+    residuals : {(1,), (K,), (0,)} ndarray
+        Sums of squared residuals: Squared Euclidean 2-norm for each column in
+        ``b - a @ x``.
+        If the rank of `a` is < N or M <= N, this is an empty array.
+        If `b` is 1-dimensional, this is a (1,) shape array.
+        Otherwise the shape is (K,).
+    rank : int
+        Rank of matrix `a`.
+    s : (min(M, N),) ndarray
+        Singular values of `a`.
+
+    Raises
+    ------
+    LinAlgError
+        If computation does not converge.
+
+    See Also
+    --------
+    scipy.linalg.lstsq : Similar function in SciPy.
+
+    Notes
+    -----
+    If `b` is a matrix, then all array results are returned as matrices.
+
+    Examples
+    --------
+    Fit a line, ``y = mx + c``, through some noisy data-points:
+
+    >>> import numpy as np
+    >>> x = np.array([0, 1, 2, 3])
+    >>> y = np.array([-1, 0.2, 0.9, 2.1])
+
+    By examining the coefficients, we see that the line should have a
+    gradient of roughly 1 and cut the y-axis at, more or less, -1.
+
+    We can rewrite the line equation as ``y = Ap``, where ``A = [[x 1]]``
+    and ``p = [[m], [c]]``.  Now use `lstsq` to solve for `p`:
+
+    >>> A = np.vstack([x, np.ones(len(x))]).T
+    >>> A
+    array([[ 0.,  1.],
+           [ 1.,  1.],
+           [ 2.,  1.],
+           [ 3.,  1.]])
+
+    >>> m, c = np.linalg.lstsq(A, y)[0]
+    >>> m, c
+    (1.0 -0.95) # may vary
+
+    Plot the data along with the fitted line:
+
+    >>> import matplotlib.pyplot as plt
+    >>> _ = plt.plot(x, y, 'o', label='Original data', markersize=10)
+    >>> _ = plt.plot(x, m*x + c, 'r', label='Fitted line')
+    >>> _ = plt.legend()
+    >>> plt.show()
+
+    """
+    a, _ = _makearray(a)
+    b, wrap = _makearray(b)
+    is_1d = b.ndim == 1
+    if is_1d:
+        b = b[:, newaxis]
+    _assert_2d(a, b)
+    m, n = a.shape[-2:]
+    m2, n_rhs = b.shape[-2:]
+    if m != m2:
+        raise LinAlgError('Incompatible dimensions')
+
+    t, result_t = _commonType(a, b)
+    result_real_t = _realType(result_t)
+
+    if rcond is None:
+        rcond = finfo(t).eps * max(n, m)
+
+    signature = 'DDd->Ddid' if isComplexType(t) else 'ddd->ddid'
+    if n_rhs == 0:
+        # lapack can't handle n_rhs = 0 - so allocate
+        # the array one larger in that axis
+        b = zeros(b.shape[:-2] + (m, n_rhs + 1), dtype=b.dtype)
+
+    with errstate(call=_raise_linalgerror_lstsq, invalid='call',
+                  over='ignore', divide='ignore', under='ignore'):
+        x, resids, rank, s = _umath_linalg.lstsq(a, b, rcond,
+                                                 signature=signature)
+    if m == 0:
+        x[...] = 0
+    if n_rhs == 0:
+        # remove the item we added
+        x = x[..., :n_rhs]
+        resids = resids[..., :n_rhs]
+
+    # remove the axis we added
+    if is_1d:
+        x = x.squeeze(axis=-1)
+        # we probably should squeeze resids too, but we can't
+        # without breaking compatibility.
+
+    # as documented
+    if rank != n or m <= n:
+        resids = array([], result_real_t)
+
+    # coerce output arrays
+    s = s.astype(result_real_t, copy=False)
+    resids = resids.astype(result_real_t, copy=False)
+    # Copying lets the memory in r_parts be freed
+    x = x.astype(result_t, copy=True)
+    return wrap(x), wrap(resids), rank, s
+
+
+def _multi_svd_norm(x, row_axis, col_axis, op, initial=None):
+    """Compute a function of the singular values of the 2-D matrices in `x`.
+
+    This is a private utility function used by `numpy.linalg.norm()`.
+
+    Parameters
+    ----------
+    x : ndarray
+    row_axis, col_axis : int
+        The axes of `x` that hold the 2-D matrices.
+    op : callable
+        This should be either numpy.amin or `numpy.amax` or `numpy.sum`.
+
+    Returns
+    -------
+    result : float or ndarray
+        If `x` is 2-D, the return values is a float.
+        Otherwise, it is an array with ``x.ndim - 2`` dimensions.
+        The return values are either the minimum or maximum or sum of the
+        singular values of the matrices, depending on whether `op`
+        is `numpy.amin` or `numpy.amax` or `numpy.sum`.
+
+    """
+    y = moveaxis(x, (row_axis, col_axis), (-2, -1))
+    result = op(svd(y, compute_uv=False), axis=-1, initial=initial)
+    return result
+
+
+def _norm_dispatcher(x, ord=None, axis=None, keepdims=None):
+    return (x,)
+
+
+@array_function_dispatch(_norm_dispatcher)
+def norm(x, ord=None, axis=None, keepdims=False):
+    """
+    Matrix or vector norm.
+
+    This function is able to return one of eight different matrix norms,
+    or one of an infinite number of vector norms (described below), depending
+    on the value of the ``ord`` parameter.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.  If `axis` is None, `x` must be 1-D or 2-D, unless `ord`
+        is None. If both `axis` and `ord` are None, the 2-norm of
+        ``x.ravel`` will be returned.
+    ord : {int, float, inf, -inf, 'fro', 'nuc'}, optional
+        Order of the norm (see table under ``Notes`` for what values are
+        supported for matrices and vectors respectively). inf means numpy's
+        `inf` object. The default is None.
+    axis : {None, int, 2-tuple of ints}, optional.
+        If `axis` is an integer, it specifies the axis of `x` along which to
+        compute the vector norms.  If `axis` is a 2-tuple, it specifies the
+        axes that hold 2-D matrices, and the matrix norms of these matrices
+        are computed.  If `axis` is None then either a vector norm (when `x`
+        is 1-D) or a matrix norm (when `x` is 2-D) is returned. The default
+        is None.
+
+    keepdims : bool, optional
+        If this is set to True, the axes which are normed over are left in the
+        result as dimensions with size one.  With this option the result will
+        broadcast correctly against the original `x`.
+
+    Returns
+    -------
+    n : float or ndarray
+        Norm of the matrix or vector(s).
+
+    See Also
+    --------
+    scipy.linalg.norm : Similar function in SciPy.
+
+    Notes
+    -----
+    For values of ``ord < 1``, the result is, strictly speaking, not a
+    mathematical 'norm', but it may still be useful for various numerical
+    purposes.
+
+    The following norms can be calculated:
+
+    =====  ============================  ==========================
+    ord    norm for matrices             norm for vectors
+    =====  ============================  ==========================
+    None   Frobenius norm                2-norm
+    'fro'  Frobenius norm                --
+    'nuc'  nuclear norm                  --
+    inf    max(sum(abs(x), axis=1))      max(abs(x))
+    -inf   min(sum(abs(x), axis=1))      min(abs(x))
+    0      --                            sum(x != 0)
+    1      max(sum(abs(x), axis=0))      as below
+    -1     min(sum(abs(x), axis=0))      as below
+    2      2-norm (largest sing. value)  as below
+    -2     smallest singular value       as below
+    other  --                            sum(abs(x)**ord)**(1./ord)
+    =====  ============================  ==========================
+
+    The Frobenius norm is given by [1]_:
+
+    :math:`||A||_F = [\\sum_{i,j} abs(a_{i,j})^2]^{1/2}`
+
+    The nuclear norm is the sum of the singular values.
+
+    Both the Frobenius and nuclear norm orders are only defined for
+    matrices and raise a ValueError when ``x.ndim != 2``.
+
+    References
+    ----------
+    .. [1] G. H. Golub and C. F. Van Loan, *Matrix Computations*,
+           Baltimore, MD, Johns Hopkins University Press, 1985, pg. 15
+
+    Examples
+    --------
+
+    >>> import numpy as np
+    >>> from numpy import linalg as LA
+    >>> a = np.arange(9) - 4
+    >>> a
+    array([-4, -3, -2, ...,  2,  3,  4])
+    >>> b = a.reshape((3, 3))
+    >>> b
+    array([[-4, -3, -2],
+           [-1,  0,  1],
+           [ 2,  3,  4]])
+
+    >>> LA.norm(a)
+    7.745966692414834
+    >>> LA.norm(b)
+    7.745966692414834
+    >>> LA.norm(b, 'fro')
+    7.745966692414834
+    >>> LA.norm(a, np.inf)
+    4.0
+    >>> LA.norm(b, np.inf)
+    9.0
+    >>> LA.norm(a, -np.inf)
+    0.0
+    >>> LA.norm(b, -np.inf)
+    2.0
+
+    >>> LA.norm(a, 1)
+    20.0
+    >>> LA.norm(b, 1)
+    7.0
+    >>> LA.norm(a, -1)
+    -4.6566128774142013e-010
+    >>> LA.norm(b, -1)
+    6.0
+    >>> LA.norm(a, 2)
+    7.745966692414834
+    >>> LA.norm(b, 2)
+    7.3484692283495345
+
+    >>> LA.norm(a, -2)
+    0.0
+    >>> LA.norm(b, -2)
+    1.8570331885190563e-016 # may vary
+    >>> LA.norm(a, 3)
+    5.8480354764257312 # may vary
+    >>> LA.norm(a, -3)
+    0.0
+
+    Using the `axis` argument to compute vector norms:
+
+    >>> c = np.array([[ 1, 2, 3],
+    ...               [-1, 1, 4]])
+    >>> LA.norm(c, axis=0)
+    array([ 1.41421356,  2.23606798,  5.        ])
+    >>> LA.norm(c, axis=1)
+    array([ 3.74165739,  4.24264069])
+    >>> LA.norm(c, ord=1, axis=1)
+    array([ 6.,  6.])
+
+    Using the `axis` argument to compute matrix norms:
+
+    >>> m = np.arange(8).reshape(2,2,2)
+    >>> LA.norm(m, axis=(1,2))
+    array([  3.74165739,  11.22497216])
+    >>> LA.norm(m[0, :, :]), LA.norm(m[1, :, :])
+    (3.7416573867739413, 11.224972160321824)
+
+    """
+    x = asarray(x)
+
+    if not issubclass(x.dtype.type, (inexact, object_)):
+        x = x.astype(float)
+
+    # Immediately handle some default, simple, fast, and common cases.
+    if axis is None:
+        ndim = x.ndim
+        if (
+            (ord is None) or
+            (ord in ('f', 'fro') and ndim == 2) or
+            (ord == 2 and ndim == 1)
+        ):
+            x = x.ravel(order='K')
+            if isComplexType(x.dtype.type):
+                x_real = x.real
+                x_imag = x.imag
+                sqnorm = x_real.dot(x_real) + x_imag.dot(x_imag)
+            else:
+                sqnorm = x.dot(x)
+            ret = sqrt(sqnorm)
+            if keepdims:
+                ret = ret.reshape(ndim * [1])
+            return ret
+
+    # Normalize the `axis` argument to a tuple.
+    nd = x.ndim
+    if axis is None:
+        axis = tuple(range(nd))
+    elif not isinstance(axis, tuple):
+        try:
+            axis = int(axis)
+        except Exception as e:
+            raise TypeError(
+                "'axis' must be None, an integer or a tuple of integers"
+            ) from e
+        axis = (axis,)
+
+    if len(axis) == 1:
+        if ord == inf:
+            return abs(x).max(axis=axis, keepdims=keepdims, initial=0)
+        elif ord == -inf:
+            return abs(x).min(axis=axis, keepdims=keepdims)
+        elif ord == 0:
+            # Zero norm
+            return (
+                (x != 0)
+                .astype(x.real.dtype)
+                .sum(axis=axis, keepdims=keepdims)
+            )
+        elif ord == 1:
+            # special case for speedup
+            return add.reduce(abs(x), axis=axis, keepdims=keepdims)
+        elif ord is None or ord == 2:
+            # special case for speedup
+            s = (x.conj() * x).real
+            return sqrt(add.reduce(s, axis=axis, keepdims=keepdims))
+        # None of the str-type keywords for ord ('fro', 'nuc')
+        # are valid for vectors
+        elif isinstance(ord, str):
+            raise ValueError(f"Invalid norm order '{ord}' for vectors")
+        else:
+            absx = abs(x)
+            absx **= ord
+            ret = add.reduce(absx, axis=axis, keepdims=keepdims)
+            ret **= reciprocal(ord, dtype=ret.dtype)
+            return ret
+    elif len(axis) == 2:
+        row_axis, col_axis = axis
+        row_axis = normalize_axis_index(row_axis, nd)
+        col_axis = normalize_axis_index(col_axis, nd)
+        if row_axis == col_axis:
+            raise ValueError('Duplicate axes given.')
+        if ord == 2:
+            ret = _multi_svd_norm(x, row_axis, col_axis, amax, 0)
+        elif ord == -2:
+            ret = _multi_svd_norm(x, row_axis, col_axis, amin)
+        elif ord == 1:
+            if col_axis > row_axis:
+                col_axis -= 1
+            ret = add.reduce(abs(x), axis=row_axis).max(axis=col_axis, initial=0)
+        elif ord == inf:
+            if row_axis > col_axis:
+                row_axis -= 1
+            ret = add.reduce(abs(x), axis=col_axis).max(axis=row_axis, initial=0)
+        elif ord == -1:
+            if col_axis > row_axis:
+                col_axis -= 1
+            ret = add.reduce(abs(x), axis=row_axis).min(axis=col_axis)
+        elif ord == -inf:
+            if row_axis > col_axis:
+                row_axis -= 1
+            ret = add.reduce(abs(x), axis=col_axis).min(axis=row_axis)
+        elif ord in [None, 'fro', 'f']:
+            ret = sqrt(add.reduce((x.conj() * x).real, axis=axis))
+        elif ord == 'nuc':
+            ret = _multi_svd_norm(x, row_axis, col_axis, sum, 0)
+        else:
+            raise ValueError("Invalid norm order for matrices.")
+        if keepdims:
+            ret_shape = list(x.shape)
+            ret_shape[axis[0]] = 1
+            ret_shape[axis[1]] = 1
+            ret = ret.reshape(ret_shape)
+        return ret
+    else:
+        raise ValueError("Improper number of dimensions to norm.")
+
+
+# multi_dot
+
+def _multidot_dispatcher(arrays, *, out=None):
+    yield from arrays
+    yield out
+
+
+@array_function_dispatch(_multidot_dispatcher)
+def multi_dot(arrays, *, out=None):
+    """
+    Compute the dot product of two or more arrays in a single function call,
+    while automatically selecting the fastest evaluation order.
+
+    `multi_dot` chains `numpy.dot` and uses optimal parenthesization
+    of the matrices [1]_ [2]_. Depending on the shapes of the matrices,
+    this can speed up the multiplication a lot.
+
+    If the first argument is 1-D it is treated as a row vector.
+    If the last argument is 1-D it is treated as a column vector.
+    The other arguments must be 2-D.
+
+    Think of `multi_dot` as::
+
+        def multi_dot(arrays): return functools.reduce(np.dot, arrays)
+
+
+    Parameters
+    ----------
+    arrays : sequence of array_like
+        If the first argument is 1-D it is treated as row vector.
+        If the last argument is 1-D it is treated as column vector.
+        The other arguments must be 2-D.
+    out : ndarray, optional
+        Output argument. This must have the exact kind that would be returned
+        if it was not used. In particular, it must have the right type, must be
+        C-contiguous, and its dtype must be the dtype that would be returned
+        for `dot(a, b)`. This is a performance feature. Therefore, if these
+        conditions are not met, an exception is raised, instead of attempting
+        to be flexible.
+
+    Returns
+    -------
+    output : ndarray
+        Returns the dot product of the supplied arrays.
+
+    See Also
+    --------
+    numpy.dot : dot multiplication with two arguments.
+
+    References
+    ----------
+
+    .. [1] Cormen, "Introduction to Algorithms", Chapter 15.2, p. 370-378
+    .. [2] https://en.wikipedia.org/wiki/Matrix_chain_multiplication
+
+    Examples
+    --------
+    `multi_dot` allows you to write::
+
+    >>> import numpy as np
+    >>> from numpy.linalg import multi_dot
+    >>> # Prepare some data
+    >>> A = np.random.random((10000, 100))
+    >>> B = np.random.random((100, 1000))
+    >>> C = np.random.random((1000, 5))
+    >>> D = np.random.random((5, 333))
+    >>> # the actual dot multiplication
+    >>> _ = multi_dot([A, B, C, D])
+
+    instead of::
+
+    >>> _ = np.dot(np.dot(np.dot(A, B), C), D)
+    >>> # or
+    >>> _ = A.dot(B).dot(C).dot(D)
+
+    Notes
+    -----
+    The cost for a matrix multiplication can be calculated with the
+    following function::
+
+        def cost(A, B):
+            return A.shape[0] * A.shape[1] * B.shape[1]
+
+    Assume we have three matrices
+    :math:`A_{10 \\times 100}, B_{100 \\times 5}, C_{5 \\times 50}`.
+
+    The costs for the two different parenthesizations are as follows::
+
+        cost((AB)C) = 10*100*5 + 10*5*50   = 5000 + 2500   = 7500
+        cost(A(BC)) = 10*100*50 + 100*5*50 = 50000 + 25000 = 75000
+
+    """
+    n = len(arrays)
+    # optimization only makes sense for len(arrays) > 2
+    if n < 2:
+        raise ValueError("Expecting at least two arrays.")
+    elif n == 2:
+        return dot(arrays[0], arrays[1], out=out)
+
+    arrays = [asanyarray(a) for a in arrays]
+
+    # save original ndim to reshape the result array into the proper form later
+    ndim_first, ndim_last = arrays[0].ndim, arrays[-1].ndim
+    # Explicitly convert vectors to 2D arrays to keep the logic of the internal
+    # _multi_dot_* functions as simple as possible.
+    if arrays[0].ndim == 1:
+        arrays[0] = atleast_2d(arrays[0])
+    if arrays[-1].ndim == 1:
+        arrays[-1] = atleast_2d(arrays[-1]).T
+    _assert_2d(*arrays)
+
+    # _multi_dot_three is much faster than _multi_dot_matrix_chain_order
+    if n == 3:
+        result = _multi_dot_three(arrays[0], arrays[1], arrays[2], out=out)
+    else:
+        order = _multi_dot_matrix_chain_order(arrays)
+        result = _multi_dot(arrays, order, 0, n - 1, out=out)
+
+    # return proper shape
+    if ndim_first == 1 and ndim_last == 1:
+        return result[0, 0]  # scalar
+    elif ndim_first == 1 or ndim_last == 1:
+        return result.ravel()  # 1-D
+    else:
+        return result
+
+
+def _multi_dot_three(A, B, C, out=None):
+    """
+    Find the best order for three arrays and do the multiplication.
+
+    For three arguments `_multi_dot_three` is approximately 15 times faster
+    than `_multi_dot_matrix_chain_order`
+
+    """
+    a0, a1b0 = A.shape
+    b1c0, c1 = C.shape
+    # cost1 = cost((AB)C) = a0*a1b0*b1c0 + a0*b1c0*c1
+    cost1 = a0 * b1c0 * (a1b0 + c1)
+    # cost2 = cost(A(BC)) = a1b0*b1c0*c1 + a0*a1b0*c1
+    cost2 = a1b0 * c1 * (a0 + b1c0)
+
+    if cost1 < cost2:
+        return dot(dot(A, B), C, out=out)
+    else:
+        return dot(A, dot(B, C), out=out)
+
+
+def _multi_dot_matrix_chain_order(arrays, return_costs=False):
+    """
+    Return a np.array that encodes the optimal order of multiplications.
+
+    The optimal order array is then used by `_multi_dot()` to do the
+    multiplication.
+
+    Also return the cost matrix if `return_costs` is `True`
+
+    The implementation CLOSELY follows Cormen, "Introduction to Algorithms",
+    Chapter 15.2, p. 370-378.  Note that Cormen uses 1-based indices.
+
+        cost[i, j] = min([
+            cost[prefix] + cost[suffix] + cost_mult(prefix, suffix)
+            for k in range(i, j)])
+
+    """
+    n = len(arrays)
+    # p stores the dimensions of the matrices
+    # Example for p: A_{10x100}, B_{100x5}, C_{5x50} --> p = [10, 100, 5, 50]
+    p = [a.shape[0] for a in arrays] + [arrays[-1].shape[1]]
+    # m is a matrix of costs of the subproblems
+    # m[i,j]: min number of scalar multiplications needed to compute A_{i..j}
+    m = zeros((n, n), dtype=double)
+    # s is the actual ordering
+    # s[i, j] is the value of k at which we split the product A_i..A_j
+    s = empty((n, n), dtype=intp)
+
+    for l in range(1, n):
+        for i in range(n - l):
+            j = i + l
+            m[i, j] = inf
+            for k in range(i, j):
+                q = m[i, k] + m[k + 1, j] + p[i] * p[k + 1] * p[j + 1]
+                if q < m[i, j]:
+                    m[i, j] = q
+                    s[i, j] = k  # Note that Cormen uses 1-based index
+
+    return (s, m) if return_costs else s
+
+
+def _multi_dot(arrays, order, i, j, out=None):
+    """Actually do the multiplication with the given order."""
+    if i == j:
+        # the initial call with non-None out should never get here
+        assert out is None
+
+        return arrays[i]
+    else:
+        return dot(_multi_dot(arrays, order, i, order[i, j]),
+                   _multi_dot(arrays, order, order[i, j] + 1, j),
+                   out=out)
+
+
+# diagonal
+
+def _diagonal_dispatcher(x, /, *, offset=None):
+    return (x,)
+
+
+@array_function_dispatch(_diagonal_dispatcher)
+def diagonal(x, /, *, offset=0):
+    """
+    Returns specified diagonals of a matrix (or a stack of matrices) ``x``.
+
+    This function is Array API compatible, contrary to
+    :py:func:`numpy.diagonal`, the matrix is assumed
+    to be defined by the last two dimensions.
+
+    Parameters
+    ----------
+    x : (...,M,N) array_like
+        Input array having shape (..., M, N) and whose innermost two
+        dimensions form MxN matrices.
+    offset : int, optional
+        Offset specifying the off-diagonal relative to the main diagonal,
+        where::
+
+            * offset = 0: the main diagonal.
+            * offset > 0: off-diagonal above the main diagonal.
+            * offset < 0: off-diagonal below the main diagonal.
+
+    Returns
+    -------
+    out : (...,min(N,M)) ndarray
+        An array containing the diagonals and whose shape is determined by
+        removing the last two dimensions and appending a dimension equal to
+        the size of the resulting diagonals. The returned array must have
+        the same data type as ``x``.
+
+    See Also
+    --------
+    numpy.diagonal
+
+    Examples
+    --------
+    >>> a = np.arange(4).reshape(2, 2); a
+    array([[0, 1],
+           [2, 3]])
+    >>> np.linalg.diagonal(a)
+    array([0, 3])
+
+    A 3-D example:
+
+    >>> a = np.arange(8).reshape(2, 2, 2); a
+    array([[[0, 1],
+            [2, 3]],
+           [[4, 5],
+            [6, 7]]])
+    >>> np.linalg.diagonal(a)
+    array([[0, 3],
+           [4, 7]])
+
+    Diagonals adjacent to the main diagonal can be obtained by using the
+    `offset` argument:
+
+    >>> a = np.arange(9).reshape(3, 3)
+    >>> a
+    array([[0, 1, 2],
+           [3, 4, 5],
+           [6, 7, 8]])
+    >>> np.linalg.diagonal(a, offset=1)  # First superdiagonal
+    array([1, 5])
+    >>> np.linalg.diagonal(a, offset=2)  # Second superdiagonal
+    array([2])
+    >>> np.linalg.diagonal(a, offset=-1)  # First subdiagonal
+    array([3, 7])
+    >>> np.linalg.diagonal(a, offset=-2)  # Second subdiagonal
+    array([6])
+
+    The anti-diagonal can be obtained by reversing the order of elements
+    using either `numpy.flipud` or `numpy.fliplr`.
+
+    >>> a = np.arange(9).reshape(3, 3)
+    >>> a
+    array([[0, 1, 2],
+           [3, 4, 5],
+           [6, 7, 8]])
+    >>> np.linalg.diagonal(np.fliplr(a))  # Horizontal flip
+    array([2, 4, 6])
+    >>> np.linalg.diagonal(np.flipud(a))  # Vertical flip
+    array([6, 4, 2])
+
+    Note that the order in which the diagonal is retrieved varies depending
+    on the flip function.
+
+    """
+    return _core_diagonal(x, offset, axis1=-2, axis2=-1)
+
+
+# trace
+
+def _trace_dispatcher(x, /, *, offset=None, dtype=None):
+    return (x,)
+
+
+@array_function_dispatch(_trace_dispatcher)
+def trace(x, /, *, offset=0, dtype=None):
+    """
+    Returns the sum along the specified diagonals of a matrix
+    (or a stack of matrices) ``x``.
+
+    This function is Array API compatible, contrary to
+    :py:func:`numpy.trace`.
+
+    Parameters
+    ----------
+    x : (...,M,N) array_like
+        Input array having shape (..., M, N) and whose innermost two
+        dimensions form MxN matrices.
+    offset : int, optional
+        Offset specifying the off-diagonal relative to the main diagonal,
+        where::
+
+            * offset = 0: the main diagonal.
+            * offset > 0: off-diagonal above the main diagonal.
+            * offset < 0: off-diagonal below the main diagonal.
+
+    dtype : dtype, optional
+        Data type of the returned array.
+
+    Returns
+    -------
+    out : ndarray
+        An array containing the traces and whose shape is determined by
+        removing the last two dimensions and storing the traces in the last
+        array dimension. For example, if x has rank k and shape:
+        (I, J, K, ..., L, M, N), then an output array has rank k-2 and shape:
+        (I, J, K, ..., L) where::
+
+            out[i, j, k, ..., l] = trace(a[i, j, k, ..., l, :, :])
+
+        The returned array must have a data type as described by the dtype
+        parameter above.
+
+    See Also
+    --------
+    numpy.trace
+
+    Examples
+    --------
+    >>> np.linalg.trace(np.eye(3))
+    3.0
+    >>> a = np.arange(8).reshape((2, 2, 2))
+    >>> np.linalg.trace(a)
+    array([3, 11])
+
+    Trace is computed with the last two axes as the 2-d sub-arrays.
+    This behavior differs from :py:func:`numpy.trace` which uses the first two
+    axes by default.
+
+    >>> a = np.arange(24).reshape((3, 2, 2, 2))
+    >>> np.linalg.trace(a).shape
+    (3, 2)
+
+    Traces adjacent to the main diagonal can be obtained by using the
+    `offset` argument:
+
+    >>> a = np.arange(9).reshape((3, 3)); a
+    array([[0, 1, 2],
+           [3, 4, 5],
+           [6, 7, 8]])
+    >>> np.linalg.trace(a, offset=1)  # First superdiagonal
+    6
+    >>> np.linalg.trace(a, offset=2)  # Second superdiagonal
+    2
+    >>> np.linalg.trace(a, offset=-1)  # First subdiagonal
+    10
+    >>> np.linalg.trace(a, offset=-2)  # Second subdiagonal
+    6
+
+    """
+    return _core_trace(x, offset, axis1=-2, axis2=-1, dtype=dtype)
+
+
+# cross
+
+def _cross_dispatcher(x1, x2, /, *, axis=None):
+    return (x1, x2,)
+
+
+@array_function_dispatch(_cross_dispatcher)
+def cross(x1, x2, /, *, axis=-1):
+    """
+    Returns the cross product of 3-element vectors.
+
+    If ``x1`` and/or ``x2`` are multi-dimensional arrays, then
+    the cross-product of each pair of corresponding 3-element vectors
+    is independently computed.
+
+    This function is Array API compatible, contrary to
+    :func:`numpy.cross`.
+
+    Parameters
+    ----------
+    x1 : array_like
+        The first input array.
+    x2 : array_like
+        The second input array. Must be compatible with ``x1`` for all
+        non-compute axes. The size of the axis over which to compute
+        the cross-product must be the same size as the respective axis
+        in ``x1``.
+    axis : int, optional
+        The axis (dimension) of ``x1`` and ``x2`` containing the vectors for
+        which to compute the cross-product. Default: ``-1``.
+
+    Returns
+    -------
+    out : ndarray
+        An array containing the cross products.
+
+    See Also
+    --------
+    numpy.cross
+
+    Examples
+    --------
+    Vector cross-product.
+
+    >>> x = np.array([1, 2, 3])
+    >>> y = np.array([4, 5, 6])
+    >>> np.linalg.cross(x, y)
+    array([-3,  6, -3])
+
+    Multiple vector cross-products. Note that the direction of the cross
+    product vector is defined by the *right-hand rule*.
+
+    >>> x = np.array([[1,2,3], [4,5,6]])
+    >>> y = np.array([[4,5,6], [1,2,3]])
+    >>> np.linalg.cross(x, y)
+    array([[-3,  6, -3],
+           [ 3, -6,  3]])
+
+    >>> x = np.array([[1, 2], [3, 4], [5, 6]])
+    >>> y = np.array([[4, 5], [6, 1], [2, 3]])
+    >>> np.linalg.cross(x, y, axis=0)
+    array([[-24,  6],
+           [ 18, 24],
+           [-6,  -18]])
+
+    """
+    x1 = asanyarray(x1)
+    x2 = asanyarray(x2)
+
+    if x1.shape[axis] != 3 or x2.shape[axis] != 3:
+        raise ValueError(
+            "Both input arrays must be (arrays of) 3-dimensional vectors, "
+            f"but they are {x1.shape[axis]} and {x2.shape[axis]} "
+            "dimensional instead."
+        )
+
+    return _core_cross(x1, x2, axis=axis)
+
+
+# matmul
+
+def _matmul_dispatcher(x1, x2, /):
+    return (x1, x2)
+
+
+@array_function_dispatch(_matmul_dispatcher)
+def matmul(x1, x2, /):
+    """
+    Computes the matrix product.
+
+    This function is Array API compatible, contrary to
+    :func:`numpy.matmul`.
+
+    Parameters
+    ----------
+    x1 : array_like
+        The first input array.
+    x2 : array_like
+        The second input array.
+
+    Returns
+    -------
+    out : ndarray
+        The matrix product of the inputs.
+        This is a scalar only when both ``x1``, ``x2`` are 1-d vectors.
+
+    Raises
+    ------
+    ValueError
+        If the last dimension of ``x1`` is not the same size as
+        the second-to-last dimension of ``x2``.
+
+        If a scalar value is passed in.
+
+    See Also
+    --------
+    numpy.matmul
+
+    Examples
+    --------
+    For 2-D arrays it is the matrix product:
+
+    >>> a = np.array([[1, 0],
+    ...               [0, 1]])
+    >>> b = np.array([[4, 1],
+    ...               [2, 2]])
+    >>> np.linalg.matmul(a, b)
+    array([[4, 1],
+           [2, 2]])
+
+    For 2-D mixed with 1-D, the result is the usual.
+
+    >>> a = np.array([[1, 0],
+    ...               [0, 1]])
+    >>> b = np.array([1, 2])
+    >>> np.linalg.matmul(a, b)
+    array([1, 2])
+    >>> np.linalg.matmul(b, a)
+    array([1, 2])
+
+
+    Broadcasting is conventional for stacks of arrays
+
+    >>> a = np.arange(2 * 2 * 4).reshape((2, 2, 4))
+    >>> b = np.arange(2 * 2 * 4).reshape((2, 4, 2))
+    >>> np.linalg.matmul(a,b).shape
+    (2, 2, 2)
+    >>> np.linalg.matmul(a, b)[0, 1, 1]
+    98
+    >>> sum(a[0, 1, :] * b[0 , :, 1])
+    98
+
+    Vector, vector returns the scalar inner product, but neither argument
+    is complex-conjugated:
+
+    >>> np.linalg.matmul([2j, 3j], [2j, 3j])
+    (-13+0j)
+
+    Scalar multiplication raises an error.
+
+    >>> np.linalg.matmul([1,2], 3)
+    Traceback (most recent call last):
+    ...
+    ValueError: matmul: Input operand 1 does not have enough dimensions ...
+
+    """
+    return _core_matmul(x1, x2)
+
+
+# tensordot
+
+def _tensordot_dispatcher(x1, x2, /, *, axes=None):
+    return (x1, x2)
+
+
+@array_function_dispatch(_tensordot_dispatcher)
+def tensordot(x1, x2, /, *, axes=2):
+    return _core_tensordot(x1, x2, axes=axes)
+
+
+tensordot.__doc__ = _core_tensordot.__doc__
+
+
+# matrix_transpose
+
+def _matrix_transpose_dispatcher(x):
+    return (x,)
+
+@array_function_dispatch(_matrix_transpose_dispatcher)
+def matrix_transpose(x, /):
+    return _core_matrix_transpose(x)
+
+
+matrix_transpose.__doc__ = f"""{_core_matrix_transpose.__doc__}
+
+    Notes
+    -----
+    This function is an alias of `numpy.matrix_transpose`.
+"""
+
+
+# matrix_norm
+
+def _matrix_norm_dispatcher(x, /, *, keepdims=None, ord=None):
+    return (x,)
+
+@array_function_dispatch(_matrix_norm_dispatcher)
+def matrix_norm(x, /, *, keepdims=False, ord="fro"):
+    """
+    Computes the matrix norm of a matrix (or a stack of matrices) ``x``.
+
+    This function is Array API compatible.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array having shape (..., M, N) and whose two innermost
+        dimensions form ``MxN`` matrices.
+    keepdims : bool, optional
+        If this is set to True, the axes which are normed over are left in
+        the result as dimensions with size one. Default: False.
+    ord : {1, -1, 2, -2, inf, -inf, 'fro', 'nuc'}, optional
+        The order of the norm. For details see the table under ``Notes``
+        in `numpy.linalg.norm`.
+
+    See Also
+    --------
+    numpy.linalg.norm : Generic norm function
+
+    Examples
+    --------
+    >>> from numpy import linalg as LA
+    >>> a = np.arange(9) - 4
+    >>> a
+    array([-4, -3, -2, ...,  2,  3,  4])
+    >>> b = a.reshape((3, 3))
+    >>> b
+    array([[-4, -3, -2],
+           [-1,  0,  1],
+           [ 2,  3,  4]])
+
+    >>> LA.matrix_norm(b)
+    7.745966692414834
+    >>> LA.matrix_norm(b, ord='fro')
+    7.745966692414834
+    >>> LA.matrix_norm(b, ord=np.inf)
+    9.0
+    >>> LA.matrix_norm(b, ord=-np.inf)
+    2.0
+
+    >>> LA.matrix_norm(b, ord=1)
+    7.0
+    >>> LA.matrix_norm(b, ord=-1)
+    6.0
+    >>> LA.matrix_norm(b, ord=2)
+    7.3484692283495345
+    >>> LA.matrix_norm(b, ord=-2)
+    1.8570331885190563e-016 # may vary
+
+    """
+    x = asanyarray(x)
+    return norm(x, axis=(-2, -1), keepdims=keepdims, ord=ord)
+
+
+# vector_norm
+
+def _vector_norm_dispatcher(x, /, *, axis=None, keepdims=None, ord=None):
+    return (x,)
+
+@array_function_dispatch(_vector_norm_dispatcher)
+def vector_norm(x, /, *, axis=None, keepdims=False, ord=2):
+    """
+    Computes the vector norm of a vector (or batch of vectors) ``x``.
+
+    This function is Array API compatible.
+
+    Parameters
+    ----------
+    x : array_like
+        Input array.
+    axis : {None, int, 2-tuple of ints}, optional
+        If an integer, ``axis`` specifies the axis (dimension) along which
+        to compute vector norms. If an n-tuple, ``axis`` specifies the axes
+        (dimensions) along which to compute batched vector norms. If ``None``,
+        the vector norm must be computed over all array values (i.e.,
+        equivalent to computing the vector norm of a flattened array).
+        Default: ``None``.
+    keepdims : bool, optional
+        If this is set to True, the axes which are normed over are left in
+        the result as dimensions with size one. Default: False.
+    ord : {int, float, inf, -inf}, optional
+        The order of the norm. For details see the table under ``Notes``
+        in `numpy.linalg.norm`.
+
+    See Also
+    --------
+    numpy.linalg.norm : Generic norm function
+
+    Examples
+    --------
+    >>> from numpy import linalg as LA
+    >>> a = np.arange(9) + 1
+    >>> a
+    array([1, 2, 3, 4, 5, 6, 7, 8, 9])
+    >>> b = a.reshape((3, 3))
+    >>> b
+    array([[1, 2, 3],
+           [4, 5, 6],
+           [7, 8, 9]])
+
+    >>> LA.vector_norm(b)
+    16.881943016134134
+    >>> LA.vector_norm(b, ord=np.inf)
+    9.0
+    >>> LA.vector_norm(b, ord=-np.inf)
+    1.0
+
+    >>> LA.vector_norm(b, ord=0)
+    9.0
+    >>> LA.vector_norm(b, ord=1)
+    45.0
+    >>> LA.vector_norm(b, ord=-1)
+    0.3534857623790153
+    >>> LA.vector_norm(b, ord=2)
+    16.881943016134134
+    >>> LA.vector_norm(b, ord=-2)
+    0.8058837395885292
+
+    """
+    x = asanyarray(x)
+    shape = list(x.shape)
+    if axis is None:
+        # Note: np.linalg.norm() doesn't handle 0-D arrays
+        x = x.ravel()
+        _axis = 0
+    elif isinstance(axis, tuple):
+        # Note: The axis argument supports any number of axes, whereas
+        # np.linalg.norm() only supports a single axis for vector norm.
+        normalized_axis = normalize_axis_tuple(axis, x.ndim)
+        rest = tuple(i for i in range(x.ndim) if i not in normalized_axis)
+        newshape = axis + rest
+        x = _core_transpose(x, newshape).reshape(
+            (
+                prod([x.shape[i] for i in axis], dtype=int),
+                *[x.shape[i] for i in rest]
+            )
+        )
+        _axis = 0
+    else:
+        _axis = axis
+
+    res = norm(x, axis=_axis, ord=ord)
+
+    if keepdims:
+        # We can't reuse np.linalg.norm(keepdims) because of the reshape hacks
+        # above to avoid matrix norm logic.
+        _axis = normalize_axis_tuple(
+            range(len(shape)) if axis is None else axis, len(shape)
+        )
+        for i in _axis:
+            shape[i] = 1
+        res = res.reshape(tuple(shape))
+
+    return res
+
+
+# vecdot
+
+def _vecdot_dispatcher(x1, x2, /, *, axis=None):
+    return (x1, x2)
+
+@array_function_dispatch(_vecdot_dispatcher)
+def vecdot(x1, x2, /, *, axis=-1):
+    """
+    Computes the vector dot product.
+
+    This function is restricted to arguments compatible with the Array API,
+    contrary to :func:`numpy.vecdot`.
+
+    Let :math:`\\mathbf{a}` be a vector in ``x1`` and :math:`\\mathbf{b}` be
+    a corresponding vector in ``x2``. The dot product is defined as:
+
+    .. math::
+       \\mathbf{a} \\cdot \\mathbf{b} = \\sum_{i=0}^{n-1} \\overline{a_i}b_i
+
+    over the dimension specified by ``axis`` and where :math:`\\overline{a_i}`
+    denotes the complex conjugate if :math:`a_i` is complex and the identity
+    otherwise.
+
+    Parameters
+    ----------
+    x1 : array_like
+        First input array.
+    x2 : array_like
+        Second input array.
+    axis : int, optional
+        Axis over which to compute the dot product. Default: ``-1``.
+
+    Returns
+    -------
+    output : ndarray
+        The vector dot product of the input.
+
+    See Also
+    --------
+    numpy.vecdot
+
+    Examples
+    --------
+    Get the projected size along a given normal for an array of vectors.
+
+    >>> v = np.array([[0., 5., 0.], [0., 0., 10.], [0., 6., 8.]])
+    >>> n = np.array([0., 0.6, 0.8])
+    >>> np.linalg.vecdot(v, n)
+    array([ 3.,  8., 10.])
+
+    """
+    return _core_vecdot(x1, x2, axis=axis)
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.pyi b/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..4dd7efadf40e76d12fbf6f474edbfba98e10c20f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/_linalg.pyi
@@ -0,0 +1,548 @@
+from collections.abc import Iterable
+from typing import (
+    Any,
+    Literal as L,
+    NamedTuple,
+    Never,
+    SupportsIndex,
+    SupportsInt,
+    TypeAlias,
+    TypeVar,
+    overload,
+)
+
+import numpy as np
+from numpy import (
+    complex128,
+    complexfloating,
+    float64,
+    floating,
+    int32,
+    object_,
+    signedinteger,
+    timedelta64,
+    unsignedinteger,
+    vecdot,
+)
+from numpy._core.fromnumeric import matrix_transpose
+from numpy._globals import _NoValueType
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeComplex_co,
+    _ArrayLikeFloat_co,
+    _ArrayLikeInt_co,
+    _ArrayLikeNumber_co,
+    _ArrayLikeObject_co,
+    _ArrayLikeTD64_co,
+    _ArrayLikeUInt_co,
+    _NestedSequence,
+    _ShapeLike,
+)
+from numpy.linalg import LinAlgError
+
+__all__ = [
+    "matrix_power",
+    "solve",
+    "tensorsolve",
+    "tensorinv",
+    "inv",
+    "cholesky",
+    "eigvals",
+    "eigvalsh",
+    "pinv",
+    "slogdet",
+    "det",
+    "svd",
+    "svdvals",
+    "eig",
+    "eigh",
+    "lstsq",
+    "norm",
+    "qr",
+    "cond",
+    "matrix_rank",
+    "LinAlgError",
+    "multi_dot",
+    "trace",
+    "diagonal",
+    "cross",
+    "outer",
+    "tensordot",
+    "matmul",
+    "matrix_transpose",
+    "matrix_norm",
+    "vector_norm",
+    "vecdot",
+]
+
+_NumberT = TypeVar("_NumberT", bound=np.number)
+_NumericScalarT = TypeVar("_NumericScalarT", bound=np.number | np.timedelta64 | np.object_)
+
+_ModeKind: TypeAlias = L["reduced", "complete", "r", "raw"]
+
+###
+
+fortran_int = np.intc
+
+class EigResult(NamedTuple):
+    eigenvalues: NDArray[Any]
+    eigenvectors: NDArray[Any]
+
+class EighResult(NamedTuple):
+    eigenvalues: NDArray[Any]
+    eigenvectors: NDArray[Any]
+
+class QRResult(NamedTuple):
+    Q: NDArray[Any]
+    R: NDArray[Any]
+
+class SlogdetResult(NamedTuple):
+    # TODO: `sign` and `logabsdet` are scalars for input 2D arrays and
+    # a `(x.ndim - 2)`` dimensionl arrays otherwise
+    sign: Any
+    logabsdet: Any
+
+class SVDResult(NamedTuple):
+    U: NDArray[Any]
+    S: NDArray[Any]
+    Vh: NDArray[Any]
+
+@overload
+def tensorsolve(
+    a: _ArrayLikeInt_co,
+    b: _ArrayLikeInt_co,
+    axes: Iterable[int] | None = None,
+) -> NDArray[float64]: ...
+@overload
+def tensorsolve(
+    a: _ArrayLikeFloat_co,
+    b: _ArrayLikeFloat_co,
+    axes: Iterable[int] | None = None,
+) -> NDArray[floating]: ...
+@overload
+def tensorsolve(
+    a: _ArrayLikeComplex_co,
+    b: _ArrayLikeComplex_co,
+    axes: Iterable[int] | None = None,
+) -> NDArray[complexfloating]: ...
+
+@overload
+def solve(
+    a: _ArrayLikeInt_co,
+    b: _ArrayLikeInt_co,
+) -> NDArray[float64]: ...
+@overload
+def solve(
+    a: _ArrayLikeFloat_co,
+    b: _ArrayLikeFloat_co,
+) -> NDArray[floating]: ...
+@overload
+def solve(
+    a: _ArrayLikeComplex_co,
+    b: _ArrayLikeComplex_co,
+) -> NDArray[complexfloating]: ...
+
+@overload
+def tensorinv(
+    a: _ArrayLikeInt_co,
+    ind: int = 2,
+) -> NDArray[float64]: ...
+@overload
+def tensorinv(
+    a: _ArrayLikeFloat_co,
+    ind: int = 2,
+) -> NDArray[floating]: ...
+@overload
+def tensorinv(
+    a: _ArrayLikeComplex_co,
+    ind: int = 2,
+) -> NDArray[complexfloating]: ...
+
+@overload
+def inv(a: _ArrayLikeInt_co) -> NDArray[float64]: ...
+@overload
+def inv(a: _ArrayLikeFloat_co) -> NDArray[floating]: ...
+@overload
+def inv(a: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+# TODO: The supported input and output dtypes are dependent on the value of `n`.
+# For example: `n < 0` always casts integer types to float64
+def matrix_power(
+    a: _ArrayLikeComplex_co | _ArrayLikeObject_co,
+    n: SupportsIndex,
+) -> NDArray[Any]: ...
+
+@overload
+def cholesky(a: _ArrayLikeInt_co, /, *, upper: bool = False) -> NDArray[float64]: ...
+@overload
+def cholesky(a: _ArrayLikeFloat_co, /, *, upper: bool = False) -> NDArray[floating]: ...
+@overload
+def cholesky(a: _ArrayLikeComplex_co, /, *, upper: bool = False) -> NDArray[complexfloating]: ...
+
+@overload
+def outer(x1: _ArrayLike[Never], x2: _ArrayLike[Never], /) -> NDArray[Any]: ...
+@overload
+def outer(x1: _ArrayLikeBool_co, x2: _ArrayLikeBool_co, /) -> NDArray[np.bool]: ...
+@overload
+def outer(x1: _ArrayLike[_NumberT], x2: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ...
+@overload
+def outer(x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ...
+@overload
+def outer(x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
+@overload
+def outer(x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
+@overload
+def outer(x1: _ArrayLikeComplex_co, x2: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
+@overload
+def outer(x1: _ArrayLikeTD64_co, x2: _ArrayLikeTD64_co, /) -> NDArray[timedelta64]: ...
+@overload
+def outer(x1: _ArrayLikeObject_co, x2: _ArrayLikeObject_co, /) -> NDArray[object_]: ...
+@overload
+def outer(
+    x1: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
+    x2: _ArrayLikeComplex_co | _ArrayLikeTD64_co | _ArrayLikeObject_co,
+    /,
+) -> NDArray[Any]: ...
+
+@overload
+def qr(a: _ArrayLikeInt_co, mode: _ModeKind = "reduced") -> QRResult: ...
+@overload
+def qr(a: _ArrayLikeFloat_co, mode: _ModeKind = "reduced") -> QRResult: ...
+@overload
+def qr(a: _ArrayLikeComplex_co, mode: _ModeKind = "reduced") -> QRResult: ...
+
+@overload
+def eigvals(a: _ArrayLikeInt_co) -> NDArray[float64] | NDArray[complex128]: ...
+@overload
+def eigvals(a: _ArrayLikeFloat_co) -> NDArray[floating] | NDArray[complexfloating]: ...
+@overload
+def eigvals(a: _ArrayLikeComplex_co) -> NDArray[complexfloating]: ...
+
+@overload
+def eigvalsh(a: _ArrayLikeInt_co, UPLO: L["L", "U", "l", "u"] = "L") -> NDArray[float64]: ...
+@overload
+def eigvalsh(a: _ArrayLikeComplex_co, UPLO: L["L", "U", "l", "u"] = "L") -> NDArray[floating]: ...
+
+@overload
+def eig(a: _ArrayLikeInt_co) -> EigResult: ...
+@overload
+def eig(a: _ArrayLikeFloat_co) -> EigResult: ...
+@overload
+def eig(a: _ArrayLikeComplex_co) -> EigResult: ...
+
+@overload
+def eigh(
+    a: _ArrayLikeInt_co,
+    UPLO: L["L", "U", "l", "u"] = "L",
+) -> EighResult: ...
+@overload
+def eigh(
+    a: _ArrayLikeFloat_co,
+    UPLO: L["L", "U", "l", "u"] = "L",
+) -> EighResult: ...
+@overload
+def eigh(
+    a: _ArrayLikeComplex_co,
+    UPLO: L["L", "U", "l", "u"] = "L",
+) -> EighResult: ...
+
+@overload
+def svd(
+    a: _ArrayLikeInt_co,
+    full_matrices: bool = True,
+    compute_uv: L[True] = True,
+    hermitian: bool = False,
+) -> SVDResult: ...
+@overload
+def svd(
+    a: _ArrayLikeFloat_co,
+    full_matrices: bool = True,
+    compute_uv: L[True] = True,
+    hermitian: bool = False,
+) -> SVDResult: ...
+@overload
+def svd(
+    a: _ArrayLikeComplex_co,
+    full_matrices: bool = True,
+    compute_uv: L[True] = True,
+    hermitian: bool = False,
+) -> SVDResult: ...
+@overload
+def svd(
+    a: _ArrayLikeInt_co,
+    full_matrices: bool = True,
+    *,
+    compute_uv: L[False],
+    hermitian: bool = False,
+) -> NDArray[float64]: ...
+@overload
+def svd(
+    a: _ArrayLikeInt_co,
+    full_matrices: bool,
+    compute_uv: L[False],
+    hermitian: bool = False,
+) -> NDArray[float64]: ...
+@overload
+def svd(
+    a: _ArrayLikeComplex_co,
+    full_matrices: bool = True,
+    *,
+    compute_uv: L[False],
+    hermitian: bool = False,
+) -> NDArray[floating]: ...
+@overload
+def svd(
+    a: _ArrayLikeComplex_co,
+    full_matrices: bool,
+    compute_uv: L[False],
+    hermitian: bool = False,
+) -> NDArray[floating]: ...
+
+# the ignored `overload-overlap` mypy error below is a false-positive
+@overload
+def svdvals(  # type: ignore[overload-overlap]
+    x: _ArrayLike[np.float64 | np.complex128 | np.integer | np.bool] | _NestedSequence[complex], /
+) -> NDArray[np.float64]: ...
+@overload
+def svdvals(x: _ArrayLike[np.float32 | np.complex64], /) -> NDArray[np.float32]: ...
+@overload
+def svdvals(x: _ArrayLikeNumber_co, /) -> NDArray[floating]: ...
+
+# TODO: Returns a scalar for 2D arrays and
+# a `(x.ndim - 2)`` dimensionl array otherwise
+def cond(x: _ArrayLikeComplex_co, p: float | L["fro", "nuc"] | None = None) -> Any: ...
+
+# TODO: Returns `int` for <2D arrays and `intp` otherwise
+def matrix_rank(
+    A: _ArrayLikeComplex_co,
+    tol: _ArrayLikeFloat_co | None = None,
+    hermitian: bool = False,
+    *,
+    rtol: _ArrayLikeFloat_co | None = None,
+) -> Any: ...
+
+@overload
+def pinv(
+    a: _ArrayLikeInt_co,
+    rcond: _ArrayLikeFloat_co | None = None,
+    hermitian: bool = False,
+    *,
+    rtol: _ArrayLikeFloat_co | _NoValueType = ...,
+) -> NDArray[float64]: ...
+@overload
+def pinv(
+    a: _ArrayLikeFloat_co,
+    rcond: _ArrayLikeFloat_co | None = None,
+    hermitian: bool = False,
+    *,
+    rtol: _ArrayLikeFloat_co | _NoValueType = ...,
+) -> NDArray[floating]: ...
+@overload
+def pinv(
+    a: _ArrayLikeComplex_co,
+    rcond: _ArrayLikeFloat_co | None = None,
+    hermitian: bool = False,
+    *,
+    rtol: _ArrayLikeFloat_co | _NoValueType = ...,
+) -> NDArray[complexfloating]: ...
+
+# TODO: Returns a 2-tuple of scalars for 2D arrays and
+# a 2-tuple of `(a.ndim - 2)`` dimensionl arrays otherwise
+def slogdet(a: _ArrayLikeComplex_co) -> SlogdetResult: ...
+
+# TODO: Returns a 2-tuple of scalars for 2D arrays and
+# a 2-tuple of `(a.ndim - 2)`` dimensionl arrays otherwise
+def det(a: _ArrayLikeComplex_co) -> Any: ...
+
+@overload
+def lstsq(a: _ArrayLikeInt_co, b: _ArrayLikeInt_co, rcond: float | None = None) -> tuple[
+    NDArray[float64],
+    NDArray[float64],
+    int32,
+    NDArray[float64],
+]: ...
+@overload
+def lstsq(a: _ArrayLikeFloat_co, b: _ArrayLikeFloat_co, rcond: float | None = None) -> tuple[
+    NDArray[floating],
+    NDArray[floating],
+    int32,
+    NDArray[floating],
+]: ...
+@overload
+def lstsq(a: _ArrayLikeComplex_co, b: _ArrayLikeComplex_co, rcond: float | None = None) -> tuple[
+    NDArray[complexfloating],
+    NDArray[floating],
+    int32,
+    NDArray[floating],
+]: ...
+
+@overload
+def norm(
+    x: ArrayLike,
+    ord: float | L["fro", "nuc"] | None = None,
+    axis: None = None,
+    keepdims: L[False] = False,
+) -> floating: ...
+@overload
+def norm(
+    x: ArrayLike,
+    ord: float | L["fro", "nuc"] | None,
+    axis: SupportsInt | SupportsIndex | tuple[int, ...] | None,
+    keepdims: bool = False,
+) -> Any: ...
+@overload
+def norm(
+    x: ArrayLike,
+    ord: float | L["fro", "nuc"] | None = None,
+    *,
+    axis: SupportsInt | SupportsIndex | tuple[int, ...] | None,
+    keepdims: bool = False,
+) -> Any: ...
+
+@overload
+def matrix_norm(
+    x: ArrayLike,
+    /,
+    *,
+    ord: float | L["fro", "nuc"] | None = "fro",
+    keepdims: L[False] = False,
+) -> floating: ...
+@overload
+def matrix_norm(
+    x: ArrayLike,
+    /,
+    *,
+    ord: float | L["fro", "nuc"] | None = "fro",
+    keepdims: bool = False,
+) -> Any: ...
+
+@overload
+def vector_norm(
+    x: ArrayLike,
+    /,
+    *,
+    axis: None = None,
+    ord: float | None = 2,
+    keepdims: L[False] = False,
+) -> floating: ...
+@overload
+def vector_norm(
+    x: ArrayLike,
+    /,
+    *,
+    axis: SupportsInt | SupportsIndex | tuple[int, ...],
+    ord: float | None = 2,
+    keepdims: bool = False,
+) -> Any: ...
+
+# keep in sync with numpy._core.numeric.tensordot (ignoring `/, *`)
+@overload
+def tensordot(
+    a: _ArrayLike[_NumericScalarT],
+    b: _ArrayLike[_NumericScalarT],
+    /,
+    *,
+    axes: int | tuple[_ShapeLike, _ShapeLike] = 2,
+) -> NDArray[_NumericScalarT]: ...
+@overload
+def tensordot(
+    a: _ArrayLikeBool_co,
+    b: _ArrayLikeBool_co,
+    /,
+    *,
+    axes: int | tuple[_ShapeLike, _ShapeLike] = 2,
+) -> NDArray[np.bool_]: ...
+@overload
+def tensordot(
+    a: _ArrayLikeInt_co,
+    b: _ArrayLikeInt_co,
+    /,
+    *,
+    axes: int | tuple[_ShapeLike, _ShapeLike] = 2,
+) -> NDArray[np.int_ | Any]: ...
+@overload
+def tensordot(
+    a: _ArrayLikeFloat_co,
+    b: _ArrayLikeFloat_co,
+    /,
+    *,
+    axes: int | tuple[_ShapeLike, _ShapeLike] = 2,
+) -> NDArray[np.float64 | Any]: ...
+@overload
+def tensordot(
+    a: _ArrayLikeComplex_co,
+    b: _ArrayLikeComplex_co,
+    /,
+    *,
+    axes: int | tuple[_ShapeLike, _ShapeLike] = 2,
+) -> NDArray[np.complex128 | Any]: ...
+
+# TODO: Returns a scalar or array
+def multi_dot(
+    arrays: Iterable[_ArrayLikeComplex_co | _ArrayLikeObject_co | _ArrayLikeTD64_co],
+    *,
+    out: NDArray[Any] | None = None,
+) -> Any: ...
+
+def diagonal(
+    x: ArrayLike,  # >= 2D array
+    /,
+    *,
+    offset: SupportsIndex = 0,
+) -> NDArray[Any]: ...
+
+def trace(
+    x: ArrayLike,  # >= 2D array
+    /,
+    *,
+    offset: SupportsIndex = 0,
+    dtype: DTypeLike | None = None,
+) -> Any: ...
+
+@overload
+def cross(
+    x1: _ArrayLikeUInt_co,
+    x2: _ArrayLikeUInt_co,
+    /,
+    *,
+    axis: int = -1,
+) -> NDArray[unsignedinteger]: ...
+@overload
+def cross(
+    x1: _ArrayLikeInt_co,
+    x2: _ArrayLikeInt_co,
+    /,
+    *,
+    axis: int = -1,
+) -> NDArray[signedinteger]: ...
+@overload
+def cross(
+    x1: _ArrayLikeFloat_co,
+    x2: _ArrayLikeFloat_co,
+    /,
+    *,
+    axis: int = -1,
+) -> NDArray[floating]: ...
+@overload
+def cross(
+    x1: _ArrayLikeComplex_co,
+    x2: _ArrayLikeComplex_co,
+    /,
+    *,
+    axis: int = -1,
+) -> NDArray[complexfloating]: ...
+
+@overload
+def matmul(x1: _ArrayLike[_NumberT], x2: _ArrayLike[_NumberT], /) -> NDArray[_NumberT]: ...
+@overload
+def matmul(x1: _ArrayLikeUInt_co, x2: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger]: ...
+@overload
+def matmul(x1: _ArrayLikeInt_co, x2: _ArrayLikeInt_co, /) -> NDArray[signedinteger]: ...
+@overload
+def matmul(x1: _ArrayLikeFloat_co, x2: _ArrayLikeFloat_co, /) -> NDArray[floating]: ...
+@overload
+def matmul(x1: _ArrayLikeComplex_co, x2: _ArrayLikeComplex_co, /) -> NDArray[complexfloating]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/_umath_linalg.cp313-win_amd64.lib b/python/user_packages/Python313/site-packages/numpy/linalg/_umath_linalg.cp313-win_amd64.lib
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index 0000000000000000000000000000000000000000..4bc4b98defdedef5c67e7725fac8296afb4bc7f0
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diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/_umath_linalg.pyi b/python/user_packages/Python313/site-packages/numpy/linalg/_umath_linalg.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..17ef482fead20ddae9bcfc53eae59ec2eefec9f2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/_umath_linalg.pyi
@@ -0,0 +1,60 @@
+from typing import Final, Literal as L
+
+import numpy as np
+from numpy._typing._ufunc import _GUFunc_Nin2_Nout1
+
+__version__: Final[str] = ...
+_ilp64: Final[bool] = ...
+
+###
+# 1 -> 1
+
+# (m,m) -> ()
+det: Final[np.ufunc] = ...
+# (m,m) -> (m)
+cholesky_lo: Final[np.ufunc] = ...
+cholesky_up: Final[np.ufunc] = ...
+eigvals: Final[np.ufunc] = ...
+eigvalsh_lo: Final[np.ufunc] = ...
+eigvalsh_up: Final[np.ufunc] = ...
+# (m,m) -> (m,m)
+inv: Final[np.ufunc] = ...
+# (m,n) -> (p)
+qr_r_raw: Final[np.ufunc] = ...
+svd: Final[np.ufunc] = ...
+
+###
+# 1 -> 2
+
+# (m,m) -> (), ()
+slogdet: Final[np.ufunc] = ...
+# (m,m) -> (m), (m,m)
+eig: Final[np.ufunc] = ...
+eigh_lo: Final[np.ufunc] = ...
+eigh_up: Final[np.ufunc] = ...
+
+###
+# 2 -> 1
+
+# (m,n), (n) -> (m,m)
+qr_complete: Final[_GUFunc_Nin2_Nout1[L["qr_complete"], L[2], None, L["(m,n),(n)->(m,m)"]]] = ...
+# (m,n), (k) -> (m,k)
+qr_reduced: Final[_GUFunc_Nin2_Nout1[L["qr_reduced"], L[2], None, L["(m,n),(k)->(m,k)"]]] = ...
+# (m,m), (m,n) -> (m,n)
+solve: Final[_GUFunc_Nin2_Nout1[L["solve"], L[4], None, L["(m,m),(m,n)->(m,n)"]]] = ...
+# (m,m), (m) -> (m)
+solve1: Final[_GUFunc_Nin2_Nout1[L["solve1"], L[4], None, L["(m,m),(m)->(m)"]]] = ...
+
+###
+# 1 -> 3
+
+# (m,n) -> (m,m), (p), (n,n)
+svd_f: Final[np.ufunc] = ...
+# (m,n) -> (m,p), (p), (p,n)
+svd_s: Final[np.ufunc] = ...
+
+###
+# 3 -> 4
+
+# (m,n), (m,k), () -> (n,k), (k), (), (p)
+lstsq: Final[np.ufunc] = ...
diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.cp313-win_amd64.lib b/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.cp313-win_amd64.lib
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diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.cp313-win_amd64.pyd b/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.cp313-win_amd64.pyd
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index 0000000000000000000000000000000000000000..44d73914afb078f5ad1e7237015919d13e807862
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diff --git a/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.pyi b/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..c341ab8f09b7ccde79adee71d625348d3e726a23
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/linalg/lapack_lite.pyi
@@ -0,0 +1,143 @@
+from typing import Final, TypedDict, type_check_only
+
+import numpy as np
+from numpy._typing import NDArray
+
+from ._linalg import fortran_int
+
+###
+
+@type_check_only
+class _GELSD(TypedDict):
+    m: int
+    n: int
+    nrhs: int
+    lda: int
+    ldb: int
+    rank: int
+    lwork: int
+    info: int
+
+@type_check_only
+class _DGELSD(_GELSD):
+    dgelsd_: int
+    rcond: float
+
+@type_check_only
+class _ZGELSD(_GELSD):
+    zgelsd_: int
+
+@type_check_only
+class _GEQRF(TypedDict):
+    m: int
+    n: int
+    lda: int
+    lwork: int
+    info: int
+
+@type_check_only
+class _DGEQRF(_GEQRF):
+    dgeqrf_: int
+
+@type_check_only
+class _ZGEQRF(_GEQRF):
+    zgeqrf_: int
+
+@type_check_only
+class _DORGQR(TypedDict):
+    dorgqr_: int
+    info: int
+
+@type_check_only
+class _ZUNGQR(TypedDict):
+    zungqr_: int
+    info: int
+
+###
+
+_ilp64: Final[bool] = ...
+
+class LapackError(Exception): ...
+
+def dgelsd(
+    m: int,
+    n: int,
+    nrhs: int,
+    a: NDArray[np.float64],
+    lda: int,
+    b: NDArray[np.float64],
+    ldb: int,
+    s: NDArray[np.float64],
+    rcond: float,
+    rank: int,
+    work: NDArray[np.float64],
+    lwork: int,
+    iwork: NDArray[fortran_int],
+    info: int,
+) -> _DGELSD: ...
+def zgelsd(
+    m: int,
+    n: int,
+    nrhs: int,
+    a: NDArray[np.complex128],
+    lda: int,
+    b: NDArray[np.complex128],
+    ldb: int,
+    s: NDArray[np.float64],
+    rcond: float,
+    rank: int,
+    work: NDArray[np.complex128],
+    lwork: int,
+    rwork: NDArray[np.float64],
+    iwork: NDArray[fortran_int],
+    info: int,
+) -> _ZGELSD: ...
+
+#
+def dgeqrf(
+    m: int,
+    n: int,
+    a: NDArray[np.float64],  # in/out, shape: (lda, n)
+    lda: int,
+    tau: NDArray[np.float64],  # out, shape: (min(m, n),)
+    work: NDArray[np.float64],  # out, shape: (max(1, lwork),)
+    lwork: int,
+    info: int,  # out
+) -> _DGEQRF: ...
+def zgeqrf(
+    m: int,
+    n: int,
+    a: NDArray[np.complex128],  # in/out, shape: (lda, n)
+    lda: int,
+    tau: NDArray[np.complex128],  # out, shape: (min(m, n),)
+    work: NDArray[np.complex128],  # out, shape: (max(1, lwork),)
+    lwork: int,
+    info: int,  # out
+) -> _ZGEQRF: ...
+
+#
+def dorgqr(
+    m: int,  # >=0
+    n: int,  # m >= n >= 0
+    k: int,  # n >= k >= 0
+    a: NDArray[np.float64],  # in/out, shape: (lda, n)
+    lda: int,  # >= max(1, m)
+    tau: NDArray[np.float64],  # in, shape: (k,)
+    work: NDArray[np.float64],  # out, shape: (max(1, lwork),)
+    lwork: int,
+    info: int,  # out
+) -> _DORGQR: ...
+def zungqr(
+    m: int,
+    n: int,
+    k: int,
+    a: NDArray[np.complex128],
+    lda: int,
+    tau: NDArray[np.complex128],
+    work: NDArray[np.complex128],
+    lwork: int,
+    info: int,
+) -> _ZUNGQR: ...
+
+#
+def xerbla(srname: object, info: int) -> None: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/API_CHANGES.txt b/python/user_packages/Python313/site-packages/numpy/ma/API_CHANGES.txt
new file mode 100644
index 0000000000000000000000000000000000000000..48c420ed33554f657ec5a0e2d63635aa1b97f061
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/API_CHANGES.txt
@@ -0,0 +1,135 @@
+.. -*- rest -*-
+
+==================================================
+API changes in the new masked array implementation
+==================================================
+
+Masked arrays are subclasses of ndarray
+---------------------------------------
+
+Contrary to the original implementation, masked arrays are now regular
+ndarrays::
+
+  >>> x = masked_array([1,2,3],mask=[0,0,1])
+  >>> print isinstance(x, numpy.ndarray)
+  True
+
+
+``_data`` returns a view of the masked array
+--------------------------------------------
+
+Masked arrays are composed of a ``_data`` part and a ``_mask``. Accessing the
+``_data`` part will return a regular ndarray or any of its subclass, depending
+on the initial data::
+
+  >>> x = masked_array(numpy.matrix([[1,2],[3,4]]),mask=[[0,0],[0,1]])
+  >>> print x._data
+  [[1 2]
+   [3 4]]
+  >>> print type(x._data)
+  <class 'numpy.matrixlib.defmatrix.matrix'>
+
+
+In practice, ``_data`` is implemented as a property, not as an attribute.
+Therefore, you cannot access it directly, and some simple tests such as the
+following one will fail::
+
+  >>>x._data is x._data
+  False
+
+
+``filled(x)`` can return a subclass of ndarray
+----------------------------------------------
+The function ``filled(a)`` returns an array of the same type as ``a._data``::
+
+  >>> x = masked_array(numpy.matrix([[1,2],[3,4]]),mask=[[0,0],[0,1]])
+  >>> y = filled(x)
+  >>> print type(y)
+  <class 'numpy.matrixlib.defmatrix.matrix'>
+  >>> print y
+  matrix([[     1,      2],
+          [     3, 999999]])
+
+
+``put``, ``putmask`` behave like their ndarray counterparts
+-----------------------------------------------------------
+
+Previously, ``putmask`` was used like this::
+
+  mask = [False,True,True]
+  x = array([1,4,7],mask=mask)
+  putmask(x,mask,[3])
+
+which translated to::
+
+  x[~mask] = [3]
+
+(Note that a ``True``-value in a mask suppresses a value.)
+
+In other words, the mask had the same length as ``x``, whereas
+``values`` had ``sum(~mask)`` elements.
+
+Now, the behaviour is similar to that of ``ndarray.putmask``, where
+the mask and the values are both the same length as ``x``, i.e.
+
+::
+
+  putmask(x,mask,[3,0,0])
+
+
+``fill_value`` is a property
+----------------------------
+
+``fill_value`` is no longer a method, but a property::
+
+  >>> print x.fill_value
+  999999
+
+``cumsum`` and ``cumprod`` ignore missing values
+------------------------------------------------
+
+Missing values are assumed to be the identity element, i.e. 0 for
+``cumsum`` and 1 for ``cumprod``::
+
+  >>> x = N.ma.array([1,2,3,4],mask=[False,True,False,False])
+  >>> print x
+  [1 -- 3 4]
+  >>> print x.cumsum()
+  [1 -- 4 8]
+  >> print x.cumprod()
+  [1 -- 3 12]
+
+``bool(x)`` raises a ValueError
+-------------------------------
+
+Masked arrays now behave like regular ``ndarrays``, in that they cannot be
+converted to booleans:
+
+::
+
+  >>> x = N.ma.array([1,2,3])
+  >>> bool(x)
+  Traceback (most recent call last):
+    File "<stdin>", line 1, in <module>
+  ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
+
+
+==================================
+New features (non exhaustive list)
+==================================
+
+``mr_``
+-------
+
+``mr_`` mimics the behavior of ``r_`` for masked arrays::
+
+  >>> np.ma.mr_[3,4,5]
+  masked_array(data = [3 4 5],
+        mask = False,
+        fill_value=999999)
+
+
+``anom``
+--------
+
+The ``anom`` method returns the deviations from the average (anomalies).
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/LICENSE b/python/user_packages/Python313/site-packages/numpy/ma/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..f165a0f6dbf57b89e2f6e23b9f042750dde3caab
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/LICENSE
@@ -0,0 +1,24 @@
+* Copyright (c) 2006, University of Georgia and Pierre G.F. Gerard-Marchant
+* All rights reserved.
+* Redistribution and use in source and binary forms, with or without
+* modification, are permitted provided that the following conditions are met:
+*
+*     * Redistributions of source code must retain the above copyright
+*       notice, this list of conditions and the following disclaimer.
+*     * Redistributions in binary form must reproduce the above copyright
+*       notice, this list of conditions and the following disclaimer in the
+*       documentation and/or other materials provided with the distribution.
+*     * Neither the name of the University of Georgia nor the
+*       names of its contributors may be used to endorse or promote products
+*       derived from this software without specific prior written permission.
+*
+* THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+* DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY
+* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
\ No newline at end of file
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/README.rst b/python/user_packages/Python313/site-packages/numpy/ma/README.rst
new file mode 100644
index 0000000000000000000000000000000000000000..0f39221be7fbcf95ecce6b296cbd16c44ac241e1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/README.rst
@@ -0,0 +1,236 @@
+==================================
+A guide to masked arrays in NumPy
+==================================
+
+.. Contents::
+
+See http://www.scipy.org/scipy/numpy/wiki/MaskedArray (dead link)
+for updates of this document.
+
+
+History
+-------
+
+As a regular user of MaskedArray, I (Pierre G.F. Gerard-Marchant) became
+increasingly frustrated with the subclassing of masked arrays (even if
+I can only blame my inexperience). I needed to develop a class of arrays
+that could store some additional information along with numerical values,
+while keeping the possibility for missing data (picture storing a series
+of dates along with measurements, what would later become the `TimeSeries
+Scikit <http://projects.scipy.org/scipy/scikits/wiki/TimeSeries>`__
+(dead link).
+
+I started to implement such a class, but then quickly realized that
+any additional information disappeared when processing these subarrays
+(for example, adding a constant value to a subarray would erase its
+dates). I ended up writing the equivalent of *numpy.core.ma* for my
+particular class, ufuncs included. Everything went fine until I needed to
+subclass my new class, when more problems showed up: some attributes of
+the new subclass were lost during processing. I identified the culprit as
+MaskedArray, which returns masked ndarrays when I expected masked
+arrays of my class. I was preparing myself to rewrite *numpy.core.ma*
+when I forced myself to learn how to subclass ndarrays. As I became more
+familiar with the *__new__* and *__array_finalize__* methods,
+I started to wonder why masked arrays were objects, and not ndarrays,
+and whether it wouldn't be more convenient for subclassing if they did
+behave like regular ndarrays.
+
+The new *maskedarray* is what I eventually come up with. The
+main differences with the initial *numpy.core.ma* package are
+that MaskedArray is now a subclass of *ndarray* and that the
+*_data* section can now be any subclass of *ndarray*. Apart from a
+couple of issues listed below, the behavior of the new MaskedArray
+class reproduces the old one. Initially the *maskedarray*
+implementation was marginally slower than *numpy.ma* in some areas,
+but work is underway to speed it up; the expectation is that it can be
+made substantially faster than the present *numpy.ma*.
+
+
+Note that if the subclass has some special methods and
+attributes, they are not propagated to the masked version:
+this would require a modification of the *__getattribute__*
+method (first trying *ndarray.__getattribute__*, then trying
+*self._data.__getattribute__* if an exception is raised in the first
+place), which really slows things down.
+
+Main differences
+----------------
+
+ * The *_data* part of the masked array can be any subclass of ndarray (but not recarray, cf below).
+ * *fill_value* is now a property, not a function.
+ * in the majority of cases, the mask is forced to *nomask* when no value is actually masked. A notable exception is when a masked array (with no masked values) has just been unpickled.
+ * I got rid of the *share_mask* flag, I never understood its purpose.
+ * *put*, *putmask* and *take* now mimic the ndarray methods, to avoid unpleasant surprises. Moreover, *put* and *putmask* both update the mask when needed.  * if *a* is a masked array, *bool(a)* raises a *ValueError*, as it does with ndarrays.
+ * in the same way, the comparison of two masked arrays is a masked array, not a boolean
+ * *filled(a)* returns an array of the same subclass as *a._data*, and no test is performed on whether it is contiguous or not.
+ * the mask is always printed, even if it's *nomask*, which makes things easy (for me at least) to remember that a masked array is used.
+ * *cumsum* works as if the *_data* array was filled with 0. The mask is preserved, but not updated.
+ * *cumprod* works as if the *_data* array was filled with 1. The mask is preserved, but not updated.
+
+New features
+------------
+
+This list is non-exhaustive...
+
+ * the *mr_* function mimics *r_* for masked arrays.
+ * the *anom* method returns the anomalies (deviations from the average)
+
+Using the new package with numpy.core.ma
+----------------------------------------
+
+I tried to make sure that the new package can understand old masked
+arrays. Unfortunately, there's no upward compatibility.
+
+For example:
+
+>>> import numpy.core.ma as old_ma
+>>> import maskedarray as new_ma
+>>> x = old_ma.array([1,2,3,4,5], mask=[0,0,1,0,0])
+>>> x
+array(data =
+ [     1      2 999999      4      5],
+      mask =
+ [False False True False False],
+      fill_value=999999)
+>>> y = new_ma.array([1,2,3,4,5], mask=[0,0,1,0,0])
+>>> y
+array(data = [1 2 -- 4 5],
+      mask = [False False True False False],
+      fill_value=999999)
+>>> x==y
+array(data =
+ [True True True True True],
+      mask =
+ [False False True False False],
+      fill_value=?)
+>>> old_ma.getmask(x) == new_ma.getmask(x)
+array([True, True, True, True, True])
+>>> old_ma.getmask(y) == new_ma.getmask(y)
+array([True, True, False, True, True])
+>>> old_ma.getmask(y)
+False
+
+
+Using maskedarray with matplotlib
+---------------------------------
+
+Starting with matplotlib 0.91.2, the masked array importing will work with
+the maskedarray branch) as well as with earlier versions.
+
+By default matplotlib still uses numpy.ma, but there is an rcParams setting
+that you can use to select maskedarray instead.  In the matplotlibrc file
+you will find::
+
+  #maskedarray : False       # True to use external maskedarray module
+                             # instead of numpy.ma; this is a temporary #
+                             setting for testing maskedarray.
+
+
+Uncomment and set to True to select maskedarray everywhere.
+Alternatively, you can test a script with maskedarray by using a
+command-line option, e.g.::
+
+  python simple_plot.py --maskedarray
+
+
+Masked records
+--------------
+
+Like *numpy.ma.core*, the *ndarray*-based implementation
+of MaskedArray is limited when working with records: you can
+mask any record of the array, but not a field in a record. If you
+need this feature, you may want to give the *mrecords* package
+a try (available in the *maskedarray* directory in the scipy
+sandbox). This module defines a new class, *MaskedRecord*. An
+instance of this class accepts a *recarray* as data, and uses two
+masks: the *fieldmask* has as many entries as records in the array,
+each entry with the same fields as a record, but of boolean types:
+they indicate whether the field is masked or not; a record entry
+is flagged as masked in the *mask* array if all the fields are
+masked. A few examples in the file should give you an idea of what
+can be done. Note that *mrecords* is still experimental...
+
+Optimizing maskedarray
+----------------------
+
+Should masked arrays be filled before processing or not?
+--------------------------------------------------------
+
+In the current implementation, most operations on masked arrays involve
+the following steps:
+
+ * the input arrays are filled
+ * the operation is performed on the filled arrays
+ * the mask is set for the results, from the combination of the input masks and the mask corresponding to the domain of the operation.
+
+For example, consider the division of two masked arrays::
+
+  import numpy
+  import maskedarray as ma
+  x = ma.array([1,2,3,4],mask=[1,0,0,0], dtype=numpy.float64)
+  y = ma.array([-1,0,1,2], mask=[0,0,0,1], dtype=numpy.float64)
+
+The division of x by y is then computed as::
+
+  d1 = x.filled(0) # d1 = array([0., 2., 3., 4.])
+  d2 = y.filled(1) # array([-1.,  0.,  1.,  1.])
+  m = ma.mask_or(ma.getmask(x), ma.getmask(y)) # m =
+  array([True,False,False,True])
+  dm = ma.divide.domain(d1,d2) # array([False,  True, False, False])
+  result = (d1/d2).view(MaskedArray) # masked_array([-0. inf, 3., 4.])
+  result._mask = logical_or(m, dm)
+
+Note that a division by zero takes place. To avoid it, we can consider
+to fill the input arrays, taking the domain mask into account, so that::
+
+  d1 = x._data.copy() # d1 = array([1., 2., 3., 4.])
+  d2 = y._data.copy() # array([-1.,  0.,  1.,  2.])
+  dm = ma.divide.domain(d1,d2) # array([False,  True, False, False])
+  numpy.putmask(d2, dm, 1) # d2 = array([-1.,  1.,  1.,  2.])
+  m = ma.mask_or(ma.getmask(x), ma.getmask(y)) # m =
+  array([True,False,False,True])
+  result = (d1/d2).view(MaskedArray) # masked_array([-1. 0., 3., 2.])
+  result._mask = logical_or(m, dm)
+
+Note that the *.copy()* is required to avoid updating the inputs with
+*putmask*.  The *.filled()* method also involves a *.copy()*.
+
+A third possibility consists in avoid filling the arrays::
+
+  d1 = x._data # d1 = array([1., 2., 3., 4.])
+  d2 = y._data # array([-1.,  0.,  1.,  2.])
+  dm = ma.divide.domain(d1,d2) # array([False,  True, False, False])
+  m = ma.mask_or(ma.getmask(x), ma.getmask(y)) # m =
+  array([True,False,False,True])
+  result = (d1/d2).view(MaskedArray) # masked_array([-1. inf, 3., 2.])
+  result._mask = logical_or(m, dm)
+
+Note that here again the division by zero takes place.
+
+A quick benchmark gives the following results:
+
+ * *numpy.ma.divide*  : 2.69 ms per loop
+ * classical division     : 2.21 ms per loop
+ * division w/ prefilling : 2.34 ms per loop
+ * division w/o filling   : 1.55 ms per loop
+
+So, is it worth filling the arrays beforehand ? Yes, if we are interested
+in avoiding floating-point exceptions that may fill the result with infs
+and nans. No, if we are only interested into speed...
+
+
+Thanks
+------
+
+I'd like to thank Paul Dubois, Travis Oliphant and Sasha for the
+original masked array package: without you, I would never have started
+that (it might be argued that I shouldn't have anyway, but that's
+another story...).  I also wish to extend these thanks to Reggie Dugard
+and Eric Firing for their suggestions and numerous improvements.
+
+
+Revision notes
+--------------
+
+  * 08/25/2007 : Creation of this page
+  * 01/23/2007 : The package has been moved to the SciPy sandbox, and is regularly updated: please check out your SVN version!
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/__init__.py b/python/user_packages/Python313/site-packages/numpy/ma/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a7bf916dee43fab000ebf9a0bf2f3a438910a6af
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/__init__.py
@@ -0,0 +1,53 @@
+"""
+=============
+Masked Arrays
+=============
+
+Arrays sometimes contain invalid or missing data.  When doing operations
+on such arrays, we wish to suppress invalid values, which is the purpose masked
+arrays fulfill (an example of typical use is given below).
+
+For example, examine the following array:
+
+>>> x = np.array([2, 1, 3, np.nan, 5, 2, 3, np.nan])
+
+When we try to calculate the mean of the data, the result is undetermined:
+
+>>> np.mean(x)
+nan
+
+The mean is calculated using roughly ``np.sum(x)/len(x)``, but since
+any number added to ``NaN`` [1]_ produces ``NaN``, this doesn't work.  Enter
+masked arrays:
+
+>>> m = np.ma.masked_array(x, np.isnan(x))
+>>> m
+masked_array(data=[2.0, 1.0, 3.0, --, 5.0, 2.0, 3.0, --],
+             mask=[False, False, False, True, False, False, False, True],
+      fill_value=1e+20)
+
+Here, we construct a masked array that suppress all ``NaN`` values.  We
+may now proceed to calculate the mean of the other values:
+
+>>> np.mean(m)
+2.6666666666666665
+
+.. [1] Not-a-Number, a floating point value that is the result of an
+       invalid operation.
+
+.. moduleauthor:: Pierre Gerard-Marchant
+.. moduleauthor:: Jarrod Millman
+
+"""
+from . import core, extras
+from .core import *
+from .extras import *
+
+__all__ = ['core', 'extras']
+__all__ += core.__all__
+__all__ += extras.__all__
+
+from numpy._pytesttester import PytestTester
+
+test = PytestTester(__name__)
+del PytestTester
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/ma/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..da977f948327851667b1ab3e3cf346554992861e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/__init__.pyi
@@ -0,0 +1,458 @@
+from . import core, extras
+from .core import (
+    MAError,
+    MaskedArray,
+    MaskError,
+    MaskType,
+    abs,
+    absolute,
+    add,
+    all,
+    allclose,
+    allequal,
+    alltrue,
+    amax,
+    amin,
+    angle,
+    anom,
+    anomalies,
+    any,
+    append,
+    arange,
+    arccos,
+    arccosh,
+    arcsin,
+    arcsinh,
+    arctan,
+    arctan2,
+    arctanh,
+    argmax,
+    argmin,
+    argsort,
+    around,
+    array,
+    asanyarray,
+    asarray,
+    bitwise_and,
+    bitwise_or,
+    bitwise_xor,
+    bool_,
+    ceil,
+    choose,
+    clip,
+    common_fill_value,
+    compress,
+    compressed,
+    concatenate,
+    conjugate,
+    convolve,
+    copy,
+    correlate,
+    cos,
+    cosh,
+    count,
+    cumprod,
+    cumsum,
+    default_fill_value,
+    diag,
+    diagonal,
+    diff,
+    divide,
+    empty,
+    empty_like,
+    equal,
+    exp,
+    expand_dims,
+    fabs,
+    filled,
+    fix_invalid,
+    flatten_mask,
+    flatten_structured_array,
+    floor,
+    floor_divide,
+    fmod,
+    frombuffer,
+    fromflex,
+    fromfunction,
+    getdata,
+    getmask,
+    getmaskarray,
+    greater,
+    greater_equal,
+    harden_mask,
+    hypot,
+    identity,
+    ids,
+    indices,
+    inner,
+    innerproduct,
+    is_mask,
+    is_masked,
+    isarray,
+    isMA,
+    isMaskedArray,
+    left_shift,
+    less,
+    less_equal,
+    log,
+    log2,
+    log10,
+    logical_and,
+    logical_not,
+    logical_or,
+    logical_xor,
+    make_mask,
+    make_mask_descr,
+    make_mask_none,
+    mask_or,
+    masked,
+    masked_array,
+    masked_equal,
+    masked_greater,
+    masked_greater_equal,
+    masked_inside,
+    masked_invalid,
+    masked_less,
+    masked_less_equal,
+    masked_not_equal,
+    masked_object,
+    masked_outside,
+    masked_print_option,
+    masked_singleton,
+    masked_values,
+    masked_where,
+    max,
+    maximum,
+    maximum_fill_value,
+    mean,
+    min,
+    minimum,
+    minimum_fill_value,
+    mod,
+    multiply,
+    mvoid,
+    ndim,
+    negative,
+    nomask,
+    nonzero,
+    not_equal,
+    ones,
+    ones_like,
+    outer,
+    outerproduct,
+    power,
+    prod,
+    product,
+    ptp,
+    put,
+    putmask,
+    ravel,
+    remainder,
+    repeat,
+    reshape,
+    resize,
+    right_shift,
+    round,
+    round_,
+    set_fill_value,
+    shape,
+    sin,
+    sinh,
+    size,
+    soften_mask,
+    sometrue,
+    sort,
+    sqrt,
+    squeeze,
+    std,
+    subtract,
+    sum,
+    swapaxes,
+    take,
+    tan,
+    tanh,
+    trace,
+    transpose,
+    true_divide,
+    var,
+    where,
+    zeros,
+    zeros_like,
+)
+from .extras import (
+    apply_along_axis,
+    apply_over_axes,
+    atleast_1d,
+    atleast_2d,
+    atleast_3d,
+    average,
+    clump_masked,
+    clump_unmasked,
+    column_stack,
+    compress_cols,
+    compress_nd,
+    compress_rowcols,
+    compress_rows,
+    corrcoef,
+    count_masked,
+    cov,
+    diagflat,
+    dot,
+    dstack,
+    ediff1d,
+    flatnotmasked_contiguous,
+    flatnotmasked_edges,
+    hsplit,
+    hstack,
+    in1d,
+    intersect1d,
+    isin,
+    mask_cols,
+    mask_rowcols,
+    mask_rows,
+    masked_all,
+    masked_all_like,
+    median,
+    mr_,
+    ndenumerate,
+    notmasked_contiguous,
+    notmasked_edges,
+    polyfit,
+    row_stack,
+    setdiff1d,
+    setxor1d,
+    stack,
+    union1d,
+    unique,
+    vander,
+    vstack,
+)
+
+__all__ = [
+    "core",
+    "extras",
+    "MAError",
+    "MaskError",
+    "MaskType",
+    "MaskedArray",
+    "abs",
+    "absolute",
+    "add",
+    "all",
+    "allclose",
+    "allequal",
+    "alltrue",
+    "amax",
+    "amin",
+    "angle",
+    "anom",
+    "anomalies",
+    "any",
+    "append",
+    "arange",
+    "arccos",
+    "arccosh",
+    "arcsin",
+    "arcsinh",
+    "arctan",
+    "arctan2",
+    "arctanh",
+    "argmax",
+    "argmin",
+    "argsort",
+    "around",
+    "array",
+    "asanyarray",
+    "asarray",
+    "bitwise_and",
+    "bitwise_or",
+    "bitwise_xor",
+    "bool_",
+    "ceil",
+    "choose",
+    "clip",
+    "common_fill_value",
+    "compress",
+    "compressed",
+    "concatenate",
+    "conjugate",
+    "convolve",
+    "copy",
+    "correlate",
+    "cos",
+    "cosh",
+    "count",
+    "cumprod",
+    "cumsum",
+    "default_fill_value",
+    "diag",
+    "diagonal",
+    "diff",
+    "divide",
+    "empty",
+    "empty_like",
+    "equal",
+    "exp",
+    "expand_dims",
+    "fabs",
+    "filled",
+    "fix_invalid",
+    "flatten_mask",
+    "flatten_structured_array",
+    "floor",
+    "floor_divide",
+    "fmod",
+    "frombuffer",
+    "fromflex",
+    "fromfunction",
+    "getdata",
+    "getmask",
+    "getmaskarray",
+    "greater",
+    "greater_equal",
+    "harden_mask",
+    "hypot",
+    "identity",
+    "ids",
+    "indices",
+    "inner",
+    "innerproduct",
+    "isMA",
+    "isMaskedArray",
+    "is_mask",
+    "is_masked",
+    "isarray",
+    "left_shift",
+    "less",
+    "less_equal",
+    "log",
+    "log10",
+    "log2",
+    "logical_and",
+    "logical_not",
+    "logical_or",
+    "logical_xor",
+    "make_mask",
+    "make_mask_descr",
+    "make_mask_none",
+    "mask_or",
+    "masked",
+    "masked_array",
+    "masked_equal",
+    "masked_greater",
+    "masked_greater_equal",
+    "masked_inside",
+    "masked_invalid",
+    "masked_less",
+    "masked_less_equal",
+    "masked_not_equal",
+    "masked_object",
+    "masked_outside",
+    "masked_print_option",
+    "masked_singleton",
+    "masked_values",
+    "masked_where",
+    "max",
+    "maximum",
+    "maximum_fill_value",
+    "mean",
+    "min",
+    "minimum",
+    "minimum_fill_value",
+    "mod",
+    "multiply",
+    "mvoid",
+    "ndim",
+    "negative",
+    "nomask",
+    "nonzero",
+    "not_equal",
+    "ones",
+    "ones_like",
+    "outer",
+    "outerproduct",
+    "power",
+    "prod",
+    "product",
+    "ptp",
+    "put",
+    "putmask",
+    "ravel",
+    "remainder",
+    "repeat",
+    "reshape",
+    "resize",
+    "right_shift",
+    "round",
+    "round_",
+    "set_fill_value",
+    "shape",
+    "sin",
+    "sinh",
+    "size",
+    "soften_mask",
+    "sometrue",
+    "sort",
+    "sqrt",
+    "squeeze",
+    "std",
+    "subtract",
+    "sum",
+    "swapaxes",
+    "take",
+    "tan",
+    "tanh",
+    "trace",
+    "transpose",
+    "true_divide",
+    "var",
+    "where",
+    "zeros",
+    "zeros_like",
+    "apply_along_axis",
+    "apply_over_axes",
+    "atleast_1d",
+    "atleast_2d",
+    "atleast_3d",
+    "average",
+    "clump_masked",
+    "clump_unmasked",
+    "column_stack",
+    "compress_cols",
+    "compress_nd",
+    "compress_rowcols",
+    "compress_rows",
+    "count_masked",
+    "corrcoef",
+    "cov",
+    "diagflat",
+    "dot",
+    "dstack",
+    "ediff1d",
+    "flatnotmasked_contiguous",
+    "flatnotmasked_edges",
+    "hsplit",
+    "hstack",
+    "isin",
+    "in1d",
+    "intersect1d",
+    "mask_cols",
+    "mask_rowcols",
+    "mask_rows",
+    "masked_all",
+    "masked_all_like",
+    "median",
+    "mr_",
+    "ndenumerate",
+    "notmasked_contiguous",
+    "notmasked_edges",
+    "polyfit",
+    "row_stack",
+    "setdiff1d",
+    "setxor1d",
+    "stack",
+    "unique",
+    "union1d",
+    "vander",
+    "vstack",
+]
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/core.py b/python/user_packages/Python313/site-packages/numpy/ma/core.py
new file mode 100644
index 0000000000000000000000000000000000000000..e272d2f6adcb7c8e7cd0521fabc56278be2a2e93
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/core.py
@@ -0,0 +1,8929 @@
+"""
+numpy.ma : a package to handle missing or invalid values.
+
+This package was initially written for numarray by Paul F. Dubois
+at Lawrence Livermore National Laboratory.
+In 2006, the package was completely rewritten by Pierre Gerard-Marchant
+(University of Georgia) to make the MaskedArray class a subclass of ndarray,
+and to improve support of structured arrays.
+
+
+Copyright 1999, 2000, 2001 Regents of the University of California.
+Released for unlimited redistribution.
+
+* Adapted for numpy_core 2005 by Travis Oliphant and (mainly) Paul Dubois.
+* Subclassing of the base `ndarray` 2006 by Pierre Gerard-Marchant
+  (pgmdevlist_AT_gmail_DOT_com)
+* Improvements suggested by Reggie Dugard (reggie_AT_merfinllc_DOT_com)
+
+.. moduleauthor:: Pierre Gerard-Marchant
+
+"""
+import builtins
+import functools
+import inspect
+import operator
+import re
+import textwrap
+import warnings
+
+import numpy as np
+import numpy._core.numerictypes as ntypes
+import numpy._core.umath as umath
+from numpy import (
+    _NoValue,
+    amax,
+    amin,
+    angle,
+    array as narray,  # noqa: F401
+    bool_,
+    expand_dims,
+    finfo,  # noqa: F401
+    iinfo,  # noqa: F401
+    iscomplexobj,
+    ndarray,
+)
+from numpy._core import multiarray as mu
+from numpy._core.numeric import normalize_axis_tuple
+from numpy._utils import set_module
+
+__all__ = [
+    'MAError', 'MaskError', 'MaskType', 'MaskedArray', 'abs', 'absolute',
+    'add', 'all', 'allclose', 'allequal', 'alltrue', 'amax', 'amin',
+    'angle', 'anom', 'anomalies', 'any', 'append', 'arange', 'arccos',
+    'arccosh', 'arcsin', 'arcsinh', 'arctan', 'arctan2', 'arctanh',
+    'argmax', 'argmin', 'argsort', 'around', 'array', 'asanyarray',
+    'asarray', 'bitwise_and', 'bitwise_or', 'bitwise_xor', 'bool_', 'ceil',
+    'choose', 'clip', 'common_fill_value', 'compress', 'compressed',
+    'concatenate', 'conjugate', 'convolve', 'copy', 'correlate', 'cos', 'cosh',
+    'count', 'cumprod', 'cumsum', 'default_fill_value', 'diag', 'diagonal',
+    'diff', 'divide', 'empty', 'empty_like', 'equal', 'exp',
+    'expand_dims', 'fabs', 'filled', 'fix_invalid', 'flatten_mask',
+    'flatten_structured_array', 'floor', 'floor_divide', 'fmod',
+    'frombuffer', 'fromflex', 'fromfunction', 'getdata', 'getmask',
+    'getmaskarray', 'greater', 'greater_equal', 'harden_mask', 'hypot',
+    'identity', 'ids', 'indices', 'inner', 'innerproduct', 'isMA',
+    'isMaskedArray', 'is_mask', 'is_masked', 'isarray', 'left_shift',
+    'less', 'less_equal', 'log', 'log10', 'log2',
+    'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'make_mask',
+    'make_mask_descr', 'make_mask_none', 'mask_or', 'masked',
+    'masked_array', 'masked_equal', 'masked_greater',
+    'masked_greater_equal', 'masked_inside', 'masked_invalid',
+    'masked_less', 'masked_less_equal', 'masked_not_equal',
+    'masked_object', 'masked_outside', 'masked_print_option',
+    'masked_singleton', 'masked_values', 'masked_where', 'max', 'maximum',
+    'maximum_fill_value', 'mean', 'min', 'minimum', 'minimum_fill_value',
+    'mod', 'multiply', 'mvoid', 'ndim', 'negative', 'nomask', 'nonzero',
+    'not_equal', 'ones', 'ones_like', 'outer', 'outerproduct', 'power', 'prod',
+    'product', 'ptp', 'put', 'putmask', 'ravel', 'remainder',
+    'repeat', 'reshape', 'resize', 'right_shift', 'round', 'round_',
+    'set_fill_value', 'shape', 'sin', 'sinh', 'size', 'soften_mask',
+    'sometrue', 'sort', 'sqrt', 'squeeze', 'std', 'subtract', 'sum',
+    'swapaxes', 'take', 'tan', 'tanh', 'trace', 'transpose', 'true_divide',
+    'var', 'where', 'zeros', 'zeros_like',
+    ]
+
+MaskType = np.bool
+nomask = MaskType(0)
+
+class MaskedArrayFutureWarning(FutureWarning):
+    pass
+
+def _deprecate_argsort_axis(arr):
+    """
+    Adjust the axis passed to argsort, warning if necessary
+
+    Parameters
+    ----------
+    arr
+        The array which argsort was called on
+
+    np.ma.argsort has a long-term bug where the default of the axis argument
+    is wrong (gh-8701), which now must be kept for backwards compatibility.
+    Thankfully, this only makes a difference when arrays are 2- or more-
+    dimensional, so we only need a warning then.
+    """
+    if arr.ndim <= 1:
+        # no warning needed - but switch to -1 anyway, to avoid surprising
+        # subclasses, which are more likely to implement scalar axes.
+        return -1
+    else:
+        # 2017-04-11, Numpy 1.13.0, gh-8701: warn on axis default
+        warnings.warn(
+            "In the future the default for argsort will be axis=-1, not the "
+            "current None, to match its documentation and np.argsort. "
+            "Explicitly pass -1 or None to silence this warning.",
+            MaskedArrayFutureWarning, stacklevel=3)
+        return None
+
+
+def doc_note(initialdoc, note):
+    """
+    Adds a Notes section to an existing docstring.
+
+    """
+    if initialdoc is None:
+        return
+    if note is None:
+        return initialdoc
+
+    notesplit = re.split(r'\n\s*?Notes\n\s*?-----', inspect.cleandoc(initialdoc))
+    notedoc = f"\n\nNotes\n-----\n{inspect.cleandoc(note)}\n"
+
+    return ''.join(notesplit[:1] + [notedoc] + notesplit[1:])
+
+
+###############################################################################
+#                              Exceptions                                     #
+###############################################################################
+
+
+class MAError(Exception):
+    """
+    Class for masked array related errors.
+
+    """
+    pass
+
+
+class MaskError(MAError):
+    """
+    Class for mask related errors.
+
+    """
+    pass
+
+
+###############################################################################
+#                           Filling options                                   #
+###############################################################################
+
+
+# b: boolean - c: complex - f: floats - i: integer - O: object - S: string
+default_filler = {'b': True,
+                  'c': 1.e20 + 0.0j,
+                  'f': 1.e20,
+                  'i': 999999,
+                  'O': '?',
+                  'S': b'N/A',
+                  'u': 999999,
+                  'V': b'???',
+                  'U': 'N/A',
+                  'T': 'N/A'
+                  }
+
+# Add datetime64 and timedelta64 types
+for v in ["Y", "M", "W", "D", "h", "m", "s", "ms", "us", "ns", "ps",
+          "fs", "as"]:
+    default_filler["M8[" + v + "]"] = np.datetime64("NaT", v)
+    default_filler["m8[" + v + "]"] = np.timedelta64("NaT", v)
+
+float_types_list = [np.half, np.single, np.double, np.longdouble,
+                    np.csingle, np.cdouble, np.clongdouble]
+
+_minvals: dict[type, int] = {}
+_maxvals: dict[type, int] = {}
+
+for sctype in ntypes.sctypeDict.values():
+    scalar_dtype = np.dtype(sctype)
+
+    if scalar_dtype.kind in "Mm":
+        info = np.iinfo(np.int64)
+        min_val, max_val = info.min + 1, info.max
+    elif np.issubdtype(scalar_dtype, np.integer):
+        info = np.iinfo(sctype)
+        min_val, max_val = info.min, info.max
+    elif np.issubdtype(scalar_dtype, np.floating):
+        info = np.finfo(sctype)
+        min_val, max_val = info.min, info.max
+    elif scalar_dtype.kind == "b":
+        min_val, max_val = 0, 1
+    else:
+        min_val, max_val = None, None
+
+    _minvals[sctype] = min_val
+    _maxvals[sctype] = max_val
+
+max_filler = _minvals
+max_filler.update([(k, -np.inf) for k in float_types_list[:4]])
+max_filler.update([(k, complex(-np.inf, -np.inf)) for k in float_types_list[-3:]])
+
+min_filler = _maxvals
+min_filler.update([(k, +np.inf) for k in float_types_list[:4]])
+min_filler.update([(k, complex(+np.inf, +np.inf)) for k in float_types_list[-3:]])
+
+del float_types_list
+
+def _recursive_fill_value(dtype, f):
+    """
+    Recursively produce a fill value for `dtype`, calling f on scalar dtypes
+    """
+    if dtype.names is not None:
+        # We wrap into `array` here, which ensures we use NumPy cast rules
+        # for integer casts, this allows the use of 99999 as a fill value
+        # for int8.
+        # TODO: This is probably a mess, but should best preserve behavior?
+        vals = tuple(
+                np.array(_recursive_fill_value(dtype[name], f))
+                for name in dtype.names)
+        return np.array(vals, dtype=dtype)[()]  # decay to void scalar from 0d
+    elif dtype.subdtype:
+        subtype, shape = dtype.subdtype
+        subval = _recursive_fill_value(subtype, f)
+        return np.full(shape, subval)
+    else:
+        return f(dtype)
+
+
+def _get_dtype_of(obj):
+    """ Convert the argument for *_fill_value into a dtype """
+    if isinstance(obj, np.dtype):
+        return obj
+    elif hasattr(obj, 'dtype'):
+        return obj.dtype
+    else:
+        return np.asanyarray(obj).dtype
+
+
+def default_fill_value(obj):
+    """
+    Return the default fill value for the argument object.
+
+    The default filling value depends on the datatype of the input
+    array or the type of the input scalar:
+
+       ===========  ========
+       datatype      default
+       ===========  ========
+       bool         True
+       int          999999
+       float        1.e20
+       complex      1.e20+0j
+       object       '?'
+       string       'N/A'
+       StringDType  'N/A'
+       ===========  ========
+
+    For structured types, a structured scalar is returned, with each field the
+    default fill value for its type.
+
+    For subarray types, the fill value is an array of the same size containing
+    the default scalar fill value.
+
+    Parameters
+    ----------
+    obj : ndarray, dtype or scalar
+        The array data-type or scalar for which the default fill value
+        is returned.
+
+    Returns
+    -------
+    fill_value : scalar
+        The default fill value.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.ma.default_fill_value(1)
+    999999
+    >>> np.ma.default_fill_value(np.array([1.1, 2., np.pi]))
+    1e+20
+    >>> np.ma.default_fill_value(np.dtype(complex))
+    (1e+20+0j)
+
+    """
+    def _scalar_fill_value(dtype):
+        if dtype.kind in 'Mm':
+            return default_filler.get(dtype.str[1:], '?')
+        else:
+            return default_filler.get(dtype.kind, '?')
+
+    dtype = _get_dtype_of(obj)
+    return _recursive_fill_value(dtype, _scalar_fill_value)
+
+
+def _extremum_fill_value(obj, extremum, extremum_name):
+
+    def _scalar_fill_value(dtype):
+        try:
+            return extremum[dtype.type]
+        except KeyError as e:
+            raise TypeError(
+                f"Unsuitable type {dtype} for calculating {extremum_name}."
+            ) from None
+
+    dtype = _get_dtype_of(obj)
+    return _recursive_fill_value(dtype, _scalar_fill_value)
+
+
+def minimum_fill_value(obj):
+    """
+    Return the maximum value that can be represented by the dtype of an object.
+
+    This function is useful for calculating a fill value suitable for
+    taking the minimum of an array with a given dtype.
+
+    Parameters
+    ----------
+    obj : ndarray, dtype or scalar
+        An object that can be queried for it's numeric type.
+
+    Returns
+    -------
+    val : scalar
+        The maximum representable value.
+
+    Raises
+    ------
+    TypeError
+        If `obj` isn't a suitable numeric type.
+
+    See Also
+    --------
+    maximum_fill_value : The inverse function.
+    set_fill_value : Set the filling value of a masked array.
+    MaskedArray.fill_value : Return current fill value.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.int8()
+    >>> ma.minimum_fill_value(a)
+    127
+    >>> a = np.int32()
+    >>> ma.minimum_fill_value(a)
+    2147483647
+
+    An array of numeric data can also be passed.
+
+    >>> a = np.array([1, 2, 3], dtype=np.int8)
+    >>> ma.minimum_fill_value(a)
+    127
+    >>> a = np.array([1, 2, 3], dtype=np.float32)
+    >>> ma.minimum_fill_value(a)
+    inf
+
+    """
+    return _extremum_fill_value(obj, min_filler, "minimum")
+
+
+def maximum_fill_value(obj):
+    """
+    Return the minimum value that can be represented by the dtype of an object.
+
+    This function is useful for calculating a fill value suitable for
+    taking the maximum of an array with a given dtype.
+
+    Parameters
+    ----------
+    obj : ndarray, dtype or scalar
+        An object that can be queried for it's numeric type.
+
+    Returns
+    -------
+    val : scalar
+        The minimum representable value.
+
+    Raises
+    ------
+    TypeError
+        If `obj` isn't a suitable numeric type.
+
+    See Also
+    --------
+    minimum_fill_value : The inverse function.
+    set_fill_value : Set the filling value of a masked array.
+    MaskedArray.fill_value : Return current fill value.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.int8()
+    >>> ma.maximum_fill_value(a)
+    -128
+    >>> a = np.int32()
+    >>> ma.maximum_fill_value(a)
+    -2147483648
+
+    An array of numeric data can also be passed.
+
+    >>> a = np.array([1, 2, 3], dtype=np.int8)
+    >>> ma.maximum_fill_value(a)
+    -128
+    >>> a = np.array([1, 2, 3], dtype=np.float32)
+    >>> ma.maximum_fill_value(a)
+    -inf
+
+    """
+    return _extremum_fill_value(obj, max_filler, "maximum")
+
+
+def _recursive_set_fill_value(fillvalue, dt):
+    """
+    Create a fill value for a structured dtype.
+
+    Parameters
+    ----------
+    fillvalue : scalar or array_like
+        Scalar or array representing the fill value. If it is of shorter
+        length than the number of fields in dt, it will be resized.
+    dt : dtype
+        The structured dtype for which to create the fill value.
+
+    Returns
+    -------
+    val : tuple
+        A tuple of values corresponding to the structured fill value.
+
+    """
+    fillvalue = np.resize(fillvalue, len(dt.names))
+    output_value = []
+    for (fval, name) in zip(fillvalue, dt.names):
+        cdtype = dt[name]
+        if cdtype.subdtype:
+            cdtype = cdtype.subdtype[0]
+
+        if cdtype.names is not None:
+            output_value.append(tuple(_recursive_set_fill_value(fval, cdtype)))
+        else:
+            output_value.append(np.array(fval, dtype=cdtype).item())
+    return tuple(output_value)
+
+
+def _check_fill_value(fill_value, ndtype):
+    """
+    Private function validating the given `fill_value` for the given dtype.
+
+    If fill_value is None, it is set to the default corresponding to the dtype.
+
+    If fill_value is not None, its value is forced to the given dtype.
+
+    The result is always a 0d array.
+
+    """
+    ndtype = np.dtype(ndtype)
+    if fill_value is None:
+        fill_value = default_fill_value(ndtype)
+        # TODO: It seems better to always store a valid fill_value, the oddity
+        #       about is that `_fill_value = None` would behave even more
+        #       different then.
+        #       (e.g. this allows arr_uint8.astype(int64) to have the default
+        #       fill value again...)
+        # The one thing that changed in 2.0/2.1 around cast safety is that the
+        # default `int(99...)` is not a same-kind cast anymore, so if we
+        # have a uint, use the default uint.
+        if ndtype.kind == "u":
+            fill_value = np.uint(fill_value)
+    elif ndtype.names is not None:
+        if isinstance(fill_value, (ndarray, np.void)):
+            try:
+                fill_value = np.asarray(fill_value, dtype=ndtype)
+            except ValueError as e:
+                err_msg = "Unable to transform %s to dtype %s"
+                raise ValueError(err_msg % (fill_value, ndtype)) from e
+        else:
+            fill_value = np.asarray(fill_value, dtype=object)
+            fill_value = np.array(_recursive_set_fill_value(fill_value, ndtype),
+                                  dtype=ndtype)
+    elif isinstance(fill_value, str) and (ndtype.char not in 'OSTVU'):
+        # Note this check doesn't work if fill_value is not a scalar
+        err_msg = "Cannot set fill value of string with array of dtype %s"
+        raise TypeError(err_msg % ndtype)
+    else:
+        # In case we want to convert 1e20 to int.
+        # Also in case of converting string arrays.
+        try:
+            fill_value = np.asarray(fill_value, dtype=ndtype)
+        except (OverflowError, ValueError) as e:
+            # Raise TypeError instead of OverflowError or ValueError.
+            # OverflowError is seldom used, and the real problem here is
+            # that the passed fill_value is not compatible with the ndtype.
+            err_msg = "Cannot convert fill_value %s to dtype %s"
+            raise TypeError(err_msg % (fill_value, ndtype)) from e
+    return np.array(fill_value)
+
+
+def set_fill_value(a, fill_value):
+    """
+    Set the filling value of a, if a is a masked array.
+
+    This function changes the fill value of the masked array `a` in place.
+    If `a` is not a masked array, the function returns silently, without
+    doing anything.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array.
+    fill_value : dtype
+        Filling value. A consistency test is performed to make sure
+        the value is compatible with the dtype of `a`.
+
+    Returns
+    -------
+    None
+        Nothing returned by this function.
+
+    See Also
+    --------
+    maximum_fill_value : Return the default fill value for a dtype.
+    MaskedArray.fill_value : Return current fill value.
+    MaskedArray.set_fill_value : Equivalent method.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(5)
+    >>> a
+    array([0, 1, 2, 3, 4])
+    >>> a = ma.masked_where(a < 3, a)
+    >>> a
+    masked_array(data=[--, --, --, 3, 4],
+                 mask=[ True,  True,  True, False, False],
+           fill_value=999999)
+    >>> ma.set_fill_value(a, -999)
+    >>> a
+    masked_array(data=[--, --, --, 3, 4],
+                 mask=[ True,  True,  True, False, False],
+           fill_value=-999)
+
+    Nothing happens if `a` is not a masked array.
+
+    >>> a = list(range(5))
+    >>> a
+    [0, 1, 2, 3, 4]
+    >>> ma.set_fill_value(a, 100)
+    >>> a
+    [0, 1, 2, 3, 4]
+    >>> a = np.arange(5)
+    >>> a
+    array([0, 1, 2, 3, 4])
+    >>> ma.set_fill_value(a, 100)
+    >>> a
+    array([0, 1, 2, 3, 4])
+
+    """
+    if isinstance(a, MaskedArray):
+        a.set_fill_value(fill_value)
+
+
+def get_fill_value(a):
+    """
+    Return the filling value of a, if any.  Otherwise, returns the
+    default filling value for that type.
+
+    """
+    if isinstance(a, MaskedArray):
+        result = a.fill_value
+    else:
+        result = default_fill_value(a)
+    return result
+
+
+def common_fill_value(a, b):
+    """
+    Return the common filling value of two masked arrays, if any.
+
+    If ``a.fill_value == b.fill_value``, return the fill value,
+    otherwise return None.
+
+    Parameters
+    ----------
+    a, b : MaskedArray
+        The masked arrays for which to compare fill values.
+
+    Returns
+    -------
+    fill_value : scalar or None
+        The common fill value, or None.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([0, 1.], fill_value=3)
+    >>> y = np.ma.array([0, 1.], fill_value=3)
+    >>> np.ma.common_fill_value(x, y)
+    3.0
+
+    """
+    t1 = get_fill_value(a)
+    t2 = get_fill_value(b)
+    if t1 == t2:
+        return t1
+    return None
+
+
+def filled(a, fill_value=None):
+    """
+    Return input as an `~numpy.ndarray`, with masked values replaced by
+    `fill_value`.
+
+    If `a` is not a `MaskedArray`, `a` itself is returned.
+    If `a` is a `MaskedArray` with no masked values, then ``a.data`` is
+    returned.
+    If `a` is a `MaskedArray` and `fill_value` is None, `fill_value` is set to
+    ``a.fill_value``.
+
+    Parameters
+    ----------
+    a : MaskedArray or array_like
+        An input object.
+    fill_value : array_like, optional.
+        Can be scalar or non-scalar. If non-scalar, the
+        resulting filled array should be broadcastable
+        over input array. Default is None.
+
+    Returns
+    -------
+    a : ndarray
+        The filled array.
+
+    See Also
+    --------
+    compressed
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
+    ...                                                [1, 0, 0],
+    ...                                                [0, 0, 0]])
+    >>> x.filled()
+    array([[999999,      1,      2],
+           [999999,      4,      5],
+           [     6,      7,      8]])
+    >>> x.filled(fill_value=333)
+    array([[333,   1,   2],
+           [333,   4,   5],
+           [  6,   7,   8]])
+    >>> x.filled(fill_value=np.arange(3))
+    array([[0, 1, 2],
+           [0, 4, 5],
+           [6, 7, 8]])
+
+    """
+    if hasattr(a, 'filled'):
+        return a.filled(fill_value)
+
+    elif isinstance(a, ndarray):
+        # Should we check for contiguity ? and a.flags['CONTIGUOUS']:
+        return a
+    elif isinstance(a, dict):
+        return np.array(a, 'O')
+    else:
+        return np.array(a)
+
+
+def get_masked_subclass(*arrays):
+    """
+    Return the youngest subclass of MaskedArray from a list of (masked) arrays.
+
+    In case of siblings, the first listed takes over.
+
+    """
+    if len(arrays) == 1:
+        arr = arrays[0]
+        if isinstance(arr, MaskedArray):
+            rcls = type(arr)
+        else:
+            rcls = MaskedArray
+    else:
+        arrcls = [type(a) for a in arrays]
+        rcls = arrcls[0]
+        if not issubclass(rcls, MaskedArray):
+            rcls = MaskedArray
+        for cls in arrcls[1:]:
+            if issubclass(cls, rcls):
+                rcls = cls
+    # Don't return MaskedConstant as result: revert to MaskedArray
+    if rcls.__name__ == 'MaskedConstant':
+        return MaskedArray
+    return rcls
+
+
+def getdata(a, subok=True):
+    """
+    Return the data of a masked array as an ndarray.
+
+    Return the data of `a` (if any) as an ndarray if `a` is a ``MaskedArray``,
+    else return `a` as a ndarray or subclass (depending on `subok`) if not.
+
+    Parameters
+    ----------
+    a : array_like
+        Input ``MaskedArray``, alternatively a ndarray or a subclass thereof.
+    subok : bool
+        Whether to force the output to be a `pure` ndarray (False) or to
+        return a subclass of ndarray if appropriate (True, default).
+
+    See Also
+    --------
+    getmask : Return the mask of a masked array, or nomask.
+    getmaskarray : Return the mask of a masked array, or full array of False.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.masked_equal([[1,2],[3,4]], 2)
+    >>> a
+    masked_array(
+      data=[[1, --],
+            [3, 4]],
+      mask=[[False,  True],
+            [False, False]],
+      fill_value=2)
+    >>> ma.getdata(a)
+    array([[1, 2],
+           [3, 4]])
+
+    Equivalently use the ``MaskedArray`` `data` attribute.
+
+    >>> a.data
+    array([[1, 2],
+           [3, 4]])
+
+    """
+    try:
+        data = a._data
+    except AttributeError:
+        data = np.array(a, copy=None, subok=subok)
+    if not subok:
+        return data.view(ndarray)
+    return data
+
+
+get_data = getdata
+
+
+def fix_invalid(a, mask=nomask, copy=True, fill_value=None):
+    """
+    Return input with invalid data masked and replaced by a fill value.
+
+    Invalid data means values of `nan`, `inf`, etc.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array, a (subclass of) ndarray.
+    mask : sequence, optional
+        Mask. Must be convertible to an array of booleans with the same
+        shape as `data`. True indicates a masked (i.e. invalid) data.
+    copy : bool, optional
+        Whether to use a copy of `a` (True) or to fix `a` in place (False).
+        Default is True.
+    fill_value : scalar, optional
+        Value used for fixing invalid data. Default is None, in which case
+        the ``a.fill_value`` is used.
+
+    Returns
+    -------
+    b : MaskedArray
+        The input array with invalid entries fixed.
+
+    Notes
+    -----
+    A copy is performed by default.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([1., -1, np.nan, np.inf], mask=[1] + [0]*3)
+    >>> x
+    masked_array(data=[--, -1.0, nan, inf],
+                 mask=[ True, False, False, False],
+           fill_value=1e+20)
+    >>> np.ma.fix_invalid(x)
+    masked_array(data=[--, -1.0, --, --],
+                 mask=[ True, False,  True,  True],
+           fill_value=1e+20)
+
+    >>> fixed = np.ma.fix_invalid(x)
+    >>> fixed.data
+    array([ 1.e+00, -1.e+00,  1.e+20,  1.e+20])
+    >>> x.data
+    array([ 1., -1., nan, inf])
+
+    """
+    a = masked_array(a, copy=copy, mask=mask, subok=True)
+    invalid = np.logical_not(np.isfinite(a._data))
+    if not invalid.any():
+        return a
+    a._mask |= invalid
+    if fill_value is None:
+        fill_value = a.fill_value
+    a._data[invalid] = fill_value
+    return a
+
+def is_string_or_list_of_strings(val):
+    return (isinstance(val, str) or
+            (isinstance(val, list) and val and
+             builtins.all(isinstance(s, str) for s in val)))
+
+###############################################################################
+#                                  Ufuncs                                     #
+###############################################################################
+
+
+ufunc_domain = {}
+ufunc_fills = {}
+
+
+class _DomainCheckInterval:
+    """
+    Define a valid interval, so that :
+
+    ``domain_check_interval(a,b)(x) == True`` where
+    ``x < a`` or ``x > b``.
+
+    """
+
+    def __init__(self, a, b):
+        "domain_check_interval(a,b)(x) = true where x < a or y > b"
+        if a > b:
+            (a, b) = (b, a)
+        self.a = a
+        self.b = b
+
+    def __call__(self, x):
+        "Execute the call behavior."
+        # nans at masked positions cause RuntimeWarnings, even though
+        # they are masked. To avoid this we suppress warnings.
+        with np.errstate(invalid='ignore'):
+            return umath.logical_or(umath.greater(x, self.b),
+                                    umath.less(x, self.a))
+
+
+class _DomainTan:
+    """
+    Define a valid interval for the `tan` function, so that:
+
+    ``domain_tan(eps) = True`` where ``abs(cos(x)) < eps``
+
+    """
+
+    def __init__(self, eps):
+        "domain_tan(eps) = true where abs(cos(x)) < eps)"
+        self.eps = eps
+
+    def __call__(self, x):
+        "Executes the call behavior."
+        with np.errstate(invalid='ignore'):
+            return umath.less(umath.absolute(umath.cos(x)), self.eps)
+
+
+class _DomainSafeDivide:
+    """
+    Define a domain for safe division.
+
+    """
+
+    def __init__(self, tolerance=None):
+        self.tolerance = tolerance
+
+    def __call__(self, a, b):
+        # Delay the selection of the tolerance to here in order to reduce numpy
+        # import times. The calculation of these parameters is a substantial
+        # component of numpy's import time.
+        if self.tolerance is None:
+            self.tolerance = np.finfo(float).tiny
+        # don't call ma ufuncs from __array_wrap__ which would fail for scalars
+        a, b = np.asarray(a), np.asarray(b)
+        with np.errstate(all='ignore'):
+            return umath.absolute(a) * self.tolerance >= umath.absolute(b)
+
+
+class _DomainGreater:
+    """
+    DomainGreater(v)(x) is True where x <= v.
+
+    """
+
+    def __init__(self, critical_value):
+        "DomainGreater(v)(x) = true where x <= v"
+        self.critical_value = critical_value
+
+    def __call__(self, x):
+        "Executes the call behavior."
+        with np.errstate(invalid='ignore'):
+            return umath.less_equal(x, self.critical_value)
+
+
+class _DomainGreaterEqual:
+    """
+    DomainGreaterEqual(v)(x) is True where x < v.
+
+    """
+
+    def __init__(self, critical_value):
+        "DomainGreaterEqual(v)(x) = true where x < v"
+        self.critical_value = critical_value
+
+    def __call__(self, x):
+        "Executes the call behavior."
+        with np.errstate(invalid='ignore'):
+            return umath.less(x, self.critical_value)
+
+
+class _MaskedUFunc:
+    def __init__(self, ufunc):
+        self.f = ufunc
+        self.__doc__ = ufunc.__doc__
+        self.__name__ = ufunc.__name__
+        self.__qualname__ = ufunc.__qualname__
+
+    def __str__(self):
+        return f"Masked version of {self.f}"
+
+
+class _MaskedUnaryOperation(_MaskedUFunc):
+    """
+    Defines masked version of unary operations, where invalid values are
+    pre-masked.
+
+    Parameters
+    ----------
+    mufunc : callable
+        The function for which to define a masked version. Made available
+        as ``_MaskedUnaryOperation.f``.
+    fill : scalar, optional
+        Filling value, default is 0.
+    domain : class instance
+        Domain for the function. Should be one of the ``_Domain*``
+        classes. Default is None.
+
+    """
+
+    def __init__(self, mufunc, fill=0, domain=None):
+        super().__init__(mufunc)
+        self.fill = fill
+        self.domain = domain
+        ufunc_domain[mufunc] = domain
+        ufunc_fills[mufunc] = fill
+
+    def __call__(self, a, *args, **kwargs):
+        """
+        Execute the call behavior.
+
+        """
+        d = getdata(a)
+        # Deal with domain
+        if self.domain is not None:
+            # Case 1.1. : Domained function
+            # nans at masked positions cause RuntimeWarnings, even though
+            # they are masked. To avoid this we suppress warnings.
+            with np.errstate(divide='ignore', invalid='ignore'):
+                result = self.f(d, *args, **kwargs)
+            # Make a mask
+            m = ~umath.isfinite(result)
+            m |= self.domain(d)
+            m |= getmask(a)
+        else:
+            # Case 1.2. : Function without a domain
+            # Get the result and the mask
+            with np.errstate(divide='ignore', invalid='ignore'):
+                result = self.f(d, *args, **kwargs)
+            m = getmask(a)
+
+        if not result.ndim:
+            # Case 2.1. : The result is scalarscalar
+            if m:
+                return masked
+            return result
+
+        if m is not nomask:
+            # Case 2.2. The result is an array
+            # We need to fill the invalid data back w/ the input Now,
+            # that's plain silly: in C, we would just skip the element and
+            # keep the original, but we do have to do it that way in Python
+
+            # In case result has a lower dtype than the inputs (as in
+            # equal)
+            try:
+                np.copyto(result, d, where=m)
+            except TypeError:
+                pass
+        # Transform to
+        masked_result = result.view(get_masked_subclass(a))
+        masked_result._mask = m
+        masked_result._update_from(a)
+        return masked_result
+
+
+class _MaskedBinaryOperation(_MaskedUFunc):
+    """
+    Define masked version of binary operations, where invalid
+    values are pre-masked.
+
+    Parameters
+    ----------
+    mbfunc : function
+        The function for which to define a masked version. Made available
+        as ``_MaskedBinaryOperation.f``.
+    domain : class instance
+        Default domain for the function. Should be one of the ``_Domain*``
+        classes. Default is None.
+    fillx : scalar, optional
+        Filling value for the first argument, default is 0.
+    filly : scalar, optional
+        Filling value for the second argument, default is 0.
+
+    """
+
+    def __init__(self, mbfunc, fillx=0, filly=0):
+        """
+        abfunc(fillx, filly) must be defined.
+
+        abfunc(x, filly) = x for all x to enable reduce.
+
+        """
+        super().__init__(mbfunc)
+        self.fillx = fillx
+        self.filly = filly
+        ufunc_domain[mbfunc] = None
+        ufunc_fills[mbfunc] = (fillx, filly)
+
+    def __call__(self, a, b, *args, **kwargs):
+        """
+        Execute the call behavior.
+
+        """
+        # Get the data, as ndarray
+        (da, db) = (getdata(a), getdata(b))
+        # Get the result
+        with np.errstate():
+            np.seterr(divide='ignore', invalid='ignore')
+            result = self.f(da, db, *args, **kwargs)
+        # Get the mask for the result
+        (ma, mb) = (getmask(a), getmask(b))
+        if ma is nomask:
+            if mb is nomask:
+                m = nomask
+            else:
+                m = umath.logical_or(getmaskarray(a), mb)
+        elif mb is nomask:
+            m = umath.logical_or(ma, getmaskarray(b))
+        else:
+            m = umath.logical_or(ma, mb)
+
+        # Case 1. : scalar
+        if not result.ndim:
+            if m:
+                return masked
+            return result
+
+        # Case 2. : array
+        # Revert result to da where masked
+        if m is not nomask and m.any():
+            # any errors, just abort; impossible to guarantee masked values
+            try:
+                np.copyto(result, da, casting='unsafe', where=m)
+            except Exception:
+                pass
+
+        # Transforms to a (subclass of) MaskedArray
+        masked_result = result.view(get_masked_subclass(a, b))
+        masked_result._mask = m
+        if isinstance(a, MaskedArray):
+            masked_result._update_from(a)
+        elif isinstance(b, MaskedArray):
+            masked_result._update_from(b)
+        return masked_result
+
+    def reduce(self, target, axis=0, dtype=None):
+        """
+        Reduce `target` along the given `axis`.
+
+        """
+        tclass = get_masked_subclass(target)
+        m = getmask(target)
+        t = filled(target, self.filly)
+        if t.shape == ():
+            t = t.reshape(1)
+            if m is not nomask:
+                m = make_mask(m, copy=True)
+                m.shape = (1,)
+
+        if m is nomask:
+            tr = self.f.reduce(t, axis)
+            mr = nomask
+        else:
+            tr = self.f.reduce(t, axis, dtype=dtype)
+            mr = umath.logical_and.reduce(m, axis)
+
+        if not tr.shape:
+            if mr:
+                return masked
+            else:
+                return tr
+        masked_tr = tr.view(tclass)
+        masked_tr._mask = mr
+        return masked_tr
+
+    def outer(self, a, b):
+        """
+        Return the function applied to the outer product of a and b.
+
+        """
+        (da, db) = (getdata(a), getdata(b))
+        d = self.f.outer(da, db)
+        ma = getmask(a)
+        mb = getmask(b)
+        if ma is nomask and mb is nomask:
+            m = nomask
+        else:
+            ma = getmaskarray(a)
+            mb = getmaskarray(b)
+            m = umath.logical_or.outer(ma, mb)
+        if (not m.ndim) and m:
+            return masked
+        if m is not nomask:
+            np.copyto(d, da, where=m)
+        if not d.shape:
+            return d
+        masked_d = d.view(get_masked_subclass(a, b))
+        masked_d._mask = m
+        return masked_d
+
+    def accumulate(self, target, axis=0):
+        """Accumulate `target` along `axis` after filling with y fill
+        value.
+
+        """
+        tclass = get_masked_subclass(target)
+        t = filled(target, self.filly)
+        result = self.f.accumulate(t, axis)
+        masked_result = result.view(tclass)
+        return masked_result
+
+
+class _DomainedBinaryOperation(_MaskedUFunc):
+    """
+    Define binary operations that have a domain, like divide.
+
+    They have no reduce, outer or accumulate.
+
+    Parameters
+    ----------
+    mbfunc : function
+        The function for which to define a masked version. Made available
+        as ``_DomainedBinaryOperation.f``.
+    domain : class instance
+        Default domain for the function. Should be one of the ``_Domain*``
+        classes.
+    fillx : scalar, optional
+        Filling value for the first argument, default is 0.
+    filly : scalar, optional
+        Filling value for the second argument, default is 0.
+
+    """
+
+    def __init__(self, dbfunc, domain, fillx=0, filly=0):
+        """abfunc(fillx, filly) must be defined.
+           abfunc(x, filly) = x for all x to enable reduce.
+        """
+        super().__init__(dbfunc)
+        self.domain = domain
+        self.fillx = fillx
+        self.filly = filly
+        ufunc_domain[dbfunc] = domain
+        ufunc_fills[dbfunc] = (fillx, filly)
+
+    def __call__(self, a, b, *args, **kwargs):
+        "Execute the call behavior."
+        # Get the data
+        (da, db) = (getdata(a), getdata(b))
+        # Get the result
+        with np.errstate(divide='ignore', invalid='ignore'):
+            result = self.f(da, db, *args, **kwargs)
+        # Get the mask as a combination of the source masks and invalid
+        m = ~umath.isfinite(result)
+        m |= getmask(a)
+        m |= getmask(b)
+        # Apply the domain
+        domain = ufunc_domain.get(self.f, None)
+        if domain is not None:
+            m |= domain(da, db)
+        # Take care of the scalar case first
+        if not m.ndim:
+            if m:
+                return masked
+            else:
+                return result
+        # When the mask is True, put back da if possible
+        # any errors, just abort; impossible to guarantee masked values
+        try:
+            np.copyto(result, 0, casting='unsafe', where=m)
+            # avoid using "*" since this may be overlaid
+            masked_da = umath.multiply(m, da)
+            # only add back if it can be cast safely
+            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
+                result += masked_da
+        except Exception:
+            pass
+
+        # Transforms to a (subclass of) MaskedArray
+        masked_result = result.view(get_masked_subclass(a, b))
+        masked_result._mask = m
+        if isinstance(a, MaskedArray):
+            masked_result._update_from(a)
+        elif isinstance(b, MaskedArray):
+            masked_result._update_from(b)
+        return masked_result
+
+
+# Unary ufuncs
+exp = _MaskedUnaryOperation(umath.exp)
+conjugate = _MaskedUnaryOperation(umath.conjugate)
+sin = _MaskedUnaryOperation(umath.sin)
+cos = _MaskedUnaryOperation(umath.cos)
+arctan = _MaskedUnaryOperation(umath.arctan)
+arcsinh = _MaskedUnaryOperation(umath.arcsinh)
+sinh = _MaskedUnaryOperation(umath.sinh)
+cosh = _MaskedUnaryOperation(umath.cosh)
+tanh = _MaskedUnaryOperation(umath.tanh)
+abs = absolute = _MaskedUnaryOperation(umath.absolute)
+angle = _MaskedUnaryOperation(angle)
+fabs = _MaskedUnaryOperation(umath.fabs)
+negative = _MaskedUnaryOperation(umath.negative)
+floor = _MaskedUnaryOperation(umath.floor)
+ceil = _MaskedUnaryOperation(umath.ceil)
+around = _MaskedUnaryOperation(np.around)
+logical_not = _MaskedUnaryOperation(umath.logical_not)
+
+# Domained unary ufuncs
+sqrt = _MaskedUnaryOperation(umath.sqrt, 0.0,
+                             _DomainGreaterEqual(0.0))
+log = _MaskedUnaryOperation(umath.log, 1.0,
+                            _DomainGreater(0.0))
+log2 = _MaskedUnaryOperation(umath.log2, 1.0,
+                             _DomainGreater(0.0))
+log10 = _MaskedUnaryOperation(umath.log10, 1.0,
+                              _DomainGreater(0.0))
+tan = _MaskedUnaryOperation(umath.tan, 0.0,
+                            _DomainTan(1e-35))
+arcsin = _MaskedUnaryOperation(umath.arcsin, 0.0,
+                               _DomainCheckInterval(-1.0, 1.0))
+arccos = _MaskedUnaryOperation(umath.arccos, 0.0,
+                               _DomainCheckInterval(-1.0, 1.0))
+arccosh = _MaskedUnaryOperation(umath.arccosh, 1.0,
+                                _DomainGreaterEqual(1.0))
+arctanh = _MaskedUnaryOperation(umath.arctanh, 0.0,
+                                _DomainCheckInterval(-1.0 + 1e-15, 1.0 - 1e-15))
+
+# Binary ufuncs
+add = _MaskedBinaryOperation(umath.add)
+subtract = _MaskedBinaryOperation(umath.subtract)
+multiply = _MaskedBinaryOperation(umath.multiply, 1, 1)
+arctan2 = _MaskedBinaryOperation(umath.arctan2, 0.0, 1.0)
+equal = _MaskedBinaryOperation(umath.equal)
+equal.reduce = None
+not_equal = _MaskedBinaryOperation(umath.not_equal)
+not_equal.reduce = None
+less_equal = _MaskedBinaryOperation(umath.less_equal)
+less_equal.reduce = None
+greater_equal = _MaskedBinaryOperation(umath.greater_equal)
+greater_equal.reduce = None
+less = _MaskedBinaryOperation(umath.less)
+less.reduce = None
+greater = _MaskedBinaryOperation(umath.greater)
+greater.reduce = None
+logical_and = _MaskedBinaryOperation(umath.logical_and)
+alltrue = _MaskedBinaryOperation(umath.logical_and, 1, 1).reduce
+logical_or = _MaskedBinaryOperation(umath.logical_or)
+sometrue = logical_or.reduce
+logical_xor = _MaskedBinaryOperation(umath.logical_xor)
+bitwise_and = _MaskedBinaryOperation(umath.bitwise_and)
+bitwise_or = _MaskedBinaryOperation(umath.bitwise_or)
+bitwise_xor = _MaskedBinaryOperation(umath.bitwise_xor)
+hypot = _MaskedBinaryOperation(umath.hypot)
+
+# Domained binary ufuncs
+divide = _DomainedBinaryOperation(umath.divide, _DomainSafeDivide(), 0, 1)
+true_divide = divide  # Just an alias for divide.
+floor_divide = _DomainedBinaryOperation(umath.floor_divide,
+                                        _DomainSafeDivide(), 0, 1)
+remainder = _DomainedBinaryOperation(umath.remainder,
+                                     _DomainSafeDivide(), 0, 1)
+fmod = _DomainedBinaryOperation(umath.fmod, _DomainSafeDivide(), 0, 1)
+mod = remainder
+
+###############################################################################
+#                        Mask creation functions                              #
+###############################################################################
+
+
+def _replace_dtype_fields_recursive(dtype, primitive_dtype):
+    "Private function allowing recursion in _replace_dtype_fields."
+    _recurse = _replace_dtype_fields_recursive
+
+    # Do we have some name fields ?
+    if dtype.names is not None:
+        descr = []
+        for name in dtype.names:
+            field = dtype.fields[name]
+            if len(field) == 3:
+                # Prepend the title to the name
+                name = (field[-1], name)
+            descr.append((name, _recurse(field[0], primitive_dtype)))
+        new_dtype = np.dtype(descr)
+
+    # Is this some kind of composite a la (float,2)
+    elif dtype.subdtype:
+        descr = list(dtype.subdtype)
+        descr[0] = _recurse(dtype.subdtype[0], primitive_dtype)
+        new_dtype = np.dtype(tuple(descr))
+
+    # this is a primitive type, so do a direct replacement
+    else:
+        new_dtype = primitive_dtype
+
+    # preserve identity of dtypes
+    if new_dtype == dtype:
+        new_dtype = dtype
+
+    return new_dtype
+
+
+def _replace_dtype_fields(dtype, primitive_dtype):
+    """
+    Construct a dtype description list from a given dtype.
+
+    Returns a new dtype object, with all fields and subtypes in the given type
+    recursively replaced with `primitive_dtype`.
+
+    Arguments are coerced to dtypes first.
+    """
+    dtype = np.dtype(dtype)
+    primitive_dtype = np.dtype(primitive_dtype)
+    return _replace_dtype_fields_recursive(dtype, primitive_dtype)
+
+
+def make_mask_descr(ndtype):
+    """
+    Construct a dtype description list from a given dtype.
+
+    Returns a new dtype object, with the type of all fields in `ndtype` to a
+    boolean type. Field names are not altered.
+
+    Parameters
+    ----------
+    ndtype : dtype
+        The dtype to convert.
+
+    Returns
+    -------
+    result : dtype
+        A dtype that looks like `ndtype`, the type of all fields is boolean.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> dtype = np.dtype({'names':['foo', 'bar'],
+    ...                   'formats':[np.float32, np.int64]})
+    >>> dtype
+    dtype([('foo', '<f4'), ('bar', '<i8')])
+    >>> ma.make_mask_descr(dtype)
+    dtype([('foo', '|b1'), ('bar', '|b1')])
+    >>> ma.make_mask_descr(np.float32)
+    dtype('bool')
+
+    """
+    return _replace_dtype_fields(ndtype, MaskType)
+
+
+def getmask(a):
+    """
+    Return the mask of a masked array, or nomask.
+
+    Return the mask of `a` as an ndarray if `a` is a `MaskedArray` and the
+    mask is not `nomask`, else return `nomask`. To guarantee a full array
+    of booleans of the same shape as a, use `getmaskarray`.
+
+    Parameters
+    ----------
+    a : array_like
+        Input `MaskedArray` for which the mask is required.
+
+    See Also
+    --------
+    getdata : Return the data of a masked array as an ndarray.
+    getmaskarray : Return the mask of a masked array, or full array of False.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.masked_equal([[1,2],[3,4]], 2)
+    >>> a
+    masked_array(
+      data=[[1, --],
+            [3, 4]],
+      mask=[[False,  True],
+            [False, False]],
+      fill_value=2)
+    >>> ma.getmask(a)
+    array([[False,  True],
+           [False, False]])
+
+    Equivalently use the `MaskedArray` `mask` attribute.
+
+    >>> a.mask
+    array([[False,  True],
+           [False, False]])
+
+    Result when mask == `nomask`
+
+    >>> b = ma.masked_array([[1,2],[3,4]])
+    >>> b
+    masked_array(
+      data=[[1, 2],
+            [3, 4]],
+      mask=False,
+      fill_value=999999)
+    >>> ma.nomask
+    False
+    >>> ma.getmask(b) == ma.nomask
+    True
+    >>> b.mask == ma.nomask
+    True
+
+    """
+    return getattr(a, '_mask', nomask)
+
+
+get_mask = getmask
+
+
+def getmaskarray(arr):
+    """
+    Return the mask of a masked array, or full boolean array of False.
+
+    Return the mask of `arr` as an ndarray if `arr` is a `MaskedArray` and
+    the mask is not `nomask`, else return a full boolean array of False of
+    the same shape as `arr`.
+
+    Parameters
+    ----------
+    arr : array_like
+        Input `MaskedArray` for which the mask is required.
+
+    See Also
+    --------
+    getmask : Return the mask of a masked array, or nomask.
+    getdata : Return the data of a masked array as an ndarray.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.masked_equal([[1,2],[3,4]], 2)
+    >>> a
+    masked_array(
+      data=[[1, --],
+            [3, 4]],
+      mask=[[False,  True],
+            [False, False]],
+      fill_value=2)
+    >>> ma.getmaskarray(a)
+    array([[False,  True],
+           [False, False]])
+
+    Result when mask == ``nomask``
+
+    >>> b = ma.masked_array([[1,2],[3,4]])
+    >>> b
+    masked_array(
+      data=[[1, 2],
+            [3, 4]],
+      mask=False,
+      fill_value=999999)
+    >>> ma.getmaskarray(b)
+    array([[False, False],
+           [False, False]])
+
+    """
+    mask = getmask(arr)
+    if mask is nomask:
+        mask = make_mask_none(np.shape(arr), getattr(arr, 'dtype', None))
+    return mask
+
+
+def is_mask(m):
+    """
+    Return True if m is a valid, standard mask.
+
+    This function does not check the contents of the input, only that the
+    type is MaskType. In particular, this function returns False if the
+    mask has a flexible dtype.
+
+    Parameters
+    ----------
+    m : array_like
+        Array to test.
+
+    Returns
+    -------
+    result : bool
+        True if `m.dtype.type` is MaskType, False otherwise.
+
+    See Also
+    --------
+    ma.isMaskedArray : Test whether input is an instance of MaskedArray.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> m = ma.masked_equal([0, 1, 0, 2, 3], 0)
+    >>> m
+    masked_array(data=[--, 1, --, 2, 3],
+                 mask=[ True, False,  True, False, False],
+           fill_value=0)
+    >>> ma.is_mask(m)
+    False
+    >>> ma.is_mask(m.mask)
+    True
+
+    Input must be an ndarray (or have similar attributes)
+    for it to be considered a valid mask.
+
+    >>> m = [False, True, False]
+    >>> ma.is_mask(m)
+    False
+    >>> m = np.array([False, True, False])
+    >>> m
+    array([False,  True, False])
+    >>> ma.is_mask(m)
+    True
+
+    Arrays with complex dtypes don't return True.
+
+    >>> dtype = np.dtype({'names':['monty', 'pithon'],
+    ...                   'formats':[bool, bool]})
+    >>> dtype
+    dtype([('monty', '|b1'), ('pithon', '|b1')])
+    >>> m = np.array([(True, False), (False, True), (True, False)],
+    ...              dtype=dtype)
+    >>> m
+    array([( True, False), (False,  True), ( True, False)],
+          dtype=[('monty', '?'), ('pithon', '?')])
+    >>> ma.is_mask(m)
+    False
+
+    """
+    try:
+        return m.dtype.type is MaskType
+    except AttributeError:
+        return False
+
+
+def _shrink_mask(m):
+    """
+    Shrink a mask to nomask if possible
+    """
+    if m.dtype.names is None and not m.any():
+        return nomask
+    else:
+        return m
+
+
+def make_mask(m, copy=False, shrink=True, dtype=MaskType):
+    """
+    Create a boolean mask from an array.
+
+    Return `m` as a boolean mask, creating a copy if necessary or requested.
+    The function can accept any sequence that is convertible to integers,
+    or ``nomask``.  Does not require that contents must be 0s and 1s, values
+    of 0 are interpreted as False, everything else as True.
+
+    Parameters
+    ----------
+    m : array_like
+        Potential mask.
+    copy : bool, optional
+        Whether to return a copy of `m` (True) or `m` itself (False).
+    shrink : bool, optional
+        Whether to shrink `m` to ``nomask`` if all its values are False.
+    dtype : dtype, optional
+        Data-type of the output mask. By default, the output mask has a
+        dtype of MaskType (bool). If the dtype is flexible, each field has
+        a boolean dtype. This is ignored when `m` is ``nomask``, in which
+        case ``nomask`` is always returned.
+
+    Returns
+    -------
+    result : ndarray
+        A boolean mask derived from `m`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> m = [True, False, True, True]
+    >>> ma.make_mask(m)
+    array([ True, False,  True,  True])
+    >>> m = [1, 0, 1, 1]
+    >>> ma.make_mask(m)
+    array([ True, False,  True,  True])
+    >>> m = [1, 0, 2, -3]
+    >>> ma.make_mask(m)
+    array([ True, False,  True,  True])
+
+    Effect of the `shrink` parameter.
+
+    >>> m = np.zeros(4)
+    >>> m
+    array([0., 0., 0., 0.])
+    >>> ma.make_mask(m)
+    False
+    >>> ma.make_mask(m, shrink=False)
+    array([False, False, False, False])
+
+    Using a flexible `dtype`.
+
+    >>> m = [1, 0, 1, 1]
+    >>> n = [0, 1, 0, 0]
+    >>> arr = []
+    >>> for man, mouse in zip(m, n):
+    ...     arr.append((man, mouse))
+    >>> arr
+    [(1, 0), (0, 1), (1, 0), (1, 0)]
+    >>> dtype = np.dtype({'names':['man', 'mouse'],
+    ...                   'formats':[np.int64, np.int64]})
+    >>> arr = np.array(arr, dtype=dtype)
+    >>> arr
+    array([(1, 0), (0, 1), (1, 0), (1, 0)],
+          dtype=[('man', '<i8'), ('mouse', '<i8')])
+    >>> ma.make_mask(arr, dtype=dtype)
+    array([(True, False), (False, True), (True, False), (True, False)],
+          dtype=[('man', '|b1'), ('mouse', '|b1')])
+
+    """
+    if m is nomask:
+        return nomask
+
+    # Make sure the input dtype is valid.
+    dtype = make_mask_descr(dtype)
+
+    # legacy boolean special case: "existence of fields implies true"
+    if isinstance(m, ndarray) and m.dtype.fields and dtype == np.bool:
+        return np.ones(m.shape, dtype=dtype)
+
+    # Fill the mask in case there are missing data; turn it into an ndarray.
+    copy = None if not copy else True
+    result = np.array(filled(m, True), copy=copy, dtype=dtype, subok=True)
+    # Bas les masques !
+    if shrink:
+        result = _shrink_mask(result)
+    return result
+
+
+def make_mask_none(newshape, dtype=None):
+    """
+    Return a boolean mask of the given shape, filled with False.
+
+    This function returns a boolean ndarray with all entries False, that can
+    be used in common mask manipulations. If a complex dtype is specified, the
+    type of each field is converted to a boolean type.
+
+    Parameters
+    ----------
+    newshape : tuple
+        A tuple indicating the shape of the mask.
+    dtype : {None, dtype}, optional
+        If None, use a MaskType instance. Otherwise, use a new datatype with
+        the same fields as `dtype`, converted to boolean types.
+
+    Returns
+    -------
+    result : ndarray
+        An ndarray of appropriate shape and dtype, filled with False.
+
+    See Also
+    --------
+    make_mask : Create a boolean mask from an array.
+    make_mask_descr : Construct a dtype description list from a given dtype.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> ma.make_mask_none((3,))
+    array([False, False, False])
+
+    Defining a more complex dtype.
+
+    >>> dtype = np.dtype({'names':['foo', 'bar'],
+    ...                   'formats':[np.float32, np.int64]})
+    >>> dtype
+    dtype([('foo', '<f4'), ('bar', '<i8')])
+    >>> ma.make_mask_none((3,), dtype=dtype)
+    array([(False, False), (False, False), (False, False)],
+          dtype=[('foo', '|b1'), ('bar', '|b1')])
+
+    """
+    if dtype is None:
+        result = np.zeros(newshape, dtype=MaskType)
+    else:
+        result = np.zeros(newshape, dtype=make_mask_descr(dtype))
+    return result
+
+
+def _recursive_mask_or(m1, m2, newmask):
+    names = m1.dtype.names
+    for name in names:
+        current1 = m1[name]
+        if current1.dtype.names is not None:
+            _recursive_mask_or(current1, m2[name], newmask[name])
+        else:
+            umath.logical_or(current1, m2[name], newmask[name])
+
+
+def mask_or(m1, m2, copy=False, shrink=True):
+    """
+    Combine two masks with the ``logical_or`` operator.
+
+    The result may be a view on `m1` or `m2` if the other is `nomask`
+    (i.e. False).
+
+    Parameters
+    ----------
+    m1, m2 : array_like
+        Input masks.
+    copy : bool, optional
+        If copy is False and one of the inputs is `nomask`, return a view
+        of the other input mask. Defaults to False.
+    shrink : bool, optional
+        Whether to shrink the output to `nomask` if all its values are
+        False. Defaults to True.
+
+    Returns
+    -------
+    mask : output mask
+        The result masks values that are masked in either `m1` or `m2`.
+
+    Raises
+    ------
+    ValueError
+        If `m1` and `m2` have different flexible dtypes.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> m1 = np.ma.make_mask([0, 1, 1, 0])
+    >>> m2 = np.ma.make_mask([1, 0, 0, 0])
+    >>> np.ma.mask_or(m1, m2)
+    array([ True,  True,  True, False])
+
+    """
+
+    if (m1 is nomask) or (m1 is False):
+        dtype = getattr(m2, 'dtype', MaskType)
+        return make_mask(m2, copy=copy, shrink=shrink, dtype=dtype)
+    if (m2 is nomask) or (m2 is False):
+        dtype = getattr(m1, 'dtype', MaskType)
+        return make_mask(m1, copy=copy, shrink=shrink, dtype=dtype)
+    if m1 is m2 and is_mask(m1):
+        return _shrink_mask(m1) if shrink else m1
+    (dtype1, dtype2) = (getattr(m1, 'dtype', None), getattr(m2, 'dtype', None))
+    if dtype1 != dtype2:
+        raise ValueError(f"Incompatible dtypes '{dtype1}'<>'{dtype2}'")
+    if dtype1.names is not None:
+        # Allocate an output mask array with the properly broadcast shape.
+        newmask = np.empty(np.broadcast(m1, m2).shape, dtype1)
+        _recursive_mask_or(m1, m2, newmask)
+        return newmask
+    return make_mask(umath.logical_or(m1, m2), copy=copy, shrink=shrink)
+
+
+def flatten_mask(mask):
+    """
+    Returns a completely flattened version of the mask, where nested fields
+    are collapsed.
+
+    Parameters
+    ----------
+    mask : array_like
+        Input array, which will be interpreted as booleans.
+
+    Returns
+    -------
+    flattened_mask : ndarray of bools
+        The flattened input.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> mask = np.array([0, 0, 1])
+    >>> np.ma.flatten_mask(mask)
+    array([False, False,  True])
+
+    >>> mask = np.array([(0, 0), (0, 1)], dtype=[('a', bool), ('b', bool)])
+    >>> np.ma.flatten_mask(mask)
+    array([False, False, False,  True])
+
+    >>> mdtype = [('a', bool), ('b', [('ba', bool), ('bb', bool)])]
+    >>> mask = np.array([(0, (0, 0)), (0, (0, 1))], dtype=mdtype)
+    >>> np.ma.flatten_mask(mask)
+    array([False, False, False, False, False,  True])
+
+    """
+
+    def _flatmask(mask):
+        "Flatten the mask and returns a (maybe nested) sequence of booleans."
+        mnames = mask.dtype.names
+        if mnames is not None:
+            return [flatten_mask(mask[name]) for name in mnames]
+        else:
+            return mask
+
+    def _flatsequence(sequence):
+        "Generates a flattened version of the sequence."
+        try:
+            for element in sequence:
+                if hasattr(element, '__iter__'):
+                    yield from _flatsequence(element)
+                else:
+                    yield element
+        except TypeError:
+            yield sequence
+
+    mask = np.asarray(mask)
+    flattened = _flatsequence(_flatmask(mask))
+    return np.array(list(flattened), dtype=bool)
+
+
+def _check_mask_axis(mask, axis, keepdims=np._NoValue):
+    "Check whether there are masked values along the given axis"
+    kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+    if mask is not nomask:
+        return mask.all(axis=axis, **kwargs)
+    return nomask
+
+
+###############################################################################
+#                             Masking functions                               #
+###############################################################################
+
+def masked_where(condition, a, copy=True):
+    """
+    Mask an array where a condition is met.
+
+    Return `a` as an array masked where `condition` is True.
+    Any masked values of `a` or `condition` are also masked in the output.
+
+    Parameters
+    ----------
+    condition : array_like
+        Masking condition.  When `condition` tests floating point values for
+        equality, consider using ``masked_values`` instead.
+    a : array_like
+        Array to mask.
+    copy : bool
+        If True (default) make a copy of `a` in the result.  If False modify
+        `a` in place and return a view.
+
+    Returns
+    -------
+    result : MaskedArray
+        The result of masking `a` where `condition` is True.
+
+    See Also
+    --------
+    masked_values : Mask using floating point equality.
+    masked_equal : Mask where equal to a given value.
+    masked_not_equal : Mask where *not* equal to a given value.
+    masked_less_equal : Mask where less than or equal to a given value.
+    masked_greater_equal : Mask where greater than or equal to a given value.
+    masked_less : Mask where less than a given value.
+    masked_greater : Mask where greater than a given value.
+    masked_inside : Mask inside a given interval.
+    masked_outside : Mask outside a given interval.
+    masked_invalid : Mask invalid values (NaNs or infs).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_where(a <= 2, a)
+    masked_array(data=[--, --, --, 3],
+                 mask=[ True,  True,  True, False],
+           fill_value=999999)
+
+    Mask array `b` conditional on `a`.
+
+    >>> b = ['a', 'b', 'c', 'd']
+    >>> ma.masked_where(a == 2, b)
+    masked_array(data=['a', 'b', --, 'd'],
+                 mask=[False, False,  True, False],
+           fill_value='N/A',
+                dtype='<U1')
+
+    Effect of the `copy` argument.
+
+    >>> c = ma.masked_where(a <= 2, a)
+    >>> c
+    masked_array(data=[--, --, --, 3],
+                 mask=[ True,  True,  True, False],
+           fill_value=999999)
+    >>> c[0] = 99
+    >>> c
+    masked_array(data=[99, --, --, 3],
+                 mask=[False,  True,  True, False],
+           fill_value=999999)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> c = ma.masked_where(a <= 2, a, copy=False)
+    >>> c[0] = 99
+    >>> c
+    masked_array(data=[99, --, --, 3],
+                 mask=[False,  True,  True, False],
+           fill_value=999999)
+    >>> a
+    array([99,  1,  2,  3])
+
+    When `condition` or `a` contain masked values.
+
+    >>> a = np.arange(4)
+    >>> a = ma.masked_where(a == 2, a)
+    >>> a
+    masked_array(data=[0, 1, --, 3],
+                 mask=[False, False,  True, False],
+           fill_value=999999)
+    >>> b = np.arange(4)
+    >>> b = ma.masked_where(b == 0, b)
+    >>> b
+    masked_array(data=[--, 1, 2, 3],
+                 mask=[ True, False, False, False],
+           fill_value=999999)
+    >>> ma.masked_where(a == 3, b)
+    masked_array(data=[--, 1, --, --],
+                 mask=[ True, False,  True,  True],
+           fill_value=999999)
+
+    """
+    # Make sure that condition is a valid standard-type mask.
+    cond = make_mask(condition, shrink=False)
+    a = np.array(a, copy=copy, subok=True)
+
+    (cshape, ashape) = (cond.shape, a.shape)
+    if cshape and cshape != ashape:
+        raise IndexError("Inconsistent shape between the condition and the input"
+                         " (got %s and %s)" % (cshape, ashape))
+    if hasattr(a, '_mask'):
+        cond = mask_or(cond, a._mask)
+        cls = type(a)
+    else:
+        cls = MaskedArray
+    result = a.view(cls)
+    # Assign to *.mask so that structured masks are handled correctly.
+    result.mask = _shrink_mask(cond)
+    # There is no view of a boolean so when 'a' is a MaskedArray with nomask
+    # the update to the result's mask has no effect.
+    if not copy and hasattr(a, '_mask') and getmask(a) is nomask:
+        a._mask = result._mask.view()
+    return result
+
+
+def masked_greater(x, value, copy=True):
+    """
+    Mask an array where greater than a given value.
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = (x > value).
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_greater(a, 2)
+    masked_array(data=[0, 1, 2, --],
+                 mask=[False, False, False,  True],
+           fill_value=999999)
+
+    """
+    return masked_where(greater(x, value), x, copy=copy)
+
+
+def masked_greater_equal(x, value, copy=True):
+    """
+    Mask an array where greater than or equal to a given value.
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = (x >= value).
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_greater_equal(a, 2)
+    masked_array(data=[0, 1, --, --],
+                 mask=[False, False,  True,  True],
+           fill_value=999999)
+
+    """
+    return masked_where(greater_equal(x, value), x, copy=copy)
+
+
+def masked_less(x, value, copy=True):
+    """
+    Mask an array where less than a given value.
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = (x < value).
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_less(a, 2)
+    masked_array(data=[--, --, 2, 3],
+                 mask=[ True,  True, False, False],
+           fill_value=999999)
+
+    """
+    return masked_where(less(x, value), x, copy=copy)
+
+
+def masked_less_equal(x, value, copy=True):
+    """
+    Mask an array where less than or equal to a given value.
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = (x <= value).
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_less_equal(a, 2)
+    masked_array(data=[--, --, --, 3],
+                 mask=[ True,  True,  True, False],
+           fill_value=999999)
+
+    """
+    return masked_where(less_equal(x, value), x, copy=copy)
+
+
+def masked_not_equal(x, value, copy=True):
+    """
+    Mask an array where *not* equal to a given value.
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = (x != value).
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_not_equal(a, 2)
+    masked_array(data=[--, --, 2, --],
+                 mask=[ True,  True, False,  True],
+           fill_value=999999)
+
+    """
+    return masked_where(not_equal(x, value), x, copy=copy)
+
+
+def masked_equal(x, value, copy=True):
+    """
+    Mask an array where equal to a given value.
+
+    Return a MaskedArray, masked where the data in array `x` are
+    equal to `value`. The fill_value of the returned MaskedArray
+    is set to `value`.
+
+    For floating point arrays, consider using ``masked_values(x, value)``.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+    masked_values : Mask using floating point equality.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(4)
+    >>> a
+    array([0, 1, 2, 3])
+    >>> ma.masked_equal(a, 2)
+    masked_array(data=[0, 1, --, 3],
+                 mask=[False, False,  True, False],
+           fill_value=2)
+
+    """
+    output = masked_where(equal(x, value), x, copy=copy)
+    output.fill_value = value
+    return output
+
+
+def masked_inside(x, v1, v2, copy=True):
+    """
+    Mask an array inside a given interval.
+
+    Shortcut to ``masked_where``, where `condition` is True for `x` inside
+    the interval [v1,v2] (v1 <= x <= v2).  The boundaries `v1` and `v2`
+    can be given in either order.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Notes
+    -----
+    The array `x` is prefilled with its filling value.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1]
+    >>> ma.masked_inside(x, -0.3, 0.3)
+    masked_array(data=[0.31, 1.2, --, --, -0.4, -1.1],
+                 mask=[False, False,  True,  True, False, False],
+           fill_value=1e+20)
+
+    The order of `v1` and `v2` doesn't matter.
+
+    >>> ma.masked_inside(x, 0.3, -0.3)
+    masked_array(data=[0.31, 1.2, --, --, -0.4, -1.1],
+                 mask=[False, False,  True,  True, False, False],
+           fill_value=1e+20)
+
+    """
+    if v2 < v1:
+        (v1, v2) = (v2, v1)
+    xf = filled(x)
+    condition = (xf >= v1) & (xf <= v2)
+    return masked_where(condition, x, copy=copy)
+
+
+def masked_outside(x, v1, v2, copy=True):
+    """
+    Mask an array outside a given interval.
+
+    Shortcut to ``masked_where``, where `condition` is True for `x` outside
+    the interval [v1,v2] (x < v1)|(x > v2).
+    The boundaries `v1` and `v2` can be given in either order.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Notes
+    -----
+    The array `x` is prefilled with its filling value.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1]
+    >>> ma.masked_outside(x, -0.3, 0.3)
+    masked_array(data=[--, --, 0.01, 0.2, --, --],
+                 mask=[ True,  True, False, False,  True,  True],
+           fill_value=1e+20)
+
+    The order of `v1` and `v2` doesn't matter.
+
+    >>> ma.masked_outside(x, 0.3, -0.3)
+    masked_array(data=[--, --, 0.01, 0.2, --, --],
+                 mask=[ True,  True, False, False,  True,  True],
+           fill_value=1e+20)
+
+    """
+    if v2 < v1:
+        (v1, v2) = (v2, v1)
+    xf = filled(x)
+    condition = (xf < v1) | (xf > v2)
+    return masked_where(condition, x, copy=copy)
+
+
+def masked_object(x, value, copy=True, shrink=True):
+    """
+    Mask the array `x` where the data are exactly equal to value.
+
+    This function is similar to `masked_values`, but only suitable
+    for object arrays: for floating point, use `masked_values` instead.
+
+    Parameters
+    ----------
+    x : array_like
+        Array to mask
+    value : object
+        Comparison value
+    copy : {True, False}, optional
+        Whether to return a copy of `x`.
+    shrink : {True, False}, optional
+        Whether to collapse a mask full of False to nomask
+
+    Returns
+    -------
+    result : MaskedArray
+        The result of masking `x` where equal to `value`.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+    masked_equal : Mask where equal to a given value (integers).
+    masked_values : Mask using floating point equality.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> food = np.array(['green_eggs', 'ham'], dtype=object)
+    >>> # don't eat spoiled food
+    >>> eat = ma.masked_object(food, 'green_eggs')
+    >>> eat
+    masked_array(data=[--, 'ham'],
+                 mask=[ True, False],
+           fill_value='green_eggs',
+                dtype=object)
+    >>> # plain ol` ham is boring
+    >>> fresh_food = np.array(['cheese', 'ham', 'pineapple'], dtype=object)
+    >>> eat = ma.masked_object(fresh_food, 'green_eggs')
+    >>> eat
+    masked_array(data=['cheese', 'ham', 'pineapple'],
+                 mask=False,
+           fill_value='green_eggs',
+                dtype=object)
+
+    Note that `mask` is set to ``nomask`` if possible.
+
+    >>> eat
+    masked_array(data=['cheese', 'ham', 'pineapple'],
+                 mask=False,
+           fill_value='green_eggs',
+                dtype=object)
+
+    """
+    if isMaskedArray(x):
+        condition = umath.equal(x._data, value)
+        mask = x._mask
+    else:
+        condition = umath.equal(np.asarray(x), value)
+        mask = nomask
+    mask = mask_or(mask, make_mask(condition, shrink=shrink))
+    return masked_array(x, mask=mask, copy=copy, fill_value=value)
+
+
+def masked_values(x, value, rtol=1e-5, atol=1e-8, copy=True, shrink=True):
+    """
+    Mask using floating point equality.
+
+    Return a MaskedArray, masked where the data in array `x` are approximately
+    equal to `value`, determined using `isclose`. The default tolerances for
+    `masked_values` are the same as those for `isclose`.
+
+    For integer types, exact equality is used, in the same way as
+    `masked_equal`.
+
+    The fill_value is set to `value` and the mask is set to ``nomask`` if
+    possible.
+
+    Parameters
+    ----------
+    x : array_like
+        Array to mask.
+    value : float
+        Masking value.
+    rtol, atol : float, optional
+        Tolerance parameters passed on to `isclose`
+    copy : bool, optional
+        Whether to return a copy of `x`.
+    shrink : bool, optional
+        Whether to collapse a mask full of False to ``nomask``.
+
+    Returns
+    -------
+    result : MaskedArray
+        The result of masking `x` where approximately equal to `value`.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+    masked_equal : Mask where equal to a given value (integers).
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = np.array([1, 1.1, 2, 1.1, 3])
+    >>> ma.masked_values(x, 1.1)
+    masked_array(data=[1.0, --, 2.0, --, 3.0],
+                 mask=[False,  True, False,  True, False],
+           fill_value=1.1)
+
+    Note that `mask` is set to ``nomask`` if possible.
+
+    >>> ma.masked_values(x, 2.1)
+    masked_array(data=[1. , 1.1, 2. , 1.1, 3. ],
+                 mask=False,
+           fill_value=2.1)
+
+    Unlike `masked_equal`, `masked_values` can perform approximate equalities.
+
+    >>> ma.masked_values(x, 2.1, atol=1e-1)
+    masked_array(data=[1.0, 1.1, --, 1.1, 3.0],
+                 mask=[False, False,  True, False, False],
+           fill_value=2.1)
+
+    """
+    xnew = filled(x, value)
+    if np.issubdtype(xnew.dtype, np.floating):
+        mask = np.isclose(xnew, value, atol=atol, rtol=rtol)
+    else:
+        mask = umath.equal(xnew, value)
+    ret = masked_array(xnew, mask=mask, copy=copy, fill_value=value)
+    if shrink:
+        ret.shrink_mask()
+    return ret
+
+
+def masked_invalid(a, copy=True):
+    """
+    Mask an array where invalid values occur (NaNs or infs).
+
+    This function is a shortcut to ``masked_where``, with
+    `condition` = ~(np.isfinite(a)). Any pre-existing mask is conserved.
+    Only applies to arrays with a dtype where NaNs or infs make sense
+    (i.e. floating point types), but accepts any array_like object.
+
+    See Also
+    --------
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.arange(5, dtype=float)
+    >>> a[2] = np.nan
+    >>> a[3] = np.inf
+    >>> a
+    array([ 0.,  1., nan, inf,  4.])
+    >>> ma.masked_invalid(a)
+    masked_array(data=[0.0, 1.0, --, --, 4.0],
+                 mask=[False, False,  True,  True, False],
+           fill_value=1e+20)
+
+    """
+    a = np.array(a, copy=None, subok=True)
+    res = masked_where(~(np.isfinite(a)), a, copy=copy)
+    # masked_invalid previously never returned nomask as a mask and doing so
+    # threw off matplotlib (gh-22842).  So use shrink=False:
+    if res._mask is nomask:
+        res._mask = make_mask_none(res.shape, res.dtype)
+    return res
+
+###############################################################################
+#                            Printing options                                 #
+###############################################################################
+
+
+class _MaskedPrintOption:
+    """
+    Handle the string used to represent missing data in a masked array.
+
+    """
+
+    def __init__(self, display):
+        """
+        Create the masked_print_option object.
+
+        """
+        self._display = display
+        self._enabled = True
+
+    def display(self):
+        """
+        Display the string to print for masked values.
+
+        """
+        return self._display
+
+    def set_display(self, s):
+        """
+        Set the string to print for masked values.
+
+        """
+        self._display = s
+
+    def enabled(self):
+        """
+        Is the use of the display value enabled?
+
+        """
+        return self._enabled
+
+    def enable(self, shrink=1):
+        """
+        Set the enabling shrink to `shrink`.
+
+        """
+        self._enabled = shrink
+
+    def __str__(self):
+        return str(self._display)
+
+    __repr__ = __str__
+
+
+# if you single index into a masked location you get this object.
+masked_print_option = _MaskedPrintOption('--')
+
+
+def _recursive_printoption(result, mask, printopt):
+    """
+    Puts printoptions in result where mask is True.
+
+    Private function allowing for recursion
+
+    """
+    names = result.dtype.names
+    if names is not None:
+        for name in names:
+            curdata = result[name]
+            curmask = mask[name]
+            _recursive_printoption(curdata, curmask, printopt)
+    else:
+        np.copyto(result, printopt, where=mask)
+
+
+# For better or worse, these end in a newline
+_legacy_print_templates = {
+    'long_std': textwrap.dedent("""\
+        masked_%(name)s(data =
+         %(data)s,
+        %(nlen)s        mask =
+         %(mask)s,
+        %(nlen)s  fill_value = %(fill)s)
+        """),
+    'long_flx': textwrap.dedent("""\
+        masked_%(name)s(data =
+         %(data)s,
+        %(nlen)s        mask =
+         %(mask)s,
+        %(nlen)s  fill_value = %(fill)s,
+        %(nlen)s       dtype = %(dtype)s)
+        """),
+    'short_std': textwrap.dedent("""\
+        masked_%(name)s(data = %(data)s,
+        %(nlen)s        mask = %(mask)s,
+        %(nlen)s  fill_value = %(fill)s)
+        """),
+    'short_flx': textwrap.dedent("""\
+        masked_%(name)s(data = %(data)s,
+        %(nlen)s        mask = %(mask)s,
+        %(nlen)s  fill_value = %(fill)s,
+        %(nlen)s       dtype = %(dtype)s)
+        """)
+}
+
+###############################################################################
+#                          MaskedArray class                                  #
+###############################################################################
+
+
+def _recursive_filled(a, mask, fill_value):
+    """
+    Recursively fill `a` with `fill_value`.
+
+    """
+    names = a.dtype.names
+    for name in names:
+        current = a[name]
+        if current.dtype.names is not None:
+            _recursive_filled(current, mask[name], fill_value[name])
+        else:
+            np.copyto(current, fill_value[name], where=mask[name])
+
+
+def flatten_structured_array(a):
+    """
+    Flatten a structured array.
+
+    The data type of the output is chosen such that it can represent all of the
+    (nested) fields.
+
+    Parameters
+    ----------
+    a : structured array
+
+    Returns
+    -------
+    output : masked array or ndarray
+        A flattened masked array if the input is a masked array, otherwise a
+        standard ndarray.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> ndtype = [('a', int), ('b', float)]
+    >>> a = np.array([(1, 1), (2, 2)], dtype=ndtype)
+    >>> np.ma.flatten_structured_array(a)
+    array([[1., 1.],
+           [2., 2.]])
+
+    """
+
+    def flatten_sequence(iterable):
+        """
+        Flattens a compound of nested iterables.
+
+        """
+        for elm in iter(iterable):
+            if hasattr(elm, "__iter__") and not isinstance(elm, (str, bytes)):
+                yield from flatten_sequence(elm)
+            else:
+                yield elm
+
+    a = np.asanyarray(a)
+    inishape = a.shape
+    a = a.ravel()
+    if isinstance(a, MaskedArray):
+        out = np.array([tuple(flatten_sequence(d.item())) for d in a._data])
+        out = out.view(MaskedArray)
+        out._mask = np.array([tuple(flatten_sequence(d.item()))
+                              for d in getmaskarray(a)])
+    else:
+        out = np.array([tuple(flatten_sequence(d.item())) for d in a])
+    if len(inishape) > 1:
+        newshape = list(out.shape)
+        newshape[0] = inishape
+        out.shape = tuple(flatten_sequence(newshape))
+    return out
+
+
+def _arraymethod(funcname, onmask=True):
+    """
+    Return a class method wrapper around a basic array method.
+
+    Creates a class method which returns a masked array, where the new
+    ``_data`` array is the output of the corresponding basic method called
+    on the original ``_data``.
+
+    If `onmask` is True, the new mask is the output of the method called
+    on the initial mask. Otherwise, the new mask is just a reference
+    to the initial mask.
+
+    Parameters
+    ----------
+    funcname : str
+        Name of the function to apply on data.
+    onmask : bool
+        Whether the mask must be processed also (True) or left
+        alone (False). Default is True. Make available as `_onmask`
+        attribute.
+
+    Returns
+    -------
+    method : instancemethod
+        Class method wrapper of the specified basic array method.
+
+    """
+    def wrapped_method(self, *args, **params):
+        result = getattr(self._data, funcname)(*args, **params)
+        result = result.view(type(self))
+        result._update_from(self)
+        mask = self._mask
+        if not onmask:
+            result.__setmask__(mask)
+        elif mask is not nomask:
+            # __setmask__ makes a copy, which we don't want
+            result._mask = getattr(mask, funcname)(*args, **params)
+        return result
+    methdoc = getattr(ndarray, funcname, None) or getattr(np, funcname, None)
+    if methdoc is not None:
+        wrapped_method.__doc__ = methdoc.__doc__
+    wrapped_method.__name__ = funcname
+    return wrapped_method
+
+
+class MaskedIterator:
+    """
+    Flat iterator object to iterate over masked arrays.
+
+    A `MaskedIterator` iterator is returned by ``x.flat`` for any masked array
+    `x`. It allows iterating over the array as if it were a 1-D array,
+    either in a for-loop or by calling its `next` method.
+
+    Iteration is done in C-contiguous style, with the last index varying the
+    fastest. The iterator can also be indexed using basic slicing or
+    advanced indexing.
+
+    See Also
+    --------
+    MaskedArray.flat : Return a flat iterator over an array.
+    MaskedArray.flatten : Returns a flattened copy of an array.
+
+    Notes
+    -----
+    `MaskedIterator` is not exported by the `ma` module. Instead of
+    instantiating a `MaskedIterator` directly, use `MaskedArray.flat`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array(arange(6).reshape(2, 3))
+    >>> fl = x.flat
+    >>> type(fl)
+    <class 'numpy.ma.MaskedIterator'>
+    >>> for item in fl:
+    ...     print(item)
+    ...
+    0
+    1
+    2
+    3
+    4
+    5
+
+    Extracting more than a single element b indexing the `MaskedIterator`
+    returns a masked array:
+
+    >>> fl[2:4]
+    masked_array(data = [2 3],
+                 mask = False,
+           fill_value = 999999)
+
+    """
+
+    def __init__(self, ma):
+        self.ma = ma
+        self.dataiter = ma._data.flat
+
+        if ma._mask is nomask:
+            self.maskiter = None
+        else:
+            self.maskiter = ma._mask.flat
+
+    def __iter__(self):
+        return self
+
+    def __getitem__(self, indx):
+        result = self.dataiter.__getitem__(indx).view(type(self.ma))
+        if self.maskiter is not None:
+            _mask = self.maskiter.__getitem__(indx)
+            if isinstance(_mask, ndarray):
+                # set shape to match that of data; this is needed for matrices
+                _mask.shape = result.shape
+                result._mask = _mask
+            elif isinstance(_mask, np.void):
+                return mvoid(result, mask=_mask, hardmask=self.ma._hardmask)
+            elif _mask:  # Just a scalar, masked
+                return masked
+        return result
+
+    # This won't work if ravel makes a copy
+    def __setitem__(self, index, value):
+        self.dataiter[index] = getdata(value)
+        if self.maskiter is not None:
+            self.maskiter[index] = getmaskarray(value)
+
+    def __next__(self):
+        """
+        Return the next value, or raise StopIteration.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([3, 2], mask=[0, 1])
+        >>> fl = x.flat
+        >>> next(fl)
+        3
+        >>> next(fl)
+        masked
+        >>> next(fl)
+        Traceback (most recent call last):
+          ...
+        StopIteration
+
+        """
+        d = next(self.dataiter)
+        if self.maskiter is not None:
+            m = next(self.maskiter)
+            if isinstance(m, np.void):
+                return mvoid(d, mask=m, hardmask=self.ma._hardmask)
+            elif m:  # Just a scalar, masked
+                return masked
+        return d
+
+
+@set_module("numpy.ma")
+class MaskedArray(ndarray):
+    """
+    An array class with possibly masked values.
+
+    Masked values of True exclude the corresponding element from any
+    computation.
+
+    Construction::
+
+      x = MaskedArray(data, mask=nomask, dtype=None, copy=False, subok=True,
+                      ndmin=0, fill_value=None, keep_mask=True, hard_mask=None,
+                      shrink=True, order=None)
+
+    Parameters
+    ----------
+    data : array_like
+        Input data.
+    mask : sequence, optional
+        Mask. Must be convertible to an array of booleans with the same
+        shape as `data`. True indicates a masked (i.e. invalid) data.
+    dtype : dtype, optional
+        Data type of the output.
+        If `dtype` is None, the type of the data argument (``data.dtype``)
+        is used. If `dtype` is not None and different from ``data.dtype``,
+        a copy is performed.
+    copy : bool, optional
+        Whether to copy the input data (True), or to use a reference instead.
+        Default is False.
+    subok : bool, optional
+        Whether to return a subclass of `MaskedArray` if possible (True) or a
+        plain `MaskedArray`. Default is True.
+    ndmin : int, optional
+        Minimum number of dimensions. Default is 0.
+    fill_value : scalar, optional
+        Value used to fill in the masked values when necessary.
+        If None, a default based on the data-type is used.
+    keep_mask : bool, optional
+        Whether to combine `mask` with the mask of the input data, if any
+        (True), or to use only `mask` for the output (False). Default is True.
+    hard_mask : bool, optional
+        Whether to use a hard mask or not. With a hard mask, masked values
+        cannot be unmasked. Default is False.
+    shrink : bool, optional
+        Whether to force compression of an empty mask. Default is True.
+    order : {'C', 'F', 'A'}, optional
+        Specify the order of the array.  If order is 'C', then the array
+        will be in C-contiguous order (last-index varies the fastest).
+        If order is 'F', then the returned array will be in
+        Fortran-contiguous order (first-index varies the fastest).
+        If order is 'A' (default), then the returned array may be
+        in any order (either C-, Fortran-contiguous, or even discontiguous),
+        unless a copy is required, in which case it will be C-contiguous.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    The ``mask`` can be initialized with an array of boolean values
+    with the same shape as ``data``.
+
+    >>> data = np.arange(6).reshape((2, 3))
+    >>> np.ma.MaskedArray(data, mask=[[False, True, False],
+    ...                               [False, False, True]])
+    masked_array(
+      data=[[0, --, 2],
+            [3, 4, --]],
+      mask=[[False,  True, False],
+            [False, False,  True]],
+      fill_value=999999)
+
+    Alternatively, the ``mask`` can be initialized to homogeneous boolean
+    array with the same shape as ``data`` by passing in a scalar
+    boolean value:
+
+    >>> np.ma.MaskedArray(data, mask=False)
+    masked_array(
+      data=[[0, 1, 2],
+            [3, 4, 5]],
+      mask=[[False, False, False],
+            [False, False, False]],
+      fill_value=999999)
+
+    >>> np.ma.MaskedArray(data, mask=True)
+    masked_array(
+      data=[[--, --, --],
+            [--, --, --]],
+      mask=[[ True,  True,  True],
+            [ True,  True,  True]],
+      fill_value=999999,
+      dtype=int64)
+
+    .. note::
+        The recommended practice for initializing ``mask`` with a scalar
+        boolean value is to use ``True``/``False`` rather than
+        ``np.True_``/``np.False_``. The reason is :attr:`nomask`
+        is represented internally as ``np.False_``.
+
+        >>> np.False_ is np.ma.nomask
+        True
+
+    """
+
+    __array_priority__ = 15
+    _defaultmask = nomask
+    _defaulthardmask = False
+    _baseclass = ndarray
+
+    # Maximum number of elements per axis used when printing an array. The
+    # 1d case is handled separately because we need more values in this case.
+    _print_width = 100
+    _print_width_1d = 1500
+
+    def __new__(cls, data=None, mask=nomask, dtype=None, copy=False,
+                subok=True, ndmin=0, fill_value=None, keep_mask=True,
+                hard_mask=None, shrink=True, order=None):
+        """
+        Create a new masked array from scratch.
+
+        Notes
+        -----
+        A masked array can also be created by taking a .view(MaskedArray).
+
+        """
+        # Process data.
+        copy = None if not copy else True
+        _data = np.array(data, dtype=dtype, copy=copy,
+                         order=order, subok=True, ndmin=ndmin)
+        _baseclass = getattr(data, '_baseclass', type(_data))
+        # Check that we're not erasing the mask.
+        if isinstance(data, MaskedArray) and (data.shape != _data.shape):
+            copy = True
+
+        # Here, we copy the _view_, so that we can attach new properties to it
+        # we must never do .view(MaskedConstant), as that would create a new
+        # instance of np.ma.masked, which make identity comparison fail
+        if isinstance(data, cls) and subok and not isinstance(data, MaskedConstant):
+            _data = ndarray.view(_data, type(data))
+        else:
+            _data = ndarray.view(_data, cls)
+
+        # Handle the case where data is not a subclass of ndarray, but
+        # still has the _mask attribute like MaskedArrays
+        if hasattr(data, '_mask') and not isinstance(data, ndarray):
+            _data._mask = data._mask
+            # FIXME: should we set `_data._sharedmask = True`?
+        # Process mask.
+        # Type of the mask
+        mdtype = make_mask_descr(_data.dtype)
+        if mask is nomask:
+            # Case 1. : no mask in input.
+            # Erase the current mask ?
+            if not keep_mask:
+                # With a reduced version
+                if shrink:
+                    _data._mask = nomask
+                # With full version
+                else:
+                    _data._mask = np.zeros(_data.shape, dtype=mdtype)
+            # Check whether we missed something
+            elif isinstance(data, (tuple, list)):
+                try:
+                    # If data is a sequence of masked array
+                    mask = np.array(
+                        [getmaskarray(np.asanyarray(m, dtype=_data.dtype))
+                         for m in data], dtype=mdtype)
+                except (ValueError, TypeError):
+                    # If data is nested
+                    mask = nomask
+                # Force shrinking of the mask if needed (and possible)
+                if (mdtype == MaskType) and mask.any():
+                    _data._mask = mask
+                    _data._sharedmask = False
+            else:
+                _data._sharedmask = not copy
+                if copy:
+                    _data._mask = _data._mask.copy()
+                    # Reset the shape of the original mask
+                    if getmask(data) is not nomask:
+                        # gh-21022 encounters an issue here
+                        # because data._mask.shape is not writeable, but
+                        # the op was also pointless in that case, because
+                        # the shapes were the same, so we can at least
+                        # avoid that path
+                        if data._mask.shape != data.shape:
+                            data._mask.shape = data.shape
+        else:
+            # Case 2. : With a mask in input.
+            # If mask is boolean, create an array of True or False
+
+            # if users pass `mask=None` be forgiving here and cast it False
+            # for speed; although the default is `mask=nomask` and can differ.
+            if mask is None:
+                mask = False
+
+            if mask is True and mdtype == MaskType:
+                mask = np.ones(_data.shape, dtype=mdtype)
+            elif mask is False and mdtype == MaskType:
+                mask = np.zeros(_data.shape, dtype=mdtype)
+            else:
+                # Read the mask with the current mdtype
+                try:
+                    mask = np.array(mask, copy=copy, dtype=mdtype)
+                # Or assume it's a sequence of bool/int
+                except TypeError:
+                    mask = np.array([tuple([m] * len(mdtype)) for m in mask],
+                                    dtype=mdtype)
+            # Make sure the mask and the data have the same shape
+            if mask.shape != _data.shape:
+                (nd, nm) = (_data.size, mask.size)
+                if nm == 1:
+                    mask = np.resize(mask, _data.shape)
+                elif nm == nd:
+                    mask = np.reshape(mask, _data.shape)
+                else:
+                    msg = (f"Mask and data not compatible:"
+                           f" data size is {nd}, mask size is {nm}.")
+                    raise MaskError(msg)
+                copy = True
+            # Set the mask to the new value
+            if _data._mask is nomask:
+                _data._mask = mask
+                _data._sharedmask = not copy
+            elif not keep_mask:
+                _data._mask = mask
+                _data._sharedmask = not copy
+            else:
+                if _data.dtype.names is not None:
+                    def _recursive_or(a, b):
+                        "do a|=b on each field of a, recursively"
+                        for name in a.dtype.names:
+                            (af, bf) = (a[name], b[name])
+                            if af.dtype.names is not None:
+                                _recursive_or(af, bf)
+                            else:
+                                af |= bf
+
+                    _recursive_or(_data._mask, mask)
+                else:
+                    _data._mask = np.logical_or(mask, _data._mask)
+                _data._sharedmask = False
+
+        # Update fill_value.
+        if fill_value is None:
+            fill_value = getattr(data, '_fill_value', None)
+        # But don't run the check unless we have something to check.
+        if fill_value is not None:
+            _data._fill_value = _check_fill_value(fill_value, _data.dtype)
+        # Process extra options ..
+        if hard_mask is None:
+            _data._hardmask = getattr(data, '_hardmask', False)
+        else:
+            _data._hardmask = hard_mask
+        _data._baseclass = _baseclass
+        return _data
+
+    def _update_from(self, obj):
+        """
+        Copies some attributes of obj to self.
+
+        """
+        if isinstance(obj, ndarray):
+            _baseclass = type(obj)
+        else:
+            _baseclass = ndarray
+        # We need to copy the _basedict to avoid backward propagation
+        _optinfo = {}
+        _optinfo.update(getattr(obj, '_optinfo', {}))
+        _optinfo.update(getattr(obj, '_basedict', {}))
+        if not isinstance(obj, MaskedArray):
+            _optinfo.update(getattr(obj, '__dict__', {}))
+        _dict = {'_fill_value': getattr(obj, '_fill_value', None),
+                     '_hardmask': getattr(obj, '_hardmask', False),
+                     '_sharedmask': getattr(obj, '_sharedmask', False),
+                     '_isfield': getattr(obj, '_isfield', False),
+                     '_baseclass': getattr(obj, '_baseclass', _baseclass),
+                     '_optinfo': _optinfo,
+                     '_basedict': _optinfo}
+        self.__dict__.update(_dict)
+        self.__dict__.update(_optinfo)
+
+    def __array_finalize__(self, obj):
+        """
+        Finalizes the masked array.
+
+        """
+        # Get main attributes.
+        self._update_from(obj)
+
+        # We have to decide how to initialize self.mask, based on
+        # obj.mask. This is very difficult.  There might be some
+        # correspondence between the elements in the array we are being
+        # created from (= obj) and us. Or there might not. This method can
+        # be called in all kinds of places for all kinds of reasons -- could
+        # be empty_like, could be slicing, could be a ufunc, could be a view.
+        # The numpy subclassing interface simply doesn't give us any way
+        # to know, which means that at best this method will be based on
+        # guesswork and heuristics. To make things worse, there isn't even any
+        # clear consensus about what the desired behavior is. For instance,
+        # most users think that np.empty_like(marr) -- which goes via this
+        # method -- should return a masked array with an empty mask (see
+        # gh-3404 and linked discussions), but others disagree, and they have
+        # existing code which depends on empty_like returning an array that
+        # matches the input mask.
+        #
+        # Historically our algorithm was: if the template object mask had the
+        # same *number of elements* as us, then we used *it's mask object
+        # itself* as our mask, so that writes to us would also write to the
+        # original array. This is horribly broken in multiple ways.
+        #
+        # Now what we do instead is, if the template object mask has the same
+        # number of elements as us, and we do not have the same base pointer
+        # as the template object (b/c views like arr[...] should keep the same
+        # mask), then we make a copy of the template object mask and use
+        # that. This is also horribly broken but somewhat less so. Maybe.
+        if isinstance(obj, ndarray):
+            # XX: This looks like a bug -- shouldn't it check self.dtype
+            # instead?
+            if obj.dtype.names is not None:
+                _mask = getmaskarray(obj)
+            else:
+                _mask = getmask(obj)
+
+            # If self and obj point to exactly the same data, then probably
+            # self is a simple view of obj (e.g., self = obj[...]), so they
+            # should share the same mask. (This isn't 100% reliable, e.g. self
+            # could be the first row of obj, or have strange strides, but as a
+            # heuristic it's not bad.) In all other cases, we make a copy of
+            # the mask, so that future modifications to 'self' do not end up
+            # side-effecting 'obj' as well.
+            if (_mask is not nomask and obj.__array_interface__["data"][0]
+                    != self.__array_interface__["data"][0]):
+                # We should make a copy. But we could get here via astype,
+                # in which case the mask might need a new dtype as well
+                # (e.g., changing to or from a structured dtype), and the
+                # order could have changed. So, change the mask type if
+                # needed and use astype instead of copy.
+                if self.dtype == obj.dtype:
+                    _mask_dtype = _mask.dtype
+                else:
+                    _mask_dtype = make_mask_descr(self.dtype)
+
+                if self.flags.c_contiguous:
+                    order = "C"
+                elif self.flags.f_contiguous:
+                    order = "F"
+                else:
+                    order = "K"
+
+                _mask = _mask.astype(_mask_dtype, order)
+            else:
+                # Take a view so shape changes, etc., do not propagate back.
+                _mask = _mask.view()
+        else:
+            _mask = nomask
+
+        self._mask = _mask
+        # Finalize the mask
+        if self._mask is not nomask:
+            try:
+                self._mask.shape = self.shape
+            except ValueError:
+                self._mask = nomask
+            except (TypeError, AttributeError):
+                # When _mask.shape is not writable (because it's a void)
+                pass
+
+        # Finalize the fill_value
+        if self._fill_value is not None:
+            self._fill_value = _check_fill_value(self._fill_value, self.dtype)
+        elif self.dtype.names is not None:
+            # Finalize the default fill_value for structured arrays
+            self._fill_value = _check_fill_value(None, self.dtype)
+
+    def __array_wrap__(self, obj, context=None, return_scalar=False):
+        """
+        Special hook for ufuncs.
+
+        Wraps the numpy array and sets the mask according to context.
+
+        """
+        if obj is self:  # for in-place operations
+            result = obj
+        else:
+            result = obj.view(type(self))
+            result._update_from(self)
+
+        if context is not None:
+            result._mask = result._mask.copy()
+            func, args, out_i = context
+            # args sometimes contains outputs (gh-10459), which we don't want
+            input_args = args[:func.nin]
+            m = functools.reduce(mask_or, [getmaskarray(arg) for arg in input_args])
+            # Get the domain mask
+            domain = ufunc_domain.get(func)
+            if domain is not None:
+                # Take the domain, and make sure it's a ndarray
+                with np.errstate(divide='ignore', invalid='ignore'):
+                    # The result may be masked for two (unary) domains.
+                    # That can't really be right as some domains drop
+                    # the mask and some don't behaving differently here.
+                    d = domain(*input_args).astype(bool, copy=False)
+                    d = filled(d, True)
+
+                if d.any():
+                    # Fill the result where the domain is wrong
+                    try:
+                        # Binary domain: take the last value
+                        fill_value = ufunc_fills[func][-1]
+                    except TypeError:
+                        # Unary domain: just use this one
+                        fill_value = ufunc_fills[func]
+                    except KeyError:
+                        # Domain not recognized, use fill_value instead
+                        fill_value = self.fill_value
+
+                    np.copyto(result, fill_value, where=d)
+
+                    # Update the mask
+                    if m is nomask:
+                        m = d
+                    else:
+                        # Don't modify inplace, we risk back-propagation
+                        m = (m | d)
+
+            # Make sure the mask has the proper size
+            if result is not self and result.shape == () and m:
+                return masked
+            else:
+                result._mask = m
+                result._sharedmask = False
+
+        return result
+
+    def view(self, dtype=None, type=None, fill_value=None):
+        """
+        Return a view of the MaskedArray data.
+
+        Parameters
+        ----------
+        dtype : data-type or ndarray sub-class, optional
+            Data-type descriptor of the returned view, e.g., float32 or int16.
+            The default, None, results in the view having the same data-type
+            as `a`. As with ``ndarray.view``, dtype can also be specified as
+            an ndarray sub-class, which then specifies the type of the
+            returned object (this is equivalent to setting the ``type``
+            parameter).
+        type : Python type, optional
+            Type of the returned view, either ndarray or a subclass.  The
+            default None results in type preservation.
+        fill_value : scalar, optional
+            The value to use for invalid entries (None by default).
+            If None, then this argument is inferred from the passed `dtype`, or
+            in its absence the original array, as discussed in the notes below.
+
+        See Also
+        --------
+        numpy.ndarray.view : Equivalent method on ndarray object.
+
+        Notes
+        -----
+
+        ``a.view()`` is used two different ways:
+
+        ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view
+        of the array's memory with a different data-type.  This can cause a
+        reinterpretation of the bytes of memory.
+
+        ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just
+        returns an instance of `ndarray_subclass` that looks at the same array
+        (same shape, dtype, etc.)  This does not cause a reinterpretation of the
+        memory.
+
+        If `fill_value` is not specified, but `dtype` is specified (and is not
+        an ndarray sub-class), the `fill_value` of the MaskedArray will be
+        reset. If neither `fill_value` nor `dtype` are specified (or if
+        `dtype` is an ndarray sub-class), then the fill value is preserved.
+        Finally, if `fill_value` is specified, but `dtype` is not, the fill
+        value is set to the specified value.
+
+        For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of
+        bytes per entry than the previous dtype (for example, converting a
+        regular array to a structured array), then the behavior of the view
+        cannot be predicted just from the superficial appearance of ``a`` (shown
+        by ``print(a)``). It also depends on exactly how ``a`` is stored in
+        memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus
+        defined as a slice or transpose, etc., the view may give different
+        results.
+        """
+
+        if dtype is None:
+            if type is None:
+                output = ndarray.view(self)
+            else:
+                output = ndarray.view(self, type)
+        elif type is None:
+            try:
+                if issubclass(dtype, ndarray):
+                    output = ndarray.view(self, dtype)
+                    dtype = None
+                else:
+                    output = ndarray.view(self, dtype)
+            except TypeError:
+                output = ndarray.view(self, dtype)
+        else:
+            output = ndarray.view(self, dtype, type)
+
+        # also make the mask be a view (so attr changes to the view's
+        # mask do no affect original object's mask)
+        # (especially important to avoid affecting np.masked singleton)
+        if getmask(output) is not nomask:
+            output._mask = output._mask.view()
+
+        # Make sure to reset the _fill_value if needed
+        if getattr(output, '_fill_value', None) is not None:
+            if fill_value is None:
+                if dtype is None:
+                    pass  # leave _fill_value as is
+                else:
+                    output._fill_value = None
+            else:
+                output.fill_value = fill_value
+        return output
+
+    def __getitem__(self, indx):
+        """
+        x.__getitem__(y) <==> x[y]
+
+        Return the item described by i, as a masked array.
+
+        """
+        # We could directly use ndarray.__getitem__ on self.
+        # But then we would have to modify __array_finalize__ to prevent the
+        # mask of being reshaped if it hasn't been set up properly yet
+        # So it's easier to stick to the current version
+        dout = self.data[indx]
+        _mask = self._mask
+
+        def _is_scalar(m):
+            return not isinstance(m, np.ndarray)
+
+        def _scalar_heuristic(arr, elem):
+            """
+            Return whether `elem` is a scalar result of indexing `arr`, or None
+            if undecidable without promoting nomask to a full mask
+            """
+            # obviously a scalar
+            if not isinstance(elem, np.ndarray):
+                return True
+
+            # object array scalar indexing can return anything
+            elif arr.dtype.type is np.object_:
+                if arr.dtype is not elem.dtype:
+                    # elem is an array, but dtypes do not match, so must be
+                    # an element
+                    return True
+
+            # well-behaved subclass that only returns 0d arrays when
+            # expected - this is not a scalar
+            elif type(arr).__getitem__ == ndarray.__getitem__:
+                return False
+
+            return None
+
+        if _mask is not nomask:
+            # _mask cannot be a subclass, so it tells us whether we should
+            # expect a scalar. It also cannot be of dtype object.
+            mout = _mask[indx]
+            scalar_expected = _is_scalar(mout)
+
+        else:
+            # attempt to apply the heuristic to avoid constructing a full mask
+            mout = nomask
+            scalar_expected = _scalar_heuristic(self.data, dout)
+            if scalar_expected is None:
+                # heuristics have failed
+                # construct a full array, so we can be certain. This is costly.
+                # we could also fall back on ndarray.__getitem__(self.data, indx)
+                scalar_expected = _is_scalar(getmaskarray(self)[indx])
+
+        # Did we extract a single item?
+        if scalar_expected:
+            # A record
+            if isinstance(dout, np.void):
+                # We should always re-cast to mvoid, otherwise users can
+                # change masks on rows that already have masked values, but not
+                # on rows that have no masked values, which is inconsistent.
+                return mvoid(dout, mask=mout, hardmask=self._hardmask)
+
+            # special case introduced in gh-5962
+            elif (self.dtype.type is np.object_ and
+                  isinstance(dout, np.ndarray) and
+                  dout is not masked):
+                # If masked, turn into a MaskedArray, with everything masked.
+                if mout:
+                    return MaskedArray(dout, mask=True)
+                else:
+                    return dout
+
+            # Just a scalar
+            elif mout:
+                return masked
+            else:
+                return dout
+        else:
+            # Force dout to MA
+            dout = dout.view(type(self))
+            # Inherit attributes from self
+            dout._update_from(self)
+            # Check the fill_value
+            if is_string_or_list_of_strings(indx):
+                if self._fill_value is not None:
+                    dout._fill_value = self._fill_value[indx]
+
+                    # Something like gh-15895 has happened if this check fails.
+                    # _fill_value should always be an ndarray.
+                    if not isinstance(dout._fill_value, np.ndarray):
+                        raise RuntimeError('Internal NumPy error.')
+                    # If we're indexing a multidimensional field in a
+                    # structured array (such as dtype("(2,)i2,(2,)i1")),
+                    # dimensionality goes up (M[field].ndim == M.ndim +
+                    # M.dtype[field].ndim).  That's fine for
+                    # M[field] but problematic for M[field].fill_value
+                    # which should have shape () to avoid breaking several
+                    # methods. There is no great way out, so set to
+                    # first element. See issue #6723.
+                    if dout._fill_value.ndim > 0:
+                        if not (dout._fill_value ==
+                                dout._fill_value.flat[0]).all():
+                            warnings.warn(
+                                "Upon accessing multidimensional field "
+                                f"{indx!s}, need to keep dimensionality "
+                                "of fill_value at 0. Discarding "
+                                "heterogeneous fill_value and setting "
+                                f"all to {dout._fill_value[0]!s}.",
+                                stacklevel=2)
+                        # Need to use `.flat[0:1].squeeze(...)` instead of just
+                        # `.flat[0]` to ensure the result is a 0d array and not
+                        # a scalar.
+                        dout._fill_value = dout._fill_value.flat[0:1].squeeze(axis=0)
+                dout._isfield = True
+            # Update the mask if needed
+            if mout is not nomask:
+                # set shape to match that of data; this is needed for matrices
+                dout._mask = reshape(mout, dout.shape)
+                dout._sharedmask = True
+                # Note: Don't try to check for m.any(), that'll take too long
+        return dout
+
+    # setitem may put NaNs into integer arrays or occasionally overflow a
+    # float.  But this may happen in masked values, so avoid otherwise
+    # correct warnings (as is typical also in masked calculations).
+    @np.errstate(over='ignore', invalid='ignore')
+    def __setitem__(self, indx, value):
+        """
+        x.__setitem__(i, y) <==> x[i]=y
+
+        Set item described by index. If value is masked, masks those
+        locations.
+
+        """
+        if self is masked:
+            raise MaskError('Cannot alter the masked element.')
+        _data = self._data
+        _mask = self._mask
+        if isinstance(indx, str):
+            _data[indx] = value
+            if _mask is nomask:
+                self._mask = _mask = make_mask_none(self.shape, self.dtype)
+            _mask[indx] = getmask(value)
+            return
+
+        _dtype = _data.dtype
+
+        if value is masked:
+            # The mask wasn't set: create a full version.
+            if _mask is nomask:
+                _mask = self._mask = make_mask_none(self.shape, _dtype)
+            # Now, set the mask to its value.
+            if _dtype.names is not None:
+                _mask[indx] = tuple([True] * len(_dtype.names))
+            else:
+                _mask[indx] = True
+            return
+
+        # Get the _data part of the new value
+        dval = getattr(value, '_data', value)
+        # Get the _mask part of the new value
+        mval = getmask(value)
+        if _dtype.names is not None and mval is nomask:
+            mval = tuple([False] * len(_dtype.names))
+        if _mask is nomask:
+            # Set the data, then the mask
+            _data[indx] = dval
+            if mval is not nomask:
+                _mask = self._mask = make_mask_none(self.shape, _dtype)
+                _mask[indx] = mval
+        elif not self._hardmask:
+            # Set the data, then the mask
+            if (isinstance(indx, masked_array) and
+                    not isinstance(value, masked_array)):
+                _data[indx.data] = dval
+            else:
+                _data[indx] = dval
+                _mask[indx] = mval
+        elif hasattr(indx, 'dtype') and (indx.dtype == MaskType):
+            indx = indx * umath.logical_not(_mask)
+            _data[indx] = dval
+        else:
+            if _dtype.names is not None:
+                err_msg = "Flexible 'hard' masks are not yet supported."
+                raise NotImplementedError(err_msg)
+            mindx = mask_or(_mask[indx], mval, copy=True)
+            dindx = self._data[indx]
+            if dindx.size > 1:
+                np.copyto(dindx, dval, where=~mindx)
+            elif mindx is nomask:
+                dindx = dval
+            _data[indx] = dindx
+            _mask[indx] = mindx
+        return
+
+    # Define so that we can overwrite the setter.
+    @property
+    def dtype(self):
+        return super().dtype
+
+    @dtype.setter
+    def dtype(self, dtype):
+        super(MaskedArray, type(self)).dtype.__set__(self, dtype)
+        if self._mask is not nomask:
+            self._mask = self._mask.view(make_mask_descr(dtype), ndarray)
+            # Try to reset the shape of the mask (if we don't have a void).
+            # This raises a ValueError if the dtype change won't work.
+            try:
+                self._mask.shape = self.shape
+            except (AttributeError, TypeError):
+                pass
+
+    @property
+    def shape(self):
+        return super().shape
+
+    @shape.setter
+    def shape(self, shape):
+        super(MaskedArray, type(self)).shape.__set__(self, shape)
+        # Cannot use self._mask, since it may not (yet) exist when a
+        # masked matrix sets the shape.
+        if getmask(self) is not nomask:
+            self._mask.shape = self.shape
+
+    def __setmask__(self, mask, copy=False):
+        """
+        Set the mask.
+
+        """
+        idtype = self.dtype
+        current_mask = self._mask
+        if mask is masked:
+            mask = True
+
+        if current_mask is nomask:
+            # Make sure the mask is set
+            # Just don't do anything if there's nothing to do.
+            if mask is nomask:
+                return
+            current_mask = self._mask = make_mask_none(self.shape, idtype)
+
+        if idtype.names is None:
+            # No named fields.
+            # Hardmask: don't unmask the data
+            if self._hardmask:
+                current_mask |= mask
+            # Softmask: set everything to False
+            # If it's obviously a compatible scalar, use a quick update
+            # method.
+            elif isinstance(mask, (int, float, np.bool, np.number)):
+                current_mask[...] = mask
+            # Otherwise fall back to the slower, general purpose way.
+            else:
+                current_mask.flat = mask
+        else:
+            # Named fields w/
+            mdtype = current_mask.dtype
+            mask = np.asarray(mask)
+            # Mask is a singleton
+            if not mask.ndim:
+                # It's a boolean : make a record
+                if mask.dtype.kind == 'b':
+                    mask = np.array(tuple([mask.item()] * len(mdtype)),
+                                    dtype=mdtype)
+                # It's a record: make sure the dtype is correct
+                else:
+                    mask = mask.astype(mdtype)
+            # Mask is a sequence
+            else:
+                # Make sure the new mask is a ndarray with the proper dtype
+                try:
+                    copy = None if not copy else True
+                    mask = np.array(mask, copy=copy, dtype=mdtype)
+                # Or assume it's a sequence of bool/int
+                except TypeError:
+                    mask = np.array([tuple([m] * len(mdtype)) for m in mask],
+                                    dtype=mdtype)
+            # Hardmask: don't unmask the data
+            if self._hardmask:
+                for n in idtype.names:
+                    current_mask[n] |= mask[n]
+            # Softmask: set everything to False
+            # If it's obviously a compatible scalar, use a quick update
+            # method.
+            elif isinstance(mask, (int, float, np.bool, np.number)):
+                current_mask[...] = mask
+            # Otherwise fall back to the slower, general purpose way.
+            else:
+                current_mask.flat = mask
+        # Reshape if needed
+        if current_mask.shape:
+            current_mask.shape = self.shape
+        return
+
+    _set_mask = __setmask__
+
+    @property
+    def mask(self):
+        """ Current mask. """
+
+        # We could try to force a reshape, but that wouldn't work in some
+        # cases.
+        # Return a view so that the dtype and shape cannot be changed in place
+        # This still preserves nomask by identity
+        return self._mask.view()
+
+    @mask.setter
+    def mask(self, value):
+        self.__setmask__(value)
+
+    @property
+    def recordmask(self):
+        """
+        Get or set the mask of the array if it has no named fields. For
+        structured arrays, returns a ndarray of booleans where entries are
+        ``True`` if **all** the fields are masked, ``False`` otherwise:
+
+        >>> x = np.ma.array([(1, 1), (2, 2), (3, 3), (4, 4), (5, 5)],
+        ...         mask=[(0, 0), (1, 0), (1, 1), (0, 1), (0, 0)],
+        ...        dtype=[('a', int), ('b', int)])
+        >>> x.recordmask
+        array([False, False,  True, False, False])
+        """
+
+        _mask = self._mask.view(ndarray)
+        if _mask.dtype.names is None:
+            return _mask
+        return np.all(flatten_structured_array(_mask), axis=-1)
+
+    @recordmask.setter
+    def recordmask(self, mask):
+        raise NotImplementedError("Coming soon: setting the mask per records!")
+
+    def harden_mask(self):
+        """
+        Force the mask to hard, preventing unmasking by assignment.
+
+        Whether the mask of a masked array is hard or soft is determined by
+        its `~ma.MaskedArray.hardmask` property. `harden_mask` sets
+        `~ma.MaskedArray.hardmask` to ``True`` (and returns the modified
+        self).
+
+        See Also
+        --------
+        ma.MaskedArray.hardmask
+        ma.MaskedArray.soften_mask
+
+        """
+        self._hardmask = True
+        return self
+
+    def soften_mask(self):
+        """
+        Force the mask to soft (default), allowing unmasking by assignment.
+
+        Whether the mask of a masked array is hard or soft is determined by
+        its `~ma.MaskedArray.hardmask` property. `soften_mask` sets
+        `~ma.MaskedArray.hardmask` to ``False`` (and returns the modified
+        self).
+
+        See Also
+        --------
+        ma.MaskedArray.hardmask
+        ma.MaskedArray.harden_mask
+
+        """
+        self._hardmask = False
+        return self
+
+    @property
+    def hardmask(self):
+        """
+        Specifies whether values can be unmasked through assignments.
+
+        By default, assigning definite values to masked array entries will
+        unmask them.  When `hardmask` is ``True``, the mask will not change
+        through assignments.
+
+        See Also
+        --------
+        ma.MaskedArray.harden_mask
+        ma.MaskedArray.soften_mask
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.arange(10)
+        >>> m = np.ma.masked_array(x, x>5)
+        >>> assert not m.hardmask
+
+        Since `m` has a soft mask, assigning an element value unmasks that
+        element:
+
+        >>> m[8] = 42
+        >>> m
+        masked_array(data=[0, 1, 2, 3, 4, 5, --, --, 42, --],
+                     mask=[False, False, False, False, False, False,
+                           True, True, False, True],
+               fill_value=999999)
+
+        After hardening, the mask is not affected by assignments:
+
+        >>> hardened = np.ma.harden_mask(m)
+        >>> assert m.hardmask and hardened is m
+        >>> m[:] = 23
+        >>> m
+        masked_array(data=[23, 23, 23, 23, 23, 23, --, --, 23, --],
+                     mask=[False, False, False, False, False, False,
+                           True, True, False, True],
+               fill_value=999999)
+
+        """
+        return self._hardmask
+
+    def unshare_mask(self):
+        """
+        Copy the mask and set the `sharedmask` flag to ``False``.
+
+        Whether the mask is shared between masked arrays can be seen from
+        the `sharedmask` property. `unshare_mask` ensures the mask is not
+        shared. A copy of the mask is only made if it was shared.
+
+        See Also
+        --------
+        sharedmask
+
+        """
+        if self._sharedmask:
+            self._mask = self._mask.copy()
+            self._sharedmask = False
+        return self
+
+    @property
+    def sharedmask(self):
+        """ Share status of the mask (read-only). """
+        return self._sharedmask
+
+    def shrink_mask(self):
+        """
+        Reduce a mask to nomask when possible.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        result : MaskedArray
+            A :class:`~ma.MaskedArray` object.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2 ], [3, 4]], mask=[0]*4)
+        >>> x.mask
+        array([[False, False],
+               [False, False]])
+        >>> x.shrink_mask()
+        masked_array(
+          data=[[1, 2],
+                [3, 4]],
+          mask=False,
+          fill_value=999999)
+        >>> x.mask
+        False
+
+        """
+        self._mask = _shrink_mask(self._mask)
+        return self
+
+    @property
+    def baseclass(self):
+        """ Class of the underlying data (read-only). """
+        return self._baseclass
+
+    def _get_data(self):
+        """
+        Returns the underlying data, as a view of the masked array.
+
+        If the underlying data is a subclass of :class:`numpy.ndarray`, it is
+        returned as such.
+
+        >>> x = np.ma.array(np.matrix([[1, 2], [3, 4]]), mask=[[0, 1], [1, 0]])
+        >>> x.data
+        matrix([[1, 2],
+                [3, 4]])
+
+        The type of the data can be accessed through the :attr:`baseclass`
+        attribute.
+        """
+        return ndarray.view(self, self._baseclass)
+
+    _data = property(fget=_get_data)
+    data = property(fget=_get_data)
+
+    @property
+    def flat(self):
+        """ Return a flat iterator, or set a flattened version of self to value. """
+        return MaskedIterator(self)
+
+    @flat.setter
+    def flat(self, value):
+        y = self.ravel()
+        y[:] = value
+
+    @property
+    def fill_value(self):
+        """
+        The filling value of the masked array is a scalar. When setting, None
+        will set to a default based on the data type.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> for dt in [np.int32, np.int64, np.float64, np.complex128]:
+        ...     np.ma.array([0, 1], dtype=dt).get_fill_value()
+        ...
+        np.int64(999999)
+        np.int64(999999)
+        np.float64(1e+20)
+        np.complex128(1e+20+0j)
+
+        >>> x = np.ma.array([0, 1.], fill_value=-np.inf)
+        >>> x.fill_value
+        np.float64(-inf)
+        >>> x.fill_value = np.pi
+        >>> x.fill_value
+        np.float64(3.1415926535897931)
+
+        Reset to default:
+
+        >>> x.fill_value = None
+        >>> x.fill_value
+        np.float64(1e+20)
+
+        """
+        if self._fill_value is None:
+            self._fill_value = _check_fill_value(None, self.dtype)
+
+        # Temporary workaround to account for the fact that str and bytes
+        # scalars cannot be indexed with (), whereas all other numpy
+        # scalars can. See issues #7259 and #7267.
+        # The if-block can be removed after #7267 has been fixed.
+        if isinstance(self._fill_value, ndarray):
+            return self._fill_value[()]
+        return self._fill_value
+
+    @fill_value.setter
+    def fill_value(self, value=None):
+        target = _check_fill_value(value, self.dtype)
+        if not target.ndim == 0:
+            # 2019-11-12, 1.18.0
+            warnings.warn(
+                "Non-scalar arrays for the fill value are deprecated. Use "
+                "arrays with scalar values instead. The filled function "
+                "still supports any array as `fill_value`.",
+                DeprecationWarning, stacklevel=2)
+
+        _fill_value = self._fill_value
+        if _fill_value is None:
+            # Create the attribute if it was undefined
+            self._fill_value = target
+        else:
+            # Don't overwrite the attribute, just fill it (for propagation)
+            _fill_value[()] = target
+
+    # kept for compatibility
+    get_fill_value = fill_value.fget
+    set_fill_value = fill_value.fset
+
+    def filled(self, fill_value=None):
+        """
+        Return a copy of self, with masked values filled with a given value.
+        **However**, if there are no masked values to fill, self will be
+        returned instead as an ndarray.
+
+        Parameters
+        ----------
+        fill_value : array_like, optional
+            The value to use for invalid entries. Can be scalar or non-scalar.
+            If non-scalar, the resulting ndarray must be broadcastable over
+            input array. Default is None, in which case, the `fill_value`
+            attribute of the array is used instead.
+
+        Returns
+        -------
+        filled_array : ndarray
+            A copy of ``self`` with invalid entries replaced by *fill_value*
+            (be it the function argument or the attribute of ``self``), or
+            ``self`` itself as an ndarray if there are no invalid entries to
+            be replaced.
+
+        Notes
+        -----
+        The result is **not** a MaskedArray!
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([1,2,3,4,5], mask=[0,0,1,0,1], fill_value=-999)
+        >>> x.filled()
+        array([   1,    2, -999,    4, -999])
+        >>> x.filled(fill_value=1000)
+        array([   1,    2, 1000,    4, 1000])
+        >>> type(x.filled())
+        <class 'numpy.ndarray'>
+
+        Subclassing is preserved. This means that if, e.g., the data part of
+        the masked array is a recarray, `filled` returns a recarray:
+
+        >>> x = np.array([(-1, 2), (-3, 4)], dtype='i8,i8').view(np.recarray)
+        >>> m = np.ma.array(x, mask=[(True, False), (False, True)])
+        >>> m.filled()
+        rec.array([(999999,      2), (    -3, 999999)],
+                  dtype=[('f0', '<i8'), ('f1', '<i8')])
+        """
+        m = self._mask
+        if m is nomask:
+            return self._data
+
+        if fill_value is None:
+            fill_value = self.fill_value
+        else:
+            fill_value = _check_fill_value(fill_value, self.dtype)
+
+        if self is masked_singleton:
+            return np.asanyarray(fill_value)
+
+        if m.dtype.names is not None:
+            result = self._data.copy('K')
+            _recursive_filled(result, self._mask, fill_value)
+        elif not m.any():
+            return self._data
+        else:
+            result = self._data.copy('K')
+            try:
+                np.copyto(result, fill_value, where=m)
+            except (TypeError, AttributeError):
+                fill_value = narray(fill_value, dtype=object)
+                d = result.astype(object)
+                result = np.choose(m, (d, fill_value))
+            except IndexError:
+                # ok, if scalar
+                if self._data.shape:
+                    raise
+                elif m:
+                    result = np.array(fill_value, dtype=self.dtype)
+                else:
+                    result = self._data
+        return result
+
+    def compressed(self):
+        """
+        Return all the non-masked data as a 1-D array.
+
+        Returns
+        -------
+        data : ndarray
+            A new `ndarray` holding the non-masked data is returned.
+
+        Notes
+        -----
+        The result is **not** a MaskedArray!
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array(np.arange(5), mask=[0]*2 + [1]*3)
+        >>> x.compressed()
+        array([0, 1])
+        >>> type(x.compressed())
+        <class 'numpy.ndarray'>
+
+        N-D arrays are compressed to 1-D.
+
+        >>> arr = [[1, 2], [3, 4]]
+        >>> mask = [[1, 0], [0, 1]]
+        >>> x = np.ma.array(arr, mask=mask)
+        >>> x.compressed()
+        array([2, 3])
+
+        """
+        data = ndarray.ravel(self._data)
+        if self._mask is not nomask:
+            data = data.compress(np.logical_not(ndarray.ravel(self._mask)))
+        return data
+
+    def compress(self, condition, axis=None, out=None):
+        """
+        Return `a` where condition is ``True``.
+
+        If condition is a `~ma.MaskedArray`, missing values are considered
+        as ``False``.
+
+        Parameters
+        ----------
+        condition : var
+            Boolean 1-d array selecting which entries to return. If len(condition)
+            is less than the size of a along the axis, then output is truncated
+            to length of condition array.
+        axis : {None, int}, optional
+            Axis along which the operation must be performed.
+        out : {None, ndarray}, optional
+            Alternative output array in which to place the result. It must have
+            the same shape as the expected output but the type will be cast if
+            necessary.
+
+        Returns
+        -------
+        result : MaskedArray
+            A :class:`~ma.MaskedArray` object.
+
+        Notes
+        -----
+        Please note the difference with :meth:`compressed` !
+        The output of :meth:`compress` has a mask, the output of
+        :meth:`compressed` does not.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
+        >>> x
+        masked_array(
+          data=[[1, --, 3],
+                [--, 5, --],
+                [7, --, 9]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+        >>> x.compress([1, 0, 1])
+        masked_array(data=[1, 3],
+                     mask=[False, False],
+               fill_value=999999)
+
+        >>> x.compress([1, 0, 1], axis=1)
+        masked_array(
+          data=[[1, 3],
+                [--, --],
+                [7, 9]],
+          mask=[[False, False],
+                [ True,  True],
+                [False, False]],
+          fill_value=999999)
+
+        """
+        # Get the basic components
+        (_data, _mask) = (self._data, self._mask)
+
+        # Force the condition to a regular ndarray and forget the missing
+        # values.
+        condition = np.asarray(condition)
+
+        _new = _data.compress(condition, axis=axis, out=out).view(type(self))
+        _new._update_from(self)
+        if _mask is not nomask:
+            _new._mask = _mask.compress(condition, axis=axis)
+        return _new
+
+    def _insert_masked_print(self):
+        """
+        Replace masked values with masked_print_option, casting all innermost
+        dtypes to object.
+        """
+        if masked_print_option.enabled():
+            mask = self._mask
+            if mask is nomask:
+                res = self._data
+            else:
+                # convert to object array to make filled work
+                data = self._data
+                # For big arrays, to avoid a costly conversion to the
+                # object dtype, extract the corners before the conversion.
+                print_width = (self._print_width if self.ndim > 1
+                               else self._print_width_1d)
+                for axis in range(self.ndim):
+                    if data.shape[axis] > print_width:
+                        ind = print_width // 2
+                        arr = np.split(data, (ind, -ind), axis=axis)
+                        data = np.concatenate((arr[0], arr[2]), axis=axis)
+                        arr = np.split(mask, (ind, -ind), axis=axis)
+                        mask = np.concatenate((arr[0], arr[2]), axis=axis)
+
+                rdtype = _replace_dtype_fields(self.dtype, "O")
+                res = data.astype(rdtype)
+                _recursive_printoption(res, mask, masked_print_option)
+        else:
+            res = self.filled(self.fill_value)
+        return res
+
+    def __str__(self):
+        return str(self._insert_masked_print())
+
+    def __repr__(self):
+        """
+        Literal string representation.
+
+        """
+        if self._baseclass is np.ndarray:
+            name = 'array'
+        else:
+            name = self._baseclass.__name__
+
+        # 2016-11-19: Demoted to legacy format
+        if np._core.arrayprint._get_legacy_print_mode() <= 113:
+            is_long = self.ndim > 1
+            parameters = {
+                'name': name,
+                'nlen': " " * len(name),
+                'data': str(self),
+                'mask': str(self._mask),
+                'fill': str(self.fill_value),
+                'dtype': str(self.dtype)
+            }
+            is_structured = bool(self.dtype.names)
+            key = '{}_{}'.format(
+                'long' if is_long else 'short',
+                'flx' if is_structured else 'std'
+            )
+            return _legacy_print_templates[key] % parameters
+
+        prefix = f"masked_{name}("
+
+        dtype_needed = (
+            not np._core.arrayprint.dtype_is_implied(self.dtype) or
+            np.all(self.mask) or
+            self.size == 0
+        )
+
+        # determine which keyword args need to be shown
+        keys = ['data', 'mask', 'fill_value']
+        if dtype_needed:
+            keys.append('dtype')
+
+        # array has only one row (non-column)
+        is_one_row = builtins.all(dim == 1 for dim in self.shape[:-1])
+
+        # choose what to indent each keyword with
+        min_indent = 2
+        if is_one_row:
+            # first key on the same line as the type, remaining keys
+            # aligned by equals
+            indents = {}
+            indents[keys[0]] = prefix
+            for k in keys[1:]:
+                n = builtins.max(min_indent, len(prefix + keys[0]) - len(k))
+                indents[k] = ' ' * n
+            prefix = ''  # absorbed into the first indent
+        else:
+            # each key on its own line, indented by two spaces
+            indents = dict.fromkeys(keys, ' ' * min_indent)
+            prefix = prefix + '\n'  # first key on the next line
+
+        # format the field values
+        reprs = {}
+        reprs['data'] = np.array2string(
+            self._insert_masked_print(),
+            separator=", ",
+            prefix=indents['data'] + 'data=',
+            suffix=',')
+        reprs['mask'] = np.array2string(
+            self._mask,
+            separator=", ",
+            prefix=indents['mask'] + 'mask=',
+            suffix=',')
+
+        if self._fill_value is None:
+            self.fill_value  # initialize fill_value  # noqa: B018
+
+        if (self._fill_value.dtype.kind in ("S", "U")
+                and self.dtype.kind == self._fill_value.dtype.kind):
+            # Allow strings: "N/A" has length 3 so would mismatch.
+            fill_repr = repr(self.fill_value.item())
+        elif self._fill_value.dtype == self.dtype and not self.dtype == object:
+            # Guess that it is OK to use the string as item repr.  To really
+            # fix this, it needs new logic (shared with structured scalars)
+            fill_repr = str(self.fill_value)
+        else:
+            fill_repr = repr(self.fill_value)
+
+        reprs['fill_value'] = fill_repr
+        if dtype_needed:
+            reprs['dtype'] = np._core.arrayprint.dtype_short_repr(self.dtype)
+
+        # join keys with values and indentations
+        result = ',\n'.join(
+            f'{indents[k]}{k}={reprs[k]}'
+            for k in keys
+        )
+        return prefix + result + ')'
+
+    def _delegate_binop(self, other):
+        # This emulates the logic in
+        #     private/binop_override.h:forward_binop_should_defer
+        if isinstance(other, type(self)):
+            return False
+        array_ufunc = getattr(other, "__array_ufunc__", False)
+        if array_ufunc is False:
+            other_priority = getattr(other, "__array_priority__", -1000000)
+            return self.__array_priority__ < other_priority
+        else:
+            # If array_ufunc is not None, it will be called inside the ufunc;
+            # None explicitly tells us to not call the ufunc, i.e., defer.
+            return array_ufunc is None
+
+    def _comparison(self, other, compare):
+        """Compare self with other using operator.eq or operator.ne.
+
+        When either of the elements is masked, the result is masked as well,
+        but the underlying boolean data are still set, with self and other
+        considered equal if both are masked, and unequal otherwise.
+
+        For structured arrays, all fields are combined, with masked values
+        ignored. The result is masked if all fields were masked, with self
+        and other considered equal only if both were fully masked.
+        """
+        omask = getmask(other)
+        smask = self.mask
+        mask = mask_or(smask, omask, copy=True)
+
+        odata = getdata(other)
+        if mask.dtype.names is not None:
+            # only == and != are reasonably defined for structured dtypes,
+            # so give up early for all other comparisons:
+            if compare not in (operator.eq, operator.ne):
+                return NotImplemented
+            # For possibly masked structured arrays we need to be careful,
+            # since the standard structured array comparison will use all
+            # fields, masked or not. To avoid masked fields influencing the
+            # outcome, we set all masked fields in self to other, so they'll
+            # count as equal.  To prepare, we ensure we have the right shape.
+            broadcast_shape = np.broadcast(self, odata).shape
+            sbroadcast = np.broadcast_to(self, broadcast_shape, subok=True)
+            sbroadcast._mask = mask
+            sdata = sbroadcast.filled(odata)
+            # Now take care of the mask; the merged mask should have an item
+            # masked if all fields were masked (in one and/or other).
+            mask = (mask == np.ones((), mask.dtype))
+            # Ensure we can compare masks below if other was not masked.
+            if omask is np.False_:
+                omask = np.zeros((), smask.dtype)
+
+        else:
+            # For regular arrays, just use the data as they come.
+            sdata = self.data
+
+        check = compare(sdata, odata)
+
+        if isinstance(check, (np.bool, bool)):
+            return masked if mask else check
+
+        if mask is not nomask:
+            if compare in (operator.eq, operator.ne):
+                # Adjust elements that were masked, which should be treated
+                # as equal if masked in both, unequal if masked in one.
+                # Note that this works automatically for structured arrays too.
+                # Ignore this for operations other than `==` and `!=`
+                check = np.where(mask, compare(smask, omask), check)
+
+            if mask.shape != check.shape:
+                # Guarantee consistency of the shape, making a copy since the
+                # the mask may need to get written to later.
+                mask = np.broadcast_to(mask, check.shape).copy()
+
+        check = check.view(type(self))
+        check._update_from(self)
+        check._mask = mask
+
+        # Cast fill value to np.bool if needed. If it cannot be cast, the
+        # default boolean fill value is used.
+        if check._fill_value is not None:
+            try:
+                fill = _check_fill_value(check._fill_value, np.bool)
+            except (TypeError, ValueError):
+                fill = _check_fill_value(None, np.bool)
+            check._fill_value = fill
+
+        return check
+
+    def __eq__(self, other):
+        """Check whether other equals self elementwise.
+
+        When either of the elements is masked, the result is masked as well,
+        but the underlying boolean data are still set, with self and other
+        considered equal if both are masked, and unequal otherwise.
+
+        For structured arrays, all fields are combined, with masked values
+        ignored. The result is masked if all fields were masked, with self
+        and other considered equal only if both were fully masked.
+        """
+        return self._comparison(other, operator.eq)
+
+    def __ne__(self, other):
+        """Check whether other does not equal self elementwise.
+
+        When either of the elements is masked, the result is masked as well,
+        but the underlying boolean data are still set, with self and other
+        considered equal if both are masked, and unequal otherwise.
+
+        For structured arrays, all fields are combined, with masked values
+        ignored. The result is masked if all fields were masked, with self
+        and other considered equal only if both were fully masked.
+        """
+        return self._comparison(other, operator.ne)
+
+    # All other comparisons:
+    def __le__(self, other):
+        return self._comparison(other, operator.le)
+
+    def __lt__(self, other):
+        return self._comparison(other, operator.lt)
+
+    def __ge__(self, other):
+        return self._comparison(other, operator.ge)
+
+    def __gt__(self, other):
+        return self._comparison(other, operator.gt)
+
+    def __add__(self, other):
+        """
+        Add self to other, and return a new masked array.
+
+        """
+        if self._delegate_binop(other):
+            return NotImplemented
+        return add(self, other)
+
+    def __radd__(self, other):
+        """
+        Add other to self, and return a new masked array.
+
+        """
+        # In analogy with __rsub__ and __rdiv__, use original order:
+        # we get here from `other + self`.
+        return add(other, self)
+
+    def __sub__(self, other):
+        """
+        Subtract other from self, and return a new masked array.
+
+        """
+        if self._delegate_binop(other):
+            return NotImplemented
+        return subtract(self, other)
+
+    def __rsub__(self, other):
+        """
+        Subtract self from other, and return a new masked array.
+
+        """
+        return subtract(other, self)
+
+    def __mul__(self, other):
+        "Multiply self by other, and return a new masked array."
+        if self._delegate_binop(other):
+            return NotImplemented
+        return multiply(self, other)
+
+    def __rmul__(self, other):
+        """
+        Multiply other by self, and return a new masked array.
+
+        """
+        # In analogy with __rsub__ and __rdiv__, use original order:
+        # we get here from `other * self`.
+        return multiply(other, self)
+
+    def __truediv__(self, other):
+        """
+        Divide other into self, and return a new masked array.
+
+        """
+        if self._delegate_binop(other):
+            return NotImplemented
+        return true_divide(self, other)
+
+    def __rtruediv__(self, other):
+        """
+        Divide self into other, and return a new masked array.
+
+        """
+        return true_divide(other, self)
+
+    def __floordiv__(self, other):
+        """
+        Divide other into self, and return a new masked array.
+
+        """
+        if self._delegate_binop(other):
+            return NotImplemented
+        return floor_divide(self, other)
+
+    def __rfloordiv__(self, other):
+        """
+        Divide self into other, and return a new masked array.
+
+        """
+        return floor_divide(other, self)
+
+    def __pow__(self, other):
+        """
+        Raise self to the power other, masking the potential NaNs/Infs
+
+        """
+        if self._delegate_binop(other):
+            return NotImplemented
+        return power(self, other)
+
+    def __rpow__(self, other):
+        """
+        Raise other to the power self, masking the potential NaNs/Infs
+
+        """
+        return power(other, self)
+
+    def __iadd__(self, other):
+        """
+        Add other to self in-place.
+
+        """
+        m = getmask(other)
+        if self._mask is nomask:
+            if m is not nomask and m.any():
+                self._mask = make_mask_none(self.shape, self.dtype)
+                self._mask += m
+        elif m is not nomask:
+            self._mask += m
+        other_data = getdata(other)
+        other_data = np.where(self._mask, other_data.dtype.type(0), other_data)
+        self._data.__iadd__(other_data)
+        return self
+
+    def __isub__(self, other):
+        """
+        Subtract other from self in-place.
+
+        """
+        m = getmask(other)
+        if self._mask is nomask:
+            if m is not nomask and m.any():
+                self._mask = make_mask_none(self.shape, self.dtype)
+                self._mask += m
+        elif m is not nomask:
+            self._mask += m
+        other_data = getdata(other)
+        other_data = np.where(self._mask, other_data.dtype.type(0), other_data)
+        self._data.__isub__(other_data)
+        return self
+
+    def __imul__(self, other):
+        """
+        Multiply self by other in-place.
+
+        """
+        m = getmask(other)
+        if self._mask is nomask:
+            if m is not nomask and m.any():
+                self._mask = make_mask_none(self.shape, self.dtype)
+                self._mask += m
+        elif m is not nomask:
+            self._mask += m
+        other_data = getdata(other)
+        other_data = np.where(self._mask, other_data.dtype.type(1), other_data)
+        self._data.__imul__(other_data)
+        return self
+
+    def __ifloordiv__(self, other):
+        """
+        Floor divide self by other in-place.
+
+        """
+        other_data = getdata(other)
+        dom_mask = _DomainSafeDivide().__call__(self._data, other_data)
+        other_mask = getmask(other)
+        new_mask = mask_or(other_mask, dom_mask)
+        # The following 3 lines control the domain filling
+        if dom_mask.any():
+            (_, fval) = ufunc_fills[np.floor_divide]
+            other_data = np.where(
+                    dom_mask, other_data.dtype.type(fval), other_data)
+        self._mask |= new_mask
+        other_data = np.where(self._mask, other_data.dtype.type(1), other_data)
+        self._data.__ifloordiv__(other_data)
+        return self
+
+    def __itruediv__(self, other):
+        """
+        True divide self by other in-place.
+
+        """
+        other_data = getdata(other)
+        dom_mask = _DomainSafeDivide().__call__(self._data, other_data)
+        other_mask = getmask(other)
+        new_mask = mask_or(other_mask, dom_mask)
+        # The following 3 lines control the domain filling
+        if dom_mask.any():
+            (_, fval) = ufunc_fills[np.true_divide]
+            other_data = np.where(
+                    dom_mask, other_data.dtype.type(fval), other_data)
+        self._mask |= new_mask
+        other_data = np.where(self._mask, other_data.dtype.type(1), other_data)
+        self._data.__itruediv__(other_data)
+        return self
+
+    def __ipow__(self, other):
+        """
+        Raise self to the power other, in place.
+
+        """
+        other_data = getdata(other)
+        other_data = np.where(self._mask, other_data.dtype.type(1), other_data)
+        other_mask = getmask(other)
+        with np.errstate(divide='ignore', invalid='ignore'):
+            self._data.__ipow__(other_data)
+        invalid = np.logical_not(np.isfinite(self._data))
+        if invalid.any():
+            if self._mask is not nomask:
+                self._mask |= invalid
+            else:
+                self._mask = invalid
+            np.copyto(self._data, self.fill_value, where=invalid)
+        new_mask = mask_or(other_mask, invalid)
+        self._mask = mask_or(self._mask, new_mask)
+        return self
+
+    def __float__(self):
+        """
+        Convert to float.
+
+        """
+        if self.size > 1:
+            raise TypeError("Only length-1 arrays can be converted "
+                            "to Python scalars")
+        elif self._mask:
+            warnings.warn("Warning: converting a masked element to nan.", stacklevel=2)
+            return np.nan
+        return float(self.item())
+
+    def __int__(self):
+        """
+        Convert to int.
+
+        """
+        if self.size > 1:
+            raise TypeError("Only length-1 arrays can be converted "
+                            "to Python scalars")
+        elif self._mask:
+            raise MaskError('Cannot convert masked element to a Python int.')
+        return int(self.item())
+
+    @property
+    def imag(self):
+        """
+        The imaginary part of the masked array.
+
+        This property is a view on the imaginary part of this `MaskedArray`.
+
+        See Also
+        --------
+        real
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([1+1.j, -2j, 3.45+1.6j], mask=[False, True, False])
+        >>> x.imag
+        masked_array(data=[1.0, --, 1.6],
+                     mask=[False,  True, False],
+               fill_value=1e+20)
+
+        """
+        result = self._data.imag.view(type(self))
+        result.__setmask__(self._mask)
+        return result
+
+    # kept for compatibility
+    get_imag = imag.fget
+
+    @property
+    def real(self):
+        """
+        The real part of the masked array.
+
+        This property is a view on the real part of this `MaskedArray`.
+
+        See Also
+        --------
+        imag
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([1+1.j, -2j, 3.45+1.6j], mask=[False, True, False])
+        >>> x.real
+        masked_array(data=[1.0, --, 3.45],
+                     mask=[False,  True, False],
+               fill_value=1e+20)
+
+        """
+        result = self._data.real.view(type(self))
+        result.__setmask__(self._mask)
+        return result
+
+    # kept for compatibility
+    get_real = real.fget
+
+    def count(self, axis=None, keepdims=np._NoValue):
+        """
+        Count the non-masked elements of the array along the given axis.
+
+        Parameters
+        ----------
+        axis : None or int or tuple of ints, optional
+            Axis or axes along which the count is performed.
+            The default, None, performs the count over all
+            the dimensions of the input array. `axis` may be negative, in
+            which case it counts from the last to the first axis.
+            If this is a tuple of ints, the count is performed on multiple
+            axes, instead of a single axis or all the axes as before.
+        keepdims : bool, optional
+            If this is set to True, the axes which are reduced are left
+            in the result as dimensions with size one. With this option,
+            the result will broadcast correctly against the array.
+
+        Returns
+        -------
+        result : ndarray or scalar
+            An array with the same shape as the input array, with the specified
+            axis removed. If the array is a 0-d array, or if `axis` is None, a
+            scalar is returned.
+
+        See Also
+        --------
+        ma.count_masked : Count masked elements in array or along a given axis.
+
+        Examples
+        --------
+        >>> import numpy.ma as ma
+        >>> a = ma.arange(6).reshape((2, 3))
+        >>> a[1, :] = ma.masked
+        >>> a
+        masked_array(
+          data=[[0, 1, 2],
+                [--, --, --]],
+          mask=[[False, False, False],
+                [ True,  True,  True]],
+          fill_value=999999)
+        >>> a.count()
+        3
+
+        When the `axis` keyword is specified an array of appropriate size is
+        returned.
+
+        >>> a.count(axis=0)
+        array([1, 1, 1])
+        >>> a.count(axis=1)
+        array([3, 0])
+
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        m = self._mask
+        # special case for matrices (we assume no other subclasses modify
+        # their dimensions)
+        if isinstance(self.data, np.matrix):
+            if m is nomask:
+                m = np.zeros(self.shape, dtype=np.bool)
+            m = m.view(type(self.data))
+
+        if m is nomask:
+            # compare to _count_reduce_items in _methods.py
+
+            if self.shape == ():
+                if axis not in (None, 0):
+                    raise np.exceptions.AxisError(axis=axis, ndim=self.ndim)
+                return 1
+            elif axis is None:
+                if kwargs.get('keepdims'):
+                    return np.array(self.size, dtype=np.intp, ndmin=self.ndim)
+                return self.size
+
+            axes = normalize_axis_tuple(axis, self.ndim)
+            items = 1
+            for ax in axes:
+                items *= self.shape[ax]
+
+            if kwargs.get('keepdims'):
+                out_dims = list(self.shape)
+                for a in axes:
+                    out_dims[a] = 1
+            else:
+                out_dims = [d for n, d in enumerate(self.shape)
+                            if n not in axes]
+            # make sure to return a 0-d array if axis is supplied
+            return np.full(out_dims, items, dtype=np.intp)
+
+        # take care of the masked singleton
+        if self is masked:
+            return 0
+
+        return (~m).sum(axis=axis, dtype=np.intp, **kwargs)
+
+    def ravel(self, order='C'):
+        """
+        Returns a 1D version of self, as a view.
+
+        Parameters
+        ----------
+        order : {'C', 'F', 'A', 'K'}, optional
+            The elements of `a` are read using this index order. 'C' means to
+            index the elements in C-like order, with the last axis index
+            changing fastest, back to the first axis index changing slowest.
+            'F' means to index the elements in Fortran-like index order, with
+            the first index changing fastest, and the last index changing
+            slowest. Note that the 'C' and 'F' options take no account of the
+            memory layout of the underlying array, and only refer to the order
+            of axis indexing.  'A' means to read the elements in Fortran-like
+            index order if `m` is Fortran *contiguous* in memory, C-like order
+            otherwise.  'K' means to read the elements in the order they occur
+            in memory, except for reversing the data when strides are negative.
+            By default, 'C' index order is used.
+            (Masked arrays currently use 'A' on the data when 'K' is passed.)
+
+        Returns
+        -------
+        MaskedArray
+            Output view is of shape ``(self.size,)`` (or
+            ``(np.ma.product(self.shape),)``).
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
+        >>> x
+        masked_array(
+          data=[[1, --, 3],
+                [--, 5, --],
+                [7, --, 9]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+        >>> x.ravel()
+        masked_array(data=[1, --, 3, --, 5, --, 7, --, 9],
+                     mask=[False,  True, False,  True, False,  True, False,  True,
+                           False],
+               fill_value=999999)
+
+        """
+        # The order of _data and _mask could be different (it shouldn't be
+        # normally).  Passing order `K` or `A` would be incorrect.
+        # So we ignore the mask memory order.
+        # TODO: We don't actually support K, so use A instead.  We could
+        #       try to guess this correct by sorting strides or deprecate.
+        if order in "kKaA":
+            order = "F" if self._data.flags.fnc else "C"
+        r = ndarray.ravel(self._data, order=order).view(type(self))
+        r._update_from(self)
+        if self._mask is not nomask:
+            r._mask = ndarray.ravel(self._mask, order=order).reshape(r.shape)
+        else:
+            r._mask = nomask
+        return r
+
+    def reshape(self, *s, **kwargs):
+        """
+        Give a new shape to the array without changing its data.
+
+        Returns a masked array containing the same data, but with a new shape.
+        The result is a view on the original array; if this is not possible, a
+        ValueError is raised.
+
+        Parameters
+        ----------
+        shape : int or tuple of ints
+            The new shape should be compatible with the original shape. If an
+            integer is supplied, then the result will be a 1-D array of that
+            length.
+        order : {'C', 'F'}, optional
+            Determines whether the array data should be viewed as in C
+            (row-major) or FORTRAN (column-major) order.
+
+        Returns
+        -------
+        reshaped_array : array
+            A new view on the array.
+
+        See Also
+        --------
+        reshape : Equivalent function in the masked array module.
+        numpy.ndarray.reshape : Equivalent method on ndarray object.
+        numpy.reshape : Equivalent function in the NumPy module.
+
+        Notes
+        -----
+        The reshaping operation cannot guarantee that a copy will not be made,
+        to modify the shape in place, use ``a.shape = s``
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2],[3,4]], mask=[1,0,0,1])
+        >>> x
+        masked_array(
+          data=[[--, 2],
+                [3, --]],
+          mask=[[ True, False],
+                [False,  True]],
+          fill_value=999999)
+        >>> x = x.reshape((4,1))
+        >>> x
+        masked_array(
+          data=[[--],
+                [2],
+                [3],
+                [--]],
+          mask=[[ True],
+                [False],
+                [False],
+                [ True]],
+          fill_value=999999)
+
+        """
+        result = self._data.reshape(*s, **kwargs).view(type(self))
+        result._update_from(self)
+        mask = self._mask
+        if mask is not nomask:
+            result._mask = mask.reshape(*s, **kwargs)
+        return result
+
+    def resize(self, newshape, refcheck=True, order=False):
+        """
+        .. warning::
+
+            This method does nothing, except raise a ValueError exception. A
+            masked array does not own its data and therefore cannot safely be
+            resized in place. Use the `numpy.ma.resize` function instead.
+
+        This method is difficult to implement safely and may be deprecated in
+        future releases of NumPy.
+
+        """
+        # Note : the 'order' keyword looks broken, let's just drop it
+        errmsg = "A masked array does not own its data "\
+                 "and therefore cannot be resized.\n" \
+                 "Use the numpy.ma.resize function instead."
+        raise ValueError(errmsg)
+
+    def put(self, indices, values, mode='raise'):
+        """
+        Set storage-indexed locations to corresponding values.
+
+        Sets self._data.flat[n] = values[n] for each n in indices.
+        If `values` is shorter than `indices` then it will repeat.
+        If `values` has some masked values, the initial mask is updated
+        in consequence, else the corresponding values are unmasked.
+
+        Parameters
+        ----------
+        indices : 1-D array_like
+            Target indices, interpreted as integers.
+        values : array_like
+            Values to place in self._data copy at target indices.
+        mode : {'raise', 'wrap', 'clip'}, optional
+            Specifies how out-of-bounds indices will behave.
+            'raise' : raise an error.
+            'wrap' : wrap around.
+            'clip' : clip to the range.
+
+        Notes
+        -----
+        `values` can be a scalar or length 1 array.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
+        >>> x
+        masked_array(
+          data=[[1, --, 3],
+                [--, 5, --],
+                [7, --, 9]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+        >>> x.put([0,4,8],[10,20,30])
+        >>> x
+        masked_array(
+          data=[[10, --, 3],
+                [--, 20, --],
+                [7, --, 30]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+
+        >>> x.put(4,999)
+        >>> x
+        masked_array(
+          data=[[10, --, 3],
+                [--, 999, --],
+                [7, --, 30]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+
+        """
+        # Hard mask: Get rid of the values/indices that fall on masked data
+        if self._hardmask and self._mask is not nomask:
+            mask = self._mask[indices]
+            indices = narray(indices, copy=None)
+            values = narray(values, copy=None, subok=True)
+            values.resize(indices.shape)
+            indices = indices[~mask]
+            values = values[~mask]
+
+        self._data.put(indices, values, mode=mode)
+
+        # short circuit if neither self nor values are masked
+        if self._mask is nomask and getmask(values) is nomask:
+            return
+
+        m = getmaskarray(self)
+
+        if getmask(values) is nomask:
+            m.put(indices, False, mode=mode)
+        else:
+            m.put(indices, values._mask, mode=mode)
+        m = make_mask(m, copy=False, shrink=True)
+        self._mask = m
+        return
+
+    def ids(self):
+        """
+        Return the addresses of the data and mask areas.
+
+        Parameters
+        ----------
+        None
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([1, 2, 3], mask=[0, 1, 1])
+        >>> x.ids()
+        (166670640, 166659832) # may vary
+
+        If the array has no mask, the address of `nomask` is returned. This address
+        is typically not close to the data in memory:
+
+        >>> x = np.ma.array([1, 2, 3])
+        >>> x.ids()
+        (166691080, 3083169284) # may vary
+
+        """
+        if self._mask is nomask:
+            return (self.ctypes.data, id(nomask))
+        return (self.ctypes.data, self._mask.ctypes.data)
+
+    def iscontiguous(self):
+        """
+        Return a boolean indicating whether the data is contiguous.
+
+        Parameters
+        ----------
+        None
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([1, 2, 3])
+        >>> x.iscontiguous()
+        True
+
+        `iscontiguous` returns one of the flags of the masked array:
+
+        >>> x.flags
+          C_CONTIGUOUS : True
+          F_CONTIGUOUS : True
+          OWNDATA : False
+          WRITEABLE : True
+          ALIGNED : True
+          WRITEBACKIFCOPY : False
+
+        """
+        return self.flags['CONTIGUOUS']
+
+    def all(self, axis=None, out=None, keepdims=np._NoValue):
+        """
+        Returns True if all elements evaluate to True.
+
+        The output array is masked where all the values along the given axis
+        are masked: if the output would have been a scalar and that all the
+        values are masked, then the output is `masked`.
+
+        Refer to `numpy.all` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.all : corresponding function for ndarrays
+        numpy.all : equivalent function
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> np.ma.array([1,2,3]).all()
+        True
+        >>> a = np.ma.array([1,2,3], mask=True)
+        >>> (a.all() is np.ma.masked)
+        True
+
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        mask = _check_mask_axis(self._mask, axis, **kwargs)
+        if out is None:
+            d = self.filled(True).all(axis=axis, **kwargs).view(type(self))
+            if d.ndim:
+                d.__setmask__(mask)
+            elif mask:
+                return masked
+            return d
+        self.filled(True).all(axis=axis, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            if out.ndim or mask:
+                out.__setmask__(mask)
+        return out
+
+    def any(self, axis=None, out=None, keepdims=np._NoValue):
+        """
+        Returns True if any of the elements of `a` evaluate to True.
+
+        Masked values are considered as False during computation.
+
+        Refer to `numpy.any` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.any : corresponding function for ndarrays
+        numpy.any : equivalent function
+
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        mask = _check_mask_axis(self._mask, axis, **kwargs)
+        if out is None:
+            d = self.filled(False).any(axis=axis, **kwargs).view(type(self))
+            if d.ndim:
+                d.__setmask__(mask)
+            elif mask:
+                d = masked
+            return d
+        self.filled(False).any(axis=axis, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            if out.ndim or mask:
+                out.__setmask__(mask)
+        return out
+
+    def nonzero(self):
+        """
+        Return the indices of unmasked elements that are not zero.
+
+        Returns a tuple of arrays, one for each dimension, containing the
+        indices of the non-zero elements in that dimension. The corresponding
+        non-zero values can be obtained with::
+
+            a[a.nonzero()]
+
+        To group the indices by element, rather than dimension, use
+        instead::
+
+            np.transpose(a.nonzero())
+
+        The result of this is always a 2d array, with a row for each non-zero
+        element.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        tuple_of_arrays : tuple
+            Indices of elements that are non-zero.
+
+        See Also
+        --------
+        numpy.nonzero :
+            Function operating on ndarrays.
+        flatnonzero :
+            Return indices that are non-zero in the flattened version of the input
+            array.
+        numpy.ndarray.nonzero :
+            Equivalent ndarray method.
+        count_nonzero :
+            Counts the number of non-zero elements in the input array.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> import numpy.ma as ma
+        >>> x = ma.array(np.eye(3))
+        >>> x
+        masked_array(
+          data=[[1., 0., 0.],
+                [0., 1., 0.],
+                [0., 0., 1.]],
+          mask=False,
+          fill_value=1e+20)
+        >>> x.nonzero()
+        (array([0, 1, 2]), array([0, 1, 2]))
+
+        Masked elements are ignored.
+
+        >>> x[1, 1] = ma.masked
+        >>> x
+        masked_array(
+          data=[[1.0, 0.0, 0.0],
+                [0.0, --, 0.0],
+                [0.0, 0.0, 1.0]],
+          mask=[[False, False, False],
+                [False,  True, False],
+                [False, False, False]],
+          fill_value=1e+20)
+        >>> x.nonzero()
+        (array([0, 2]), array([0, 2]))
+
+        Indices can also be grouped by element.
+
+        >>> np.transpose(x.nonzero())
+        array([[0, 0],
+               [2, 2]])
+
+        A common use for ``nonzero`` is to find the indices of an array, where
+        a condition is True.  Given an array `a`, the condition `a` > 3 is a
+        boolean array and since False is interpreted as 0, ma.nonzero(a > 3)
+        yields the indices of the `a` where the condition is true.
+
+        >>> a = ma.array([[1,2,3],[4,5,6],[7,8,9]])
+        >>> a > 3
+        masked_array(
+          data=[[False, False, False],
+                [ True,  True,  True],
+                [ True,  True,  True]],
+          mask=False,
+          fill_value=True)
+        >>> ma.nonzero(a > 3)
+        (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
+
+        The ``nonzero`` method of the condition array can also be called.
+
+        >>> (a > 3).nonzero()
+        (array([1, 1, 1, 2, 2, 2]), array([0, 1, 2, 0, 1, 2]))
+
+        """
+        return np.asarray(self.filled(0)).nonzero()
+
+    def trace(self, offset=0, axis1=0, axis2=1, dtype=None, out=None):
+        """
+        (this docstring should be overwritten)
+        """
+        # !!!: implement out + test!
+        m = self._mask
+        if m is nomask:
+            result = super().trace(offset=offset, axis1=axis1, axis2=axis2,
+                                   out=out)
+            return result.astype(dtype)
+        else:
+            D = self.diagonal(offset=offset, axis1=axis1, axis2=axis2)
+            return D.astype(dtype).filled(0).sum(axis=-1, out=out)
+    trace.__doc__ = ndarray.trace.__doc__
+
+    def dot(self, b, out=None, strict=False):
+        """
+        a.dot(b, out=None)
+
+        Masked dot product of two arrays. Note that `out` and `strict` are
+        located in different positions than in `ma.dot`. In order to
+        maintain compatibility with the functional version, it is
+        recommended that the optional arguments be treated as keyword only.
+        At some point that may be mandatory.
+
+        Parameters
+        ----------
+        b : masked_array_like
+            Inputs array.
+        out : masked_array, optional
+            Output argument. This must have the exact kind that would be
+            returned if it was not used. In particular, it must have the
+            right type, must be C-contiguous, and its dtype must be the
+            dtype that would be returned for `ma.dot(a,b)`. This is a
+            performance feature. Therefore, if these conditions are not
+            met, an exception is raised, instead of attempting to be
+            flexible.
+        strict : bool, optional
+            Whether masked data are propagated (True) or set to 0 (False)
+            for the computation. Default is False.  Propagating the mask
+            means that if a masked value appears in a row or column, the
+            whole row or column is considered masked.
+
+        See Also
+        --------
+        numpy.ma.dot : equivalent function
+
+        """
+        return dot(self, b, out=out, strict=strict)
+
+    def sum(self, axis=None, dtype=None, out=None, keepdims=np._NoValue):
+        """
+        Return the sum of the array elements over the given axis.
+
+        Masked elements are set to 0 internally.
+
+        Refer to `numpy.sum` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.sum : corresponding function for ndarrays
+        numpy.sum : equivalent function
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
+        >>> x
+        masked_array(
+          data=[[1, --, 3],
+                [--, 5, --],
+                [7, --, 9]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+        >>> x.sum()
+        25
+        >>> x.sum(axis=1)
+        masked_array(data=[4, 5, 16],
+                     mask=[False, False, False],
+               fill_value=999999)
+        >>> x.sum(axis=0)
+        masked_array(data=[8, 5, 12],
+                     mask=[False, False, False],
+               fill_value=999999)
+        >>> print(type(x.sum(axis=0, dtype=np.int64)[0]))
+        <class 'numpy.int64'>
+
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        _mask = self._mask
+        newmask = _check_mask_axis(_mask, axis, **kwargs)
+        # No explicit output
+        if out is None:
+            result = self.filled(0).sum(axis, dtype=dtype, **kwargs)
+            rndim = getattr(result, 'ndim', 0)
+            if rndim:
+                result = result.view(type(self))
+                result.__setmask__(newmask)
+            elif newmask:
+                result = masked
+            return result
+        # Explicit output
+        result = self.filled(0).sum(axis, dtype=dtype, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            outmask = getmask(out)
+            if outmask is nomask:
+                outmask = out._mask = make_mask_none(out.shape)
+            outmask.flat = newmask
+        return out
+
+    def cumsum(self, axis=None, dtype=None, out=None):
+        """
+        Return the cumulative sum of the array elements over the given axis.
+
+        Masked values are set to 0 internally during the computation.
+        However, their position is saved, and the result will be masked at
+        the same locations.
+
+        Refer to `numpy.cumsum` for full documentation.
+
+        Notes
+        -----
+        The mask is lost if `out` is not a valid :class:`ma.MaskedArray` !
+
+        Arithmetic is modular when using integer types, and no error is
+        raised on overflow.
+
+        See Also
+        --------
+        numpy.ndarray.cumsum : corresponding function for ndarrays
+        numpy.cumsum : equivalent function
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> marr = np.ma.array(np.arange(10), mask=[0,0,0,1,1,1,0,0,0,0])
+        >>> marr.cumsum()
+        masked_array(data=[0, 1, 3, --, --, --, 9, 16, 24, 33],
+                     mask=[False, False, False,  True,  True,  True, False, False,
+                           False, False],
+               fill_value=999999)
+
+        """
+        result = self.filled(0).cumsum(axis=axis, dtype=dtype, out=out)
+        if out is not None:
+            if isinstance(out, MaskedArray):
+                out.__setmask__(self.mask)
+            return out
+        result = result.view(type(self))
+        result.__setmask__(self._mask)
+        return result
+
+    def prod(self, axis=None, dtype=None, out=None, keepdims=np._NoValue):
+        """
+        Return the product of the array elements over the given axis.
+
+        Masked elements are set to 1 internally for computation.
+
+        Refer to `numpy.prod` for full documentation.
+
+        Notes
+        -----
+        Arithmetic is modular when using integer types, and no error is raised
+        on overflow.
+
+        See Also
+        --------
+        numpy.ndarray.prod : corresponding function for ndarrays
+        numpy.prod : equivalent function
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        _mask = self._mask
+        newmask = _check_mask_axis(_mask, axis, **kwargs)
+        # No explicit output
+        if out is None:
+            result = self.filled(1).prod(axis, dtype=dtype, **kwargs)
+            rndim = getattr(result, 'ndim', 0)
+            if rndim:
+                result = result.view(type(self))
+                result.__setmask__(newmask)
+            elif newmask:
+                result = masked
+            return result
+        # Explicit output
+        result = self.filled(1).prod(axis, dtype=dtype, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            outmask = getmask(out)
+            if outmask is nomask:
+                outmask = out._mask = make_mask_none(out.shape)
+            outmask.flat = newmask
+        return out
+    product = prod
+
+    def cumprod(self, axis=None, dtype=None, out=None):
+        """
+        Return the cumulative product of the array elements over the given axis.
+
+        Masked values are set to 1 internally during the computation.
+        However, their position is saved, and the result will be masked at
+        the same locations.
+
+        Refer to `numpy.cumprod` for full documentation.
+
+        Notes
+        -----
+        The mask is lost if `out` is not a valid MaskedArray !
+
+        Arithmetic is modular when using integer types, and no error is
+        raised on overflow.
+
+        See Also
+        --------
+        numpy.ndarray.cumprod : corresponding function for ndarrays
+        numpy.cumprod : equivalent function
+        """
+        result = self.filled(1).cumprod(axis=axis, dtype=dtype, out=out)
+        if out is not None:
+            if isinstance(out, MaskedArray):
+                out.__setmask__(self._mask)
+            return out
+        result = result.view(type(self))
+        result.__setmask__(self._mask)
+        return result
+
+    def mean(self, axis=None, dtype=None, out=None, keepdims=np._NoValue):
+        """
+        Returns the average of the array elements along given axis.
+
+        Masked entries are ignored, and result elements which are not
+        finite will be masked.
+
+        Refer to `numpy.mean` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.mean : corresponding function for ndarrays
+        numpy.mean : Equivalent function
+        numpy.ma.average : Weighted average.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.ma.array([1,2,3], mask=[False, False, True])
+        >>> a
+        masked_array(data=[1, 2, --],
+                     mask=[False, False,  True],
+               fill_value=999999)
+        >>> a.mean()
+        1.5
+
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+        if self._mask is nomask:
+            result = super().mean(axis=axis, dtype=dtype, **kwargs)[()]
+        else:
+            is_float16_result = False
+            if dtype is None:
+                if issubclass(self.dtype.type, (ntypes.integer, ntypes.bool)):
+                    dtype = mu.dtype('f8')
+                elif issubclass(self.dtype.type, ntypes.float16):
+                    dtype = mu.dtype('f4')
+                    is_float16_result = True
+            dsum = self.sum(axis=axis, dtype=dtype, **kwargs)
+            cnt = self.count(axis=axis, **kwargs)
+            if cnt.shape == () and (cnt == 0):
+                result = masked
+            elif is_float16_result:
+                result = self.dtype.type(dsum * 1. / cnt)
+            else:
+                result = dsum * 1. / cnt
+        if out is not None:
+            out.flat = result
+            if isinstance(out, MaskedArray):
+                outmask = getmask(out)
+                if outmask is nomask:
+                    outmask = out._mask = make_mask_none(out.shape)
+                outmask.flat = getmask(result)
+            return out
+        return result
+
+    def anom(self, axis=None, dtype=None):
+        """
+        Compute the anomalies (deviations from the arithmetic mean)
+        along the given axis.
+
+        Returns an array of anomalies, with the same shape as the input and
+        where the arithmetic mean is computed along the given axis.
+
+        Parameters
+        ----------
+        axis : int, optional
+            Axis over which the anomalies are taken.
+            The default is to use the mean of the flattened array as reference.
+        dtype : dtype, optional
+            Type to use in computing the variance. For arrays of integer type
+            the default is float32; for arrays of float types it is the same as
+            the array type.
+
+        See Also
+        --------
+        mean : Compute the mean of the array.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.ma.array([1,2,3])
+        >>> a.anom()
+        masked_array(data=[-1.,  0.,  1.],
+                     mask=False,
+               fill_value=1e+20)
+
+        """
+        m = self.mean(axis, dtype)
+        if not axis:
+            return self - m
+        else:
+            return self - expand_dims(m, axis)
+
+    def var(self, axis=None, dtype=None, out=None, ddof=0,
+            keepdims=np._NoValue, mean=np._NoValue):
+        """
+        Returns the variance of the array elements along given axis.
+
+        Masked entries are ignored, and result elements which are not
+        finite will be masked.
+
+        Refer to `numpy.var` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.var : corresponding function for ndarrays
+        numpy.var : Equivalent function
+        """
+        kwargs = {}
+
+        if keepdims is not np._NoValue:
+            kwargs['keepdims'] = keepdims
+
+        # Easy case: nomask, business as usual
+        if self._mask is nomask:
+
+            if mean is not np._NoValue:
+                kwargs['mean'] = mean
+
+            ret = super().var(axis=axis, dtype=dtype, out=out, ddof=ddof,
+                              **kwargs)[()]
+            if out is not None:
+                if isinstance(out, MaskedArray):
+                    out.__setmask__(nomask)
+                return out
+            return ret
+
+        # Some data are masked, yay!
+        cnt = self.count(axis=axis, **kwargs) - ddof
+
+        if mean is not np._NoValue:
+            danom = self - mean
+        else:
+            danom = self - self.mean(axis, dtype, keepdims=True)
+
+        if iscomplexobj(self):
+            danom = umath.absolute(danom) ** 2
+        else:
+            danom *= danom
+        dvar = divide(danom.sum(axis, **kwargs), cnt).view(type(self))
+        # Apply the mask if it's not a scalar
+        if dvar.ndim:
+            dvar._mask = mask_or(self._mask.all(axis, **kwargs), (cnt <= 0))
+            dvar._update_from(self)
+        elif getmask(dvar):
+            # Make sure that masked is returned when the scalar is masked.
+            dvar = masked
+            if out is not None:
+                if isinstance(out, MaskedArray):
+                    out.flat = 0
+                    out.__setmask__(True)
+                elif out.dtype.kind in 'biu':
+                    errmsg = "Masked data information would be lost in one or "\
+                             "more location."
+                    raise MaskError(errmsg)
+                else:
+                    out.flat = np.nan
+                return out
+        # In case with have an explicit output
+        if out is not None:
+            # Set the data
+            out.flat = dvar
+            # Set the mask if needed
+            if isinstance(out, MaskedArray):
+                out.__setmask__(dvar.mask)
+            return out
+        return dvar
+    var.__doc__ = np.var.__doc__
+
+    def std(self, axis=None, dtype=None, out=None, ddof=0,
+            keepdims=np._NoValue, mean=np._NoValue):
+        """
+        Returns the standard deviation of the array elements along given axis.
+
+        Masked entries are ignored.
+
+        Refer to `numpy.std` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.std : corresponding function for ndarrays
+        numpy.std : Equivalent function
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        dvar = self.var(axis, dtype, out, ddof, **kwargs)
+        if dvar is not masked:
+            if out is not None:
+                np.power(out, 0.5, out=out, casting='unsafe')
+                return out
+            dvar = sqrt(dvar)
+        return dvar
+
+    def round(self, decimals=0, out=None):
+        """
+        Return each element rounded to the given number of decimals.
+
+        Refer to `numpy.around` for full documentation.
+
+        See Also
+        --------
+        numpy.ndarray.round : corresponding function for ndarrays
+        numpy.around : equivalent function
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> import numpy.ma as ma
+        >>> x = ma.array([1.35, 2.5, 1.5, 1.75, 2.25, 2.75],
+        ...              mask=[0, 0, 0, 1, 0, 0])
+        >>> ma.round(x)
+        masked_array(data=[1.0, 2.0, 2.0, --, 2.0, 3.0],
+                     mask=[False, False, False,  True, False, False],
+                fill_value=1e+20)
+
+        """
+        result = self._data.round(decimals=decimals, out=out).view(type(self))
+        if result.ndim > 0:
+            result._mask = self._mask
+            result._update_from(self)
+        elif self._mask:
+            # Return masked when the scalar is masked
+            result = masked
+        # No explicit output: we're done
+        if out is None:
+            return result
+        if isinstance(out, MaskedArray):
+            out.__setmask__(self._mask)
+        return out
+
+    def argsort(self, axis=np._NoValue, kind=None, order=None, endwith=True,
+                fill_value=None, *, stable=False):
+        """
+        Return an ndarray of indices that sort the array along the
+        specified axis.  Masked values are filled beforehand to
+        `fill_value`.
+
+        Parameters
+        ----------
+        axis : int, optional
+            Axis along which to sort. If None, the default, the flattened array
+            is used.
+        kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional
+            The sorting algorithm used.
+        order : str or list of str, optional
+            When `a` is an array with fields defined, this argument specifies
+            which fields to compare first, second, etc.  Not all fields need be
+            specified.
+        endwith : {True, False}, optional
+            Whether missing values (if any) should be treated as the largest values
+            (True) or the smallest values (False)
+            When the array contains unmasked values at the same extremes of the
+            datatype, the ordering of these values and the masked values is
+            undefined.
+        fill_value : scalar or None, optional
+            Value used internally for the masked values.
+            If ``fill_value`` is not None, it supersedes ``endwith``.
+        stable : bool, optional
+            Only for compatibility with ``np.argsort``. Ignored.
+
+        Returns
+        -------
+        index_array : ndarray, int
+            Array of indices that sort `a` along the specified axis.
+            In other words, ``a[index_array]`` yields a sorted `a`.
+
+        See Also
+        --------
+        ma.MaskedArray.sort : Describes sorting algorithms used.
+        lexsort : Indirect stable sort with multiple keys.
+        numpy.ndarray.sort : Inplace sort.
+
+        Notes
+        -----
+        See `sort` for notes on the different sorting algorithms.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.ma.array([3,2,1], mask=[False, False, True])
+        >>> a
+        masked_array(data=[3, 2, --],
+                     mask=[False, False,  True],
+               fill_value=999999)
+        >>> a.argsort()
+        array([1, 0, 2])
+
+        """
+        if stable:
+            raise ValueError(
+                "`stable` parameter is not supported for masked arrays."
+            )
+
+        # 2017-04-11, Numpy 1.13.0, gh-8701: warn on axis default
+        if axis is np._NoValue:
+            axis = _deprecate_argsort_axis(self)
+
+        if fill_value is None:
+            if endwith:
+                # nan > inf
+                if np.issubdtype(self.dtype, np.floating):
+                    fill_value = np.nan
+                else:
+                    fill_value = minimum_fill_value(self)
+            else:
+                fill_value = maximum_fill_value(self)
+
+        filled = self.filled(fill_value)
+        return filled.argsort(axis=axis, kind=kind, order=order)
+
+    def argmin(self, axis=None, fill_value=None, out=None, *,
+                keepdims=np._NoValue):
+        """
+        Return array of indices to the minimum values along the given axis.
+
+        Parameters
+        ----------
+        axis : {None, integer}
+            If None, the index is into the flattened array, otherwise along
+            the specified axis
+        fill_value : scalar or None, optional
+            Value used to fill in the masked values.  If None, the output of
+            minimum_fill_value(self._data) is used instead.
+        out : {None, array}, optional
+            Array into which the result can be placed. Its type is preserved
+            and it must be of the right shape to hold the output.
+
+        Returns
+        -------
+        ndarray or scalar
+            If multi-dimension input, returns a new ndarray of indices to the
+            minimum values along the given axis.  Otherwise, returns a scalar
+            of index to the minimum values along the given axis.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array(np.arange(4), mask=[1,1,0,0])
+        >>> x.shape = (2,2)
+        >>> x
+        masked_array(
+          data=[[--, --],
+                [2, 3]],
+          mask=[[ True,  True],
+                [False, False]],
+          fill_value=999999)
+        >>> x.argmin(axis=0, fill_value=-1)
+        array([0, 0])
+        >>> x.argmin(axis=0, fill_value=9)
+        array([1, 1])
+
+        """
+        if fill_value is None:
+            fill_value = minimum_fill_value(self)
+        d = self.filled(fill_value).view(ndarray)
+        keepdims = False if keepdims is np._NoValue else bool(keepdims)
+        return d.argmin(axis, out=out, keepdims=keepdims)
+
+    def argmax(self, axis=None, fill_value=None, out=None, *,
+                keepdims=np._NoValue):
+        """
+        Returns array of indices of the maximum values along the given axis.
+        Masked values are treated as if they had the value fill_value.
+
+        Parameters
+        ----------
+        axis : {None, integer}
+            If None, the index is into the flattened array, otherwise along
+            the specified axis
+        fill_value : scalar or None, optional
+            Value used to fill in the masked values.  If None, the output of
+            maximum_fill_value(self._data) is used instead.
+        out : {None, array}, optional
+            Array into which the result can be placed. Its type is preserved
+            and it must be of the right shape to hold the output.
+
+        Returns
+        -------
+        index_array : {integer_array}
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.arange(6).reshape(2,3)
+        >>> a.argmax()
+        5
+        >>> a.argmax(0)
+        array([1, 1, 1])
+        >>> a.argmax(1)
+        array([2, 2])
+
+        """
+        if fill_value is None:
+            fill_value = maximum_fill_value(self._data)
+        d = self.filled(fill_value).view(ndarray)
+        keepdims = False if keepdims is np._NoValue else bool(keepdims)
+        return d.argmax(axis, out=out, keepdims=keepdims)
+
+    def sort(self, axis=-1, kind=None, order=None, endwith=True,
+             fill_value=None, *, stable=False):
+        """
+        Sort the array, in-place
+
+        Parameters
+        ----------
+        a : array_like
+            Array to be sorted.
+        axis : int, optional
+            Axis along which to sort. If None, the array is flattened before
+            sorting. The default is -1, which sorts along the last axis.
+        kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional
+            The sorting algorithm used.
+        order : list, optional
+            When `a` is a structured array, this argument specifies which fields
+            to compare first, second, and so on.  This list does not need to
+            include all of the fields.
+        endwith : {True, False}, optional
+            Whether missing values (if any) should be treated as the largest values
+            (True) or the smallest values (False)
+            When the array contains unmasked values sorting at the same extremes of the
+            datatype, the ordering of these values and the masked values is
+            undefined.
+        fill_value : scalar or None, optional
+            Value used internally for the masked values.
+            If ``fill_value`` is not None, it supersedes ``endwith``.
+        stable : bool, optional
+            Only for compatibility with ``np.sort``. Ignored.
+
+        See Also
+        --------
+        numpy.ndarray.sort : Method to sort an array in-place.
+        argsort : Indirect sort.
+        lexsort : Indirect stable sort on multiple keys.
+        searchsorted : Find elements in a sorted array.
+
+        Notes
+        -----
+        See ``sort`` for notes on the different sorting algorithms.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
+        >>> # Default
+        >>> a.sort()
+        >>> a
+        masked_array(data=[1, 3, 5, --, --],
+                     mask=[False, False, False,  True,  True],
+               fill_value=999999)
+
+        >>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
+        >>> # Put missing values in the front
+        >>> a.sort(endwith=False)
+        >>> a
+        masked_array(data=[--, --, 1, 3, 5],
+                     mask=[ True,  True, False, False, False],
+               fill_value=999999)
+
+        >>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
+        >>> # fill_value takes over endwith
+        >>> a.sort(endwith=False, fill_value=3)
+        >>> a
+        masked_array(data=[1, --, --, 3, 5],
+                     mask=[False,  True,  True, False, False],
+               fill_value=999999)
+
+        """
+        if stable:
+            raise ValueError(
+                "`stable` parameter is not supported for masked arrays."
+            )
+
+        if self._mask is nomask:
+            ndarray.sort(self, axis=axis, kind=kind, order=order)
+            return
+
+        if self is masked:
+            return
+
+        sidx = self.argsort(axis=axis, kind=kind, order=order,
+                            fill_value=fill_value, endwith=endwith)
+
+        self[...] = np.take_along_axis(self, sidx, axis=axis)
+
+    def min(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
+        """
+        Return the minimum along a given axis.
+
+        Parameters
+        ----------
+        axis : None or int or tuple of ints, optional
+            Axis along which to operate.  By default, ``axis`` is None and the
+            flattened input is used.
+            If this is a tuple of ints, the minimum is selected over multiple
+            axes, instead of a single axis or all the axes as before.
+        out : array_like, optional
+            Alternative output array in which to place the result.  Must be of
+            the same shape and buffer length as the expected output.
+        fill_value : scalar or None, optional
+            Value used to fill in the masked values.
+            If None, use the output of `minimum_fill_value`.
+        keepdims : bool, optional
+            If this is set to True, the axes which are reduced are left
+            in the result as dimensions with size one. With this option,
+            the result will broadcast correctly against the array.
+
+        Returns
+        -------
+        amin : array_like
+            New array holding the result.
+            If ``out`` was specified, ``out`` is returned.
+
+        See Also
+        --------
+        ma.minimum_fill_value
+            Returns the minimum filling value for a given datatype.
+
+        Examples
+        --------
+        >>> import numpy.ma as ma
+        >>> x = [[1., -2., 3.], [0.2, -0.7, 0.1]]
+        >>> mask = [[1, 1, 0], [0, 0, 1]]
+        >>> masked_x = ma.masked_array(x, mask)
+        >>> masked_x
+        masked_array(
+          data=[[--, --, 3.0],
+                [0.2, -0.7, --]],
+          mask=[[ True,  True, False],
+                [False, False,  True]],
+          fill_value=1e+20)
+        >>> ma.min(masked_x)
+        -0.7
+        >>> ma.min(masked_x, axis=-1)
+        masked_array(data=[3.0, -0.7],
+                     mask=[False, False],
+                fill_value=1e+20)
+        >>> ma.min(masked_x, axis=0, keepdims=True)
+        masked_array(data=[[0.2, -0.7, 3.0]],
+                     mask=[[False, False, False]],
+                fill_value=1e+20)
+        >>> mask = [[1, 1, 1,], [1, 1, 1]]
+        >>> masked_x = ma.masked_array(x, mask)
+        >>> ma.min(masked_x, axis=0)
+        masked_array(data=[--, --, --],
+                     mask=[ True,  True,  True],
+                fill_value=1e+20,
+                    dtype=float64)
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        _mask = self._mask
+        newmask = _check_mask_axis(_mask, axis, **kwargs)
+        if fill_value is None:
+            fill_value = minimum_fill_value(self)
+        # No explicit output
+        if out is None:
+            result = self.filled(fill_value).min(
+                axis=axis, out=out, **kwargs).view(type(self))
+            if result.ndim:
+                # Set the mask
+                result.__setmask__(newmask)
+                # Get rid of Infs
+                if newmask.ndim:
+                    np.copyto(result, result.fill_value, where=newmask)
+            elif newmask:
+                result = masked
+            return result
+        # Explicit output
+        self.filled(fill_value).min(axis=axis, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            outmask = getmask(out)
+            if outmask is nomask:
+                outmask = out._mask = make_mask_none(out.shape)
+            outmask.flat = newmask
+        else:
+            if out.dtype.kind in 'biu':
+                errmsg = "Masked data information would be lost in one or more"\
+                         " location."
+                raise MaskError(errmsg)
+            np.copyto(out, np.nan, where=newmask)
+        return out
+
+    def max(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
+        """
+        Return the maximum along a given axis.
+
+        Parameters
+        ----------
+        axis : None or int or tuple of ints, optional
+            Axis along which to operate.  By default, ``axis`` is None and the
+            flattened input is used.
+            If this is a tuple of ints, the maximum is selected over multiple
+            axes, instead of a single axis or all the axes as before.
+        out : array_like, optional
+            Alternative output array in which to place the result.  Must
+            be of the same shape and buffer length as the expected output.
+        fill_value : scalar or None, optional
+            Value used to fill in the masked values.
+            If None, use the output of maximum_fill_value().
+        keepdims : bool, optional
+            If this is set to True, the axes which are reduced are left
+            in the result as dimensions with size one. With this option,
+            the result will broadcast correctly against the array.
+
+        Returns
+        -------
+        amax : array_like
+            New array holding the result.
+            If ``out`` was specified, ``out`` is returned.
+
+        See Also
+        --------
+        ma.maximum_fill_value
+            Returns the maximum filling value for a given datatype.
+
+        Examples
+        --------
+        >>> import numpy.ma as ma
+        >>> x = [[-1., 2.5], [4., -2.], [3., 0.]]
+        >>> mask = [[0, 0], [1, 0], [1, 0]]
+        >>> masked_x = ma.masked_array(x, mask)
+        >>> masked_x
+        masked_array(
+          data=[[-1.0, 2.5],
+                [--, -2.0],
+                [--, 0.0]],
+          mask=[[False, False],
+                [ True, False],
+                [ True, False]],
+          fill_value=1e+20)
+        >>> ma.max(masked_x)
+        2.5
+        >>> ma.max(masked_x, axis=0)
+        masked_array(data=[-1.0, 2.5],
+                     mask=[False, False],
+               fill_value=1e+20)
+        >>> ma.max(masked_x, axis=1, keepdims=True)
+        masked_array(
+          data=[[2.5],
+                [-2.0],
+                [0.0]],
+          mask=[[False],
+                [False],
+                [False]],
+          fill_value=1e+20)
+        >>> mask = [[1, 1], [1, 1], [1, 1]]
+        >>> masked_x = ma.masked_array(x, mask)
+        >>> ma.max(masked_x, axis=1)
+        masked_array(data=[--, --, --],
+                     mask=[ True,  True,  True],
+               fill_value=1e+20,
+                    dtype=float64)
+        """
+        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+        _mask = self._mask
+        newmask = _check_mask_axis(_mask, axis, **kwargs)
+        if fill_value is None:
+            fill_value = maximum_fill_value(self)
+        # No explicit output
+        if out is None:
+            result = self.filled(fill_value).max(
+                axis=axis, out=out, **kwargs).view(type(self))
+            if result.ndim:
+                # Set the mask
+                result.__setmask__(newmask)
+                # Get rid of Infs
+                if newmask.ndim:
+                    np.copyto(result, result.fill_value, where=newmask)
+            elif newmask:
+                result = masked
+            return result
+        # Explicit output
+        self.filled(fill_value).max(axis=axis, out=out, **kwargs)
+        if isinstance(out, MaskedArray):
+            outmask = getmask(out)
+            if outmask is nomask:
+                outmask = out._mask = make_mask_none(out.shape)
+            outmask.flat = newmask
+        else:
+
+            if out.dtype.kind in 'biu':
+                errmsg = "Masked data information would be lost in one or more"\
+                         " location."
+                raise MaskError(errmsg)
+            np.copyto(out, np.nan, where=newmask)
+        return out
+
+    def ptp(self, axis=None, out=None, fill_value=None, keepdims=False):
+        """
+        Return (maximum - minimum) along the given dimension
+        (i.e. peak-to-peak value).
+
+        .. warning::
+            `ptp` preserves the data type of the array. This means the
+            return value for an input of signed integers with n bits
+            (e.g. `np.int8`, `np.int16`, etc) is also a signed integer
+            with n bits.  In that case, peak-to-peak values greater than
+            ``2**(n-1)-1`` will be returned as negative values. An example
+            with a work-around is shown below.
+
+        Parameters
+        ----------
+        axis : {None, int}, optional
+            Axis along which to find the peaks.  If None (default) the
+            flattened array is used.
+        out : {None, array_like}, optional
+            Alternative output array in which to place the result. It must
+            have the same shape and buffer length as the expected output
+            but the type will be cast if necessary.
+        fill_value : scalar or None, optional
+            Value used to fill in the masked values.
+        keepdims : bool, optional
+            If this is set to True, the axes which are reduced are left
+            in the result as dimensions with size one. With this option,
+            the result will broadcast correctly against the array.
+
+        Returns
+        -------
+        ptp : ndarray.
+            A new array holding the result, unless ``out`` was
+            specified, in which case a reference to ``out`` is returned.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.MaskedArray([[4, 9, 2, 10],
+        ...                        [6, 9, 7, 12]])
+
+        >>> x.ptp(axis=1)
+        masked_array(data=[8, 6],
+                     mask=False,
+               fill_value=999999)
+
+        >>> x.ptp(axis=0)
+        masked_array(data=[2, 0, 5, 2],
+                     mask=False,
+               fill_value=999999)
+
+        >>> x.ptp()
+        10
+
+        This example shows that a negative value can be returned when
+        the input is an array of signed integers.
+
+        >>> y = np.ma.MaskedArray([[1, 127],
+        ...                        [0, 127],
+        ...                        [-1, 127],
+        ...                        [-2, 127]], dtype=np.int8)
+        >>> y.ptp(axis=1)
+        masked_array(data=[ 126,  127, -128, -127],
+                     mask=False,
+               fill_value=np.int64(999999),
+                    dtype=int8)
+
+        A work-around is to use the `view()` method to view the result as
+        unsigned integers with the same bit width:
+
+        >>> y.ptp(axis=1).view(np.uint8)
+        masked_array(data=[126, 127, 128, 129],
+                     mask=False,
+               fill_value=np.uint64(999999),
+                    dtype=uint8)
+        """
+        if out is None:
+            result = self.max(axis=axis, fill_value=fill_value,
+                              keepdims=keepdims)
+            result -= self.min(axis=axis, fill_value=fill_value,
+                               keepdims=keepdims)
+            return result
+        out.flat = self.max(axis=axis, out=out, fill_value=fill_value,
+                            keepdims=keepdims)
+        min_value = self.min(axis=axis, fill_value=fill_value,
+                             keepdims=keepdims)
+        np.subtract(out, min_value, out=out, casting='unsafe')
+        return out
+
+    def partition(self, *args, **kwargs):
+        warnings.warn("Warning: 'partition' will ignore the 'mask' "
+                      f"of the {self.__class__.__name__}.",
+                      stacklevel=2)
+        return super().partition(*args, **kwargs)
+
+    def argpartition(self, *args, **kwargs):
+        warnings.warn("Warning: 'argpartition' will ignore the 'mask' "
+                      f"of the {self.__class__.__name__}.",
+                      stacklevel=2)
+        return super().argpartition(*args, **kwargs)
+
+    def take(self, indices, axis=None, out=None, mode='raise'):
+        """
+        Take elements from a masked array along an axis.
+
+        This function does the same thing as "fancy" indexing (indexing arrays
+        using arrays) for masked arrays. It can be easier to use if you need
+        elements along a given axis.
+
+        Parameters
+        ----------
+        a : masked_array
+            The source masked array.
+        indices : array_like
+            The indices of the values to extract. Also allow scalars for indices.
+        axis : int, optional
+            The axis over which to select values. By default, the flattened
+            input array is used.
+        out : MaskedArray, optional
+            If provided, the result will be placed in this array. It should
+            be of the appropriate shape and dtype. Note that `out` is always
+            buffered if `mode='raise'`; use other modes for better performance.
+        mode : {'raise', 'wrap', 'clip'}, optional
+            Specifies how out-of-bounds indices will behave.
+
+            * 'raise' -- raise an error (default)
+            * 'wrap' -- wrap around
+            * 'clip' -- clip to the range
+
+            'clip' mode means that all indices that are too large are replaced
+            by the index that addresses the last element along that axis. Note
+            that this disables indexing with negative numbers.
+
+        Returns
+        -------
+        out : MaskedArray
+            The returned array has the same type as `a`.
+
+        See Also
+        --------
+        numpy.take : Equivalent function for ndarrays.
+        compress : Take elements using a boolean mask.
+        take_along_axis : Take elements by matching the array and the index arrays.
+
+        Notes
+        -----
+        This function behaves similarly to `numpy.take`, but it handles masked
+        values. The mask is retained in the output array, and masked values
+        in the input array remain masked in the output.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> a = np.ma.array([4, 3, 5, 7, 6, 8], mask=[0, 0, 1, 0, 1, 0])
+        >>> indices = [0, 1, 4]
+        >>> np.ma.take(a, indices)
+        masked_array(data=[4, 3, --],
+                    mask=[False, False,  True],
+            fill_value=999999)
+
+        When `indices` is not one-dimensional, the output also has these dimensions:
+
+        >>> np.ma.take(a, [[0, 1], [2, 3]])
+        masked_array(data=[[4, 3],
+                        [--, 7]],
+                    mask=[[False, False],
+                        [ True, False]],
+            fill_value=999999)
+        """
+        (_data, _mask) = (self._data, self._mask)
+        cls = type(self)
+        # Make sure the indices are not masked
+        maskindices = getmask(indices)
+        if maskindices is not nomask:
+            indices = indices.filled(0)
+        # Get the data, promoting scalars to 0d arrays with [...] so that
+        # .view works correctly
+        if out is None:
+            out = _data.take(indices, axis=axis, mode=mode)[...].view(cls)
+        else:
+            np.take(_data, indices, axis=axis, mode=mode, out=out)
+        # Get the mask
+        if isinstance(out, MaskedArray):
+            if _mask is nomask:
+                outmask = maskindices
+            else:
+                outmask = _mask.take(indices, axis=axis, mode=mode)
+                outmask |= maskindices
+            out.__setmask__(outmask)
+        # demote 0d arrays back to scalars, for consistency with ndarray.take
+        return out[()]
+
+    # Array methods
+    copy = _arraymethod('copy')
+    diagonal = _arraymethod('diagonal')
+    flatten = _arraymethod('flatten')
+    repeat = _arraymethod('repeat')
+    squeeze = _arraymethod('squeeze')
+    swapaxes = _arraymethod('swapaxes')
+    T = property(fget=lambda self: self.transpose())
+    transpose = _arraymethod('transpose')
+
+    @property
+    def mT(self):
+        """
+        Return the matrix-transpose of the masked array.
+
+        The matrix transpose is the transpose of the last two dimensions, even
+        if the array is of higher dimension.
+
+        .. versionadded:: 2.0
+
+        Returns
+        -------
+        result: MaskedArray
+            The masked array with the last two dimensions transposed
+
+        Raises
+        ------
+        ValueError
+            If the array is of dimension less than 2.
+
+        See Also
+        --------
+        ndarray.mT:
+            Equivalent method for arrays
+        """
+
+        if self.ndim < 2:
+            raise ValueError("matrix transpose with ndim < 2 is undefined")
+
+        if self._mask is nomask:
+            return masked_array(data=self._data.mT)
+        else:
+            return masked_array(data=self.data.mT, mask=self.mask.mT)
+
+    def tolist(self, fill_value=None):
+        """
+        Return the data portion of the masked array as a hierarchical Python list.
+
+        Data items are converted to the nearest compatible Python type.
+        Masked values are converted to `fill_value`. If `fill_value` is None,
+        the corresponding entries in the output list will be ``None``.
+
+        Parameters
+        ----------
+        fill_value : scalar, optional
+            The value to use for invalid entries. Default is None.
+
+        Returns
+        -------
+        result : list
+            The Python list representation of the masked array.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3], [4,5,6], [7,8,9]], mask=[0] + [1,0]*4)
+        >>> x.tolist()
+        [[1, None, 3], [None, 5, None], [7, None, 9]]
+        >>> x.tolist(-999)
+        [[1, -999, 3], [-999, 5, -999], [7, -999, 9]]
+
+        """
+        _mask = self._mask
+        # No mask ? Just return .data.tolist ?
+        if _mask is nomask:
+            return self._data.tolist()
+        # Explicit fill_value: fill the array and get the list
+        if fill_value is not None:
+            return self.filled(fill_value).tolist()
+        # Structured array.
+        names = self.dtype.names
+        if names:
+            result = self._data.astype([(_, object) for _ in names])
+            for n in names:
+                result[n][_mask[n]] = None
+            return result.tolist()
+        # Standard arrays.
+        if _mask is nomask:
+            return [None]
+        # Set temps to save time when dealing w/ marrays.
+        inishape = self.shape
+        result = np.array(self._data.ravel(), dtype=object)
+        result[_mask.ravel()] = None
+        result.shape = inishape
+        return result.tolist()
+
+    def tobytes(self, fill_value=None, order='C'):
+        """
+        Return the array data as a string containing the raw bytes in the array.
+
+        The array is filled with a fill value before the string conversion.
+
+        Parameters
+        ----------
+        fill_value : scalar, optional
+            Value used to fill in the masked values. Default is None, in which
+            case `MaskedArray.fill_value` is used.
+        order : {'C','F','A'}, optional
+            Order of the data item in the copy. Default is 'C'.
+
+            - 'C'   -- C order (row major).
+            - 'F'   -- Fortran order (column major).
+            - 'A'   -- Any, current order of array.
+            - None  -- Same as 'A'.
+
+        See Also
+        --------
+        numpy.ndarray.tobytes
+        tolist, tofile
+
+        Notes
+        -----
+        As for `ndarray.tobytes`, information about the shape, dtype, etc.,
+        but also about `fill_value`, will be lost.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array(np.array([[1, 2], [3, 4]]), mask=[[0, 1], [1, 0]])
+        >>> x.tobytes()
+        b'\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00?B\\x0f\\x00\\x00\\x00\\x00\\x00?B\\x0f\\x00\\x00\\x00\\x00\\x00\\x04\\x00\\x00\\x00\\x00\\x00\\x00\\x00'
+
+        """
+        return self.filled(fill_value).tobytes(order=order)
+
+    def tofile(self, fid, sep="", format="%s"):
+        """
+        Save a masked array to a file in binary format.
+
+        .. warning::
+          This function is not implemented yet.
+
+        Raises
+        ------
+        NotImplementedError
+            When `tofile` is called.
+
+        """
+        raise NotImplementedError("MaskedArray.tofile() not implemented yet.")
+
+    def toflex(self):
+        """
+        Transforms a masked array into a flexible-type array.
+
+        The flexible type array that is returned will have two fields:
+
+        * the ``_data`` field stores the ``_data`` part of the array.
+        * the ``_mask`` field stores the ``_mask`` part of the array.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        record : ndarray
+            A new flexible-type `ndarray` with two fields: the first element
+            containing a value, the second element containing the corresponding
+            mask boolean. The returned record shape matches self.shape.
+
+        Notes
+        -----
+        A side-effect of transforming a masked array into a flexible `ndarray` is
+        that meta information (``fill_value``, ...) will be lost.
+
+        Examples
+        --------
+        >>> import numpy as np
+        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
+        >>> x
+        masked_array(
+          data=[[1, --, 3],
+                [--, 5, --],
+                [7, --, 9]],
+          mask=[[False,  True, False],
+                [ True, False,  True],
+                [False,  True, False]],
+          fill_value=999999)
+        >>> x.toflex()
+        array([[(1, False), (2,  True), (3, False)],
+               [(4,  True), (5, False), (6,  True)],
+               [(7, False), (8,  True), (9, False)]],
+              dtype=[('_data', '<i8'), ('_mask', '?')])
+
+        """
+        # Get the basic dtype.
+        ddtype = self.dtype
+        # Make sure we have a mask
+        _mask = self._mask
+        if _mask is None:
+            _mask = make_mask_none(self.shape, ddtype)
+        # And get its dtype
+        mdtype = self._mask.dtype
+
+        record = np.ndarray(shape=self.shape,
+                            dtype=[('_data', ddtype), ('_mask', mdtype)])
+        record['_data'] = self._data
+        record['_mask'] = self._mask
+        return record
+    torecords = toflex
+
+    # Pickling
+    def __getstate__(self):
+        """Return the internal state of the masked array, for pickling
+        purposes.
+
+        """
+        cf = 'CF'[self.flags.fnc]
+        data_state = super().__reduce__()[2]
+        return data_state + (getmaskarray(self).tobytes(cf), self._fill_value)
+
+    def __setstate__(self, state):
+        """Restore the internal state of the masked array, for
+        pickling purposes.  ``state`` is typically the output of the
+        ``__getstate__`` output, and is a 5-tuple:
+
+        - class name
+        - a tuple giving the shape of the data
+        - a typecode for the data
+        - a binary string for the data
+        - a binary string for the mask.
+
+        """
+        (_, shp, typ, isf, raw, msk, flv) = state
+        super().__setstate__((shp, typ, isf, raw))
+        self._mask.__setstate__((shp, make_mask_descr(typ), isf, msk))
+        self.fill_value = flv
+
+    def __reduce__(self):
+        """Return a 3-tuple for pickling a MaskedArray.
+
+        """
+        return (_mareconstruct,
+                (self.__class__, self._baseclass, (0,), 'b',),
+                self.__getstate__())
+
+    def __deepcopy__(self, memo=None):
+        from copy import deepcopy
+        copied = MaskedArray.__new__(type(self), self, copy=True)
+        if memo is None:
+            memo = {}
+        memo[id(self)] = copied
+        for (k, v) in self.__dict__.items():
+            copied.__dict__[k] = deepcopy(v, memo)
+        # as clearly documented for np.copy(), you need to use
+        # deepcopy() directly for arrays of object type that may
+        # contain compound types--you cannot depend on normal
+        # copy semantics to do the right thing here
+        if self.dtype.hasobject:
+            copied._data[...] = deepcopy(copied._data)
+        return copied
+
+
+def _mareconstruct(subtype, baseclass, baseshape, basetype,):
+    """Internal function that builds a new MaskedArray from the
+    information stored in a pickle.
+
+    """
+    _data = ndarray.__new__(baseclass, baseshape, basetype)
+    _mask = ndarray.__new__(ndarray, baseshape, make_mask_descr(basetype))
+    return subtype.__new__(subtype, _data, mask=_mask, dtype=basetype,)
+
+
+class mvoid(MaskedArray):
+    """
+    Fake a 'void' object to use for masked array with structured dtypes.
+    """
+
+    def __new__(self, data, mask=nomask, dtype=None, fill_value=None,
+                hardmask=False, copy=False, subok=True):
+        copy = None if not copy else True
+        _data = np.array(data, copy=copy, subok=subok, dtype=dtype)
+        _data = _data.view(self)
+        _data._hardmask = hardmask
+        if mask is not nomask:
+            if isinstance(mask, np.void):
+                _data._mask = mask
+            else:
+                try:
+                    # Mask is already a 0D array
+                    _data._mask = np.void(mask)
+                except TypeError:
+                    # Transform the mask to a void
+                    mdtype = make_mask_descr(dtype)
+                    _data._mask = np.array(mask, dtype=mdtype)[()]
+        if fill_value is not None:
+            _data.fill_value = fill_value
+        return _data
+
+    @property
+    def _data(self):
+        # Make sure that the _data part is a np.void
+        return super()._data[()]
+
+    def __getitem__(self, indx):
+        """
+        Get the index.
+
+        """
+        m = self._mask
+        if isinstance(m[indx], ndarray):
+            # Can happen when indx is a multi-dimensional field:
+            # A = ma.masked_array(data=[([0,1],)], mask=[([True,
+            #                     False],)], dtype=[("A", ">i2", (2,))])
+            # x = A[0]; y = x["A"]; then y.mask["A"].size==2
+            # and we can not say masked/unmasked.
+            # The result is no longer mvoid!
+            # See also issue #6724.
+            return masked_array(
+                data=self._data[indx], mask=m[indx],
+                fill_value=self._fill_value[indx],
+                hard_mask=self._hardmask)
+        if m is not nomask and m[indx]:
+            return masked
+        return self._data[indx]
+
+    def __setitem__(self, indx, value):
+        self._data[indx] = value
+        if self._hardmask:
+            self._mask[indx] |= getattr(value, "_mask", False)
+        else:
+            self._mask[indx] = getattr(value, "_mask", False)
+
+    def __str__(self):
+        m = self._mask
+        if m is nomask:
+            return str(self._data)
+
+        rdtype = _replace_dtype_fields(self._data.dtype, "O")
+        data_arr = super()._data
+        res = data_arr.astype(rdtype)
+        _recursive_printoption(res, self._mask, masked_print_option)
+        return str(res)
+
+    __repr__ = __str__
+
+    def __iter__(self):
+        "Defines an iterator for mvoid"
+        (_data, _mask) = (self._data, self._mask)
+        if _mask is nomask:
+            yield from _data
+        else:
+            for (d, m) in zip(_data, _mask):
+                if m:
+                    yield masked
+                else:
+                    yield d
+
+    def __len__(self):
+        return self._data.__len__()
+
+    def filled(self, fill_value=None):
+        """
+        Return a copy with masked fields filled with a given value.
+
+        Parameters
+        ----------
+        fill_value : array_like, optional
+            The value to use for invalid entries. Can be scalar or
+            non-scalar. If latter is the case, the filled array should
+            be broadcastable over input array. Default is None, in
+            which case the `fill_value` attribute is used instead.
+
+        Returns
+        -------
+        filled_void
+            A `np.void` object
+
+        See Also
+        --------
+        MaskedArray.filled
+
+        """
+        return asarray(self).filled(fill_value)[()]
+
+    def tolist(self):
+        """
+        Transforms the mvoid object into a tuple.
+
+        Masked fields are replaced by None.
+
+        Returns
+        -------
+        returned_tuple
+            Tuple of fields
+        """
+        _mask = self._mask
+        if _mask is nomask:
+            return self._data.tolist()
+        result = []
+        for (d, m) in zip(self._data, self._mask):
+            if m:
+                result.append(None)
+            else:
+                # .item() makes sure we return a standard Python object
+                result.append(d.item())
+        return tuple(result)
+
+
+##############################################################################
+#                                Shortcuts                                   #
+##############################################################################
+
+
+def isMaskedArray(x):
+    """
+    Test whether input is an instance of MaskedArray.
+
+    This function returns True if `x` is an instance of MaskedArray
+    and returns False otherwise.  Any object is accepted as input.
+
+    Parameters
+    ----------
+    x : object
+        Object to test.
+
+    Returns
+    -------
+    result : bool
+        True if `x` is a MaskedArray.
+
+    See Also
+    --------
+    isMA : Alias to isMaskedArray.
+    isarray : Alias to isMaskedArray.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = np.eye(3, 3)
+    >>> a
+    array([[ 1.,  0.,  0.],
+           [ 0.,  1.,  0.],
+           [ 0.,  0.,  1.]])
+    >>> m = ma.masked_values(a, 0)
+    >>> m
+    masked_array(
+      data=[[1.0, --, --],
+            [--, 1.0, --],
+            [--, --, 1.0]],
+      mask=[[False,  True,  True],
+            [ True, False,  True],
+            [ True,  True, False]],
+      fill_value=0.0)
+    >>> ma.isMaskedArray(a)
+    False
+    >>> ma.isMaskedArray(m)
+    True
+    >>> ma.isMaskedArray([0, 1, 2])
+    False
+
+    """
+    return isinstance(x, MaskedArray)
+
+
+isarray = isMaskedArray
+isMA = isMaskedArray  # backward compatibility
+
+
+class MaskedConstant(MaskedArray):
+    # the lone np.ma.masked instance
+    __singleton = None
+
+    @classmethod
+    def __has_singleton(cls):
+        # second case ensures `cls.__singleton` is not just a view on the
+        # superclass singleton
+        return cls.__singleton is not None and type(cls.__singleton) is cls
+
+    def __new__(cls):
+        if not cls.__has_singleton():
+            # We define the masked singleton as a float for higher precedence.
+            # Note that it can be tricky sometimes w/ type comparison
+            data = np.array(0.)
+            mask = np.array(True)
+
+            # prevent any modifications
+            data.flags.writeable = False
+            mask.flags.writeable = False
+
+            # don't fall back on MaskedArray.__new__(MaskedConstant), since
+            # that might confuse it - this way, the construction is entirely
+            # within our control
+            cls.__singleton = MaskedArray(data, mask=mask).view(cls)
+
+        return cls.__singleton
+
+    def __array_finalize__(self, obj):
+        if not self.__has_singleton():
+            # this handles the `.view` in __new__, which we want to copy across
+            # properties normally
+            return super().__array_finalize__(obj)
+        elif self is self.__singleton:
+            # not clear how this can happen, play it safe
+            pass
+        else:
+            # everywhere else, we want to downcast to MaskedArray, to prevent a
+            # duplicate maskedconstant.
+            self.__class__ = MaskedArray
+            MaskedArray.__array_finalize__(self, obj)
+
+    def __array_wrap__(self, obj, context=None, return_scalar=False):
+        return self.view(MaskedArray).__array_wrap__(obj, context)
+
+    def __str__(self):
+        return str(masked_print_option._display)
+
+    def __repr__(self):
+        if self is MaskedConstant.__singleton:
+            return 'masked'
+        else:
+            # it's a subclass, or something is wrong, make it obvious
+            return object.__repr__(self)
+
+    def __format__(self, format_spec):
+        # Replace ndarray.__format__ with the default, which supports no
+        # format characters.
+        # Supporting format characters is unwise here, because we do not know
+        # what type the user was expecting - better to not guess.
+        try:
+            return object.__format__(self, format_spec)
+        except TypeError:
+            # 2020-03-23, NumPy 1.19.0
+            warnings.warn(
+                "Format strings passed to MaskedConstant are ignored,"
+                " but in future may error or produce different behavior",
+                FutureWarning, stacklevel=2
+            )
+            return object.__format__(self, "")
+
+    def __reduce__(self):
+        """Override of MaskedArray's __reduce__.
+        """
+        return (self.__class__, ())
+
+    # inplace operations have no effect. We have to override them to avoid
+    # trying to modify the readonly data and mask arrays
+    def __iop__(self, other):
+        return self
+    __iadd__ = \
+    __isub__ = \
+    __imul__ = \
+    __ifloordiv__ = \
+    __itruediv__ = \
+    __ipow__ = \
+        __iop__
+    del __iop__  # don't leave this around
+
+    def copy(self, *args, **kwargs):
+        """ Copy is a no-op on the maskedconstant, as it is a scalar """
+        # maskedconstant is a scalar, so copy doesn't need to copy. There's
+        # precedent for this with `np.bool` scalars.
+        return self
+
+    def __copy__(self):
+        return self
+
+    def __deepcopy__(self, memo):
+        return self
+
+    def __setattr__(self, attr, value):
+        if not self.__has_singleton():
+            # allow the singleton to be initialized
+            return super().__setattr__(attr, value)
+        elif self is self.__singleton:
+            raise AttributeError(
+                f"attributes of {self!r} are not writeable")
+        else:
+            # duplicate instance - we can end up here from __array_finalize__,
+            # where we set the __class__ attribute
+            return super().__setattr__(attr, value)
+
+
+masked = masked_singleton = MaskedConstant()
+masked_array = MaskedArray
+
+
+def array(data, dtype=None, copy=False, order=None,
+          mask=nomask, fill_value=None, keep_mask=True,
+          hard_mask=False, shrink=True, subok=True, ndmin=0):
+    """
+    Shortcut to MaskedArray.
+
+    The options are in a different order for convenience and backwards
+    compatibility.
+
+    """
+    return MaskedArray(data, mask=mask, dtype=dtype, copy=copy,
+                       subok=subok, keep_mask=keep_mask,
+                       hard_mask=hard_mask, fill_value=fill_value,
+                       ndmin=ndmin, shrink=shrink, order=order)
+
+
+array.__doc__ = masked_array.__doc__
+
+
+def is_masked(x):
+    """
+    Determine whether input has masked values.
+
+    Accepts any object as input, but always returns False unless the
+    input is a MaskedArray containing masked values.
+
+    Parameters
+    ----------
+    x : array_like
+        Array to check for masked values.
+
+    Returns
+    -------
+    result : bool
+        True if `x` is a MaskedArray with masked values, False otherwise.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = ma.masked_equal([0, 1, 0, 2, 3], 0)
+    >>> x
+    masked_array(data=[--, 1, --, 2, 3],
+                 mask=[ True, False,  True, False, False],
+           fill_value=0)
+    >>> ma.is_masked(x)
+    True
+    >>> x = ma.masked_equal([0, 1, 0, 2, 3], 42)
+    >>> x
+    masked_array(data=[0, 1, 0, 2, 3],
+                 mask=False,
+           fill_value=42)
+    >>> ma.is_masked(x)
+    False
+
+    Always returns False if `x` isn't a MaskedArray.
+
+    >>> x = [False, True, False]
+    >>> ma.is_masked(x)
+    False
+    >>> x = 'a string'
+    >>> ma.is_masked(x)
+    False
+
+    """
+    m = getmask(x)
+    if m is nomask:
+        return False
+    elif m.any():
+        return True
+    return False
+
+
+##############################################################################
+#                             Extrema functions                              #
+##############################################################################
+
+
+class _extrema_operation(_MaskedUFunc):
+    """
+    Generic class for maximum/minimum functions.
+
+    .. note::
+      This is the base class for `_maximum_operation` and
+      `_minimum_operation`.
+
+    """
+    def __init__(self, ufunc, compare, fill_value):
+        super().__init__(ufunc)
+        self.compare = compare
+        self.fill_value_func = fill_value
+
+    def __call__(self, a, b):
+        "Executes the call behavior."
+
+        return where(self.compare(a, b), a, b)
+
+    def reduce(self, target, axis=np._NoValue):
+        "Reduce target along the given axis."
+        target = narray(target, copy=None, subok=True)
+        m = getmask(target)
+
+        if axis is np._NoValue and target.ndim > 1:
+            name = self.__name__
+            # 2017-05-06, Numpy 1.13.0: warn on axis default
+            warnings.warn(
+                f"In the future the default for ma.{name}.reduce will be axis=0, "
+                f"not the current None, to match np.{name}.reduce. "
+                "Explicitly pass 0 or None to silence this warning.",
+                MaskedArrayFutureWarning, stacklevel=2)
+            axis = None
+
+        if axis is not np._NoValue:
+            kwargs = {'axis': axis}
+        else:
+            kwargs = {}
+
+        if m is nomask:
+            t = self.f.reduce(target, **kwargs)
+        else:
+            target = target.filled(
+                self.fill_value_func(target)).view(type(target))
+            t = self.f.reduce(target, **kwargs)
+            m = umath.logical_and.reduce(m, **kwargs)
+            if hasattr(t, '_mask'):
+                t._mask = m
+            elif m:
+                t = masked
+        return t
+
+    def outer(self, a, b):
+        "Return the function applied to the outer product of a and b."
+        ma = getmask(a)
+        mb = getmask(b)
+        if ma is nomask and mb is nomask:
+            m = nomask
+        else:
+            ma = getmaskarray(a)
+            mb = getmaskarray(b)
+            m = logical_or.outer(ma, mb)
+        result = self.f.outer(filled(a), filled(b))
+        if not isinstance(result, MaskedArray):
+            result = result.view(MaskedArray)
+        result._mask = m
+        return result
+
+def min(obj, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
+    kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+    try:
+        return obj.min(axis=axis, fill_value=fill_value, out=out, **kwargs)
+    except (AttributeError, TypeError):
+        # If obj doesn't have a min method, or if the method doesn't accept a
+        # fill_value argument
+        return asanyarray(obj).min(axis=axis, fill_value=fill_value,
+                                   out=out, **kwargs)
+
+
+min.__doc__ = MaskedArray.min.__doc__
+
+def max(obj, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
+    kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+
+    try:
+        return obj.max(axis=axis, fill_value=fill_value, out=out, **kwargs)
+    except (AttributeError, TypeError):
+        # If obj doesn't have a max method, or if the method doesn't accept a
+        # fill_value argument
+        return asanyarray(obj).max(axis=axis, fill_value=fill_value,
+                                   out=out, **kwargs)
+
+
+max.__doc__ = MaskedArray.max.__doc__
+
+
+def ptp(obj, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
+    kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
+    try:
+        return obj.ptp(axis, out=out, fill_value=fill_value, **kwargs)
+    except (AttributeError, TypeError):
+        # If obj doesn't have a ptp method or if the method doesn't accept
+        # a fill_value argument
+        return asanyarray(obj).ptp(axis=axis, fill_value=fill_value,
+                                   out=out, **kwargs)
+
+
+ptp.__doc__ = MaskedArray.ptp.__doc__
+
+
+##############################################################################
+#           Definition of functions from the corresponding methods           #
+##############################################################################
+
+
+def _frommethod(methodname: str, reversed: bool = False):
+    """
+    Define functions from existing MaskedArray methods.
+
+    Parameters
+    ----------
+    methodname : str
+        Name of the method to transform.
+    reversed : bool, optional
+        Whether to reverse the first two arguments of the method. Default is False.
+    """
+    method = getattr(MaskedArray, methodname)
+    assert callable(method)
+
+    signature = inspect.signature(method)
+    params = list(signature.parameters.values())
+    params[0] = params[0].replace(name="a")  # rename 'self' to 'a'
+
+    if reversed:
+        assert len(params) >= 2
+        params[0], params[1] = params[1], params[0]
+
+        def wrapper(a, b, *args, **params):
+            return getattr(asanyarray(b), methodname)(a, *args, **params)
+
+    else:
+        def wrapper(a, *args, **params):
+            return getattr(asanyarray(a), methodname)(*args, **params)
+
+    wrapper.__signature__ = signature.replace(parameters=params)
+    wrapper.__name__ = wrapper.__qualname__ = methodname
+
+    # __doc__  is None when using `python -OO ...`
+    if method.__doc__ is not None:
+        str_signature = f"{methodname}{signature}"
+        # TODO: For methods with a docstring "Parameters" section, that do not already
+        # mention `a` (see e.g. `MaskedArray.var.__doc__`), it should be inserted there.
+        wrapper.__doc__ = f"    {str_signature}\n{method.__doc__}"
+
+    return wrapper
+
+
+all = _frommethod('all')
+anomalies = anom = _frommethod('anom')
+any = _frommethod('any')
+argmax = _frommethod('argmax')
+argmin = _frommethod('argmin')
+compress = _frommethod('compress', reversed=True)
+count = _frommethod('count')
+cumprod = _frommethod('cumprod')
+cumsum = _frommethod('cumsum')
+copy = _frommethod('copy')
+diagonal = _frommethod('diagonal')
+harden_mask = _frommethod('harden_mask')
+ids = _frommethod('ids')
+maximum = _extrema_operation(umath.maximum, greater, maximum_fill_value)
+mean = _frommethod('mean')
+minimum = _extrema_operation(umath.minimum, less, minimum_fill_value)
+nonzero = _frommethod('nonzero')
+prod = _frommethod('prod')
+product = _frommethod('product')
+ravel = _frommethod('ravel')
+repeat = _frommethod('repeat')
+shrink_mask = _frommethod('shrink_mask')
+soften_mask = _frommethod('soften_mask')
+std = _frommethod('std')
+sum = _frommethod('sum')
+swapaxes = _frommethod('swapaxes')
+#take = _frommethod('take')
+trace = _frommethod('trace')
+var = _frommethod('var')
+
+
+def take(a, indices, axis=None, out=None, mode='raise'):
+    """
+
+    """
+    a = masked_array(a)
+    return a.take(indices, axis=axis, out=out, mode=mode)
+
+
+def power(a, b, third=None):
+    """
+    Returns element-wise base array raised to power from second array.
+
+    This is the masked array version of `numpy.power`. For details see
+    `numpy.power`.
+
+    See Also
+    --------
+    numpy.power
+
+    Notes
+    -----
+    The *out* argument to `numpy.power` is not supported, `third` has to be
+    None.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [11.2, -3.973, 0.801, -1.41]
+    >>> mask = [0, 0, 0, 1]
+    >>> masked_x = ma.masked_array(x, mask)
+    >>> masked_x
+    masked_array(data=[11.2, -3.973, 0.801, --],
+             mask=[False, False, False,  True],
+       fill_value=1e+20)
+    >>> ma.power(masked_x, 2)
+    masked_array(data=[125.43999999999998, 15.784728999999999,
+                   0.6416010000000001, --],
+             mask=[False, False, False,  True],
+       fill_value=1e+20)
+    >>> y = [-0.5, 2, 0, 17]
+    >>> masked_y = ma.masked_array(y, mask)
+    >>> masked_y
+    masked_array(data=[-0.5, 2.0, 0.0, --],
+             mask=[False, False, False,  True],
+       fill_value=1e+20)
+    >>> ma.power(masked_x, masked_y)
+    masked_array(data=[0.2988071523335984, 15.784728999999999, 1.0, --],
+             mask=[False, False, False,  True],
+       fill_value=1e+20)
+
+    """
+    if third is not None:
+        raise MaskError("3-argument power not supported.")
+    # Get the masks
+    ma = getmask(a)
+    mb = getmask(b)
+    m = mask_or(ma, mb)
+    # Get the rawdata
+    fa = getdata(a)
+    fb = getdata(b)
+    # Get the type of the result (so that we preserve subclasses)
+    if isinstance(a, MaskedArray):
+        basetype = type(a)
+    else:
+        basetype = MaskedArray
+    # Get the result and view it as a (subclass of) MaskedArray
+    with np.errstate(divide='ignore', invalid='ignore'):
+        result = np.where(m, fa, umath.power(fa, fb)).view(basetype)
+    result._update_from(a)
+    # Find where we're in trouble w/ NaNs and Infs
+    invalid = np.logical_not(np.isfinite(result.view(ndarray)))
+    # Add the initial mask
+    if m is not nomask:
+        if not result.ndim:
+            return masked
+        result._mask = np.logical_or(m, invalid)
+    # Fix the invalid parts
+    if invalid.any():
+        if not result.ndim:
+            return masked
+        elif result._mask is nomask:
+            result._mask = invalid
+        result._data[invalid] = result.fill_value
+    return result
+
+
+def argsort(a, axis=np._NoValue, kind=None, order=None, endwith=True,
+            fill_value=None, *, stable=None):
+    "Function version of the eponymous method."
+    a = np.asanyarray(a)
+
+    # 2017-04-11, Numpy 1.13.0, gh-8701: warn on axis default
+    if axis is np._NoValue:
+        axis = _deprecate_argsort_axis(a)
+
+    if isinstance(a, MaskedArray):
+        return a.argsort(axis=axis, kind=kind, order=order, endwith=endwith,
+                         fill_value=fill_value, stable=None)
+    else:
+        return a.argsort(axis=axis, kind=kind, order=order, stable=None)
+
+
+argsort.__doc__ = MaskedArray.argsort.__doc__
+
+def sort(a, axis=-1, kind=None, order=None, endwith=True, fill_value=None, *,
+         stable=None):
+    """
+    Return a sorted copy of the masked array.
+
+    Equivalent to creating a copy of the array
+    and applying the  MaskedArray ``sort()`` method.
+
+    Refer to ``MaskedArray.sort`` for the full documentation
+
+    See Also
+    --------
+    MaskedArray.sort : equivalent method
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [11.2, -3.973, 0.801, -1.41]
+    >>> mask = [0, 0, 0, 1]
+    >>> masked_x = ma.masked_array(x, mask)
+    >>> masked_x
+    masked_array(data=[11.2, -3.973, 0.801, --],
+                 mask=[False, False, False,  True],
+           fill_value=1e+20)
+    >>> ma.sort(masked_x)
+    masked_array(data=[-3.973, 0.801, 11.2, --],
+                 mask=[False, False, False,  True],
+           fill_value=1e+20)
+    """
+    a = np.array(a, copy=True, subok=True)
+    if axis is None:
+        a = a.flatten()
+        axis = 0
+
+    if isinstance(a, MaskedArray):
+        a.sort(axis=axis, kind=kind, order=order, endwith=endwith,
+               fill_value=fill_value, stable=stable)
+    else:
+        a.sort(axis=axis, kind=kind, order=order, stable=stable)
+    return a
+
+
+def compressed(x):
+    """
+    Return all the non-masked data as a 1-D array.
+
+    This function is equivalent to calling the "compressed" method of a
+    `ma.MaskedArray`, see `ma.MaskedArray.compressed` for details.
+
+    See Also
+    --------
+    ma.MaskedArray.compressed : Equivalent method.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create an array with negative values masked:
+
+    >>> import numpy as np
+    >>> x = np.array([[1, -1, 0], [2, -1, 3], [7, 4, -1]])
+    >>> masked_x = np.ma.masked_array(x, mask=x < 0)
+    >>> masked_x
+    masked_array(
+      data=[[1, --, 0],
+            [2, --, 3],
+            [7, 4, --]],
+      mask=[[False,  True, False],
+            [False,  True, False],
+            [False, False,  True]],
+      fill_value=999999)
+
+    Compress the masked array into a 1-D array of non-masked values:
+
+    >>> np.ma.compressed(masked_x)
+    array([1, 0, 2, 3, 7, 4])
+
+    """
+    return asanyarray(x).compressed()
+
+
+def concatenate(arrays, axis=0):
+    """
+    Concatenate a sequence of arrays along the given axis.
+
+    Parameters
+    ----------
+    arrays : sequence of array_like
+        The arrays must have the same shape, except in the dimension
+        corresponding to `axis` (the first, by default).
+    axis : int, optional
+        The axis along which the arrays will be joined. Default is 0.
+
+    Returns
+    -------
+    result : MaskedArray
+        The concatenated array with any masked entries preserved.
+
+    See Also
+    --------
+    numpy.concatenate : Equivalent function in the top-level NumPy module.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.arange(3)
+    >>> a[1] = ma.masked
+    >>> b = ma.arange(2, 5)
+    >>> a
+    masked_array(data=[0, --, 2],
+                 mask=[False,  True, False],
+           fill_value=999999)
+    >>> b
+    masked_array(data=[2, 3, 4],
+                 mask=False,
+           fill_value=999999)
+    >>> ma.concatenate([a, b])
+    masked_array(data=[0, --, 2, 2, 3, 4],
+                 mask=[False,  True, False, False, False, False],
+           fill_value=999999)
+
+    """
+    d = np.concatenate([getdata(a) for a in arrays], axis)
+    rcls = get_masked_subclass(*arrays)
+    data = d.view(rcls)
+    # Check whether one of the arrays has a non-empty mask.
+    for x in arrays:
+        if getmask(x) is not nomask:
+            break
+    else:
+        return data
+    # OK, so we have to concatenate the masks
+    dm = np.concatenate([getmaskarray(a) for a in arrays], axis)
+    dm = dm.reshape(d.shape)
+
+    # If we decide to keep a '_shrinkmask' option, we want to check that
+    # all of them are True, and then check for dm.any()
+    data._mask = _shrink_mask(dm)
+    return data
+
+
+def diag(v, k=0):
+    """
+    Extract a diagonal or construct a diagonal array.
+
+    This function is the equivalent of `numpy.diag` that takes masked
+    values into account, see `numpy.diag` for details.
+
+    See Also
+    --------
+    numpy.diag : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+
+    Create an array with negative values masked:
+
+    >>> import numpy as np
+    >>> x = np.array([[11.2, -3.973, 18], [0.801, -1.41, 12], [7, 33, -12]])
+    >>> masked_x = np.ma.masked_array(x, mask=x < 0)
+    >>> masked_x
+    masked_array(
+      data=[[11.2, --, 18.0],
+            [0.801, --, 12.0],
+            [7.0, 33.0, --]],
+      mask=[[False,  True, False],
+            [False,  True, False],
+            [False, False,  True]],
+      fill_value=1e+20)
+
+    Isolate the main diagonal from the masked array:
+
+    >>> np.ma.diag(masked_x)
+    masked_array(data=[11.2, --, --],
+                 mask=[False,  True,  True],
+           fill_value=1e+20)
+
+    Isolate the first diagonal below the main diagonal:
+
+    >>> np.ma.diag(masked_x, -1)
+    masked_array(data=[0.801, 33.0],
+                 mask=[False, False],
+           fill_value=1e+20)
+
+    """
+    output = np.diag(v, k).view(MaskedArray)
+    if getmask(v) is not nomask:
+        output._mask = np.diag(v._mask, k)
+    return output
+
+
+def left_shift(a, n):
+    """
+    Shift the bits of an integer to the left.
+
+    This is the masked array version of `numpy.left_shift`, for details
+    see that function.
+
+    See Also
+    --------
+    numpy.left_shift
+
+    Examples
+    --------
+    Shift with a masked array:
+
+    >>> arr = np.ma.array([10, 20, 30], mask=[False, True, False])
+    >>> np.ma.left_shift(arr, 1)
+    masked_array(data=[20, --, 60],
+                 mask=[False,  True, False],
+           fill_value=999999)
+
+    Large shift:
+
+    >>> np.ma.left_shift(10, 10)
+    masked_array(data=10240,
+                 mask=False,
+           fill_value=999999)
+
+    Shift with a scalar and an array:
+
+    >>> scalar = 10
+    >>> arr = np.ma.array([1, 2, 3], mask=[False, True, False])
+    >>> np.ma.left_shift(scalar, arr)
+    masked_array(data=[20, --, 80],
+                 mask=[False,  True, False],
+           fill_value=999999)
+
+
+    """
+    m = getmask(a)
+    if m is nomask:
+        d = umath.left_shift(filled(a), n)
+        return masked_array(d)
+    else:
+        d = umath.left_shift(filled(a, 0), n)
+        return masked_array(d, mask=m)
+
+
+def right_shift(a, n):
+    """
+    Shift the bits of an integer to the right.
+
+    This is the masked array version of `numpy.right_shift`, for details
+    see that function.
+
+    See Also
+    --------
+    numpy.right_shift
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [11, 3, 8, 1]
+    >>> mask = [0, 0, 0, 1]
+    >>> masked_x = ma.masked_array(x, mask)
+    >>> masked_x
+    masked_array(data=[11, 3, 8, --],
+                 mask=[False, False, False,  True],
+           fill_value=999999)
+    >>> ma.right_shift(masked_x,1)
+    masked_array(data=[5, 1, 4, --],
+                 mask=[False, False, False,  True],
+           fill_value=999999)
+
+    """
+    m = getmask(a)
+    if m is nomask:
+        d = umath.right_shift(filled(a), n)
+        return masked_array(d)
+    else:
+        d = umath.right_shift(filled(a, 0), n)
+        return masked_array(d, mask=m)
+
+
+def put(a, indices, values, mode='raise'):
+    """
+    Set storage-indexed locations to corresponding values.
+
+    This function is equivalent to `MaskedArray.put`, see that method
+    for details.
+
+    See Also
+    --------
+    MaskedArray.put
+
+    Examples
+    --------
+    Putting values in a masked array:
+
+    >>> a = np.ma.array([1, 2, 3, 4], mask=[False, True, False, False])
+    >>> np.ma.put(a, [1, 3], [10, 30])
+    >>> a
+    masked_array(data=[ 1, 10,  3, 30],
+                 mask=False,
+           fill_value=999999)
+
+    Using put with a 2D array:
+
+    >>> b = np.ma.array([[1, 2], [3, 4]], mask=[[False, True], [False, False]])
+    >>> np.ma.put(b, [[0, 1], [1, 0]], [[10, 20], [30, 40]])
+    >>> b
+    masked_array(
+      data=[[40, 30],
+            [ 3,  4]],
+      mask=False,
+      fill_value=999999)
+
+    """
+    # We can't use 'frommethod', the order of arguments is different
+    try:
+        return a.put(indices, values, mode=mode)
+    except AttributeError:
+        return np.asarray(a).put(indices, values, mode=mode)
+
+
+def putmask(a, mask, values):  # , mode='raise'):
+    """
+    Changes elements of an array based on conditional and input values.
+
+    This is the masked array version of `numpy.putmask`, for details see
+    `numpy.putmask`.
+
+    See Also
+    --------
+    numpy.putmask
+
+    Notes
+    -----
+    Using a masked array as `values` will **not** transform a `ndarray` into
+    a `MaskedArray`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = [[1, 2], [3, 4]]
+    >>> mask = [[1, 0], [0, 0]]
+    >>> x = np.ma.array(arr, mask=mask)
+    >>> np.ma.putmask(x, x < 4, 10*x)
+    >>> x
+    masked_array(
+      data=[[--, 20],
+            [30, 4]],
+      mask=[[ True, False],
+            [False, False]],
+      fill_value=999999)
+    >>> x.data
+    array([[10, 20],
+           [30,  4]])
+
+    """
+    # We can't use 'frommethod', the order of arguments is different
+    if not isinstance(a, MaskedArray):
+        a = a.view(MaskedArray)
+    (valdata, valmask) = (getdata(values), getmask(values))
+    if getmask(a) is nomask:
+        if valmask is not nomask:
+            a._sharedmask = True
+            a._mask = make_mask_none(a.shape, a.dtype)
+            np.copyto(a._mask, valmask, where=mask)
+    elif a._hardmask:
+        if valmask is not nomask:
+            m = a._mask.copy()
+            np.copyto(m, valmask, where=mask)
+            a.mask |= m
+    else:
+        if valmask is nomask:
+            valmask = getmaskarray(values)
+        np.copyto(a._mask, valmask, where=mask)
+    np.copyto(a._data, valdata, where=mask)
+
+
+def transpose(a, axes=None):
+    """
+    Permute the dimensions of an array.
+
+    This function is exactly equivalent to `numpy.transpose`.
+
+    See Also
+    --------
+    numpy.transpose : Equivalent function in top-level NumPy module.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = ma.arange(4).reshape((2,2))
+    >>> x[1, 1] = ma.masked
+    >>> x
+    masked_array(
+      data=[[0, 1],
+            [2, --]],
+      mask=[[False, False],
+            [False,  True]],
+      fill_value=999999)
+
+    >>> ma.transpose(x)
+    masked_array(
+      data=[[0, 2],
+            [1, --]],
+      mask=[[False, False],
+            [False,  True]],
+      fill_value=999999)
+    """
+    # We can't use 'frommethod', as 'transpose' doesn't take keywords
+    try:
+        return a.transpose(axes)
+    except AttributeError:
+        return np.asarray(a).transpose(axes).view(MaskedArray)
+
+
+def reshape(a, new_shape, order='C'):
+    """
+    Returns an array containing the same data with a new shape.
+
+    Refer to `MaskedArray.reshape` for full documentation.
+
+    See Also
+    --------
+    MaskedArray.reshape : equivalent function
+
+    Examples
+    --------
+    Reshaping a 1-D array:
+
+    >>> a = np.ma.array([1, 2, 3, 4])
+    >>> np.ma.reshape(a, (2, 2))
+    masked_array(
+      data=[[1, 2],
+            [3, 4]],
+      mask=False,
+      fill_value=999999)
+
+    Reshaping a 2-D array:
+
+    >>> b = np.ma.array([[1, 2], [3, 4]])
+    >>> np.ma.reshape(b, (1, 4))
+    masked_array(data=[[1, 2, 3, 4]],
+                 mask=False,
+           fill_value=999999)
+
+    Reshaping a 1-D array with a mask:
+
+    >>> c = np.ma.array([1, 2, 3, 4], mask=[False, True, False, False])
+    >>> np.ma.reshape(c, (2, 2))
+    masked_array(
+      data=[[1, --],
+            [3, 4]],
+      mask=[[False,  True],
+            [False, False]],
+      fill_value=999999)
+
+    """
+    # We can't use 'frommethod', it whine about some parameters. Dmmit.
+    try:
+        return a.reshape(new_shape, order=order)
+    except AttributeError:
+        _tmp = np.asarray(a).reshape(new_shape, order=order)
+        return _tmp.view(MaskedArray)
+
+
+def resize(x, new_shape):
+    """
+    Return a new masked array with the specified size and shape.
+
+    This is the masked equivalent of the `numpy.resize` function. The new
+    array is filled with repeated copies of `x` (in the order that the
+    data are stored in memory). If `x` is masked, the new array will be
+    masked, and the new mask will be a repetition of the old one.
+
+    See Also
+    --------
+    numpy.resize : Equivalent function in the top level NumPy module.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.array([[1, 2] ,[3, 4]])
+    >>> a[0, 1] = ma.masked
+    >>> a
+    masked_array(
+      data=[[1, --],
+            [3, 4]],
+      mask=[[False,  True],
+            [False, False]],
+      fill_value=999999)
+    >>> np.resize(a, (3, 3))
+    masked_array(
+      data=[[1, 2, 3],
+            [4, 1, 2],
+            [3, 4, 1]],
+      mask=False,
+      fill_value=999999)
+    >>> ma.resize(a, (3, 3))
+    masked_array(
+      data=[[1, --, 3],
+            [4, 1, --],
+            [3, 4, 1]],
+      mask=[[False,  True, False],
+            [False, False,  True],
+            [False, False, False]],
+      fill_value=999999)
+
+    A MaskedArray is always returned, regardless of the input type.
+
+    >>> a = np.array([[1, 2] ,[3, 4]])
+    >>> ma.resize(a, (3, 3))
+    masked_array(
+      data=[[1, 2, 3],
+            [4, 1, 2],
+            [3, 4, 1]],
+      mask=False,
+      fill_value=999999)
+
+    """
+    # We can't use _frommethods here, as N.resize is notoriously whiny.
+    m = getmask(x)
+    if m is not nomask:
+        m = np.resize(m, new_shape)
+    result = np.resize(x, new_shape).view(get_masked_subclass(x))
+    if result.ndim:
+        result._mask = m
+    return result
+
+
+def ndim(obj):
+    """
+    maskedarray version of the numpy function.
+
+    """
+    return np.ndim(getdata(obj))
+
+
+ndim.__doc__ = np.ndim.__doc__
+
+
+def shape(obj):
+    "maskedarray version of the numpy function."
+    return np.shape(getdata(obj))
+
+
+shape.__doc__ = np.shape.__doc__
+
+
+def size(obj, axis=None):
+    "maskedarray version of the numpy function."
+    return np.size(getdata(obj), axis)
+
+
+size.__doc__ = np.size.__doc__
+
+
+def diff(a, /, n=1, axis=-1, prepend=np._NoValue, append=np._NoValue):
+    """
+    Calculate the n-th discrete difference along the given axis.
+    The first difference is given by ``out[i] = a[i+1] - a[i]`` along
+    the given axis, higher differences are calculated by using `diff`
+    recursively.
+    Preserves the input mask.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array
+    n : int, optional
+        The number of times values are differenced. If zero, the input
+        is returned as-is.
+    axis : int, optional
+        The axis along which the difference is taken, default is the
+        last axis.
+    prepend, append : array_like, optional
+        Values to prepend or append to `a` along axis prior to
+        performing the difference.  Scalar values are expanded to
+        arrays with length 1 in the direction of axis and the shape
+        of the input array in along all other axes.  Otherwise the
+        dimension and shape must match `a` except along axis.
+
+    Returns
+    -------
+    diff : MaskedArray
+        The n-th differences. The shape of the output is the same as `a`
+        except along `axis` where the dimension is smaller by `n`. The
+        type of the output is the same as the type of the difference
+        between any two elements of `a`. This is the same as the type of
+        `a` in most cases. A notable exception is `datetime64`, which
+        results in a `timedelta64` output array.
+
+    See Also
+    --------
+    numpy.diff : Equivalent function in the top-level NumPy module.
+
+    Notes
+    -----
+    Type is preserved for boolean arrays, so the result will contain
+    `False` when consecutive elements are the same and `True` when they
+    differ.
+
+    For unsigned integer arrays, the results will also be unsigned. This
+    should not be surprising, as the result is consistent with
+    calculating the difference directly:
+
+    >>> u8_arr = np.array([1, 0], dtype=np.uint8)
+    >>> np.ma.diff(u8_arr)
+    masked_array(data=[255],
+                 mask=False,
+           fill_value=np.uint64(999999),
+                dtype=uint8)
+    >>> u8_arr[1,...] - u8_arr[0,...]
+    np.uint8(255)
+
+    If this is not desirable, then the array should be cast to a larger
+    integer type first:
+
+    >>> i16_arr = u8_arr.astype(np.int16)
+    >>> np.ma.diff(i16_arr)
+    masked_array(data=[-1],
+                 mask=False,
+           fill_value=np.int64(999999),
+                dtype=int16)
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.array([1, 2, 3, 4, 7, 0, 2, 3])
+    >>> x = np.ma.masked_where(a < 2, a)
+    >>> np.ma.diff(x)
+    masked_array(data=[--, 1, 1, 3, --, --, 1],
+            mask=[ True, False, False, False,  True,  True, False],
+        fill_value=999999)
+
+    >>> np.ma.diff(x, n=2)
+    masked_array(data=[--, 0, 2, --, --, --],
+                mask=[ True, False, False,  True,  True,  True],
+        fill_value=999999)
+
+    >>> a = np.array([[1, 3, 1, 5, 10], [0, 1, 5, 6, 8]])
+    >>> x = np.ma.masked_equal(a, value=1)
+    >>> np.ma.diff(x)
+    masked_array(
+        data=[[--, --, --, 5],
+                [--, --, 1, 2]],
+        mask=[[ True,  True,  True, False],
+                [ True,  True, False, False]],
+        fill_value=1)
+
+    >>> np.ma.diff(x, axis=0)
+    masked_array(data=[[--, --, --, 1, -2]],
+            mask=[[ True,  True,  True, False, False]],
+        fill_value=1)
+
+    """
+    if n == 0:
+        return a
+    if n < 0:
+        raise ValueError("order must be non-negative but got " + repr(n))
+
+    a = np.ma.asanyarray(a)
+    if a.ndim == 0:
+        raise ValueError(
+            "diff requires input that is at least one dimensional"
+            )
+
+    combined = []
+    if prepend is not np._NoValue:
+        prepend = np.ma.asanyarray(prepend)
+        if prepend.ndim == 0:
+            shape = list(a.shape)
+            shape[axis] = 1
+            prepend = np.broadcast_to(prepend, tuple(shape))
+        combined.append(prepend)
+
+    combined.append(a)
+
+    if append is not np._NoValue:
+        append = np.ma.asanyarray(append)
+        if append.ndim == 0:
+            shape = list(a.shape)
+            shape[axis] = 1
+            append = np.broadcast_to(append, tuple(shape))
+        combined.append(append)
+
+    if len(combined) > 1:
+        a = np.ma.concatenate(combined, axis)
+
+    # GH 22465 np.diff without prepend/append preserves the mask
+    return np.diff(a, n, axis)
+
+
+##############################################################################
+#                            Extra functions                                 #
+##############################################################################
+
+
+def where(condition, x=_NoValue, y=_NoValue):
+    """
+    Return a masked array with elements from `x` or `y`, depending on condition.
+
+    .. note::
+        When only `condition` is provided, this function is identical to
+        `nonzero`. The rest of this documentation covers only the case where
+        all three arguments are provided.
+
+    Parameters
+    ----------
+    condition : array_like, bool
+        Where True, yield `x`, otherwise yield `y`.
+    x, y : array_like, optional
+        Values from which to choose. `x`, `y` and `condition` need to be
+        broadcastable to some shape.
+
+    Returns
+    -------
+    out : MaskedArray
+        An masked array with `masked` elements where the condition is masked,
+        elements from `x` where `condition` is True, and elements from `y`
+        elsewhere.
+
+    See Also
+    --------
+    numpy.where : Equivalent function in the top-level NumPy module.
+    nonzero : The function that is called when x and y are omitted
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array(np.arange(9.).reshape(3, 3), mask=[[0, 1, 0],
+    ...                                                    [1, 0, 1],
+    ...                                                    [0, 1, 0]])
+    >>> x
+    masked_array(
+      data=[[0.0, --, 2.0],
+            [--, 4.0, --],
+            [6.0, --, 8.0]],
+      mask=[[False,  True, False],
+            [ True, False,  True],
+            [False,  True, False]],
+      fill_value=1e+20)
+    >>> np.ma.where(x > 5, x, -3.1416)
+    masked_array(
+      data=[[-3.1416, --, -3.1416],
+            [--, -3.1416, --],
+            [6.0, --, 8.0]],
+      mask=[[False,  True, False],
+            [ True, False,  True],
+            [False,  True, False]],
+      fill_value=1e+20)
+
+    """
+
+    # handle the single-argument case
+    missing = (x is _NoValue, y is _NoValue).count(True)
+    if missing == 1:
+        raise ValueError("Must provide both 'x' and 'y' or neither.")
+    if missing == 2:
+        return nonzero(condition)
+
+    # we only care if the condition is true - false or masked pick y
+    cf = filled(condition, False)
+    xd = getdata(x)
+    yd = getdata(y)
+
+    # we need the full arrays here for correct final dimensions
+    cm = getmaskarray(condition)
+    xm = getmaskarray(x)
+    ym = getmaskarray(y)
+
+    # deal with the fact that masked.dtype == float64, but we don't actually
+    # want to treat it as that.
+    if x is masked and y is not masked:
+        xd = np.zeros((), dtype=yd.dtype)
+        xm = np.ones((),  dtype=ym.dtype)
+    elif y is masked and x is not masked:
+        yd = np.zeros((), dtype=xd.dtype)
+        ym = np.ones((),  dtype=xm.dtype)
+
+    data = np.where(cf, xd, yd)
+    mask = np.where(cf, xm, ym)
+    mask = np.where(cm, np.ones((), dtype=mask.dtype), mask)
+
+    # collapse the mask, for backwards compatibility
+    mask = _shrink_mask(mask)
+
+    return masked_array(data, mask=mask)
+
+
+def choose(indices, choices, out=None, mode='raise'):
+    """
+    Use an index array to construct a new array from a list of choices.
+
+    Given an array of integers and a list of n choice arrays, this method
+    will create a new array that merges each of the choice arrays.  Where a
+    value in `index` is i, the new array will have the value that choices[i]
+    contains in the same place.
+
+    Parameters
+    ----------
+    indices : ndarray of ints
+        This array must contain integers in ``[0, n-1]``, where n is the
+        number of choices.
+    choices : sequence of arrays
+        Choice arrays. The index array and all of the choices should be
+        broadcastable to the same shape.
+    out : array, optional
+        If provided, the result will be inserted into this array. It should
+        be of the appropriate shape and `dtype`.
+    mode : {'raise', 'wrap', 'clip'}, optional
+        Specifies how out-of-bounds indices will behave.
+
+        * 'raise' : raise an error
+        * 'wrap' : wrap around
+        * 'clip' : clip to the range
+
+    Returns
+    -------
+    merged_array : array
+
+    See Also
+    --------
+    choose : equivalent function
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> choice = np.array([[1,1,1], [2,2,2], [3,3,3]])
+    >>> a = np.array([2, 1, 0])
+    >>> np.ma.choose(a, choice)
+    masked_array(data=[3, 2, 1],
+                 mask=False,
+           fill_value=999999)
+
+    """
+    def fmask(x):
+        "Returns the filled array, or True if masked."
+        if x is masked:
+            return True
+        return filled(x)
+
+    def nmask(x):
+        "Returns the mask, True if ``masked``, False if ``nomask``."
+        if x is masked:
+            return True
+        return getmask(x)
+    # Get the indices.
+    c = filled(indices, 0)
+    # Get the masks.
+    masks = [nmask(x) for x in choices]
+    data = [fmask(x) for x in choices]
+    # Construct the mask
+    outputmask = np.choose(c, masks, mode=mode)
+    outputmask = make_mask(mask_or(outputmask, getmask(indices)),
+                           copy=False, shrink=True)
+    # Get the choices.
+    d = np.choose(c, data, mode=mode, out=out).view(MaskedArray)
+    if out is not None:
+        if isinstance(out, MaskedArray):
+            out.__setmask__(outputmask)
+        return out
+    d.__setmask__(outputmask)
+    return d
+
+
+def round_(a, decimals=0, out=None):
+    """
+    Return a copy of a, rounded to 'decimals' places.
+
+    When 'decimals' is negative, it specifies the number of positions
+    to the left of the decimal point.  The real and imaginary parts of
+    complex numbers are rounded separately. Nothing is done if the
+    array is not of float type and 'decimals' is greater than or equal
+    to 0.
+
+    Parameters
+    ----------
+    decimals : int
+        Number of decimals to round to. May be negative.
+    out : array_like
+        Existing array to use for output.
+        If not given, returns a default copy of a.
+
+    Notes
+    -----
+    If out is given and does not have a mask attribute, the mask of a
+    is lost!
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> x = [11.2, -3.973, 0.801, -1.41]
+    >>> mask = [0, 0, 0, 1]
+    >>> masked_x = ma.masked_array(x, mask)
+    >>> masked_x
+    masked_array(data=[11.2, -3.973, 0.801, --],
+                 mask=[False, False, False, True],
+        fill_value=1e+20)
+    >>> ma.round_(masked_x)
+    masked_array(data=[11.0, -4.0, 1.0, --],
+                 mask=[False, False, False, True],
+        fill_value=1e+20)
+    >>> ma.round(masked_x, decimals=1)
+    masked_array(data=[11.2, -4.0, 0.8, --],
+                 mask=[False, False, False, True],
+        fill_value=1e+20)
+    >>> ma.round_(masked_x, decimals=-1)
+    masked_array(data=[10.0, -0.0, 0.0, --],
+                 mask=[False, False, False, True],
+        fill_value=1e+20)
+    """
+    if out is None:
+        return np.round(a, decimals, out)
+    else:
+        np.round(getdata(a), decimals, out)
+        if hasattr(out, '_mask'):
+            out._mask = getmask(a)
+        return out
+
+
+round = round_
+
+
+def _mask_propagate(a, axis):
+    """
+    Mask whole 1-d vectors of an array that contain masked values.
+    """
+    a = array(a, subok=False)
+    m = getmask(a)
+    if m is nomask or not m.any() or axis is None:
+        return a
+    a._mask = a._mask.copy()
+    axes = normalize_axis_tuple(axis, a.ndim)
+    for ax in axes:
+        a._mask |= m.any(axis=ax, keepdims=True)
+    return a
+
+
+# Include masked dot here to avoid import problems in getting it from
+# extras.py. Note that it is not included in __all__, but rather exported
+# from extras in order to avoid backward compatibility problems.
+def dot(a, b, strict=False, out=None):
+    """
+    Return the dot product of two arrays.
+
+    This function is the equivalent of `numpy.dot` that takes masked values
+    into account. Note that `strict` and `out` are in different position
+    than in the method version. In order to maintain compatibility with the
+    corresponding method, it is recommended that the optional arguments be
+    treated as keyword only.  At some point that may be mandatory.
+
+    Parameters
+    ----------
+    a, b : masked_array_like
+        Inputs arrays.
+    strict : bool, optional
+        Whether masked data are propagated (True) or set to 0 (False) for
+        the computation. Default is False.  Propagating the mask means that
+        if a masked value appears in a row or column, the whole row or
+        column is considered masked.
+    out : masked_array, optional
+        Output argument. This must have the exact kind that would be returned
+        if it was not used. In particular, it must have the right type, must be
+        C-contiguous, and its dtype must be the dtype that would be returned
+        for `dot(a,b)`. This is a performance feature. Therefore, if these
+        conditions are not met, an exception is raised, instead of attempting
+        to be flexible.
+
+    See Also
+    --------
+    numpy.dot : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array([[1, 2, 3], [4, 5, 6]], mask=[[1, 0, 0], [0, 0, 0]])
+    >>> b = np.ma.array([[1, 2], [3, 4], [5, 6]], mask=[[1, 0], [0, 0], [0, 0]])
+    >>> np.ma.dot(a, b)
+    masked_array(
+      data=[[21, 26],
+            [45, 64]],
+      mask=[[False, False],
+            [False, False]],
+      fill_value=999999)
+    >>> np.ma.dot(a, b, strict=True)
+    masked_array(
+      data=[[--, --],
+            [--, 64]],
+      mask=[[ True,  True],
+            [ True, False]],
+      fill_value=999999)
+
+    """
+    if strict is True:
+        if np.ndim(a) == 0 or np.ndim(b) == 0:
+            pass
+        elif b.ndim == 1:
+            a = _mask_propagate(a, a.ndim - 1)
+            b = _mask_propagate(b, b.ndim - 1)
+        else:
+            a = _mask_propagate(a, a.ndim - 1)
+            b = _mask_propagate(b, b.ndim - 2)
+    am = ~getmaskarray(a)
+    bm = ~getmaskarray(b)
+
+    if out is None:
+        d = np.dot(filled(a, 0), filled(b, 0))
+        m = ~np.dot(am, bm)
+        if np.ndim(d) == 0:
+            d = np.asarray(d)
+        r = d.view(get_masked_subclass(a, b))
+        r.__setmask__(m)
+        return r
+    else:
+        d = np.dot(filled(a, 0), filled(b, 0), out._data)
+        if out.mask.shape != d.shape:
+            out._mask = np.empty(d.shape, MaskType)
+        np.dot(am, bm, out._mask)
+        np.logical_not(out._mask, out._mask)
+        return out
+
+
+def inner(a, b):
+    """
+    Returns the inner product of a and b for arrays of floating point types.
+
+    Like the generic NumPy equivalent the product sum is over the last dimension
+    of a and b. The first argument is not conjugated.
+
+    """
+    fa = filled(a, 0)
+    fb = filled(b, 0)
+    if fa.ndim == 0:
+        fa.shape = (1,)
+    if fb.ndim == 0:
+        fb.shape = (1,)
+    return np.inner(fa, fb).view(MaskedArray)
+
+
+inner.__doc__ = doc_note(np.inner.__doc__,
+                         "Masked values are replaced by 0.")
+innerproduct = inner
+
+
+def outer(a, b):
+    "maskedarray version of the numpy function."
+    fa = filled(a, 0).ravel()
+    fb = filled(b, 0).ravel()
+    d = np.outer(fa, fb)
+    ma = getmask(a)
+    mb = getmask(b)
+    if ma is nomask and mb is nomask:
+        return masked_array(d)
+    ma = getmaskarray(a)
+    mb = getmaskarray(b)
+    m = make_mask(1 - np.outer(1 - ma, 1 - mb), copy=False)
+    return masked_array(d, mask=m)
+
+
+outer.__doc__ = doc_note(np.outer.__doc__,
+                         "Masked values are replaced by 0.")
+outerproduct = outer
+
+
+def _convolve_or_correlate(f, a, v, mode, propagate_mask):
+    """
+    Helper function for ma.correlate and ma.convolve
+    """
+    if propagate_mask:
+        # results which are contributed to by either item in any pair being invalid
+        mask = (
+            f(getmaskarray(a), np.ones(np.shape(v), dtype=bool), mode=mode)
+          | f(np.ones(np.shape(a), dtype=bool), getmaskarray(v), mode=mode)
+        )
+        data = f(getdata(a), getdata(v), mode=mode)
+    else:
+        # results which are not contributed to by any pair of valid elements
+        mask = ~f(~getmaskarray(a), ~getmaskarray(v), mode=mode)
+        data = f(filled(a, 0), filled(v, 0), mode=mode)
+
+    return masked_array(data, mask=mask)
+
+
+def correlate(a, v, mode='valid', propagate_mask=True):
+    """
+    Cross-correlation of two 1-dimensional sequences.
+
+    Parameters
+    ----------
+    a, v : array_like
+        Input sequences.
+    mode : {'valid', 'same', 'full'}, optional
+        Refer to the `np.convolve` docstring.  Note that the default
+        is 'valid', unlike `convolve`, which uses 'full'.
+    propagate_mask : bool
+        If True, then a result element is masked if any masked element contributes
+        towards it. If False, then a result element is only masked if no non-masked
+        element contribute towards it
+
+    Returns
+    -------
+    out : MaskedArray
+        Discrete cross-correlation of `a` and `v`.
+
+    See Also
+    --------
+    numpy.correlate : Equivalent function in the top-level NumPy module.
+
+    Examples
+    --------
+    Basic correlation:
+
+    >>> a = np.ma.array([1, 2, 3])
+    >>> v = np.ma.array([0, 1, 0])
+    >>> np.ma.correlate(a, v, mode='valid')
+    masked_array(data=[2],
+                 mask=[False],
+           fill_value=999999)
+
+    Correlation with masked elements:
+
+    >>> a = np.ma.array([1, 2, 3], mask=[False, True, False])
+    >>> v = np.ma.array([0, 1, 0])
+    >>> np.ma.correlate(a, v, mode='valid', propagate_mask=True)
+    masked_array(data=[--],
+                 mask=[ True],
+           fill_value=999999,
+                dtype=int64)
+
+    Correlation with different modes and mixed array types:
+
+    >>> a = np.ma.array([1, 2, 3])
+    >>> v = np.ma.array([0, 1, 0])
+    >>> np.ma.correlate(a, v, mode='full')
+    masked_array(data=[0, 1, 2, 3, 0],
+                 mask=[False, False, False, False, False],
+           fill_value=999999)
+
+    """
+    return _convolve_or_correlate(np.correlate, a, v, mode, propagate_mask)
+
+
+def convolve(a, v, mode='full', propagate_mask=True):
+    """
+    Returns the discrete, linear convolution of two one-dimensional sequences.
+
+    Parameters
+    ----------
+    a, v : array_like
+        Input sequences.
+    mode : {'valid', 'same', 'full'}, optional
+        Refer to the `np.convolve` docstring.
+    propagate_mask : bool
+        If True, then if any masked element is included in the sum for a result
+        element, then the result is masked.
+        If False, then the result element is only masked if no non-masked cells
+        contribute towards it
+
+    Returns
+    -------
+    out : MaskedArray
+        Discrete, linear convolution of `a` and `v`.
+
+    See Also
+    --------
+    numpy.convolve : Equivalent function in the top-level NumPy module.
+    """
+    return _convolve_or_correlate(np.convolve, a, v, mode, propagate_mask)
+
+
+def allequal(a, b, fill_value=True):
+    """
+    Return True if all entries of a and b are equal, using
+    fill_value as a truth value where either or both are masked.
+
+    Parameters
+    ----------
+    a, b : array_like
+        Input arrays to compare.
+    fill_value : bool, optional
+        Whether masked values in a or b are considered equal (True) or not
+        (False).
+
+    Returns
+    -------
+    y : bool
+        Returns True if the two arrays are equal within the given
+        tolerance, False otherwise. If either array contains NaN,
+        then False is returned.
+
+    See Also
+    --------
+    all, any
+    numpy.ma.allclose
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array([1e10, 1e-7, 42.0], mask=[0, 0, 1])
+    >>> a
+    masked_array(data=[10000000000.0, 1e-07, --],
+                 mask=[False, False,  True],
+           fill_value=1e+20)
+
+    >>> b = np.array([1e10, 1e-7, -42.0])
+    >>> b
+    array([  1.00000000e+10,   1.00000000e-07,  -4.20000000e+01])
+    >>> np.ma.allequal(a, b, fill_value=False)
+    False
+    >>> np.ma.allequal(a, b)
+    True
+
+    """
+    m = mask_or(getmask(a), getmask(b))
+    if m is nomask:
+        x = getdata(a)
+        y = getdata(b)
+        d = umath.equal(x, y)
+        return d.all()
+    elif fill_value:
+        x = getdata(a)
+        y = getdata(b)
+        d = umath.equal(x, y)
+        dm = array(d, mask=m, copy=False)
+        return dm.filled(True).all(None)
+    else:
+        return False
+
+
+def allclose(a, b, masked_equal=True, rtol=1e-5, atol=1e-8):
+    """
+    Returns True if two arrays are element-wise equal within a tolerance.
+
+    This function is equivalent to `allclose` except that masked values
+    are treated as equal (default) or unequal, depending on the `masked_equal`
+    argument.
+
+    Parameters
+    ----------
+    a, b : array_like
+        Input arrays to compare.
+    masked_equal : bool, optional
+        Whether masked values in `a` and `b` are considered equal (True) or not
+        (False). They are considered equal by default.
+    rtol : float, optional
+        Relative tolerance. The relative difference is equal to ``rtol * b``.
+        Default is 1e-5.
+    atol : float, optional
+        Absolute tolerance. The absolute difference is equal to `atol`.
+        Default is 1e-8.
+
+    Returns
+    -------
+    y : bool
+        Returns True if the two arrays are equal within the given
+        tolerance, False otherwise. If either array contains NaN, then
+        False is returned.
+
+    See Also
+    --------
+    all, any
+    numpy.allclose : the non-masked `allclose`.
+
+    Notes
+    -----
+    If the following equation is element-wise True, then `allclose` returns
+    True::
+
+      absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))
+
+    Return True if all elements of `a` and `b` are equal subject to
+    given tolerances.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array([1e10, 1e-7, 42.0], mask=[0, 0, 1])
+    >>> a
+    masked_array(data=[10000000000.0, 1e-07, --],
+                 mask=[False, False,  True],
+           fill_value=1e+20)
+    >>> b = np.ma.array([1e10, 1e-8, -42.0], mask=[0, 0, 1])
+    >>> np.ma.allclose(a, b)
+    False
+
+    >>> a = np.ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1])
+    >>> b = np.ma.array([1.00001e10, 1e-9, -42.0], mask=[0, 0, 1])
+    >>> np.ma.allclose(a, b)
+    True
+    >>> np.ma.allclose(a, b, masked_equal=False)
+    False
+
+    Masked values are not compared directly.
+
+    >>> a = np.ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1])
+    >>> b = np.ma.array([1.00001e10, 1e-9, 42.0], mask=[0, 0, 1])
+    >>> np.ma.allclose(a, b)
+    True
+    >>> np.ma.allclose(a, b, masked_equal=False)
+    False
+
+    """
+    x = masked_array(a, copy=False)
+    y = masked_array(b, copy=False)
+
+    # make sure y is an inexact type to avoid abs(MIN_INT); will cause
+    # casting of x later.
+    # NOTE: We explicitly allow timedelta, which used to work. This could
+    #       possibly be deprecated. See also gh-18286.
+    #       timedelta works if `atol` is an integer or also a timedelta.
+    #       Although, the default tolerances are unlikely to be useful
+    if y.dtype.kind != "m":
+        dtype = np.result_type(y, 1.)
+        if y.dtype != dtype:
+            y = masked_array(y, dtype=dtype, copy=False)
+
+    m = mask_or(getmask(x), getmask(y))
+    xinf = np.isinf(masked_array(x, copy=False, mask=m)).filled(False)
+    # If we have some infs, they should fall at the same place.
+    if not np.all(xinf == filled(np.isinf(y), False)):
+        return False
+    # No infs at all
+    if not np.any(xinf):
+        d = filled(less_equal(absolute(x - y), atol + rtol * absolute(y)),
+                   masked_equal)
+        return np.all(d)
+
+    if not np.all(filled(x[xinf] == y[xinf], masked_equal)):
+        return False
+    x = x[~xinf]
+    y = y[~xinf]
+
+    d = filled(less_equal(absolute(x - y), atol + rtol * absolute(y)),
+               masked_equal)
+
+    return np.all(d)
+
+
+def asarray(a, dtype=None, order=None):
+    """
+    Convert the input to a masked array of the given data-type.
+
+    No copy is performed if the input is already an `ndarray`. If `a` is
+    a subclass of `MaskedArray`, a base class `MaskedArray` is returned.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data, in any form that can be converted to a masked array. This
+        includes lists, lists of tuples, tuples, tuples of tuples, tuples
+        of lists, ndarrays and masked arrays.
+    dtype : dtype, optional
+        By default, the data-type is inferred from the input data.
+    order : {'C', 'F'}, optional
+        Whether to use row-major ('C') or column-major ('FORTRAN') memory
+        representation.  Default is 'C'.
+
+    Returns
+    -------
+    out : MaskedArray
+        Masked array interpretation of `a`.
+
+    See Also
+    --------
+    asanyarray : Similar to `asarray`, but conserves subclasses.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(10.).reshape(2, 5)
+    >>> x
+    array([[0., 1., 2., 3., 4.],
+           [5., 6., 7., 8., 9.]])
+    >>> np.ma.asarray(x)
+    masked_array(
+      data=[[0., 1., 2., 3., 4.],
+            [5., 6., 7., 8., 9.]],
+      mask=False,
+      fill_value=1e+20)
+    >>> type(np.ma.asarray(x))
+    <class 'numpy.ma.MaskedArray'>
+
+    """
+    order = order or 'C'
+    return masked_array(a, dtype=dtype, copy=False, keep_mask=True,
+                        subok=False, order=order)
+
+
+def asanyarray(a, dtype=None, order=None):
+    """
+    Convert the input to a masked array, conserving subclasses.
+
+    If `a` is a subclass of `MaskedArray`, its class is conserved.
+    No copy is performed if the input is already an `ndarray`.
+
+    Parameters
+    ----------
+    a : array_like
+        Input data, in any form that can be converted to an array.
+    dtype : dtype, optional
+        By default, the data-type is inferred from the input data.
+    order : {'C', 'F', 'A', 'K'}, optional
+        Memory layout.  'A' and 'K' depend on the order of input array ``a``.
+        'C' row-major (C-style),
+        'F' column-major (Fortran-style) memory representation.
+        'A' (any) means 'F' if ``a`` is Fortran contiguous, 'C' otherwise
+        'K' (keep) preserve input order
+        Defaults to 'K'.
+
+    Returns
+    -------
+    out : MaskedArray
+        MaskedArray interpretation of `a`.
+
+    See Also
+    --------
+    asarray : Similar to `asanyarray`, but does not conserve subclass.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.arange(10.).reshape(2, 5)
+    >>> x
+    array([[0., 1., 2., 3., 4.],
+           [5., 6., 7., 8., 9.]])
+    >>> np.ma.asanyarray(x)
+    masked_array(
+      data=[[0., 1., 2., 3., 4.],
+            [5., 6., 7., 8., 9.]],
+      mask=False,
+      fill_value=1e+20)
+    >>> type(np.ma.asanyarray(x))
+    <class 'numpy.ma.MaskedArray'>
+
+    """
+    # workaround for #8666, to preserve identity. Ideally the bottom line
+    # would handle this for us.
+    if (
+        isinstance(a, MaskedArray)
+        and (dtype is None or dtype == a.dtype)
+        and (
+            order in {None, 'A', 'K'}
+            or order == 'C' and a.flags.carray
+            or order == 'F' and a.flags.f_contiguous
+        )
+    ):
+        return a
+    return masked_array(a, dtype=dtype, copy=False, keep_mask=True, subok=True,
+                        order=order)
+
+
+##############################################################################
+#                               Pickling                                     #
+##############################################################################
+
+
+def fromfile(file, dtype=float, count=-1, sep=''):
+    raise NotImplementedError(
+        "fromfile() not yet implemented for a MaskedArray.")
+
+
+def fromflex(fxarray):
+    """
+    Build a masked array from a suitable flexible-type array.
+
+    The input array has to have a data-type with ``_data`` and ``_mask``
+    fields. This type of array is output by `MaskedArray.toflex`.
+
+    Parameters
+    ----------
+    fxarray : ndarray
+        The structured input array, containing ``_data`` and ``_mask``
+        fields. If present, other fields are discarded.
+
+    Returns
+    -------
+    result : MaskedArray
+        The constructed masked array.
+
+    See Also
+    --------
+    MaskedArray.toflex : Build a flexible-type array from a masked array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[0] + [1, 0] * 4)
+    >>> rec = x.toflex()
+    >>> rec
+    array([[(0, False), (1,  True), (2, False)],
+           [(3,  True), (4, False), (5,  True)],
+           [(6, False), (7,  True), (8, False)]],
+          dtype=[('_data', '<i8'), ('_mask', '?')])
+    >>> x2 = np.ma.fromflex(rec)
+    >>> x2
+    masked_array(
+      data=[[0, --, 2],
+            [--, 4, --],
+            [6, --, 8]],
+      mask=[[False,  True, False],
+            [ True, False,  True],
+            [False,  True, False]],
+      fill_value=999999)
+
+    Extra fields can be present in the structured array but are discarded:
+
+    >>> dt = [('_data', '<i4'), ('_mask', '|b1'), ('field3', '<f4')]
+    >>> rec2 = np.zeros((2, 2), dtype=dt)
+    >>> rec2
+    array([[(0, False, 0.), (0, False, 0.)],
+           [(0, False, 0.), (0, False, 0.)]],
+          dtype=[('_data', '<i4'), ('_mask', '?'), ('field3', '<f4')])
+    >>> y = np.ma.fromflex(rec2)
+    >>> y
+    masked_array(
+      data=[[0, 0],
+            [0, 0]],
+      mask=[[False, False],
+            [False, False]],
+      fill_value=np.int64(999999),
+      dtype=int32)
+
+    """
+    return masked_array(fxarray['_data'], mask=fxarray['_mask'])
+
+
+def _convert2ma(funcname: str, np_ret: str, np_ma_ret: str,
+                params: dict[str, str] | None = None):
+    """Convert function from numpy to numpy.ma."""
+    func = getattr(np, funcname)
+    params = params or {}
+
+    @functools.wraps(func, assigned=set(functools.WRAPPER_ASSIGNMENTS) - {"__module__"})
+    def wrapper(*args, **kwargs):
+        common_params = kwargs.keys() & params.keys()
+        extras = params | {p: kwargs.pop(p) for p in common_params}
+
+        result = func.__call__(*args, **kwargs).view(MaskedArray)
+
+        if "fill_value" in common_params:
+            result.fill_value = extras["fill_value"]
+        if "hardmask" in common_params:
+            result._hardmask = bool(extras["hardmask"])
+
+        return result
+
+    # workaround for a doctest bug in Python 3.11 that incorrectly assumes `__code__`
+    # exists on wrapped functions
+    del wrapper.__wrapped__
+
+    # `arange`, `empty`, `empty_like`, `frombuffer`, and `zeros` have no signature
+    try:
+        signature = inspect.signature(func)
+    except ValueError:
+        signature = inspect.Signature([
+            inspect.Parameter('args', inspect.Parameter.VAR_POSITIONAL),
+            inspect.Parameter('kwargs', inspect.Parameter.VAR_KEYWORD),
+        ])
+
+    if params:
+        sig_params = list(signature.parameters.values())
+
+        # pop `**kwargs` if present
+        sig_kwargs = None
+        if sig_params[-1].kind is inspect.Parameter.VAR_KEYWORD:
+            sig_kwargs = sig_params.pop()
+
+        # add new keyword-only parameters
+        for param_name, default in params.items():
+            new_param = inspect.Parameter(
+                param_name,
+                inspect.Parameter.KEYWORD_ONLY,
+                default=default,
+            )
+            sig_params.append(new_param)
+
+        # re-append `**kwargs` if it was present
+        if sig_kwargs:
+            sig_params.append(sig_kwargs)
+
+        signature = signature.replace(parameters=sig_params)
+
+    wrapper.__signature__ = signature
+
+    # __doc__  is None when using `python -OO ...`
+    if func.__doc__ is not None:
+        assert np_ret in func.__doc__, (
+            f"Failed to replace `{np_ret}` with `{np_ma_ret}`. "
+            f"The documentation string for return type, {np_ret}, is not "
+            f"found in the docstring for `np.{func.__name__}`. "
+            f"Fix the docstring for `np.{func.__name__}` or "
+            "update the expected string for return type."
+        )
+        wrapper.__doc__ = inspect.cleandoc(func.__doc__).replace(np_ret, np_ma_ret)
+
+    return wrapper
+
+
+arange = _convert2ma(
+    'arange',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='arange : ndarray',
+    np_ma_ret='arange : MaskedArray',
+)
+clip = _convert2ma(
+    'clip',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='clipped_array : ndarray',
+    np_ma_ret='clipped_array : MaskedArray',
+)
+empty = _convert2ma(
+    'empty',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+empty_like = _convert2ma(
+    'empty_like',
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+frombuffer = _convert2ma(
+    'frombuffer',
+    np_ret='out : ndarray',
+    np_ma_ret='out: MaskedArray',
+)
+fromfunction = _convert2ma(
+   'fromfunction',
+   np_ret='fromfunction : any',
+   np_ma_ret='fromfunction: MaskedArray',
+)
+identity = _convert2ma(
+    'identity',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+indices = _convert2ma(
+    'indices',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='grid : one ndarray or tuple of ndarrays',
+    np_ma_ret='grid : one MaskedArray or tuple of MaskedArrays',
+)
+ones = _convert2ma(
+    'ones',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+ones_like = _convert2ma(
+    'ones_like',
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+squeeze = _convert2ma(
+    'squeeze',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='squeezed : ndarray',
+    np_ma_ret='squeezed : MaskedArray',
+)
+zeros = _convert2ma(
+    'zeros',
+    params={'fill_value': None, 'hardmask': False},
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+zeros_like = _convert2ma(
+    'zeros_like',
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+
+
+def append(a, b, axis=None):
+    """Append values to the end of an array.
+
+    Parameters
+    ----------
+    a : array_like
+        Values are appended to a copy of this array.
+    b : array_like
+        These values are appended to a copy of `a`.  It must be of the
+        correct shape (the same shape as `a`, excluding `axis`).  If `axis`
+        is not specified, `b` can be any shape and will be flattened
+        before use.
+    axis : int, optional
+        The axis along which `v` are appended.  If `axis` is not given,
+        both `a` and `b` are flattened before use.
+
+    Returns
+    -------
+    append : MaskedArray
+        A copy of `a` with `b` appended to `axis`.  Note that `append`
+        does not occur in-place: a new array is allocated and filled.  If
+        `axis` is None, the result is a flattened array.
+
+    See Also
+    --------
+    numpy.append : Equivalent function in the top-level NumPy module.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> import numpy.ma as ma
+    >>> a = ma.masked_values([1, 2, 3], 2)
+    >>> b = ma.masked_values([[4, 5, 6], [7, 8, 9]], 7)
+    >>> ma.append(a, b)
+    masked_array(data=[1, --, 3, 4, 5, 6, --, 8, 9],
+                 mask=[False,  True, False, False, False, False,  True, False,
+                       False],
+           fill_value=999999)
+    """
+    return concatenate([a, b], axis)
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/core.pyi b/python/user_packages/Python313/site-packages/numpy/ma/core.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..5e144e5fa54a537c1da498f57fe565d2620a12a5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/core.pyi
@@ -0,0 +1,3733 @@
+# pyright: reportIncompatibleMethodOverride=false
+
+import datetime as dt
+import types
+from _typeshed import Incomplete
+from collections.abc import Callable, Sequence
+from typing import (
+    Any,
+    Concatenate,
+    Final,
+    Generic,
+    Literal,
+    Never,
+    NoReturn,
+    Self,
+    SupportsComplex,
+    SupportsFloat,
+    SupportsIndex,
+    SupportsInt,
+    TypeAlias,
+    Unpack,
+    final,
+    overload,
+)
+from typing_extensions import Buffer, ParamSpec, TypeIs, TypeVar, override
+
+import numpy as np
+from numpy import (
+    _AnyShapeT,
+    _HasDType,
+    _HasDTypeWithRealAndImag,
+    _ModeKind,
+    _OrderACF,
+    _OrderCF,
+    _OrderKACF,
+    _PartitionKind,
+    _SortKind,
+    _ToIndices,
+    amax,
+    amin,
+    bool_,
+    bytes_,
+    character,
+    complex128,
+    complexfloating,
+    datetime64,
+    dtype,
+    dtypes,
+    expand_dims,
+    flexible,
+    float16,
+    float32,
+    float64,
+    floating,
+    generic,
+    inexact,
+    int8,
+    int64,
+    int_,
+    integer,
+    intp,
+    ndarray,
+    number,
+    object_,
+    signedinteger,
+    str_,
+    timedelta64,
+    ufunc,
+    unsignedinteger,
+    void,
+)
+from numpy._core.fromnumeric import _UFuncKwargs  # type-check only
+from numpy._globals import _NoValueType
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _32Bit,
+    _64Bit,
+    _AnyShape,
+    _ArrayLike,
+    _ArrayLikeBool_co,
+    _ArrayLikeBytes_co,
+    _ArrayLikeComplex128_co,
+    _ArrayLikeComplex_co,
+    _ArrayLikeDT64_co,
+    _ArrayLikeFloat64_co,
+    _ArrayLikeFloat_co,
+    _ArrayLikeInt,
+    _ArrayLikeInt_co,
+    _ArrayLikeNumber_co,
+    _ArrayLikeObject_co,
+    _ArrayLikeStr_co,
+    _ArrayLikeString_co,
+    _ArrayLikeTD64_co,
+    _ArrayLikeUInt_co,
+    _CharLike_co,
+    _DT64Codes,
+    _DTypeLike,
+    _DTypeLikeBool,
+    _DTypeLikeVoid,
+    _FloatLike_co,
+    _IntLike_co,
+    _NestedSequence,
+    _ScalarLike_co,
+    _Shape,
+    _ShapeLike,
+    _SupportsArrayFunc,
+    _SupportsDType,
+    _TD64Like_co,
+)
+from numpy._typing._dtype_like import _VoidDTypeLike
+
+__all__ = [
+    "MAError",
+    "MaskError",
+    "MaskType",
+    "MaskedArray",
+    "abs",
+    "absolute",
+    "add",
+    "all",
+    "allclose",
+    "allequal",
+    "alltrue",
+    "amax",
+    "amin",
+    "angle",
+    "anom",
+    "anomalies",
+    "any",
+    "append",
+    "arange",
+    "arccos",
+    "arccosh",
+    "arcsin",
+    "arcsinh",
+    "arctan",
+    "arctan2",
+    "arctanh",
+    "argmax",
+    "argmin",
+    "argsort",
+    "around",
+    "array",
+    "asanyarray",
+    "asarray",
+    "bitwise_and",
+    "bitwise_or",
+    "bitwise_xor",
+    "bool_",
+    "ceil",
+    "choose",
+    "clip",
+    "common_fill_value",
+    "compress",
+    "compressed",
+    "concatenate",
+    "conjugate",
+    "convolve",
+    "copy",
+    "correlate",
+    "cos",
+    "cosh",
+    "count",
+    "cumprod",
+    "cumsum",
+    "default_fill_value",
+    "diag",
+    "diagonal",
+    "diff",
+    "divide",
+    "empty",
+    "empty_like",
+    "equal",
+    "exp",
+    "expand_dims",
+    "fabs",
+    "filled",
+    "fix_invalid",
+    "flatten_mask",
+    "flatten_structured_array",
+    "floor",
+    "floor_divide",
+    "fmod",
+    "frombuffer",
+    "fromflex",
+    "fromfunction",
+    "getdata",
+    "getmask",
+    "getmaskarray",
+    "greater",
+    "greater_equal",
+    "harden_mask",
+    "hypot",
+    "identity",
+    "ids",
+    "indices",
+    "inner",
+    "innerproduct",
+    "isMA",
+    "isMaskedArray",
+    "is_mask",
+    "is_masked",
+    "isarray",
+    "left_shift",
+    "less",
+    "less_equal",
+    "log",
+    "log2",
+    "log10",
+    "logical_and",
+    "logical_not",
+    "logical_or",
+    "logical_xor",
+    "make_mask",
+    "make_mask_descr",
+    "make_mask_none",
+    "mask_or",
+    "masked",
+    "masked_array",
+    "masked_equal",
+    "masked_greater",
+    "masked_greater_equal",
+    "masked_inside",
+    "masked_invalid",
+    "masked_less",
+    "masked_less_equal",
+    "masked_not_equal",
+    "masked_object",
+    "masked_outside",
+    "masked_print_option",
+    "masked_singleton",
+    "masked_values",
+    "masked_where",
+    "max",
+    "maximum",
+    "maximum_fill_value",
+    "mean",
+    "min",
+    "minimum",
+    "minimum_fill_value",
+    "mod",
+    "multiply",
+    "mvoid",
+    "ndim",
+    "negative",
+    "nomask",
+    "nonzero",
+    "not_equal",
+    "ones",
+    "ones_like",
+    "outer",
+    "outerproduct",
+    "power",
+    "prod",
+    "product",
+    "ptp",
+    "put",
+    "putmask",
+    "ravel",
+    "remainder",
+    "repeat",
+    "reshape",
+    "resize",
+    "right_shift",
+    "round",
+    "round_",
+    "set_fill_value",
+    "shape",
+    "sin",
+    "sinh",
+    "size",
+    "soften_mask",
+    "sometrue",
+    "sort",
+    "sqrt",
+    "squeeze",
+    "std",
+    "subtract",
+    "sum",
+    "swapaxes",
+    "take",
+    "tan",
+    "tanh",
+    "trace",
+    "transpose",
+    "true_divide",
+    "var",
+    "where",
+    "zeros",
+    "zeros_like",
+]
+
+_ShapeT = TypeVar("_ShapeT", bound=_Shape)
+_ShapeOrAnyT = TypeVar("_ShapeOrAnyT", bound=_Shape, default=_AnyShape)
+_ShapeT_co = TypeVar("_ShapeT_co", bound=_Shape, default=_AnyShape, covariant=True)
+_DTypeT = TypeVar("_DTypeT", bound=dtype)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=dtype, default=dtype, covariant=True)
+_ArrayT = TypeVar("_ArrayT", bound=ndarray[Any, Any])
+_MArrayT = TypeVar("_MArrayT", bound=MaskedArray[Any, Any])
+_ScalarT = TypeVar("_ScalarT", bound=generic)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=generic, covariant=True)
+_NumberT = TypeVar("_NumberT", bound=number)
+_RealNumberT = TypeVar("_RealNumberT", bound=floating | integer)
+_ArangeScalarT = TypeVar("_ArangeScalarT", bound=_ArangeScalar)
+_UFuncT_co = TypeVar(
+    "_UFuncT_co",
+    # the `| Callable` simplifies self-binding to the ufunc's callable signature
+    bound=np.ufunc | Callable[..., object],
+    default=np.ufunc,
+    covariant=True,
+)
+_Pss = ParamSpec("_Pss")
+_T = TypeVar("_T")
+
+_Ignored: TypeAlias = object
+
+# A subset of `MaskedArray` that can be parametrized w.r.t. `np.generic`
+_MaskedArray: TypeAlias = MaskedArray[_AnyShape, dtype[_ScalarT]]
+_Masked1D: TypeAlias = MaskedArray[tuple[int], dtype[_ScalarT]]
+
+_MaskedArrayUInt_co: TypeAlias = _MaskedArray[unsignedinteger | np.bool]
+_MaskedArrayInt_co: TypeAlias = _MaskedArray[integer | np.bool]
+_MaskedArrayFloat64_co: TypeAlias = _MaskedArray[floating[_64Bit] | float32 | float16 | integer | np.bool]
+_MaskedArrayFloat_co: TypeAlias = _MaskedArray[floating | integer | np.bool]
+_MaskedArrayComplex128_co: TypeAlias = _MaskedArray[number[_64Bit] | number[_32Bit] | float16 | integer | np.bool]
+_MaskedArrayComplex_co: TypeAlias = _MaskedArray[inexact | integer | np.bool]
+_MaskedArrayNumber_co: TypeAlias = _MaskedArray[number | np.bool]
+_MaskedArrayTD64_co: TypeAlias = _MaskedArray[timedelta64 | integer | np.bool]
+
+_ArrayInt_co: TypeAlias = NDArray[integer | bool_]
+_Array1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]]
+
+_ConvertibleToInt: TypeAlias = SupportsInt | SupportsIndex | _CharLike_co
+_ConvertibleToFloat: TypeAlias = SupportsFloat | SupportsIndex | _CharLike_co
+_ConvertibleToComplex: TypeAlias = SupportsComplex | SupportsFloat | SupportsIndex | _CharLike_co
+_ConvertibleToTD64: TypeAlias = dt.timedelta | int | _CharLike_co | character | number | timedelta64 | np.bool | None
+_ConvertibleToDT64: TypeAlias = dt.date | int | _CharLike_co | character | number | datetime64 | np.bool | None
+_ArangeScalar: TypeAlias = floating | integer | datetime64 | timedelta64
+
+_NoMaskType: TypeAlias = np.bool_[Literal[False]]  # type of `np.False_`
+_MaskArray: TypeAlias = np.ndarray[_ShapeOrAnyT, np.dtype[np.bool_]]
+
+_FillValue: TypeAlias = complex | None  # int | float | complex | None
+_FillValueCallable: TypeAlias = Callable[[np.dtype | ArrayLike], _FillValue]
+_DomainCallable: TypeAlias = Callable[..., NDArray[np.bool_]]
+
+###
+
+MaskType = np.bool_
+
+nomask: Final[_NoMaskType] = ...
+
+class MaskedArrayFutureWarning(FutureWarning): ...
+class MAError(Exception): ...
+class MaskError(MAError): ...
+
+# not generic at runtime
+class _MaskedUFunc(Generic[_UFuncT_co]):
+    f: _UFuncT_co  # readonly
+    def __init__(self, /, ufunc: _UFuncT_co) -> None: ...
+
+# not generic at runtime
+class _MaskedUnaryOperation(_MaskedUFunc[_UFuncT_co], Generic[_UFuncT_co]):
+    fill: Final[_FillValue]
+    domain: Final[_DomainCallable | None]
+
+    def __init__(self, /, mufunc: _UFuncT_co, fill: _FillValue = 0, domain: _DomainCallable | None = None) -> None: ...
+
+    # NOTE: This might not work with overloaded callable signatures might not work on
+    # pyright, which is a long-standing issue, and is unique to pyright:
+    # https://github.com/microsoft/pyright/issues/9663
+    # https://github.com/microsoft/pyright/issues/10849
+    # https://github.com/microsoft/pyright/issues/10899
+    # https://github.com/microsoft/pyright/issues/11049
+    def __call__(
+        self: _MaskedUnaryOperation[Callable[Concatenate[Any, _Pss], _T]],
+        /,
+        a: ArrayLike,
+        *args: _Pss.args,
+        **kwargs: _Pss.kwargs,
+    ) -> _T: ...
+
+# not generic at runtime
+class _MaskedBinaryOperation(_MaskedUFunc[_UFuncT_co], Generic[_UFuncT_co]):
+    fillx: Final[_FillValue]
+    filly: Final[_FillValue]
+
+    def __init__(self, /, mbfunc: _UFuncT_co, fillx: _FillValue = 0, filly: _FillValue = 0) -> None: ...
+
+    # NOTE: See the comment in `_MaskedUnaryOperation.__call__`
+    def __call__(
+        self: _MaskedBinaryOperation[Callable[Concatenate[Any, Any, _Pss], _T]],
+        /,
+        a: ArrayLike,
+        b: ArrayLike,
+        *args: _Pss.args,
+        **kwargs: _Pss.kwargs,
+    ) -> _T: ...
+
+    # NOTE: We cannot meaningfully annotate the return (d)types of these methods until
+    # the signatures of the corresponding `numpy.ufunc` methods are specified.
+    def reduce(self, /, target: ArrayLike, axis: SupportsIndex = 0, dtype: DTypeLike | None = None) -> Incomplete: ...
+    def outer(self, /, a: ArrayLike, b: ArrayLike) -> _MaskedArray[Incomplete]: ...
+    def accumulate(self, /, target: ArrayLike, axis: SupportsIndex = 0) -> _MaskedArray[Incomplete]: ...
+
+# not generic at runtime
+class _DomainedBinaryOperation(_MaskedUFunc[_UFuncT_co], Generic[_UFuncT_co]):
+    domain: Final[_DomainCallable]
+    fillx: Final[_FillValue]
+    filly: Final[_FillValue]
+
+    def __init__(
+        self,
+        /,
+        dbfunc: _UFuncT_co,
+        domain: _DomainCallable,
+        fillx: _FillValue = 0,
+        filly: _FillValue = 0,
+    ) -> None: ...
+
+    # NOTE: See the comment in `_MaskedUnaryOperation.__call__`
+    def __call__(
+        self: _DomainedBinaryOperation[Callable[Concatenate[Any, Any, _Pss], _T]],
+        /,
+        a: ArrayLike,
+        b: ArrayLike,
+        *args: _Pss.args,
+        **kwargs: _Pss.kwargs,
+    ) -> _T: ...
+
+# not generic at runtime
+class _extrema_operation(_MaskedUFunc[_UFuncT_co], Generic[_UFuncT_co]):
+    compare: Final[_MaskedBinaryOperation]
+    fill_value_func: Final[_FillValueCallable]
+
+    def __init__(
+        self,
+        /,
+        ufunc: _UFuncT_co,
+        compare: _MaskedBinaryOperation,
+        fill_value: _FillValueCallable,
+    ) -> None: ...
+
+    # NOTE: This class is only used internally for `maximum` and `minimum`, so we are
+    # able to annotate the `__call__` method specifically for those two functions.
+    @overload
+    def __call__(self, /, a: _ArrayLike[_ScalarT], b: _ArrayLike[_ScalarT]) -> _MaskedArray[_ScalarT]: ...
+    @overload
+    def __call__(self, /, a: ArrayLike, b: ArrayLike) -> _MaskedArray[Incomplete]: ...
+
+    # NOTE: We cannot meaningfully annotate the return (d)types of these methods until
+    # the signatures of the corresponding `numpy.ufunc` methods are specified.
+    def reduce(self, /, target: ArrayLike, axis: SupportsIndex | _NoValueType = ...) -> Incomplete: ...
+    def outer(self, /, a: ArrayLike, b: ArrayLike) -> _MaskedArray[Incomplete]: ...
+
+@final
+class _MaskedPrintOption:
+    _display: str
+    _enabled: bool | Literal[0, 1]
+    def __init__(self, /, display: str) -> None: ...
+    def display(self, /) -> str: ...
+    def set_display(self, /, s: str) -> None: ...
+    def enabled(self, /) -> bool: ...
+    def enable(self, /, shrink: bool | Literal[0, 1] = 1) -> None: ...
+
+masked_print_option: Final[_MaskedPrintOption] = ...
+
+exp: _MaskedUnaryOperation = ...
+conjugate: _MaskedUnaryOperation = ...
+sin: _MaskedUnaryOperation = ...
+cos: _MaskedUnaryOperation = ...
+arctan: _MaskedUnaryOperation = ...
+arcsinh: _MaskedUnaryOperation = ...
+sinh: _MaskedUnaryOperation = ...
+cosh: _MaskedUnaryOperation = ...
+tanh: _MaskedUnaryOperation = ...
+abs: _MaskedUnaryOperation = ...
+absolute: _MaskedUnaryOperation = ...
+angle: _MaskedUnaryOperation = ...
+fabs: _MaskedUnaryOperation = ...
+negative: _MaskedUnaryOperation = ...
+floor: _MaskedUnaryOperation = ...
+ceil: _MaskedUnaryOperation = ...
+around: _MaskedUnaryOperation = ...
+logical_not: _MaskedUnaryOperation = ...
+sqrt: _MaskedUnaryOperation = ...
+log: _MaskedUnaryOperation = ...
+log2: _MaskedUnaryOperation = ...
+log10: _MaskedUnaryOperation = ...
+tan: _MaskedUnaryOperation = ...
+arcsin: _MaskedUnaryOperation = ...
+arccos: _MaskedUnaryOperation = ...
+arccosh: _MaskedUnaryOperation = ...
+arctanh: _MaskedUnaryOperation = ...
+
+add: _MaskedBinaryOperation = ...
+subtract: _MaskedBinaryOperation = ...
+multiply: _MaskedBinaryOperation = ...
+arctan2: _MaskedBinaryOperation = ...
+equal: _MaskedBinaryOperation = ...
+not_equal: _MaskedBinaryOperation = ...
+less_equal: _MaskedBinaryOperation = ...
+greater_equal: _MaskedBinaryOperation = ...
+less: _MaskedBinaryOperation = ...
+greater: _MaskedBinaryOperation = ...
+logical_and: _MaskedBinaryOperation = ...
+def alltrue(target: ArrayLike, axis: SupportsIndex | None = 0, dtype: _DTypeLikeBool | None = None) -> Incomplete: ...
+logical_or: _MaskedBinaryOperation = ...
+def sometrue(target: ArrayLike, axis: SupportsIndex | None = 0, dtype: _DTypeLikeBool | None = None) -> Incomplete: ...
+logical_xor: _MaskedBinaryOperation = ...
+bitwise_and: _MaskedBinaryOperation = ...
+bitwise_or: _MaskedBinaryOperation = ...
+bitwise_xor: _MaskedBinaryOperation = ...
+hypot: _MaskedBinaryOperation = ...
+
+divide: _DomainedBinaryOperation = ...
+true_divide: _DomainedBinaryOperation = ...
+floor_divide: _DomainedBinaryOperation = ...
+remainder: _DomainedBinaryOperation = ...
+fmod: _DomainedBinaryOperation = ...
+mod: _DomainedBinaryOperation = ...
+
+# `obj` can be anything (even `object()`), and is too "flexible", so we can't
+# meaningfully annotate it, or its return type.
+def default_fill_value(obj: object) -> Any: ...
+def minimum_fill_value(obj: object) -> Any: ...
+def maximum_fill_value(obj: object) -> Any: ...
+
+#
+@overload  # returns `a.fill_value` if `a` is a `MaskedArray`
+def get_fill_value(a: _MaskedArray[_ScalarT]) -> _ScalarT: ...
+@overload  # otherwise returns `default_fill_value(a)`
+def get_fill_value(a: object) -> Any: ...
+
+# this is a noop if `a` isn't a `MaskedArray`, so we only accept `MaskedArray` input
+def set_fill_value(a: MaskedArray, fill_value: _ScalarLike_co) -> None: ...
+
+# the return type depends on the *values* of `a` and `b` (which cannot be known
+# statically), which is why we need to return an awkward `_ | None`
+@overload
+def common_fill_value(a: _MaskedArray[_ScalarT], b: MaskedArray) -> _ScalarT | None: ...
+@overload
+def common_fill_value(a: object, b: object) -> Any: ...
+
+# keep in sync with `fix_invalid`, but return `ndarray` instead of `MaskedArray`
+@overload
+def filled(a: ndarray[_ShapeT, _DTypeT], fill_value: _ScalarLike_co | None = None) -> ndarray[_ShapeT, _DTypeT]: ...
+@overload
+def filled(a: _ArrayLike[_ScalarT], fill_value: _ScalarLike_co | None = None) -> NDArray[_ScalarT]: ...
+@overload
+def filled(a: ArrayLike, fill_value: _ScalarLike_co | None = None) -> NDArray[Incomplete]: ...
+
+# keep in sync with `filled`, but return `MaskedArray` instead of `ndarray`
+@overload
+def fix_invalid(
+    a: np.ndarray[_ShapeT, _DTypeT],
+    mask: _ArrayLikeBool_co = nomask,
+    copy: bool = True,
+    fill_value: _ScalarLike_co | None = None,
+) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload
+def fix_invalid(
+    a: _ArrayLike[_ScalarT],
+    mask: _ArrayLikeBool_co = nomask,
+    copy: bool = True,
+    fill_value: _ScalarLike_co | None = None,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def fix_invalid(
+    a: ArrayLike,
+    mask: _ArrayLikeBool_co = nomask,
+    copy: bool = True,
+    fill_value: _ScalarLike_co | None = None,
+) -> _MaskedArray[Incomplete]: ...
+
+#
+def get_masked_subclass(*arrays: object) -> type[MaskedArray]: ...
+
+#
+@overload
+def getdata(a: np.ndarray[_ShapeT, _DTypeT], subok: bool = True) -> np.ndarray[_ShapeT, _DTypeT]: ...
+@overload
+def getdata(a: _ArrayLike[_ScalarT], subok: bool = True) -> NDArray[_ScalarT]: ...
+@overload
+def getdata(a: ArrayLike, subok: bool = True) -> NDArray[Incomplete]: ...
+
+get_data = getdata
+
+#
+@overload
+def getmask(a: _ScalarLike_co) -> _NoMaskType: ...
+@overload
+def getmask(a: MaskedArray[_ShapeT, Any]) -> _MaskArray[_ShapeT] | _NoMaskType: ...
+@overload
+def getmask(a: ArrayLike) -> _MaskArray | _NoMaskType: ...
+
+get_mask = getmask
+
+# like `getmask`, but instead of `nomask` returns `make_mask_none(arr, arr.dtype?)`
+@overload
+def getmaskarray(arr: _ScalarLike_co) -> _MaskArray[tuple[()]]: ...
+@overload
+def getmaskarray(arr: np.ndarray[_ShapeT, Any]) -> _MaskArray[_ShapeT]: ...
+
+# It's sufficient for `m` to have dtype with type: `type[np.bool_]`,
+# which isn't necessarily a ndarray. Please open an issue if this causes issues.
+def is_mask(m: object) -> TypeIs[NDArray[bool_]]: ...
+
+#
+@overload
+def make_mask_descr(ndtype: _VoidDTypeLike) -> np.dtype[np.void]: ...
+@overload
+def make_mask_descr(ndtype: _DTypeLike[np.generic] | str | type) -> np.dtype[np.bool_]: ...
+
+#
+@overload  # m is nomask
+def make_mask(
+    m: _NoMaskType,
+    copy: bool = False,
+    shrink: bool = True,
+    dtype: _DTypeLikeBool = ...,
+) -> _NoMaskType: ...
+@overload  # m: ndarray, shrink=True (default), dtype: bool-like (default)
+def make_mask(
+    m: np.ndarray[_ShapeT],
+    copy: bool = False,
+    shrink: Literal[True] = True,
+    dtype: _DTypeLikeBool = ...,
+) -> _MaskArray[_ShapeT] | _NoMaskType: ...
+@overload  # m: ndarray, shrink=False (kwarg), dtype: bool-like (default)
+def make_mask(
+    m: np.ndarray[_ShapeT],
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+    dtype: _DTypeLikeBool = ...,
+) -> _MaskArray[_ShapeT]: ...
+@overload  # m: ndarray, dtype: void-like
+def make_mask(
+    m: np.ndarray[_ShapeT],
+    copy: bool = False,
+    shrink: bool = True,
+    *,
+    dtype: _DTypeLikeVoid,
+) -> np.ndarray[_ShapeT, np.dtype[np.void]]: ...
+@overload  # m: array-like, shrink=True (default), dtype: bool-like (default)
+def make_mask(
+    m: ArrayLike,
+    copy: bool = False,
+    shrink: Literal[True] = True,
+    dtype: _DTypeLikeBool = ...,
+) -> _MaskArray | _NoMaskType: ...
+@overload  # m: array-like, shrink=False (kwarg), dtype: bool-like (default)
+def make_mask(
+    m: ArrayLike,
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+    dtype: _DTypeLikeBool = ...,
+) -> _MaskArray: ...
+@overload  # m: array-like, dtype: void-like
+def make_mask(
+    m: ArrayLike,
+    copy: bool = False,
+    shrink: bool = True,
+    *,
+    dtype: _DTypeLikeVoid,
+) -> NDArray[np.void]: ...
+@overload  # fallback
+def make_mask(
+    m: ArrayLike,
+    copy: bool = False,
+    shrink: bool = True,
+    *,
+    dtype: DTypeLike = ...,
+) -> NDArray[Incomplete] | _NoMaskType: ...
+
+#
+@overload  # known shape, dtype: unstructured (default)
+def make_mask_none(newshape: _ShapeT, dtype: np.dtype | type | str | None = None) -> _MaskArray[_ShapeT]: ...
+@overload  # known shape, dtype: structured
+def make_mask_none(newshape: _ShapeT, dtype: _VoidDTypeLike) -> np.ndarray[_ShapeT, dtype[np.void]]: ...
+@overload  # unknown shape, dtype: unstructured (default)
+def make_mask_none(newshape: _ShapeLike, dtype: np.dtype | type | str | None = None) -> _MaskArray: ...
+@overload  # unknown shape, dtype: structured
+def make_mask_none(newshape: _ShapeLike, dtype: _VoidDTypeLike) -> NDArray[np.void]: ...
+
+#
+@overload  # nomask, scalar-like, shrink=True (default)
+def mask_or(
+    m1: _NoMaskType | Literal[False],
+    m2: _ScalarLike_co,
+    copy: bool = False,
+    shrink: Literal[True] = True,
+) -> _NoMaskType: ...
+@overload  # nomask, scalar-like, shrink=False (kwarg)
+def mask_or(
+    m1: _NoMaskType | Literal[False],
+    m2: _ScalarLike_co,
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+) -> _MaskArray[tuple[()]]: ...
+@overload  # scalar-like, nomask, shrink=True (default)
+def mask_or(
+    m1: _ScalarLike_co,
+    m2: _NoMaskType | Literal[False],
+    copy: bool = False,
+    shrink: Literal[True] = True,
+) -> _NoMaskType: ...
+@overload  # scalar-like, nomask, shrink=False (kwarg)
+def mask_or(
+    m1: _ScalarLike_co,
+    m2: _NoMaskType | Literal[False],
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+) -> _MaskArray[tuple[()]]: ...
+@overload  # ndarray, ndarray | nomask, shrink=True (default)
+def mask_or(
+    m1: np.ndarray[_ShapeT, np.dtype[_ScalarT]],
+    m2: np.ndarray[_ShapeT, np.dtype[_ScalarT]] | _NoMaskType | Literal[False],
+    copy: bool = False,
+    shrink: Literal[True] = True,
+) -> _MaskArray[_ShapeT] | _NoMaskType: ...
+@overload  # ndarray, ndarray | nomask, shrink=False (kwarg)
+def mask_or(
+    m1: np.ndarray[_ShapeT, np.dtype[_ScalarT]],
+    m2: np.ndarray[_ShapeT, np.dtype[_ScalarT]] | _NoMaskType | Literal[False],
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+) -> _MaskArray[_ShapeT]: ...
+@overload  # ndarray | nomask, ndarray, shrink=True (default)
+def mask_or(
+    m1: np.ndarray[_ShapeT, np.dtype[_ScalarT]] | _NoMaskType | Literal[False],
+    m2: np.ndarray[_ShapeT, np.dtype[_ScalarT]],
+    copy: bool = False,
+    shrink: Literal[True] = True,
+) -> _MaskArray[_ShapeT] | _NoMaskType: ...
+@overload  # ndarray | nomask, ndarray, shrink=False (kwarg)
+def mask_or(
+    m1: np.ndarray[_ShapeT, np.dtype[_ScalarT]] | _NoMaskType | Literal[False],
+    m2: np.ndarray[_ShapeT, np.dtype[_ScalarT]],
+    copy: bool = False,
+    *,
+    shrink: Literal[False],
+) -> _MaskArray[_ShapeT]: ...
+
+#
+@overload
+def flatten_mask(mask: np.ndarray[_ShapeT]) -> _MaskArray[_ShapeT]: ...
+@overload
+def flatten_mask(mask: ArrayLike) -> _MaskArray: ...
+
+# NOTE: we currently don't know the field types of `void` dtypes, so it's not possible
+# to know the output dtype of the returned array.
+@overload
+def flatten_structured_array(a: MaskedArray[_ShapeT, np.dtype[np.void]]) -> MaskedArray[_ShapeT]: ...
+@overload
+def flatten_structured_array(a: np.ndarray[_ShapeT, np.dtype[np.void]]) -> np.ndarray[_ShapeT]: ...
+@overload  # for some reason this accepts unstructured array-likes, hence this fallback overload
+def flatten_structured_array(a: ArrayLike) -> np.ndarray: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_invalid(a: ndarray[_ShapeT, _DTypeT], copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_invalid(a: _ArrayLike[_ScalarT], copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_invalid(a: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # array-like of known scalar-type
+def masked_where(
+    condition: _ArrayLikeBool_co, a: ndarray[_ShapeT, _DTypeT], copy: bool = True
+) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_where(condition: _ArrayLikeBool_co, a: _ArrayLike[_ScalarT], copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_where(condition: _ArrayLikeBool_co, a: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_greater(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_greater(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_greater(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_greater_equal(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_greater_equal(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_greater_equal(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_less(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_less(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_less(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_less_equal(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_less_equal(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_less_equal(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_not_equal(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_not_equal(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_not_equal(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_equal(x: ndarray[_ShapeT, _DTypeT], value: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_equal(x: _ArrayLike[_ScalarT], value: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_equal(x: ArrayLike, value: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_inside(x: ndarray[_ShapeT, _DTypeT], v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_inside(x: _ArrayLike[_ScalarT], v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_inside(x: ArrayLike, v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with other the `masked_*` functions
+@overload  # known array with known shape and dtype
+def masked_outside(x: ndarray[_ShapeT, _DTypeT], v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload  # array-like of known scalar-type
+def masked_outside(x: _ArrayLike[_ScalarT], v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> _MaskedArray[_ScalarT]: ...
+@overload  # unknown array-like
+def masked_outside(x: ArrayLike, v1: ArrayLike, v2: ArrayLike, copy: bool = True) -> _MaskedArray[Incomplete]: ...
+
+# only intended for object arrays, so we assume that's how it's always used in practice
+@overload
+def masked_object(
+    x: np.ndarray[_ShapeT, np.dtype[np.object_]],
+    value: object,
+    copy: bool = True,
+    shrink: bool = True,
+) -> MaskedArray[_ShapeT, np.dtype[np.object_]]: ...
+@overload
+def masked_object(
+    x: _ArrayLikeObject_co,
+    value: object,
+    copy: bool = True,
+    shrink: bool = True,
+) -> _MaskedArray[np.object_]: ...
+
+# keep roughly in sync with `filled`
+@overload
+def masked_values(
+    x: np.ndarray[_ShapeT, _DTypeT],
+    value: _ScalarLike_co,
+    rtol: float = 1e-5,
+    atol: float = 1e-8,
+    copy: bool = True,
+    shrink: bool = True
+) -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload
+def masked_values(
+    x: _ArrayLike[_ScalarT],
+    value: _ScalarLike_co,
+    rtol: float = 1e-5,
+    atol: float = 1e-8,
+    copy: bool = True,
+    shrink: bool = True
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def masked_values(
+    x: ArrayLike,
+    value: _ScalarLike_co,
+    rtol: float = 1e-5,
+    atol: float = 1e-8,
+    copy: bool = True,
+    shrink: bool = True
+) -> _MaskedArray[Incomplete]: ...
+
+# TODO: Support non-boolean mask dtypes, such as `np.void`. This will require adding an
+# additional generic type parameter to (at least) `MaskedArray` and `MaskedIterator` to
+# hold the dtype of the mask.
+
+class MaskedIterator(Generic[_ShapeT_co, _DTypeT_co]):
+    ma: MaskedArray[_ShapeT_co, _DTypeT_co]  # readonly
+    dataiter: np.flatiter[ndarray[_ShapeT_co, _DTypeT_co]]  # readonly
+    maskiter: Final[np.flatiter[NDArray[np.bool]]]
+
+    def __init__(self, ma: MaskedArray[_ShapeT_co, _DTypeT_co]) -> None: ...
+    def __iter__(self) -> Self: ...
+
+    # Similar to `MaskedArray.__getitem__` but without the `void` case.
+    @overload
+    def __getitem__(self, indx: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, indx: SupportsIndex | tuple[SupportsIndex, ...], /) -> Incomplete: ...
+    @overload
+    def __getitem__(self, indx: _ToIndices, /) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    # Similar to `ndarray.__setitem__` but without the `void` case.
+    @overload  # flexible | object_ | bool
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[flexible | object_ | np.bool] | dtypes.StringDType],
+        index: _ToIndices,
+        value: object,
+        /,
+    ) -> None: ...
+    @overload  # integer
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[integer]],
+        index: _ToIndices,
+        value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co,
+        /,
+    ) -> None: ...
+    @overload  # floating
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[floating]],
+        index: _ToIndices,
+        value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None,
+        /,
+    ) -> None: ...
+    @overload  # complexfloating
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[complexfloating]],
+        index: _ToIndices,
+        value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None,
+        /,
+    ) -> None: ...
+    @overload  # timedelta64
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[timedelta64]],
+        index: _ToIndices,
+        value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64],
+        /,
+    ) -> None: ...
+    @overload  # datetime64
+    def __setitem__(
+        self: MaskedIterator[Any, dtype[datetime64]],
+        index: _ToIndices,
+        value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64],
+        /,
+    ) -> None: ...
+    @overload  # catch-all
+    def __setitem__(self, index: _ToIndices, value: ArrayLike, /) -> None: ...
+
+    # TODO: Returns `mvoid[(), _DTypeT_co]` for masks with `np.void` dtype.
+    def __next__(self: MaskedIterator[Any, np.dtype[_ScalarT]]) -> _ScalarT: ...
+
+class MaskedArray(ndarray[_ShapeT_co, _DTypeT_co]):
+    __array_priority__: Final[Literal[15]] = 15
+
+    @overload
+    def __new__(
+        cls,
+        data: _ArrayLike[_ScalarT],
+        mask: _ArrayLikeBool_co = nomask,
+        dtype: None = None,
+        copy: bool = False,
+        subok: bool = True,
+        ndmin: int = 0,
+        fill_value: _ScalarLike_co | None = None,
+        keep_mask: bool = True,
+        hard_mask: bool | None = None,
+        shrink: bool = True,
+        order: _OrderKACF | None = None,
+    ) -> _MaskedArray[_ScalarT]: ...
+    @overload
+    def __new__(
+        cls,
+        data: object,
+        mask: _ArrayLikeBool_co,
+        dtype: _DTypeLike[_ScalarT],
+        copy: bool = False,
+        subok: bool = True,
+        ndmin: int = 0,
+        fill_value: _ScalarLike_co | None = None,
+        keep_mask: bool = True,
+        hard_mask: bool | None = None,
+        shrink: bool = True,
+        order: _OrderKACF | None = None,
+    ) -> _MaskedArray[_ScalarT]: ...
+    @overload
+    def __new__(
+        cls,
+        data: object,
+        mask: _ArrayLikeBool_co = nomask,
+        *,
+        dtype: _DTypeLike[_ScalarT],
+        copy: bool = False,
+        subok: bool = True,
+        ndmin: int = 0,
+        fill_value: _ScalarLike_co | None = None,
+        keep_mask: bool = True,
+        hard_mask: bool | None = None,
+        shrink: bool = True,
+        order: _OrderKACF | None = None,
+    ) -> _MaskedArray[_ScalarT]: ...
+    @overload
+    def __new__(
+        cls,
+        data: object = None,
+        mask: _ArrayLikeBool_co = nomask,
+        dtype: DTypeLike | None = None,
+        copy: bool = False,
+        subok: bool = True,
+        ndmin: int = 0,
+        fill_value: _ScalarLike_co | None = None,
+        keep_mask: bool = True,
+        hard_mask: bool | None = None,
+        shrink: bool = True,
+        order: _OrderKACF | None = None,
+    ) -> _MaskedArray[Any]: ...
+
+    def __array_wrap__(
+        self,
+        obj: ndarray[_ShapeT, _DTypeT],
+        context: tuple[ufunc, tuple[Any, ...], int] | None = None,
+        return_scalar: bool = False,
+    ) -> MaskedArray[_ShapeT, _DTypeT]: ...
+
+    @overload  # type: ignore[override]  # ()
+    def view(self, /, dtype: None = None, type: None = None, fill_value: _ScalarLike_co | None = None) -> Self: ...
+    @overload  # (dtype: DTypeT)
+    def view(
+        self,
+        /,
+        dtype: _DTypeT | _HasDType[_DTypeT],
+        type: None = None,
+        fill_value: _ScalarLike_co | None = None
+    ) -> MaskedArray[_ShapeT_co, _DTypeT]: ...
+    @overload  # (dtype: dtype[ScalarT])
+    def view(
+        self,
+        /,
+        dtype: _DTypeLike[_ScalarT],
+        type: None = None,
+        fill_value: _ScalarLike_co | None = None
+    ) -> MaskedArray[_ShapeT_co, dtype[_ScalarT]]: ...
+    @overload  # ([dtype: _, ]*, type: ArrayT)
+    def view(
+        self,
+        /,
+        dtype: DTypeLike | None = None,
+        *,
+        type: type[_ArrayT],
+        fill_value: _ScalarLike_co | None = None
+    ) -> _ArrayT: ...
+    @overload  # (dtype: _, type: ArrayT)
+    def view(self, /, dtype: DTypeLike | None, type: type[_ArrayT], fill_value: _ScalarLike_co | None = None) -> _ArrayT: ...
+    @overload  # (dtype: ArrayT, /)
+    def view(self, /, dtype: type[_ArrayT], type: None = None, fill_value: _ScalarLike_co | None = None) -> _ArrayT: ...
+    @overload  # (dtype: ?)
+    def view(
+        self,
+        /,
+        # `_VoidDTypeLike | str | None` is like `DTypeLike` but without `_DTypeLike[Any]` to avoid
+        # overlaps with previous overloads.
+        dtype: _VoidDTypeLike | str | None,
+        type: None = None,
+        fill_value: _ScalarLike_co | None = None
+    ) -> MaskedArray[_ShapeT_co, dtype]: ...
+
+    # Keep in sync with `ndarray.__getitem__`
+    @overload
+    def __getitem__(self, key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any: ...
+    @overload
+    def __getitem__(self, key: _ToIndices, /) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self: _MaskedArray[void], indx: str, /) -> MaskedArray[_ShapeT_co, dtype]: ...
+    @overload
+    def __getitem__(self: _MaskedArray[void], indx: list[str], /) -> MaskedArray[_ShapeT_co, dtype[void]]: ...
+
+    @property
+    def shape(self) -> _ShapeT_co: ...
+    @shape.setter  # type: ignore[override]
+    def shape(self: MaskedArray[_ShapeT, Any], shape: _ShapeT, /) -> None: ...
+
+    def __setmask__(self, mask: _ArrayLikeBool_co, copy: bool = False) -> None: ...
+    @property
+    def mask(self) -> np.ndarray[_ShapeT_co, dtype[MaskType]] | MaskType: ...
+    @mask.setter
+    def mask(self, value: _ArrayLikeBool_co, /) -> None: ...
+    @property
+    def recordmask(self) -> np.ndarray[_ShapeT_co, dtype[MaskType]] | MaskType: ...
+    @recordmask.setter
+    def recordmask(self, mask: Never, /) -> NoReturn: ...
+    def harden_mask(self) -> Self: ...
+    def soften_mask(self) -> Self: ...
+    @property
+    def hardmask(self) -> bool: ...
+    def unshare_mask(self) -> Self: ...
+    @property
+    def sharedmask(self) -> bool: ...
+    def shrink_mask(self) -> Self: ...
+
+    @property
+    def baseclass(self) -> type[ndarray]: ...
+
+    @property
+    def _data(self) -> ndarray[_ShapeT_co, _DTypeT_co]: ...
+    @property
+    def data(self) -> ndarray[_ShapeT_co, _DTypeT_co]: ...  # type: ignore[override]
+
+    @property  # type: ignore[override]
+    def flat(self) -> MaskedIterator[_ShapeT_co, _DTypeT_co]: ...
+    @flat.setter
+    def flat(self, value: ArrayLike, /) -> None: ...
+
+    @property
+    def fill_value(self: _MaskedArray[_ScalarT]) -> _ScalarT: ...
+    @fill_value.setter
+    def fill_value(self, value: _ScalarLike_co | None = None, /) -> None: ...
+
+    def get_fill_value(self: _MaskedArray[_ScalarT]) -> _ScalarT: ...
+    def set_fill_value(self, /, value: _ScalarLike_co | None = None) -> None: ...
+
+    def filled(self, /, fill_value: _ScalarLike_co | None = None) -> ndarray[_ShapeT_co, _DTypeT_co]: ...
+    def compressed(self) -> ndarray[tuple[int], _DTypeT_co]: ...
+
+    # keep roughly in sync with `ma.core.compress`, but swap the first two arguments
+    @overload  # type: ignore[override]
+    def compress(
+        self,
+        condition: _ArrayLikeBool_co,
+        axis: _ShapeLike | None,
+        out: _ArrayT
+    ) -> _ArrayT: ...
+    @overload
+    def compress(
+        self,
+        condition: _ArrayLikeBool_co,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT
+    ) -> _ArrayT: ...
+    @overload
+    def compress(
+        self,
+        condition: _ArrayLikeBool_co,
+        axis: None = None,
+        out: None = None
+    ) -> MaskedArray[tuple[int], _DTypeT_co]: ...
+    @overload
+    def compress(
+        self,
+        condition: _ArrayLikeBool_co,
+        axis: _ShapeLike | None = None,
+        out: None = None
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    # TODO: How to deal with the non-commutative nature of `==` and `!=`?
+    # xref numpy/numpy#17368
+    def __eq__(self, other: Incomplete, /) -> Incomplete: ...
+    def __ne__(self, other: Incomplete, /) -> Incomplete: ...
+
+    def __ge__(self, other: ArrayLike, /) -> _MaskedArray[bool_]: ...  # type: ignore[override]
+    def __gt__(self, other: ArrayLike, /) -> _MaskedArray[bool_]: ...  # type: ignore[override]
+    def __le__(self, other: ArrayLike, /) -> _MaskedArray[bool_]: ...  # type: ignore[override]
+    def __lt__(self, other: ArrayLike, /) -> _MaskedArray[bool_]: ...  # type: ignore[override]
+
+    # Keep in sync with `ndarray.__add__`
+    @overload  # type: ignore[override]
+    def __add__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __add__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __add__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __add__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __add__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __add__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __add__(self: _MaskedArrayTD64_co, other: _ArrayLikeTD64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __add__(self: _MaskedArrayTD64_co, other: _ArrayLikeDT64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __add__(self: _MaskedArray[datetime64], other: _ArrayLikeTD64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __add__(self: _MaskedArray[bytes_], other: _ArrayLikeBytes_co, /) -> _MaskedArray[bytes_]: ...
+    @overload
+    def __add__(self: _MaskedArray[str_], other: _ArrayLikeStr_co, /) -> _MaskedArray[str_]: ...
+    @overload
+    def __add__(
+        self: MaskedArray[Any, dtypes.StringDType],
+        other: _ArrayLikeStr_co | _ArrayLikeString_co,
+        /,
+    ) -> MaskedArray[_AnyShape, dtypes.StringDType]: ...
+    @overload
+    def __add__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __add__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__radd__`
+    @overload  # type: ignore[override]  # signature equivalent to __add__
+    def __radd__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __radd__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __radd__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __radd__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __radd__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __radd__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __radd__(self: _MaskedArrayTD64_co, other: _ArrayLikeTD64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __radd__(self: _MaskedArrayTD64_co, other: _ArrayLikeDT64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __radd__(self: _MaskedArray[datetime64], other: _ArrayLikeTD64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __radd__(self: _MaskedArray[bytes_], other: _ArrayLikeBytes_co, /) -> _MaskedArray[bytes_]: ...
+    @overload
+    def __radd__(self: _MaskedArray[str_], other: _ArrayLikeStr_co, /) -> _MaskedArray[str_]: ...
+    @overload
+    def __radd__(
+        self: MaskedArray[Any, dtypes.StringDType],
+        other: _ArrayLikeStr_co | _ArrayLikeString_co,
+        /,
+    ) -> MaskedArray[_AnyShape, dtypes.StringDType]: ...
+    @overload
+    def __radd__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __radd__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__sub__`
+    @overload  # type: ignore[override]
+    def __sub__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __sub__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> NoReturn: ...
+    @overload
+    def __sub__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __sub__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __sub__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __sub__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __sub__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __sub__(self: _MaskedArrayTD64_co, other: _ArrayLikeTD64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __sub__(self: _MaskedArray[datetime64], other: _ArrayLikeTD64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __sub__(self: _MaskedArray[datetime64], other: _ArrayLikeDT64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __sub__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __sub__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__rsub__`
+    @overload  # type: ignore[override]
+    def __rsub__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __rsub__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> NoReturn: ...
+    @overload
+    def __rsub__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rsub__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rsub__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rsub__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rsub__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rsub__(self: _MaskedArrayTD64_co, other: _ArrayLikeTD64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rsub__(self: _MaskedArrayTD64_co, other: _ArrayLikeDT64_co, /) -> _MaskedArray[datetime64]: ...
+    @overload
+    def __rsub__(self: _MaskedArray[datetime64], other: _ArrayLikeDT64_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rsub__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __rsub__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__mul__`
+    @overload  # type: ignore[override]
+    def __mul__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __mul__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __mul__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __mul__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __mul__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __mul__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __mul__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __mul__(self: _MaskedArray[timedelta64], other: _ArrayLikeFloat_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __mul__(self: _MaskedArrayFloat_co, other: _ArrayLike[timedelta64], /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __mul__(
+        self: MaskedArray[Any, dtype[character] | dtypes.StringDType],
+        other: _ArrayLikeInt,
+        /,
+    ) -> MaskedArray[tuple[Any, ...], _DTypeT_co]: ...
+    @overload
+    def __mul__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __mul__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__rmul__`
+    @overload  # type: ignore[override]  # signature equivalent to __mul__
+    def __rmul__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __rmul__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[np.bool]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rmul__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rmul__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rmul__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rmul__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rmul__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __rmul__(self: _MaskedArray[timedelta64], other: _ArrayLikeFloat_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rmul__(self: _MaskedArrayFloat_co, other: _ArrayLike[timedelta64], /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rmul__(
+        self: MaskedArray[Any, dtype[character] | dtypes.StringDType],
+        other: _ArrayLikeInt,
+        /,
+    ) -> MaskedArray[tuple[Any, ...], _DTypeT_co]: ...
+    @overload
+    def __rmul__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __rmul__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__truediv__`
+    @overload  # type: ignore[override]
+    def __truediv__(self: _MaskedArrayInt_co | _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __truediv__(self: _MaskedArrayFloat64_co, other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __truediv__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[floating], other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...
+    @overload
+    def __truediv__(self: _MaskedArrayFloat_co, other: _ArrayLike[floating], /) -> _MaskedArray[floating]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[complexfloating], other: _ArrayLikeNumber_co, /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __truediv__(self: _MaskedArrayNumber_co, other: _ArrayLike[complexfloating], /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[inexact], other: _ArrayLikeNumber_co, /) -> _MaskedArray[inexact]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[timedelta64], other: _ArrayLike[timedelta64], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[timedelta64], other: _ArrayLikeBool_co, /) -> NoReturn: ...
+    @overload
+    def __truediv__(self: _MaskedArray[timedelta64], other: _ArrayLikeFloat_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __truediv__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __truediv__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__rtruediv__`
+    @overload  # type: ignore[override]
+    def __rtruediv__(self: _MaskedArrayInt_co | _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArrayFloat64_co, other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[floating], other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArrayFloat_co, other: _ArrayLike[floating], /) -> _MaskedArray[floating]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[complexfloating], other: _ArrayLikeNumber_co, /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArrayNumber_co, other: _ArrayLike[complexfloating], /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[inexact], other: _ArrayLikeNumber_co, /) -> _MaskedArray[inexact]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[timedelta64], other: _ArrayLike[timedelta64], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[integer | floating], other: _ArrayLike[timedelta64], /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __rtruediv__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__floordiv__`
+    @overload  # type: ignore[override]
+    def __floordiv__(self: _MaskedArray[_RealNumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_RealNumberT]]: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_RealNumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __floordiv__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[int8]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __floordiv__(self: _MaskedArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> _MaskedArray[_RealNumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __floordiv__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __floordiv__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __floordiv__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __floordiv__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __floordiv__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[timedelta64], other: _ArrayLike[timedelta64], /) -> _MaskedArray[int64]: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[timedelta64], other: _ArrayLikeBool_co, /) -> NoReturn: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[timedelta64], other: _ArrayLikeFloat_co, /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __floordiv__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__rfloordiv__`
+    @overload  # type: ignore[override]
+    def __rfloordiv__(self: _MaskedArray[_RealNumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_RealNumberT]]: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArray[_RealNumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_RealNumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[int8]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArray[np.bool], other: _ArrayLike[_RealNumberT], /) -> _MaskedArray[_RealNumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rfloordiv__(self: _MaskedArray[timedelta64], other: _ArrayLike[timedelta64], /) -> _MaskedArray[int64]: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArray[floating | integer], other: _ArrayLike[timedelta64], /) -> _MaskedArray[timedelta64]: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __rfloordiv__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__pow__` (minus the `mod` parameter)
+    @overload  # type: ignore[override]
+    def __pow__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __pow__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[int8]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __pow__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __pow__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __pow__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __pow__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __pow__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __pow__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __pow__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __pow__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    # Keep in sync with `ndarray.__rpow__` (minus the `mod` parameter)
+    @overload  # type: ignore[override]
+    def __rpow__(self: _MaskedArray[_NumberT], other: int | np.bool, /) -> MaskedArray[_ShapeT_co, dtype[_NumberT]]: ...
+    @overload
+    def __rpow__(self: _MaskedArray[_NumberT], other: _ArrayLikeBool_co, /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArray[np.bool], other: _ArrayLikeBool_co, /) -> _MaskedArray[int8]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArray[np.bool], other: _ArrayLike[_NumberT], /) -> _MaskedArray[_NumberT]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArray[float64], other: _ArrayLikeFloat64_co, /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rpow__(self: _MaskedArrayFloat64_co, other: _ArrayLike[floating[_64Bit]], /) -> _MaskedArray[float64]: ...
+    @overload
+    def __rpow__(self: _MaskedArray[complex128], other: _ArrayLikeComplex128_co, /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rpow__(self: _MaskedArrayComplex128_co, other: _ArrayLike[complexfloating[_64Bit]], /) -> _MaskedArray[complex128]: ...
+    @overload
+    def __rpow__(self: _MaskedArrayUInt_co, other: _ArrayLikeUInt_co, /) -> _MaskedArray[unsignedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArrayInt_co, other: _ArrayLikeInt_co, /) -> _MaskedArray[signedinteger]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArrayFloat_co, other: _ArrayLikeFloat_co, /) -> _MaskedArray[floating]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __rpow__(self: _MaskedArrayComplex_co, other: _ArrayLikeComplex_co, /) -> _MaskedArray[complexfloating]: ...
+    @overload
+    def __rpow__(self: _MaskedArray[number], other: _ArrayLikeNumber_co, /) -> _MaskedArray[number]: ...
+    @overload
+    def __rpow__(self: _MaskedArray[object_], other: Any, /) -> Any: ...
+    @overload
+    def __rpow__(self: _MaskedArray[Any], other: _ArrayLikeObject_co, /) -> Any: ...
+
+    #
+    @property  # type: ignore[misc]
+    def imag(self: _HasDTypeWithRealAndImag[object, _ScalarT], /) -> MaskedArray[_ShapeT_co, dtype[_ScalarT]]: ...  # type: ignore[override]
+    def get_imag(self: _HasDTypeWithRealAndImag[object, _ScalarT], /) -> MaskedArray[_ShapeT_co, dtype[_ScalarT]]: ...
+
+    #
+    @property  # type: ignore[misc]
+    def real(self: _HasDTypeWithRealAndImag[_ScalarT, object], /) -> MaskedArray[_ShapeT_co, dtype[_ScalarT]]: ...  # type: ignore[override]
+    def get_real(self: _HasDTypeWithRealAndImag[_ScalarT, object], /) -> MaskedArray[_ShapeT_co, dtype[_ScalarT]]: ...
+
+    # keep in sync with `np.ma.count`
+    @overload
+    def count(self, axis: None = None, keepdims: Literal[False] | _NoValueType = ...) -> int: ...
+    @overload
+    def count(self, axis: _ShapeLike, keepdims: bool | _NoValueType = ...) -> NDArray[int_]: ...
+    @overload
+    def count(self, axis: _ShapeLike | None = None, *, keepdims: Literal[True]) -> NDArray[int_]: ...
+    @overload
+    def count(self, axis: _ShapeLike | None, keepdims: Literal[True]) -> NDArray[int_]: ...
+
+    # Keep in sync with `ndarray.reshape`
+    # NOTE: reshape also accepts negative integers, so we can't use integer literals
+    @overload  # (None)
+    def reshape(self, shape: None, /, *, order: _OrderACF = "C", copy: bool | None = None) -> Self: ...
+    @overload  # (empty_sequence)
+    def reshape(  # type: ignore[overload-overlap]  # mypy false positive
+        self,
+        shape: Sequence[Never],
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[tuple[()], _DTypeT_co]: ...
+    @overload  # (() | (int) | (int, int) | ....)  # up to 8-d
+    def reshape(
+        self,
+        shape: _AnyShapeT,
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[_AnyShapeT, _DTypeT_co]: ...
+    @overload  # (index)
+    def reshape(
+        self,
+        size1: SupportsIndex,
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[tuple[int], _DTypeT_co]: ...
+    @overload  # (index, index)
+    def reshape(
+        self,
+        size1: SupportsIndex,
+        size2: SupportsIndex,
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[tuple[int, int], _DTypeT_co]: ...
+    @overload  # (index, index, index)
+    def reshape(
+        self,
+        size1: SupportsIndex,
+        size2: SupportsIndex,
+        size3: SupportsIndex,
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[tuple[int, int, int], _DTypeT_co]: ...
+    @overload  # (index, index, index, index)
+    def reshape(
+        self,
+        size1: SupportsIndex,
+        size2: SupportsIndex,
+        size3: SupportsIndex,
+        size4: SupportsIndex,
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[tuple[int, int, int, int], _DTypeT_co]: ...
+    @overload  # (int, *(index, ...))
+    def reshape(
+        self,
+        size0: SupportsIndex,
+        /,
+        *shape: SupportsIndex,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+    @overload  # (sequence[index])
+    def reshape(
+        self,
+        shape: Sequence[SupportsIndex],
+        /,
+        *,
+        order: _OrderACF = "C",
+        copy: bool | None = None,
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    def resize(self, newshape: Never, refcheck: bool = True, order: bool = False) -> NoReturn: ...  # type: ignore[override]
+    def put(self, indices: _ArrayLikeInt_co, values: ArrayLike, mode: _ModeKind = "raise") -> None: ...
+    def ids(self) -> tuple[int, int]: ...
+    def iscontiguous(self) -> bool: ...
+
+    # Keep in sync with `ma.core.all`
+    @overload  # type: ignore[override]
+    def all(
+        self,
+        axis: None = None,
+        out: None = None,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> bool_: ...
+    @overload
+    def all(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        *,
+        keepdims: Literal[True],
+    ) -> _MaskedArray[bool_]: ...
+    @overload
+    def all(
+        self,
+        axis: _ShapeLike | None,
+        out: None,
+        keepdims: Literal[True],
+    ) -> _MaskedArray[bool_]: ...
+    @overload
+    def all(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> bool_ | _MaskedArray[bool_]: ...
+    @overload
+    def all(
+        self,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def all(
+        self,
+        axis: _ShapeLike | None,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # Keep in sync with `ma.core.any`
+    @overload  # type: ignore[override]
+    def any(
+        self,
+        axis: None = None,
+        out: None = None,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> bool_: ...
+    @overload
+    def any(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        *,
+        keepdims: Literal[True],
+    ) -> _MaskedArray[bool_]: ...
+    @overload
+    def any(
+        self,
+        axis: _ShapeLike | None,
+        out: None,
+        keepdims: Literal[True],
+    ) -> _MaskedArray[bool_]: ...
+    @overload
+    def any(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> bool_ | _MaskedArray[bool_]: ...
+    @overload
+    def any(
+        self,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def any(
+        self,
+        axis: _ShapeLike | None,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # Keep in sync with `ndarray.trace` and `ma.core.trace`
+    @overload
+    def trace(
+        self,  # >= 2D MaskedArray
+        offset: SupportsIndex = 0,
+        axis1: SupportsIndex = 0,
+        axis2: SupportsIndex = 1,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+    ) -> Any: ...
+    @overload
+    def trace(
+        self,  # >= 2D MaskedArray
+        offset: SupportsIndex = 0,
+        axis1: SupportsIndex = 0,
+        axis2: SupportsIndex = 1,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+    ) -> _ArrayT: ...
+    @overload
+    def trace(
+        self,  # >= 2D MaskedArray
+        offset: SupportsIndex,
+        axis1: SupportsIndex,
+        axis2: SupportsIndex,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+    ) -> _ArrayT: ...
+
+    # This differs from `ndarray.dot`, in that 1D dot 1D returns a 0D array.
+    @overload
+    def dot(self, b: ArrayLike, out: None = None, strict: bool = False) -> _MaskedArray[Any]: ...
+    @overload
+    def dot(self, b: ArrayLike, out: _ArrayT, strict: bool = False) -> _ArrayT: ...
+
+    # Keep in sync with `ma.core.sum`
+    @overload  # type: ignore[override]
+    def sum(
+        self,
+        /,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def sum(
+        self,
+        /,
+        axis: _ShapeLike | None,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def sum(
+        self,
+        /,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # Keep in sync with `ndarray.cumsum` and `ma.core.cumsum`
+    @overload  # out: None (default)
+    def cumsum(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None) -> _MaskedArray[Any]: ...
+    @overload  # out: ndarray
+    def cumsum(self, /, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def cumsum(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
+
+    # Keep in sync with `ma.core.prod`
+    @overload  # type: ignore[override]
+    def prod(
+        self,
+        /,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def prod(
+        self,
+        /,
+        axis: _ShapeLike | None,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def prod(
+        self,
+        /,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    product = prod
+
+    # Keep in sync with `ndarray.cumprod` and `ma.core.cumprod`
+    @overload  # out: None (default)
+    def cumprod(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None) -> _MaskedArray[Any]: ...
+    @overload  # out: ndarray
+    def cumprod(self, /, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def cumprod(self, /, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
+
+    # Keep in sync with `ma.core.mean`
+    @overload  # type: ignore[override]
+    def mean(
+        self,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def mean(
+        self,
+        /,
+        axis: _ShapeLike | None,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def mean(
+        self,
+        /,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # keep roughly in sync with `ma.core.anom`
+    @overload
+    def anom(self, axis: SupportsIndex | None = None, dtype: None = None) -> Self: ...
+    @overload
+    def anom(self, axis: SupportsIndex | None = None, *, dtype: DTypeLike) -> MaskedArray[_ShapeT_co, dtype]: ...
+    @overload
+    def anom(self, axis: SupportsIndex | None, dtype: DTypeLike) -> MaskedArray[_ShapeT_co, dtype]: ...
+
+    # keep in sync with `std` and `ma.core.var`
+    @overload  # type: ignore[override]
+    def var(
+        self,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def var(
+        self,
+        axis: _ShapeLike | None,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def var(
+        self,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # keep in sync with `var` and `ma.core.std`
+    @overload  # type: ignore[override]
+    def std(
+        self,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        out: None = None,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def std(
+        self,
+        axis: _ShapeLike | None,
+        dtype: DTypeLike | None,
+        out: _ArrayT,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def std(
+        self,
+        axis: _ShapeLike | None = None,
+        dtype: DTypeLike | None = None,
+        *,
+        out: _ArrayT,
+        ddof: float = 0,
+        keepdims: bool | _NoValueType = ...,
+        mean: _ArrayLikeNumber_co | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # Keep in sync with `ndarray.round`
+    @overload  # out=None (default)
+    def round(self, /, decimals: SupportsIndex = 0, out: None = None) -> Self: ...
+    @overload  # out=ndarray
+    def round(self, /, decimals: SupportsIndex, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def round(self, /, decimals: SupportsIndex = 0, *, out: _ArrayT) -> _ArrayT: ...
+
+    def argsort(  # type: ignore[override]
+        self,
+        axis: SupportsIndex | _NoValueType = ...,
+        kind: _SortKind | None = None,
+        order: str | Sequence[str] | None = None,
+        endwith: bool = True,
+        fill_value: _ScalarLike_co | None = None,
+        *,
+        stable: bool = False,
+    ) -> _MaskedArray[intp]: ...
+
+    # Keep in-sync with np.ma.argmin
+    @overload  # type: ignore[override]
+    def argmin(
+        self,
+        axis: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        out: None = None,
+        *,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> intp: ...
+    @overload
+    def argmin(
+        self,
+        axis: SupportsIndex | None = None,
+        fill_value: _ScalarLike_co | None = None,
+        out: None = None,
+        *,
+        keepdims: bool | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def argmin(
+        self,
+        axis: SupportsIndex | None = None,
+        fill_value: _ScalarLike_co | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def argmin(
+        self,
+        axis: SupportsIndex | None,
+        fill_value: _ScalarLike_co | None,
+        out: _ArrayT,
+        *,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    # Keep in-sync with np.ma.argmax
+    @overload  # type: ignore[override]
+    def argmax(
+        self,
+        axis: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        out: None = None,
+        *,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> intp: ...
+    @overload
+    def argmax(
+        self,
+        axis: SupportsIndex | None = None,
+        fill_value: _ScalarLike_co | None = None,
+        out: None = None,
+        *,
+        keepdims: bool | _NoValueType = ...,
+    ) -> Any: ...
+    @overload
+    def argmax(
+        self,
+        axis: SupportsIndex | None = None,
+        fill_value: _ScalarLike_co | None = None,
+        *,
+        out: _ArrayT,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def argmax(
+        self,
+        axis: SupportsIndex | None,
+        fill_value: _ScalarLike_co | None,
+        out: _ArrayT,
+        *,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    #
+    def sort(  # type: ignore[override]
+        self,
+        axis: SupportsIndex = -1,
+        kind: _SortKind | None = None,
+        order: str | Sequence[str] | None = None,
+        endwith: bool | None = True,
+        fill_value: _ScalarLike_co | None = None,
+        *,
+        stable: Literal[False] | None = False,
+    ) -> None: ...
+
+    #
+    @overload  # type: ignore[override]
+    def min(
+        self: _MaskedArray[_ScalarT],
+        axis: None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> _ScalarT: ...
+    @overload
+    def min(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...
+    ) -> Any: ...
+    @overload
+    def min(
+        self,
+        axis: _ShapeLike | None,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def min(
+        self,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    #
+    @overload  # type: ignore[override]
+    def max(
+        self: _MaskedArray[_ScalarT],
+        axis: None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: Literal[False] | _NoValueType = ...,
+    ) -> _ScalarT: ...
+    @overload
+    def max(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...
+    ) -> Any: ...
+    @overload
+    def max(
+        self,
+        axis: _ShapeLike | None,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+    @overload
+    def max(
+        self,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool | _NoValueType = ...,
+    ) -> _ArrayT: ...
+
+    #
+    @overload
+    def ptp(
+        self: _MaskedArray[_ScalarT],
+        axis: None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: Literal[False] = False,
+    ) -> _ScalarT: ...
+    @overload
+    def ptp(
+        self,
+        axis: _ShapeLike | None = None,
+        out: None = None,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool = False,
+    ) -> Any: ...
+    @overload
+    def ptp(
+        self,
+        axis: _ShapeLike | None,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool = False,
+    ) -> _ArrayT: ...
+    @overload
+    def ptp(
+        self,
+        axis: _ShapeLike | None = None,
+        *,
+        out: _ArrayT,
+        fill_value: _ScalarLike_co | None = None,
+        keepdims: bool = False,
+    ) -> _ArrayT: ...
+
+    #
+    @overload
+    def partition(
+        self,
+        /,
+        kth: _ArrayLikeInt,
+        axis: SupportsIndex = -1,
+        kind: _PartitionKind = "introselect",
+        order: None = None
+    ) -> None: ...
+    @overload
+    def partition(
+        self: _MaskedArray[np.void],
+        /,
+        kth: _ArrayLikeInt,
+        axis: SupportsIndex = -1,
+        kind: _PartitionKind = "introselect",
+        order: str | Sequence[str] | None = None,
+    ) -> None: ...
+
+    #
+    @overload
+    def argpartition(
+        self,
+        /,
+        kth: _ArrayLikeInt,
+        axis: SupportsIndex | None = -1,
+        kind: _PartitionKind = "introselect",
+        order: None = None,
+    ) -> _MaskedArray[intp]: ...
+    @overload
+    def argpartition(
+        self: _MaskedArray[np.void],
+        /,
+        kth: _ArrayLikeInt,
+        axis: SupportsIndex | None = -1,
+        kind: _PartitionKind = "introselect",
+        order: str | Sequence[str] | None = None,
+    ) -> _MaskedArray[intp]: ...
+
+    # Keep in-sync with np.ma.take
+    @overload  # type: ignore[override]
+    def take(  # type: ignore[overload-overlap]
+        self: _MaskedArray[_ScalarT],
+        indices: _IntLike_co,
+        axis: None = None,
+        out: None = None,
+        mode: _ModeKind = "raise"
+    ) -> _ScalarT: ...
+    @overload
+    def take(
+        self: _MaskedArray[_ScalarT],
+        indices: _ArrayLikeInt_co,
+        axis: SupportsIndex | None = None,
+        out: None = None,
+        mode: _ModeKind = "raise",
+    ) -> _MaskedArray[_ScalarT]: ...
+    @overload
+    def take(
+        self,
+        indices: _ArrayLikeInt_co,
+        axis: SupportsIndex | None,
+        out: _ArrayT,
+        mode: _ModeKind = "raise",
+    ) -> _ArrayT: ...
+    @overload
+    def take(
+        self,
+        indices: _ArrayLikeInt_co,
+        axis: SupportsIndex | None = None,
+        *,
+        out: _ArrayT,
+        mode: _ModeKind = "raise",
+    ) -> _ArrayT: ...
+
+    # keep in sync with `ndarray.diagonal`
+    @override
+    def diagonal(
+        self,
+        /,
+        offset: SupportsIndex = 0,
+        axis1: SupportsIndex = 0,
+        axis2: SupportsIndex = 1,
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    # keep in sync with `ndarray.repeat`
+    @override
+    @overload
+    def repeat(
+        self,
+        /,
+        repeats: _ArrayLikeInt_co,
+        axis: None = None,
+    ) -> MaskedArray[tuple[int], _DTypeT_co]: ...
+    @overload
+    def repeat(
+        self,
+        /,
+        repeats: _ArrayLikeInt_co,
+        axis: SupportsIndex,
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    # keep in sync with `ndarray.flatten` and `ndarray.ravel`
+    @override
+    def flatten(self, /, order: _OrderKACF = "C") -> MaskedArray[tuple[int], _DTypeT_co]: ...
+    @override
+    def ravel(self, order: _OrderKACF = "C") -> MaskedArray[tuple[int], _DTypeT_co]: ...
+
+    # keep in sync with `ndarray.squeeze`
+    @override
+    def squeeze(
+        self,
+        /,
+        axis: SupportsIndex | tuple[SupportsIndex, ...] | None = None,
+    ) -> MaskedArray[_AnyShape, _DTypeT_co]: ...
+
+    #
+    def toflex(self) -> MaskedArray[_ShapeT_co, np.dtype[np.void]]: ...
+    def torecords(self) -> MaskedArray[_ShapeT_co, np.dtype[np.void]]: ...
+
+    #
+    @override
+    def tobytes(self, /, fill_value: Incomplete | None = None, order: _OrderKACF = "C") -> bytes: ...  # type: ignore[override]
+
+    # keep in sync with `ndarray.tolist`
+    @override
+    @overload
+    def tolist(self: MaskedArray[tuple[Never], dtype[generic[_T]]], /, fill_value: _ScalarLike_co | None = None) -> Any: ...
+    @overload
+    def tolist(self: MaskedArray[tuple[()], dtype[generic[_T]]], /, fill_value: _ScalarLike_co | None = None) -> _T: ...
+    @overload
+    def tolist(self: MaskedArray[tuple[int], dtype[generic[_T]]], /, fill_value: _ScalarLike_co | None = None) -> list[_T]: ...
+    @overload
+    def tolist(
+        self: MaskedArray[tuple[int, int], dtype[generic[_T]]], /, fill_value: _ScalarLike_co | None = None
+    ) -> list[list[_T]]: ...
+    @overload
+    def tolist(
+        self: MaskedArray[tuple[int, int, int], dtype[generic[_T]]], /, fill_value: _ScalarLike_co | None = None
+    ) -> list[list[list[_T]]]: ...
+    @overload
+    def tolist(self, /, fill_value: _ScalarLike_co | None = None) -> Any: ...
+
+    # NOTE: will raise `NotImplementedError`
+    @override
+    def tofile(self, /, fid: Never, sep: str = "", format: str = "%s") -> NoReturn: ...  # type: ignore[override]
+
+    #
+    @override
+    def __deepcopy__(self, memo: dict[int, Any] | None = None) -> Self: ...
+
+    # Keep `dtype` at the bottom to avoid name conflicts with `np.dtype`
+    @property
+    def dtype(self) -> _DTypeT_co: ...
+    @dtype.setter
+    def dtype(self: MaskedArray[_AnyShape, _DTypeT], dtype: _DTypeT, /) -> None: ...
+
+class mvoid(MaskedArray[_ShapeT_co, _DTypeT_co]):
+    def __new__(
+        self,  # pyright: ignore[reportSelfClsParameterName]
+        data,
+        mask=...,
+        dtype=...,
+        fill_value=...,
+        hardmask=...,
+        copy=...,
+        subok=...,
+    ): ...
+    def __getitem__(self, indx): ...
+    def __setitem__(self, indx, value): ...
+    def __iter__(self): ...
+    def __len__(self): ...
+    def filled(self, fill_value=None): ...
+    def tolist(self): ...  # type: ignore[override]
+
+def isMaskedArray(x: object) -> TypeIs[MaskedArray]: ...
+def isarray(x: object) -> TypeIs[MaskedArray]: ...  # alias to isMaskedArray
+def isMA(x: object) -> TypeIs[MaskedArray]: ...  # alias to isMaskedArray
+
+# 0D float64 array
+class MaskedConstant(MaskedArray[tuple[()], dtype[float64]]):
+    def __new__(cls) -> Self: ...
+
+    # these overrides are no-ops
+    @override
+    def __iadd__(self, other: _Ignored, /) -> Self: ...  # type: ignore[override]
+    @override
+    def __isub__(self, other: _Ignored, /) -> Self: ...  # type: ignore[override]
+    @override
+    def __imul__(self, other: _Ignored, /) -> Self: ...  # type: ignore[override]
+    @override
+    def __ifloordiv__(self, other: _Ignored, /) -> Self: ...
+    @override
+    def __itruediv__(self, other: _Ignored, /) -> Self: ...  # type: ignore[override]
+    @override
+    def __ipow__(self, other: _Ignored, /) -> Self: ...  # type: ignore[override]
+    @override
+    def __deepcopy__(self, /, memo: _Ignored) -> Self: ...  # type: ignore[override]
+    @override
+    def copy(self, /, *args: _Ignored, **kwargs: _Ignored) -> Self: ...
+
+masked: Final[MaskedConstant] = ...
+masked_singleton: Final[MaskedConstant] = ...
+
+masked_array: TypeAlias = MaskedArray
+
+# keep in sync with `MaskedArray.__new__`
+@overload
+def array(
+    data: _ArrayLike[_ScalarT],
+    dtype: None = None,
+    copy: bool = False,
+    order: _OrderKACF | None = None,
+    mask: _ArrayLikeBool_co = nomask,
+    fill_value: _ScalarLike_co | None = None,
+    keep_mask: bool = True,
+    hard_mask: bool = False,
+    shrink: bool = True,
+    subok: bool = True,
+    ndmin: int = 0,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def array(
+    data: object,
+    dtype: _DTypeLike[_ScalarT],
+    copy: bool = False,
+    order: _OrderKACF | None = None,
+    mask: _ArrayLikeBool_co = nomask,
+    fill_value: _ScalarLike_co | None = None,
+    keep_mask: bool = True,
+    hard_mask: bool = False,
+    shrink: bool = True,
+    subok: bool = True,
+    ndmin: int = 0,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def array(
+    data: object,
+    dtype: DTypeLike | None = None,
+    copy: bool = False,
+    order: _OrderKACF | None = None,
+    mask: _ArrayLikeBool_co = nomask,
+    fill_value: _ScalarLike_co | None = None,
+    keep_mask: bool = True,
+    hard_mask: bool = False,
+    shrink: bool = True,
+    subok: bool = True,
+    ndmin: int = 0,
+) -> _MaskedArray[_ScalarT]: ...
+
+# keep in sync with `array`
+@overload
+def asarray(a: _ArrayLike[_ScalarT], dtype: None = None, order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+@overload
+def asarray(a: object, dtype: _DTypeLike[_ScalarT], order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+@overload
+def asarray(a: object, dtype: DTypeLike | None = None, order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+
+# keep in sync with `asarray` (but note the additional first overload)
+@overload
+def asanyarray(a: _MArrayT, dtype: None = None, order: _OrderKACF | None = None) -> _MArrayT: ...
+@overload
+def asanyarray(a: _ArrayLike[_ScalarT], dtype: None = None, order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+@overload
+def asanyarray(a: object, dtype: _DTypeLike[_ScalarT], order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+@overload
+def asanyarray(a: object, dtype: DTypeLike | None = None, order: _OrderKACF | None = None) -> _MaskedArray[_ScalarT]: ...
+
+#
+def is_masked(x: object) -> bool: ...
+
+@overload
+def min(
+    obj: _ArrayLike[_ScalarT],
+    axis: None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: Literal[False] | _NoValueType = ...,
+) -> _ScalarT: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...
+) -> Any: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def min(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+@overload
+def max(
+    obj: _ArrayLike[_ScalarT],
+    axis: None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: Literal[False] | _NoValueType = ...,
+) -> _ScalarT: ...
+@overload
+def max(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...
+) -> Any: ...
+@overload
+def max(
+    obj: ArrayLike,
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def max(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+@overload
+def ptp(
+    obj: _ArrayLike[_ScalarT],
+    axis: None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: Literal[False] | _NoValueType = ...,
+) -> _ScalarT: ...
+@overload
+def ptp(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    out: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...
+) -> Any: ...
+@overload
+def ptp(
+    obj: ArrayLike,
+    axis: _ShapeLike | None,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def ptp(
+    obj: ArrayLike,
+    axis: _ShapeLike | None = None,
+    *,
+    out: _ArrayT,
+    fill_value: _ScalarLike_co | None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# we cannot meaningfully annotate `frommethod` further, because the callable signature
+# of the return type fully depends on the *value* of `methodname` and `reversed` in
+# a way that cannot be expressed in the Python type system.
+def _frommethod(methodname: str, reversed: bool = False) -> types.FunctionType: ...
+
+# NOTE: The following `*_mask` functions will accept any array-like input runtime, but
+# since their use-cases are specific to masks, they only accept `MaskedArray` inputs.
+
+# keep in sync with `MaskedArray.harden_mask`
+def harden_mask(a: _MArrayT) -> _MArrayT: ...
+# keep in sync with `MaskedArray.soften_mask`
+def soften_mask(a: _MArrayT) -> _MArrayT: ...
+# keep in sync with `MaskedArray.shrink_mask`
+def shrink_mask(a: _MArrayT) -> _MArrayT: ...
+
+# keep in sync with `MaskedArray.ids`
+def ids(a: ArrayLike) -> tuple[int, int]: ...
+
+# keep in sync with `ndarray.nonzero`
+def nonzero(a: ArrayLike) -> tuple[ndarray[tuple[int], np.dtype[intp]], ...]: ...
+
+# keep first overload in sync with `MaskedArray.ravel`
+@overload
+def ravel(a: np.ndarray[Any, _DTypeT], order: _OrderKACF = "C") -> MaskedArray[tuple[int], _DTypeT]: ...
+@overload
+def ravel(a: _ArrayLike[_ScalarT], order: _OrderKACF = "C") -> MaskedArray[tuple[int], np.dtype[_ScalarT]]: ...
+@overload
+def ravel(a: ArrayLike, order: _OrderKACF = "C") -> MaskedArray[tuple[int], _DTypeT_co]: ...
+
+# keep roughly in sync with `lib._function_base_impl.copy`
+@overload
+def copy(a: _MArrayT, order: _OrderKACF = "C") -> _MArrayT: ...
+@overload
+def copy(a: np.ndarray[_ShapeT, _DTypeT], order: _OrderKACF = "C") -> MaskedArray[_ShapeT, _DTypeT]: ...
+@overload
+def copy(a: _ArrayLike[_ScalarT], order: _OrderKACF = "C") -> _MaskedArray[_ScalarT]: ...
+@overload
+def copy(a: ArrayLike, order: _OrderKACF = "C") -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with `_core.fromnumeric.diagonal`
+@overload
+def diagonal(
+    a: _ArrayLike[_ScalarT],
+    offset: SupportsIndex = 0,
+    axis1: SupportsIndex = 0,
+    axis2: SupportsIndex = 1,
+) -> NDArray[_ScalarT]: ...
+@overload
+def diagonal(
+    a: ArrayLike,
+    offset: SupportsIndex = 0,
+    axis1: SupportsIndex = 0,
+    axis2: SupportsIndex = 1,
+) -> NDArray[Incomplete]: ...
+
+# keep in sync with `_core.fromnumeric.repeat`
+@overload
+def repeat(a: _ArrayLike[_ScalarT], repeats: _ArrayLikeInt_co, axis: None = None) -> MaskedArray[tuple[int], dtype[_ScalarT]]: ...
+@overload
+def repeat(a: _ArrayLike[_ScalarT], repeats: _ArrayLikeInt_co, axis: SupportsIndex) -> _MaskedArray[_ScalarT]: ...
+@overload
+def repeat(a: ArrayLike, repeats: _ArrayLikeInt_co, axis: None = None) -> MaskedArray[tuple[int], dtype[Incomplete]]: ...
+@overload
+def repeat(a: ArrayLike, repeats: _ArrayLikeInt_co, axis: SupportsIndex) -> _MaskedArray[Incomplete]: ...
+
+# keep in sync with `_core.fromnumeric.swapaxes`
+@overload
+def swapaxes(a: _MArrayT, axis1: SupportsIndex, axis2: SupportsIndex) -> _MArrayT: ...
+@overload
+def swapaxes(a: _ArrayLike[_ScalarT], axis1: SupportsIndex, axis2: SupportsIndex) -> _MaskedArray[_ScalarT]: ...
+@overload
+def swapaxes(a: ArrayLike, axis1: SupportsIndex, axis2: SupportsIndex) -> _MaskedArray[Incomplete]: ...
+
+# NOTE: The `MaskedArray.anom` definition is specific to `MaskedArray`, so we need
+# additional overloads to cover the array-like input here.
+@overload  # a: MaskedArray, dtype=None
+def anom(a: _MArrayT, axis: SupportsIndex | None = None, dtype: None = None) -> _MArrayT: ...
+@overload  # a: array-like, dtype=None
+def anom(a: _ArrayLike[_ScalarT], axis: SupportsIndex | None = None, dtype: None = None) -> _MaskedArray[_ScalarT]: ...
+@overload  # a: unknown array-like, dtype: dtype-like (positional)
+def anom(a: ArrayLike, axis: SupportsIndex | None, dtype: _DTypeLike[_ScalarT]) -> _MaskedArray[_ScalarT]: ...
+@overload  # a: unknown array-like, dtype: dtype-like (keyword)
+def anom(a: ArrayLike, axis: SupportsIndex | None = None, *, dtype: _DTypeLike[_ScalarT]) -> _MaskedArray[_ScalarT]: ...
+@overload  # a: unknown array-like, dtype: unknown dtype-like (positional)
+def anom(a: ArrayLike, axis: SupportsIndex | None, dtype: DTypeLike) -> _MaskedArray[Incomplete]: ...
+@overload  # a: unknown array-like, dtype: unknown dtype-like (keyword)
+def anom(a: ArrayLike, axis: SupportsIndex | None = None, *, dtype: DTypeLike) -> _MaskedArray[Incomplete]: ...
+
+anomalies = anom
+
+# Keep in sync with `any` and `MaskedArray.all`
+@overload
+def all(a: ArrayLike, axis: None = None, out: None = None, keepdims: Literal[False] | _NoValueType = ...) -> np.bool: ...
+@overload
+def all(a: ArrayLike, axis: _ShapeLike | None, out: None, keepdims: Literal[True]) -> _MaskedArray[np.bool]: ...
+@overload
+def all(a: ArrayLike, axis: _ShapeLike | None = None, out: None = None, *, keepdims: Literal[True]) -> _MaskedArray[np.bool]: ...
+@overload
+def all(
+    a: ArrayLike, axis: _ShapeLike | None = None, out: None = None, keepdims: bool | _NoValueType = ...
+) -> np.bool | _MaskedArray[np.bool]: ...
+@overload
+def all(a: ArrayLike, axis: _ShapeLike | None, out: _ArrayT, keepdims: bool | _NoValueType = ...) -> _ArrayT: ...
+@overload
+def all(a: ArrayLike, axis: _ShapeLike | None = None, *, out: _ArrayT, keepdims: bool | _NoValueType = ...) -> _ArrayT: ...
+
+# Keep in sync with `all` and `MaskedArray.any`
+@overload
+def any(a: ArrayLike, axis: None = None, out: None = None, keepdims: Literal[False] | _NoValueType = ...) -> np.bool: ...
+@overload
+def any(a: ArrayLike, axis: _ShapeLike | None, out: None, keepdims: Literal[True]) -> _MaskedArray[np.bool]: ...
+@overload
+def any(a: ArrayLike, axis: _ShapeLike | None = None, out: None = None, *, keepdims: Literal[True]) -> _MaskedArray[np.bool]: ...
+@overload
+def any(
+    a: ArrayLike, axis: _ShapeLike | None = None, out: None = None, keepdims: bool | _NoValueType = ...
+) -> np.bool | _MaskedArray[np.bool]: ...
+@overload
+def any(a: ArrayLike, axis: _ShapeLike | None, out: _ArrayT, keepdims: bool | _NoValueType = ...) -> _ArrayT: ...
+@overload
+def any(a: ArrayLike, axis: _ShapeLike | None = None, *, out: _ArrayT, keepdims: bool | _NoValueType = ...) -> _ArrayT: ...
+
+# NOTE: The `MaskedArray.compress` definition uses its `DTypeT_co` type parameter,
+# which wouldn't work here for array-like inputs, so we need additional overloads.
+@overload
+def compress(
+    condition: _ArrayLikeBool_co, a: _ArrayLike[_ScalarT], axis: None = None, out: None = None
+) -> MaskedArray[tuple[int], np.dtype[_ScalarT]]: ...
+@overload
+def compress(
+    condition: _ArrayLikeBool_co, a: _ArrayLike[_ScalarT], axis: _ShapeLike | None = None, out: None = None
+) -> MaskedArray[_AnyShape, np.dtype[_ScalarT]]: ...
+@overload
+def compress(condition: _ArrayLikeBool_co, a: ArrayLike, axis: None = None, out: None = None) -> MaskedArray[tuple[int]]: ...
+@overload
+def compress(
+    condition: _ArrayLikeBool_co, a: ArrayLike, axis: _ShapeLike | None = None, out: None = None
+) -> _MaskedArray[Incomplete]: ...
+@overload
+def compress(condition: _ArrayLikeBool_co, a: ArrayLike, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+@overload
+def compress(condition: _ArrayLikeBool_co, a: ArrayLike, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
+
+# Keep in sync with `cumprod` and `MaskedArray.cumsum`
+@overload  # out: None (default)
+def cumsum(
+    a: ArrayLike, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None
+) -> _MaskedArray[Incomplete]: ...
+@overload  # out: ndarray (positional)
+def cumsum(a: ArrayLike, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+@overload  # out: ndarray (kwarg)
+def cumsum(a: ArrayLike, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
+
+# Keep in sync with `cumsum` and `MaskedArray.cumsum`
+@overload  # out: None (default)
+def cumprod(
+    a: ArrayLike, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, out: None = None
+) -> _MaskedArray[Incomplete]: ...
+@overload  # out: ndarray (positional)
+def cumprod(a: ArrayLike, axis: SupportsIndex | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+@overload  # out: ndarray (kwarg)
+def cumprod(a: ArrayLike, axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...
+
+# Keep in sync with `sum`, `prod`, `product`, and `MaskedArray.mean`
+@overload
+def mean(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def mean(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def mean(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# Keep in sync with `mean`, `prod`, `product`, and `MaskedArray.sum`
+@overload
+def sum(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def sum(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def sum(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# Keep in sync with `product` and `MaskedArray.prod`
+@overload
+def prod(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def prod(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def prod(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# Keep in sync with `prod` and `MaskedArray.prod`
+@overload
+def product(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    keepdims: bool | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def product(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def product(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# Keep in sync with `MaskedArray.trace` and `_core.fromnumeric.trace`
+@overload
+def trace(
+    a: ArrayLike,
+    offset: SupportsIndex = 0,
+    axis1: SupportsIndex = 0,
+    axis2: SupportsIndex = 1,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+) -> Incomplete: ...
+@overload
+def trace(
+    a: ArrayLike,
+    offset: SupportsIndex,
+    axis1: SupportsIndex,
+    axis2: SupportsIndex,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+) -> _ArrayT: ...
+@overload
+def trace(
+    a: ArrayLike,
+    offset: SupportsIndex = 0,
+    axis1: SupportsIndex = 0,
+    axis2: SupportsIndex = 1,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+) -> _ArrayT: ...
+
+# keep in sync with `std` and `MaskedArray.var`
+@overload
+def std(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def std(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def std(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# keep in sync with `std` and `MaskedArray.var`
+@overload
+def var(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    out: None = None,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> Incomplete: ...
+@overload
+def var(
+    a: ArrayLike,
+    axis: _ShapeLike | None,
+    dtype: DTypeLike | None,
+    out: _ArrayT,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def var(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    dtype: DTypeLike | None = None,
+    *,
+    out: _ArrayT,
+    ddof: float = 0,
+    keepdims: bool | _NoValueType = ...,
+    mean: _ArrayLikeNumber_co | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# (a, b)
+minimum: _extrema_operation = ...
+maximum: _extrema_operation = ...
+
+# NOTE: this is a `_frommethod` instance at runtime
+@overload
+def count(a: ArrayLike, axis: None = None, keepdims: Literal[False] | _NoValueType = ...) -> int: ...
+@overload
+def count(a: ArrayLike, axis: _ShapeLike, keepdims: bool | _NoValueType = ...) -> NDArray[int_]: ...
+@overload
+def count(a: ArrayLike, axis: _ShapeLike | None = None, *, keepdims: Literal[True]) -> NDArray[int_]: ...
+@overload
+def count(a: ArrayLike, axis: _ShapeLike | None, keepdims: Literal[True]) -> NDArray[int_]: ...
+
+# NOTE: this is a `_frommethod` instance at runtime
+@overload
+def argmin(
+    a: ArrayLike,
+    axis: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    out: None = None,
+    *,
+    keepdims: Literal[False] | _NoValueType = ...,
+) -> intp: ...
+@overload
+def argmin(
+    a: ArrayLike,
+    axis: SupportsIndex | None = None,
+    fill_value: _ScalarLike_co | None = None,
+    out: None = None,
+    *,
+    keepdims: bool | _NoValueType = ...,
+) -> Any: ...
+@overload
+def argmin(
+    a: ArrayLike,
+    axis: SupportsIndex | None = None,
+    fill_value: _ScalarLike_co | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def argmin(
+    a: ArrayLike,
+    axis: SupportsIndex | None,
+    fill_value: _ScalarLike_co | None,
+    out: _ArrayT,
+    *,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+# keep in sync with `argmin`
+@overload
+def argmax(
+    a: ArrayLike,
+    axis: None = None,
+    fill_value: _ScalarLike_co | None = None,
+    out: None = None,
+    *,
+    keepdims: Literal[False] | _NoValueType = ...,
+) -> intp: ...
+@overload
+def argmax(
+    a: ArrayLike,
+    axis: SupportsIndex | None = None,
+    fill_value: _ScalarLike_co | None = None,
+    out: None = None,
+    *,
+    keepdims: bool | _NoValueType = ...,
+) -> Any: ...
+@overload
+def argmax(
+    a: ArrayLike,
+    axis: SupportsIndex | None = None,
+    fill_value: _ScalarLike_co | None = None,
+    *,
+    out: _ArrayT,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+@overload
+def argmax(
+    a: ArrayLike,
+    axis: SupportsIndex | None,
+    fill_value: _ScalarLike_co | None,
+    out: _ArrayT,
+    *,
+    keepdims: bool | _NoValueType = ...,
+) -> _ArrayT: ...
+
+@overload
+def take(
+    a: _ArrayLike[_ScalarT],
+    indices: _IntLike_co,
+    axis: None = None,
+    out: None = None,
+    mode: _ModeKind = "raise"
+) -> _ScalarT: ...
+@overload
+def take(
+    a: _ArrayLike[_ScalarT],
+    indices: _ArrayLikeInt_co,
+    axis: SupportsIndex | None = None,
+    out: None = None,
+    mode: _ModeKind = "raise",
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def take(
+    a: ArrayLike,
+    indices: _IntLike_co,
+    axis: SupportsIndex | None = None,
+    out: None = None,
+    mode: _ModeKind = "raise",
+) -> Any: ...
+@overload
+def take(
+    a: ArrayLike,
+    indices: _ArrayLikeInt_co,
+    axis: SupportsIndex | None = None,
+    out: None = None,
+    mode: _ModeKind = "raise",
+) -> _MaskedArray[Any]: ...
+@overload
+def take(
+    a: ArrayLike,
+    indices: _ArrayLikeInt_co,
+    axis: SupportsIndex | None,
+    out: _ArrayT,
+    mode: _ModeKind = "raise",
+) -> _ArrayT: ...
+@overload
+def take(
+    a: ArrayLike,
+    indices: _ArrayLikeInt_co,
+    axis: SupportsIndex | None = None,
+    *,
+    out: _ArrayT,
+    mode: _ModeKind = "raise",
+) -> _ArrayT: ...
+
+def power(a, b, third=None): ...
+def argsort(a, axis=..., kind=None, order=None, endwith=True, fill_value=None, *, stable=None): ...
+@overload
+def sort(
+    a: _ArrayT,
+    axis: SupportsIndex = -1,
+    kind: _SortKind | None = None,
+    order: str | Sequence[str] | None = None,
+    endwith: bool | None = True,
+    fill_value: _ScalarLike_co | None = None,
+    *,
+    stable: Literal[False] | None = None,
+) -> _ArrayT: ...
+@overload
+def sort(
+    a: ArrayLike,
+    axis: SupportsIndex = -1,
+    kind: _SortKind | None = None,
+    order: str | Sequence[str] | None = None,
+    endwith: bool | None = True,
+    fill_value: _ScalarLike_co | None = None,
+    *,
+    stable: Literal[False] | None = None,
+) -> NDArray[Any]: ...
+@overload
+def compressed(x: _ArrayLike[_ScalarT_co]) -> _Array1D[_ScalarT_co]: ...
+@overload
+def compressed(x: ArrayLike) -> _Array1D[Any]: ...
+def concatenate(arrays, axis=0): ...
+def diag(v, k=0): ...
+def left_shift(a, n): ...
+def right_shift(a, n): ...
+def put(a: NDArray[Any], indices: _ArrayLikeInt_co, values: ArrayLike, mode: _ModeKind = "raise") -> None: ...
+def putmask(a: NDArray[Any], mask: _ArrayLikeBool_co, values: ArrayLike) -> None: ...
+def transpose(a, axes=None): ...
+def reshape(a, new_shape, order="C"): ...
+def resize(x, new_shape): ...
+def ndim(obj: ArrayLike) -> int: ...
+def shape(obj): ...
+def size(obj: ArrayLike, axis: SupportsIndex | None = None) -> int: ...
+def diff(a, /, n=1, axis=-1, prepend=..., append=...): ...
+def where(condition, x=..., y=...): ...
+def choose(indices, choices, out=None, mode="raise"): ...
+def round_(a, decimals=0, out=None): ...
+round = round_
+
+def inner(a, b): ...
+innerproduct = inner
+
+def outer(a, b): ...
+outerproduct = outer
+
+def correlate(a, v, mode="valid", propagate_mask=True): ...
+def convolve(a, v, mode="full", propagate_mask=True): ...
+
+def allequal(a: ArrayLike, b: ArrayLike, fill_value: bool = True) -> bool: ...
+
+def allclose(a: ArrayLike, b: ArrayLike, masked_equal: bool = True, rtol: float = 1e-5, atol: float = 1e-8) -> bool: ...
+
+def fromflex(fxarray): ...
+
+def append(a, b, axis=None): ...
+def dot(a, b, strict=False, out=None): ...
+
+# internal wrapper functions for the functions below
+def _convert2ma(
+    funcname: str,
+    np_ret: str,
+    np_ma_ret: str,
+    params: dict[str, Any] | None = None,
+) -> Callable[..., Any]: ...
+
+# keep in sync with `_core.multiarray.arange`
+@overload  # dtype=<known>
+def arange(
+    start_or_stop: _ArangeScalar | float,
+    /,
+    stop: _ArangeScalar | float | None = None,
+    step: _ArangeScalar | float | None = 1,
+    *,
+    dtype: _DTypeLike[_ArangeScalarT],
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[_ArangeScalarT]: ...
+@overload  # (int-like, int-like?, int-like?)
+def arange(
+    start_or_stop: _IntLike_co,
+    /,
+    stop: _IntLike_co | None = None,
+    step: _IntLike_co | None = 1,
+    *,
+    dtype: type[int] | _DTypeLike[np.int_] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.int_]: ...
+@overload  # (float, float-like?, float-like?)
+def arange(
+    start_or_stop: float | floating,
+    /,
+    stop: _FloatLike_co | None = None,
+    step: _FloatLike_co | None = 1,
+    *,
+    dtype: type[float] | _DTypeLike[np.float64] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.float64 | Any]: ...
+@overload  # (float-like, float, float-like?)
+def arange(
+    start_or_stop: _FloatLike_co,
+    /,
+    stop: float | floating,
+    step: _FloatLike_co | None = 1,
+    *,
+    dtype: type[float] | _DTypeLike[np.float64] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.float64 | Any]: ...
+@overload  # (timedelta, timedelta-like?, timedelta-like?)
+def arange(
+    start_or_stop: np.timedelta64,
+    /,
+    stop: _TD64Like_co | None = None,
+    step: _TD64Like_co | None = 1,
+    *,
+    dtype: _DTypeLike[np.timedelta64] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.timedelta64[Incomplete]]: ...
+@overload  # (timedelta-like, timedelta, timedelta-like?)
+def arange(
+    start_or_stop: _TD64Like_co,
+    /,
+    stop: np.timedelta64,
+    step: _TD64Like_co | None = 1,
+    *,
+    dtype: _DTypeLike[np.timedelta64] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.timedelta64[Incomplete]]: ...
+@overload  # (datetime, datetime, timedelta-like) (requires both start and stop)
+def arange(
+    start_or_stop: np.datetime64,
+    /,
+    stop: np.datetime64,
+    step: _TD64Like_co | None = 1,
+    *,
+    dtype: _DTypeLike[np.datetime64] | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.datetime64[Incomplete]]: ...
+@overload  # (str, str, timedelta-like, dtype=dt64-like) (requires both start and stop)
+def arange(
+    start_or_stop: str,
+    /,
+    stop: str,
+    step: _TD64Like_co | None = 1,
+    *,
+    dtype: _DTypeLike[np.datetime64] | _DT64Codes,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[np.datetime64[Incomplete]]: ...
+@overload  # dtype=<unknown>
+def arange(
+    start_or_stop: _ArangeScalar | float | str,
+    /,
+    stop: _ArangeScalar | float | str | None = None,
+    step: _ArangeScalar | float | None = 1,
+    *,
+    dtype: DTypeLike | None = None,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _Masked1D[Incomplete]: ...
+
+# based on `_core.fromnumeric.clip`
+@overload
+def clip(
+    a: _ScalarT,
+    a_min: ArrayLike | _NoValueType | None = ...,
+    a_max: ArrayLike | _NoValueType | None = ...,
+    out: None = None,
+    *,
+    min: ArrayLike | _NoValueType | None = ...,
+    max: ArrayLike | _NoValueType | None = ...,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+    dtype: None = None,
+    **kwargs: Unpack[_UFuncKwargs],
+) -> _ScalarT: ...
+@overload
+def clip(
+    a: NDArray[_ScalarT],
+    a_min: ArrayLike | _NoValueType | None = ...,
+    a_max: ArrayLike | _NoValueType | None = ...,
+    out: None = None,
+    *,
+    min: ArrayLike | _NoValueType | None = ...,
+    max: ArrayLike | _NoValueType | None = ...,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+    dtype: None = None,
+    **kwargs: Unpack[_UFuncKwargs],
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def clip(
+    a: ArrayLike,
+    a_min: ArrayLike | None,
+    a_max: ArrayLike | None,
+    out: _MArrayT,
+    *,
+    min: ArrayLike | _NoValueType | None = ...,
+    max: ArrayLike | _NoValueType | None = ...,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+    dtype: DTypeLike | None = None,
+    **kwargs: Unpack[_UFuncKwargs],
+) -> _MArrayT: ...
+@overload
+def clip(
+    a: ArrayLike,
+    a_min: ArrayLike | _NoValueType | None = ...,
+    a_max: ArrayLike | _NoValueType | None = ...,
+    *,
+    out: _MArrayT,
+    min: ArrayLike | _NoValueType | None = ...,
+    max: ArrayLike | _NoValueType | None = ...,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+    dtype: DTypeLike | None = None,
+    **kwargs: Unpack[_UFuncKwargs],
+) -> _MArrayT: ...
+@overload
+def clip(
+    a: ArrayLike,
+    a_min: ArrayLike | _NoValueType | None = ...,
+    a_max: ArrayLike | _NoValueType | None = ...,
+    out: None = None,
+    *,
+    min: ArrayLike | _NoValueType | None = ...,
+    max: ArrayLike | _NoValueType | None = ...,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+    dtype: DTypeLike | None = None,
+    **kwargs: Unpack[_UFuncKwargs],
+) -> Incomplete: ...
+
+# keep in sync with `_core.multiarray.ones`
+@overload
+def empty(
+    shape: SupportsIndex,
+    dtype: None = None,
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int], np.dtype[np.float64]]: ...
+@overload
+def empty(
+    shape: SupportsIndex,
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int], _DTypeT]: ...
+@overload
+def empty(
+    shape: SupportsIndex,
+    dtype: type[_ScalarT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int], np.dtype[_ScalarT]]: ...
+@overload
+def empty(
+    shape: SupportsIndex,
+    dtype: DTypeLike | None = None,
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int]]: ...
+@overload  # known shape
+def empty(
+    shape: _AnyShapeT,
+    dtype: None = None,
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[_AnyShapeT, np.dtype[np.float64]]: ...
+@overload
+def empty(
+    shape: _AnyShapeT,
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[_AnyShapeT, _DTypeT]: ...
+@overload
+def empty(
+    shape: _AnyShapeT,
+    dtype: type[_ScalarT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[_AnyShapeT, np.dtype[_ScalarT]]: ...
+@overload
+def empty(
+    shape: _AnyShapeT,
+    dtype: DTypeLike | None = None,
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[_AnyShapeT]: ...
+@overload  # unknown shape
+def empty(
+    shape: _ShapeLike,
+    dtype: None = None,
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[np.float64]: ...
+@overload
+def empty(
+    shape: _ShapeLike,
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[_AnyShape, _DTypeT]: ...
+@overload
+def empty(
+    shape: _ShapeLike,
+    dtype: type[_ScalarT],
+    order: _OrderCF = "C",
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def empty(
+    shape: _ShapeLike,
+    dtype: DTypeLike | None = None,
+    *,
+    device: Literal["cpu"] | None = None,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray: ...
+
+# keep in sync with `_core.multiarray.empty_like`
+@overload
+def empty_like(
+    a: _MArrayT,
+    /,
+    dtype: None = None,
+    order: _OrderKACF = "K",
+    subok: bool = True,
+    shape: _ShapeLike | None = None,
+    *,
+    device: Literal["cpu"] | None = None,
+) -> _MArrayT: ...
+@overload
+def empty_like(
+    a: _ArrayLike[_ScalarT],
+    /,
+    dtype: None = None,
+    order: _OrderKACF = "K",
+    subok: bool = True,
+    shape: _ShapeLike | None = None,
+    *,
+    device: Literal["cpu"] | None = None,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def empty_like(
+    a: Incomplete,
+    /,
+    dtype: _DTypeLike[_ScalarT],
+    order: _OrderKACF = "K",
+    subok: bool = True,
+    shape: _ShapeLike | None = None,
+    *,
+    device: Literal["cpu"] | None = None,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def empty_like(
+    a: Incomplete,
+    /,
+    dtype: DTypeLike | None = None,
+    order: _OrderKACF = "K",
+    subok: bool = True,
+    shape: _ShapeLike | None = None,
+    *,
+    device: Literal["cpu"] | None = None,
+) -> _MaskedArray[Incomplete]: ...
+
+# This is a bit of a hack to avoid having to duplicate all those `empty` overloads for
+# `ones` and `zeros`, that relies on the fact that empty/zeros/ones have identical
+# type signatures, but may cause some type-checkers to report incorrect names in case
+# of user errors. Mypy and Pyright seem to handle this just fine.
+ones = empty
+ones_like = empty_like
+zeros = empty
+zeros_like = empty_like
+
+# keep in sync with `_core.multiarray.frombuffer`
+@overload
+def frombuffer(
+    buffer: Buffer,
+    *,
+    count: SupportsIndex = -1,
+    offset: SupportsIndex = 0,
+    like: _SupportsArrayFunc | None = None,
+) -> _MaskedArray[np.float64]: ...
+@overload
+def frombuffer(
+    buffer: Buffer,
+    dtype: _DTypeLike[_ScalarT],
+    count: SupportsIndex = -1,
+    offset: SupportsIndex = 0,
+    *,
+    like: _SupportsArrayFunc | None = None,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def frombuffer(
+    buffer: Buffer,
+    dtype: DTypeLike | None = float,
+    count: SupportsIndex = -1,
+    offset: SupportsIndex = 0,
+    *,
+    like: _SupportsArrayFunc | None = None,
+) -> _MaskedArray[Incomplete]: ...
+
+# keep roughly in sync with `_core.numeric.fromfunction`
+def fromfunction(
+    function: Callable[..., np.ndarray[_ShapeT, _DTypeT]],
+    shape: Sequence[int],
+    *,
+    dtype: DTypeLike | None = float,
+    like: _SupportsArrayFunc | None = None,
+    **kwargs: object,
+) -> MaskedArray[_ShapeT, _DTypeT]: ...
+
+# keep roughly in sync with `_core.numeric.identity`
+@overload
+def identity(
+    n: int,
+    dtype: None = None,
+    *,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int, int], np.dtype[np.float64]]: ...
+@overload
+def identity(
+    n: int,
+    dtype: _DTypeLike[_ScalarT],
+    *,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int, int], np.dtype[_ScalarT]]: ...
+@overload
+def identity(
+    n: int,
+    dtype: DTypeLike | None = None,
+    *,
+    like: _SupportsArrayFunc | None = None,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> MaskedArray[tuple[int, int], np.dtype[Incomplete]]: ...
+
+# keep roughly in sync with `_core.numeric.indices`
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: type[int] = int,
+    sparse: Literal[False] = False,
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[np.intp]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: type[int],
+    sparse: Literal[True],
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> tuple[_MaskedArray[np.intp], ...]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: type[int] = int,
+    *,
+    sparse: Literal[True],
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> tuple[_MaskedArray[np.intp], ...]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: _DTypeLike[_ScalarT],
+    sparse: Literal[False] = False,
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: _DTypeLike[_ScalarT],
+    sparse: Literal[True],
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> tuple[_MaskedArray[_ScalarT], ...]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: DTypeLike | None = int,
+    sparse: Literal[False] = False,
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[Incomplete]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: DTypeLike | None,
+    sparse: Literal[True],
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> tuple[_MaskedArray[Incomplete], ...]: ...
+@overload
+def indices(
+    dimensions: Sequence[int],
+    dtype: DTypeLike | None = int,
+    *,
+    sparse: Literal[True],
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> tuple[_MaskedArray[Incomplete], ...]: ...
+
+# keep roughly in sync with `_core.fromnumeric.squeeze`
+@overload
+def squeeze(
+    a: _ArrayLike[_ScalarT],
+    axis: _ShapeLike | None = None,
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[_ScalarT]: ...
+@overload
+def squeeze(
+    a: ArrayLike,
+    axis: _ShapeLike | None = None,
+    *,
+    fill_value: _FillValue | None = None,
+    hardmask: bool = False,
+) -> _MaskedArray[Incomplete]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/extras.py b/python/user_packages/Python313/site-packages/numpy/ma/extras.py
new file mode 100644
index 0000000000000000000000000000000000000000..82f1b6bcac5a3b39f59a9438d862112670560150
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/extras.py
@@ -0,0 +1,2266 @@
+"""
+Masked arrays add-ons.
+
+A collection of utilities for `numpy.ma`.
+
+:author: Pierre Gerard-Marchant
+:contact: pierregm_at_uga_dot_edu
+
+"""
+__all__ = [
+    'apply_along_axis', 'apply_over_axes', 'atleast_1d', 'atleast_2d',
+    'atleast_3d', 'average', 'clump_masked', 'clump_unmasked', 'column_stack',
+    'compress_cols', 'compress_nd', 'compress_rowcols', 'compress_rows',
+    'count_masked', 'corrcoef', 'cov', 'diagflat', 'dot', 'dstack', 'ediff1d',
+    'flatnotmasked_contiguous', 'flatnotmasked_edges', 'hsplit', 'hstack',
+    'isin', 'in1d', 'intersect1d', 'mask_cols', 'mask_rowcols', 'mask_rows',
+    'masked_all', 'masked_all_like', 'median', 'mr_', 'ndenumerate',
+    'notmasked_contiguous', 'notmasked_edges', 'polyfit', 'row_stack',
+    'setdiff1d', 'setxor1d', 'stack', 'unique', 'union1d', 'vander', 'vstack',
+    ]
+
+import functools
+import itertools
+import warnings
+
+import numpy as np
+from numpy import array as nxarray, ndarray
+from numpy.lib._function_base_impl import _ureduce
+from numpy.lib._index_tricks_impl import AxisConcatenator
+from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+
+from . import core as ma
+from .core import (  # noqa: F401
+    MAError,
+    MaskedArray,
+    add,
+    array,
+    asarray,
+    concatenate,
+    count,
+    dot,
+    filled,
+    get_masked_subclass,
+    getdata,
+    getmask,
+    getmaskarray,
+    make_mask_descr,
+    mask_or,
+    masked,
+    masked_array,
+    nomask,
+    ones,
+    sort,
+    zeros,
+)
+
+
+def issequence(seq):
+    """
+    Is seq a sequence (ndarray, list or tuple)?
+
+    """
+    return isinstance(seq, (ndarray, tuple, list))
+
+
+def count_masked(arr, axis=None):
+    """
+    Count the number of masked elements along the given axis.
+
+    Parameters
+    ----------
+    arr : array_like
+        An array with (possibly) masked elements.
+    axis : int, optional
+        Axis along which to count. If None (default), a flattened
+        version of the array is used.
+
+    Returns
+    -------
+    count : int, ndarray
+        The total number of masked elements (axis=None) or the number
+        of masked elements along each slice of the given axis.
+
+    See Also
+    --------
+    MaskedArray.count : Count non-masked elements.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(9).reshape((3,3))
+    >>> a = np.ma.array(a)
+    >>> a[1, 0] = np.ma.masked
+    >>> a[1, 2] = np.ma.masked
+    >>> a[2, 1] = np.ma.masked
+    >>> a
+    masked_array(
+      data=[[0, 1, 2],
+            [--, 4, --],
+            [6, --, 8]],
+      mask=[[False, False, False],
+            [ True, False,  True],
+            [False,  True, False]],
+      fill_value=999999)
+    >>> np.ma.count_masked(a)
+    3
+
+    When the `axis` keyword is used an array is returned.
+
+    >>> np.ma.count_masked(a, axis=0)
+    array([1, 1, 1])
+    >>> np.ma.count_masked(a, axis=1)
+    array([0, 2, 1])
+
+    """
+    m = getmaskarray(arr)
+    return m.sum(axis)
+
+
+def masked_all(shape, dtype=float):
+    """
+    Empty masked array with all elements masked.
+
+    Return an empty masked array of the given shape and dtype, where all the
+    data are masked.
+
+    Parameters
+    ----------
+    shape : int or tuple of ints
+        Shape of the required MaskedArray, e.g., ``(2, 3)`` or ``2``.
+    dtype : dtype, optional
+        Data type of the output.
+
+    Returns
+    -------
+    a : MaskedArray
+        A masked array with all data masked.
+
+    See Also
+    --------
+    masked_all_like : Empty masked array modelled on an existing array.
+
+    Notes
+    -----
+    Unlike other masked array creation functions (e.g. `numpy.ma.zeros`,
+    `numpy.ma.ones`, `numpy.ma.full`), `masked_all` does not initialize the
+    values of the array, and may therefore be marginally faster. However,
+    the values stored in the newly allocated array are arbitrary. For
+    reproducible behavior, be sure to set each element of the array before
+    reading.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.ma.masked_all((3, 3))
+    masked_array(
+      data=[[--, --, --],
+            [--, --, --],
+            [--, --, --]],
+      mask=[[ True,  True,  True],
+            [ True,  True,  True],
+            [ True,  True,  True]],
+      fill_value=1e+20,
+      dtype=float64)
+
+    The `dtype` parameter defines the underlying data type.
+
+    >>> a = np.ma.masked_all((3, 3))
+    >>> a.dtype
+    dtype('float64')
+    >>> a = np.ma.masked_all((3, 3), dtype=np.int32)
+    >>> a.dtype
+    dtype('int32')
+
+    """
+    a = masked_array(np.empty(shape, dtype),
+                     mask=np.ones(shape, make_mask_descr(dtype)))
+    return a
+
+
+def masked_all_like(arr):
+    """
+    Empty masked array with the properties of an existing array.
+
+    Return an empty masked array of the same shape and dtype as
+    the array `arr`, where all the data are masked.
+
+    Parameters
+    ----------
+    arr : ndarray
+        An array describing the shape and dtype of the required MaskedArray.
+
+    Returns
+    -------
+    a : MaskedArray
+        A masked array with all data masked.
+
+    Raises
+    ------
+    AttributeError
+        If `arr` doesn't have a shape attribute (i.e. not an ndarray)
+
+    See Also
+    --------
+    masked_all : Empty masked array with all elements masked.
+
+    Notes
+    -----
+    Unlike other masked array creation functions (e.g. `numpy.ma.zeros_like`,
+    `numpy.ma.ones_like`, `numpy.ma.full_like`), `masked_all_like` does not
+    initialize the values of the array, and may therefore be marginally
+    faster. However, the values stored in the newly allocated array are
+    arbitrary. For reproducible behavior, be sure to set each element of the
+    array before reading.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.zeros((2, 3), dtype=np.float32)
+    >>> arr
+    array([[0., 0., 0.],
+           [0., 0., 0.]], dtype=float32)
+    >>> np.ma.masked_all_like(arr)
+    masked_array(
+      data=[[--, --, --],
+            [--, --, --]],
+      mask=[[ True,  True,  True],
+            [ True,  True,  True]],
+      fill_value=np.float64(1e+20),
+      dtype=float32)
+
+    The dtype of the masked array matches the dtype of `arr`.
+
+    >>> arr.dtype
+    dtype('float32')
+    >>> np.ma.masked_all_like(arr).dtype
+    dtype('float32')
+
+    """
+    a = np.empty_like(arr).view(MaskedArray)
+    a._mask = np.ones(a.shape, dtype=make_mask_descr(a.dtype))
+    return a
+
+
+#####--------------------------------------------------------------------------
+#---- --- Standard functions ---
+#####--------------------------------------------------------------------------
+
+def _fromnxfunction_function(_fromnxfunction):
+    """
+    Decorator to wrap a "_fromnxfunction" function, wrapping a numpy function as a
+    masked array function, with proper docstring and name.
+
+    Parameters
+    ----------
+    _fromnxfunction : ({params}) -> ndarray, {params}) -> masked_array
+        Wrapper function that calls the wrapped numpy function
+
+    Returns
+    -------
+    decorator : (f: ({params}) -> ndarray) -> ({params}) -> masked_array
+        Function that accepts a numpy function and returns a masked array function
+
+    """
+    def decorator(npfunc, /):
+        def wrapper(*args, **kwargs):
+            return _fromnxfunction(npfunc, *args, **kwargs)
+
+        functools.update_wrapper(wrapper, npfunc, assigned=("__name__", "__qualname__"))
+        wrapper.__doc__ = ma.doc_note(
+            npfunc.__doc__,
+            "The function is applied to both the ``_data`` and the ``_mask``, if any.",
+        )
+        return wrapper
+
+    return decorator
+
+
+@_fromnxfunction_function
+def _fromnxfunction_single(npfunc, a, /, *args, **kwargs):
+    """
+    Wraps a NumPy function that can be called with a single array argument followed by
+    auxiliary args that are passed verbatim for both the data and mask calls.
+    """
+    return masked_array(
+        data=npfunc(np.asarray(a), *args, **kwargs),
+        mask=npfunc(getmaskarray(a), *args, **kwargs),
+    )
+
+
+@_fromnxfunction_function
+def _fromnxfunction_seq(npfunc, arys, /, *args, **kwargs):
+    """
+    Wraps a NumPy function that can be called with a single sequence of arrays followed
+    by auxiliary args that are passed verbatim for both the data and mask calls.
+    """
+    return masked_array(
+        data=npfunc(tuple(np.asarray(a) for a in arys), *args, **kwargs),
+        mask=npfunc(tuple(getmaskarray(a) for a in arys), *args, **kwargs),
+    )
+
+@_fromnxfunction_function
+def _fromnxfunction_allargs(npfunc, /, *arys, **kwargs):
+    """
+    Wraps a NumPy function that can be called with multiple array arguments.
+    All args are converted to arrays even if they are not so already.
+    This makes it possible to process scalars as 1-D arrays.
+    Only keyword arguments are passed through verbatim for the data and mask calls.
+    Arrays arguments are processed independently and the results are returned in a list.
+    If only one arg is present, the return value is just the processed array instead of
+    a list.
+    """
+    out = tuple(
+        masked_array(
+            data=npfunc(np.asarray(a), **kwargs),
+            mask=npfunc(getmaskarray(a), **kwargs),
+        )
+        for a in arys
+    )
+    return out[0] if len(out) == 1 else out
+
+
+atleast_1d = _fromnxfunction_allargs(np.atleast_1d)
+atleast_2d = _fromnxfunction_allargs(np.atleast_2d)
+atleast_3d = _fromnxfunction_allargs(np.atleast_3d)
+
+vstack = row_stack = _fromnxfunction_seq(np.vstack)
+hstack = _fromnxfunction_seq(np.hstack)
+column_stack = _fromnxfunction_seq(np.column_stack)
+dstack = _fromnxfunction_seq(np.dstack)
+stack = _fromnxfunction_seq(np.stack)
+
+hsplit = _fromnxfunction_single(np.hsplit)
+diagflat = _fromnxfunction_single(np.diagflat)
+
+
+#####--------------------------------------------------------------------------
+#----
+#####--------------------------------------------------------------------------
+def flatten_inplace(seq):
+    """Flatten a sequence in place."""
+    k = 0
+    while (k != len(seq)):
+        while hasattr(seq[k], '__iter__'):
+            seq[k:(k + 1)] = seq[k]
+        k += 1
+    return seq
+
+
+def apply_along_axis(func1d, axis, arr, *args, **kwargs):
+    """
+    (This docstring should be overwritten)
+    """
+    arr = array(arr, copy=False, subok=True)
+    nd = arr.ndim
+    axis = normalize_axis_index(axis, nd)
+    ind = [0] * (nd - 1)
+    i = np.zeros(nd, 'O')
+    indlist = list(range(nd))
+    indlist.remove(axis)
+    i[axis] = slice(None, None)
+    outshape = np.asarray(arr.shape).take(indlist)
+    i.put(indlist, ind)
+    res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
+    #  if res is a number, then we have a smaller output array
+    asscalar = np.isscalar(res)
+    if not asscalar:
+        try:
+            len(res)
+        except TypeError:
+            asscalar = True
+    # Note: we shouldn't set the dtype of the output from the first result
+    # so we force the type to object, and build a list of dtypes.  We'll
+    # just take the largest, to avoid some downcasting
+    dtypes = []
+    if asscalar:
+        dtypes.append(np.asarray(res).dtype)
+        outarr = zeros(outshape, object)
+        outarr[tuple(ind)] = res
+        Ntot = np.prod(outshape)
+        k = 1
+        while k < Ntot:
+            # increment the index
+            ind[-1] += 1
+            n = -1
+            while (ind[n] >= outshape[n]) and (n > (1 - nd)):
+                ind[n - 1] += 1
+                ind[n] = 0
+                n -= 1
+            i.put(indlist, ind)
+            res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
+            outarr[tuple(ind)] = res
+            dtypes.append(asarray(res).dtype)
+            k += 1
+    else:
+        res = array(res, copy=False, subok=True)
+        j = i.copy()
+        j[axis] = ([slice(None, None)] * res.ndim)
+        j.put(indlist, ind)
+        Ntot = np.prod(outshape)
+        holdshape = outshape
+        outshape = list(arr.shape)
+        outshape[axis] = res.shape
+        dtypes.append(asarray(res).dtype)
+        outshape = flatten_inplace(outshape)
+        outarr = zeros(outshape, object)
+        outarr[tuple(flatten_inplace(j.tolist()))] = res
+        k = 1
+        while k < Ntot:
+            # increment the index
+            ind[-1] += 1
+            n = -1
+            while (ind[n] >= holdshape[n]) and (n > (1 - nd)):
+                ind[n - 1] += 1
+                ind[n] = 0
+                n -= 1
+            i.put(indlist, ind)
+            j.put(indlist, ind)
+            res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
+            outarr[tuple(flatten_inplace(j.tolist()))] = res
+            dtypes.append(asarray(res).dtype)
+            k += 1
+    max_dtypes = np.dtype(np.asarray(dtypes).max())
+    if not hasattr(arr, '_mask'):
+        result = np.asarray(outarr, dtype=max_dtypes)
+    else:
+        result = asarray(outarr, dtype=max_dtypes)
+        result.fill_value = ma.default_fill_value(result)
+    return result
+
+
+apply_along_axis.__doc__ = np.apply_along_axis.__doc__
+
+
+def apply_over_axes(func, a, axes):
+    """
+    (This docstring will be overwritten)
+    """
+    val = asarray(a)
+    N = a.ndim
+    if array(axes).ndim == 0:
+        axes = (axes,)
+    for axis in axes:
+        if axis < 0:
+            axis = N + axis
+        args = (val, axis)
+        res = func(*args)
+        if res.ndim == val.ndim:
+            val = res
+        else:
+            res = ma.expand_dims(res, axis)
+            if res.ndim == val.ndim:
+                val = res
+            else:
+                raise ValueError("function is not returning "
+                        "an array of the correct shape")
+    return val
+
+
+if apply_over_axes.__doc__ is not None:
+    apply_over_axes.__doc__ = np.apply_over_axes.__doc__[
+        :np.apply_over_axes.__doc__.find('Notes')].rstrip() + \
+    """
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.arange(24).reshape(2,3,4)
+    >>> a[:,0,1] = np.ma.masked
+    >>> a[:,1,:] = np.ma.masked
+    >>> a
+    masked_array(
+      data=[[[0, --, 2, 3],
+             [--, --, --, --],
+             [8, 9, 10, 11]],
+            [[12, --, 14, 15],
+             [--, --, --, --],
+             [20, 21, 22, 23]]],
+      mask=[[[False,  True, False, False],
+             [ True,  True,  True,  True],
+             [False, False, False, False]],
+            [[False,  True, False, False],
+             [ True,  True,  True,  True],
+             [False, False, False, False]]],
+      fill_value=999999)
+    >>> np.ma.apply_over_axes(np.ma.sum, a, [0,2])
+    masked_array(
+      data=[[[46],
+             [--],
+             [124]]],
+      mask=[[[False],
+             [ True],
+             [False]]],
+      fill_value=999999)
+
+    Tuple axis arguments to ufuncs are equivalent:
+
+    >>> np.ma.sum(a, axis=(0,2)).reshape((1,-1,1))
+    masked_array(
+      data=[[[46],
+             [--],
+             [124]]],
+      mask=[[[False],
+             [ True],
+             [False]]],
+      fill_value=999999)
+    """
+
+
+def average(a, axis=None, weights=None, returned=False, *,
+            keepdims=np._NoValue):
+    """
+    Return the weighted average of array over the given axis.
+
+    Parameters
+    ----------
+    a : array_like
+        Data to be averaged.
+        Masked entries are not taken into account in the computation.
+    axis : None or int or tuple of ints, optional
+        Axis or axes along which to average `a`.  The default,
+        `axis=None`, will average over all of the elements of the input array.
+        If axis is a tuple of ints, averaging is performed on all of the axes
+        specified in the tuple instead of a single axis or all the axes as
+        before.
+    weights : array_like, optional
+        An array of weights associated with the values in `a`. Each value in
+        `a` contributes to the average according to its associated weight.
+        The array of weights must be the same shape as `a` if no axis is
+        specified, otherwise the weights must have dimensions and shape
+        consistent with `a` along the specified axis.
+        If `weights=None`, then all data in `a` are assumed to have a
+        weight equal to one.
+        The calculation is::
+
+            avg = sum(a * weights) / sum(weights)
+
+        where the sum is over all included elements.
+        The only constraint on the values of `weights` is that `sum(weights)`
+        must not be 0.
+    returned : bool, optional
+        Flag indicating whether a tuple ``(result, sum of weights)``
+        should be returned as output (True), or just the result (False).
+        Default is False.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the original `a`.
+        *Note:* `keepdims` will not work with instances of `numpy.matrix`
+        or other classes whose methods do not support `keepdims`.
+
+        .. versionadded:: 1.23.0
+
+    Returns
+    -------
+    average, [sum_of_weights] : (tuple of) scalar or MaskedArray
+        The average along the specified axis. When returned is `True`,
+        return a tuple with the average as the first element and the sum
+        of the weights as the second element. The return type is `np.float64`
+        if `a` is of integer type and floats smaller than `float64`, or the
+        input data-type, otherwise. If returned, `sum_of_weights` is always
+        `float64`.
+
+    Raises
+    ------
+    ZeroDivisionError
+        When all weights along axis are zero. See `numpy.ma.average` for a
+        version robust to this type of error.
+    TypeError
+        When `weights` does not have the same shape as `a`, and `axis=None`.
+    ValueError
+        When `weights` does not have dimensions and shape consistent with `a`
+        along specified `axis`.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array([1., 2., 3., 4.], mask=[False, False, True, True])
+    >>> np.ma.average(a, weights=[3, 1, 0, 0])
+    1.25
+
+    >>> x = np.ma.arange(6.).reshape(3, 2)
+    >>> x
+    masked_array(
+      data=[[0., 1.],
+            [2., 3.],
+            [4., 5.]],
+      mask=False,
+      fill_value=1e+20)
+    >>> data = np.arange(8).reshape((2, 2, 2))
+    >>> data
+    array([[[0, 1],
+            [2, 3]],
+           [[4, 5],
+            [6, 7]]])
+    >>> np.ma.average(data, axis=(0, 1), weights=[[1./4, 3./4], [1., 1./2]])
+    masked_array(data=[3.4, 4.4],
+             mask=[False, False],
+       fill_value=1e+20)
+    >>> np.ma.average(data, axis=0, weights=[[1./4, 3./4], [1., 1./2]])
+    Traceback (most recent call last):
+        ...
+    ValueError: Shape of weights must be consistent
+    with shape of a along specified axis.
+
+    >>> avg, sumweights = np.ma.average(x, axis=0, weights=[1, 2, 3],
+    ...                                 returned=True)
+    >>> avg
+    masked_array(data=[2.6666666666666665, 3.6666666666666665],
+                 mask=[False, False],
+           fill_value=1e+20)
+
+    With ``keepdims=True``, the following result has shape (3, 1).
+
+    >>> np.ma.average(x, axis=1, keepdims=True)
+    masked_array(
+      data=[[0.5],
+            [2.5],
+            [4.5]],
+      mask=False,
+      fill_value=1e+20)
+    """
+    a = asarray(a)
+    m = getmask(a)
+
+    if axis is not None:
+        axis = normalize_axis_tuple(axis, a.ndim, argname="axis")
+
+    if keepdims is np._NoValue:
+        # Don't pass on the keepdims argument if one wasn't given.
+        keepdims_kw = {}
+    else:
+        keepdims_kw = {'keepdims': keepdims}
+
+    if weights is None:
+        avg = a.mean(axis, **keepdims_kw)
+        scl = avg.dtype.type(a.count(axis))
+    else:
+        wgt = asarray(weights)
+
+        if issubclass(a.dtype.type, (np.integer, np.bool)):
+            result_dtype = np.result_type(a.dtype, wgt.dtype, 'f8')
+        else:
+            result_dtype = np.result_type(a.dtype, wgt.dtype)
+
+        # Sanity checks
+        if a.shape != wgt.shape:
+            if axis is None:
+                raise TypeError(
+                    "Axis must be specified when shapes of a and weights "
+                    "differ.")
+            if wgt.shape != tuple(a.shape[ax] for ax in axis):
+                raise ValueError(
+                    "Shape of weights must be consistent with "
+                    "shape of a along specified axis.")
+
+            # setup wgt to broadcast along axis
+            wgt = wgt.transpose(np.argsort(axis))
+            wgt = wgt.reshape(tuple((s if ax in axis else 1)
+                                    for ax, s in enumerate(a.shape)))
+
+        if m is not nomask:
+            wgt = wgt * (~a.mask)
+            wgt.mask |= a.mask
+
+        scl = wgt.sum(axis=axis, dtype=result_dtype, **keepdims_kw)
+        avg = np.multiply(a, wgt,
+                          dtype=result_dtype).sum(axis, **keepdims_kw) / scl
+
+    if returned:
+        if scl.shape != avg.shape:
+            scl = np.broadcast_to(scl, avg.shape).copy()
+        return avg, scl
+    else:
+        return avg
+
+
+def median(a, axis=None, out=None, overwrite_input=False, keepdims=False):
+    """
+    Compute the median along the specified axis.
+
+    Returns the median of the array elements.
+
+    Parameters
+    ----------
+    a : array_like
+        Input array or object that can be converted to an array.
+    axis : int, optional
+        Axis along which the medians are computed. The default (None) is
+        to compute the median along a flattened version of the array.
+    out : ndarray, optional
+        Alternative output array in which to place the result. It must
+        have the same shape and buffer length as the expected output
+        but the type will be cast if necessary.
+    overwrite_input : bool, optional
+        If True, then allow use of memory of input array (a) for
+        calculations. The input array will be modified by the call to
+        median. This will save memory when you do not need to preserve
+        the contents of the input array. Treat the input as undefined,
+        but it will probably be fully or partially sorted. Default is
+        False. Note that, if `overwrite_input` is True, and the input
+        is not already an `ndarray`, an error will be raised.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the input array.
+
+    Returns
+    -------
+    median : ndarray
+        A new array holding the result is returned unless out is
+        specified, in which case a reference to out is returned.
+        Return data-type is `float64` for integers and floats smaller than
+        `float64`, or the input data-type, otherwise.
+
+    See Also
+    --------
+    mean
+
+    Notes
+    -----
+    Given a vector ``V`` with ``N`` non masked values, the median of ``V``
+    is the middle value of a sorted copy of ``V`` (``Vs``) - i.e.
+    ``Vs[(N-1)/2]``, when ``N`` is odd, or ``{Vs[N/2 - 1] + Vs[N/2]}/2``
+    when ``N`` is even.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array(np.arange(8), mask=[0]*4 + [1]*4)
+    >>> np.ma.median(x)
+    1.5
+
+    >>> x = np.ma.array(np.arange(10).reshape(2, 5), mask=[0]*6 + [1]*4)
+    >>> np.ma.median(x)
+    2.5
+    >>> np.ma.median(x, axis=-1, overwrite_input=True)
+    masked_array(data=[2.0, 5.0],
+                 mask=[False, False],
+           fill_value=1e+20)
+
+    """
+    if not hasattr(a, 'mask'):
+        m = np.median(getdata(a, subok=True), axis=axis,
+                      out=out, overwrite_input=overwrite_input,
+                      keepdims=keepdims)
+        if isinstance(m, np.ndarray) and 1 <= m.ndim:
+            return masked_array(m, copy=False)
+        else:
+            return m
+
+    return _ureduce(a, func=_median, keepdims=keepdims, axis=axis, out=out,
+                    overwrite_input=overwrite_input)
+
+
+def _median(a, axis=None, out=None, overwrite_input=False):
+    # when an unmasked NaN is present return it, so we need to sort the NaN
+    # values behind the mask
+    if np.issubdtype(a.dtype, np.inexact):
+        fill_value = np.inf
+    else:
+        fill_value = None
+    if overwrite_input:
+        if axis is None:
+            asorted = a.ravel()
+            asorted.sort(fill_value=fill_value)
+        else:
+            a.sort(axis=axis, fill_value=fill_value)
+            asorted = a
+    else:
+        asorted = sort(a, axis=axis, fill_value=fill_value)
+
+    if axis is None:
+        axis = 0
+    else:
+        axis = normalize_axis_index(axis, asorted.ndim)
+
+    if asorted.shape[axis] == 0:
+        # for empty axis integer indices fail so use slicing to get same result
+        # as median (which is mean of empty slice = nan)
+        indexer = [slice(None)] * asorted.ndim
+        indexer[axis] = slice(0, 0)
+        indexer = tuple(indexer)
+        return np.ma.mean(asorted[indexer], axis=axis, out=out)
+
+    if asorted.ndim == 1:
+        idx, odd = divmod(count(asorted), 2)
+        mid = asorted[idx + odd - 1:idx + 1]
+        if np.issubdtype(asorted.dtype, np.inexact) and asorted.size > 0:
+            # avoid inf / x = masked
+            s = mid.sum(out=out)
+            if not odd:
+                s = np.true_divide(s, 2., casting='safe', out=out)
+            s = np.lib._utils_impl._median_nancheck(asorted, s, axis)
+        else:
+            s = mid.mean(out=out)
+
+        # if result is masked either the input contained enough
+        # minimum_fill_value so that it would be the median or all values
+        # masked
+        if np.ma.is_masked(s) and not np.all(asorted.mask):
+            return np.ma.minimum_fill_value(asorted)
+        return s
+
+    counts = count(asorted, axis=axis, keepdims=True)
+    h = counts // 2
+
+    # duplicate high if odd number of elements so mean does nothing
+    odd = counts % 2 == 1
+    l = np.where(odd, h, h - 1)
+
+    lh = np.concatenate([l, h], axis=axis)
+
+    # get low and high median
+    low_high = np.take_along_axis(asorted, lh, axis=axis)
+
+    def replace_masked(s):
+        # Replace masked entries with minimum_full_value unless it all values
+        # are masked. This is required as the sort order of values equal or
+        # larger than the fill value is undefined and a valid value placed
+        # elsewhere, e.g. [4, --, inf].
+        if np.ma.is_masked(s):
+            rep = (~np.all(asorted.mask, axis=axis, keepdims=True)) & s.mask
+            s.data[rep] = np.ma.minimum_fill_value(asorted)
+            s.mask[rep] = False
+
+    replace_masked(low_high)
+
+    if np.issubdtype(asorted.dtype, np.inexact):
+        # avoid inf / x = masked
+        s = np.ma.sum(low_high, axis=axis, out=out)
+        np.true_divide(s.data, 2., casting='unsafe', out=s.data)
+
+        s = np.lib._utils_impl._median_nancheck(asorted, s, axis)
+    else:
+        s = np.ma.mean(low_high, axis=axis, out=out)
+
+    return s
+
+
+def compress_nd(x, axis=None):
+    """Suppress slices from multiple dimensions which contain masked values.
+
+    Parameters
+    ----------
+    x : array_like, MaskedArray
+        The array to operate on. If not a MaskedArray instance (or if no array
+        elements are masked), `x` is interpreted as a MaskedArray with `mask`
+        set to `nomask`.
+    axis : tuple of ints or int, optional
+        Which dimensions to suppress slices from can be configured with this
+        parameter.
+        - If axis is a tuple of ints, those are the axes to suppress slices from.
+        - If axis is an int, then that is the only axis to suppress slices from.
+        - If axis is None, all axis are selected.
+
+    Returns
+    -------
+    compress_array : ndarray
+        The compressed array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = [[1, 2], [3, 4]]
+    >>> mask = [[0, 1], [0, 0]]
+    >>> x = np.ma.array(arr, mask=mask)
+    >>> np.ma.compress_nd(x, axis=0)
+    array([[3, 4]])
+    >>> np.ma.compress_nd(x, axis=1)
+    array([[1],
+           [3]])
+    >>> np.ma.compress_nd(x)
+    array([[3]])
+
+    """
+    x = asarray(x)
+    m = getmask(x)
+    # Set axis to tuple of ints
+    if axis is None:
+        axis = tuple(range(x.ndim))
+    else:
+        axis = normalize_axis_tuple(axis, x.ndim)
+
+    # Nothing is masked: return x
+    if m is nomask or not m.any():
+        return x._data
+    # All is masked: return empty
+    if m.all():
+        return nxarray([])
+    # Filter elements through boolean indexing
+    data = x._data
+    for ax in axis:
+        axes = tuple(list(range(ax)) + list(range(ax + 1, x.ndim)))
+        data = data[(slice(None),) * ax + (~m.any(axis=axes),)]
+    return data
+
+
+def compress_rowcols(x, axis=None):
+    """
+    Suppress the rows and/or columns of a 2-D array that contain
+    masked values.
+
+    The suppression behavior is selected with the `axis` parameter.
+
+    - If axis is None, both rows and columns are suppressed.
+    - If axis is 0, only rows are suppressed.
+    - If axis is 1 or -1, only columns are suppressed.
+
+    Parameters
+    ----------
+    x : array_like, MaskedArray
+        The array to operate on.  If not a MaskedArray instance (or if no array
+        elements are masked), `x` is interpreted as a MaskedArray with
+        `mask` set to `nomask`. Must be a 2D array.
+    axis : int, optional
+        Axis along which to perform the operation. Default is None.
+
+    Returns
+    -------
+    compressed_array : ndarray
+        The compressed array.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
+    ...                                                   [1, 0, 0],
+    ...                                                   [0, 0, 0]])
+    >>> x
+    masked_array(
+      data=[[--, 1, 2],
+            [--, 4, 5],
+            [6, 7, 8]],
+      mask=[[ True, False, False],
+            [ True, False, False],
+            [False, False, False]],
+      fill_value=999999)
+
+    >>> np.ma.compress_rowcols(x)
+    array([[7, 8]])
+    >>> np.ma.compress_rowcols(x, 0)
+    array([[6, 7, 8]])
+    >>> np.ma.compress_rowcols(x, 1)
+    array([[1, 2],
+           [4, 5],
+           [7, 8]])
+
+    """
+    if asarray(x).ndim != 2:
+        raise NotImplementedError("compress_rowcols works for 2D arrays only.")
+    return compress_nd(x, axis=axis)
+
+
+def compress_rows(a):
+    """
+    Suppress whole rows of a 2-D array that contain masked values.
+
+    This is equivalent to ``np.ma.compress_rowcols(a, 0)``, see
+    `compress_rowcols` for details.
+
+    Parameters
+    ----------
+    x : array_like, MaskedArray
+        The array to operate on. If not a MaskedArray instance (or if no array
+        elements are masked), `x` is interpreted as a MaskedArray with
+        `mask` set to `nomask`. Must be a 2D array.
+
+    Returns
+    -------
+    compressed_array : ndarray
+        The compressed array.
+
+    See Also
+    --------
+    compress_rowcols
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
+    ...                                                   [1, 0, 0],
+    ...                                                   [0, 0, 0]])
+    >>> np.ma.compress_rows(a)
+    array([[6, 7, 8]])
+
+    """
+    a = asarray(a)
+    if a.ndim != 2:
+        raise NotImplementedError("compress_rows works for 2D arrays only.")
+    return compress_rowcols(a, 0)
+
+
+def compress_cols(a):
+    """
+    Suppress whole columns of a 2-D array that contain masked values.
+
+    This is equivalent to ``np.ma.compress_rowcols(a, 1)``, see
+    `compress_rowcols` for details.
+
+    Parameters
+    ----------
+    x : array_like, MaskedArray
+        The array to operate on.  If not a MaskedArray instance (or if no array
+        elements are masked), `x` is interpreted as a MaskedArray with
+        `mask` set to `nomask`. Must be a 2D array.
+
+    Returns
+    -------
+    compressed_array : ndarray
+        The compressed array.
+
+    See Also
+    --------
+    compress_rowcols
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
+    ...                                                   [1, 0, 0],
+    ...                                                   [0, 0, 0]])
+    >>> np.ma.compress_cols(a)
+    array([[1, 2],
+           [4, 5],
+           [7, 8]])
+
+    """
+    a = asarray(a)
+    if a.ndim != 2:
+        raise NotImplementedError("compress_cols works for 2D arrays only.")
+    return compress_rowcols(a, 1)
+
+
+def mask_rowcols(a, axis=None):
+    """
+    Mask rows and/or columns of a 2D array that contain masked values.
+
+    Mask whole rows and/or columns of a 2D array that contain
+    masked values.  The masking behavior is selected using the
+    `axis` parameter.
+
+      - If `axis` is None, rows *and* columns are masked.
+      - If `axis` is 0, only rows are masked.
+      - If `axis` is 1 or -1, only columns are masked.
+
+    Parameters
+    ----------
+    a : array_like, MaskedArray
+        The array to mask.  If not a MaskedArray instance (or if no array
+        elements are masked), the result is a MaskedArray with `mask` set
+        to `nomask` (False). Must be a 2D array.
+    axis : int, optional
+        Axis along which to perform the operation. If None, applies to a
+        flattened version of the array.
+
+    Returns
+    -------
+    a : MaskedArray
+        A modified version of the input array, masked depending on the value
+        of the `axis` parameter.
+
+    Raises
+    ------
+    NotImplementedError
+        If input array `a` is not 2D.
+
+    See Also
+    --------
+    mask_rows : Mask rows of a 2D array that contain masked values.
+    mask_cols : Mask cols of a 2D array that contain masked values.
+    masked_where : Mask where a condition is met.
+
+    Notes
+    -----
+    The input array's mask is modified by this function.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.zeros((3, 3), dtype=int)
+    >>> a[1, 1] = 1
+    >>> a
+    array([[0, 0, 0],
+           [0, 1, 0],
+           [0, 0, 0]])
+    >>> a = np.ma.masked_equal(a, 1)
+    >>> a
+    masked_array(
+      data=[[0, 0, 0],
+            [0, --, 0],
+            [0, 0, 0]],
+      mask=[[False, False, False],
+            [False,  True, False],
+            [False, False, False]],
+      fill_value=1)
+    >>> np.ma.mask_rowcols(a)
+    masked_array(
+      data=[[0, --, 0],
+            [--, --, --],
+            [0, --, 0]],
+      mask=[[False,  True, False],
+            [ True,  True,  True],
+            [False,  True, False]],
+      fill_value=1)
+
+    """
+    a = array(a, subok=False)
+    if a.ndim != 2:
+        raise NotImplementedError("mask_rowcols works for 2D arrays only.")
+    m = getmask(a)
+    # Nothing is masked: return a
+    if m is nomask or not m.any():
+        return a
+    maskedval = m.nonzero()
+    a._mask = a._mask.copy()
+    if not axis:
+        a[np.unique(maskedval[0])] = masked
+    if axis in [None, 1, -1]:
+        a[:, np.unique(maskedval[1])] = masked
+    return a
+
+
+def mask_rows(a, axis=np._NoValue):
+    """
+    Mask rows of a 2D array that contain masked values.
+
+    This function is a shortcut to ``mask_rowcols`` with `axis` equal to 0.
+
+    See Also
+    --------
+    mask_rowcols : Mask rows and/or columns of a 2D array.
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.zeros((3, 3), dtype=int)
+    >>> a[1, 1] = 1
+    >>> a
+    array([[0, 0, 0],
+           [0, 1, 0],
+           [0, 0, 0]])
+    >>> a = np.ma.masked_equal(a, 1)
+    >>> a
+    masked_array(
+      data=[[0, 0, 0],
+            [0, --, 0],
+            [0, 0, 0]],
+      mask=[[False, False, False],
+            [False,  True, False],
+            [False, False, False]],
+      fill_value=1)
+
+    >>> np.ma.mask_rows(a)
+    masked_array(
+      data=[[0, 0, 0],
+            [--, --, --],
+            [0, 0, 0]],
+      mask=[[False, False, False],
+            [ True,  True,  True],
+            [False, False, False]],
+      fill_value=1)
+
+    """
+    if axis is not np._NoValue:
+        # remove the axis argument when this deprecation expires
+        # NumPy 1.18.0, 2019-11-28
+        warnings.warn(
+            "The axis argument has always been ignored, in future passing it "
+            "will raise TypeError", DeprecationWarning, stacklevel=2)
+    return mask_rowcols(a, 0)
+
+
+def mask_cols(a, axis=np._NoValue):
+    """
+    Mask columns of a 2D array that contain masked values.
+
+    This function is a shortcut to ``mask_rowcols`` with `axis` equal to 1.
+
+    See Also
+    --------
+    mask_rowcols : Mask rows and/or columns of a 2D array.
+    masked_where : Mask where a condition is met.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.zeros((3, 3), dtype=int)
+    >>> a[1, 1] = 1
+    >>> a
+    array([[0, 0, 0],
+           [0, 1, 0],
+           [0, 0, 0]])
+    >>> a = np.ma.masked_equal(a, 1)
+    >>> a
+    masked_array(
+      data=[[0, 0, 0],
+            [0, --, 0],
+            [0, 0, 0]],
+      mask=[[False, False, False],
+            [False,  True, False],
+            [False, False, False]],
+      fill_value=1)
+    >>> np.ma.mask_cols(a)
+    masked_array(
+      data=[[0, --, 0],
+            [0, --, 0],
+            [0, --, 0]],
+      mask=[[False,  True, False],
+            [False,  True, False],
+            [False,  True, False]],
+      fill_value=1)
+
+    """
+    if axis is not np._NoValue:
+        # remove the axis argument when this deprecation expires
+        # NumPy 1.18.0, 2019-11-28
+        warnings.warn(
+            "The axis argument has always been ignored, in future passing it "
+            "will raise TypeError", DeprecationWarning, stacklevel=2)
+    return mask_rowcols(a, 1)
+
+
+#####--------------------------------------------------------------------------
+#---- --- arraysetops ---
+#####--------------------------------------------------------------------------
+
+def ediff1d(arr, to_end=None, to_begin=None):
+    """
+    Compute the differences between consecutive elements of an array.
+
+    This function is the equivalent of `numpy.ediff1d` that takes masked
+    values into account, see `numpy.ediff1d` for details.
+
+    See Also
+    --------
+    numpy.ediff1d : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> arr = np.ma.array([1, 2, 4, 7, 0])
+    >>> np.ma.ediff1d(arr)
+    masked_array(data=[ 1,  2,  3, -7],
+                 mask=False,
+           fill_value=999999)
+
+    """
+    arr = ma.asanyarray(arr).flat
+    ed = arr[1:] - arr[:-1]
+    arrays = [ed]
+    #
+    if to_begin is not None:
+        arrays.insert(0, to_begin)
+    if to_end is not None:
+        arrays.append(to_end)
+    #
+    if len(arrays) != 1:
+        # We'll save ourselves a copy of a potentially large array in the common
+        # case where neither to_begin or to_end was given.
+        ed = hstack(arrays)
+    #
+    return ed
+
+
+def unique(ar1, return_index=False, return_inverse=False):
+    """
+    Finds the unique elements of an array.
+
+    Masked values are considered the same element (masked). The output array
+    is always a masked array. See `numpy.unique` for more details.
+
+    See Also
+    --------
+    numpy.unique : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = [1, 2, 1000, 2, 3]
+    >>> mask = [0, 0, 1, 0, 0]
+    >>> masked_a = np.ma.masked_array(a, mask)
+    >>> masked_a
+    masked_array(data=[1, 2, --, 2, 3],
+                mask=[False, False,  True, False, False],
+        fill_value=999999)
+    >>> np.ma.unique(masked_a)
+    masked_array(data=[1, 2, 3, --],
+                mask=[False, False, False,  True],
+        fill_value=999999)
+    >>> np.ma.unique(masked_a, return_index=True)
+    (masked_array(data=[1, 2, 3, --],
+                mask=[False, False, False,  True],
+        fill_value=999999), array([0, 1, 4, 2]))
+    >>> np.ma.unique(masked_a, return_inverse=True)
+    (masked_array(data=[1, 2, 3, --],
+                mask=[False, False, False,  True],
+        fill_value=999999), array([0, 1, 3, 1, 2]))
+    >>> np.ma.unique(masked_a, return_index=True, return_inverse=True)
+    (masked_array(data=[1, 2, 3, --],
+                mask=[False, False, False,  True],
+        fill_value=999999), array([0, 1, 4, 2]), array([0, 1, 3, 1, 2]))
+    """
+    output = np.unique(ar1,
+                       return_index=return_index,
+                       return_inverse=return_inverse)
+    if isinstance(output, tuple):
+        output = list(output)
+        output[0] = output[0].view(MaskedArray)
+        output = tuple(output)
+    else:
+        output = output.view(MaskedArray)
+    return output
+
+
+def intersect1d(ar1, ar2, assume_unique=False):
+    """
+    Returns the unique elements common to both arrays.
+
+    Masked values are considered equal one to the other.
+    The output is always a masked array.
+
+    See `numpy.intersect1d` for more details.
+
+    See Also
+    --------
+    numpy.intersect1d : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([1, 3, 3, 3], mask=[0, 0, 0, 1])
+    >>> y = np.ma.array([3, 1, 1, 1], mask=[0, 0, 0, 1])
+    >>> np.ma.intersect1d(x, y)
+    masked_array(data=[1, 3, --],
+                 mask=[False, False,  True],
+           fill_value=999999)
+
+    """
+    if assume_unique:
+        aux = ma.concatenate((ar1, ar2))
+    else:
+        # Might be faster than unique( intersect1d( ar1, ar2 ) )?
+        aux = ma.concatenate((unique(ar1), unique(ar2)))
+    aux.sort()
+    return aux[:-1][aux[1:] == aux[:-1]]
+
+
+def setxor1d(ar1, ar2, assume_unique=False):
+    """
+    Set exclusive-or of 1-D arrays with unique elements.
+
+    The output is always a masked array. See `numpy.setxor1d` for more details.
+
+    See Also
+    --------
+    numpy.setxor1d : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> ar1 = np.ma.array([1, 2, 3, 2, 4])
+    >>> ar2 = np.ma.array([2, 3, 5, 7, 5])
+    >>> np.ma.setxor1d(ar1, ar2)
+    masked_array(data=[1, 4, 5, 7],
+                 mask=False,
+           fill_value=999999)
+
+    """
+    if not assume_unique:
+        ar1 = unique(ar1)
+        ar2 = unique(ar2)
+
+    aux = ma.concatenate((ar1, ar2), axis=None)
+    if aux.size == 0:
+        return aux
+    aux.sort()
+    auxf = aux.filled()
+#    flag = ediff1d( aux, to_end = 1, to_begin = 1 ) == 0
+    flag = ma.concatenate(([True], (auxf[1:] != auxf[:-1]), [True]))
+#    flag2 = ediff1d( flag ) == 0
+    flag2 = (flag[1:] == flag[:-1])
+    return aux[flag2]
+
+
+def in1d(ar1, ar2, assume_unique=False, invert=False):
+    """
+    Test whether each element of an array is also present in a second
+    array.
+
+    The output is always a masked array.
+
+    We recommend using :func:`isin` instead of `in1d` for new code.
+
+    See Also
+    --------
+    isin       : Version of this function that preserves the shape of ar1.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> ar1 = np.ma.array([0, 1, 2, 5, 0])
+    >>> ar2 = [0, 2]
+    >>> np.ma.in1d(ar1, ar2)
+    masked_array(data=[ True, False,  True, False,  True],
+                 mask=False,
+           fill_value=True)
+
+    """
+    if not assume_unique:
+        ar1, rev_idx = unique(ar1, return_inverse=True)
+        ar2 = unique(ar2)
+
+    ar = ma.concatenate((ar1, ar2))
+    # We need this to be a stable sort, so always use 'mergesort'
+    # here. The values from the first array should always come before
+    # the values from the second array.
+    order = ar.argsort(kind='mergesort')
+    sar = ar[order]
+    if invert:
+        bool_ar = (sar[1:] != sar[:-1])
+    else:
+        bool_ar = (sar[1:] == sar[:-1])
+    flag = ma.concatenate((bool_ar, [invert]))
+    indx = order.argsort(kind='mergesort')[:len(ar1)]
+
+    if assume_unique:
+        return flag[indx]
+    else:
+        return flag[indx][rev_idx]
+
+
+def isin(element, test_elements, assume_unique=False, invert=False):
+    """
+    Calculates `element in test_elements`, broadcasting over
+    `element` only.
+
+    The output is always a masked array of the same shape as `element`.
+    See `numpy.isin` for more details.
+
+    See Also
+    --------
+    in1d       : Flattened version of this function.
+    numpy.isin : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> element = np.ma.array([1, 2, 3, 4, 5, 6])
+    >>> test_elements = [0, 2]
+    >>> np.ma.isin(element, test_elements)
+    masked_array(data=[False,  True, False, False, False, False],
+                 mask=False,
+           fill_value=True)
+
+    """
+    element = ma.asarray(element)
+    return in1d(element, test_elements, assume_unique=assume_unique,
+                invert=invert).reshape(element.shape)
+
+
+def union1d(ar1, ar2):
+    """
+    Union of two arrays.
+
+    The output is always a masked array. See `numpy.union1d` for more details.
+
+    See Also
+    --------
+    numpy.union1d : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> ar1 = np.ma.array([1, 2, 3, 4])
+    >>> ar2 = np.ma.array([3, 4, 5, 6])
+    >>> np.ma.union1d(ar1, ar2)
+    masked_array(data=[1, 2, 3, 4, 5, 6],
+             mask=False,
+       fill_value=999999)
+
+    """
+    return unique(ma.concatenate((ar1, ar2), axis=None))
+
+
+def setdiff1d(ar1, ar2, assume_unique=False):
+    """
+    Set difference of 1D arrays with unique elements.
+
+    The output is always a masked array. See `numpy.setdiff1d` for more
+    details.
+
+    See Also
+    --------
+    numpy.setdiff1d : Equivalent function for ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([1, 2, 3, 4], mask=[0, 1, 0, 1])
+    >>> np.ma.setdiff1d(x, [1, 2])
+    masked_array(data=[3, --],
+                 mask=[False,  True],
+           fill_value=999999)
+
+    """
+    if assume_unique:
+        ar1 = ma.asarray(ar1).ravel()
+    else:
+        ar1 = unique(ar1)
+        ar2 = unique(ar2)
+    return ar1[in1d(ar1, ar2, assume_unique=True, invert=True)]
+
+
+###############################################################################
+#                                Covariance                                   #
+###############################################################################
+
+
+def _covhelper(x, y=None, rowvar=True, allow_masked=True):
+    """
+    Private function for the computation of covariance and correlation
+    coefficients.
+
+    """
+    x = ma.array(x, ndmin=2, copy=True, dtype=float)
+    xmask = ma.getmaskarray(x)
+    # Quick exit if we can't process masked data
+    if not allow_masked and xmask.any():
+        raise ValueError("Cannot process masked data.")
+    #
+    if x.shape[0] == 1:
+        rowvar = True
+    # Make sure that rowvar is either 0 or 1
+    rowvar = int(bool(rowvar))
+    axis = 1 - rowvar
+    if rowvar:
+        tup = (slice(None), None)
+    else:
+        tup = (None, slice(None))
+    #
+    if y is None:
+        # Check if we can guarantee that the integers in the (N - ddof)
+        # normalisation can be accurately represented with single-precision
+        # before computing the dot product.
+        if x.shape[0] > 2 ** 24 or x.shape[1] > 2 ** 24:
+            xnm_dtype = np.float64
+        else:
+            xnm_dtype = np.float32
+        xnotmask = np.logical_not(xmask).astype(xnm_dtype)
+    else:
+        y = array(y, copy=False, ndmin=2, dtype=float)
+        ymask = ma.getmaskarray(y)
+        if not allow_masked and ymask.any():
+            raise ValueError("Cannot process masked data.")
+        if xmask.any() or ymask.any():
+            if y.shape == x.shape:
+                # Define some common mask
+                common_mask = np.logical_or(xmask, ymask)
+                if common_mask is not nomask:
+                    xmask = x._mask = y._mask = ymask = common_mask
+                    x._sharedmask = False
+                    y._sharedmask = False
+        x = ma.concatenate((x, y), axis)
+        # Check if we can guarantee that the integers in the (N - ddof)
+        # normalisation can be accurately represented with single-precision
+        # before computing the dot product.
+        if x.shape[0] > 2 ** 24 or x.shape[1] > 2 ** 24:
+            xnm_dtype = np.float64
+        else:
+            xnm_dtype = np.float32
+        xnotmask = np.logical_not(np.concatenate((xmask, ymask), axis)).astype(
+            xnm_dtype
+        )
+    x -= x.mean(axis=rowvar)[tup]
+    return (x, xnotmask, rowvar)
+
+
+def cov(x, y=None, rowvar=True, bias=False, allow_masked=True, ddof=None):
+    """
+    Estimate the covariance matrix.
+
+    Except for the handling of missing data this function does the same as
+    `numpy.cov`. For more details and examples, see `numpy.cov`.
+
+    By default, masked values are recognized as such. If `x` and `y` have the
+    same shape, a common mask is allocated: if ``x[i,j]`` is masked, then
+    ``y[i,j]`` will also be masked.
+    Setting `allow_masked` to False will raise an exception if values are
+    missing in either of the input arrays.
+
+    Parameters
+    ----------
+    x : array_like
+        A 1-D or 2-D array containing multiple variables and observations.
+        Each row of `x` represents a variable, and each column a single
+        observation of all those variables. Also see `rowvar` below.
+    y : array_like, optional
+        An additional set of variables and observations. `y` has the same
+        shape as `x`.
+    rowvar : bool, optional
+        If `rowvar` is True (default), then each row represents a
+        variable, with observations in the columns. Otherwise, the relationship
+        is transposed: each column represents a variable, while the rows
+        contain observations.
+    bias : bool, optional
+        Default normalization (False) is by ``(N-1)``, where ``N`` is the
+        number of observations given (unbiased estimate). If `bias` is True,
+        then normalization is by ``N``. This keyword can be overridden by
+        the keyword ``ddof`` in numpy versions >= 1.5.
+    allow_masked : bool, optional
+        If True, masked values are propagated pair-wise: if a value is masked
+        in `x`, the corresponding value is masked in `y`.
+        If False, raises a `ValueError` exception when some values are missing.
+    ddof : {None, int}, optional
+        If not ``None`` normalization is by ``(N - ddof)``, where ``N`` is
+        the number of observations; this overrides the value implied by
+        ``bias``. The default value is ``None``.
+
+    Raises
+    ------
+    ValueError
+        Raised if some values are missing and `allow_masked` is False.
+
+    See Also
+    --------
+    numpy.cov
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([[0, 1], [1, 1]], mask=[0, 1, 0, 1])
+    >>> y = np.ma.array([[1, 0], [0, 1]], mask=[0, 0, 1, 1])
+    >>> np.ma.cov(x, y)
+    masked_array(
+    data=[[--, --, --, --],
+          [--, --, --, --],
+          [--, --, --, --],
+          [--, --, --, --]],
+    mask=[[ True,  True,  True,  True],
+          [ True,  True,  True,  True],
+          [ True,  True,  True,  True],
+          [ True,  True,  True,  True]],
+    fill_value=1e+20,
+    dtype=float64)
+
+    """
+    # Check inputs
+    if ddof is not None and ddof != int(ddof):
+        raise ValueError("ddof must be an integer")
+    # Set up ddof
+    if ddof is None:
+        if bias:
+            ddof = 0
+        else:
+            ddof = 1
+
+    (x, xnotmask, rowvar) = _covhelper(x, y, rowvar, allow_masked)
+    if not rowvar:
+        fact = np.dot(xnotmask.T, xnotmask) - ddof
+        mask = np.less_equal(fact, 0, dtype=bool)
+        with np.errstate(divide="ignore", invalid="ignore"):
+            data = np.dot(filled(x.T, 0), filled(x.conj(), 0)) / fact
+        result = ma.array(data, mask=mask).squeeze()
+    else:
+        fact = np.dot(xnotmask, xnotmask.T) - ddof
+        mask = np.less_equal(fact, 0, dtype=bool)
+        with np.errstate(divide="ignore", invalid="ignore"):
+            data = np.dot(filled(x, 0), filled(x.T.conj(), 0)) / fact
+        result = ma.array(data, mask=mask).squeeze()
+    return result
+
+
+def corrcoef(x, y=None, rowvar=True, allow_masked=True,
+             ):
+    """
+    Return Pearson product-moment correlation coefficients.
+
+    Except for the handling of missing data this function does the same as
+    `numpy.corrcoef`. For more details and examples, see `numpy.corrcoef`.
+
+    Parameters
+    ----------
+    x : array_like
+        A 1-D or 2-D array containing multiple variables and observations.
+        Each row of `x` represents a variable, and each column a single
+        observation of all those variables. Also see `rowvar` below.
+    y : array_like, optional
+        An additional set of variables and observations. `y` has the same
+        shape as `x`.
+    rowvar : bool, optional
+        If `rowvar` is True (default), then each row represents a
+        variable, with observations in the columns. Otherwise, the relationship
+        is transposed: each column represents a variable, while the rows
+        contain observations.
+    allow_masked : bool, optional
+        If True, masked values are propagated pair-wise: if a value is masked
+        in `x`, the corresponding value is masked in `y`.
+        If False, raises an exception.  Because `bias` is deprecated, this
+        argument needs to be treated as keyword only to avoid a warning.
+
+    See Also
+    --------
+    numpy.corrcoef : Equivalent function in top-level NumPy module.
+    cov : Estimate the covariance matrix.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.ma.array([[0, 1], [1, 1]], mask=[0, 1, 0, 1])
+    >>> np.ma.corrcoef(x)
+    masked_array(
+      data=[[--, --],
+            [--, --]],
+      mask=[[ True,  True],
+            [ True,  True]],
+      fill_value=1e+20,
+      dtype=float64)
+
+    """
+    # Estimate the covariance matrix.
+    corr = cov(x, y, rowvar, allow_masked=allow_masked)
+    # The non-masked version returns a masked value for a scalar.
+    try:
+        std = ma.sqrt(ma.diagonal(corr))
+    except ValueError:
+        return ma.MaskedConstant()
+    corr /= ma.multiply.outer(std, std)
+    return corr
+
+#####--------------------------------------------------------------------------
+#---- --- Concatenation helpers ---
+#####--------------------------------------------------------------------------
+
+class MAxisConcatenator(AxisConcatenator):
+    """
+    Translate slice objects to concatenation along an axis.
+
+    For documentation on usage, see `mr_class`.
+
+    See Also
+    --------
+    mr_class
+
+    """
+    __slots__ = ()
+
+    concatenate = staticmethod(concatenate)
+
+    @classmethod
+    def makemat(cls, arr):
+        # There used to be a view as np.matrix here, but we may eventually
+        # deprecate that class. In preparation, we use the unmasked version
+        # to construct the matrix (with copy=False for backwards compatibility
+        # with the .view)
+        data = super().makemat(arr.data, copy=False)
+        return array(data, mask=arr.mask)
+
+    def __getitem__(self, key):
+        # matrix builder syntax, like 'a, b; c, d'
+        if isinstance(key, str):
+            raise MAError("Unavailable for masked array.")
+
+        return super().__getitem__(key)
+
+
+class mr_class(MAxisConcatenator):
+    """
+    Translate slice objects to concatenation along the first axis.
+
+    This is the masked array version of `r_`.
+
+    See Also
+    --------
+    r_
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> np.ma.mr_[np.ma.array([1,2,3]), 0, 0, np.ma.array([4,5,6])]
+    masked_array(data=[1, 2, 3, ..., 4, 5, 6],
+                 mask=False,
+           fill_value=999999)
+
+    """
+    __slots__ = ()
+
+    def __init__(self):
+        MAxisConcatenator.__init__(self, 0)
+
+
+mr_ = mr_class()
+
+
+#####--------------------------------------------------------------------------
+#---- Find unmasked data ---
+#####--------------------------------------------------------------------------
+
+def ndenumerate(a, compressed=True):
+    """
+    Multidimensional index iterator.
+
+    Return an iterator yielding pairs of array coordinates and values,
+    skipping elements that are masked. With `compressed=False`,
+    `ma.masked` is yielded as the value of masked elements. This
+    behavior differs from that of `numpy.ndenumerate`, which yields the
+    value of the underlying data array.
+
+    Notes
+    -----
+    .. versionadded:: 1.23.0
+
+    Parameters
+    ----------
+    a : array_like
+        An array with (possibly) masked elements.
+    compressed : bool, optional
+        If True (default), masked elements are skipped.
+
+    See Also
+    --------
+    numpy.ndenumerate : Equivalent function ignoring any mask.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.arange(9).reshape((3, 3))
+    >>> a[1, 0] = np.ma.masked
+    >>> a[1, 2] = np.ma.masked
+    >>> a[2, 1] = np.ma.masked
+    >>> a
+    masked_array(
+      data=[[0, 1, 2],
+            [--, 4, --],
+            [6, --, 8]],
+      mask=[[False, False, False],
+            [ True, False,  True],
+            [False,  True, False]],
+      fill_value=999999)
+    >>> for index, x in np.ma.ndenumerate(a):
+    ...     print(index, x)
+    (0, 0) 0
+    (0, 1) 1
+    (0, 2) 2
+    (1, 1) 4
+    (2, 0) 6
+    (2, 2) 8
+
+    >>> for index, x in np.ma.ndenumerate(a, compressed=False):
+    ...     print(index, x)
+    (0, 0) 0
+    (0, 1) 1
+    (0, 2) 2
+    (1, 0) --
+    (1, 1) 4
+    (1, 2) --
+    (2, 0) 6
+    (2, 1) --
+    (2, 2) 8
+    """
+    for it, mask in zip(np.ndenumerate(a), getmaskarray(a).flat):
+        if not mask:
+            yield it
+        elif not compressed:
+            yield it[0], masked
+
+
+def flatnotmasked_edges(a):
+    """
+    Find the indices of the first and last unmasked values.
+
+    Expects a 1-D `MaskedArray`, returns None if all values are masked.
+
+    Parameters
+    ----------
+    a : array_like
+        Input 1-D `MaskedArray`
+
+    Returns
+    -------
+    edges : ndarray or None
+        The indices of first and last non-masked value in the array.
+        Returns None if all values are masked.
+
+    See Also
+    --------
+    flatnotmasked_contiguous, notmasked_contiguous, notmasked_edges
+    clump_masked, clump_unmasked
+
+    Notes
+    -----
+    Only accepts 1-D arrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.arange(10)
+    >>> np.ma.flatnotmasked_edges(a)
+    array([0, 9])
+
+    >>> mask = (a < 3) | (a > 8) | (a == 5)
+    >>> a[mask] = np.ma.masked
+    >>> np.array(a[~a.mask])
+    array([3, 4, 6, 7, 8])
+
+    >>> np.ma.flatnotmasked_edges(a)
+    array([3, 8])
+
+    >>> a[:] = np.ma.masked
+    >>> print(np.ma.flatnotmasked_edges(a))
+    None
+
+    """
+    m = getmask(a)
+    if m is nomask or not np.any(m):
+        return np.array([0, a.size - 1])
+    unmasked = np.flatnonzero(~m)
+    if len(unmasked) > 0:
+        return unmasked[[0, -1]]
+    else:
+        return None
+
+
+def notmasked_edges(a, axis=None):
+    """
+    Find the indices of the first and last unmasked values along an axis.
+
+    If all values are masked, return None.  Otherwise, return a list
+    of two tuples, corresponding to the indices of the first and last
+    unmasked values respectively.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array.
+    axis : int, optional
+        Axis along which to perform the operation.
+        If None (default), applies to a flattened version of the array.
+
+    Returns
+    -------
+    edges : ndarray or list
+        An array of start and end indexes if there are any masked data in
+        the array. If there are no masked data in the array, `edges` is a
+        list of the first and last index.
+
+    See Also
+    --------
+    flatnotmasked_contiguous, flatnotmasked_edges, notmasked_contiguous
+    clump_masked, clump_unmasked
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(9).reshape((3, 3))
+    >>> m = np.zeros_like(a)
+    >>> m[1:, 1:] = 1
+
+    >>> am = np.ma.array(a, mask=m)
+    >>> np.array(am[~am.mask])
+    array([0, 1, 2, 3, 6])
+
+    >>> np.ma.notmasked_edges(am)
+    array([0, 6])
+
+    """
+    a = asarray(a)
+    if axis is None or a.ndim == 1:
+        return flatnotmasked_edges(a)
+    m = getmaskarray(a)
+    idx = array(np.indices(a.shape), mask=np.asarray([m] * a.ndim))
+    return [tuple(idx[i].min(axis).compressed() for i in range(a.ndim)),
+            tuple(idx[i].max(axis).compressed() for i in range(a.ndim)), ]
+
+
+def flatnotmasked_contiguous(a):
+    """
+    Find contiguous unmasked data in a masked array.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array.
+
+    Returns
+    -------
+    slice_list : list
+        A sorted sequence of `slice` objects (start index, end index).
+
+    See Also
+    --------
+    flatnotmasked_edges, notmasked_contiguous, notmasked_edges
+    clump_masked, clump_unmasked
+
+    Notes
+    -----
+    Only accepts 2-D arrays at most.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.arange(10)
+    >>> np.ma.flatnotmasked_contiguous(a)
+    [slice(0, 10, None)]
+
+    >>> mask = (a < 3) | (a > 8) | (a == 5)
+    >>> a[mask] = np.ma.masked
+    >>> np.array(a[~a.mask])
+    array([3, 4, 6, 7, 8])
+
+    >>> np.ma.flatnotmasked_contiguous(a)
+    [slice(3, 5, None), slice(6, 9, None)]
+    >>> a[:] = np.ma.masked
+    >>> np.ma.flatnotmasked_contiguous(a)
+    []
+
+    """
+    m = getmask(a)
+    if m is nomask:
+        return [slice(0, a.size)]
+    i = 0
+    result = []
+    for (k, g) in itertools.groupby(m.ravel()):
+        n = len(list(g))
+        if not k:
+            result.append(slice(i, i + n))
+        i += n
+    return result
+
+
+def notmasked_contiguous(a, axis=None):
+    """
+    Find contiguous unmasked data in a masked array along the given axis.
+
+    Parameters
+    ----------
+    a : array_like
+        The input array.
+    axis : int, optional
+        Axis along which to perform the operation.
+        If None (default), applies to a flattened version of the array, and this
+        is the same as `flatnotmasked_contiguous`.
+
+    Returns
+    -------
+    endpoints : list
+        A list of slices (start and end indexes) of unmasked indexes
+        in the array.
+
+        If the input is 2d and axis is specified, the result is a list of lists.
+
+    See Also
+    --------
+    flatnotmasked_edges, flatnotmasked_contiguous, notmasked_edges
+    clump_masked, clump_unmasked
+
+    Notes
+    -----
+    Only accepts 2-D arrays at most.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.arange(12).reshape((3, 4))
+    >>> mask = np.zeros_like(a)
+    >>> mask[1:, :-1] = 1; mask[0, 1] = 1; mask[-1, 0] = 0
+    >>> ma = np.ma.array(a, mask=mask)
+    >>> ma
+    masked_array(
+      data=[[0, --, 2, 3],
+            [--, --, --, 7],
+            [8, --, --, 11]],
+      mask=[[False,  True, False, False],
+            [ True,  True,  True, False],
+            [False,  True,  True, False]],
+      fill_value=999999)
+    >>> np.array(ma[~ma.mask])
+    array([ 0,  2,  3,  7, 8, 11])
+
+    >>> np.ma.notmasked_contiguous(ma)
+    [slice(0, 1, None), slice(2, 4, None), slice(7, 9, None), slice(11, 12, None)]
+
+    >>> np.ma.notmasked_contiguous(ma, axis=0)
+    [[slice(0, 1, None), slice(2, 3, None)], [], [slice(0, 1, None)], [slice(0, 3, None)]]
+
+    >>> np.ma.notmasked_contiguous(ma, axis=1)
+    [[slice(0, 1, None), slice(2, 4, None)], [slice(3, 4, None)], [slice(0, 1, None), slice(3, 4, None)]]
+
+    """  # noqa: E501
+    a = asarray(a)
+    nd = a.ndim
+    if nd > 2:
+        raise NotImplementedError("Currently limited to at most 2D array.")
+    if axis is None or nd == 1:
+        return flatnotmasked_contiguous(a)
+    #
+    result = []
+    #
+    other = (axis + 1) % 2
+    idx = [0, 0]
+    idx[axis] = slice(None, None)
+    #
+    for i in range(a.shape[other]):
+        idx[other] = i
+        result.append(flatnotmasked_contiguous(a[tuple(idx)]))
+    return result
+
+
+def _ezclump(mask):
+    """
+    Finds the clumps (groups of data with the same values) for a 1D bool array.
+
+    Returns a series of slices.
+    """
+    if mask.ndim > 1:
+        mask = mask.ravel()
+    idx = (mask[1:] ^ mask[:-1]).nonzero()
+    idx = idx[0] + 1
+
+    if mask[0]:
+        if len(idx) == 0:
+            return [slice(0, mask.size)]
+
+        r = [slice(0, idx[0])]
+        r.extend((slice(left, right)
+                  for left, right in zip(idx[1:-1:2], idx[2::2])))
+    else:
+        if len(idx) == 0:
+            return []
+
+        r = [slice(left, right) for left, right in zip(idx[:-1:2], idx[1::2])]
+
+    if mask[-1]:
+        r.append(slice(idx[-1], mask.size))
+    return r
+
+
+def clump_unmasked(a):
+    """
+    Return list of slices corresponding to the unmasked clumps of a 1-D array.
+    (A "clump" is defined as a contiguous region of the array).
+
+    Parameters
+    ----------
+    a : ndarray
+        A one-dimensional masked array.
+
+    Returns
+    -------
+    slices : list of slice
+        The list of slices, one for each continuous region of unmasked
+        elements in `a`.
+
+    See Also
+    --------
+    flatnotmasked_edges, flatnotmasked_contiguous, notmasked_edges
+    notmasked_contiguous, clump_masked
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.masked_array(np.arange(10))
+    >>> a[[0, 1, 2, 6, 8, 9]] = np.ma.masked
+    >>> np.ma.clump_unmasked(a)
+    [slice(3, 6, None), slice(7, 8, None)]
+
+    """
+    mask = getattr(a, '_mask', nomask)
+    if mask is nomask:
+        return [slice(0, a.size)]
+    return _ezclump(~mask)
+
+
+def clump_masked(a):
+    """
+    Returns a list of slices corresponding to the masked clumps of a 1-D array.
+    (A "clump" is defined as a contiguous region of the array).
+
+    Parameters
+    ----------
+    a : ndarray
+        A one-dimensional masked array.
+
+    Returns
+    -------
+    slices : list of slice
+        The list of slices, one for each continuous region of masked elements
+        in `a`.
+
+    See Also
+    --------
+    flatnotmasked_edges, flatnotmasked_contiguous, notmasked_edges
+    notmasked_contiguous, clump_unmasked
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.ma.masked_array(np.arange(10))
+    >>> a[[0, 1, 2, 6, 8, 9]] = np.ma.masked
+    >>> np.ma.clump_masked(a)
+    [slice(0, 3, None), slice(6, 7, None), slice(8, 10, None)]
+
+    """
+    mask = ma.getmask(a)
+    if mask is nomask:
+        return []
+    return _ezclump(mask)
+
+
+###############################################################################
+#                              Polynomial fit                                 #
+###############################################################################
+
+
+def vander(x, n=None):
+    """
+    Masked values in the input array result in rows of zeros.
+
+    """
+    _vander = np.vander(x, n)
+    m = getmask(x)
+    if m is not nomask:
+        _vander[m] = 0
+    return _vander
+
+
+vander.__doc__ = ma.doc_note(np.vander.__doc__, vander.__doc__)
+
+
+def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False):
+    """
+    Any masked values in x is propagated in y, and vice-versa.
+
+    """
+    x = asarray(x)
+    y = asarray(y)
+
+    m = getmask(x)
+    if y.ndim == 1:
+        m = mask_or(m, getmask(y))
+    elif y.ndim == 2:
+        my = getmask(mask_rows(y))
+        if my is not nomask:
+            m = mask_or(m, my[:, 0])
+    else:
+        raise TypeError("Expected a 1D or 2D array for y!")
+
+    if w is not None:
+        w = asarray(w)
+        if w.ndim != 1:
+            raise TypeError("expected a 1-d array for weights")
+        if w.shape[0] != y.shape[0]:
+            raise TypeError("expected w and y to have the same length")
+        m = mask_or(m, getmask(w))
+
+    if m is not nomask:
+        not_m = ~m
+        if w is not None:
+            w = w[not_m]
+        return np.polyfit(x[not_m], y[not_m], deg, rcond, full, w, cov)
+    else:
+        return np.polyfit(x, y, deg, rcond, full, w, cov)
+
+
+polyfit.__doc__ = ma.doc_note(np.polyfit.__doc__, polyfit.__doc__)
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/extras.pyi b/python/user_packages/Python313/site-packages/numpy/ma/extras.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..a03a198642051aa2fe45652366b5a86aeb0750f3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/extras.pyi
@@ -0,0 +1,297 @@
+from _typeshed import Incomplete
+from collections.abc import Sequence
+from typing import SupportsIndex, TypeAlias, TypeVar, overload
+
+import numpy as np
+from numpy import _CastingKind
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    _AnyShape,
+    _ArrayLike,
+    _DTypeLike,
+    _ShapeLike,
+)
+from numpy.lib._function_base_impl import average
+from numpy.lib._index_tricks_impl import AxisConcatenator
+
+from .core import MaskedArray, dot
+
+__all__ = [
+    "apply_along_axis",
+    "apply_over_axes",
+    "atleast_1d",
+    "atleast_2d",
+    "atleast_3d",
+    "average",
+    "clump_masked",
+    "clump_unmasked",
+    "column_stack",
+    "compress_cols",
+    "compress_nd",
+    "compress_rowcols",
+    "compress_rows",
+    "corrcoef",
+    "count_masked",
+    "cov",
+    "diagflat",
+    "dot",
+    "dstack",
+    "ediff1d",
+    "flatnotmasked_contiguous",
+    "flatnotmasked_edges",
+    "hsplit",
+    "hstack",
+    "in1d",
+    "intersect1d",
+    "isin",
+    "mask_cols",
+    "mask_rowcols",
+    "mask_rows",
+    "masked_all",
+    "masked_all_like",
+    "median",
+    "mr_",
+    "ndenumerate",
+    "notmasked_contiguous",
+    "notmasked_edges",
+    "polyfit",
+    "row_stack",
+    "setdiff1d",
+    "setxor1d",
+    "stack",
+    "union1d",
+    "unique",
+    "vander",
+    "vstack",
+]
+
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ScalarT1 = TypeVar("_ScalarT1", bound=np.generic)
+_ScalarT2 = TypeVar("_ScalarT2", bound=np.generic)
+_MArrayT = TypeVar("_MArrayT", bound=MaskedArray)
+
+_MArray: TypeAlias = MaskedArray[_AnyShape, np.dtype[_ScalarT]]
+
+###
+
+# keep in sync with `numpy._core.shape_base.atleast_1d`
+@overload
+def atleast_1d(a0: _ArrayLike[_ScalarT], /) -> _MArray[_ScalarT]: ...
+@overload
+def atleast_1d(a0: _ArrayLike[_ScalarT1], a1: _ArrayLike[_ScalarT2], /) -> tuple[_MArray[_ScalarT1], _MArray[_ScalarT2]]: ...
+@overload
+def atleast_1d(
+    a0: _ArrayLike[_ScalarT], a1: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[_MArray[_ScalarT], ...]: ...
+@overload
+def atleast_1d(a0: ArrayLike, /) -> _MArray[Incomplete]: ...
+@overload
+def atleast_1d(a0: ArrayLike, a1: ArrayLike, /) -> tuple[_MArray[Incomplete], _MArray[Incomplete]]: ...
+@overload
+def atleast_1d(a0: ArrayLike, a1: ArrayLike, /, *ai: ArrayLike) -> tuple[_MArray[Incomplete], ...]: ...
+
+# keep in sync with `numpy._core.shape_base.atleast_2d`
+@overload
+def atleast_2d(a0: _ArrayLike[_ScalarT], /) -> _MArray[_ScalarT]: ...
+@overload
+def atleast_2d(a0: _ArrayLike[_ScalarT1], a1: _ArrayLike[_ScalarT2], /) -> tuple[_MArray[_ScalarT1], _MArray[_ScalarT2]]: ...
+@overload
+def atleast_2d(
+    a0: _ArrayLike[_ScalarT], a1: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[_MArray[_ScalarT], ...]: ...
+@overload
+def atleast_2d(a0: ArrayLike, /) -> _MArray[Incomplete]: ...
+@overload
+def atleast_2d(a0: ArrayLike, a1: ArrayLike, /) -> tuple[_MArray[Incomplete], _MArray[Incomplete]]: ...
+@overload
+def atleast_2d(a0: ArrayLike, a1: ArrayLike, /, *ai: ArrayLike) -> tuple[_MArray[Incomplete], ...]: ...
+
+# keep in sync with `numpy._core.shape_base.atleast_2d`
+@overload
+def atleast_3d(a0: _ArrayLike[_ScalarT], /) -> _MArray[_ScalarT]: ...
+@overload
+def atleast_3d(a0: _ArrayLike[_ScalarT1], a1: _ArrayLike[_ScalarT2], /) -> tuple[_MArray[_ScalarT1], _MArray[_ScalarT2]]: ...
+@overload
+def atleast_3d(
+    a0: _ArrayLike[_ScalarT], a1: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[_MArray[_ScalarT], ...]: ...
+@overload
+def atleast_3d(a0: ArrayLike, /) -> _MArray[Incomplete]: ...
+@overload
+def atleast_3d(a0: ArrayLike, a1: ArrayLike, /) -> tuple[_MArray[Incomplete], _MArray[Incomplete]]: ...
+@overload
+def atleast_3d(a0: ArrayLike, a1: ArrayLike, /, *ai: ArrayLike) -> tuple[_MArray[Incomplete], ...]: ...
+
+# keep in sync with `numpy._core.shape_base.vstack`
+@overload
+def vstack(
+    tup: Sequence[_ArrayLike[_ScalarT]],
+    *,
+    dtype: None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def vstack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: _DTypeLike[_ScalarT],
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def vstack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[Incomplete]: ...
+
+row_stack = vstack
+
+# keep in sync with `numpy._core.shape_base.hstack`
+@overload
+def hstack(
+    tup: Sequence[_ArrayLike[_ScalarT]],
+    *,
+    dtype: None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def hstack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: _DTypeLike[_ScalarT],
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def hstack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[Incomplete]: ...
+
+# keep in sync with `numpy._core.shape_base_impl.column_stack`
+@overload
+def column_stack(tup: Sequence[_ArrayLike[_ScalarT]]) -> _MArray[_ScalarT]: ...
+@overload
+def column_stack(tup: Sequence[ArrayLike]) -> _MArray[Incomplete]: ...
+
+# keep in sync with `numpy._core.shape_base_impl.dstack`
+@overload
+def dstack(tup: Sequence[_ArrayLike[_ScalarT]]) -> _MArray[_ScalarT]: ...
+@overload
+def dstack(tup: Sequence[ArrayLike]) -> _MArray[Incomplete]: ...
+
+# keep in sync with `numpy._core.shape_base.stack`
+@overload
+def stack(
+    arrays: Sequence[_ArrayLike[_ScalarT]],
+    axis: SupportsIndex = 0,
+    out: None = None,
+    *,
+    dtype: None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def stack(
+    arrays: Sequence[ArrayLike],
+    axis: SupportsIndex = 0,
+    out: None = None,
+    *,
+    dtype: _DTypeLike[_ScalarT],
+    casting: _CastingKind = "same_kind"
+) -> _MArray[_ScalarT]: ...
+@overload
+def stack(
+    arrays: Sequence[ArrayLike],
+    axis: SupportsIndex = 0,
+    out: None = None,
+    *,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind"
+) -> _MArray[Incomplete]: ...
+@overload
+def stack(
+    arrays: Sequence[ArrayLike],
+    axis: SupportsIndex,
+    out: _MArrayT,
+    *,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind",
+) -> _MArrayT: ...
+@overload
+def stack(
+    arrays: Sequence[ArrayLike],
+    axis: SupportsIndex = 0,
+    *,
+    out: _MArrayT,
+    dtype: DTypeLike | None = None,
+    casting: _CastingKind = "same_kind",
+) -> _MArrayT: ...
+
+# keep in sync with `numpy._core.shape_base_impl.hsplit`
+@overload
+def hsplit(ary: _ArrayLike[_ScalarT], indices_or_sections: _ShapeLike) -> list[_MArray[_ScalarT]]: ...
+@overload
+def hsplit(ary: ArrayLike, indices_or_sections: _ShapeLike) -> list[_MArray[Incomplete]]: ...
+
+# keep in sync with `numpy._core.twodim_base_impl.hsplit`
+@overload
+def diagflat(v: _ArrayLike[_ScalarT], k: int = 0) -> _MArray[_ScalarT]: ...
+@overload
+def diagflat(v: ArrayLike, k: int = 0) -> _MArray[Incomplete]: ...
+
+# TODO: everything below
+
+def count_masked(arr, axis=None): ...
+def masked_all(shape, dtype=float): ...  # noqa: PYI014
+def masked_all_like(arr): ...
+
+def apply_along_axis(func1d, axis, arr, *args, **kwargs): ...
+def apply_over_axes(func, a, axes): ...
+def median(a, axis=None, out=None, overwrite_input=False, keepdims=False): ...
+def compress_nd(x, axis=None): ...
+def compress_rowcols(x, axis=None): ...
+def compress_rows(a): ...
+def compress_cols(a): ...
+def mask_rows(a, axis=...): ...
+def mask_cols(a, axis=...): ...
+def ediff1d(arr, to_end=None, to_begin=None): ...
+def unique(ar1, return_index=False, return_inverse=False): ...
+def intersect1d(ar1, ar2, assume_unique=False): ...
+def setxor1d(ar1, ar2, assume_unique=False): ...
+def in1d(ar1, ar2, assume_unique=False, invert=False): ...
+def isin(element, test_elements, assume_unique=False, invert=False): ...
+def union1d(ar1, ar2): ...
+def setdiff1d(ar1, ar2, assume_unique=False): ...
+def cov(x, y=None, rowvar=True, bias=False, allow_masked=True, ddof=None): ...
+def corrcoef(x, y=None, rowvar=True, allow_masked=True): ...
+
+class MAxisConcatenator(AxisConcatenator):
+    __slots__ = ()
+
+    @staticmethod
+    def concatenate(arrays: Incomplete, axis: int = 0) -> Incomplete: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    @classmethod
+    def makemat(cls, arr: Incomplete) -> Incomplete: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleVariableOverride]
+
+class mr_class(MAxisConcatenator):
+    __slots__ = ()
+
+    def __init__(self) -> None: ...
+
+mr_: mr_class
+
+def ndenumerate(a, compressed=True): ...
+def flatnotmasked_edges(a): ...
+def notmasked_edges(a, axis=None): ...
+def flatnotmasked_contiguous(a): ...
+def notmasked_contiguous(a, axis=None): ...
+def clump_unmasked(a): ...
+def clump_masked(a): ...
+def vander(x, n=None): ...
+def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): ...
+
+#
+def mask_rowcols(a: Incomplete, axis: Incomplete | None = None) -> MaskedArray[Incomplete, np.dtype[Incomplete]]: ...
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/mrecords.py b/python/user_packages/Python313/site-packages/numpy/ma/mrecords.py
new file mode 100644
index 0000000000000000000000000000000000000000..c37767f1beb6a1e95a0fc21876a45edc13ef8596
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/mrecords.py
@@ -0,0 +1,762 @@
+""":mod:`numpy.ma..mrecords`
+
+Defines the equivalent of :class:`numpy.recarrays` for masked arrays,
+where fields can be accessed as attributes.
+Note that :class:`numpy.ma.MaskedArray` already supports structured datatypes
+and the masking of individual fields.
+
+.. moduleauthor:: Pierre Gerard-Marchant
+
+"""
+#  We should make sure that no field is called '_mask','mask','_fieldmask',
+#  or whatever restricted keywords.  An idea would be to no bother in the
+#  first place, and then rename the invalid fields with a trailing
+#  underscore. Maybe we could just overload the parser function ?
+
+import warnings
+
+import numpy as np
+import numpy.ma as ma
+
+_byteorderconv = np._core.records._byteorderconv
+
+
+_check_fill_value = ma.core._check_fill_value
+
+
+__all__ = [
+    'MaskedRecords', 'mrecarray', 'fromarrays', 'fromrecords',
+    'fromtextfile', 'addfield',
+]
+
+reserved_fields = ['_data', '_mask', '_fieldmask', 'dtype']
+
+
+def _checknames(descr, names=None):
+    """
+    Checks that field names ``descr`` are not reserved keywords.
+
+    If this is the case, a default 'f%i' is substituted.  If the argument
+    `names` is not None, updates the field names to valid names.
+
+    """
+    ndescr = len(descr)
+    default_names = [f'f{i}' for i in range(ndescr)]
+    if names is None:
+        new_names = default_names
+    else:
+        if isinstance(names, (tuple, list)):
+            new_names = names
+        elif isinstance(names, str):
+            new_names = names.split(',')
+        else:
+            raise NameError(f'illegal input names {names!r}')
+        nnames = len(new_names)
+        if nnames < ndescr:
+            new_names += default_names[nnames:]
+    ndescr = []
+    for (n, d, t) in zip(new_names, default_names, descr.descr):
+        if n in reserved_fields:
+            if t[0] in reserved_fields:
+                ndescr.append((d, t[1]))
+            else:
+                ndescr.append(t)
+        else:
+            ndescr.append((n, t[1]))
+    return np.dtype(ndescr)
+
+
+def _get_fieldmask(self):
+    mdescr = [(n, '|b1') for n in self.dtype.names]
+    fdmask = np.empty(self.shape, dtype=mdescr)
+    fdmask.flat = tuple([False] * len(mdescr))
+    return fdmask
+
+
+class MaskedRecords(ma.MaskedArray):
+    """
+
+    Attributes
+    ----------
+    _data : recarray
+        Underlying data, as a record array.
+    _mask : boolean array
+        Mask of the records. A record is masked when all its fields are
+        masked.
+    _fieldmask : boolean recarray
+        Record array of booleans, setting the mask of each individual field
+        of each record.
+    _fill_value : record
+        Filling values for each field.
+
+    """
+
+    def __new__(cls, shape, dtype=None, buf=None, offset=0, strides=None,
+                formats=None, names=None, titles=None,
+                byteorder=None, aligned=False,
+                mask=ma.nomask, hard_mask=False, fill_value=None, keep_mask=True,
+                copy=False,
+                **options):
+
+        self = np.recarray.__new__(cls, shape, dtype=dtype, buf=buf, offset=offset,
+                                   strides=strides, formats=formats, names=names,
+                                   titles=titles, byteorder=byteorder,
+                                   aligned=aligned,)
+
+        mdtype = ma.make_mask_descr(self.dtype)
+        if mask is ma.nomask or not np.size(mask):
+            if not keep_mask:
+                self._mask = tuple([False] * len(mdtype))
+        else:
+            mask = np.array(mask, copy=copy)
+            if mask.shape != self.shape:
+                (nd, nm) = (self.size, mask.size)
+                if nm == 1:
+                    mask = np.resize(mask, self.shape)
+                elif nm == nd:
+                    mask = np.reshape(mask, self.shape)
+                else:
+                    msg = (f"Mask and data not compatible: data size is {nd},"
+                           " mask size is {nm}.")
+                    raise ma.MAError(msg)
+            if not keep_mask:
+                self.__setmask__(mask)
+                self._sharedmask = True
+            else:
+                if mask.dtype == mdtype:
+                    _mask = mask
+                else:
+                    _mask = np.array([tuple([m] * len(mdtype)) for m in mask],
+                                     dtype=mdtype)
+                self._mask = _mask
+        return self
+
+    def __array_finalize__(self, obj):
+        # Make sure we have a _fieldmask by default
+        _mask = getattr(obj, '_mask', None)
+        if _mask is None:
+            objmask = getattr(obj, '_mask', ma.nomask)
+            _dtype = np.ndarray.__getattribute__(self, 'dtype')
+            if objmask is ma.nomask:
+                _mask = ma.make_mask_none(self.shape, dtype=_dtype)
+            else:
+                mdescr = ma.make_mask_descr(_dtype)
+                _mask = np.array([tuple([m] * len(mdescr)) for m in objmask],
+                               dtype=mdescr).view(np.recarray)
+        # Update some of the attributes
+        _dict = self.__dict__
+        _dict.update(_mask=_mask)
+        self._update_from(obj)
+        if _dict['_baseclass'] == np.ndarray:
+            _dict['_baseclass'] = np.recarray
+
+    @property
+    def _data(self):
+        """
+        Returns the data as a recarray.
+
+        """
+        return np.ndarray.view(self, np.recarray)
+
+    @property
+    def _fieldmask(self):
+        """
+        Alias to mask.
+
+        """
+        return self._mask
+
+    def __len__(self):
+        """
+        Returns the length
+
+        """
+        # We have more than one record
+        if self.ndim:
+            return len(self._data)
+        # We have only one record: return the nb of fields
+        return len(self.dtype)
+
+    def __getattribute__(self, attr):
+        try:
+            return object.__getattribute__(self, attr)
+        except AttributeError:
+            # attr must be a fieldname
+            pass
+        fielddict = np.ndarray.__getattribute__(self, 'dtype').fields
+        try:
+            res = fielddict[attr][:2]
+        except (TypeError, KeyError) as e:
+            raise AttributeError(
+                f'record array has no attribute {attr}') from e
+        # So far, so good
+        _localdict = np.ndarray.__getattribute__(self, '__dict__')
+        _data = np.ndarray.view(self, _localdict['_baseclass'])
+        obj = _data.getfield(*res)
+        if obj.dtype.names is not None:
+            raise NotImplementedError("MaskedRecords is currently limited to"
+                                      "simple records.")
+        # Get some special attributes
+        # Reset the object's mask
+        hasmasked = False
+        _mask = _localdict.get('_mask', None)
+        if _mask is not None:
+            try:
+                _mask = _mask[attr]
+            except IndexError:
+                # Couldn't find a mask: use the default (nomask)
+                pass
+            tp_len = len(_mask.dtype)
+            hasmasked = _mask.view((bool, ((tp_len,) if tp_len else ()))).any()
+        if (obj.shape or hasmasked):
+            obj = obj.view(ma.MaskedArray)
+            obj._baseclass = np.ndarray
+            obj._isfield = True
+            obj._mask = _mask
+            # Reset the field values
+            _fill_value = _localdict.get('_fill_value', None)
+            if _fill_value is not None:
+                try:
+                    obj._fill_value = _fill_value[attr]
+                except ValueError:
+                    obj._fill_value = None
+        else:
+            obj = obj.item()
+        return obj
+
+    def __setattr__(self, attr, val):
+        """
+        Sets the attribute attr to the value val.
+
+        """
+        # Should we call __setmask__ first ?
+        if attr in ['mask', 'fieldmask']:
+            self.__setmask__(val)
+            return
+        # Create a shortcut (so that we don't have to call getattr all the time)
+        _localdict = object.__getattribute__(self, '__dict__')
+        # Check whether we're creating a new field
+        newattr = attr not in _localdict
+        try:
+            # Is attr a generic attribute ?
+            ret = object.__setattr__(self, attr, val)
+        except Exception:
+            # Not a generic attribute: exit if it's not a valid field
+            fielddict = np.ndarray.__getattribute__(self, 'dtype').fields or {}
+            optinfo = np.ndarray.__getattribute__(self, '_optinfo') or {}
+            if not (attr in fielddict or attr in optinfo):
+                raise
+        else:
+            # Get the list of names
+            fielddict = np.ndarray.__getattribute__(self, 'dtype').fields or {}
+            # Check the attribute
+            if attr not in fielddict:
+                return ret
+            if newattr:
+                # We just added this one or this setattr worked on an
+                # internal attribute.
+                try:
+                    object.__delattr__(self, attr)
+                except Exception:
+                    return ret
+        # Let's try to set the field
+        try:
+            res = fielddict[attr][:2]
+        except (TypeError, KeyError) as e:
+            raise AttributeError(
+                f'record array has no attribute {attr}') from e
+
+        if val is ma.masked:
+            _fill_value = _localdict['_fill_value']
+            if _fill_value is not None:
+                dval = _localdict['_fill_value'][attr]
+            else:
+                dval = val
+            mval = True
+        else:
+            dval = ma.filled(val)
+            mval = ma.getmaskarray(val)
+        obj = np.ndarray.__getattribute__(self, '_data').setfield(dval, *res)
+        _localdict['_mask'].__setitem__(attr, mval)
+        return obj
+
+    def __getitem__(self, indx):
+        """
+        Returns all the fields sharing the same fieldname base.
+
+        The fieldname base is either `_data` or `_mask`.
+
+        """
+        _localdict = self.__dict__
+        _mask = np.ndarray.__getattribute__(self, '_mask')
+        _data = np.ndarray.view(self, _localdict['_baseclass'])
+        # We want a field
+        if isinstance(indx, str):
+            # Make sure _sharedmask is True to propagate back to _fieldmask
+            # Don't use _set_mask, there are some copies being made that
+            # break propagation Don't force the mask to nomask, that wreaks
+            # easy masking
+            obj = _data[indx].view(ma.MaskedArray)
+            obj._mask = _mask[indx]
+            obj._sharedmask = True
+            fval = _localdict['_fill_value']
+            if fval is not None:
+                obj._fill_value = fval[indx]
+            # Force to masked if the mask is True
+            if not obj.ndim and obj._mask:
+                return ma.masked
+            return obj
+        # We want some elements.
+        # First, the data.
+        obj = np.asarray(_data[indx]).view(mrecarray)
+        obj._mask = np.asarray(_mask[indx]).view(np.recarray)
+        return obj
+
+    def __setitem__(self, indx, value):
+        """
+        Sets the given record to value.
+
+        """
+        ma.MaskedArray.__setitem__(self, indx, value)
+        if isinstance(indx, str):
+            self._mask[indx] = ma.getmaskarray(value)
+
+    def __str__(self):
+        """
+        Calculates the string representation.
+
+        """
+        if self.size > 1:
+            mstr = [f"({','.join([str(i) for i in s])})"
+                    for s in zip(*[getattr(self, f) for f in self.dtype.names])]
+            return f"[{', '.join(mstr)}]"
+        else:
+            mstr = [f"{','.join([str(i) for i in s])}"
+                    for s in zip([getattr(self, f) for f in self.dtype.names])]
+            return f"({', '.join(mstr)})"
+
+    def __repr__(self):
+        """
+        Calculates the repr representation.
+
+        """
+        _names = self.dtype.names
+        fmt = f"%{max(len(n) for n in _names) + 4}s : %s"
+        reprstr = [fmt % (f, getattr(self, f)) for f in self.dtype.names]
+        reprstr.insert(0, 'masked_records(')
+        reprstr.extend([fmt % ('    fill_value', self.fill_value),
+                        '              )'])
+        return str("\n".join(reprstr))
+
+    def view(self, dtype=None, type=None):
+        """
+        Returns a view of the mrecarray.
+
+        """
+        # OK, basic copy-paste from MaskedArray.view.
+        if dtype is None:
+            if type is None:
+                output = np.ndarray.view(self)
+            else:
+                output = np.ndarray.view(self, type)
+        # Here again.
+        elif type is None:
+            try:
+                if issubclass(dtype, np.ndarray):
+                    output = np.ndarray.view(self, dtype)
+                else:
+                    output = np.ndarray.view(self, dtype)
+            # OK, there's the change
+            except TypeError:
+                dtype = np.dtype(dtype)
+                # we need to revert to MaskedArray, but keeping the possibility
+                # of subclasses (eg, TimeSeriesRecords), so we'll force a type
+                # set to the first parent
+                if dtype.fields is None:
+                    basetype = self.__class__.__bases__[0]
+                    output = self.__array__().view(dtype, basetype)
+                    output._update_from(self)
+                else:
+                    output = np.ndarray.view(self, dtype)
+                output._fill_value = None
+        else:
+            output = np.ndarray.view(self, dtype, type)
+        # Update the mask, just like in MaskedArray.view
+        if (getattr(output, '_mask', ma.nomask) is not ma.nomask):
+            mdtype = ma.make_mask_descr(output.dtype)
+            output._mask = self._mask.view(mdtype, np.ndarray)
+            output._mask.shape = output.shape
+        return output
+
+    def harden_mask(self):
+        """
+        Forces the mask to hard.
+
+        """
+        self._hardmask = True
+
+    def soften_mask(self):
+        """
+        Forces the mask to soft
+
+        """
+        self._hardmask = False
+
+    def copy(self):
+        """
+        Returns a copy of the masked record.
+
+        """
+        copied = self._data.copy().view(type(self))
+        copied._mask = self._mask.copy()
+        return copied
+
+    def tolist(self, fill_value=None):
+        """
+        Return the data portion of the array as a list.
+
+        Data items are converted to the nearest compatible Python type.
+        Masked values are converted to fill_value. If fill_value is None,
+        the corresponding entries in the output list will be ``None``.
+
+        """
+        if fill_value is not None:
+            return self.filled(fill_value).tolist()
+        result = np.array(self.filled().tolist(), dtype=object)
+        mask = np.array(self._mask.tolist())
+        result[mask] = None
+        return result.tolist()
+
+    def __getstate__(self):
+        """Return the internal state of the masked array.
+
+        This is for pickling.
+
+        """
+        state = (1,
+                 self.shape,
+                 self.dtype,
+                 self.flags.fnc,
+                 self._data.tobytes(),
+                 self._mask.tobytes(),
+                 self._fill_value,
+                 )
+        return state
+
+    def __setstate__(self, state):
+        """
+        Restore the internal state of the masked array.
+
+        This is for pickling.  ``state`` is typically the output of the
+        ``__getstate__`` output, and is a 5-tuple:
+
+        - class name
+        - a tuple giving the shape of the data
+        - a typecode for the data
+        - a binary string for the data
+        - a binary string for the mask.
+
+        """
+        (ver, shp, typ, isf, raw, msk, flv) = state
+        np.ndarray.__setstate__(self, (shp, typ, isf, raw))
+        mdtype = np.dtype([(k, np.bool) for (k, _) in self.dtype.descr])
+        self.__dict__['_mask'].__setstate__((shp, mdtype, isf, msk))
+        self.fill_value = flv
+
+    def __reduce__(self):
+        """
+        Return a 3-tuple for pickling a MaskedArray.
+
+        """
+        return (_mrreconstruct,
+                (self.__class__, self._baseclass, (0,), 'b',),
+                self.__getstate__())
+
+
+def _mrreconstruct(subtype, baseclass, baseshape, basetype,):
+    """
+    Build a new MaskedArray from the information stored in a pickle.
+
+    """
+    _data = np.ndarray.__new__(baseclass, baseshape, basetype).view(subtype)
+    _mask = np.ndarray.__new__(np.ndarray, baseshape, 'b1')
+    return subtype.__new__(subtype, _data, mask=_mask, dtype=basetype,)
+
+
+mrecarray = MaskedRecords
+
+
+###############################################################################
+#                             Constructors                                    #
+###############################################################################
+
+
+def fromarrays(arraylist, dtype=None, shape=None, formats=None,
+               names=None, titles=None, aligned=False, byteorder=None,
+               fill_value=None):
+    """
+    Creates a mrecarray from a (flat) list of masked arrays.
+
+    Parameters
+    ----------
+    arraylist : sequence
+        A list of (masked) arrays. Each element of the sequence is first converted
+        to a masked array if needed. If a 2D array is passed as argument, it is
+        processed line by line
+    dtype : {None, dtype}, optional
+        Data type descriptor.
+    shape : {None, integer}, optional
+        Number of records. If None, shape is defined from the shape of the
+        first array in the list.
+    formats : {None, sequence}, optional
+        Sequence of formats for each individual field. If None, the formats will
+        be autodetected by inspecting the fields and selecting the highest dtype
+        possible.
+    names : {None, sequence}, optional
+        Sequence of the names of each field.
+    fill_value : {None, sequence}, optional
+        Sequence of data to be used as filling values.
+
+    Notes
+    -----
+    Lists of tuples should be preferred over lists of lists for faster processing.
+
+    """
+    datalist = [ma.getdata(x) for x in arraylist]
+    masklist = [np.atleast_1d(ma.getmaskarray(x)) for x in arraylist]
+    _array = np.rec.fromarrays(datalist,
+                               dtype=dtype, shape=shape, formats=formats,
+                               names=names, titles=titles, aligned=aligned,
+                               byteorder=byteorder).view(mrecarray)
+    _array._mask.flat = list(zip(*masklist))
+    if fill_value is not None:
+        _array.fill_value = fill_value
+    return _array
+
+
+def fromrecords(reclist, dtype=None, shape=None, formats=None, names=None,
+                titles=None, aligned=False, byteorder=None,
+                fill_value=None, mask=ma.nomask):
+    """
+    Creates a MaskedRecords from a list of records.
+
+    Parameters
+    ----------
+    reclist : sequence
+        A list of records. Each element of the sequence is first converted
+        to a masked array if needed. If a 2D array is passed as argument, it is
+        processed line by line
+    dtype : {None, dtype}, optional
+        Data type descriptor.
+    shape : {None,int}, optional
+        Number of records. If None, ``shape`` is defined from the shape of the
+        first array in the list.
+    formats : {None, sequence}, optional
+        Sequence of formats for each individual field. If None, the formats will
+        be autodetected by inspecting the fields and selecting the highest dtype
+        possible.
+    names : {None, sequence}, optional
+        Sequence of the names of each field.
+    fill_value : {None, sequence}, optional
+        Sequence of data to be used as filling values.
+    mask : {nomask, sequence}, optional.
+        External mask to apply on the data.
+
+    Notes
+    -----
+    Lists of tuples should be preferred over lists of lists for faster processing.
+
+    """
+    # Grab the initial _fieldmask, if needed:
+    _mask = getattr(reclist, '_mask', None)
+    # Get the list of records.
+    if isinstance(reclist, np.ndarray):
+        # Make sure we don't have some hidden mask
+        if isinstance(reclist, ma.MaskedArray):
+            reclist = reclist.filled().view(np.ndarray)
+        # Grab the initial dtype, just in case
+        if dtype is None:
+            dtype = reclist.dtype
+        reclist = reclist.tolist()
+    mrec = np.rec.fromrecords(reclist, dtype=dtype, shape=shape, formats=formats,
+                          names=names, titles=titles,
+                          aligned=aligned, byteorder=byteorder).view(mrecarray)
+    # Set the fill_value if needed
+    if fill_value is not None:
+        mrec.fill_value = fill_value
+    # Now, let's deal w/ the mask
+    if mask is not ma.nomask:
+        mask = np.asarray(mask)
+        maskrecordlength = len(mask.dtype)
+        if maskrecordlength:
+            mrec._mask.flat = mask
+        elif mask.ndim == 2:
+            mrec._mask.flat = [tuple(m) for m in mask]
+        else:
+            mrec.__setmask__(mask)
+    if _mask is not None:
+        mrec._mask[:] = _mask
+    return mrec
+
+
+def _guessvartypes(arr):
+    """
+    Tries to guess the dtypes of the str_ ndarray `arr`.
+
+    Guesses by testing element-wise conversion. Returns a list of dtypes.
+    The array is first converted to ndarray. If the array is 2D, the test
+    is performed on the first line. An exception is raised if the file is
+    3D or more.
+
+    """
+    vartypes = []
+    arr = np.asarray(arr)
+    if arr.ndim == 2:
+        arr = arr[0]
+    elif arr.ndim > 2:
+        raise ValueError("The array should be 2D at most!")
+    # Start the conversion loop.
+    for f in arr:
+        try:
+            int(f)
+        except (ValueError, TypeError):
+            try:
+                float(f)
+            except (ValueError, TypeError):
+                try:
+                    complex(f)
+                except (ValueError, TypeError):
+                    vartypes.append(arr.dtype)
+                else:
+                    vartypes.append(np.dtype(complex))
+            else:
+                vartypes.append(np.dtype(float))
+        else:
+            vartypes.append(np.dtype(int))
+    return vartypes
+
+
+def openfile(fname):
+    """
+    Opens the file handle of file `fname`.
+
+    """
+    # A file handle
+    if hasattr(fname, 'readline'):
+        return fname
+    # Try to open the file and guess its type
+    try:
+        f = open(fname)
+    except FileNotFoundError as e:
+        raise FileNotFoundError(f"No such file: '{fname}'") from e
+    if f.readline()[:2] != "\\x":
+        f.seek(0, 0)
+        return f
+    f.close()
+    raise NotImplementedError("Wow, binary file")
+
+
+def fromtextfile(fname, delimiter=None, commentchar='#', missingchar='',
+                 varnames=None, vartypes=None):
+    """
+    Creates a mrecarray from data stored in the file `filename`.
+
+    Parameters
+    ----------
+    fname : {file name/handle}
+        Handle of an opened file.
+    delimiter : {None, string}, optional
+        Alphanumeric character used to separate columns in the file.
+        If None, any (group of) white spacestring(s) will be used.
+    commentchar : {'#', string}, optional
+        Alphanumeric character used to mark the start of a comment.
+    missingchar : {'', string}, optional
+        String indicating missing data, and used to create the masks.
+    varnames : {None, sequence}, optional
+        Sequence of the variable names. If None, a list will be created from
+        the first non empty line of the file.
+    vartypes : {None, sequence}, optional
+        Sequence of the variables dtypes. If None, it will be estimated from
+        the first non-commented line.
+
+
+    Ultra simple: the varnames are in the header, one line"""
+
+    # Try to open the file.
+    ftext = openfile(fname)
+
+    # Get the first non-empty line as the varnames
+    while True:
+        line = ftext.readline()
+        firstline = line[:line.find(commentchar)].strip()
+        _varnames = firstline.split(delimiter)
+        if len(_varnames) > 1:
+            break
+    if varnames is None:
+        varnames = _varnames
+
+    # Get the data.
+    _variables = ma.masked_array([line.strip().split(delimiter) for line in ftext
+                                 if line[0] != commentchar and len(line) > 1])
+    (_, nfields) = _variables.shape
+    ftext.close()
+
+    # Try to guess the dtype.
+    if vartypes is None:
+        vartypes = _guessvartypes(_variables[0])
+    else:
+        vartypes = [np.dtype(v) for v in vartypes]
+        if len(vartypes) != nfields:
+            msg = f"Attempting to {len(vartypes)} dtypes for {nfields} fields!"
+            msg += " Reverting to default."
+            warnings.warn(msg, stacklevel=2)
+            vartypes = _guessvartypes(_variables[0])
+
+    # Construct the descriptor.
+    mdescr = list(zip(varnames, vartypes))
+    mfillv = [ma.default_fill_value(f) for f in vartypes]
+
+    # Get the data and the mask.
+    # We just need a list of masked_arrays. It's easier to create it like that:
+    _mask = (_variables.T == missingchar)
+    _datalist = [ma.masked_array(a, mask=m, dtype=t, fill_value=f)
+                 for (a, m, t, f) in zip(_variables.T, _mask, vartypes, mfillv)]
+
+    return fromarrays(_datalist, dtype=mdescr)
+
+
+def addfield(mrecord, newfield, newfieldname=None):
+    """Adds a new field to the masked record array
+
+    Uses `newfield` as data and `newfieldname` as name. If `newfieldname`
+    is None, the new field name is set to 'fi', where `i` is the number of
+    existing fields.
+
+    """
+    _data = mrecord._data
+    _mask = mrecord._mask
+    if newfieldname is None or newfieldname in reserved_fields:
+        newfieldname = f'f{len(_data.dtype)}'
+    newfield = ma.array(newfield)
+    # Get the new data.
+    # Create a new empty recarray
+    newdtype = np.dtype(_data.dtype.descr + [(newfieldname, newfield.dtype)])
+    newdata = np.recarray(_data.shape, newdtype)
+    # Add the existing field
+    [newdata.setfield(_data.getfield(*f), *f)
+     for f in _data.dtype.fields.values()]
+    # Add the new field
+    newdata.setfield(newfield._data, *newdata.dtype.fields[newfieldname])
+    newdata = newdata.view(MaskedRecords)
+    # Get the new mask
+    # Create a new empty recarray
+    newmdtype = np.dtype([(n, np.bool) for n in newdtype.names])
+    newmask = np.recarray(_data.shape, newmdtype)
+    # Add the old masks
+    [newmask.setfield(_mask.getfield(*f), *f)
+     for f in _mask.dtype.fields.values()]
+    # Add the mask of the new field
+    newmask.setfield(ma.getmaskarray(newfield),
+                     *newmask.dtype.fields[newfieldname])
+    newdata._mask = newmask
+    return newdata
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/mrecords.pyi b/python/user_packages/Python313/site-packages/numpy/ma/mrecords.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..c11df1d064568472e7eb4ee85a1aca16601bf48b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/mrecords.pyi
@@ -0,0 +1,96 @@
+from typing import Any, Generic
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy._typing import _AnyShape
+
+from .core import MaskedArray
+
+__all__ = [
+    "MaskedRecords",
+    "mrecarray",
+    "fromarrays",
+    "fromrecords",
+    "fromtextfile",
+    "addfield",
+]
+
+_ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=_AnyShape, covariant=True)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
+
+class MaskedRecords(MaskedArray[_ShapeT_co, _DTypeT_co], Generic[_ShapeT_co, _DTypeT_co]):
+    def __new__(
+        cls,
+        shape,
+        dtype=...,
+        buf=...,
+        offset=...,
+        strides=...,
+        formats=...,
+        names=...,
+        titles=...,
+        byteorder=...,
+        aligned=...,
+        mask=...,
+        hard_mask=...,
+        fill_value=...,
+        keep_mask=...,
+        copy=...,
+        **options,
+    ): ...
+    _mask: Any
+    _fill_value: Any
+    @property
+    def _data(self): ...
+    @property
+    def _fieldmask(self): ...
+    def __array_finalize__(self, obj): ...
+    def __len__(self): ...
+    def __getattribute__(self, attr): ...
+    def __setattr__(self, attr, val): ...
+    def __getitem__(self, indx): ...
+    def __setitem__(self, indx, value): ...
+    def view(self, dtype=None, type=None): ...
+    def harden_mask(self): ...
+    def soften_mask(self): ...
+    def copy(self): ...
+    def tolist(self, fill_value=None): ...
+    def __reduce__(self): ...
+
+mrecarray = MaskedRecords
+
+def fromarrays(
+    arraylist,
+    dtype=None,
+    shape=None,
+    formats=None,
+    names=None,
+    titles=None,
+    aligned=False,
+    byteorder=None,
+    fill_value=None,
+): ...
+
+def fromrecords(
+    reclist,
+    dtype=None,
+    shape=None,
+    formats=None,
+    names=None,
+    titles=None,
+    aligned=False,
+    byteorder=None,
+    fill_value=None,
+    mask=...,
+): ...
+
+def fromtextfile(
+    fname,
+    delimiter=None,
+    commentchar="#",
+    missingchar="",
+    varnames=None,
+    vartypes=None,
+): ...
+
+def addfield(mrecord, newfield, newfieldname=None): ...
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/testutils.py b/python/user_packages/Python313/site-packages/numpy/ma/testutils.py
new file mode 100644
index 0000000000000000000000000000000000000000..2c72a530c5959aa50cd96008b70686295660d0e4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/testutils.py
@@ -0,0 +1,294 @@
+"""Miscellaneous functions for testing masked arrays and subclasses
+
+:author: Pierre Gerard-Marchant
+:contact: pierregm_at_uga_dot_edu
+
+"""
+import operator
+
+import numpy as np
+import numpy._core.umath as umath
+import numpy.testing
+from numpy import ndarray
+from numpy.testing import (  # noqa: F401
+    assert_,
+    assert_allclose,
+    assert_array_almost_equal_nulp,
+    assert_raises,
+    build_err_msg,
+)
+
+from .core import filled, getmask, mask_or, masked, masked_array, nomask
+
+__all__masked = [
+    'almost', 'approx', 'assert_almost_equal', 'assert_array_almost_equal',
+    'assert_array_approx_equal', 'assert_array_compare',
+    'assert_array_equal', 'assert_array_less', 'assert_close',
+    'assert_equal', 'assert_equal_records', 'assert_mask_equal',
+    'assert_not_equal', 'fail_if_array_equal',
+    ]
+
+# Include some normal test functions to avoid breaking other projects who
+# have mistakenly included them from this file. SciPy is one. That is
+# unfortunate, as some of these functions are not intended to work with
+# masked arrays. But there was no way to tell before.
+from unittest import TestCase  # noqa: F401
+
+__some__from_testing = [
+    'TestCase', 'assert_', 'assert_allclose', 'assert_array_almost_equal_nulp',
+    'assert_raises'
+    ]
+
+__all__ = __all__masked + __some__from_testing  # noqa: PLE0605
+
+
+def approx(a, b, fill_value=True, rtol=1e-5, atol=1e-8):
+    """
+    Returns true if all components of a and b are equal to given tolerances.
+
+    If fill_value is True, masked values considered equal. Otherwise,
+    masked values are considered unequal.  The relative error rtol should
+    be positive and << 1.0 The absolute error atol comes into play for
+    those elements of b that are very small or zero; it says how small a
+    must be also.
+
+    """
+    m = mask_or(getmask(a), getmask(b))
+    d1 = filled(a)
+    d2 = filled(b)
+    if d1.dtype.char == "O" or d2.dtype.char == "O":
+        return np.equal(d1, d2).ravel()
+    x = filled(
+        masked_array(d1, copy=False, mask=m), fill_value
+    ).astype(np.float64)
+    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(np.float64)
+    d = np.less_equal(umath.absolute(x - y), atol + rtol * umath.absolute(y))
+    return d.ravel()
+
+
+def almost(a, b, decimal=6, fill_value=True):
+    """
+    Returns True if a and b are equal up to decimal places.
+
+    If fill_value is True, masked values considered equal. Otherwise,
+    masked values are considered unequal.
+
+    """
+    m = mask_or(getmask(a), getmask(b))
+    d1 = filled(a)
+    d2 = filled(b)
+    if d1.dtype.char == "O" or d2.dtype.char == "O":
+        return np.equal(d1, d2).ravel()
+    x = filled(
+        masked_array(d1, copy=False, mask=m), fill_value
+    ).astype(np.float64)
+    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(np.float64)
+    d = np.around(np.abs(x - y), decimal) <= 10.0 ** (-decimal)
+    return d.ravel()
+
+
+def _assert_equal_on_sequences(actual, desired, err_msg=''):
+    """
+    Asserts the equality of two non-array sequences.
+
+    """
+    assert_equal(len(actual), len(desired), err_msg)
+    for k in range(len(desired)):
+        assert_equal(actual[k], desired[k], f'item={k!r}\n{err_msg}')
+
+
+def assert_equal_records(a, b):
+    """
+    Asserts that two records are equal.
+
+    Pretty crude for now.
+
+    """
+    assert_equal(a.dtype, b.dtype)
+    for f in a.dtype.names:
+        (af, bf) = (operator.getitem(a, f), operator.getitem(b, f))
+        if not (af is masked) and not (bf is masked):
+            assert_equal(operator.getitem(a, f), operator.getitem(b, f))
+
+
+def assert_equal(actual, desired, err_msg=''):
+    """
+    Asserts that two items are equal.
+
+    """
+    # Case #1: dictionary .....
+    if isinstance(desired, dict):
+        if not isinstance(actual, dict):
+            raise AssertionError(repr(type(actual)))
+        assert_equal(len(actual), len(desired), err_msg)
+        for k in desired:
+            if k not in actual:
+                raise AssertionError(f"{k} not in {actual}")
+            assert_equal(actual[k], desired[k], f'key={k!r}\n{err_msg}')
+        return
+    # Case #2: lists .....
+    if isinstance(desired, (list, tuple)) and isinstance(actual, (list, tuple)):
+        return _assert_equal_on_sequences(actual, desired, err_msg='')
+    if not (isinstance(actual, ndarray) or isinstance(desired, ndarray)):
+        msg = build_err_msg([actual, desired], err_msg,)
+        if not desired == actual:
+            raise AssertionError(msg)
+        return
+    # Case #4. arrays or equivalent
+    if ((actual is masked) and not (desired is masked)) or \
+            ((desired is masked) and not (actual is masked)):
+        msg = build_err_msg([actual, desired],
+                            err_msg, header='', names=('x', 'y'))
+        raise ValueError(msg)
+    actual = np.asanyarray(actual)
+    desired = np.asanyarray(desired)
+    (actual_dtype, desired_dtype) = (actual.dtype, desired.dtype)
+    if actual_dtype.char == "S" and desired_dtype.char == "S":
+        return _assert_equal_on_sequences(actual.tolist(),
+                                          desired.tolist(),
+                                          err_msg='')
+    return assert_array_equal(actual, desired, err_msg)
+
+
+def fail_if_equal(actual, desired, err_msg='',):
+    """
+    Raises an assertion error if two items are equal.
+
+    """
+    if isinstance(desired, dict):
+        if not isinstance(actual, dict):
+            raise AssertionError(repr(type(actual)))
+        fail_if_equal(len(actual), len(desired), err_msg)
+        for k in desired:
+            if k not in actual:
+                raise AssertionError(repr(k))
+            fail_if_equal(actual[k], desired[k], f'key={k!r}\n{err_msg}')
+        return
+    if isinstance(desired, (list, tuple)) and isinstance(actual, (list, tuple)):
+        fail_if_equal(len(actual), len(desired), err_msg)
+        for k in range(len(desired)):
+            fail_if_equal(actual[k], desired[k], f'item={k!r}\n{err_msg}')
+        return
+    if isinstance(actual, np.ndarray) or isinstance(desired, np.ndarray):
+        return fail_if_array_equal(actual, desired, err_msg)
+    msg = build_err_msg([actual, desired], err_msg)
+    if not desired != actual:
+        raise AssertionError(msg)
+
+
+assert_not_equal = fail_if_equal
+
+
+def assert_almost_equal(actual, desired, decimal=7, err_msg='', verbose=True):
+    """
+    Asserts that two items are almost equal.
+
+    The test is equivalent to abs(desired-actual) < 0.5 * 10**(-decimal).
+
+    """
+    if isinstance(actual, np.ndarray) or isinstance(desired, np.ndarray):
+        return assert_array_almost_equal(actual, desired, decimal=decimal,
+                                         err_msg=err_msg, verbose=verbose)
+    msg = build_err_msg([actual, desired],
+                        err_msg=err_msg, verbose=verbose)
+    if not round(abs(desired - actual), decimal) == 0:
+        raise AssertionError(msg)
+
+
+assert_close = assert_almost_equal
+
+
+def assert_array_compare(comparison, x, y, err_msg='', verbose=True, header='',
+                         fill_value=True):
+    """
+    Asserts that comparison between two masked arrays is satisfied.
+
+    The comparison is elementwise.
+
+    """
+    # Allocate a common mask and refill
+    m = mask_or(getmask(x), getmask(y))
+    x = masked_array(x, copy=False, mask=m, keep_mask=False, subok=False)
+    y = masked_array(y, copy=False, mask=m, keep_mask=False, subok=False)
+    if ((x is masked) and not (y is masked)) or \
+            ((y is masked) and not (x is masked)):
+        msg = build_err_msg([x, y], err_msg=err_msg, verbose=verbose,
+                            header=header, names=('x', 'y'))
+        raise ValueError(msg)
+    # OK, now run the basic tests on filled versions
+    return np.testing.assert_array_compare(comparison,
+                                           x.filled(fill_value),
+                                           y.filled(fill_value),
+                                           err_msg=err_msg,
+                                           verbose=verbose, header=header)
+
+
+def assert_array_equal(x, y, err_msg='', verbose=True):
+    """
+    Checks the elementwise equality of two masked arrays.
+
+    """
+    assert_array_compare(operator.__eq__, x, y,
+                         err_msg=err_msg, verbose=verbose,
+                         header='Arrays are not equal')
+
+
+def fail_if_array_equal(x, y, err_msg='', verbose=True):
+    """
+    Raises an assertion error if two masked arrays are not equal elementwise.
+
+    """
+    def compare(x, y):
+        return (not np.all(approx(x, y)))
+    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
+                         header='Arrays are not equal')
+
+
+def assert_array_approx_equal(x, y, decimal=6, err_msg='', verbose=True):
+    """
+    Checks the equality of two masked arrays, up to given number odecimals.
+
+    The equality is checked elementwise.
+
+    """
+    def compare(x, y):
+        "Returns the result of the loose comparison between x and y)."
+        return approx(x, y, rtol=10. ** -decimal)
+    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
+                         header='Arrays are not almost equal')
+
+
+def assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True):
+    """
+    Checks the equality of two masked arrays, up to given number odecimals.
+
+    The equality is checked elementwise.
+
+    """
+    def compare(x, y):
+        "Returns the result of the loose comparison between x and y)."
+        return almost(x, y, decimal)
+    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
+                         header='Arrays are not almost equal')
+
+
+def assert_array_less(x, y, err_msg='', verbose=True):
+    """
+    Checks that x is smaller than y elementwise.
+
+    """
+    assert_array_compare(operator.__lt__, x, y,
+                         err_msg=err_msg, verbose=verbose,
+                         header='Arrays are not less-ordered')
+
+
+def assert_mask_equal(m1, m2, err_msg=''):
+    """
+    Asserts the equality of two masks.
+
+    """
+    if m1 is nomask:
+        assert_(m2 is nomask)
+    if m2 is nomask:
+        assert_(m1 is nomask)
+    assert_array_equal(m1, m2, err_msg=err_msg)
diff --git a/python/user_packages/Python313/site-packages/numpy/ma/testutils.pyi b/python/user_packages/Python313/site-packages/numpy/ma/testutils.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..5760c8cf92fd8bb1a71862d416b5e8f36a3f1e8d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/ma/testutils.pyi
@@ -0,0 +1,69 @@
+import numpy as np
+from numpy._typing import NDArray
+from numpy.testing import (
+    TestCase,
+    assert_,
+    assert_allclose,
+    assert_array_almost_equal_nulp,
+    assert_raises,
+)
+from numpy.testing._private.utils import _ComparisonFunc
+
+__all__ = [
+    "TestCase",
+    "almost",
+    "approx",
+    "assert_",
+    "assert_allclose",
+    "assert_almost_equal",
+    "assert_array_almost_equal",
+    "assert_array_almost_equal_nulp",
+    "assert_array_approx_equal",
+    "assert_array_compare",
+    "assert_array_equal",
+    "assert_array_less",
+    "assert_close",
+    "assert_equal",
+    "assert_equal_records",
+    "assert_mask_equal",
+    "assert_not_equal",
+    "assert_raises",
+    "fail_if_array_equal",
+]
+
+def approx(
+    a: object, b: object, fill_value: bool = True, rtol: float = 1e-5, atol: float = 1e-8
+) -> np.ndarray[tuple[int], np.dtype[np.bool]]: ...
+def almost(a: object, b: object, decimal: int = 6, fill_value: bool = True) -> np.ndarray[tuple[int], np.dtype[np.bool]]: ...
+
+#
+def assert_equal_records(a: NDArray[np.void], b: NDArray[np.void]) -> None: ...
+def assert_equal(actual: object, desired: object, err_msg: str = "") -> None: ...
+def fail_if_equal(actual: object, desired: object, err_msg: str = "") -> None: ...
+def assert_almost_equal(
+    actual: object, desired: object, decimal: int = 7, err_msg: str = "", verbose: bool = True
+) -> None: ...
+
+#
+def assert_array_compare(
+    comparison: _ComparisonFunc,
+    x: object,
+    y: object,
+    err_msg: str = "",
+    verbose: bool = True,
+    header: str = "",
+    fill_value: bool = True,
+) -> None: ...
+def assert_array_equal(x: object, y: object, err_msg: str = "", verbose: bool = True) -> None: ...
+def fail_if_array_equal(x: object, y: object, err_msg: str = "", verbose: bool = True) -> None: ...
+def assert_array_approx_equal(
+    x: object, y: object, decimal: int = 6, err_msg: str = "", verbose: bool = True
+) -> None: ...
+def assert_array_almost_equal(
+    x: object, y: object, decimal: int = 6, err_msg: str = "", verbose: bool = True
+) -> None: ...
+def assert_array_less(x: object, y: object, err_msg: str = "", verbose: bool = True) -> None: ...
+def assert_mask_equal(m1: object, m2: object, err_msg: str = "") -> None: ...
+
+assert_not_equal = fail_if_equal
+assert_close = assert_almost_equal
diff --git a/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.py b/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e376271aca708c7bd6bb3c34a0a31cba2cd0ff36
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.py
@@ -0,0 +1,12 @@
+"""Sub-package containing the matrix class and related functions.
+
+"""
+from . import defmatrix
+from .defmatrix import *
+
+__all__ = defmatrix.__all__
+
+from numpy._pytesttester import PytestTester
+
+test = PytestTester(__name__)
+del PytestTester
diff --git a/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.pyi b/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..cb5a8420eacfc2bb7a44331b1ecc8ab320c9d2b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/matrixlib/__init__.pyi
@@ -0,0 +1,3 @@
+from .defmatrix import asmatrix, bmat, matrix
+
+__all__ = ["matrix", "bmat", "asmatrix"]
diff --git a/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.py b/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.py
new file mode 100644
index 0000000000000000000000000000000000000000..62312a82cc60e9ae15bd8cf7b47481d09c26963c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.py
@@ -0,0 +1,1119 @@
+__all__ = ['matrix', 'bmat', 'asmatrix']
+
+import ast
+import sys
+import warnings
+
+import numpy._core.numeric as N
+from numpy._core.numeric import concatenate, isscalar
+from numpy._utils import set_module
+
+# While not in __all__, matrix_power used to be defined here, so we import
+# it for backward compatibility.
+from numpy.linalg import matrix_power
+
+
+def _convert_from_string(data):
+    for char in '[]':
+        data = data.replace(char, '')
+
+    rows = data.split(';')
+    newdata = []
+    for count, row in enumerate(rows):
+        trow = row.split(',')
+        newrow = []
+        for col in trow:
+            temp = col.split()
+            newrow.extend(map(ast.literal_eval, temp))
+        if count == 0:
+            Ncols = len(newrow)
+        elif len(newrow) != Ncols:
+            raise ValueError("Rows not the same size.")
+        newdata.append(newrow)
+    return newdata
+
+
+@set_module('numpy')
+def asmatrix(data, dtype=None):
+    """
+    Interpret the input as a matrix.
+
+    Unlike `matrix`, `asmatrix` does not make a copy if the input is already
+    a matrix or an ndarray.  Equivalent to ``matrix(data, copy=False)``.
+
+    Parameters
+    ----------
+    data : array_like
+        Input data.
+    dtype : data-type
+       Data-type of the output matrix.
+
+    Returns
+    -------
+    mat : matrix
+        `data` interpreted as a matrix.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> x = np.array([[1, 2], [3, 4]])
+
+    >>> m = np.asmatrix(x)
+
+    >>> x[0,0] = 5
+
+    >>> m
+    matrix([[5, 2],
+            [3, 4]])
+
+    """
+    return matrix(data, dtype=dtype, copy=False)
+
+
+@set_module('numpy')
+class matrix(N.ndarray):
+    """
+    matrix(data, dtype=None, copy=True)
+
+    Returns a matrix from an array-like object, or from a string of data.
+
+    A matrix is a specialized 2-D array that retains its 2-D nature
+    through operations.  It has certain special operators, such as ``*``
+    (matrix multiplication) and ``**`` (matrix power).
+
+    .. note:: It is no longer recommended to use this class, even for linear
+              algebra. Instead use regular arrays. The class may be removed
+              in the future.
+
+    Parameters
+    ----------
+    data : array_like or string
+       If `data` is a string, it is interpreted as a matrix with commas
+       or spaces separating columns, and semicolons separating rows.
+    dtype : data-type
+       Data-type of the output matrix.
+    copy : bool
+       If `data` is already an `ndarray`, then this flag determines
+       whether the data is copied (the default), or whether a view is
+       constructed.
+
+    See Also
+    --------
+    array
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> a = np.matrix('1 2; 3 4')
+    >>> a
+    matrix([[1, 2],
+            [3, 4]])
+
+    >>> np.matrix([[1, 2], [3, 4]])
+    matrix([[1, 2],
+            [3, 4]])
+
+    """
+    __array_priority__ = 10.0
+
+    def __new__(subtype, data, dtype=None, copy=True):
+        warnings.warn('the matrix subclass is not the recommended way to '
+                      'represent matrices or deal with linear algebra (see '
+                      'https://docs.scipy.org/doc/numpy/user/'
+                      'numpy-for-matlab-users.html). '
+                      'Please adjust your code to use regular ndarray.',
+                      PendingDeprecationWarning, stacklevel=2)
+        if isinstance(data, matrix):
+            dtype2 = data.dtype
+            if (dtype is None):
+                dtype = dtype2
+            if (dtype2 == dtype) and (not copy):
+                return data
+            return data.astype(dtype)
+
+        if isinstance(data, N.ndarray):
+            if dtype is None:
+                intype = data.dtype
+            else:
+                intype = N.dtype(dtype)
+            new = data.view(subtype)
+            if intype != data.dtype:
+                return new.astype(intype)
+            if copy:
+                return new.copy()
+            else:
+                return new
+
+        if isinstance(data, str):
+            data = _convert_from_string(data)
+
+        # now convert data to an array
+        copy = None if not copy else True
+        arr = N.array(data, dtype=dtype, copy=copy)
+        ndim = arr.ndim
+        shape = arr.shape
+        if (ndim > 2):
+            raise ValueError("matrix must be 2-dimensional")
+        elif ndim == 0:
+            shape = (1, 1)
+        elif ndim == 1:
+            shape = (1, shape[0])
+
+        order = 'C'
+        if (ndim == 2) and arr.flags.fortran:
+            order = 'F'
+
+        if not (order or arr.flags.contiguous):
+            arr = arr.copy()
+
+        ret = N.ndarray.__new__(subtype, shape, arr.dtype,
+                                buffer=arr,
+                                order=order)
+        return ret
+
+    def __array_finalize__(self, obj):
+        self._getitem = False
+        if (isinstance(obj, matrix) and obj._getitem):
+            return
+        ndim = self.ndim
+        if (ndim == 2):
+            return
+        if (ndim > 2):
+            newshape = tuple(x for x in self.shape if x > 1)
+            ndim = len(newshape)
+            if ndim == 2:
+                self.shape = newshape
+                return
+            elif (ndim > 2):
+                raise ValueError("shape too large to be a matrix.")
+        else:
+            newshape = self.shape
+        if ndim == 0:
+            self.shape = (1, 1)
+        elif ndim == 1:
+            self.shape = (1, newshape[0])
+        return
+
+    def __getitem__(self, index):
+        self._getitem = True
+
+        try:
+            out = N.ndarray.__getitem__(self, index)
+        finally:
+            self._getitem = False
+
+        if not isinstance(out, N.ndarray):
+            return out
+
+        if out.ndim == 0:
+            return out[()]
+        if out.ndim == 1:
+            sh = out.shape[0]
+            # Determine when we should have a column array
+            try:
+                n = len(index)
+            except Exception:
+                n = 0
+            if n > 1 and isscalar(index[1]):
+                out.shape = (sh, 1)
+            else:
+                out.shape = (1, sh)
+        return out
+
+    def __mul__(self, other):
+        if isinstance(other, (N.ndarray, list, tuple)):
+            # This promotes 1-D vectors to row vectors
+            return N.dot(self, asmatrix(other))
+        if isscalar(other) or not hasattr(other, '__rmul__'):
+            return N.dot(self, other)
+        return NotImplemented
+
+    def __rmul__(self, other):
+        return N.dot(other, self)
+
+    def __imul__(self, other):
+        self[:] = self * other
+        return self
+
+    def __pow__(self, other):
+        return matrix_power(self, other)
+
+    def __ipow__(self, other):
+        self[:] = self ** other
+        return self
+
+    def __rpow__(self, other):
+        return NotImplemented
+
+    def _align(self, axis):
+        """A convenience function for operations that need to preserve axis
+        orientation.
+        """
+        if axis is None:
+            return self[0, 0]
+        elif axis == 0:
+            return self
+        elif axis == 1:
+            return self.transpose()
+        else:
+            raise ValueError("unsupported axis")
+
+    def _collapse(self, axis):
+        """A convenience function for operations that want to collapse
+        to a scalar like _align, but are using keepdims=True
+        """
+        if axis is None:
+            return self[0, 0]
+        else:
+            return self
+
+    # Necessary because base-class tolist expects dimension
+    #  reduction by x[0]
+    def tolist(self):
+        """
+        Return the matrix as a (possibly nested) list.
+
+        See `ndarray.tolist` for full documentation.
+
+        See Also
+        --------
+        ndarray.tolist
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.tolist()
+        [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]
+
+        """
+        return self.__array__().tolist()
+
+    # To preserve orientation of result...
+    def sum(self, axis=None, dtype=None, out=None):
+        """
+        Returns the sum of the matrix elements, along the given axis.
+
+        Refer to `numpy.sum` for full documentation.
+
+        See Also
+        --------
+        numpy.sum
+
+        Notes
+        -----
+        This is the same as `ndarray.sum`, except that where an `ndarray` would
+        be returned, a `matrix` object is returned instead.
+
+        Examples
+        --------
+        >>> x = np.matrix([[1, 2], [4, 3]])
+        >>> x.sum()
+        10
+        >>> x.sum(axis=1)
+        matrix([[3],
+                [7]])
+        >>> x.sum(axis=1, dtype='float')
+        matrix([[3.],
+                [7.]])
+        >>> out = np.zeros((2, 1), dtype='float')
+        >>> x.sum(axis=1, dtype='float', out=np.asmatrix(out))
+        matrix([[3.],
+                [7.]])
+
+        """
+        return N.ndarray.sum(self, axis, dtype, out, keepdims=True)._collapse(axis)
+
+    # To update docstring from array to matrix...
+    def squeeze(self, axis=None):
+        """
+        Return a possibly reshaped matrix.
+
+        Refer to `numpy.squeeze` for more documentation.
+
+        Parameters
+        ----------
+        axis : None or int or tuple of ints, optional
+            Selects a subset of the axes of length one in the shape.
+            If an axis is selected with shape entry greater than one,
+            an error is raised.
+
+        Returns
+        -------
+        squeezed : matrix
+            The matrix, but as a (1, N) matrix if it had shape (N, 1).
+
+        See Also
+        --------
+        numpy.squeeze : related function
+
+        Notes
+        -----
+        If `m` has a single column then that column is returned
+        as the single row of a matrix.  Otherwise `m` is returned.
+        The returned matrix is always either `m` itself or a view into `m`.
+        Supplying an axis keyword argument will not affect the returned matrix
+        but it may cause an error to be raised.
+
+        Examples
+        --------
+        >>> c = np.matrix([[1], [2]])
+        >>> c
+        matrix([[1],
+                [2]])
+        >>> c.squeeze()
+        matrix([[1, 2]])
+        >>> r = c.T
+        >>> r
+        matrix([[1, 2]])
+        >>> r.squeeze()
+        matrix([[1, 2]])
+        >>> m = np.matrix([[1, 2], [3, 4]])
+        >>> m.squeeze()
+        matrix([[1, 2],
+                [3, 4]])
+
+        """
+        return N.ndarray.squeeze(self, axis=axis)
+
+    # To update docstring from array to matrix...
+    def flatten(self, order='C'):
+        """
+        Return a flattened copy of the matrix.
+
+        All `N` elements of the matrix are placed into a single row.
+
+        Parameters
+        ----------
+        order : {'C', 'F', 'A', 'K'}, optional
+            'C' means to flatten in row-major (C-style) order. 'F' means to
+            flatten in column-major (Fortran-style) order. 'A' means to
+            flatten in column-major order if `m` is Fortran *contiguous* in
+            memory, row-major order otherwise. 'K' means to flatten `m` in
+            the order the elements occur in memory. The default is 'C'.
+
+        Returns
+        -------
+        y : matrix
+            A copy of the matrix, flattened to a `(1, N)` matrix where `N`
+            is the number of elements in the original matrix.
+
+        See Also
+        --------
+        ravel : Return a flattened array.
+        flat : A 1-D flat iterator over the matrix.
+
+        Examples
+        --------
+        >>> m = np.matrix([[1,2], [3,4]])
+        >>> m.flatten()
+        matrix([[1, 2, 3, 4]])
+        >>> m.flatten('F')
+        matrix([[1, 3, 2, 4]])
+
+        """
+        return N.ndarray.flatten(self, order=order)
+
+    def mean(self, axis=None, dtype=None, out=None):
+        """
+        Returns the average of the matrix elements along the given axis.
+
+        Refer to `numpy.mean` for full documentation.
+
+        See Also
+        --------
+        numpy.mean
+
+        Notes
+        -----
+        Same as `ndarray.mean` except that, where that returns an `ndarray`,
+        this returns a `matrix` object.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3, 4)))
+        >>> x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.mean()
+        5.5
+        >>> x.mean(0)
+        matrix([[4., 5., 6., 7.]])
+        >>> x.mean(1)
+        matrix([[ 1.5],
+                [ 5.5],
+                [ 9.5]])
+
+        """
+        return N.ndarray.mean(self, axis, dtype, out, keepdims=True)._collapse(axis)
+
+    def std(self, axis=None, dtype=None, out=None, ddof=0):
+        """
+        Return the standard deviation of the array elements along the given axis.
+
+        Refer to `numpy.std` for full documentation.
+
+        See Also
+        --------
+        numpy.std
+
+        Notes
+        -----
+        This is the same as `ndarray.std`, except that where an `ndarray` would
+        be returned, a `matrix` object is returned instead.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3, 4)))
+        >>> x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.std()
+        3.4520525295346629 # may vary
+        >>> x.std(0)
+        matrix([[ 3.26598632,  3.26598632,  3.26598632,  3.26598632]]) # may vary
+        >>> x.std(1)
+        matrix([[ 1.11803399],
+                [ 1.11803399],
+                [ 1.11803399]])
+
+        """
+        return N.ndarray.std(self, axis, dtype, out, ddof,
+                             keepdims=True)._collapse(axis)
+
+    def var(self, axis=None, dtype=None, out=None, ddof=0):
+        """
+        Returns the variance of the matrix elements, along the given axis.
+
+        Refer to `numpy.var` for full documentation.
+
+        See Also
+        --------
+        numpy.var
+
+        Notes
+        -----
+        This is the same as `ndarray.var`, except that where an `ndarray` would
+        be returned, a `matrix` object is returned instead.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3, 4)))
+        >>> x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.var()
+        11.916666666666666
+        >>> x.var(0)
+        matrix([[ 10.66666667,  10.66666667,  10.66666667,  10.66666667]]) # may vary
+        >>> x.var(1)
+        matrix([[1.25],
+                [1.25],
+                [1.25]])
+
+        """
+        return N.ndarray.var(self, axis, dtype, out, ddof,
+                             keepdims=True)._collapse(axis)
+
+    def prod(self, axis=None, dtype=None, out=None):
+        """
+        Return the product of the array elements over the given axis.
+
+        Refer to `prod` for full documentation.
+
+        See Also
+        --------
+        prod, ndarray.prod
+
+        Notes
+        -----
+        Same as `ndarray.prod`, except, where that returns an `ndarray`, this
+        returns a `matrix` object instead.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.prod()
+        0
+        >>> x.prod(0)
+        matrix([[  0,  45, 120, 231]])
+        >>> x.prod(1)
+        matrix([[   0],
+                [ 840],
+                [7920]])
+
+        """
+        return N.ndarray.prod(self, axis, dtype, out, keepdims=True)._collapse(axis)
+
+    def any(self, axis=None, out=None):
+        """
+        Test whether any array element along a given axis evaluates to True.
+
+        Refer to `numpy.any` for full documentation.
+
+        Parameters
+        ----------
+        axis : int, optional
+            Axis along which logical OR is performed
+        out : ndarray, optional
+            Output to existing array instead of creating new one, must have
+            same shape as expected output
+
+        Returns
+        -------
+            any : bool, ndarray
+                Returns a single bool if `axis` is ``None``; otherwise,
+                returns `ndarray`
+
+        """
+        return N.ndarray.any(self, axis, out, keepdims=True)._collapse(axis)
+
+    def all(self, axis=None, out=None):
+        """
+        Test whether all matrix elements along a given axis evaluate to True.
+
+        Parameters
+        ----------
+        See `numpy.all` for complete descriptions
+
+        See Also
+        --------
+        numpy.all
+
+        Notes
+        -----
+        This is the same as `ndarray.all`, but it returns a `matrix` object.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> y = x[0]; y
+        matrix([[0, 1, 2, 3]])
+        >>> (x == y)
+        matrix([[ True,  True,  True,  True],
+                [False, False, False, False],
+                [False, False, False, False]])
+        >>> (x == y).all()
+        False
+        >>> (x == y).all(0)
+        matrix([[False, False, False, False]])
+        >>> (x == y).all(1)
+        matrix([[ True],
+                [False],
+                [False]])
+
+        """
+        return N.ndarray.all(self, axis, out, keepdims=True)._collapse(axis)
+
+    def max(self, axis=None, out=None):
+        """
+        Return the maximum value along an axis.
+
+        Parameters
+        ----------
+        See `amax` for complete descriptions
+
+        See Also
+        --------
+        amax, ndarray.max
+
+        Notes
+        -----
+        This is the same as `ndarray.max`, but returns a `matrix` object
+        where `ndarray.max` would return an ndarray.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.max()
+        11
+        >>> x.max(0)
+        matrix([[ 8,  9, 10, 11]])
+        >>> x.max(1)
+        matrix([[ 3],
+                [ 7],
+                [11]])
+
+        """
+        return N.ndarray.max(self, axis, out, keepdims=True)._collapse(axis)
+
+    def argmax(self, axis=None, out=None):
+        """
+        Indexes of the maximum values along an axis.
+
+        Return the indexes of the first occurrences of the maximum values
+        along the specified axis.  If axis is None, the index is for the
+        flattened matrix.
+
+        Parameters
+        ----------
+        See `numpy.argmax` for complete descriptions
+
+        See Also
+        --------
+        numpy.argmax
+
+        Notes
+        -----
+        This is the same as `ndarray.argmax`, but returns a `matrix` object
+        where `ndarray.argmax` would return an `ndarray`.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.argmax()
+        11
+        >>> x.argmax(0)
+        matrix([[2, 2, 2, 2]])
+        >>> x.argmax(1)
+        matrix([[3],
+                [3],
+                [3]])
+
+        """
+        return N.ndarray.argmax(self, axis, out)._align(axis)
+
+    def min(self, axis=None, out=None):
+        """
+        Return the minimum value along an axis.
+
+        Parameters
+        ----------
+        See `amin` for complete descriptions.
+
+        See Also
+        --------
+        amin, ndarray.min
+
+        Notes
+        -----
+        This is the same as `ndarray.min`, but returns a `matrix` object
+        where `ndarray.min` would return an ndarray.
+
+        Examples
+        --------
+        >>> x = -np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[  0,  -1,  -2,  -3],
+                [ -4,  -5,  -6,  -7],
+                [ -8,  -9, -10, -11]])
+        >>> x.min()
+        -11
+        >>> x.min(0)
+        matrix([[ -8,  -9, -10, -11]])
+        >>> x.min(1)
+        matrix([[ -3],
+                [ -7],
+                [-11]])
+
+        """
+        return N.ndarray.min(self, axis, out, keepdims=True)._collapse(axis)
+
+    def argmin(self, axis=None, out=None):
+        """
+        Indexes of the minimum values along an axis.
+
+        Return the indexes of the first occurrences of the minimum values
+        along the specified axis.  If axis is None, the index is for the
+        flattened matrix.
+
+        Parameters
+        ----------
+        See `numpy.argmin` for complete descriptions.
+
+        See Also
+        --------
+        numpy.argmin
+
+        Notes
+        -----
+        This is the same as `ndarray.argmin`, but returns a `matrix` object
+        where `ndarray.argmin` would return an `ndarray`.
+
+        Examples
+        --------
+        >>> x = -np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[  0,  -1,  -2,  -3],
+                [ -4,  -5,  -6,  -7],
+                [ -8,  -9, -10, -11]])
+        >>> x.argmin()
+        11
+        >>> x.argmin(0)
+        matrix([[2, 2, 2, 2]])
+        >>> x.argmin(1)
+        matrix([[3],
+                [3],
+                [3]])
+
+        """
+        return N.ndarray.argmin(self, axis, out)._align(axis)
+
+    def ptp(self, axis=None, out=None):
+        """
+        Peak-to-peak (maximum - minimum) value along the given axis.
+
+        Refer to `numpy.ptp` for full documentation.
+
+        See Also
+        --------
+        numpy.ptp
+
+        Notes
+        -----
+        Same as `ndarray.ptp`, except, where that would return an `ndarray` object,
+        this returns a `matrix` object.
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.ptp()
+        11
+        >>> x.ptp(0)
+        matrix([[8, 8, 8, 8]])
+        >>> x.ptp(1)
+        matrix([[3],
+                [3],
+                [3]])
+
+        """
+        return N.ptp(self, axis, out)._align(axis)
+
+    @property
+    def I(self):  # noqa: E743
+        """
+        Returns the (multiplicative) inverse of invertible `self`.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        ret : matrix object
+            If `self` is non-singular, `ret` is such that ``ret * self`` ==
+            ``self * ret`` == ``np.matrix(np.eye(self[0,:].size))`` all return
+            ``True``.
+
+        Raises
+        ------
+        numpy.linalg.LinAlgError: Singular matrix
+            If `self` is singular.
+
+        See Also
+        --------
+        linalg.inv
+
+        Examples
+        --------
+        >>> m = np.matrix('[1, 2; 3, 4]'); m
+        matrix([[1, 2],
+                [3, 4]])
+        >>> m.getI()
+        matrix([[-2. ,  1. ],
+                [ 1.5, -0.5]])
+        >>> m.getI() * m
+        matrix([[ 1.,  0.], # may vary
+                [ 0.,  1.]])
+
+        """
+        M, N = self.shape
+        if M == N:
+            from numpy.linalg import inv as func
+        else:
+            from numpy.linalg import pinv as func
+        return asmatrix(func(self))
+
+    @property
+    def A(self):
+        """
+        Return `self` as an `ndarray` object.
+
+        Equivalent to ``np.asarray(self)``.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        ret : ndarray
+            `self` as an `ndarray`
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.getA()
+        array([[ 0,  1,  2,  3],
+               [ 4,  5,  6,  7],
+               [ 8,  9, 10, 11]])
+
+        """
+        return self.__array__()
+
+    @property
+    def A1(self):
+        """
+        Return `self` as a flattened `ndarray`.
+
+        Equivalent to ``np.asarray(x).ravel()``
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        ret : ndarray
+            `self`, 1-D, as an `ndarray`
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4))); x
+        matrix([[ 0,  1,  2,  3],
+                [ 4,  5,  6,  7],
+                [ 8,  9, 10, 11]])
+        >>> x.getA1()
+        array([ 0,  1,  2, ...,  9, 10, 11])
+
+
+        """
+        return self.__array__().ravel()
+
+    def ravel(self, order='C'):
+        """
+        Return a flattened matrix.
+
+        Refer to `numpy.ravel` for more documentation.
+
+        Parameters
+        ----------
+        order : {'C', 'F', 'A', 'K'}, optional
+            The elements of `m` are read using this index order. 'C' means to
+            index the elements in C-like order, with the last axis index
+            changing fastest, back to the first axis index changing slowest.
+            'F' means to index the elements in Fortran-like index order, with
+            the first index changing fastest, and the last index changing
+            slowest. Note that the 'C' and 'F' options take no account of the
+            memory layout of the underlying array, and only refer to the order
+            of axis indexing.  'A' means to read the elements in Fortran-like
+            index order if `m` is Fortran *contiguous* in memory, C-like order
+            otherwise.  'K' means to read the elements in the order they occur
+            in memory, except for reversing the data when strides are negative.
+            By default, 'C' index order is used.
+
+        Returns
+        -------
+        ret : matrix
+            Return the matrix flattened to shape `(1, N)` where `N`
+            is the number of elements in the original matrix.
+            A copy is made only if necessary.
+
+        See Also
+        --------
+        matrix.flatten : returns a similar output matrix but always a copy
+        matrix.flat : a flat iterator on the array.
+        numpy.ravel : related function which returns an ndarray
+
+        """
+        return N.ndarray.ravel(self, order=order)
+
+    @property
+    def T(self):
+        """
+        Returns the transpose of the matrix.
+
+        Does *not* conjugate!  For the complex conjugate transpose, use ``.H``.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        ret : matrix object
+            The (non-conjugated) transpose of the matrix.
+
+        See Also
+        --------
+        transpose, getH
+
+        Examples
+        --------
+        >>> m = np.matrix('[1, 2; 3, 4]')
+        >>> m
+        matrix([[1, 2],
+                [3, 4]])
+        >>> m.getT()
+        matrix([[1, 3],
+                [2, 4]])
+
+        """
+        return self.transpose()
+
+    @property
+    def H(self):
+        """
+        Returns the (complex) conjugate transpose of `self`.
+
+        Equivalent to ``np.transpose(self)`` if `self` is real-valued.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        ret : matrix object
+            complex conjugate transpose of `self`
+
+        Examples
+        --------
+        >>> x = np.matrix(np.arange(12).reshape((3,4)))
+        >>> z = x - 1j*x; z
+        matrix([[  0. +0.j,   1. -1.j,   2. -2.j,   3. -3.j],
+                [  4. -4.j,   5. -5.j,   6. -6.j,   7. -7.j],
+                [  8. -8.j,   9. -9.j,  10.-10.j,  11.-11.j]])
+        >>> z.getH()
+        matrix([[ 0. -0.j,  4. +4.j,  8. +8.j],
+                [ 1. +1.j,  5. +5.j,  9. +9.j],
+                [ 2. +2.j,  6. +6.j, 10.+10.j],
+                [ 3. +3.j,  7. +7.j, 11.+11.j]])
+
+        """
+        if issubclass(self.dtype.type, N.complexfloating):
+            return self.transpose().conjugate()
+        else:
+            return self.transpose()
+
+    # kept for compatibility
+    getT = T.fget
+    getA = A.fget
+    getA1 = A1.fget
+    getH = H.fget
+    getI = I.fget
+
+def _from_string(str, gdict, ldict):
+    rows = str.split(';')
+    rowtup = []
+    for row in rows:
+        trow = row.split(',')
+        newrow = []
+        for x in trow:
+            newrow.extend(x.split())
+        trow = newrow
+        coltup = []
+        for col in trow:
+            col = col.strip()
+            try:
+                thismat = ldict[col]
+            except KeyError:
+                try:
+                    thismat = gdict[col]
+                except KeyError as e:
+                    raise NameError(f"name {col!r} is not defined") from None
+
+            coltup.append(thismat)
+        rowtup.append(concatenate(coltup, axis=-1))
+    return concatenate(rowtup, axis=0)
+
+
+@set_module('numpy')
+def bmat(obj, ldict=None, gdict=None):
+    """
+    Build a matrix object from a string, nested sequence, or array.
+
+    Parameters
+    ----------
+    obj : str or array_like
+        Input data. If a string, variables in the current scope may be
+        referenced by name.
+    ldict : dict, optional
+        A dictionary that replaces local operands in current frame.
+        Ignored if `obj` is not a string or `gdict` is None.
+    gdict : dict, optional
+        A dictionary that replaces global operands in current frame.
+        Ignored if `obj` is not a string.
+
+    Returns
+    -------
+    out : matrix
+        Returns a matrix object, which is a specialized 2-D array.
+
+    See Also
+    --------
+    block :
+        A generalization of this function for N-d arrays, that returns normal
+        ndarrays.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> A = np.asmatrix('1 1; 1 1')
+    >>> B = np.asmatrix('2 2; 2 2')
+    >>> C = np.asmatrix('3 4; 5 6')
+    >>> D = np.asmatrix('7 8; 9 0')
+
+    All the following expressions construct the same block matrix:
+
+    >>> np.bmat([[A, B], [C, D]])
+    matrix([[1, 1, 2, 2],
+            [1, 1, 2, 2],
+            [3, 4, 7, 8],
+            [5, 6, 9, 0]])
+    >>> np.bmat(np.r_[np.c_[A, B], np.c_[C, D]])
+    matrix([[1, 1, 2, 2],
+            [1, 1, 2, 2],
+            [3, 4, 7, 8],
+            [5, 6, 9, 0]])
+    >>> np.bmat('A,B; C,D')
+    matrix([[1, 1, 2, 2],
+            [1, 1, 2, 2],
+            [3, 4, 7, 8],
+            [5, 6, 9, 0]])
+
+    """
+    if isinstance(obj, str):
+        if gdict is None:
+            # get previous frame
+            frame = sys._getframe().f_back
+            glob_dict = frame.f_globals
+            loc_dict = frame.f_locals
+        else:
+            glob_dict = gdict
+            loc_dict = ldict
+
+        return matrix(_from_string(obj, glob_dict, loc_dict))
+
+    if isinstance(obj, (tuple, list)):
+        # [[A,B],[C,D]]
+        arr_rows = []
+        for row in obj:
+            if isinstance(row, N.ndarray):  # not 2-d
+                return matrix(concatenate(obj, axis=-1))
+            else:
+                arr_rows.append(concatenate(row, axis=-1))
+        return matrix(concatenate(arr_rows, axis=0))
+    if isinstance(obj, N.ndarray):
+        return matrix(obj)
diff --git a/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.pyi b/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.pyi
new file mode 100644
index 0000000000000000000000000000000000000000..825ab89ccaef215f1b7dea9b635c014a1b35b8ae
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/numpy/matrixlib/defmatrix.pyi
@@ -0,0 +1,218 @@
+from _typeshed import Incomplete
+from collections.abc import Mapping, Sequence
+from types import EllipsisType
+from typing import Any, ClassVar, Literal as L, Self, SupportsIndex, TypeAlias, overload
+from typing_extensions import TypeVar
+
+import numpy as np
+from numpy._typing import (
+    ArrayLike,
+    DTypeLike,
+    NDArray,
+    _AnyShape,
+    _ArrayLikeInt_co,
+    _NestedSequence,
+    _ShapeLike,
+)
+
+__all__ = ["asmatrix", "bmat", "matrix"]
+
+_T = TypeVar("_T")
+_ArrayT = TypeVar("_ArrayT", bound=np.ndarray)
+_BoolOrIntArrayT = TypeVar("_BoolOrIntArrayT", bound=NDArray[np.integer | np.bool])
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ShapeT_co = TypeVar("_ShapeT_co", bound=_2D, default=_2D, covariant=True)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, default=np.dtype, covariant=True)
+
+_2D: TypeAlias = tuple[int, int]
+_Matrix: TypeAlias = matrix[_2D, np.dtype[_ScalarT]]
+_ToIndex1: TypeAlias = slice | EllipsisType | NDArray[np.integer | np.bool] | _NestedSequence[int] | None
+_ToIndex2: TypeAlias = tuple[_ToIndex1, _ToIndex1 | SupportsIndex] | tuple[_ToIndex1 | SupportsIndex, _ToIndex1]
+
+class matrix(np.ndarray[_ShapeT_co, _DTypeT_co]):
+    __array_priority__: ClassVar[float] = 10.0  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    def __new__(
+        subtype,  # pyright: ignore[reportSelfClsParameterName]
+        data: ArrayLike,
+        dtype: DTypeLike | None = None,
+        copy: bool = True,
+    ) -> _Matrix[Incomplete]: ...
+
+    #
+    @overload  # type: ignore[override]
+    def __getitem__(
+        self, key: SupportsIndex | _ArrayLikeInt_co | tuple[SupportsIndex | _ArrayLikeInt_co, ...], /
+    ) -> Incomplete: ...
+    @overload
+    def __getitem__(self, key: _ToIndex1 | _ToIndex2, /) -> matrix[_2D, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self: _Matrix[np.void], key: str, /) -> _Matrix[Incomplete]: ...
+    @overload
+    def __getitem__(self: _Matrix[np.void], key: list[str], /) -> matrix[_2D, _DTypeT_co]: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    #
+    def __mul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    def __rmul__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    #
+    def __pow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    def __rpow__(self, other: ArrayLike, /) -> _Matrix[Incomplete]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `prod` and `mean`
+    @overload  # type: ignore[override]
+    def sum(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
+    @overload
+    def sum(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
+    @overload
+    def sum(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def sum(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `sum` and `mean`
+    @overload  # type: ignore[override]
+    def prod(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
+    @overload
+    def prod(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
+    @overload
+    def prod(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def prod(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `sum` and `prod`
+    @overload  # type: ignore[override]
+    def mean(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None) -> Incomplete: ...
+    @overload
+    def mean(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None) -> _Matrix[Incomplete]: ...
+    @overload
+    def mean(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def mean(self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `var`
+    @overload  # type: ignore[override]
+    def std(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
+    @overload
+    def std(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
+    @overload
+    def std(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ...
+    @overload
+    def std(  # pyright: ignore[reportIncompatibleMethodOverride]
+        self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0
+    ) -> _ArrayT: ...
+
+    # keep in sync with `std`
+    @overload  # type: ignore[override]
+    def var(self, axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> Incomplete: ...
+    @overload
+    def var(self, axis: _ShapeLike, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0) -> _Matrix[Incomplete]: ...
+    @overload
+    def var(self, axis: _ShapeLike | None, dtype: DTypeLike | None, out: _ArrayT, ddof: float = 0) -> _ArrayT: ...
+    @overload
+    def var(  # pyright: ignore[reportIncompatibleMethodOverride]
+        self, axis: _ShapeLike | None = None, dtype: DTypeLike | None = None, *, out: _ArrayT, ddof: float = 0
+    ) -> _ArrayT: ...
+
+    # keep in sync with `all`
+    @overload  # type: ignore[override]
+    def any(self, axis: None = None, out: None = None) -> np.bool: ...
+    @overload
+    def any(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
+    @overload
+    def any(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def any(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `any`
+    @overload  # type: ignore[override]
+    def all(self, axis: None = None, out: None = None) -> np.bool: ...
+    @overload
+    def all(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.bool]: ...
+    @overload
+    def all(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def all(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `min` and `ptp`
+    @overload  # type: ignore[override]
+    def max(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
+    @overload
+    def max(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
+    @overload
+    def max(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def max(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `max` and `ptp`
+    @overload  # type: ignore[override]
+    def min(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
+    @overload
+    def min(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
+    @overload
+    def min(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def min(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `max` and `min`
+    @overload
+    def ptp(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> _ScalarT: ...
+    @overload
+    def ptp(self, axis: _ShapeLike, out: None = None) -> matrix[_2D, _DTypeT_co]: ...
+    @overload
+    def ptp(self, axis: _ShapeLike | None, out: _ArrayT) -> _ArrayT: ...
+    @overload
+    def ptp(self, axis: _ShapeLike | None = None, *, out: _ArrayT) -> _ArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `argmin`
+    @overload  # type: ignore[override]
+    def argmax(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> np.intp: ...
+    @overload
+    def argmax(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
+    @overload
+    def argmax(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...
+    @overload
+    def argmax(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # keep in sync with `argmax`
+    @overload  # type: ignore[override]
+    def argmin(self: NDArray[_ScalarT], axis: None = None, out: None = None) -> np.intp: ...
+    @overload
+    def argmin(self, axis: _ShapeLike, out: None = None) -> _Matrix[np.intp]: ...
+    @overload
+    def argmin(self, axis: _ShapeLike | None, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...
+    @overload
+    def argmin(self, axis: _ShapeLike | None = None, *, out: _BoolOrIntArrayT) -> _BoolOrIntArrayT: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # the second overload handles the (rare) case that the matrix is not 2-d
+    @overload
+    def tolist(self: _Matrix[np.generic[_T]]) -> list[list[_T]]: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+    @overload
+    def tolist(self) -> Incomplete: ...  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # these three methods will at least return a `2-d` array of shape (1, n)
+    def squeeze(self, /, axis: _ShapeLike | None = None) -> matrix[_2D, _DTypeT_co]: ...
+    def ravel(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    def flatten(self, /, order: L["K", "A", "C", "F"] | None = "C") -> matrix[_2D, _DTypeT_co]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    # matrix.T is inherited from _ScalarOrArrayCommon
+    def getT(self) -> Self: ...
+    @property
+    def I(self) -> _Matrix[Incomplete]: ...  # noqa: E743
+    def getI(self) -> _Matrix[Incomplete]: ...
+    @property
+    def A(self) -> np.ndarray[_2D, _DTypeT_co]: ...
+    def getA(self) -> np.ndarray[_2D, _DTypeT_co]: ...
+    @property
+    def A1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
+    def getA1(self) -> np.ndarray[_AnyShape, _DTypeT_co]: ...
+    @property
+    def H(self) -> matrix[_2D, _DTypeT_co]: ...
+    def getH(self) -> matrix[_2D, _DTypeT_co]: ...
+
+def bmat(
+    obj: str | Sequence[ArrayLike] | NDArray[Any],
+    ldict: Mapping[str, Any] | None = None,
+    gdict: Mapping[str, Any] | None = None,
+) -> _Matrix[Incomplete]: ...
+
+def asmatrix(data: ArrayLike, dtype: DTypeLike | None = None) -> _Matrix[Incomplete]: ...
diff --git a/python/user_packages/Python313/site-packages/oauthlib-3.3.1.dist-info/licenses/LICENSE b/python/user_packages/Python313/site-packages/oauthlib-3.3.1.dist-info/licenses/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..ffab12676f701309c33ae08d489e7305c9883ccb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib-3.3.1.dist-info/licenses/LICENSE
@@ -0,0 +1,27 @@
+Copyright (c) The OAuthlib Community
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+    1. Redistributions of source code must retain the above copyright notice,
+       this list of conditions and the following disclaimer.
+
+    2. Redistributions in binary form must reproduce the above copyright
+       notice, this list of conditions and the following disclaimer in the
+       documentation and/or other materials provided with the distribution.
+
+    3. Neither the name of the copyright holder nor the names of its
+       contributors may be used to endorse or promote products derived from this
+       software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
diff --git a/python/user_packages/Python313/site-packages/oauthlib/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/__pycache__/uri_validate.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/__pycache__/uri_validate.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9caf12a90d878efa4460811310818ee3572fcdd4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/__init__.py
@@ -0,0 +1,23 @@
+"""
+oauthlib.oauth1
+~~~~~~~~~~~~~~
+
+This module is a wrapper for the most recent implementation of OAuth 1.0 Client
+and Server classes.
+"""
+from .rfc5849 import (
+    SIGNATURE_HMAC, SIGNATURE_HMAC_SHA1, SIGNATURE_HMAC_SHA256,
+    SIGNATURE_HMAC_SHA512, SIGNATURE_PLAINTEXT, SIGNATURE_RSA,
+    SIGNATURE_RSA_SHA1, SIGNATURE_RSA_SHA256, SIGNATURE_RSA_SHA512,
+    SIGNATURE_TYPE_AUTH_HEADER, SIGNATURE_TYPE_BODY, SIGNATURE_TYPE_QUERY,
+    Client,
+)
+from .rfc5849.endpoints import (
+    AccessTokenEndpoint, AuthorizationEndpoint, RequestTokenEndpoint,
+    ResourceEndpoint, SignatureOnlyEndpoint, WebApplicationServer,
+)
+from .rfc5849.errors import (
+    InsecureTransportError, InvalidClientError, InvalidRequestError,
+    InvalidSignatureMethodError, OAuth1Error,
+)
+from .rfc5849.request_validator import RequestValidator
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/oauth1/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..85e0b90b635398a3a2636ed8b5887d5ddb8c59c3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/__init__.py
@@ -0,0 +1,366 @@
+"""
+oauthlib.oauth1.rfc5849
+~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for signing and checking OAuth 1.0 RFC 5849 requests.
+
+It supports all three standard signature methods defined in RFC 5849:
+
+- HMAC-SHA1
+- RSA-SHA1
+- PLAINTEXT
+
+It also supports signature methods that are not defined in RFC 5849. These are
+based on the standard ones but replace SHA-1 with the more secure SHA-256:
+
+- HMAC-SHA256
+- RSA-SHA256
+
+"""
+import base64
+import hashlib
+import logging
+import urllib.parse as urlparse
+
+from oauthlib.common import (
+    Request, generate_nonce, generate_timestamp, to_unicode, urlencode,
+)
+
+from . import parameters, signature
+
+log = logging.getLogger(__name__)
+
+# Available signature methods
+#
+# Note: SIGNATURE_HMAC and SIGNATURE_RSA are kept for backward compatibility
+# with previous versions of this library, when it the only HMAC-based and
+# RSA-based signature methods were HMAC-SHA1 and RSA-SHA1. But now that it
+# supports other hashing algorithms besides SHA1, explicitly identifying which
+# hashing algorithm is being used is recommended.
+#
+# Note: if additional values are defined here, don't forget to update the
+# imports in "../__init__.py" so they are available outside this module.
+
+SIGNATURE_HMAC_SHA1 = "HMAC-SHA1"
+SIGNATURE_HMAC_SHA256 = "HMAC-SHA256"
+SIGNATURE_HMAC_SHA512 = "HMAC-SHA512"
+SIGNATURE_HMAC = SIGNATURE_HMAC_SHA1  # deprecated variable for HMAC-SHA1
+
+SIGNATURE_RSA_SHA1 = "RSA-SHA1"
+SIGNATURE_RSA_SHA256 = "RSA-SHA256"
+SIGNATURE_RSA_SHA512 = "RSA-SHA512"
+SIGNATURE_RSA = SIGNATURE_RSA_SHA1  # deprecated variable for RSA-SHA1
+
+SIGNATURE_PLAINTEXT = "PLAINTEXT"
+
+SIGNATURE_METHODS = (
+    SIGNATURE_HMAC_SHA1,
+    SIGNATURE_HMAC_SHA256,
+    SIGNATURE_HMAC_SHA512,
+    SIGNATURE_RSA_SHA1,
+    SIGNATURE_RSA_SHA256,
+    SIGNATURE_RSA_SHA512,
+    SIGNATURE_PLAINTEXT
+)
+
+SIGNATURE_TYPE_AUTH_HEADER = 'AUTH_HEADER'
+SIGNATURE_TYPE_QUERY = 'QUERY'
+SIGNATURE_TYPE_BODY = 'BODY'
+
+CONTENT_TYPE_FORM_URLENCODED = 'application/x-www-form-urlencoded'
+
+
+class Client:
+
+    """A client used to sign OAuth 1.0 RFC 5849 requests."""
+    SIGNATURE_METHODS = {
+        SIGNATURE_HMAC_SHA1: signature.sign_hmac_sha1_with_client,
+        SIGNATURE_HMAC_SHA256: signature.sign_hmac_sha256_with_client,
+        SIGNATURE_HMAC_SHA512: signature.sign_hmac_sha512_with_client,
+        SIGNATURE_RSA_SHA1: signature.sign_rsa_sha1_with_client,
+        SIGNATURE_RSA_SHA256: signature.sign_rsa_sha256_with_client,
+        SIGNATURE_RSA_SHA512: signature.sign_rsa_sha512_with_client,
+        SIGNATURE_PLAINTEXT: signature.sign_plaintext_with_client
+    }
+
+    @classmethod
+    def register_signature_method(cls, method_name, method_callback):
+        cls.SIGNATURE_METHODS[method_name] = method_callback
+
+    def __init__(self, client_key,
+                 client_secret=None,
+                 resource_owner_key=None,
+                 resource_owner_secret=None,
+                 callback_uri=None,
+                 signature_method=SIGNATURE_HMAC_SHA1,
+                 signature_type=SIGNATURE_TYPE_AUTH_HEADER,
+                 rsa_key=None, verifier=None, realm=None,
+                 encoding='utf-8', decoding=None,
+                 nonce=None, timestamp=None):
+        """Create an OAuth 1 client.
+
+        :param client_key: Client key (consumer key), mandatory.
+        :param resource_owner_key: Resource owner key (oauth token).
+        :param resource_owner_secret: Resource owner secret (oauth token secret).
+        :param callback_uri: Callback used when obtaining request token.
+        :param signature_method: SIGNATURE_HMAC, SIGNATURE_RSA or SIGNATURE_PLAINTEXT.
+        :param signature_type: SIGNATURE_TYPE_AUTH_HEADER (default),
+                               SIGNATURE_TYPE_QUERY or SIGNATURE_TYPE_BODY
+                               depending on where you want to embed the oauth
+                               credentials.
+        :param rsa_key: RSA key used with SIGNATURE_RSA.
+        :param verifier: Verifier used when obtaining an access token.
+        :param realm: Realm (scope) to which access is being requested.
+        :param encoding: If you provide non-unicode input you may use this
+                         to have oauthlib automatically convert.
+        :param decoding: If you wish that the returned uri, headers and body
+                         from sign be encoded back from unicode, then set
+                         decoding to your preferred encoding, i.e. utf-8.
+        :param nonce: Use this nonce instead of generating one. (Mainly for testing)
+        :param timestamp: Use this timestamp instead of using current. (Mainly for testing)
+        """
+        # Convert to unicode using encoding if given, else assume unicode
+        def encode(x):
+            return to_unicode(x, encoding) if encoding else x
+
+        self.client_key = encode(client_key)
+        self.client_secret = encode(client_secret)
+        self.resource_owner_key = encode(resource_owner_key)
+        self.resource_owner_secret = encode(resource_owner_secret)
+        self.signature_method = encode(signature_method)
+        self.signature_type = encode(signature_type)
+        self.callback_uri = encode(callback_uri)
+        self.rsa_key = encode(rsa_key)
+        self.verifier = encode(verifier)
+        self.realm = encode(realm)
+        self.encoding = encode(encoding)
+        self.decoding = encode(decoding)
+        self.nonce = encode(nonce)
+        self.timestamp = encode(timestamp)
+
+    def __repr__(self):
+        attrs = vars(self).copy()
+        attrs['client_secret'] = '****' if attrs['client_secret'] else None
+        attrs['rsa_key'] = '****' if attrs['rsa_key'] else None
+        attrs[
+            'resource_owner_secret'] = '****' if attrs['resource_owner_secret'] else None
+        attribute_str = ', '.join('{}={}'.format(k, v) for k, v in attrs.items())
+        return '<{} {}>'.format(self.__class__.__name__, attribute_str)
+
+    def get_oauth_signature(self, request):
+        """Get an OAuth signature to be used in signing a request
+
+        To satisfy `section 3.4.1.2`_ item 2, if the request argument's
+        headers dict attribute contains a Host item, its value will
+        replace any netloc part of the request argument's uri attribute
+        value.
+
+        .. _`section 3.4.1.2`: https://tools.ietf.org/html/rfc5849#section-3.4.1.2
+        """
+        if self.signature_method == SIGNATURE_PLAINTEXT:
+            # fast-path
+            return signature.sign_plaintext(self.client_secret,
+                                            self.resource_owner_secret)
+
+        uri, headers, body = self._render(request)
+
+        collected_params = signature.collect_parameters(
+            uri_query=urlparse.urlparse(uri).query,
+            body=body,
+            headers=headers)
+        log.debug("Collected params: {}".format(collected_params))
+
+        normalized_params = signature.normalize_parameters(collected_params)
+        normalized_uri = signature.base_string_uri(uri, headers.get('Host', None))
+        log.debug("Normalized params: {}".format(normalized_params))
+        log.debug("Normalized URI: {}".format(normalized_uri))
+
+        base_string = signature.signature_base_string(request.http_method,
+                                                      normalized_uri, normalized_params)
+
+        log.debug("Signing: signature base string: {}".format(base_string))
+
+        if self.signature_method not in self.SIGNATURE_METHODS:
+            raise ValueError('Invalid signature method.')
+
+        sig = self.SIGNATURE_METHODS[self.signature_method](base_string, self)
+
+        log.debug("Signature: {}".format(sig))
+        return sig
+
+    def get_oauth_params(self, request):
+        """Get the basic OAuth parameters to be used in generating a signature.
+        """
+        nonce = (generate_nonce()
+                 if self.nonce is None else self.nonce)
+        timestamp = (generate_timestamp()
+                     if self.timestamp is None else self.timestamp)
+        params = [
+            ('oauth_nonce', nonce),
+            ('oauth_timestamp', timestamp),
+            ('oauth_version', '1.0'),
+            ('oauth_signature_method', self.signature_method),
+            ('oauth_consumer_key', self.client_key),
+        ]
+        if self.resource_owner_key:
+            params.append(('oauth_token', self.resource_owner_key))
+        if self.callback_uri:
+            params.append(('oauth_callback', self.callback_uri))
+        if self.verifier:
+            params.append(('oauth_verifier', self.verifier))
+
+        # providing body hash for requests other than x-www-form-urlencoded
+        # as described in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-4.1.1
+        # 4.1.1. When to include the body hash
+        #    *  [...] MUST NOT include an oauth_body_hash parameter on requests with form-encoded request bodies
+        #    *  [...] SHOULD include the oauth_body_hash parameter on all other requests.
+        # Note that SHA-1 is vulnerable. The spec acknowledges that in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-6.2
+        # At this time, no further effort has been made to replace SHA-1 for the OAuth Request Body Hash extension.
+        content_type = request.headers.get('Content-Type', None)
+        content_type_eligible = content_type and content_type.find('application/x-www-form-urlencoded') < 0
+        if request.body is not None and content_type_eligible:
+            params.append(('oauth_body_hash', base64.b64encode(hashlib.sha1(request.body.encode('utf-8')).digest()).decode('utf-8')))  # noqa: S324
+
+        return params
+
+    def _render(self, request, formencode=False, realm=None):
+        """Render a signed request according to signature type
+
+        Returns a 3-tuple containing the request URI, headers, and body.
+
+        If the formencode argument is True and the body contains parameters, it
+        is escaped and returned as a valid formencoded string.
+        """
+        # TODO what if there are body params on a header-type auth?
+        # TODO what if there are query params on a body-type auth?
+
+        uri, headers, body = request.uri, request.headers, request.body
+
+        # TODO: right now these prepare_* methods are very narrow in scope--they
+        # only affect their little thing. In some cases (for example, with
+        # header auth) it might be advantageous to allow these methods to touch
+        # other parts of the request, like the headers—so the prepare_headers
+        # method could also set the Content-Type header to x-www-form-urlencoded
+        # like the spec requires. This would be a fundamental change though, and
+        # I'm not sure how I feel about it.
+        if self.signature_type == SIGNATURE_TYPE_AUTH_HEADER:
+            headers = parameters.prepare_headers(
+                request.oauth_params, request.headers, realm=realm)
+        elif self.signature_type == SIGNATURE_TYPE_BODY and request.decoded_body is not None:
+            body = parameters.prepare_form_encoded_body(
+                request.oauth_params, request.decoded_body)
+            if formencode:
+                body = urlencode(body)
+            headers['Content-Type'] = 'application/x-www-form-urlencoded'
+        elif self.signature_type == SIGNATURE_TYPE_QUERY:
+            uri = parameters.prepare_request_uri_query(
+                request.oauth_params, request.uri)
+        else:
+            raise ValueError('Unknown signature type specified.')
+
+        return uri, headers, body
+
+    def sign(self, uri, http_method='GET', body=None, headers=None, realm=None):
+        """Sign a request
+
+        Signs an HTTP request with the specified parts.
+
+        Returns a 3-tuple of the signed request's URI, headers, and body.
+        Note that http_method is not returned as it is unaffected by the OAuth
+        signing process. Also worth noting is that duplicate parameters
+        will be included in the signature, regardless of where they are
+        specified (query, body).
+
+        The body argument may be a dict, a list of 2-tuples, or a formencoded
+        string. The Content-Type header must be 'application/x-www-form-urlencoded'
+        if it is present.
+
+        If the body argument is not one of the above, it will be returned
+        verbatim as it is unaffected by the OAuth signing process. Attempting to
+        sign a request with non-formencoded data using the OAuth body signature
+        type is invalid and will raise an exception.
+
+        If the body does contain parameters, it will be returned as a properly-
+        formatted formencoded string.
+
+        Body may not be included if the http_method is either GET or HEAD as
+        this changes the semantic meaning of the request.
+
+        All string data MUST be unicode or be encoded with the same encoding
+        scheme supplied to the Client constructor, default utf-8. This includes
+        strings inside body dicts, for example.
+        """
+        # normalize request data
+        request = Request(uri, http_method, body, headers,
+                          encoding=self.encoding)
+
+        # sanity check
+        content_type = request.headers.get('Content-Type', None)
+        multipart = content_type and content_type.startswith('multipart/')
+        should_have_params = content_type == CONTENT_TYPE_FORM_URLENCODED
+        has_params = request.decoded_body is not None
+        # 3.4.1.3.1.  Parameter Sources
+        # [Parameters are collected from the HTTP request entity-body, but only
+        # if [...]:
+        #    *  The entity-body is single-part.
+        if multipart and has_params:
+            raise ValueError(
+                "Headers indicate a multipart body but body contains parameters.")
+        #    *  The entity-body follows the encoding requirements of the
+        #       "application/x-www-form-urlencoded" content-type as defined by
+        #       [W3C.REC-html40-19980424].
+        elif should_have_params and not has_params:
+            raise ValueError(
+                "Headers indicate a formencoded body but body was not decodable.")
+        #    *  The HTTP request entity-header includes the "Content-Type"
+        #       header field set to "application/x-www-form-urlencoded".
+        elif not should_have_params and has_params:
+            raise ValueError(
+                "Body contains parameters but Content-Type header was {} "
+                "instead of {}".format(content_type or "not set",
+                                        CONTENT_TYPE_FORM_URLENCODED))
+
+        # 3.5.2.  Form-Encoded Body
+        # Protocol parameters can be transmitted in the HTTP request entity-
+        # body, but only if the following REQUIRED conditions are met:
+        # o  The entity-body is single-part.
+        # o  The entity-body follows the encoding requirements of the
+        #    "application/x-www-form-urlencoded" content-type as defined by
+        #    [W3C.REC-html40-19980424].
+        # o  The HTTP request entity-header includes the "Content-Type" header
+        #    field set to "application/x-www-form-urlencoded".
+        elif self.signature_type == SIGNATURE_TYPE_BODY and not (
+                should_have_params and has_params and not multipart):
+            raise ValueError(
+                'Body signatures may only be used with form-urlencoded content')
+
+        # We amend https://tools.ietf.org/html/rfc5849#section-3.4.1.3.1
+        # with the clause that parameters from body should only be included
+        # in non GET or HEAD requests. Extracting the request body parameters
+        # and including them in the signature base string would give semantic
+        # meaning to the body, which it should not have according to the
+        # HTTP 1.1 spec.
+        elif http_method.upper() in ('GET', 'HEAD') and has_params:
+            raise ValueError('GET/HEAD requests should not include body.')
+
+        # generate the basic OAuth parameters
+        request.oauth_params = self.get_oauth_params(request)
+
+        # generate the signature
+        request.oauth_params.append(
+            ('oauth_signature', self.get_oauth_signature(request)))
+
+        # render the signed request and return it
+        uri, headers, body = self._render(request, formencode=True,
+                                          realm=(realm or self.realm))
+
+        if self.decoding:
+            log.debug('Encoding URI, headers and body to %s.', self.decoding)
+            uri = uri.encode(self.decoding)
+            body = body.encode(self.decoding) if body else body
+            new_headers = {}
+            for k, v in headers.items():
+                new_headers[k.encode(self.decoding)] = v.encode(self.decoding)
+            headers = new_headers
+        return uri, headers, body
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/__init__.py
@@ -0,0 +1,8 @@
+from .access_token import AccessTokenEndpoint
+from .authorization import AuthorizationEndpoint
+from .base import BaseEndpoint
+from .request_token import RequestTokenEndpoint
+from .resource import ResourceEndpoint
+from .signature_only import SignatureOnlyEndpoint
+
+from .pre_configured import WebApplicationServer  # isort:skip
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new file mode 100644
index 0000000000000000000000000000000000000000..13665db08fda810cfc46fa45448d06fe9ec99ae9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/access_token.py
@@ -0,0 +1,215 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.access_token
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of the access token provider logic of
+OAuth 1.0 RFC 5849. It validates the correctness of access token requests,
+creates and persists tokens as well as create the proper response to be
+returned to the client.
+"""
+import logging
+
+from oauthlib.common import urlencode
+
+from .. import errors
+from .base import BaseEndpoint
+
+log = logging.getLogger(__name__)
+
+
+class AccessTokenEndpoint(BaseEndpoint):
+
+    """An endpoint responsible for providing OAuth 1 access tokens.
+
+    Typical use is to instantiate with a request validator and invoke the
+    ``create_access_token_response`` from a view function. The tuple returned
+    has all information necessary (body, status, headers) to quickly form
+    and return a proper response. See :doc:`/oauth1/validator` for details on which
+    validator methods to implement for this endpoint.
+    """
+
+    def create_access_token(self, request, credentials):
+        """Create and save a new access token.
+
+        Similar to OAuth 2, indication of granted scopes will be included as a
+        space separated list in ``oauth_authorized_realms``.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The token as an urlencoded string.
+        """
+        request.realms = self.request_validator.get_realms(
+            request.resource_owner_key, request)
+        token = {
+            'oauth_token': self.token_generator(),
+            'oauth_token_secret': self.token_generator(),
+            # Backport the authorized scopes indication used in OAuth2
+            'oauth_authorized_realms': ' '.join(request.realms)
+        }
+        token.update(credentials)
+        self.request_validator.save_access_token(token, request)
+        return urlencode(token.items())
+
+    def create_access_token_response(self, uri, http_method='GET', body=None,
+                                     headers=None, credentials=None):
+        """Create an access token response, with a new request token if valid.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :param credentials: A list of extra credentials to include in the token.
+        :returns: A tuple of 3 elements.
+                  1. A dict of headers to set on the response.
+                  2. The response body as a string.
+                  3. The response status code as an integer.
+
+        An example of a valid request::
+
+            >>> from your_validator import your_validator
+            >>> from oauthlib.oauth1 import AccessTokenEndpoint
+            >>> endpoint = AccessTokenEndpoint(your_validator)
+            >>> h, b, s = endpoint.create_access_token_response(
+            ...     'https://your.provider/access_token?foo=bar',
+            ...     headers={
+            ...         'Authorization': 'OAuth oauth_token=234lsdkf....'
+            ...     },
+            ...     credentials={
+            ...         'my_specific': 'argument',
+            ...     })
+            >>> h
+            {'Content-Type': 'application/x-www-form-urlencoded'}
+            >>> b
+            'oauth_token=lsdkfol23w54jlksdef&oauth_token_secret=qwe089234lkjsdf&oauth_authorized_realms=movies+pics&my_specific=argument'
+            >>> s
+            200
+
+        An response to invalid request would have a different body and status::
+
+            >>> b
+            'error=invalid_request&description=missing+resource+owner+key'
+            >>> s
+            400
+
+        The same goes for an an unauthorized request:
+
+            >>> b
+            ''
+            >>> s
+            401
+        """
+        resp_headers = {'Content-Type': 'application/x-www-form-urlencoded'}
+        try:
+            request = self._create_request(uri, http_method, body, headers)
+            valid, processed_request = self.validate_access_token_request(
+                request)
+            if valid:
+                token = self.create_access_token(request, credentials or {})
+                self.request_validator.invalidate_request_token(
+                    request.client_key,
+                    request.resource_owner_key,
+                    request)
+                return resp_headers, token, 200
+            else:
+                return {}, None, 401
+        except errors.OAuth1Error as e:
+            return resp_headers, e.urlencoded, e.status_code
+
+    def validate_access_token_request(self, request):
+        """Validate an access token request.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :raises: OAuth1Error if the request is invalid.
+        :returns: A tuple of 2 elements.
+                  1. The validation result (True or False).
+                  2. The request object.
+        """
+        self._check_transport_security(request)
+        self._check_mandatory_parameters(request)
+
+        if not request.resource_owner_key:
+            raise errors.InvalidRequestError(
+                description='Missing resource owner.')
+
+        if not self.request_validator.check_request_token(
+                request.resource_owner_key):
+            raise errors.InvalidRequestError(
+                description='Invalid resource owner key format.')
+
+        if not request.verifier:
+            raise errors.InvalidRequestError(
+                description='Missing verifier.')
+
+        if not self.request_validator.check_verifier(request.verifier):
+            raise errors.InvalidRequestError(
+                description='Invalid verifier format.')
+
+        if not self.request_validator.validate_timestamp_and_nonce(
+                request.client_key, request.timestamp, request.nonce, request,
+                request_token=request.resource_owner_key):
+            return False, request
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid client credentials.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy client is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable client enumeration
+        valid_client = self.request_validator.validate_client_key(
+            request.client_key, request)
+        if not valid_client:
+            request.client_key = self.request_validator.dummy_client
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid or expired token.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy token is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable resource owner enumeration
+        valid_resource_owner = self.request_validator.validate_request_token(
+            request.client_key, request.resource_owner_key, request)
+        if not valid_resource_owner:
+            request.resource_owner_key = self.request_validator.dummy_request_token
+
+        # The server MUST verify (Section 3.2) the validity of the request,
+        # ensure that the resource owner has authorized the provisioning of
+        # token credentials to the client, and ensure that the temporary
+        # credentials have not expired or been used before.  The server MUST
+        # also verify the verification code received from the client.
+        # .. _`Section 3.2`: https://tools.ietf.org/html/rfc5849#section-3.2
+        #
+        # Note that early exit would enable resource owner authorization
+        # verifier enumertion.
+        valid_verifier = self.request_validator.validate_verifier(
+            request.client_key,
+            request.resource_owner_key,
+            request.verifier,
+            request)
+
+        valid_signature = self._check_signature(request, is_token_request=True)
+
+        # log the results to the validator_log
+        # this lets us handle internal reporting and analysis
+        request.validator_log['client'] = valid_client
+        request.validator_log['resource_owner'] = valid_resource_owner
+        request.validator_log['verifier'] = valid_verifier
+        request.validator_log['signature'] = valid_signature
+
+        # We delay checking validity until the very end, using dummy values for
+        # calculations and fetching secrets/keys to ensure the flow of every
+        # request remains almost identical regardless of whether valid values
+        # have been supplied. This ensures near constant time execution and
+        # prevents malicious users from guessing sensitive information
+        v = all((valid_client, valid_resource_owner, valid_verifier,
+                 valid_signature))
+        if not v:
+            log.info("[Failure] request verification failed.")
+            log.info("Valid client:, %s", valid_client)
+            log.info("Valid token:, %s", valid_resource_owner)
+            log.info("Valid verifier:, %s", valid_verifier)
+            log.info("Valid signature:, %s", valid_signature)
+        return v, request
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/authorization.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/authorization.py
new file mode 100644
index 0000000000000000000000000000000000000000..00d9576b01ecd9879a4485cf083c2affa79a520c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/authorization.py
@@ -0,0 +1,158 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.authorization
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for signing and checking OAuth 1.0 RFC 5849 requests.
+"""
+from urllib.parse import urlencode
+
+from oauthlib.common import add_params_to_uri
+
+from .. import errors
+from .base import BaseEndpoint
+
+
+class AuthorizationEndpoint(BaseEndpoint):
+
+    """An endpoint responsible for letting authenticated users authorize access
+    to their protected resources to a client.
+
+    Typical use would be to have two views, one for displaying the authorization
+    form and one to process said form on submission.
+
+    The first view will want to utilize ``get_realms_and_credentials`` to fetch
+    requested realms and useful client credentials, such as name and
+    description, to be used when creating the authorization form.
+
+    During form processing you can use ``create_authorization_response`` to
+    validate the request, create a verifier as well as prepare the final
+    redirection URI used to send the user back to the client.
+
+    See :doc:`/oauth1/validator` for details on which validator methods to implement
+    for this endpoint.
+    """
+
+    def create_verifier(self, request, credentials):
+        """Create and save a new request token.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param credentials: A dict of extra token credentials.
+        :returns: The verifier as a dict.
+        """
+        verifier = {
+            'oauth_token': request.resource_owner_key,
+            'oauth_verifier': self.token_generator(),
+        }
+        verifier.update(credentials)
+        self.request_validator.save_verifier(
+            request.resource_owner_key, verifier, request)
+        return verifier
+
+    def create_authorization_response(self, uri, http_method='GET', body=None,
+                                      headers=None, realms=None, credentials=None):
+        """Create an authorization response, with a new request token if valid.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :param credentials: A list of credentials to include in the verifier.
+        :returns: A tuple of 3 elements.
+                  1. A dict of headers to set on the response.
+                  2. The response body as a string.
+                  3. The response status code as an integer.
+
+        If the callback URI tied to the current token is "oob", a response with
+        a 200 status code will be returned. In this case, it may be desirable to
+        modify the response to better display the verifier to the client.
+
+        An example of an authorization request::
+
+            >>> from your_validator import your_validator
+            >>> from oauthlib.oauth1 import AuthorizationEndpoint
+            >>> endpoint = AuthorizationEndpoint(your_validator)
+            >>> h, b, s = endpoint.create_authorization_response(
+            ...     'https://your.provider/authorize?oauth_token=...',
+            ...     credentials={
+            ...         'extra': 'argument',
+            ...     })
+            >>> h
+            {'Location': 'https://the.client/callback?oauth_verifier=...&extra=argument'}
+            >>> b
+            None
+            >>> s
+            302
+
+        An example of a request with an "oob" callback::
+
+            >>> from your_validator import your_validator
+            >>> from oauthlib.oauth1 import AuthorizationEndpoint
+            >>> endpoint = AuthorizationEndpoint(your_validator)
+            >>> h, b, s = endpoint.create_authorization_response(
+            ...     'https://your.provider/authorize?foo=bar',
+            ...     credentials={
+            ...         'extra': 'argument',
+            ...     })
+            >>> h
+            {'Content-Type': 'application/x-www-form-urlencoded'}
+            >>> b
+            'oauth_verifier=...&extra=argument'
+            >>> s
+            200
+        """
+        request = self._create_request(uri, http_method=http_method, body=body,
+                                       headers=headers)
+
+        if not request.resource_owner_key:
+            raise errors.InvalidRequestError(
+                'Missing mandatory parameter oauth_token.')
+        if not self.request_validator.verify_request_token(
+                request.resource_owner_key, request):
+            raise errors.InvalidClientError()
+
+        request.realms = realms
+        if (request.realms and not self.request_validator.verify_realms(
+                request.resource_owner_key, request.realms, request)):
+            raise errors.InvalidRequestError(
+                description=('User granted access to realms outside of '
+                             'what the client may request.'))
+
+        verifier = self.create_verifier(request, credentials or {})
+        redirect_uri = self.request_validator.get_redirect_uri(
+            request.resource_owner_key, request)
+        if redirect_uri == 'oob':
+            response_headers = {
+                'Content-Type': 'application/x-www-form-urlencoded'}
+            response_body = urlencode(verifier)
+            return response_headers, response_body, 200
+        else:
+            populated_redirect = add_params_to_uri(
+                redirect_uri, verifier.items())
+            return {'Location': populated_redirect}, None, 302
+
+    def get_realms_and_credentials(self, uri, http_method='GET', body=None,
+                                   headers=None):
+        """Fetch realms and credentials for the presented request token.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :returns: A tuple of 2 elements.
+                  1. A list of request realms.
+                  2. A dict of credentials which may be useful in creating the
+                  authorization form.
+        """
+        request = self._create_request(uri, http_method=http_method, body=body,
+                                       headers=headers)
+
+        if not self.request_validator.verify_request_token(
+                request.resource_owner_key, request):
+            raise errors.InvalidClientError()
+
+        realms = self.request_validator.get_realms(
+            request.resource_owner_key, request)
+        return realms, {'resource_owner_key': request.resource_owner_key}
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/base.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..8d3d89c6727c430e0e216c5bdb5abb26cabebf40
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/base.py
@@ -0,0 +1,239 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.base
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for signing and checking OAuth 1.0 RFC 5849 requests.
+"""
+import time
+
+from oauthlib.common import CaseInsensitiveDict, Request, generate_token
+
+from .. import (
+    CONTENT_TYPE_FORM_URLENCODED, SIGNATURE_HMAC_SHA1, SIGNATURE_HMAC_SHA256,
+    SIGNATURE_HMAC_SHA512, SIGNATURE_PLAINTEXT, SIGNATURE_RSA_SHA1,
+    SIGNATURE_RSA_SHA256, SIGNATURE_RSA_SHA512, SIGNATURE_TYPE_AUTH_HEADER,
+    SIGNATURE_TYPE_BODY, SIGNATURE_TYPE_QUERY, errors, signature, utils,
+)
+
+
+class BaseEndpoint:
+
+    def __init__(self, request_validator, token_generator=None):
+        self.request_validator = request_validator
+        self.token_generator = token_generator or generate_token
+
+    def _get_signature_type_and_params(self, request):
+        """Extracts parameters from query, headers and body. Signature type
+        is set to the source in which parameters were found.
+        """
+        # Per RFC5849, only the Authorization header may contain the 'realm'
+        # optional parameter.
+        header_params = signature.collect_parameters(headers=request.headers,
+                                                     exclude_oauth_signature=False, with_realm=True)
+        body_params = signature.collect_parameters(body=request.body,
+                                                   exclude_oauth_signature=False)
+        query_params = signature.collect_parameters(uri_query=request.uri_query,
+                                                    exclude_oauth_signature=False)
+
+        params = []
+        params.extend(header_params)
+        params.extend(body_params)
+        params.extend(query_params)
+        signature_types_with_oauth_params = list(filter(lambda s: s[2], (
+            (SIGNATURE_TYPE_AUTH_HEADER, params,
+                utils.filter_oauth_params(header_params)),
+            (SIGNATURE_TYPE_BODY, params,
+                utils.filter_oauth_params(body_params)),
+            (SIGNATURE_TYPE_QUERY, params,
+                utils.filter_oauth_params(query_params))
+        )))
+
+        if len(signature_types_with_oauth_params) > 1:
+            found_types = [s[0] for s in signature_types_with_oauth_params]
+            raise errors.InvalidRequestError(
+                description=('oauth_ params must come from only 1 signature'
+                             'type but were found in %s',
+                             ', '.join(found_types)))
+
+        try:
+            signature_type, params, oauth_params = signature_types_with_oauth_params[
+                0]
+        except IndexError:
+            raise errors.InvalidRequestError(
+                description='Missing mandatory OAuth parameters.')
+
+        return signature_type, params, oauth_params
+
+    def _create_request(self, uri, http_method, body, headers):
+        # Only include body data from x-www-form-urlencoded requests
+        headers = CaseInsensitiveDict(headers or {})
+        if "Content-Type" in headers and CONTENT_TYPE_FORM_URLENCODED in headers["Content-Type"]:  # noqa: SIM108
+            request = Request(uri, http_method, body, headers)
+        else:
+            request = Request(uri, http_method, '', headers)
+        signature_type, params, oauth_params = (
+            self._get_signature_type_and_params(request))
+
+        # The server SHOULD return a 400 (Bad Request) status code when
+        # receiving a request with duplicated protocol parameters.
+        if len(dict(oauth_params)) != len(oauth_params):
+            raise errors.InvalidRequestError(
+                description='Duplicate OAuth1 entries.')
+
+        oauth_params = dict(oauth_params)
+        request.signature = oauth_params.get('oauth_signature')
+        request.client_key = oauth_params.get('oauth_consumer_key')
+        request.resource_owner_key = oauth_params.get('oauth_token')
+        request.nonce = oauth_params.get('oauth_nonce')
+        request.timestamp = oauth_params.get('oauth_timestamp')
+        request.redirect_uri = oauth_params.get('oauth_callback')
+        request.verifier = oauth_params.get('oauth_verifier')
+        request.signature_method = oauth_params.get('oauth_signature_method')
+        request.realm = dict(params).get('realm')
+        request.oauth_params = oauth_params
+
+        # Parameters to Client depend on signature method which may vary
+        # for each request. Note that HMAC-SHA1 and PLAINTEXT share parameters
+        request.params = [(k, v) for k, v in params if k != "oauth_signature"]
+
+        if 'realm' in request.headers.get('Authorization', ''):
+            request.params = [(k, v)
+                              for k, v in request.params if k != "realm"]
+
+        return request
+
+    def _check_transport_security(self, request):
+        # TODO: move into oauthlib.common from oauth2.utils
+        if (self.request_validator.enforce_ssl and
+                not request.uri.lower().startswith("https://")):
+            raise errors.InsecureTransportError()
+
+    def _check_mandatory_parameters(self, request):
+        # The server SHOULD return a 400 (Bad Request) status code when
+        # receiving a request with missing parameters.
+        if not all((request.signature, request.client_key,
+                    request.nonce, request.timestamp,
+                    request.signature_method)):
+            raise errors.InvalidRequestError(
+                description='Missing mandatory OAuth parameters.')
+
+        # OAuth does not mandate a particular signature method, as each
+        # implementation can have its own unique requirements.  Servers are
+        # free to implement and document their own custom methods.
+        # Recommending any particular method is beyond the scope of this
+        # specification.  Implementers should review the Security
+        # Considerations section (`Section 4`_) before deciding on which
+        # method to support.
+        # .. _`Section 4`: https://tools.ietf.org/html/rfc5849#section-4
+        if (request.signature_method not in self.request_validator.allowed_signature_methods):
+            raise errors.InvalidSignatureMethodError(
+                description="Invalid signature, {} not in {!r}.".format(
+                    request.signature_method,
+                    self.request_validator.allowed_signature_methods))
+
+        # Servers receiving an authenticated request MUST validate it by:
+        #   If the "oauth_version" parameter is present, ensuring its value is
+        #   "1.0".
+        if ('oauth_version' in request.oauth_params and
+                request.oauth_params['oauth_version'] != '1.0'):
+            raise errors.InvalidRequestError(
+                description='Invalid OAuth version.')
+
+        # The timestamp value MUST be a positive integer. Unless otherwise
+        # specified by the server's documentation, the timestamp is expressed
+        # in the number of seconds since January 1, 1970 00:00:00 GMT.
+        if len(request.timestamp) != 10:
+            raise errors.InvalidRequestError(
+                description='Invalid timestamp size')
+
+        try:
+            ts = int(request.timestamp)
+
+        except ValueError:
+            raise errors.InvalidRequestError(
+                description='Timestamp must be an integer.')
+
+        else:
+            # To avoid the need to retain an infinite number of nonce values for
+            # future checks, servers MAY choose to restrict the time period after
+            # which a request with an old timestamp is rejected.
+            if abs(time.time() - ts) > self.request_validator.timestamp_lifetime:
+                raise errors.InvalidRequestError(
+                    description=('Timestamp given is invalid, differ from '
+                                 'allowed by over %s seconds.' % (
+                                     self.request_validator.timestamp_lifetime)))
+
+        # Provider specific validation of parameters, used to enforce
+        # restrictions such as character set and length.
+        if not self.request_validator.check_client_key(request.client_key):
+            raise errors.InvalidRequestError(
+                description='Invalid client key format.')
+
+        if not self.request_validator.check_nonce(request.nonce):
+            raise errors.InvalidRequestError(
+                description='Invalid nonce format.')
+
+    def _check_signature(self, request, is_token_request=False):
+        # ---- RSA Signature verification ----
+        if request.signature_method in {SIGNATURE_RSA_SHA1, SIGNATURE_RSA_SHA256, SIGNATURE_RSA_SHA512}:
+            # RSA-based signature method
+
+            # The server verifies the signature per `[RFC3447] section 8.2.2`_
+            # .. _`[RFC3447] section 8.2.2`: https://tools.ietf.org/html/rfc3447#section-8.2.1
+
+            rsa_key = self.request_validator.get_rsa_key(
+                request.client_key, request)
+
+            if request.signature_method == SIGNATURE_RSA_SHA1:
+                valid_signature = signature.verify_rsa_sha1(request, rsa_key)
+            elif request.signature_method == SIGNATURE_RSA_SHA256:
+                valid_signature = signature.verify_rsa_sha256(request, rsa_key)
+            elif request.signature_method == SIGNATURE_RSA_SHA512:
+                valid_signature = signature.verify_rsa_sha512(request, rsa_key)
+            else:
+                valid_signature = False
+
+        # ---- HMAC or Plaintext Signature verification ----
+        else:
+            # Non-RSA based signature method
+
+            # Servers receiving an authenticated request MUST validate it by:
+            #   Recalculating the request signature independently as described in
+            #   `Section 3.4`_ and comparing it to the value received from the
+            #   client via the "oauth_signature" parameter.
+            # .. _`Section 3.4`: https://tools.ietf.org/html/rfc5849#section-3.4
+
+            client_secret = self.request_validator.get_client_secret(
+                request.client_key, request)
+
+            resource_owner_secret = None
+            if request.resource_owner_key:
+                if is_token_request:
+                    resource_owner_secret = \
+                        self.request_validator.get_request_token_secret(
+                            request.client_key, request.resource_owner_key,
+                            request)
+                else:
+                    resource_owner_secret = \
+                        self.request_validator.get_access_token_secret(
+                            request.client_key, request.resource_owner_key,
+                            request)
+
+            if request.signature_method == SIGNATURE_HMAC_SHA1:
+                valid_signature = signature.verify_hmac_sha1(
+                    request, client_secret, resource_owner_secret)
+            elif request.signature_method == SIGNATURE_HMAC_SHA256:
+                valid_signature = signature.verify_hmac_sha256(
+                    request, client_secret, resource_owner_secret)
+            elif request.signature_method == SIGNATURE_HMAC_SHA512:
+                valid_signature = signature.verify_hmac_sha512(
+                    request, client_secret, resource_owner_secret)
+            elif request.signature_method == SIGNATURE_PLAINTEXT:
+                valid_signature = signature.verify_plaintext(
+                    request, client_secret, resource_owner_secret)
+            else:
+                valid_signature = False
+
+        return valid_signature
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/pre_configured.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/pre_configured.py
new file mode 100644
index 0000000000000000000000000000000000000000..23e3cfc84e0ee61cd461f476c435ef318945ff66
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/pre_configured.py
@@ -0,0 +1,14 @@
+from . import (
+    AccessTokenEndpoint, AuthorizationEndpoint, RequestTokenEndpoint,
+    ResourceEndpoint,
+)
+
+
+class WebApplicationServer(RequestTokenEndpoint, AuthorizationEndpoint,
+                           AccessTokenEndpoint, ResourceEndpoint):
+
+    def __init__(self, request_validator):
+        RequestTokenEndpoint.__init__(self, request_validator)
+        AuthorizationEndpoint.__init__(self, request_validator)
+        AccessTokenEndpoint.__init__(self, request_validator)
+        ResourceEndpoint.__init__(self, request_validator)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/request_token.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/request_token.py
new file mode 100644
index 0000000000000000000000000000000000000000..0323cfb845a7836eab0e181cc9229031788e957e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/request_token.py
@@ -0,0 +1,209 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.request_token
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of the request token provider logic of
+OAuth 1.0 RFC 5849. It validates the correctness of request token requests,
+creates and persists tokens as well as create the proper response to be
+returned to the client.
+"""
+import logging
+
+from oauthlib.common import urlencode
+
+from .. import errors
+from .base import BaseEndpoint
+
+log = logging.getLogger(__name__)
+
+
+class RequestTokenEndpoint(BaseEndpoint):
+
+    """An endpoint responsible for providing OAuth 1 request tokens.
+
+    Typical use is to instantiate with a request validator and invoke the
+    ``create_request_token_response`` from a view function. The tuple returned
+    has all information necessary (body, status, headers) to quickly form
+    and return a proper response. See :doc:`/oauth1/validator` for details on which
+    validator methods to implement for this endpoint.
+    """
+
+    def create_request_token(self, request, credentials):
+        """Create and save a new request token.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param credentials: A dict of extra token credentials.
+        :returns: The token as an urlencoded string.
+        """
+        token = {
+            'oauth_token': self.token_generator(),
+            'oauth_token_secret': self.token_generator(),
+            'oauth_callback_confirmed': 'true'
+        }
+        token.update(credentials)
+        self.request_validator.save_request_token(token, request)
+        return urlencode(token.items())
+
+    def create_request_token_response(self, uri, http_method='GET', body=None,
+                                      headers=None, credentials=None):
+        """Create a request token response, with a new request token if valid.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :param credentials: A list of extra credentials to include in the token.
+        :returns: A tuple of 3 elements.
+                  1. A dict of headers to set on the response.
+                  2. The response body as a string.
+                  3. The response status code as an integer.
+
+        An example of a valid request::
+
+            >>> from your_validator import your_validator
+            >>> from oauthlib.oauth1 import RequestTokenEndpoint
+            >>> endpoint = RequestTokenEndpoint(your_validator)
+            >>> h, b, s = endpoint.create_request_token_response(
+            ...     'https://your.provider/request_token?foo=bar',
+            ...     headers={
+            ...         'Authorization': 'OAuth realm=movies user, oauth_....'
+            ...     },
+            ...     credentials={
+            ...         'my_specific': 'argument',
+            ...     })
+            >>> h
+            {'Content-Type': 'application/x-www-form-urlencoded'}
+            >>> b
+            'oauth_token=lsdkfol23w54jlksdef&oauth_token_secret=qwe089234lkjsdf&oauth_callback_confirmed=true&my_specific=argument'
+            >>> s
+            200
+
+        An response to invalid request would have a different body and status::
+
+            >>> b
+            'error=invalid_request&description=missing+callback+uri'
+            >>> s
+            400
+
+        The same goes for an an unauthorized request:
+
+            >>> b
+            ''
+            >>> s
+            401
+        """
+        resp_headers = {'Content-Type': 'application/x-www-form-urlencoded'}
+        try:
+            request = self._create_request(uri, http_method, body, headers)
+            valid, processed_request = self.validate_request_token_request(
+                request)
+            if valid:
+                token = self.create_request_token(request, credentials or {})
+                return resp_headers, token, 200
+            else:
+                return {}, None, 401
+        except errors.OAuth1Error as e:
+            return resp_headers, e.urlencoded, e.status_code
+
+    def validate_request_token_request(self, request):
+        """Validate a request token request.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :raises: OAuth1Error if the request is invalid.
+        :returns: A tuple of 2 elements.
+                  1. The validation result (True or False).
+                  2. The request object.
+        """
+        self._check_transport_security(request)
+        self._check_mandatory_parameters(request)
+
+        if request.realm:
+            request.realms = request.realm.split(' ')
+        else:
+            request.realms = self.request_validator.get_default_realms(
+                request.client_key, request)
+        if not self.request_validator.check_realms(request.realms):
+            raise errors.InvalidRequestError(
+                description='Invalid realm {}. Allowed are {!r}.'.format(
+                    request.realms, self.request_validator.realms))
+
+        if not request.redirect_uri:
+            raise errors.InvalidRequestError(
+                description='Missing callback URI.')
+
+        if not self.request_validator.validate_timestamp_and_nonce(
+                request.client_key, request.timestamp, request.nonce, request,
+                request_token=request.resource_owner_key):
+            return False, request
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid client credentials.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy client is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable client enumeration
+        valid_client = self.request_validator.validate_client_key(
+            request.client_key, request)
+        if not valid_client:
+            request.client_key = self.request_validator.dummy_client
+
+        # Note that `realm`_ is only used in authorization headers and how
+        # it should be interpreted is not included in the OAuth spec.
+        # However they could be seen as a scope or realm to which the
+        # client has access and as such every client should be checked
+        # to ensure it is authorized access to that scope or realm.
+        # .. _`realm`: https://tools.ietf.org/html/rfc2617#section-1.2
+        #
+        # Note that early exit would enable client realm access enumeration.
+        #
+        # The require_realm indicates this is the first step in the OAuth
+        # workflow where a client requests access to a specific realm.
+        # This first step (obtaining request token) need not require a realm
+        # and can then be identified by checking the require_resource_owner
+        # flag and absence of realm.
+        #
+        # Clients obtaining an access token will not supply a realm and it will
+        # not be checked. Instead the previously requested realm should be
+        # transferred from the request token to the access token.
+        #
+        # Access to protected resources will always validate the realm but note
+        # that the realm is now tied to the access token and not provided by
+        # the client.
+        valid_realm = self.request_validator.validate_requested_realms(
+            request.client_key, request.realms, request)
+
+        # Callback is normally never required, except for requests for
+        # a Temporary Credential as described in `Section 2.1`_
+        # .._`Section 2.1`: https://tools.ietf.org/html/rfc5849#section-2.1
+        valid_redirect = self.request_validator.validate_redirect_uri(
+            request.client_key, request.redirect_uri, request)
+        if not request.redirect_uri:
+            raise NotImplementedError('Redirect URI must either be provided '
+                                      'or set to a default during validation.')
+
+        valid_signature = self._check_signature(request)
+
+        # log the results to the validator_log
+        # this lets us handle internal reporting and analysis
+        request.validator_log['client'] = valid_client
+        request.validator_log['realm'] = valid_realm
+        request.validator_log['callback'] = valid_redirect
+        request.validator_log['signature'] = valid_signature
+
+        # We delay checking validity until the very end, using dummy values for
+        # calculations and fetching secrets/keys to ensure the flow of every
+        # request remains almost identical regardless of whether valid values
+        # have been supplied. This ensures near constant time execution and
+        # prevents malicious users from guessing sensitive information
+        v = all((valid_client, valid_realm, valid_redirect, valid_signature))
+        if not v:
+            log.info("[Failure] request verification failed.")
+            log.info("Valid client: %s.", valid_client)
+            log.info("Valid realm: %s.", valid_realm)
+            log.info("Valid callback: %s.", valid_redirect)
+            log.info("Valid signature: %s.", valid_signature)
+        return v, request
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/resource.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/resource.py
new file mode 100644
index 0000000000000000000000000000000000000000..8641152e4ee765c889ab608080ae3c6aee3e58e8
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/resource.py
@@ -0,0 +1,163 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.resource
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of the resource protection provider logic of
+OAuth 1.0 RFC 5849.
+"""
+import logging
+
+from .. import errors
+from .base import BaseEndpoint
+
+log = logging.getLogger(__name__)
+
+
+class ResourceEndpoint(BaseEndpoint):
+
+    """An endpoint responsible for protecting resources.
+
+    Typical use is to instantiate with a request validator and invoke the
+    ``validate_protected_resource_request`` in a decorator around a view
+    function. If the request is valid, invoke and return the response of the
+    view. If invalid create and return an error response directly from the
+    decorator.
+
+    See :doc:`/oauth1/validator` for details on which validator methods to implement
+    for this endpoint.
+
+    An example decorator::
+
+        from functools import wraps
+        from your_validator import your_validator
+        from oauthlib.oauth1 import ResourceEndpoint
+        endpoint = ResourceEndpoint(your_validator)
+
+        def require_oauth(realms=None):
+            def decorator(f):
+                @wraps(f)
+                def wrapper(request, *args, **kwargs):
+                    v, r = provider.validate_protected_resource_request(
+                            request.url,
+                            http_method=request.method,
+                            body=request.data,
+                            headers=request.headers,
+                            realms=realms or [])
+                    if v:
+                        return f(*args, **kwargs)
+                    else:
+                        return abort(403)
+    """
+
+    def validate_protected_resource_request(self, uri, http_method='GET',
+                                            body=None, headers=None, realms=None):
+        """Create a request token response, with a new request token if valid.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :param realms: A list of realms the resource is protected under.
+                       This will be supplied to the ``validate_realms``
+                       method of the request validator.
+        :returns: A tuple of 2 elements.
+                  1. True if valid, False otherwise.
+                  2. An oauthlib.common.Request object.
+        """
+        try:
+            request = self._create_request(uri, http_method, body, headers)
+        except errors.OAuth1Error:
+            return False, None
+
+        try:
+            self._check_transport_security(request)
+            self._check_mandatory_parameters(request)
+        except errors.OAuth1Error:
+            return False, request
+
+        if not request.resource_owner_key:
+            return False, request
+
+        if not self.request_validator.check_access_token(
+                request.resource_owner_key):
+            return False, request
+
+        if not self.request_validator.validate_timestamp_and_nonce(
+                request.client_key, request.timestamp, request.nonce, request,
+                access_token=request.resource_owner_key):
+            return False, request
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid client credentials.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy client is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable client enumeration
+        valid_client = self.request_validator.validate_client_key(
+            request.client_key, request)
+        if not valid_client:
+            request.client_key = self.request_validator.dummy_client
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid or expired token.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy token is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable resource owner enumeration
+        valid_resource_owner = self.request_validator.validate_access_token(
+            request.client_key, request.resource_owner_key, request)
+        if not valid_resource_owner:
+            request.resource_owner_key = self.request_validator.dummy_access_token
+
+        # Note that `realm`_ is only used in authorization headers and how
+        # it should be interpreted is not included in the OAuth spec.
+        # However they could be seen as a scope or realm to which the
+        # client has access and as such every client should be checked
+        # to ensure it is authorized access to that scope or realm.
+        # .. _`realm`: https://tools.ietf.org/html/rfc2617#section-1.2
+        #
+        # Note that early exit would enable client realm access enumeration.
+        #
+        # The require_realm indicates this is the first step in the OAuth
+        # workflow where a client requests access to a specific realm.
+        # This first step (obtaining request token) need not require a realm
+        # and can then be identified by checking the require_resource_owner
+        # flag and absence of realm.
+        #
+        # Clients obtaining an access token will not supply a realm and it will
+        # not be checked. Instead the previously requested realm should be
+        # transferred from the request token to the access token.
+        #
+        # Access to protected resources will always validate the realm but note
+        # that the realm is now tied to the access token and not provided by
+        # the client.
+        valid_realm = self.request_validator.validate_realms(request.client_key,
+                                                             request.resource_owner_key, request, uri=request.uri,
+                                                             realms=realms)
+
+        valid_signature = self._check_signature(request)
+
+        # log the results to the validator_log
+        # this lets us handle internal reporting and analysis
+        request.validator_log['client'] = valid_client
+        request.validator_log['resource_owner'] = valid_resource_owner
+        request.validator_log['realm'] = valid_realm
+        request.validator_log['signature'] = valid_signature
+
+        # We delay checking validity until the very end, using dummy values for
+        # calculations and fetching secrets/keys to ensure the flow of every
+        # request remains almost identical regardless of whether valid values
+        # have been supplied. This ensures near constant time execution and
+        # prevents malicious users from guessing sensitive information
+        v = all((valid_client, valid_resource_owner, valid_realm,
+                 valid_signature))
+        if not v:
+            log.info("[Failure] request verification failed.")
+            log.info("Valid client: %s", valid_client)
+            log.info("Valid token: %s", valid_resource_owner)
+            log.info("Valid realm: %s", valid_realm)
+            log.info("Valid signature: %s", valid_signature)
+        return v, request
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/signature_only.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/signature_only.py
new file mode 100644
index 0000000000000000000000000000000000000000..d693ccb7f6bf368754223f822a143dc81b8232df
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/endpoints/signature_only.py
@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth1.rfc5849.endpoints.signature_only
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of the signing logic of OAuth 1.0 RFC 5849.
+"""
+
+import logging
+
+from .. import errors
+from .base import BaseEndpoint
+
+log = logging.getLogger(__name__)
+
+
+class SignatureOnlyEndpoint(BaseEndpoint):
+
+    """An endpoint only responsible for verifying an oauth signature."""
+
+    def validate_request(self, uri, http_method='GET',
+                         body=None, headers=None):
+        """Validate a signed OAuth request.
+
+        :param uri: The full URI of the token request.
+        :param http_method: A valid HTTP verb, i.e. GET, POST, PUT, HEAD, etc.
+        :param body: The request body as a string.
+        :param headers: The request headers as a dict.
+        :returns: A tuple of 2 elements.
+                  1. True if valid, False otherwise.
+                  2. An oauthlib.common.Request object.
+        """
+        try:
+            request = self._create_request(uri, http_method, body, headers)
+        except errors.OAuth1Error as err:
+            log.info(
+                'Exception caught while validating request, %s.' % err)
+            return False, None
+
+        try:
+            self._check_transport_security(request)
+            self._check_mandatory_parameters(request)
+        except errors.OAuth1Error as err:
+            log.info(
+                'Exception caught while validating request, %s.' % err)
+            return False, request
+
+        if not self.request_validator.validate_timestamp_and_nonce(
+                request.client_key, request.timestamp, request.nonce, request):
+            log.debug('[Failure] verification failed: timestamp/nonce')
+            return False, request
+
+        # The server SHOULD return a 401 (Unauthorized) status code when
+        # receiving a request with invalid client credentials.
+        # Note: This is postponed in order to avoid timing attacks, instead
+        # a dummy client is assigned and used to maintain near constant
+        # time request verification.
+        #
+        # Note that early exit would enable client enumeration
+        valid_client = self.request_validator.validate_client_key(
+            request.client_key, request)
+        if not valid_client:
+            request.client_key = self.request_validator.dummy_client
+
+        valid_signature = self._check_signature(request)
+
+        # log the results to the validator_log
+        # this lets us handle internal reporting and analysis
+        request.validator_log['client'] = valid_client
+        request.validator_log['signature'] = valid_signature
+
+        # We delay checking validity until the very end, using dummy values for
+        # calculations and fetching secrets/keys to ensure the flow of every
+        # request remains almost identical regardless of whether valid values
+        # have been supplied. This ensures near constant time execution and
+        # prevents malicious users from guessing sensitive information
+        v = all((valid_client, valid_signature))
+        if not v:
+            log.info("[Failure] request verification failed.")
+            log.info("Valid client: %s", valid_client)
+            log.info("Valid signature: %s", valid_signature)
+        return v, request
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/errors.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/errors.py
new file mode 100644
index 0000000000000000000000000000000000000000..8774d40741b4b26a3721be545c66513505aaa8d1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/errors.py
@@ -0,0 +1,76 @@
+"""
+oauthlib.oauth1.rfc5849.errors
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Error used both by OAuth 1 clients and provicers to represent the spec
+defined error responses for all four core grant types.
+"""
+from oauthlib.common import add_params_to_uri, urlencode
+
+
+class OAuth1Error(Exception):
+    error = None
+    description = ''
+
+    def __init__(self, description=None, uri=None, status_code=400,
+                 request=None):
+        """
+        description:    A human-readable ASCII [USASCII] text providing
+                        additional information, used to assist the client
+                        developer in understanding the error that occurred.
+                        Values for the "error_description" parameter MUST NOT
+                        include characters outside the set
+                        x20-21 / x23-5B / x5D-7E.
+
+        uri:    A URI identifying a human-readable web page with information
+                about the error, used to provide the client developer with
+                additional information about the error.  Values for the
+                "error_uri" parameter MUST conform to the URI- Reference
+                syntax, and thus MUST NOT include characters outside the set
+                x21 / x23-5B / x5D-7E.
+
+        state:  A CSRF protection value received from the client.
+
+        request:  Oauthlib Request object
+        """
+        self.description = description or self.description
+        message = '({}) {}'.format(self.error, self.description)
+        if request:
+            message += ' ' + repr(request)
+        super().__init__(message)
+
+        self.uri = uri
+        self.status_code = status_code
+
+    def in_uri(self, uri):
+        return add_params_to_uri(uri, self.twotuples)
+
+    @property
+    def twotuples(self):
+        error = [('error', self.error)]
+        if self.description:
+            error.append(('error_description', self.description))
+        if self.uri:
+            error.append(('error_uri', self.uri))
+        return error
+
+    @property
+    def urlencoded(self):
+        return urlencode(self.twotuples)
+
+
+class InsecureTransportError(OAuth1Error):
+    error = 'insecure_transport_protocol'
+    description = 'Only HTTPS connections are permitted.'
+
+
+class InvalidSignatureMethodError(OAuth1Error):
+    error = 'invalid_signature_method'
+
+
+class InvalidRequestError(OAuth1Error):
+    error = 'invalid_request'
+
+
+class InvalidClientError(OAuth1Error):
+    error = 'invalid_client'
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/parameters.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/parameters.py
new file mode 100644
index 0000000000000000000000000000000000000000..2163772df3c7f53d539fa8cb0b73cc0e547614f2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/parameters.py
@@ -0,0 +1,133 @@
+"""
+oauthlib.parameters
+~~~~~~~~~~~~~~~~~~~
+
+This module contains methods related to `section 3.5`_ of the OAuth 1.0a spec.
+
+.. _`section 3.5`: https://tools.ietf.org/html/rfc5849#section-3.5
+"""
+from urllib.parse import urlparse, urlunparse
+
+from oauthlib.common import extract_params, urlencode
+
+from . import utils
+
+
+# TODO: do we need filter_params now that oauth_params are handled by Request?
+#       We can easily pass in just oauth protocol params.
+@utils.filter_params
+def prepare_headers(oauth_params, headers=None, realm=None):
+    """**Prepare the Authorization header.**
+    Per `section 3.5.1`_ of the spec.
+
+    Protocol parameters can be transmitted using the HTTP "Authorization"
+    header field as defined by `RFC2617`_ with the auth-scheme name set to
+    "OAuth" (case insensitive).
+
+    For example::
+
+        Authorization: OAuth realm="Example",
+            oauth_consumer_key="0685bd9184jfhq22",
+            oauth_token="ad180jjd733klru7",
+            oauth_signature_method="HMAC-SHA1",
+            oauth_signature="wOJIO9A2W5mFwDgiDvZbTSMK%2FPY%3D",
+            oauth_timestamp="137131200",
+            oauth_nonce="4572616e48616d6d65724c61686176",
+            oauth_version="1.0"
+
+
+    .. _`section 3.5.1`: https://tools.ietf.org/html/rfc5849#section-3.5.1
+    .. _`RFC2617`: https://tools.ietf.org/html/rfc2617
+    """
+    headers = headers or {}
+
+    # Protocol parameters SHALL be included in the "Authorization" header
+    # field as follows:
+    authorization_header_parameters_parts = []
+    for oauth_parameter_name, value in oauth_params:
+        # 1.  Parameter names and values are encoded per Parameter Encoding
+        #     (`Section 3.6`_)
+        #
+        # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+        escaped_name = utils.escape(oauth_parameter_name)
+        escaped_value = utils.escape(value)
+
+        # 2.  Each parameter's name is immediately followed by an "=" character
+        #     (ASCII code 61), a """ character (ASCII code 34), the parameter
+        #     value (MAY be empty), and another """ character (ASCII code 34).
+        part = '{}="{}"'.format(escaped_name, escaped_value)
+
+        authorization_header_parameters_parts.append(part)
+
+    # 3.  Parameters are separated by a "," character (ASCII code 44) and
+    #     OPTIONAL linear whitespace per `RFC2617`_.
+    #
+    # .. _`RFC2617`: https://tools.ietf.org/html/rfc2617
+    authorization_header_parameters = ', '.join(
+        authorization_header_parameters_parts)
+
+    # 4.  The OPTIONAL "realm" parameter MAY be added and interpreted per
+    #     `RFC2617 section 1.2`_.
+    #
+    # .. _`RFC2617 section 1.2`: https://tools.ietf.org/html/rfc2617#section-1.2
+    if realm:
+        # NOTE: realm should *not* be escaped
+        authorization_header_parameters = ('realm="%s", ' % realm +
+                                           authorization_header_parameters)
+
+    # the auth-scheme name set to "OAuth" (case insensitive).
+    authorization_header = 'OAuth %s' % authorization_header_parameters
+
+    # contribute the Authorization header to the given headers
+    full_headers = {}
+    full_headers.update(headers)
+    full_headers['Authorization'] = authorization_header
+    return full_headers
+
+
+def _append_params(oauth_params, params):
+    """Append OAuth params to an existing set of parameters.
+
+    Both params and oauth_params is must be lists of 2-tuples.
+
+    Per `section 3.5.2`_ and `3.5.3`_ of the spec.
+
+    .. _`section 3.5.2`: https://tools.ietf.org/html/rfc5849#section-3.5.2
+    .. _`3.5.3`: https://tools.ietf.org/html/rfc5849#section-3.5.3
+
+    """
+    merged = list(params)
+    merged.extend(oauth_params)
+    # The request URI / entity-body MAY include other request-specific
+    # parameters, in which case, the protocol parameters SHOULD be appended
+    # following the request-specific parameters, properly separated by an "&"
+    # character (ASCII code 38)
+    merged.sort(key=lambda i: i[0].startswith('oauth_'))
+    return merged
+
+
+def prepare_form_encoded_body(oauth_params, body):
+    """Prepare the Form-Encoded Body.
+
+    Per `section 3.5.2`_ of the spec.
+
+    .. _`section 3.5.2`: https://tools.ietf.org/html/rfc5849#section-3.5.2
+
+    """
+    # append OAuth params to the existing body
+    return _append_params(oauth_params, body)
+
+
+def prepare_request_uri_query(oauth_params, uri):
+    """Prepare the Request URI Query.
+
+    Per `section 3.5.3`_ of the spec.
+
+    .. _`section 3.5.3`: https://tools.ietf.org/html/rfc5849#section-3.5.3
+
+    """
+    # append OAuth params to the existing set of query components
+    sch, net, path, par, query, fra = urlparse(uri)
+    query = urlencode(
+        _append_params(oauth_params, extract_params(query) or []))
+    return urlunparse((sch, net, path, par, query, fra))
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/request_validator.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/request_validator.py
new file mode 100644
index 0000000000000000000000000000000000000000..e937aabf4082850d8e966e75530dde6ff0becb13
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/request_validator.py
@@ -0,0 +1,849 @@
+"""
+oauthlib.oauth1.rfc5849
+~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for signing and checking OAuth 1.0 RFC 5849 requests.
+"""
+from . import SIGNATURE_METHODS, utils
+
+
+class RequestValidator:
+
+    """A validator/datastore interaction base class for OAuth 1 providers.
+
+    OAuth providers should inherit from RequestValidator and implement the
+    methods and properties outlined below. Further details are provided in the
+    documentation for each method and property.
+
+    Methods used to check the format of input parameters. Common tests include
+    length, character set, membership, range or pattern. These tests are
+    referred to as `whitelisting or blacklisting`_. Whitelisting is better
+    but blacklisting can be useful to spot malicious activity.
+    The following have methods a default implementation:
+
+    - check_client_key
+    - check_request_token
+    - check_access_token
+    - check_nonce
+    - check_verifier
+    - check_realms
+
+    The methods above default to whitelist input parameters, checking that they
+    are alphanumerical and between a minimum and maximum length. Rather than
+    overloading the methods a few properties can be used to configure these
+    methods.
+
+    * @safe_characters -> (character set)
+    * @client_key_length -> (min, max)
+    * @request_token_length -> (min, max)
+    * @access_token_length -> (min, max)
+    * @nonce_length -> (min, max)
+    * @verifier_length -> (min, max)
+    * @realms -> [list, of, realms]
+
+    Methods used to validate/invalidate input parameters. These checks usually
+    hit either persistent or temporary storage such as databases or the
+    filesystem. See each methods documentation for detailed usage.
+    The following methods must be implemented:
+
+    - validate_client_key
+    - validate_request_token
+    - validate_access_token
+    - validate_timestamp_and_nonce
+    - validate_redirect_uri
+    - validate_requested_realms
+    - validate_realms
+    - validate_verifier
+    - invalidate_request_token
+
+    Methods used to retrieve sensitive information from storage.
+    The following methods must be implemented:
+
+    - get_client_secret
+    - get_request_token_secret
+    - get_access_token_secret
+    - get_rsa_key
+    - get_realms
+    - get_default_realms
+    - get_redirect_uri
+
+    Methods used to save credentials.
+    The following methods must be implemented:
+
+    - save_request_token
+    - save_verifier
+    - save_access_token
+
+    Methods used to verify input parameters. This methods are used during
+    authorizing request token by user (AuthorizationEndpoint), to check if
+    parameters are valid. During token authorization request is not signed,
+    thus 'validation' methods can not be used. The following methods must be
+    implemented:
+
+    - verify_realms
+    - verify_request_token
+
+    To prevent timing attacks it is necessary to not exit early even if the
+    client key or resource owner key is invalid. Instead dummy values should
+    be used during the remaining verification process. It is very important
+    that the dummy client and token are valid input parameters to the methods
+    get_client_secret, get_rsa_key and get_(access/request)_token_secret and
+    that the running time of those methods when given a dummy value remain
+    equivalent to the running time when given a valid client/resource owner.
+    The following properties must be implemented:
+
+    * @dummy_client
+    * @dummy_request_token
+    * @dummy_access_token
+
+    Example implementations have been provided, note that the database used is
+    a simple dictionary and serves only an illustrative purpose. Use whichever
+    database suits your project and how to access it is entirely up to you.
+    The methods are introduced in an order which should make understanding
+    their use more straightforward and as such it could be worth reading what
+    follows in chronological order.
+
+    .. _`whitelisting or blacklisting`: https://www.schneier.com/blog/archives/2011/01/whitelisting_vs.html
+    """
+
+    def __init__(self):
+        pass
+
+    @property
+    def allowed_signature_methods(self):
+        return SIGNATURE_METHODS
+
+    @property
+    def safe_characters(self):
+        return set(utils.UNICODE_ASCII_CHARACTER_SET)
+
+    @property
+    def client_key_length(self):
+        return 20, 30
+
+    @property
+    def request_token_length(self):
+        return 20, 30
+
+    @property
+    def access_token_length(self):
+        return 20, 30
+
+    @property
+    def timestamp_lifetime(self):
+        return 600
+
+    @property
+    def nonce_length(self):
+        return 20, 30
+
+    @property
+    def verifier_length(self):
+        return 20, 30
+
+    @property
+    def realms(self):
+        return []
+
+    @property
+    def enforce_ssl(self):
+        return True
+
+    def check_client_key(self, client_key):
+        """Check that the client key only contains safe characters
+        and is no shorter than lower and no longer than upper.
+        """
+        lower, upper = self.client_key_length
+        return (set(client_key) <= self.safe_characters and
+                lower <= len(client_key) <= upper)
+
+    def check_request_token(self, request_token):
+        """Checks that the request token contains only safe characters
+        and is no shorter than lower and no longer than upper.
+        """
+        lower, upper = self.request_token_length
+        return (set(request_token) <= self.safe_characters and
+                lower <= len(request_token) <= upper)
+
+    def check_access_token(self, request_token):
+        """Checks that the token contains only safe characters
+        and is no shorter than lower and no longer than upper.
+        """
+        lower, upper = self.access_token_length
+        return (set(request_token) <= self.safe_characters and
+                lower <= len(request_token) <= upper)
+
+    def check_nonce(self, nonce):
+        """Checks that the nonce only contains only safe characters
+        and is no shorter than lower and no longer than upper.
+        """
+        lower, upper = self.nonce_length
+        return (set(nonce) <= self.safe_characters and
+                lower <= len(nonce) <= upper)
+
+    def check_verifier(self, verifier):
+        """Checks that the verifier contains only safe characters
+        and is no shorter than lower and no longer than upper.
+        """
+        lower, upper = self.verifier_length
+        return (set(verifier) <= self.safe_characters and
+                lower <= len(verifier) <= upper)
+
+    def check_realms(self, realms):
+        """Check that the realm is one of a set allowed realms."""
+        return all(r in self.realms for r in realms)
+
+    def _subclass_must_implement(self, fn):
+        """
+        Returns a NotImplementedError for a function that should be implemented.
+        :param fn: name of the function
+        """
+        m = "Missing function implementation in {}: {}".format(type(self), fn)
+        return NotImplementedError(m)
+
+    @property
+    def dummy_client(self):
+        """Dummy client used when an invalid client key is supplied.
+
+        :returns: The dummy client key string.
+
+        The dummy client should be associated with either a client secret,
+        a rsa key or both depending on which signature methods are supported.
+        Providers should make sure that
+
+        get_client_secret(dummy_client)
+        get_rsa_key(dummy_client)
+
+        return a valid secret or key for the dummy client.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        * RequestTokenEndpoint
+        * ResourceEndpoint
+        * SignatureOnlyEndpoint
+        """
+        raise self._subclass_must_implement("dummy_client")
+
+    @property
+    def dummy_request_token(self):
+        """Dummy request token used when an invalid token was supplied.
+
+        :returns: The dummy request token string.
+
+        The dummy request token should be associated with a request token
+        secret such that get_request_token_secret(.., dummy_request_token)
+        returns a valid secret.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("dummy_request_token")
+
+    @property
+    def dummy_access_token(self):
+        """Dummy access token used when an invalid token was supplied.
+
+        :returns: The dummy access token string.
+
+        The dummy access token should be associated with an access token
+        secret such that get_access_token_secret(.., dummy_access_token)
+        returns a valid secret.
+
+        This method is used by
+
+        * ResourceEndpoint
+        """
+        raise self._subclass_must_implement("dummy_access_token")
+
+    def get_client_secret(self, client_key, request):
+        """Retrieves the client secret associated with the client key.
+
+        :param client_key: The client/consumer key.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The client secret as a string.
+
+        This method must allow the use of a dummy client_key value.
+        Fetching the secret using the dummy key must take the same amount of
+        time as fetching a secret for a valid client::
+
+            # Unlikely to be near constant time as it uses two database
+            # lookups for a valid client, and only one for an invalid.
+            from your_datastore import ClientSecret
+            if ClientSecret.has(client_key):
+                return ClientSecret.get(client_key)
+            else:
+                return 'dummy'
+
+            # Aim to mimic number of latency inducing operations no matter
+            # whether the client is valid or not.
+            from your_datastore import ClientSecret
+            return ClientSecret.get(client_key, 'dummy')
+
+        Note that the returned key must be in plaintext.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        * RequestTokenEndpoint
+        * ResourceEndpoint
+        * SignatureOnlyEndpoint
+        """
+        raise self._subclass_must_implement('get_client_secret')
+
+    def get_request_token_secret(self, client_key, token, request):
+        """Retrieves the shared secret associated with the request token.
+
+        :param client_key: The client/consumer key.
+        :param token: The request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The token secret as a string.
+
+        This method must allow the use of a dummy values and the running time
+        must be roughly equivalent to that of the running time of valid values::
+
+            # Unlikely to be near constant time as it uses two database
+            # lookups for a valid client, and only one for an invalid.
+            from your_datastore import RequestTokenSecret
+            if RequestTokenSecret.has(client_key):
+                return RequestTokenSecret.get((client_key, request_token))
+            else:
+                return 'dummy'
+
+            # Aim to mimic number of latency inducing operations no matter
+            # whether the client is valid or not.
+            from your_datastore import RequestTokenSecret
+            return ClientSecret.get((client_key, request_token), 'dummy')
+
+        Note that the returned key must be in plaintext.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement('get_request_token_secret')
+
+    def get_access_token_secret(self, client_key, token, request):
+        """Retrieves the shared secret associated with the access token.
+
+        :param client_key: The client/consumer key.
+        :param token: The access token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The token secret as a string.
+
+        This method must allow the use of a dummy values and the running time
+        must be roughly equivalent to that of the running time of valid values::
+
+            # Unlikely to be near constant time as it uses two database
+            # lookups for a valid client, and only one for an invalid.
+            from your_datastore import AccessTokenSecret
+            if AccessTokenSecret.has(client_key):
+                return AccessTokenSecret.get((client_key, request_token))
+            else:
+                return 'dummy'
+
+            # Aim to mimic number of latency inducing operations no matter
+            # whether the client is valid or not.
+            from your_datastore import AccessTokenSecret
+            return ClientSecret.get((client_key, request_token), 'dummy')
+
+        Note that the returned key must be in plaintext.
+
+        This method is used by
+
+        * ResourceEndpoint
+        """
+        raise self._subclass_must_implement("get_access_token_secret")
+
+    def get_default_realms(self, client_key, request):
+        """Get the default realms for a client.
+
+        :param client_key: The client/consumer key.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The list of default realms associated with the client.
+
+        The list of default realms will be set during client registration and
+        is outside the scope of OAuthLib.
+
+        This method is used by
+
+        * RequestTokenEndpoint
+        """
+        raise self._subclass_must_implement("get_default_realms")
+
+    def get_realms(self, token, request):
+        """Get realms associated with a request token.
+
+        :param token: The request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The list of realms associated with the request token.
+
+        This method is used by
+
+        * AuthorizationEndpoint
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("get_realms")
+
+    def get_redirect_uri(self, token, request):
+        """Get the redirect URI associated with a request token.
+
+        :param token: The request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The redirect URI associated with the request token.
+
+        It may be desirable to return a custom URI if the redirect is set to "oob".
+        In this case, the user will be redirected to the returned URI and at that
+        endpoint the verifier can be displayed.
+
+        This method is used by
+
+        * AuthorizationEndpoint
+        """
+        raise self._subclass_must_implement("get_redirect_uri")
+
+    def get_rsa_key(self, client_key, request):
+        """Retrieves a previously stored client provided RSA key.
+
+        :param client_key: The client/consumer key.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: The rsa public key as a string.
+
+        This method must allow the use of a dummy client_key value. Fetching
+        the rsa key using the dummy key must take the same amount of time
+        as fetching a key for a valid client. The dummy key must also be of
+        the same bit length as client keys.
+
+        Note that the key must be returned in plaintext.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        * RequestTokenEndpoint
+        * ResourceEndpoint
+        * SignatureOnlyEndpoint
+        """
+        raise self._subclass_must_implement("get_rsa_key")
+
+    def invalidate_request_token(self, client_key, request_token, request):
+        """Invalidates a used request token.
+
+        :param client_key: The client/consumer key.
+        :param request_token: The request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: None
+
+        Per `Section 2.3`_ of the spec:
+
+        "The server MUST (...) ensure that the temporary
+        credentials have not expired or been used before."
+
+        .. _`Section 2.3`: https://tools.ietf.org/html/rfc5849#section-2.3
+
+        This method should ensure that provided token won't validate anymore.
+        It can be simply removing RequestToken from storage or setting
+        specific flag that makes it invalid (note that such flag should be
+        also validated during request token validation).
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("invalidate_request_token")
+
+    def validate_client_key(self, client_key, request):
+        """Validates that supplied client key is a registered and valid client.
+
+        :param client_key: The client/consumer key.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        Note that if the dummy client is supplied it should validate in same
+        or nearly the same amount of time as a valid one.
+
+        Ensure latency inducing tasks are mimiced even for dummy clients.
+        For example, use::
+
+            from your_datastore import Client
+            try:
+                return Client.exists(client_key, access_token)
+            except DoesNotExist:
+                return False
+
+        Rather than::
+
+            from your_datastore import Client
+            if access_token == self.dummy_access_token:
+                return False
+            else:
+                return Client.exists(client_key, access_token)
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        * RequestTokenEndpoint
+        * ResourceEndpoint
+        * SignatureOnlyEndpoint
+        """
+        raise self._subclass_must_implement("validate_client_key")
+
+    def validate_request_token(self, client_key, token, request):
+        """Validates that supplied request token is registered and valid.
+
+        :param client_key: The client/consumer key.
+        :param token: The request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        Note that if the dummy request_token is supplied it should validate in
+        the same nearly the same amount of time as a valid one.
+
+        Ensure latency inducing tasks are mimiced even for dummy clients.
+        For example, use::
+
+            from your_datastore import RequestToken
+            try:
+                return RequestToken.exists(client_key, access_token)
+            except DoesNotExist:
+                return False
+
+        Rather than::
+
+            from your_datastore import RequestToken
+            if access_token == self.dummy_access_token:
+                return False
+            else:
+                return RequestToken.exists(client_key, access_token)
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("validate_request_token")
+
+    def validate_access_token(self, client_key, token, request):
+        """Validates that supplied access token is registered and valid.
+
+        :param client_key: The client/consumer key.
+        :param token: The access token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        Note that if the dummy access token is supplied it should validate in
+        the same or nearly the same amount of time as a valid one.
+
+        Ensure latency inducing tasks are mimiced even for dummy clients.
+        For example, use::
+
+            from your_datastore import AccessToken
+            try:
+                return AccessToken.exists(client_key, access_token)
+            except DoesNotExist:
+                return False
+
+        Rather than::
+
+            from your_datastore import AccessToken
+            if access_token == self.dummy_access_token:
+                return False
+            else:
+                return AccessToken.exists(client_key, access_token)
+
+        This method is used by
+
+        * ResourceEndpoint
+        """
+        raise self._subclass_must_implement("validate_access_token")
+
+    def validate_timestamp_and_nonce(self, client_key, timestamp, nonce,
+                                     request, request_token=None, access_token=None):
+        """Validates that the nonce has not been used before.
+
+        :param client_key: The client/consumer key.
+        :param timestamp: The ``oauth_timestamp`` parameter.
+        :param nonce: The ``oauth_nonce`` parameter.
+        :param request_token: Request token string, if any.
+        :param access_token: Access token string, if any.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        Per `Section 3.3`_ of the spec.
+
+        "A nonce is a random string, uniquely generated by the client to allow
+        the server to verify that a request has never been made before and
+        helps prevent replay attacks when requests are made over a non-secure
+        channel.  The nonce value MUST be unique across all requests with the
+        same timestamp, client credentials, and token combinations."
+
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc5849#section-3.3
+
+        One of the first validation checks that will be made is for the validity
+        of the nonce and timestamp, which are associated with a client key and
+        possibly a token. If invalid then immediately fail the request
+        by returning False. If the nonce/timestamp pair has been used before and
+        you may just have detected a replay attack. Therefore it is an essential
+        part of OAuth security that you not allow nonce/timestamp reuse.
+        Note that this validation check is done before checking the validity of
+        the client and token.::
+
+           nonces_and_timestamps_database = [
+              (u'foo', 1234567890, u'rannoMstrInghere', u'bar')
+           ]
+
+           def validate_timestamp_and_nonce(self, client_key, timestamp, nonce,
+              request_token=None, access_token=None):
+
+              return ((client_key, timestamp, nonce, request_token or access_token)
+                       not in self.nonces_and_timestamps_database)
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        * RequestTokenEndpoint
+        * ResourceEndpoint
+        * SignatureOnlyEndpoint
+        """
+        raise self._subclass_must_implement("validate_timestamp_and_nonce")
+
+    def validate_redirect_uri(self, client_key, redirect_uri, request):
+        """Validates the client supplied redirection URI.
+
+        :param client_key: The client/consumer key.
+        :param redirect_uri: The URI the client which to redirect back to after
+                             authorization is successful.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        It is highly recommended that OAuth providers require their clients
+        to register all redirection URIs prior to using them in requests and
+        register them as absolute URIs. See `CWE-601`_ for more information
+        about open redirection attacks.
+
+        By requiring registration of all redirection URIs it should be
+        straightforward for the provider to verify whether the supplied
+        redirect_uri is valid or not.
+
+        Alternatively per `Section 2.1`_ of the spec:
+
+        "If the client is unable to receive callbacks or a callback URI has
+        been established via other means, the parameter value MUST be set to
+        "oob" (case sensitive), to indicate an out-of-band configuration."
+
+        .. _`CWE-601`: http://cwe.mitre.org/top25/index.html#CWE-601
+        .. _`Section 2.1`: https://tools.ietf.org/html/rfc5849#section-2.1
+
+        This method is used by
+
+        * RequestTokenEndpoint
+        """
+        raise self._subclass_must_implement("validate_redirect_uri")
+
+    def validate_requested_realms(self, client_key, realms, request):
+        """Validates that the client may request access to the realm.
+
+        :param client_key: The client/consumer key.
+        :param realms: The list of realms that client is requesting access to.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        This method is invoked when obtaining a request token and should
+        tie a realm to the request token and after user authorization
+        this realm restriction should transfer to the access token.
+
+        This method is used by
+
+        * RequestTokenEndpoint
+        """
+        raise self._subclass_must_implement("validate_requested_realms")
+
+    def validate_realms(self, client_key, token, request, uri=None,
+                        realms=None):
+        """Validates access to the request realm.
+
+        :param client_key: The client/consumer key.
+        :param token: A request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param uri: The URI the realms is protecting.
+        :param realms: A list of realms that must have been granted to
+                       the access token.
+        :returns: True or False
+
+        How providers choose to use the realm parameter is outside the OAuth
+        specification but it is commonly used to restrict access to a subset
+        of protected resources such as "photos".
+
+        realms is a convenience parameter which can be used to provide
+        a per view method pre-defined list of allowed realms.
+
+        Can be as simple as::
+
+            from your_datastore import RequestToken
+            request_token = RequestToken.get(token, None)
+
+            if not request_token:
+                return False
+            return set(request_token.realms).issuperset(set(realms))
+
+        This method is used by
+
+        * ResourceEndpoint
+        """
+        raise self._subclass_must_implement("validate_realms")
+
+    def validate_verifier(self, client_key, token, verifier, request):
+        """Validates a verification code.
+
+        :param client_key: The client/consumer key.
+        :param token: A request token string.
+        :param verifier: The authorization verifier string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        OAuth providers issue a verification code to clients after the
+        resource owner authorizes access. This code is used by the client to
+        obtain token credentials and the provider must verify that the
+        verifier is valid and associated with the client as well as the
+        resource owner.
+
+        Verifier validation should be done in near constant time
+        (to avoid verifier enumeration). To achieve this we need a
+        constant time string comparison which is provided by OAuthLib
+        in ``oauthlib.common.safe_string_equals``::
+
+            from your_datastore import Verifier
+            correct_verifier = Verifier.get(client_key, request_token)
+            from oauthlib.common import safe_string_equals
+            return safe_string_equals(verifier, correct_verifier)
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("validate_verifier")
+
+    def verify_request_token(self, token, request):
+        """Verify that the given OAuth1 request token is valid.
+
+        :param token: A request token string.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        This method is used only in AuthorizationEndpoint to check whether the
+        oauth_token given in the authorization URL is valid or not.
+        This request is not signed and thus similar ``validate_request_token``
+        method can not be used.
+
+        This method is used by
+
+        * AuthorizationEndpoint
+        """
+        raise self._subclass_must_implement("verify_request_token")
+
+    def verify_realms(self, token, realms, request):
+        """Verify authorized realms to see if they match those given to token.
+
+        :param token: An access token string.
+        :param realms: A list of realms the client attempts to access.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :returns: True or False
+
+        This prevents the list of authorized realms sent by the client during
+        the authorization step to be altered to include realms outside what
+        was bound with the request token.
+
+        Can be as simple as::
+
+            valid_realms = self.get_realms(token)
+            return all((r in valid_realms for r in realms))
+
+        This method is used by
+
+        * AuthorizationEndpoint
+        """
+        raise self._subclass_must_implement("verify_realms")
+
+    def save_access_token(self, token, request):
+        """Save an OAuth1 access token.
+
+        :param token: A dict with token credentials.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        The token dictionary will at minimum include
+
+        * ``oauth_token`` the access token string.
+        * ``oauth_token_secret`` the token specific secret used in signing.
+        * ``oauth_authorized_realms`` a space separated list of realms.
+
+        Client key can be obtained from ``request.client_key``.
+
+        The list of realms (not joined string) can be obtained from
+        ``request.realm``.
+
+        This method is used by
+
+        * AccessTokenEndpoint
+        """
+        raise self._subclass_must_implement("save_access_token")
+
+    def save_request_token(self, token, request):
+        """Save an OAuth1 request token.
+
+        :param token: A dict with token credentials.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        The token dictionary will at minimum include
+
+        * ``oauth_token`` the request token string.
+        * ``oauth_token_secret`` the token specific secret used in signing.
+        * ``oauth_callback_confirmed`` the string ``true``.
+
+        Client key can be obtained from ``request.client_key``.
+
+        This method is used by
+
+        * RequestTokenEndpoint
+        """
+        raise self._subclass_must_implement("save_request_token")
+
+    def save_verifier(self, token, verifier, request):
+        """Associate an authorization verifier with a request token.
+
+        :param token: A request token string.
+        :param verifier: A dictionary containing the oauth_verifier and
+                        oauth_token
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        We need to associate verifiers with tokens for validation during the
+        access token request.
+
+        Note that unlike save_x_token token here is the ``oauth_token`` token
+        string from the request token saved previously.
+
+        This method is used by
+
+        * AuthorizationEndpoint
+        """
+        raise self._subclass_must_implement("save_verifier")
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/signature.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/signature.py
new file mode 100644
index 0000000000000000000000000000000000000000..a27cb2e76fcae785b8672401458e04c96ab25cb6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/signature.py
@@ -0,0 +1,852 @@
+"""
+This module is an implementation of `section 3.4`_ of RFC 5849.
+
+**Usage**
+
+Steps for signing a request:
+
+1. Collect parameters from the request using ``collect_parameters``.
+2. Normalize those parameters using ``normalize_parameters``.
+3. Create the *base string URI* using ``base_string_uri``.
+4. Create the *signature base string* from the above three components
+   using ``signature_base_string``.
+5. Pass the *signature base string* and the client credentials to one of the
+   sign-with-client functions. The HMAC-based signing functions needs
+   client credentials with secrets. The RSA-based signing functions needs
+   client credentials with an RSA private key.
+
+To verify a request, pass the request and credentials to one of the verify
+functions. The HMAC-based signing functions needs the shared secrets. The
+RSA-based verify functions needs the RSA public key.
+
+**Scope**
+
+All of the functions in this module should be considered internal to OAuthLib,
+since they are not imported into the "oauthlib.oauth1" module. Programs using
+OAuthLib should not use directly invoke any of the functions in this module.
+
+**Deprecated functions**
+
+The "sign_" methods that are not "_with_client" have been deprecated. They may
+be removed in a future release. Since they are all internal functions, this
+should have no impact on properly behaving programs.
+
+.. _`section 3.4`: https://tools.ietf.org/html/rfc5849#section-3.4
+"""
+
+import binascii
+import hashlib
+import hmac
+import ipaddress
+import logging
+import urllib.parse as urlparse
+import warnings
+
+from oauthlib.common import extract_params, safe_string_equals, urldecode
+
+from . import utils
+import contextlib
+
+log = logging.getLogger(__name__)
+
+
+# ==== Common functions ==========================================
+
+def signature_base_string(
+        http_method: str,
+        base_str_uri: str,
+        normalized_encoded_request_parameters: str) -> str:
+    """
+    Construct the signature base string.
+
+    The *signature base string* is the value that is calculated and signed by
+    the client. It is also independently calculated by the server to verify
+    the signature, and therefore must produce the exact same value at both
+    ends or the signature won't verify.
+
+    The rules for calculating the *signature base string* are defined in
+    section 3.4.1.1`_ of RFC 5849.
+
+    .. _`section 3.4.1.1`: https://tools.ietf.org/html/rfc5849#section-3.4.1.1
+    """
+
+    # The signature base string is constructed by concatenating together,
+    # in order, the following HTTP request elements:
+
+    # 1.  The HTTP request method in uppercase.  For example: "HEAD",
+    #     "GET", "POST", etc.  If the request uses a custom HTTP method, it
+    #     MUST be encoded (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    base_string = utils.escape(http_method.upper())
+
+    # 2.  An "&" character (ASCII code 38).
+    base_string += '&'
+
+    # 3.  The base string URI from `Section 3.4.1.2`_, after being encoded
+    #     (`Section 3.6`_).
+    #
+    # .. _`Section 3.4.1.2`: https://tools.ietf.org/html/rfc5849#section-3.4.1.2
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    base_string += utils.escape(base_str_uri)
+
+    # 4.  An "&" character (ASCII code 38).
+    base_string += '&'
+
+    # 5.  The request parameters as normalized in `Section 3.4.1.3.2`_, after
+    #     being encoded (`Section 3.6`).
+    #
+    # .. _`Sec 3.4.1.3.2`: https://tools.ietf.org/html/rfc5849#section-3.4.1.3.2
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    base_string += utils.escape(normalized_encoded_request_parameters)
+
+    return base_string
+
+
+def base_string_uri(uri: str, host: str = None) -> str:
+    """
+    Calculates the _base string URI_.
+
+    The *base string URI* is one of the components that make up the
+     *signature base string*.
+
+    The ``host`` is optional. If provided, it is used to override any host and
+    port values in the ``uri``. The value for ``host`` is usually extracted from
+    the "Host" request header from the HTTP request. Its value may be just the
+    hostname, or the hostname followed by a colon and a TCP/IP port number
+    (hostname:port). If a value for the``host`` is provided but it does not
+    contain a port number, the default port number is used (i.e. if the ``uri``
+    contained a port number, it will be discarded).
+
+    The rules for calculating the *base string URI* are defined in
+    section 3.4.1.2`_ of RFC 5849.
+
+    .. _`section 3.4.1.2`: https://tools.ietf.org/html/rfc5849#section-3.4.1.2
+
+    :param uri: URI
+    :param host: hostname with optional port number, separated by a colon
+    :return: base string URI
+    """
+
+    if not isinstance(uri, str):
+        raise ValueError('uri must be a string.')
+
+    # FIXME: urlparse does not support unicode
+    output = urlparse.urlparse(uri)
+    scheme = output.scheme
+    hostname = output.hostname
+    port = output.port
+    path = output.path
+    params = output.params
+
+    # The scheme, authority, and path of the request resource URI `RFC3986`
+    # are included by constructing an "http" or "https" URI representing
+    # the request resource (without the query or fragment) as follows:
+    #
+    # .. _`RFC3986`: https://tools.ietf.org/html/rfc3986
+
+    if not scheme:
+        raise ValueError('missing scheme')
+
+    # Per `RFC 2616 section 5.1.2`_:
+    #
+    # Note that the absolute path cannot be empty; if none is present in
+    # the original URI, it MUST be given as "/" (the server root).
+    #
+    # .. _`RFC 2616 5.1.2`: https://tools.ietf.org/html/rfc2616#section-5.1.2
+    if not path:
+        path = '/'
+
+    # 1.  The scheme and host MUST be in lowercase.
+    scheme = scheme.lower()
+    # Note: if ``host`` is used, it will be converted to lowercase below
+    if hostname is not None:
+        hostname = hostname.lower()
+
+    # 2.  The host and port values MUST match the content of the HTTP
+    #     request "Host" header field.
+    if host is not None:
+        # NOTE: override value in uri with provided host
+        # Host argument is equal to netloc. It means it's missing scheme.
+        # Add it back, before parsing.
+
+        host = host.lower()
+        host = f"{scheme}://{host}"
+        output = urlparse.urlparse(host)
+        hostname = output.hostname
+        port = output.port
+
+    # 3.  The port MUST be included if it is not the default port for the
+    #     scheme, and MUST be excluded if it is the default.  Specifically,
+    #     the port MUST be excluded when making an HTTP request `RFC2616`_
+    #     to port 80 or when making an HTTPS request `RFC2818`_ to port 443.
+    #     All other non-default port numbers MUST be included.
+    #
+    # .. _`RFC2616`: https://tools.ietf.org/html/rfc2616
+    # .. _`RFC2818`: https://tools.ietf.org/html/rfc2818
+
+    if hostname is None:
+        raise ValueError('missing host')
+
+    # NOTE: Try guessing if we're dealing with IP or hostname
+    with contextlib.suppress(ValueError):
+        hostname = ipaddress.ip_address(hostname)
+
+
+    if isinstance(hostname, ipaddress.IPv6Address):
+        hostname = f"[{hostname}]"
+    elif isinstance(hostname, ipaddress.IPv4Address):
+        hostname = f"{hostname}"
+
+    if port is not None and not (0 < port <= 65535):
+        raise ValueError('port out of range')  # 16-bit unsigned ints
+    if (scheme, port) in (('http', 80), ('https', 443)):
+        netloc = hostname  # default port for scheme: exclude port num
+    elif port:
+        netloc = f"{hostname}:{port}"  # use hostname:port
+    else:
+        netloc = hostname
+
+    v = urlparse.urlunparse((scheme, netloc, path, params, '', ''))
+
+    # RFC 5849 does not specify which characters are encoded in the
+    # "base string URI", nor how they are encoded - which is very bad, since
+    # the signatures won't match if there are any differences. Fortunately,
+    # most URIs only use characters that are clearly not encoded (e.g. digits
+    # and A-Z, a-z), so have avoided any differences between implementations.
+    #
+    # The example from its section 3.4.1.2 illustrates that spaces in
+    # the path are percent encoded. But it provides no guidance as to what other
+    # characters (if any) must be encoded (nor how); nor if characters in the
+    # other components are to be encoded or not.
+    #
+    # This implementation **assumes** that **only** the space is percent-encoded
+    # and it is done to the entire value (not just to spaces in the path).
+    #
+    # This code may need to be changed if it is discovered that other characters
+    # are expected to be encoded.
+    #
+    # Note: the "base string URI" returned by this function will be encoded
+    # again before being concatenated into the "signature base string". So any
+    # spaces in the URI will actually appear in the "signature base string"
+    # as "%2520" (the "%20" further encoded according to section 3.6).
+
+    return v.replace(' ', '%20')
+
+
+def collect_parameters(uri_query='', body=None, headers=None,
+                       exclude_oauth_signature=True, with_realm=False):
+    """
+    Gather the request parameters from all the parameter sources.
+
+    This function is used to extract all the parameters, which are then passed
+    to ``normalize_parameters`` to produce one of the components that make up
+    the *signature base string*.
+
+    Parameters starting with `oauth_` will be unescaped.
+
+    Body parameters must be supplied as a dict, a list of 2-tuples, or a
+    form encoded query string.
+
+    Headers must be supplied as a dict.
+
+    The rules where the parameters must be sourced from are defined in
+    `section 3.4.1.3.1`_ of RFC 5849.
+
+    .. _`Sec 3.4.1.3.1`: https://tools.ietf.org/html/rfc5849#section-3.4.1.3.1
+    """
+    if body is None:
+        body = []
+    headers = headers or {}
+    params = []
+
+    # The parameters from the following sources are collected into a single
+    # list of name/value pairs:
+
+    # *  The query component of the HTTP request URI as defined by
+    #    `RFC3986, Section 3.4`_.  The query component is parsed into a list
+    #    of name/value pairs by treating it as an
+    #    "application/x-www-form-urlencoded" string, separating the names
+    #    and values and decoding them as defined by W3C.REC-html40-19980424
+    #    `W3C-HTML-4.0`_, Section 17.13.4.
+    #
+    # .. _`RFC3986, Sec 3.4`: https://tools.ietf.org/html/rfc3986#section-3.4
+    # .. _`W3C-HTML-4.0`: https://www.w3.org/TR/1998/REC-html40-19980424/
+    if uri_query:
+        params.extend(urldecode(uri_query))
+
+    # *  The OAuth HTTP "Authorization" header field (`Section 3.5.1`_) if
+    #    present.  The header's content is parsed into a list of name/value
+    #    pairs excluding the "realm" parameter if present.  The parameter
+    #    values are decoded as defined by `Section 3.5.1`_.
+    #
+    # .. _`Section 3.5.1`: https://tools.ietf.org/html/rfc5849#section-3.5.1
+    if headers:
+        headers_lower = {k.lower(): v for k, v in headers.items()}
+        authorization_header = headers_lower.get('authorization')
+        if authorization_header is not None:
+            params.extend([i for i in utils.parse_authorization_header(
+                authorization_header) if with_realm or i[0] != 'realm'])
+
+    # *  The HTTP request entity-body, but only if all of the following
+    #    conditions are met:
+    #     *  The entity-body is single-part.
+    #
+    #     *  The entity-body follows the encoding requirements of the
+    #        "application/x-www-form-urlencoded" content-type as defined by
+    #        W3C.REC-html40-19980424 `W3C-HTML-4.0`_.
+
+    #     *  The HTTP request entity-header includes the "Content-Type"
+    #        header field set to "application/x-www-form-urlencoded".
+    #
+    # .. _`W3C-HTML-4.0`: https://www.w3.org/TR/1998/REC-html40-19980424/
+
+    # TODO: enforce header param inclusion conditions
+    bodyparams = extract_params(body) or []
+    params.extend(bodyparams)
+
+    # ensure all oauth params are unescaped
+    unescaped_params = []
+    for k, v in params:
+        if k.startswith('oauth_'):
+            v = utils.unescape(v)
+        unescaped_params.append((k, v))
+
+    # The "oauth_signature" parameter MUST be excluded from the signature
+    # base string if present.
+    if exclude_oauth_signature:
+        unescaped_params = list(filter(lambda i: i[0] != 'oauth_signature',
+                                       unescaped_params))
+
+    return unescaped_params
+
+
+def normalize_parameters(params) -> str:
+    """
+    Calculate the normalized request parameters.
+
+    The *normalized request parameters* is one of the components that make up
+    the *signature base string*.
+
+    The rules for parameter normalization are defined in `section 3.4.1.3.2`_ of
+    RFC 5849.
+
+    .. _`Sec 3.4.1.3.2`: https://tools.ietf.org/html/rfc5849#section-3.4.1.3.2
+    """
+
+    # The parameters collected in `Section 3.4.1.3`_ are normalized into a
+    # single string as follows:
+    #
+    # .. _`Section 3.4.1.3`: https://tools.ietf.org/html/rfc5849#section-3.4.1.3
+
+    # 1.  First, the name and value of each parameter are encoded
+    #     (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    key_values = [(utils.escape(k), utils.escape(v)) for k, v in params]
+
+    # 2.  The parameters are sorted by name, using ascending byte value
+    #     ordering.  If two or more parameters share the same name, they
+    #     are sorted by their value.
+    key_values.sort()
+
+    # 3.  The name of each parameter is concatenated to its corresponding
+    #     value using an "=" character (ASCII code 61) as a separator, even
+    #     if the value is empty.
+    parameter_parts = ['{}={}'.format(k, v) for k, v in key_values]
+
+    # 4.  The sorted name/value pairs are concatenated together into a
+    #     single string by using an "&" character (ASCII code 38) as
+    #     separator.
+    return '&'.join(parameter_parts)
+
+
+# ==== Common functions for HMAC-based signature methods =========
+
+def _sign_hmac(hash_algorithm_name: str,
+               sig_base_str: str,
+               client_secret: str,
+               resource_owner_secret: str):
+    """
+    **HMAC-SHA256**
+
+    The "HMAC-SHA256" signature method uses the HMAC-SHA256 signature
+    algorithm as defined in `RFC4634`_::
+
+        digest = HMAC-SHA256 (key, text)
+
+    Per `section 3.4.2`_ of the spec.
+
+    .. _`RFC4634`: https://tools.ietf.org/html/rfc4634
+    .. _`section 3.4.2`: https://tools.ietf.org/html/rfc5849#section-3.4.2
+    """
+
+    # The HMAC-SHA256 function variables are used in following way:
+
+    # text is set to the value of the signature base string from
+    # `Section 3.4.1.1`_.
+    #
+    # .. _`Section 3.4.1.1`: https://tools.ietf.org/html/rfc5849#section-3.4.1.1
+    text = sig_base_str
+
+    # key is set to the concatenated values of:
+    # 1.  The client shared-secret, after being encoded (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    key = utils.escape(client_secret or '')
+
+    # 2.  An "&" character (ASCII code 38), which MUST be included
+    #     even when either secret is empty.
+    key += '&'
+
+    # 3.  The token shared-secret, after being encoded (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    key += utils.escape(resource_owner_secret or '')
+
+    # Get the hashing algorithm to use
+
+    m = {
+        'SHA-1': hashlib.sha1,
+        'SHA-256': hashlib.sha256,
+        'SHA-512': hashlib.sha512,
+    }
+    hash_alg = m[hash_algorithm_name]
+
+    # Calculate the signature
+
+    # FIXME: HMAC does not support unicode!
+    key_utf8 = key.encode('utf-8')
+    text_utf8 = text.encode('utf-8')
+    signature = hmac.new(key_utf8, text_utf8, hash_alg)
+
+    # digest  is used to set the value of the "oauth_signature" protocol
+    #         parameter, after the result octet string is base64-encoded
+    #         per `RFC2045, Section 6.8`.
+    #
+    # .. _`RFC2045, Sec 6.8`: https://tools.ietf.org/html/rfc2045#section-6.8
+    return binascii.b2a_base64(signature.digest())[:-1].decode('utf-8')
+
+
+def _verify_hmac(hash_algorithm_name: str,
+                 request,
+                 client_secret=None,
+                 resource_owner_secret=None):
+    """Verify a HMAC-SHA1 signature.
+
+    Per `section 3.4`_ of the spec.
+
+    .. _`section 3.4`: https://tools.ietf.org/html/rfc5849#section-3.4
+
+    To satisfy `RFC2616 section 5.2`_ item 1, the request argument's uri
+    attribute MUST be an absolute URI whose netloc part identifies the
+    origin server or gateway on which the resource resides. Any Host
+    item of the request argument's headers dict attribute will be
+    ignored.
+
+    .. _`RFC2616 section 5.2`: https://tools.ietf.org/html/rfc2616#section-5.2
+
+    """
+    norm_params = normalize_parameters(request.params)
+    bs_uri = base_string_uri(request.uri)
+    sig_base_str = signature_base_string(request.http_method, bs_uri,
+                                         norm_params)
+    signature = _sign_hmac(hash_algorithm_name, sig_base_str,
+                           client_secret, resource_owner_secret)
+    match = safe_string_equals(signature, request.signature)
+    if not match:
+        log.debug('Verify HMAC failed: signature base string: %s', sig_base_str)
+    return match
+
+
+# ==== HMAC-SHA1 =================================================
+
+def sign_hmac_sha1_with_client(sig_base_str, client):
+    return _sign_hmac('SHA-1', sig_base_str,
+                      client.client_secret, client.resource_owner_secret)
+
+
+def verify_hmac_sha1(request, client_secret=None, resource_owner_secret=None):
+    return _verify_hmac('SHA-1', request, client_secret, resource_owner_secret)
+
+
+def sign_hmac_sha1(base_string, client_secret, resource_owner_secret):
+    """
+    Deprecated function for calculating a HMAC-SHA1 signature.
+
+    This function has been replaced by invoking ``sign_hmac`` with "SHA-1"
+    as the hash algorithm name.
+
+    This function was invoked by sign_hmac_sha1_with_client and
+    test_signatures.py, but does any application invoke it directly? If not,
+    it can be removed.
+    """
+    warnings.warn('use sign_hmac_sha1_with_client instead of sign_hmac_sha1',
+                  DeprecationWarning)
+
+    # For some unknown reason, the original implementation assumed base_string
+    # could either be bytes or str. The signature base string calculating
+    # function always returned a str, so the new ``sign_rsa`` only expects that.
+
+    base_string = base_string.decode('ascii') \
+        if isinstance(base_string, bytes) else base_string
+
+    return _sign_hmac('SHA-1', base_string,
+                      client_secret, resource_owner_secret)
+
+
+# ==== HMAC-SHA256 ===============================================
+
+def sign_hmac_sha256_with_client(sig_base_str, client):
+    return _sign_hmac('SHA-256', sig_base_str,
+                      client.client_secret, client.resource_owner_secret)
+
+
+def verify_hmac_sha256(request, client_secret=None, resource_owner_secret=None):
+    return _verify_hmac('SHA-256', request,
+                        client_secret, resource_owner_secret)
+
+
+def sign_hmac_sha256(base_string, client_secret, resource_owner_secret):
+    """
+    Deprecated function for calculating a HMAC-SHA256 signature.
+
+    This function has been replaced by invoking ``sign_hmac`` with "SHA-256"
+    as the hash algorithm name.
+
+    This function was invoked by sign_hmac_sha256_with_client and
+    test_signatures.py, but does any application invoke it directly? If not,
+    it can be removed.
+    """
+    warnings.warn(
+        'use sign_hmac_sha256_with_client instead of sign_hmac_sha256',
+        DeprecationWarning)
+
+    # For some unknown reason, the original implementation assumed base_string
+    # could either be bytes or str. The signature base string calculating
+    # function always returned a str, so the new ``sign_rsa`` only expects that.
+
+    base_string = base_string.decode('ascii') \
+        if isinstance(base_string, bytes) else base_string
+
+    return _sign_hmac('SHA-256', base_string,
+                      client_secret, resource_owner_secret)
+
+
+# ==== HMAC-SHA512 ===============================================
+
+def sign_hmac_sha512_with_client(sig_base_str: str,
+                                 client):
+    return _sign_hmac('SHA-512', sig_base_str,
+                      client.client_secret, client.resource_owner_secret)
+
+
+def verify_hmac_sha512(request,
+                       client_secret: str = None,
+                       resource_owner_secret: str = None):
+    return _verify_hmac('SHA-512', request,
+                        client_secret, resource_owner_secret)
+
+
+# ==== Common functions for RSA-based signature methods ==========
+
+_jwt_rsa = {}  # cache of RSA-hash implementations from PyJWT jwt.algorithms
+
+
+def _get_jwt_rsa_algorithm(hash_algorithm_name: str):
+    """
+    Obtains an RSAAlgorithm object that implements RSA with the hash algorithm.
+
+    This method maintains the ``_jwt_rsa`` cache.
+
+    Returns a jwt.algorithm.RSAAlgorithm.
+    """
+    if hash_algorithm_name in _jwt_rsa:
+        # Found in cache: return it
+        return _jwt_rsa[hash_algorithm_name]
+    else:
+        # Not in cache: instantiate a new RSAAlgorithm
+
+        # PyJWT has some nice pycrypto/cryptography abstractions
+        import jwt.algorithms as jwt_algorithms  # noqa: PLC0415
+        m = {
+            'SHA-1': jwt_algorithms.hashes.SHA1,
+            'SHA-256': jwt_algorithms.hashes.SHA256,
+            'SHA-512': jwt_algorithms.hashes.SHA512,
+        }
+        v = jwt_algorithms.RSAAlgorithm(m[hash_algorithm_name])
+
+        _jwt_rsa[hash_algorithm_name] = v  # populate cache
+
+        return v
+
+
+def _prepare_key_plus(alg, keystr):
+    """
+    Prepare a PEM encoded key (public or private), by invoking the `prepare_key`
+    method on alg with the keystr.
+
+    The keystr should be a string or bytes.  If the keystr is bytes, it is
+    decoded as UTF-8 before being passed to prepare_key. Otherwise, it
+    is passed directly.
+    """
+    if isinstance(keystr, bytes):
+        keystr = keystr.decode('utf-8')
+    return alg.prepare_key(keystr)
+
+
+def _sign_rsa(hash_algorithm_name: str,
+              sig_base_str: str,
+              rsa_private_key: str):
+    """
+    Calculate the signature for an RSA-based signature method.
+
+    The ``alg`` is used to calculate the digest over the signature base string.
+    For the "RSA_SHA1" signature method, the alg must be SHA-1. While OAuth 1.0a
+    only defines the RSA-SHA1 signature method, this function can be used for
+    other non-standard signature methods that only differ from RSA-SHA1 by the
+    digest algorithm.
+
+    Signing for the RSA-SHA1 signature method is defined in
+    `section 3.4.3`_ of RFC 5849.
+
+    The RSASSA-PKCS1-v1_5 signature algorithm used defined by
+    `RFC3447, Section 8.2`_ (also known as PKCS#1), with the `alg` as the
+    hash function for EMSA-PKCS1-v1_5.  To
+    use this method, the client MUST have established client credentials
+    with the server that included its RSA public key (in a manner that is
+    beyond the scope of this specification).
+
+    .. _`section 3.4.3`: https://tools.ietf.org/html/rfc5849#section-3.4.3
+    .. _`RFC3447, Section 8.2`: https://tools.ietf.org/html/rfc3447#section-8.2
+    """
+
+    # Get the implementation of RSA-hash
+
+    alg = _get_jwt_rsa_algorithm(hash_algorithm_name)
+
+    # Check private key
+
+    if not rsa_private_key:
+        raise ValueError('rsa_private_key required for RSA with ' +
+                         alg.hash_alg.name + ' signature method')
+
+    # Convert the "signature base string" into a sequence of bytes (M)
+    #
+    # The signature base string, by definition, only contain printable US-ASCII
+    # characters. So encoding it as 'ascii' will always work. It will raise a
+    # ``UnicodeError`` if it can't encode the value, which will never happen
+    # if the signature base string was created correctly. Therefore, using
+    # 'ascii' encoding provides an extra level of error checking.
+
+    m = sig_base_str.encode('ascii')
+
+    # Perform signing: S = RSASSA-PKCS1-V1_5-SIGN (K, M)
+
+    key = _prepare_key_plus(alg, rsa_private_key)
+    s = alg.sign(m, key)
+
+    # base64-encoded per RFC2045 section 6.8.
+    #
+    # 1. While b2a_base64 implements base64 defined by RFC 3548. As used here,
+    #    it is the same as base64 defined by RFC 2045.
+    # 2. b2a_base64 includes a "\n" at the end of its result ([:-1] removes it)
+    # 3. b2a_base64 produces a binary string. Use decode to produce a str.
+    #    It should only contain only printable US-ASCII characters.
+
+    return binascii.b2a_base64(s)[:-1].decode('ascii')
+
+
+def _verify_rsa(hash_algorithm_name: str,
+                request,
+                rsa_public_key: str):
+    """
+    Verify a base64 encoded signature for a RSA-based signature method.
+
+    The ``alg`` is used to calculate the digest over the signature base string.
+    For the "RSA_SHA1" signature method, the alg must be SHA-1. While OAuth 1.0a
+    only defines the RSA-SHA1 signature method, this function can be used for
+    other non-standard signature methods that only differ from RSA-SHA1 by the
+    digest algorithm.
+
+    Verification for the RSA-SHA1 signature method is defined in
+    `section 3.4.3`_ of RFC 5849.
+
+    .. _`section 3.4.3`: https://tools.ietf.org/html/rfc5849#section-3.4.3
+
+        To satisfy `RFC2616 section 5.2`_ item 1, the request argument's uri
+        attribute MUST be an absolute URI whose netloc part identifies the
+        origin server or gateway on which the resource resides. Any Host
+        item of the request argument's headers dict attribute will be
+        ignored.
+
+        .. _`RFC2616 Sec 5.2`: https://tools.ietf.org/html/rfc2616#section-5.2
+    """
+
+    try:
+        # Calculate the *signature base string* of the actual received request
+
+        norm_params = normalize_parameters(request.params)
+        bs_uri = base_string_uri(request.uri)
+        sig_base_str = signature_base_string(
+            request.http_method, bs_uri, norm_params)
+
+        # Obtain the signature that was received in the request
+
+        sig = binascii.a2b_base64(request.signature.encode('ascii'))
+
+        # Get the implementation of RSA-with-hash algorithm to use
+
+        alg = _get_jwt_rsa_algorithm(hash_algorithm_name)
+
+        # Verify the received signature was produced by the private key
+        # corresponding to the `rsa_public_key`, signing exact same
+        # *signature base string*.
+        #
+        #     RSASSA-PKCS1-V1_5-VERIFY ((n, e), M, S)
+
+        key = _prepare_key_plus(alg, rsa_public_key)
+
+        # The signature base string only contain printable US-ASCII characters.
+        # The ``encode`` method with the default "strict" error handling will
+        # raise a ``UnicodeError`` if it can't encode the value. So using
+        # "ascii" will always work.
+
+        verify_ok = alg.verify(sig_base_str.encode('ascii'), key, sig)
+
+        if not verify_ok:
+            log.debug('Verify failed: RSA with ' + alg.hash_alg.name +
+                      ': signature base string=%s' + sig_base_str)
+        return verify_ok
+
+    except UnicodeError:
+        # A properly encoded signature will only contain printable US-ASCII
+        # characters. The ``encode`` method with the default "strict" error
+        # handling will raise a ``UnicodeError`` if it can't decode the value.
+        # So using "ascii" will work with all valid signatures. But an
+        # incorrectly or maliciously produced signature could contain other
+        # bytes.
+        #
+        # This implementation treats that situation as equivalent to the
+        # signature verification having failed.
+        #
+        # Note: simply changing the encode to use 'utf-8' will not remove this
+        # case, since an incorrect or malicious request can contain bytes which
+        # are invalid as UTF-8.
+        return False
+
+
+# ==== RSA-SHA1 ==================================================
+
+def sign_rsa_sha1_with_client(sig_base_str, client):
+    # For some reason, this function originally accepts both str and bytes.
+    # This behaviour is preserved here. But won't be done for the newer
+    # sign_rsa_sha256_with_client and sign_rsa_sha512_with_client functions,
+    # which will only accept strings. The function to calculate a
+    # "signature base string" always produces a string, so it is not clear
+    # why support for bytes would ever be needed.
+    sig_base_str = sig_base_str.decode('ascii')\
+        if isinstance(sig_base_str, bytes) else sig_base_str
+
+    return _sign_rsa('SHA-1', sig_base_str, client.rsa_key)
+
+
+def verify_rsa_sha1(request, rsa_public_key: str):
+    return _verify_rsa('SHA-1', request, rsa_public_key)
+
+
+def sign_rsa_sha1(base_string, rsa_private_key):
+    """
+    Deprecated function for calculating a RSA-SHA1 signature.
+
+    This function has been replaced by invoking ``sign_rsa`` with "SHA-1"
+    as the hash algorithm name.
+
+    This function was invoked by sign_rsa_sha1_with_client and
+    test_signatures.py, but does any application invoke it directly? If not,
+    it can be removed.
+    """
+    warnings.warn('use _sign_rsa("SHA-1", ...) instead of sign_rsa_sha1',
+                  DeprecationWarning)
+
+    if isinstance(base_string, bytes):
+        base_string = base_string.decode('ascii')
+
+    return _sign_rsa('SHA-1', base_string, rsa_private_key)
+
+
+# ==== RSA-SHA256 ================================================
+
+def sign_rsa_sha256_with_client(sig_base_str: str, client):
+    return _sign_rsa('SHA-256', sig_base_str, client.rsa_key)
+
+
+def verify_rsa_sha256(request, rsa_public_key: str):
+    return _verify_rsa('SHA-256', request, rsa_public_key)
+
+
+# ==== RSA-SHA512 ================================================
+
+def sign_rsa_sha512_with_client(sig_base_str: str, client):
+    return _sign_rsa('SHA-512', sig_base_str, client.rsa_key)
+
+
+def verify_rsa_sha512(request, rsa_public_key: str):
+    return _verify_rsa('SHA-512', request, rsa_public_key)
+
+
+# ==== PLAINTEXT =================================================
+
+def sign_plaintext_with_client(_signature_base_string, client):
+    # _signature_base_string is not used because the signature with PLAINTEXT
+    # is just the secret: it isn't a real signature.
+    return sign_plaintext(client.client_secret, client.resource_owner_secret)
+
+
+def sign_plaintext(client_secret, resource_owner_secret):
+    """Sign a request using plaintext.
+
+    Per `section 3.4.4`_ of the spec.
+
+    The "PLAINTEXT" method does not employ a signature algorithm.  It
+    MUST be used with a transport-layer mechanism such as TLS or SSL (or
+    sent over a secure channel with equivalent protections).  It does not
+    utilize the signature base string or the "oauth_timestamp" and
+    "oauth_nonce" parameters.
+
+    .. _`section 3.4.4`: https://tools.ietf.org/html/rfc5849#section-3.4.4
+
+    """
+
+    # The "oauth_signature" protocol parameter is set to the concatenated
+    # value of:
+
+    # 1.  The client shared-secret, after being encoded (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    signature = utils.escape(client_secret or '')
+
+    # 2.  An "&" character (ASCII code 38), which MUST be included even
+    #     when either secret is empty.
+    signature += '&'
+
+    # 3.  The token shared-secret, after being encoded (`Section 3.6`_).
+    #
+    # .. _`Section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+    signature += utils.escape(resource_owner_secret or '')
+
+    return signature
+
+
+def verify_plaintext(request, client_secret=None, resource_owner_secret=None):
+    """Verify a PLAINTEXT signature.
+
+    Per `section 3.4`_ of the spec.
+
+    .. _`section 3.4`: https://tools.ietf.org/html/rfc5849#section-3.4
+    """
+    signature = sign_plaintext(client_secret, resource_owner_secret)
+    match = safe_string_equals(signature, request.signature)
+    if not match:
+        log.debug('Verify PLAINTEXT failed')
+    return match
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/utils.py b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..0915105bcbd0a0d392c68ff84ee0d1cdf80119ca
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth1/rfc5849/utils.py
@@ -0,0 +1,84 @@
+"""
+oauthlib.utils
+~~~~~~~~~~~~~~
+
+This module contains utility methods used by various parts of the OAuth
+spec.
+"""
+import urllib.request as urllib2
+
+from oauthlib.common import quote, unquote
+
+UNICODE_ASCII_CHARACTER_SET = ('abcdefghijklmnopqrstuvwxyz'
+                               'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
+                               '0123456789')
+
+
+def filter_params(target):
+    """Decorator which filters params to remove non-oauth_* parameters
+
+    Assumes the decorated method takes a params dict or list of tuples as its
+    first argument.
+    """
+    def wrapper(params, *args, **kwargs):
+        params = filter_oauth_params(params)
+        return target(params, *args, **kwargs)
+
+    wrapper.__doc__ = target.__doc__
+    return wrapper
+
+
+def filter_oauth_params(params):
+    """Removes all non oauth parameters from a dict or a list of params."""
+    def is_oauth(kv):
+        return kv[0].startswith('oauth_')
+    if isinstance(params, dict):
+        return list(filter(is_oauth, list(params.items())))
+    else:
+        return list(filter(is_oauth, params))
+
+
+def escape(u):
+    """Escape a unicode string in an OAuth-compatible fashion.
+
+    Per `section 3.6`_ of the spec.
+
+    .. _`section 3.6`: https://tools.ietf.org/html/rfc5849#section-3.6
+
+    """
+    if not isinstance(u, str):
+        raise ValueError('Only unicode objects are escapable. ' +
+                         'Got {!r} of type {}.'.format(u, type(u)))
+    # Letters, digits, and the characters '_.-' are already treated as safe
+    # by urllib.quote(). We need to add '~' to fully support rfc5849.
+    return quote(u, safe=b'~')
+
+
+def unescape(u):
+    if not isinstance(u, str):
+        raise ValueError('Only unicode objects are unescapable.')
+    return unquote(u)
+
+
+def parse_keqv_list(l):  # noqa: E741
+    """A unicode-safe version of urllib2.parse_keqv_list"""
+    # With Python 2.6, parse_http_list handles unicode fine
+    return urllib2.parse_keqv_list(l)
+
+
+def parse_http_list(u):
+    """A unicode-safe version of urllib2.parse_http_list"""
+    # With Python 2.6, parse_http_list handles unicode fine
+    return urllib2.parse_http_list(u)
+
+
+def parse_authorization_header(authorization_header):
+    """Parse an OAuth authorization header into a list of 2-tuples"""
+    auth_scheme = 'OAuth '.lower()
+    if authorization_header[:len(auth_scheme)].lower().startswith(auth_scheme):
+        items = parse_http_list(authorization_header[len(auth_scheme):])
+        try:
+            return list(parse_keqv_list(items).items())
+        except (IndexError, ValueError):
+            pass
+    raise ValueError('Malformed authorization header')
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..3bb51021741f2a0acc423c4a61b3061814ce7b32
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/__init__.py
@@ -0,0 +1,70 @@
+"""
+oauthlib.oauth2
+~~~~~~~~~~~~~~
+
+This module is a wrapper for the most recent implementation of OAuth 2.0 Client
+and Server classes.
+"""
+
+from .rfc6749.clients import (
+    BackendApplicationClient,
+    Client,
+    LegacyApplicationClient,
+    MobileApplicationClient,
+    ServiceApplicationClient,
+    WebApplicationClient,
+)
+from .rfc6749.endpoints import (
+    AuthorizationEndpoint,
+    BackendApplicationServer,
+    IntrospectEndpoint,
+    LegacyApplicationServer,
+    MetadataEndpoint,
+    MobileApplicationServer,
+    ResourceEndpoint,
+    RevocationEndpoint,
+    Server,
+    TokenEndpoint,
+    WebApplicationServer,
+)
+from .rfc6749.errors import (
+    AccessDeniedError,
+    FatalClientError,
+    InsecureTransportError,
+    InvalidClientError,
+    InvalidClientIdError,
+    InvalidGrantError,
+    InvalidRedirectURIError,
+    InvalidRequestError,
+    InvalidRequestFatalError,
+    InvalidScopeError,
+    MismatchingRedirectURIError,
+    MismatchingStateError,
+    MissingClientIdError,
+    MissingCodeError,
+    MissingRedirectURIError,
+    MissingResponseTypeError,
+    MissingTokenError,
+    MissingTokenTypeError,
+    OAuth2Error,
+    ServerError,
+    TemporarilyUnavailableError,
+    TokenExpiredError,
+    UnauthorizedClientError,
+    UnsupportedGrantTypeError,
+    UnsupportedResponseTypeError,
+    UnsupportedTokenTypeError,
+)
+from .rfc6749.grant_types import (
+    AuthorizationCodeGrant,
+    ClientCredentialsGrant,
+    ImplicitGrant,
+    RefreshTokenGrant,
+    ResourceOwnerPasswordCredentialsGrant,
+)
+from .rfc6749.request_validator import RequestValidator
+from .rfc6749.tokens import BearerToken, OAuth2Token
+from .rfc6749.utils import is_secure_transport
+from .rfc8628.clients import DeviceClient
+from oauthlib.oauth2.rfc8628.endpoints import DeviceAuthorizationEndpoint, DeviceApplicationServer
+from oauthlib.oauth2.rfc8628.grant_types import DeviceCodeGrant
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@@ -0,0 +1,16 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import functools
+import logging
+
+from .endpoints.base import BaseEndpoint, catch_errors_and_unavailability
+from .errors import (
+    FatalClientError, OAuth2Error, ServerError, TemporarilyUnavailableError,
+)
+
+log = logging.getLogger(__name__)
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/__init__.py
@@ -0,0 +1,14 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming OAuth 2.0 RFC6749.
+"""
+from .backend_application import BackendApplicationClient
+from .base import AUTH_HEADER, BODY, URI_QUERY, Client
+from .legacy_application import LegacyApplicationClient
+from .mobile_application import MobileApplicationClient
+from .service_application import ServiceApplicationClient
+from .web_application import WebApplicationClient
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/backend_application.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/backend_application.py
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index 0000000000000000000000000000000000000000..e11e8fae380fc88784c0d429488b67aac3447dd3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/backend_application.py
@@ -0,0 +1,74 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+from ..parameters import prepare_token_request
+from .base import Client
+
+
+class BackendApplicationClient(Client):
+
+    """A public client utilizing the client credentials grant workflow.
+
+    The client can request an access token using only its client
+    credentials (or other supported means of authentication) when the
+    client is requesting access to the protected resources under its
+    control, or those of another resource owner which has been previously
+    arranged with the authorization server (the method of which is beyond
+    the scope of this specification).
+
+    The client credentials grant type MUST only be used by confidential
+    clients.
+
+    Since the client authentication is used as the authorization grant,
+    no additional authorization request is needed.
+    """
+
+    grant_type = 'client_credentials'
+
+    def prepare_request_body(self, body='', scope=None,
+                             include_client_id=False, **kwargs):
+        """Add the client credentials to the request body.
+
+        The client makes a request to the token endpoint by adding the
+        following parameters using the "application/x-www-form-urlencoded"
+        format per `Appendix B`_ in the HTTP request entity-body:
+
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+        :param scope:   The scope of the access request as described by
+                        `Section 3.3`_.
+
+        :param include_client_id: `True` to send the `client_id` in the
+                                  body of the upstream request. This is required
+                                  if the client is not authenticating with the
+                                  authorization server as described in
+                                  `Section 3.2.1`_. False otherwise (default).
+        :type include_client_id: Boolean
+
+        :param kwargs:  Extra credentials to include in the token request.
+
+        The client MUST authenticate with the authorization server as
+        described in `Section 3.2.1`_.
+
+        The prepared body will include all provided credentials as well as
+        the ``grant_type`` parameter set to ``client_credentials``::
+
+            >>> from oauthlib.oauth2 import BackendApplicationClient
+            >>> client = BackendApplicationClient('your_id')
+            >>> client.prepare_request_body(scope=['hello', 'world'])
+            'grant_type=client_credentials&scope=hello+world'
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 3.2.1`: https://tools.ietf.org/html/rfc6749#section-3.2.1
+        """
+        kwargs['client_id'] = self.client_id
+        kwargs['include_client_id'] = include_client_id
+        scope = self.scope if scope is None else scope
+        return prepare_token_request(self.grant_type, body=body,
+                                     scope=scope, **kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/base.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/base.py
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index 0000000000000000000000000000000000000000..17f833d236cb0f1ca7a4dd85f661b2e6be6b087e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/base.py
@@ -0,0 +1,597 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming OAuth 2.0 RFC6749.
+"""
+import base64
+import hashlib
+import time
+import warnings
+
+from oauthlib.common import UNICODE_ASCII_CHARACTER_SET, generate_token
+from oauthlib.oauth2.rfc6749 import tokens
+from oauthlib.oauth2.rfc6749.errors import (
+    InsecureTransportError, TokenExpiredError,
+)
+from oauthlib.oauth2.rfc6749.parameters import (
+    parse_expires,
+    parse_token_response, prepare_token_request,
+    prepare_token_revocation_request,
+)
+from oauthlib.oauth2.rfc6749.utils import is_secure_transport
+
+AUTH_HEADER = 'auth_header'
+URI_QUERY = 'query'
+BODY = 'body'
+
+FORM_ENC_HEADERS = {
+    'Content-Type': 'application/x-www-form-urlencoded'
+}
+
+
+class Client:
+    """Base OAuth2 client responsible for access token management.
+
+    This class also acts as a generic interface providing methods common to all
+    client types such as ``prepare_authorization_request`` and
+    ``prepare_token_revocation_request``. The ``prepare_x_request`` methods are
+    the recommended way of interacting with clients (as opposed to the abstract
+    prepare uri/body/etc methods). They are recommended over the older set
+    because they are easier to use (more consistent) and add a few additional
+    security checks, such as HTTPS and state checking.
+
+    Some of these methods require further implementation only provided by the
+    specific purpose clients such as
+    :py:class:`oauthlib.oauth2.MobileApplicationClient` and thus you should always
+    seek to use the client class matching the OAuth workflow you need. For
+    Python, this is usually :py:class:`oauthlib.oauth2.WebApplicationClient`.
+
+    """
+    refresh_token_key = 'refresh_token'
+
+    def __init__(self, client_id,
+                 default_token_placement=AUTH_HEADER,
+                 token_type='Bearer',
+                 access_token=None,
+                 refresh_token=None,
+                 mac_key=None,
+                 mac_algorithm=None,
+                 token=None,
+                 scope=None,
+                 state=None,
+                 redirect_url=None,
+                 state_generator=generate_token,
+                 code_verifier=None,
+                 code_challenge=None,
+                 code_challenge_method=None,
+                 **kwargs):
+        """Initialize a client with commonly used attributes.
+
+        :param client_id: Client identifier given by the OAuth provider upon
+        registration.
+
+        :param default_token_placement: Tokens can be supplied in the Authorization
+        header (default), the URL query component (``query``) or the request
+        body (``body``).
+
+        :param token_type: OAuth 2 token type. Defaults to Bearer. Change this
+        if you specify the ``access_token`` parameter and know it is of a
+        different token type, such as a MAC, JWT or SAML token. Can
+        also be supplied as ``token_type`` inside the ``token`` dict parameter.
+
+        :param access_token: An access token (string) used to authenticate
+        requests to protected resources. Can also be supplied inside the
+        ``token`` dict parameter.
+
+        :param refresh_token: A refresh token (string) used to refresh expired
+        tokens. Can also be supplied inside the ``token`` dict parameter.
+
+        :param mac_key: Encryption key used with MAC tokens.
+
+        :param mac_algorithm:  Hashing algorithm for MAC tokens.
+
+        :param token: A dict of token attributes such as ``access_token``,
+        ``token_type`` and ``expires_at``.
+
+        :param scope: A list of default scopes to request authorization for.
+
+        :param state: A CSRF protection string used during authorization.
+
+        :param redirect_url: The redirection endpoint on the client side to which
+        the user returns after authorization.
+
+        :param state_generator: A no argument state generation callable. Defaults
+        to :py:meth:`oauthlib.common.generate_token`.
+
+        :param code_verifier: PKCE parameter. A cryptographically random string that is used to correlate the
+        authorization request to the token request.
+
+        :param code_challenge: PKCE parameter. A challenge derived from the code verifier that is sent in the
+        authorization request, to be verified against later.
+
+        :param code_challenge_method: PKCE parameter. A method that was used to derive code challenge.
+        Defaults to "plain" if not present in the request.
+        """
+
+        self.client_id = client_id
+        self.default_token_placement = default_token_placement
+        self.token_type = token_type
+        self.access_token = access_token
+        self.refresh_token = refresh_token
+        self.mac_key = mac_key
+        self.mac_algorithm = mac_algorithm
+        self.token = token or {}
+        self.scope = scope
+        self.state_generator = state_generator
+        self.state = state
+        self.redirect_url = redirect_url
+        self.code_verifier = code_verifier
+        self.code_challenge = code_challenge
+        self.code_challenge_method = code_challenge_method
+        self.code = None
+        self.expires_in = None
+        self._expires_at = None
+        self.populate_token_attributes(self.token)
+
+    @property
+    def token_types(self):
+        """Supported token types and their respective methods
+
+        Additional tokens can be supported by extending this dictionary.
+
+        The Bearer token spec is stable and safe to use.
+
+        The MAC token spec is not yet stable and support for MAC tokens
+        is experimental and currently matching version 00 of the spec.
+        """
+        return {
+            'Bearer': self._add_bearer_token,
+            'MAC': self._add_mac_token
+        }
+
+    def prepare_request_uri(self, *args, **kwargs):
+        """Abstract method used to create request URIs."""
+        raise NotImplementedError("Must be implemented by inheriting classes.")
+
+    def prepare_request_body(self, *args, **kwargs):
+        """Abstract method used to create request bodies."""
+        raise NotImplementedError("Must be implemented by inheriting classes.")
+
+    def parse_request_uri_response(self, *args, **kwargs):
+        """Abstract method used to parse redirection responses."""
+        raise NotImplementedError("Must be implemented by inheriting classes.")
+
+    def add_token(self, uri, http_method='GET', body=None, headers=None,
+                  token_placement=None, **kwargs):
+        """Add token to the request uri, body or authorization header.
+
+        The access token type provides the client with the information
+        required to successfully utilize the access token to make a protected
+        resource request (along with type-specific attributes).  The client
+        MUST NOT use an access token if it does not understand the token
+        type.
+
+        For example, the "bearer" token type defined in
+        [`I-D.ietf-oauth-v2-bearer`_] is utilized by simply including the access
+        token string in the request:
+
+        .. code-block:: http
+
+            GET /resource/1 HTTP/1.1
+            Host: example.com
+            Authorization: Bearer mF_9.B5f-4.1JqM
+
+        while the "mac" token type defined in [`I-D.ietf-oauth-v2-http-mac`_] is
+        utilized by issuing a MAC key together with the access token which is
+        used to sign certain components of the HTTP requests:
+
+        .. code-block:: http
+
+            GET /resource/1 HTTP/1.1
+            Host: example.com
+            Authorization: MAC id="h480djs93hd8",
+                                nonce="274312:dj83hs9s",
+                                mac="kDZvddkndxvhGRXZhvuDjEWhGeE="
+
+        .. _`I-D.ietf-oauth-v2-bearer`: https://tools.ietf.org/html/rfc6749#section-12.2
+        .. _`I-D.ietf-oauth-v2-http-mac`: https://tools.ietf.org/html/rfc6749#section-12.2
+        """
+        if not is_secure_transport(uri):
+            raise InsecureTransportError()
+
+        token_placement = token_placement or self.default_token_placement
+
+        case_insensitive_token_types = {
+            k.lower(): v for k, v in self.token_types.items()}
+        if self.token_type.lower() not in case_insensitive_token_types:
+            raise ValueError("Unsupported token type: %s" % self.token_type)
+
+        if not (self.access_token or self.token.get('access_token')):
+            raise ValueError("Missing access token.")
+
+        if self._expires_at and self._expires_at < time.time():
+            raise TokenExpiredError()
+
+        return case_insensitive_token_types[self.token_type.lower()](uri, http_method, body,
+                                                                     headers, token_placement, **kwargs)
+
+    def prepare_authorization_request(self, authorization_url, state=None,
+                                      redirect_url=None, scope=None, **kwargs):
+        """Prepare the authorization request.
+
+        This is the first step in many OAuth flows in which the user is
+        redirected to a certain authorization URL. This method adds
+        required parameters to the authorization URL.
+
+        :param authorization_url: Provider authorization endpoint URL.
+        :param state: CSRF protection string. Will be automatically created if
+            not provided. The generated state is available via the ``state``
+            attribute. Clients should verify that the state is unchanged and
+            present in the authorization response. This verification is done
+            automatically if using the ``authorization_response`` parameter
+            with ``prepare_token_request``.
+        :param redirect_url: Redirect URL to which the user will be returned
+            after authorization. Must be provided unless previously setup with
+            the provider. If provided then it must also be provided in the
+            token request.
+        :param scope: List of scopes to request. Must be equal to
+            or a subset of the scopes granted when obtaining the refresh
+            token. If none is provided, the ones provided in the constructor are
+            used.
+        :param kwargs: Additional parameters to included in the request.
+        :returns: The prepared request tuple with (url, headers, body).
+        """
+        if not is_secure_transport(authorization_url):
+            raise InsecureTransportError()
+
+        self.state = state or self.state_generator()
+        self.redirect_url = redirect_url or self.redirect_url
+        # do not assign scope to self automatically anymore
+        scope = self.scope if scope is None else scope
+        auth_url = self.prepare_request_uri(
+            authorization_url, redirect_uri=self.redirect_url,
+            scope=scope, state=self.state, **kwargs)
+        return auth_url, FORM_ENC_HEADERS, ''
+
+    def prepare_token_request(self, token_url, authorization_response=None,
+                              redirect_url=None, state=None, body='', **kwargs):
+        """Prepare a token creation request.
+
+        Note that these requests usually require client authentication, either
+        by including client_id or a set of provider specific authentication
+        credentials.
+
+        :param token_url: Provider token creation endpoint URL.
+        :param authorization_response: The full redirection URL string, i.e.
+            the location to which the user was redirected after successful
+            authorization. Used to mine credentials needed to obtain a token
+            in this step, such as authorization code.
+        :param redirect_url: The redirect_url supplied with the authorization
+            request (if there was one).
+        :param state:
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+        :param kwargs: Additional parameters to included in the request.
+        :returns: The prepared request tuple with (url, headers, body).
+        """
+        if not is_secure_transport(token_url):
+            raise InsecureTransportError()
+
+        state = state or self.state
+        if authorization_response:
+            self.parse_request_uri_response(
+                authorization_response, state=state)
+        self.redirect_url = redirect_url or self.redirect_url
+        body = self.prepare_request_body(body=body,
+                                         redirect_uri=self.redirect_url, **kwargs)
+
+        return token_url, FORM_ENC_HEADERS, body
+
+    def prepare_refresh_token_request(self, token_url, refresh_token=None,
+                                      body='', scope=None, **kwargs):
+        """Prepare an access token refresh request.
+
+        Expired access tokens can be replaced by new access tokens without
+        going through the OAuth dance if the client obtained a refresh token.
+        This refresh token and authentication credentials can be used to
+        obtain a new access token, and possibly a new refresh token.
+
+        :param token_url: Provider token refresh endpoint URL.
+        :param refresh_token: Refresh token string.
+        :param body: Existing request body (URL encoded string) to embed parameters
+            into. This may contain extra parameters. Default ''.
+        :param scope: List of scopes to request. Must be equal to
+            or a subset of the scopes granted when obtaining the refresh
+            token. If none is provided, the ones provided in the constructor are
+            used.
+        :param kwargs: Additional parameters to included in the request.
+        :returns: The prepared request tuple with (url, headers, body).
+        """
+        if not is_secure_transport(token_url):
+            raise InsecureTransportError()
+
+        # do not assign scope to self automatically anymore
+        scope = self.scope if scope is None else scope
+        body = self.prepare_refresh_body(body=body,
+                                         refresh_token=refresh_token, scope=scope, **kwargs)
+        return token_url, FORM_ENC_HEADERS, body
+
+    def prepare_token_revocation_request(self, revocation_url, token,
+                                         token_type_hint="access_token", body='', callback=None, **kwargs):
+        """Prepare a token revocation request.
+
+        :param revocation_url: Provider token revocation endpoint URL.
+        :param token: The access or refresh token to be revoked (string).
+        :param token_type_hint: ``"access_token"`` (default) or
+            ``"refresh_token"``. This is optional and if you wish to not pass it you
+            must provide ``token_type_hint=None``.
+        :param body:
+        :param callback: A jsonp callback such as ``package.callback`` to be invoked
+            upon receiving the response. Not that it should not include a () suffix.
+        :param kwargs: Additional parameters to included in the request.
+        :returns: The prepared request tuple with (url, headers, body).
+
+        Note that JSONP request may use GET requests as the parameters will
+        be added to the request URL query as opposed to the request body.
+
+        An example of a revocation request
+
+        .. code-block:: http
+
+            POST /revoke HTTP/1.1
+            Host: server.example.com
+            Content-Type: application/x-www-form-urlencoded
+            Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
+
+            token=45ghiukldjahdnhzdauz&token_type_hint=refresh_token
+
+        An example of a jsonp revocation request
+
+        .. code-block:: http
+
+            GET /revoke?token=agabcdefddddafdd&callback=package.myCallback HTTP/1.1
+            Host: server.example.com
+            Content-Type: application/x-www-form-urlencoded
+            Authorization: Basic czZCaGRSa3F0MzpnWDFmQmF0M2JW
+
+        and an error response
+
+        .. code-block:: javascript
+
+            package.myCallback({"error":"unsupported_token_type"});
+
+        Note that these requests usually require client credentials, client_id in
+        the case for public clients and provider specific authentication
+        credentials for confidential clients.
+        """
+        if not is_secure_transport(revocation_url):
+            raise InsecureTransportError()
+
+        return prepare_token_revocation_request(revocation_url, token,
+                                                token_type_hint=token_type_hint, body=body, callback=callback,
+                                                **kwargs)
+
+    def parse_request_body_response(self, body, scope=None, **kwargs):
+        """Parse the JSON response body.
+
+        If the access token request is valid and authorized, the
+        authorization server issues an access token as described in
+        `Section 5.1`_.  A refresh token SHOULD NOT be included.  If the request
+        failed client authentication or is invalid, the authorization server
+        returns an error response as described in `Section 5.2`_.
+
+        :param body: The response body from the token request.
+        :param scope: Scopes originally requested. If none is provided, the ones
+            provided in the constructor are used.
+        :return: Dictionary of token parameters.
+        :raises: Warning if scope has changed. :py:class:`oauthlib.oauth2.errors.OAuth2Error`
+            if response is invalid.
+
+        These response are json encoded and could easily be parsed without
+        the assistance of OAuthLib. However, there are a few subtle issues
+        to be aware of regarding the response which are helpfully addressed
+        through the raising of various errors.
+
+        A successful response should always contain
+
+        **access_token**
+                The access token issued by the authorization server. Often
+                a random string.
+
+        **token_type**
+            The type of the token issued as described in `Section 7.1`_.
+            Commonly ``Bearer``.
+
+        While it is not mandated it is recommended that the provider include
+
+        **expires_in**
+            The lifetime in seconds of the access token.  For
+            example, the value "3600" denotes that the access token will
+            expire in one hour from the time the response was generated.
+            If omitted, the authorization server SHOULD provide the
+            expiration time via other means or document the default value.
+
+         **scope**
+            Providers may supply this in all responses but are required to only
+            if it has changed since the authorization request.
+
+        .. _`Section 5.1`: https://tools.ietf.org/html/rfc6749#section-5.1
+        .. _`Section 5.2`: https://tools.ietf.org/html/rfc6749#section-5.2
+        .. _`Section 7.1`: https://tools.ietf.org/html/rfc6749#section-7.1
+        """
+        scope = self.scope if scope is None else scope
+        self.token = parse_token_response(body, scope=scope)
+        self.populate_token_attributes(self.token)
+        return self.token
+
+    def prepare_refresh_body(self, body='', refresh_token=None, scope=None, **kwargs):
+        """Prepare an access token request, using a refresh token.
+
+        If the authorization server issued a refresh token to the client, the
+        client makes a refresh request to the token endpoint by adding the
+        following parameters using the `application/x-www-form-urlencoded`
+        format in the HTTP request entity-body:
+
+        :param refresh_token: REQUIRED.  The refresh token issued to the client.
+        :param scope:  OPTIONAL.  The scope of the access request as described by
+            Section 3.3.  The requested scope MUST NOT include any scope
+            not originally granted by the resource owner, and if omitted is
+            treated as equal to the scope originally granted by the
+            resource owner. Note that if none is provided, the ones provided
+            in the constructor are used if any.
+        """
+        refresh_token = refresh_token or self.refresh_token
+        scope = self.scope if scope is None else scope
+        return prepare_token_request(self.refresh_token_key, body=body, scope=scope,
+                                     refresh_token=refresh_token, **kwargs)
+
+    def _add_bearer_token(self, uri, http_method='GET', body=None,
+                          headers=None, token_placement=None):
+        """Add a bearer token to the request uri, body or authorization header."""
+        if token_placement == AUTH_HEADER:
+            headers = tokens.prepare_bearer_headers(self.access_token, headers)
+
+        elif token_placement == URI_QUERY:
+            uri = tokens.prepare_bearer_uri(self.access_token, uri)
+
+        elif token_placement == BODY:
+            body = tokens.prepare_bearer_body(self.access_token, body)
+
+        else:
+            raise ValueError("Invalid token placement.")
+        return uri, headers, body
+
+    def create_code_verifier(self, length):
+        """Create PKCE **code_verifier** used in computing **code_challenge**.
+        See `RFC7636 Section 4.1`_
+
+        :param length: REQUIRED. The length of the code_verifier.
+
+        The client first creates a code verifier, "code_verifier", for each
+        OAuth 2.0 [RFC6749] Authorization Request, in the following manner:
+
+        .. code-block:: text
+
+               code_verifier = high-entropy cryptographic random STRING using the
+               unreserved characters [A-Z] / [a-z] / [0-9] / "-" / "." / "_" / "~"
+               from Section 2.3 of [RFC3986], with a minimum length of 43 characters
+               and a maximum length of 128 characters.
+
+        .. _`RFC7636 Section 4.1`: https://tools.ietf.org/html/rfc7636#section-4.1
+        """
+        code_verifier = None
+
+        if not length >= 43:
+            raise ValueError("Length must be greater than or equal to 43")
+
+        if not length <= 128:
+            raise ValueError("Length must be less than or equal to 128")
+
+        code_verifier = generate_token(length, UNICODE_ASCII_CHARACTER_SET + "-._~")
+
+        self.code_verifier = code_verifier
+
+        return code_verifier
+
+    def create_code_challenge(self, code_verifier, code_challenge_method=None):
+        """Create PKCE **code_challenge** derived from the  **code_verifier**.
+        See `RFC7636 Section 4.2`_
+
+        :param code_verifier: REQUIRED. The **code_verifier** generated from `create_code_verifier()`.
+        :param code_challenge_method: OPTIONAL. The method used to derive the **code_challenge**. Acceptable values include `S256`. DEFAULT is `plain`.
+
+               The client then creates a code challenge derived from the code
+               verifier by using one of the following transformations on the code
+               verifier::
+
+                   plain
+                      code_challenge = code_verifier
+                   S256
+                      code_challenge = BASE64URL-ENCODE(SHA256(ASCII(code_verifier)))
+
+               If the client is capable of using `S256`, it MUST use `S256`, as
+               `S256` is Mandatory To Implement (MTI) on the server.  Clients are
+               permitted to use `plain` only if they cannot support `S256` for some
+               technical reason and know via out-of-band configuration that the
+               server supports `plain`.
+
+               The plain transformation is for compatibility with existing
+               deployments and for constrained environments that can't use the S256 transformation.
+
+        .. _`RFC7636 Section 4.2`: https://tools.ietf.org/html/rfc7636#section-4.2
+        """
+        code_challenge = None
+
+        if code_verifier is None:
+            raise ValueError("Invalid code_verifier")
+
+        if code_challenge_method is None:
+            code_challenge_method = "plain"
+            self.code_challenge_method = code_challenge_method
+            code_challenge = code_verifier
+            self.code_challenge = code_challenge
+
+        if code_challenge_method == "S256":
+            h = hashlib.sha256()
+            h.update(code_verifier.encode(encoding='ascii'))
+            sha256_val = h.digest()
+            code_challenge = bytes.decode(base64.urlsafe_b64encode(sha256_val))
+            # replace '+' with '-', '/' with '_', and remove trailing '='
+            code_challenge = code_challenge.replace("+", "-").replace("/", "_").replace("=", "")
+            self.code_challenge = code_challenge
+
+        return code_challenge
+
+    def _add_mac_token(self, uri, http_method='GET', body=None,
+                       headers=None, token_placement=AUTH_HEADER, ext=None, **kwargs):
+        """Add a MAC token to the request authorization header.
+
+        Warning: MAC token support is experimental as the spec is not yet stable.
+        """
+        if token_placement != AUTH_HEADER:
+            raise ValueError("Invalid token placement.")
+
+        headers = tokens.prepare_mac_header(self.access_token, uri,
+                                            self.mac_key, http_method, headers=headers, body=body, ext=ext,
+                                            hash_algorithm=self.mac_algorithm, **kwargs)
+        return uri, headers, body
+
+    def _populate_attributes(self, response):
+        warnings.warn("Please switch to the public method "
+                      "populate_token_attributes.", DeprecationWarning)
+        return self.populate_token_attributes(response)
+
+    def populate_code_attributes(self, response):
+        """Add attributes from an auth code response to self."""
+
+        if 'code' in response:
+            self.code = response.get('code')
+
+    def populate_token_attributes(self, response):
+        """Add attributes from a token exchange response to self."""
+
+        if 'access_token' in response:
+            self.access_token = response.get('access_token')
+
+        if 'refresh_token' in response:
+            self.refresh_token = response.get('refresh_token')
+
+        if 'token_type' in response:
+            self.token_type = response.get('token_type')
+
+        vin, vat, v_at = parse_expires(response)
+        if vin:
+            self.expires_in = vin
+        if vat:
+            self.expires_at = vat
+        if v_at:
+            self._expires_at = v_at
+
+        if 'mac_key' in response:
+            self.mac_key = response.get('mac_key')
+
+        if 'mac_algorithm' in response:
+            self.mac_algorithm = response.get('mac_algorithm')
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/legacy_application.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/legacy_application.py
new file mode 100644
index 0000000000000000000000000000000000000000..9920981d2c601761492ac1511c3ecd7a6a6a2e51
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/legacy_application.py
@@ -0,0 +1,84 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+from ..parameters import prepare_token_request
+from .base import Client
+
+
+class LegacyApplicationClient(Client):
+
+    """A public client using the resource owner password and username directly.
+
+    The resource owner password credentials grant type is suitable in
+    cases where the resource owner has a trust relationship with the
+    client, such as the device operating system or a highly privileged
+    application.  The authorization server should take special care when
+    enabling this grant type, and only allow it when other flows are not
+    viable.
+
+    The grant type is suitable for clients capable of obtaining the
+    resource owner's credentials (username and password, typically using
+    an interactive form).  It is also used to migrate existing clients
+    using direct authentication schemes such as HTTP Basic or Digest
+    authentication to OAuth by converting the stored credentials to an
+    access token.
+
+    The method through which the client obtains the resource owner
+    credentials is beyond the scope of this specification.  The client
+    MUST discard the credentials once an access token has been obtained.
+    """
+
+    grant_type = 'password'
+
+    def __init__(self, client_id, **kwargs):
+        super().__init__(client_id, **kwargs)
+
+    def prepare_request_body(self, username, password, body='', scope=None,
+                             include_client_id=False, **kwargs):
+        """Add the resource owner password and username to the request body.
+
+        The client makes a request to the token endpoint by adding the
+        following parameters using the "application/x-www-form-urlencoded"
+        format per `Appendix B`_ in the HTTP request entity-body:
+
+        :param username:    The resource owner username.
+        :param password:    The resource owner password.
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+        :param scope:   The scope of the access request as described by
+                        `Section 3.3`_.
+        :param include_client_id: `True` to send the `client_id` in the
+                                  body of the upstream request. This is required
+                                  if the client is not authenticating with the
+                                  authorization server as described in
+                                  `Section 3.2.1`_. False otherwise (default).
+        :type include_client_id: Boolean
+        :param kwargs:  Extra credentials to include in the token request.
+
+        If the client type is confidential or the client was issued client
+        credentials (or assigned other authentication requirements), the
+        client MUST authenticate with the authorization server as described
+        in `Section 3.2.1`_.
+
+        The prepared body will include all provided credentials as well as
+        the ``grant_type`` parameter set to ``password``::
+
+            >>> from oauthlib.oauth2 import LegacyApplicationClient
+            >>> client = LegacyApplicationClient('your_id')
+            >>> client.prepare_request_body(username='foo', password='bar', scope=['hello', 'world'])
+            'grant_type=password&username=foo&scope=hello+world&password=bar'
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 3.2.1`: https://tools.ietf.org/html/rfc6749#section-3.2.1
+        """
+        kwargs['client_id'] = self.client_id
+        kwargs['include_client_id'] = include_client_id
+        scope = self.scope if scope is None else scope
+        return prepare_token_request(self.grant_type, body=body, username=username,
+                                     password=password, scope=scope, **kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/mobile_application.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/mobile_application.py
new file mode 100644
index 0000000000000000000000000000000000000000..023cf23623ba806446eec8716f34b62d06e00cff
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/mobile_application.py
@@ -0,0 +1,174 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+from ..parameters import parse_implicit_response, prepare_grant_uri
+from .base import Client
+
+
+class MobileApplicationClient(Client):
+
+    """A public client utilizing the implicit code grant workflow.
+
+    A user-agent-based application is a public client in which the
+    client code is downloaded from a web server and executes within a
+    user-agent (e.g. web browser) on the device used by the resource
+    owner.  Protocol data and credentials are easily accessible (and
+    often visible) to the resource owner.  Since such applications
+    reside within the user-agent, they can make seamless use of the
+    user-agent capabilities when requesting authorization.
+
+    The implicit grant type is used to obtain access tokens (it does not
+    support the issuance of refresh tokens) and is optimized for public
+    clients known to operate a particular redirection URI.  These clients
+    are typically implemented in a browser using a scripting language
+    such as JavaScript.
+
+    As a redirection-based flow, the client must be capable of
+    interacting with the resource owner's user-agent (typically a web
+    browser) and capable of receiving incoming requests (via redirection)
+    from the authorization server.
+
+    Unlike the authorization code grant type in which the client makes
+    separate requests for authorization and access token, the client
+    receives the access token as the result of the authorization request.
+
+    The implicit grant type does not include client authentication, and
+    relies on the presence of the resource owner and the registration of
+    the redirection URI.  Because the access token is encoded into the
+    redirection URI, it may be exposed to the resource owner and other
+    applications residing on the same device.
+    """
+
+    response_type = 'token'
+
+    def prepare_request_uri(self, uri, redirect_uri=None, scope=None,
+                            state=None, **kwargs):
+        """Prepare the implicit grant request URI.
+
+        The client constructs the request URI by adding the following
+        parameters to the query component of the authorization endpoint URI
+        using the "application/x-www-form-urlencoded" format, per `Appendix B`_:
+
+        :param redirect_uri:  OPTIONAL. The redirect URI must be an absolute URI
+                              and it should have been registered with the OAuth
+                              provider prior to use. As described in `Section 3.1.2`_.
+
+        :param scope:  OPTIONAL. The scope of the access request as described by
+                       Section 3.3`_. These may be any string but are commonly
+                       URIs or various categories such as ``videos`` or ``documents``.
+
+        :param state:   RECOMMENDED.  An opaque value used by the client to maintain
+                        state between the request and callback.  The authorization
+                        server includes this value when redirecting the user-agent back
+                        to the client.  The parameter SHOULD be used for preventing
+                        cross-site request forgery as described in `Section 10.12`_.
+
+        :param kwargs:  Extra arguments to include in the request URI.
+
+        In addition to supplied parameters, OAuthLib will append the ``client_id``
+        that was provided in the constructor as well as the mandatory ``response_type``
+        argument, set to ``token``::
+
+            >>> from oauthlib.oauth2 import MobileApplicationClient
+            >>> client = MobileApplicationClient('your_id')
+            >>> client.prepare_request_uri('https://example.com')
+            'https://example.com?client_id=your_id&response_type=token'
+            >>> client.prepare_request_uri('https://example.com', redirect_uri='https://a.b/callback')
+            'https://example.com?client_id=your_id&response_type=token&redirect_uri=https%3A%2F%2Fa.b%2Fcallback'
+            >>> client.prepare_request_uri('https://example.com', scope=['profile', 'pictures'])
+            'https://example.com?client_id=your_id&response_type=token&scope=profile+pictures'
+            >>> client.prepare_request_uri('https://example.com', foo='bar')
+            'https://example.com?client_id=your_id&response_type=token&foo=bar'
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 2.2`: https://tools.ietf.org/html/rfc6749#section-2.2
+        .. _`Section 3.1.2`: https://tools.ietf.org/html/rfc6749#section-3.1.2
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 10.12`: https://tools.ietf.org/html/rfc6749#section-10.12
+        """
+        scope = self.scope if scope is None else scope
+        return prepare_grant_uri(uri, self.client_id, self.response_type,
+                                 redirect_uri=redirect_uri, state=state, scope=scope, **kwargs)
+
+    def parse_request_uri_response(self, uri, state=None, scope=None):
+        """Parse the response URI fragment.
+
+        If the resource owner grants the access request, the authorization
+        server issues an access token and delivers it to the client by adding
+        the following parameters to the fragment component of the redirection
+        URI using the "application/x-www-form-urlencoded" format:
+
+        :param uri: The callback URI that resulted from the user being redirected
+                    back from the provider to you, the client.
+        :param state: The state provided in the authorization request.
+        :param scope: The scopes provided in the authorization request.
+        :return: Dictionary of token parameters.
+        :raises: OAuth2Error if response is invalid.
+
+        A successful response should always contain
+
+        **access_token**
+                The access token issued by the authorization server. Often
+                a random string.
+
+        **token_type**
+            The type of the token issued as described in `Section 7.1`_.
+            Commonly ``Bearer``.
+
+        **state**
+            If you provided the state parameter in the authorization phase, then
+            the provider is required to include that exact state value in the
+            response.
+
+        While it is not mandated it is recommended that the provider include
+
+        **expires_in**
+            The lifetime in seconds of the access token.  For
+            example, the value "3600" denotes that the access token will
+            expire in one hour from the time the response was generated.
+            If omitted, the authorization server SHOULD provide the
+            expiration time via other means or document the default value.
+
+        **scope**
+            Providers may supply this in all responses but are required to only
+            if it has changed since the authorization request.
+
+        A few example responses can be seen below::
+
+            >>> response_uri = 'https://example.com/callback#access_token=sdlfkj452&state=ss345asyht&token_type=Bearer&scope=hello+world'
+            >>> from oauthlib.oauth2 import MobileApplicationClient
+            >>> client = MobileApplicationClient('your_id')
+            >>> client.parse_request_uri_response(response_uri)
+            {
+                'access_token': 'sdlfkj452',
+                'token_type': 'Bearer',
+                'state': 'ss345asyht',
+                'scope': [u'hello', u'world']
+            }
+            >>> client.parse_request_uri_response(response_uri, state='other')
+            Traceback (most recent call last):
+                File "<stdin>", line 1, in <module>
+                File "oauthlib/oauth2/rfc6749/__init__.py", line 598, in parse_request_uri_response
+                    **scope**
+                File "oauthlib/oauth2/rfc6749/parameters.py", line 197, in parse_implicit_response
+                    raise ValueError("Mismatching or missing state in params.")
+            ValueError: Mismatching or missing state in params.
+            >>> def alert_scope_changed(message, old, new):
+            ...     print(message, old, new)
+            ...
+            >>> oauthlib.signals.scope_changed.connect(alert_scope_changed)
+            >>> client.parse_request_body_response(response_body, scope=['other'])
+            ('Scope has changed from "other" to "hello world".', ['other'], ['hello', 'world'])
+
+        .. _`Section 7.1`: https://tools.ietf.org/html/rfc6749#section-7.1
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        """
+        scope = self.scope if scope is None else scope
+        self.token = parse_implicit_response(uri, state=state, scope=scope)
+        self.populate_token_attributes(self.token)
+        return self.token
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/service_application.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/service_application.py
new file mode 100644
index 0000000000000000000000000000000000000000..abf22d2d8e8dd52a921bda529341ba01ee59249b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/service_application.py
@@ -0,0 +1,189 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import time
+
+from oauthlib.common import to_unicode
+
+from ..parameters import prepare_token_request
+from .base import Client
+
+
+class ServiceApplicationClient(Client):
+    """A public client utilizing the JWT bearer grant.
+
+    JWT bearer tokes can be used to request an access token when a client
+    wishes to utilize an existing trust relationship, expressed through the
+    semantics of (and digital signature or keyed message digest calculated
+    over) the JWT, without a direct user approval step at the authorization
+    server.
+
+    This grant type does not involve an authorization step. It may be
+    used by both public and confidential clients.
+    """
+
+    grant_type = 'urn:ietf:params:oauth:grant-type:jwt-bearer'
+
+    def __init__(self, client_id, private_key=None, subject=None, issuer=None,
+                 audience=None, **kwargs):
+        """Initialize a JWT client with defaults for implicit use later.
+
+        :param client_id: Client identifier given by the OAuth provider upon
+                          registration.
+
+        :param private_key: Private key used for signing and encrypting.
+                            Must be given as a string.
+
+        :param subject: The principal that is the subject of the JWT, i.e.
+                        which user is the token requested on behalf of.
+                        For example, ``foo@example.com.
+
+        :param issuer: The JWT MUST contain an "iss" (issuer) claim that
+                       contains a unique identifier for the entity that issued
+                       the JWT. For example, ``your-client@provider.com``.
+
+        :param audience: A value identifying the authorization server as an
+                         intended audience, e.g.
+                         ``https://provider.com/oauth2/token``.
+
+        :param kwargs: Additional arguments to pass to base client, such as
+                       state and token. See ``Client.__init__.__doc__`` for
+                       details.
+        """
+        super().__init__(client_id, **kwargs)
+        self.private_key = private_key
+        self.subject = subject
+        self.issuer = issuer
+        self.audience = audience
+
+    def prepare_request_body(self,
+                             private_key=None,
+                             subject=None,
+                             issuer=None,
+                             audience=None,
+                             expires_at=None,
+                             issued_at=None,
+                             extra_claims=None,
+                             body='',
+                             scope=None,
+                             include_client_id=False,
+                             **kwargs):
+        """Create and add a JWT assertion to the request body.
+
+        :param private_key: Private key used for signing and encrypting.
+                            Must be given as a string.
+
+        :param subject: (sub) The principal that is the subject of the JWT,
+                        i.e.  which user is the token requested on behalf of.
+                        For example, ``foo@example.com.
+
+        :param issuer: (iss) The JWT MUST contain an "iss" (issuer) claim that
+                       contains a unique identifier for the entity that issued
+                       the JWT. For example, ``your-client@provider.com``.
+
+        :param audience: (aud) A value identifying the authorization server as an
+                         intended audience, e.g.
+                         ``https://provider.com/oauth2/token``.
+
+        :param expires_at: A unix expiration timestamp for the JWT. Defaults
+                           to an hour from now, i.e. ``round(time.time()) + 3600``.
+
+        :param issued_at: A unix timestamp of when the JWT was created.
+                          Defaults to now, i.e. ``time.time()``.
+
+        :param extra_claims: A dict of additional claims to include in the JWT.
+
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+
+        :param scope: The scope of the access request.
+
+        :param include_client_id: `True` to send the `client_id` in the
+                                  body of the upstream request. This is required
+                                  if the client is not authenticating with the
+                                  authorization server as described in
+                                  `Section 3.2.1`_. False otherwise (default).
+        :type include_client_id: Boolean
+
+        :param not_before: A unix timestamp after which the JWT may be used.
+                           Not included unless provided. *
+
+        :param jwt_id: A unique JWT token identifier. Not included unless
+                       provided. *
+
+        :param kwargs: Extra credentials to include in the token request.
+
+        Parameters marked with a `*` above are not explicit arguments in the
+        function signature, but are specially documented arguments for items
+        appearing in the generic `**kwargs` keyworded input.
+
+        The "scope" parameter may be used, as defined in the Assertion
+        Framework for OAuth 2.0 Client Authentication and Authorization Grants
+        [I-D.ietf-oauth-assertions] specification, to indicate the requested
+        scope.
+
+        Authentication of the client is optional, as described in
+        `Section 3.2.1`_ of OAuth 2.0 [RFC6749] and consequently, the
+        "client_id" is only needed when a form of client authentication that
+        relies on the parameter is used.
+
+        The following non-normative example demonstrates an Access Token
+        Request with a JWT as an authorization grant (with extra line breaks
+        for display purposes only):
+
+        .. code-block: http
+
+            POST /token.oauth2 HTTP/1.1
+            Host: as.example.com
+            Content-Type: application/x-www-form-urlencoded
+
+            grant_type=urn%3Aietf%3Aparams%3Aoauth%3Agrant-type%3Ajwt-bearer
+            &assertion=eyJhbGciOiJFUzI1NiJ9.
+            eyJpc3Mi[...omitted for brevity...].
+            J9l-ZhwP[...omitted for brevity...]
+
+        .. _`Section 3.2.1`: https://tools.ietf.org/html/rfc6749#section-3.2.1
+        """
+        import jwt  # noqa: PLC0415
+
+        key = private_key or self.private_key
+        if not key:
+            raise ValueError('An encryption key must be supplied to make JWT'
+                             ' token requests.')
+        claim = {
+            'iss': issuer or self.issuer,
+            'aud': audience or self.audience,
+            'sub': subject or self.subject,
+            'exp': int(expires_at or time.time() + 3600),
+            'iat': int(issued_at or time.time()),
+        }
+
+        for attr in ('iss', 'aud', 'sub'):
+            if claim[attr] is None:
+                raise ValueError(
+                        'Claim must include %s but none was given.' % attr)
+
+        if 'not_before' in kwargs:
+            claim['nbf'] = kwargs.pop('not_before')
+
+        if 'jwt_id' in kwargs:
+            claim['jti'] = kwargs.pop('jwt_id')
+
+        claim.update(extra_claims or {})
+
+        assertion = jwt.encode(claim, key, 'RS256')
+        assertion = to_unicode(assertion)
+
+        kwargs['client_id'] = self.client_id
+        kwargs['include_client_id'] = include_client_id
+        scope = self.scope if scope is None else scope
+        return prepare_token_request(self.grant_type,
+                                     body=body,
+                                     assertion=assertion,
+                                     scope=scope,
+                                     **kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/web_application.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/web_application.py
new file mode 100644
index 0000000000000000000000000000000000000000..3bf94c4b51b30c85a94edf261394ddfce5bce2a5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/clients/web_application.py
@@ -0,0 +1,222 @@
+# -*- coding: utf-8 -*-
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import warnings
+
+from ..parameters import (
+    parse_authorization_code_response, prepare_grant_uri,
+    prepare_token_request,
+)
+from .base import Client
+
+
+class WebApplicationClient(Client):
+
+    """A client utilizing the authorization code grant workflow.
+
+    A web application is a confidential client running on a web
+    server.  Resource owners access the client via an HTML user
+    interface rendered in a user-agent on the device used by the
+    resource owner.  The client credentials as well as any access
+    token issued to the client are stored on the web server and are
+    not exposed to or accessible by the resource owner.
+
+    The authorization code grant type is used to obtain both access
+    tokens and refresh tokens and is optimized for confidential clients.
+    As a redirection-based flow, the client must be capable of
+    interacting with the resource owner's user-agent (typically a web
+    browser) and capable of receiving incoming requests (via redirection)
+    from the authorization server.
+    """
+
+    grant_type = 'authorization_code'
+
+    def __init__(self, client_id, code=None, **kwargs):
+        super().__init__(client_id, **kwargs)
+        self.code = code
+
+    def prepare_request_uri(self, uri, redirect_uri=None, scope=None,
+                            state=None, code_challenge=None, code_challenge_method='plain', **kwargs):
+        """Prepare the authorization code request URI
+
+        The client constructs the request URI by adding the following
+        parameters to the query component of the authorization endpoint URI
+        using the "application/x-www-form-urlencoded" format, per `Appendix B`_:
+
+        :param redirect_uri:  OPTIONAL. The redirect URI must be an absolute URI
+                              and it should have been registered with the OAuth
+                              provider prior to use. As described in `Section 3.1.2`_.
+
+        :param scope:  OPTIONAL. The scope of the access request as described by
+                       Section 3.3`_. These may be any string but are commonly
+                       URIs or various categories such as ``videos`` or ``documents``.
+
+        :param state:   RECOMMENDED.  An opaque value used by the client to maintain
+                        state between the request and callback.  The authorization
+                        server includes this value when redirecting the user-agent back
+                        to the client.  The parameter SHOULD be used for preventing
+                        cross-site request forgery as described in `Section 10.12`_.
+
+        :param code_challenge: OPTIONAL. PKCE parameter. REQUIRED if PKCE is enforced.
+                        A challenge derived from the code_verifier that is sent in the
+                        authorization request, to be verified against later.
+
+        :param code_challenge_method: OPTIONAL. PKCE parameter. A method that was used to derive code challenge.
+                                      Defaults to "plain" if not present in the request.
+
+        :param kwargs:  Extra arguments to include in the request URI.
+
+        In addition to supplied parameters, OAuthLib will append the ``client_id``
+        that was provided in the constructor as well as the mandatory ``response_type``
+        argument, set to ``code``::
+
+            >>> from oauthlib.oauth2 import WebApplicationClient
+            >>> client = WebApplicationClient('your_id')
+            >>> client.prepare_request_uri('https://example.com')
+            'https://example.com?client_id=your_id&response_type=code'
+            >>> client.prepare_request_uri('https://example.com', redirect_uri='https://a.b/callback')
+            'https://example.com?client_id=your_id&response_type=code&redirect_uri=https%3A%2F%2Fa.b%2Fcallback'
+            >>> client.prepare_request_uri('https://example.com', scope=['profile', 'pictures'])
+            'https://example.com?client_id=your_id&response_type=code&scope=profile+pictures'
+            >>> client.prepare_request_uri('https://example.com', code_challenge='kjasBS523KdkAILD2k78NdcJSk2k3KHG6')
+            'https://example.com?client_id=your_id&response_type=code&code_challenge=kjasBS523KdkAILD2k78NdcJSk2k3KHG6'
+            >>> client.prepare_request_uri('https://example.com', code_challenge_method='S256')
+            'https://example.com?client_id=your_id&response_type=code&code_challenge_method=S256'
+            >>> client.prepare_request_uri('https://example.com', foo='bar')
+            'https://example.com?client_id=your_id&response_type=code&foo=bar'
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 2.2`: https://tools.ietf.org/html/rfc6749#section-2.2
+        .. _`Section 3.1.2`: https://tools.ietf.org/html/rfc6749#section-3.1.2
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 10.12`: https://tools.ietf.org/html/rfc6749#section-10.12
+        """
+        scope = self.scope if scope is None else scope
+        return prepare_grant_uri(uri, self.client_id, 'code',
+                                 redirect_uri=redirect_uri, scope=scope, state=state, code_challenge=code_challenge,
+                                 code_challenge_method=code_challenge_method, **kwargs)
+
+    def prepare_request_body(self, code=None, redirect_uri=None, body='',
+                             include_client_id=True, code_verifier=None, **kwargs):
+        """Prepare the access token request body.
+
+        The client makes a request to the token endpoint by adding the
+        following parameters using the "application/x-www-form-urlencoded"
+        format in the HTTP request entity-body:
+
+        :param code:    REQUIRED. The authorization code received from the
+                        authorization server.
+
+        :param redirect_uri:    REQUIRED, if the "redirect_uri" parameter was included in the
+                                authorization request as described in `Section 4.1.1`_, and their
+                                values MUST be identical.
+
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+
+        :param include_client_id: `True` (default) to send the `client_id` in the
+                                  body of the upstream request. This is required
+                                  if the client is not authenticating with the
+                                  authorization server as described in `Section 3.2.1`_.
+        :type include_client_id: Boolean
+
+        :param code_verifier: OPTIONAL. A cryptographically random string that is used to correlate the
+                                        authorization request to the token request.
+
+        :param kwargs: Extra parameters to include in the token request.
+
+        In addition OAuthLib will add the ``grant_type`` parameter set to
+        ``authorization_code``.
+
+        If the client type is confidential or the client was issued client
+        credentials (or assigned other authentication requirements), the
+        client MUST authenticate with the authorization server as described
+        in `Section 3.2.1`_::
+
+            >>> from oauthlib.oauth2 import WebApplicationClient
+            >>> client = WebApplicationClient('your_id')
+            >>> client.prepare_request_body(code='sh35ksdf09sf')
+            'grant_type=authorization_code&code=sh35ksdf09sf'
+            >>> client.prepare_request_body(code_verifier='KB46DCKJ873NCGXK5GD682NHDKK34GR')
+            'grant_type=authorization_code&code_verifier=KB46DCKJ873NCGXK5GD682NHDKK34GR'
+            >>> client.prepare_request_body(code='sh35ksdf09sf', foo='bar')
+            'grant_type=authorization_code&code=sh35ksdf09sf&foo=bar'
+
+        `Section 3.2.1` also states:
+            In the "authorization_code" "grant_type" request to the token
+            endpoint, an unauthenticated client MUST send its "client_id" to
+            prevent itself from inadvertently accepting a code intended for a
+            client with a different "client_id".  This protects the client from
+            substitution of the authentication code.  (It provides no additional
+            security for the protected resource.)
+
+        .. _`Section 4.1.1`: https://tools.ietf.org/html/rfc6749#section-4.1.1
+        .. _`Section 3.2.1`: https://tools.ietf.org/html/rfc6749#section-3.2.1
+        """
+        code = code or self.code
+        if 'client_id' in kwargs:
+            warnings.warn("`client_id` has been deprecated in favor of "
+                          "`include_client_id`, a boolean value which will "
+                          "include the already configured `self.client_id`.",
+                          DeprecationWarning)
+            if kwargs['client_id'] != self.client_id:
+                raise ValueError("`client_id` was supplied as an argument, but "
+                                 "it does not match `self.client_id`")
+
+        kwargs['client_id'] = self.client_id
+        kwargs['include_client_id'] = include_client_id
+        return prepare_token_request(self.grant_type, code=code, body=body,
+                                     redirect_uri=redirect_uri, code_verifier=code_verifier, **kwargs)
+
+    def parse_request_uri_response(self, uri, state=None):
+        """Parse the URI query for code and state.
+
+        If the resource owner grants the access request, the authorization
+        server issues an authorization code and delivers it to the client by
+        adding the following parameters to the query component of the
+        redirection URI using the "application/x-www-form-urlencoded" format:
+
+        :param uri: The callback URI that resulted from the user being redirected
+                    back from the provider to you, the client.
+        :param state: The state provided in the authorization request.
+
+        **code**
+            The authorization code generated by the authorization server.
+            The authorization code MUST expire shortly after it is issued
+            to mitigate the risk of leaks. A maximum authorization code
+            lifetime of 10 minutes is RECOMMENDED. The client MUST NOT
+            use the authorization code more than once. If an authorization
+            code is used more than once, the authorization server MUST deny
+            the request and SHOULD revoke (when possible) all tokens
+            previously issued based on that authorization code.
+            The authorization code is bound to the client identifier and
+            redirection URI.
+
+        **state**
+                If the "state" parameter was present in the authorization request.
+
+        This method is mainly intended to enforce strict state checking with
+        the added benefit of easily extracting parameters from the URI::
+
+            >>> from oauthlib.oauth2 import WebApplicationClient
+            >>> client = WebApplicationClient('your_id')
+            >>> uri = 'https://example.com/callback?code=sdfkjh345&state=sfetw45'
+            >>> client.parse_request_uri_response(uri, state='sfetw45')
+            {'state': 'sfetw45', 'code': 'sdfkjh345'}
+            >>> client.parse_request_uri_response(uri, state='other')
+            Traceback (most recent call last):
+                File "<stdin>", line 1, in <module>
+                File "oauthlib/oauth2/rfc6749/__init__.py", line 357, in parse_request_uri_response
+                    back from the provider to you, the client.
+                File "oauthlib/oauth2/rfc6749/parameters.py", line 153, in parse_authorization_code_response
+                    raise MismatchingStateError()
+            oauthlib.oauth2.rfc6749.errors.MismatchingStateError
+        """
+        response = parse_authorization_code_response(uri, state=state)
+        self.populate_code_attributes(response)
+        return response
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..1695b41b663eded80893849ec0b4ecc6f69c0e5c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/__init__.py
@@ -0,0 +1,17 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+from .authorization import AuthorizationEndpoint
+from .introspect import IntrospectEndpoint
+from .metadata import MetadataEndpoint
+from .pre_configured import (
+    BackendApplicationServer, LegacyApplicationServer, MobileApplicationServer,
+    Server, WebApplicationServer,
+)
+from .resource import ResourceEndpoint
+from .revocation import RevocationEndpoint
+from .token import TokenEndpoint
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/authorization.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/authorization.py
new file mode 100644
index 0000000000000000000000000000000000000000..71967865dce4a1d6cc344036a732f7bc008dbaeb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/authorization.py
@@ -0,0 +1,114 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import logging
+
+from oauthlib.common import Request
+from oauthlib.oauth2.rfc6749 import utils
+
+from .base import BaseEndpoint, catch_errors_and_unavailability
+
+log = logging.getLogger(__name__)
+
+
+class AuthorizationEndpoint(BaseEndpoint):
+
+    """Authorization endpoint - used by the client to obtain authorization
+    from the resource owner via user-agent redirection.
+
+    The authorization endpoint is used to interact with the resource
+    owner and obtain an authorization grant.  The authorization server
+    MUST first verify the identity of the resource owner.  The way in
+    which the authorization server authenticates the resource owner (e.g.
+    username and password login, session cookies) is beyond the scope of
+    this specification.
+
+    The endpoint URI MAY include an "application/x-www-form-urlencoded"
+    formatted (per `Appendix B`_) query component,
+    which MUST be retained when adding additional query parameters.  The
+    endpoint URI MUST NOT include a fragment component::
+
+        https://example.com/path?query=component             # OK
+        https://example.com/path?query=component#fragment    # Not OK
+
+    Since requests to the authorization endpoint result in user
+    authentication and the transmission of clear-text credentials (in the
+    HTTP response), the authorization server MUST require the use of TLS
+    as described in Section 1.6 when sending requests to the
+    authorization endpoint::
+
+        # We will deny any request which URI schema is not with https
+
+    The authorization server MUST support the use of the HTTP "GET"
+    method [RFC2616] for the authorization endpoint, and MAY support the
+    use of the "POST" method as well::
+
+        # HTTP method is currently not enforced
+
+    Parameters sent without a value MUST be treated as if they were
+    omitted from the request.  The authorization server MUST ignore
+    unrecognized request parameters.  Request and response parameters
+    MUST NOT be included more than once::
+
+        # Enforced through the design of oauthlib.common.Request
+
+    .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+    """
+
+    def __init__(self, default_response_type, default_token_type,
+                 response_types):
+        BaseEndpoint.__init__(self)
+        self._response_types = response_types
+        self._default_response_type = default_response_type
+        self._default_token_type = default_token_type
+
+    @property
+    def response_types(self):
+        return self._response_types
+
+    @property
+    def default_response_type(self):
+        return self._default_response_type
+
+    @property
+    def default_response_type_handler(self):
+        return self.response_types.get(self.default_response_type)
+
+    @property
+    def default_token_type(self):
+        return self._default_token_type
+
+    @catch_errors_and_unavailability
+    def create_authorization_response(self, uri, http_method='GET', body=None,
+                                      headers=None, scopes=None, credentials=None):
+        """Extract response_type and route to the designated handler."""
+        request = Request(
+            uri, http_method=http_method, body=body, headers=headers)
+        request.scopes = scopes
+        # TODO: decide whether this should be a required argument
+        request.user = None     # TODO: explain this in docs
+        for k, v in (credentials or {}).items():
+            setattr(request, k, v)
+        response_type_handler = self.response_types.get(
+            request.response_type, self.default_response_type_handler)
+        log.debug('Dispatching response_type %s request to %r.',
+                  request.response_type, response_type_handler)
+        return response_type_handler.create_authorization_response(
+            request, self.default_token_type)
+
+    @catch_errors_and_unavailability
+    def validate_authorization_request(self, uri, http_method='GET', body=None,
+                                       headers=None):
+        """Extract response_type and route to the designated handler."""
+        request = Request(
+            uri, http_method=http_method, body=body, headers=headers)
+
+        request.scopes = utils.scope_to_list(request.scope)
+
+        response_type_handler = self.response_types.get(
+            request.response_type, self.default_response_type_handler)
+        return response_type_handler.validate_authorization_request(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/base.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..987fac6a8fbd272ce98008e5e21d43fa7f9bcd67
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/base.py
@@ -0,0 +1,113 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import functools
+import logging
+
+from ..errors import (
+    FatalClientError, InvalidClientError, InvalidRequestError, OAuth2Error,
+    ServerError, TemporarilyUnavailableError, UnsupportedTokenTypeError,
+)
+
+log = logging.getLogger(__name__)
+
+
+class BaseEndpoint:
+
+    def __init__(self):
+        self._available = True
+        self._catch_errors = False
+        self._valid_request_methods = None
+
+    @property
+    def valid_request_methods(self):
+        return self._valid_request_methods
+
+    @valid_request_methods.setter
+    def valid_request_methods(self, valid_request_methods):
+        if valid_request_methods is not None:
+            valid_request_methods = [x.upper() for x in valid_request_methods]
+        self._valid_request_methods = valid_request_methods
+
+
+    @property
+    def available(self):
+        return self._available
+
+    @available.setter
+    def available(self, available):
+        self._available = available
+
+    @property
+    def catch_errors(self):
+        return self._catch_errors
+
+    @catch_errors.setter
+    def catch_errors(self, catch_errors):
+        self._catch_errors = catch_errors
+
+    def _raise_on_missing_token(self, request):
+        """Raise error on missing token."""
+        if not request.token:
+            raise InvalidRequestError(request=request,
+                                      description='Missing token parameter.')
+    def _raise_on_invalid_client(self, request):
+        """Raise on failed client authentication."""
+        if self.request_validator.client_authentication_required(request):
+            if not self.request_validator.authenticate_client(request):
+                log.debug('Client authentication failed, %r.', request)
+                raise InvalidClientError(request=request)
+        elif not self.request_validator.authenticate_client_id(request.client_id, request):
+            log.debug('Client authentication failed, %r.', request)
+            raise InvalidClientError(request=request)
+
+    def _raise_on_unsupported_token(self, request):
+        """Raise on unsupported tokens."""
+        if (request.token_type_hint and
+            request.token_type_hint in self.valid_token_types and
+            request.token_type_hint not in self.supported_token_types):
+            raise UnsupportedTokenTypeError(request=request)
+
+    def _raise_on_bad_method(self, request):
+        if self.valid_request_methods is None:
+            raise ValueError('Configure "valid_request_methods" property first')
+        if request.http_method.upper() not in self.valid_request_methods:
+            raise InvalidRequestError(request=request,
+                                      description=('Unsupported request method %s' % request.http_method.upper()))
+
+    def _raise_on_bad_post_request(self, request):
+        """Raise if invalid POST request received
+        """
+        if request.http_method.upper() == 'POST':
+            query_params = request.uri_query or ""
+            if query_params:
+                raise InvalidRequestError(request=request,
+                                          description=('URL query parameters are not allowed'))
+
+def catch_errors_and_unavailability(f):
+    @functools.wraps(f)
+    def wrapper(endpoint, uri, *args, **kwargs):
+        if not endpoint.available:
+            e = TemporarilyUnavailableError()
+            log.info('Endpoint unavailable, ignoring request %s.' % uri)
+            return {}, e.json, 503
+
+        if endpoint.catch_errors:
+            try:
+                return f(endpoint, uri, *args, **kwargs)
+            except OAuth2Error:
+                raise
+            except FatalClientError:
+                raise
+            except Exception as e:
+                error = ServerError()
+                log.warning(
+                    'Exception caught while processing request, %s.' % e)
+                return {}, error.json, 500
+        else:
+            return f(endpoint, uri, *args, **kwargs)
+    return wrapper
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/introspect.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/introspect.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef73988d48db03e7fc64d54e9fb6315f32923fde
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/introspect.py
@@ -0,0 +1,120 @@
+"""
+oauthlib.oauth2.rfc6749.endpoint.introspect
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+An implementation of the OAuth 2.0 `Token Introspection`.
+
+.. _`Token Introspection`: https://tools.ietf.org/html/rfc7662
+"""
+import json
+import logging
+
+from oauthlib.common import Request
+
+from ..errors import OAuth2Error
+from .base import BaseEndpoint, catch_errors_and_unavailability
+
+log = logging.getLogger(__name__)
+
+
+class IntrospectEndpoint(BaseEndpoint):
+
+    """Introspect token endpoint.
+
+   This endpoint defines a method to query an OAuth 2.0 authorization
+   server to determine the active state of an OAuth 2.0 token and to
+   determine meta-information about this token. OAuth 2.0 deployments
+   can use this method to convey information about the authorization
+   context of the token from the authorization server to the protected
+   resource.
+
+   To prevent the values of access tokens from leaking into
+   server-side logs via query parameters, an authorization server
+   offering token introspection MAY disallow the use of HTTP GET on
+   the introspection endpoint and instead require the HTTP POST method
+   to be used at the introspection endpoint.
+   """
+
+    valid_token_types = ('access_token', 'refresh_token')
+    valid_request_methods = ('POST',)
+
+    def __init__(self, request_validator, supported_token_types=None):
+        BaseEndpoint.__init__(self)
+        self.request_validator = request_validator
+        self.supported_token_types = (
+            supported_token_types or self.valid_token_types)
+
+    @catch_errors_and_unavailability
+    def create_introspect_response(self, uri, http_method='POST', body=None,
+                                   headers=None):
+        """Create introspect valid or invalid response
+
+        If the authorization server is unable to determine the state
+        of the token without additional information, it SHOULD return
+        an introspection response indicating the token is not active
+        as described in Section 2.2.
+        """
+        resp_headers = {
+            'Content-Type': 'application/json',
+            'Cache-Control': 'no-store',
+            'Pragma': 'no-cache',
+        }
+        request = Request(uri, http_method, body, headers)
+        try:
+            self.validate_introspect_request(request)
+            log.debug('Token introspect valid for %r.', request)
+        except OAuth2Error as e:
+            log.debug('Client error during validation of %r. %r.', request, e)
+            resp_headers.update(e.headers)
+            return resp_headers, e.json, e.status_code
+
+        claims = self.request_validator.introspect_token(
+            request.token,
+            request.token_type_hint,
+            request
+        )
+        if claims is None:
+            return resp_headers, json.dumps({'active': False}), 200
+        if "active" in claims:
+            claims.pop("active")
+        return resp_headers, json.dumps(dict(active=True, **claims)), 200
+
+    def validate_introspect_request(self, request):
+        """Ensure the request is valid.
+
+        The protected resource calls the introspection endpoint using
+        an HTTP POST request with parameters sent as
+        "application/x-www-form-urlencoded".
+
+        * token REQUIRED.  The string value of the token.
+        * token_type_hint OPTIONAL.
+
+        A hint about the type of the token submitted for
+        introspection.  The protected resource MAY pass this parameter to
+        help the authorization server optimize the token lookup.  If the
+        server is unable to locate the token using the given hint, it MUST
+        extend its search across all of its supported token types.  An
+        authorization server MAY ignore this parameter, particularly if it
+        is able to detect the token type automatically.
+
+        *  access_token: An Access Token as defined in [`RFC6749`], `section 1.4`_
+        *  refresh_token: A Refresh Token as defined in [`RFC6749`], `section 1.5`_
+
+        The introspection endpoint MAY accept other OPTIONAL
+        parameters to provide further context to the query.  For
+        instance, an authorization server may desire to know the IP
+        address of the client accessing the protected resource to
+        determine if the correct client is likely to be presenting the
+        token.  The definition of this or any other parameters are
+        outside the scope of this specification, to be defined by
+        service documentation or extensions to this specification.
+
+        .. _`section 1.4`: http://tools.ietf.org/html/rfc6749#section-1.4
+        .. _`section 1.5`: http://tools.ietf.org/html/rfc6749#section-1.5
+        .. _`RFC6749`: http://tools.ietf.org/html/rfc6749
+        """
+        self._raise_on_bad_method(request)
+        self._raise_on_bad_post_request(request)
+        self._raise_on_missing_token(request)
+        self._raise_on_invalid_client(request)
+        self._raise_on_unsupported_token(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/metadata.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/metadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..34274cba67baf4699d9c3f82ecc421a6af824d8e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/metadata.py
@@ -0,0 +1,238 @@
+"""
+oauthlib.oauth2.rfc6749.endpoint.metadata
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+An implementation of the `OAuth 2.0 Authorization Server Metadata`.
+
+.. _`OAuth 2.0 Authorization Server Metadata`: https://tools.ietf.org/html/rfc8414
+"""
+import copy
+import json
+import logging
+
+from .. import grant_types, utils
+from .authorization import AuthorizationEndpoint
+from .base import BaseEndpoint, catch_errors_and_unavailability
+from .introspect import IntrospectEndpoint
+from .revocation import RevocationEndpoint
+from .token import TokenEndpoint
+
+log = logging.getLogger(__name__)
+
+
+class MetadataEndpoint(BaseEndpoint):
+
+    """OAuth2.0 Authorization Server Metadata endpoint.
+
+   This specification generalizes the metadata format defined by
+   `OpenID Connect Discovery 1.0` in a way that is compatible
+   with OpenID Connect Discovery while being applicable to a wider set
+   of OAuth 2.0 use cases.  This is intentionally parallel to the way
+   that OAuth 2.0 Dynamic Client Registration Protocol [`RFC7591`_]
+   generalized the dynamic client registration mechanisms defined by
+   OpenID Connect Dynamic Client Registration 1.0
+   in a way that is compatible with it.
+
+   .. _`OpenID Connect Discovery 1.0`: https://openid.net/specs/openid-connect-discovery-1_0.html
+   .. _`RFC7591`: https://tools.ietf.org/html/rfc7591
+   """
+
+    def __init__(self, endpoints, claims={}, raise_errors=True):
+        assert isinstance(claims, dict)  # noqa: S101
+        for endpoint in endpoints:
+            assert isinstance(endpoint, BaseEndpoint)  # noqa: S101
+
+        BaseEndpoint.__init__(self)
+        self.raise_errors = raise_errors
+        self.endpoints = endpoints
+        self.initial_claims = claims
+        self.claims = self.validate_metadata_server()
+
+    @catch_errors_and_unavailability
+    def create_metadata_response(self, uri, http_method='GET', body=None,
+                                 headers=None):
+        """Create metadata response
+        """
+        headers = {
+            'Content-Type': 'application/json',
+            'Access-Control-Allow-Origin': '*',
+        }
+        return headers, json.dumps(self.claims), 200
+
+    def validate_metadata(self, array, key, is_required=False, is_list=False, is_url=False, is_issuer=False):
+        if not self.raise_errors:
+            return
+
+        if key not in array:
+            if is_required:
+                raise ValueError("key {} is a mandatory metadata.".format(key))
+
+        elif is_issuer:
+            if not utils.is_secure_transport(array[key]):
+                raise ValueError("key {}: {} must be an HTTPS URL".format(key, array[key]))
+            if "?" in array[key] or "&" in array[key] or "#" in array[key]:
+                raise ValueError("key {}: {} must not contain query or fragment components".format(key, array[key]))
+
+        elif is_url:
+            if not array[key].startswith("http"):
+                raise ValueError("key {}: {} must be an URL".format(key, array[key]))
+
+        elif is_list:
+            if not isinstance(array[key], list):
+                raise ValueError("key {}: {} must be an Array".format(key, array[key]))
+            for elem in array[key]:
+                if not isinstance(elem, str):
+                    raise ValueError("array {}: {} must contains only string (not {})".format(key, array[key], elem))
+
+    def validate_metadata_token(self, claims, endpoint):
+        """
+        If the token endpoint is used in the grant type, the value of this
+        parameter MUST be the same as the value of the "grant_type"
+        parameter passed to the token endpoint defined in the grant type
+        definition.
+        """
+        self._grant_types.extend(endpoint._grant_types.keys())
+        claims.setdefault("token_endpoint_auth_methods_supported", ["client_secret_post", "client_secret_basic"])
+
+        self.validate_metadata(claims, "token_endpoint_auth_methods_supported", is_list=True)
+        self.validate_metadata(claims, "token_endpoint_auth_signing_alg_values_supported", is_list=True)
+        self.validate_metadata(claims, "token_endpoint", is_required=True, is_url=True)
+
+    def validate_metadata_authorization(self, claims, endpoint):
+        claims.setdefault("response_types_supported",
+                          list(filter(lambda x: x != "none", endpoint._response_types.keys())))
+        claims.setdefault("response_modes_supported", ["query", "fragment"])
+
+        # The OAuth2.0 Implicit flow is defined as a "grant type" but it is not
+        # using the "token" endpoint, as such, we have to add it explicitly to
+        # the list of "grant_types_supported" when enabled.
+        if "token" in claims["response_types_supported"]:
+            self._grant_types.append("implicit")
+
+        self.validate_metadata(claims, "response_types_supported", is_required=True, is_list=True)
+        self.validate_metadata(claims, "response_modes_supported", is_list=True)
+        if "code" in claims["response_types_supported"]:
+            code_grant = endpoint._response_types["code"]
+            if not isinstance(code_grant, grant_types.AuthorizationCodeGrant) and hasattr(code_grant, "default_grant"):
+                code_grant = code_grant.default_grant
+
+            claims.setdefault("code_challenge_methods_supported",
+                              list(code_grant._code_challenge_methods.keys()))
+            self.validate_metadata(claims, "code_challenge_methods_supported", is_list=True)
+        self.validate_metadata(claims, "authorization_endpoint", is_required=True, is_url=True)
+
+    def validate_metadata_revocation(self, claims, endpoint):
+        claims.setdefault("revocation_endpoint_auth_methods_supported",
+                          ["client_secret_post", "client_secret_basic"])
+
+        self.validate_metadata(claims, "revocation_endpoint_auth_methods_supported", is_list=True)
+        self.validate_metadata(claims, "revocation_endpoint_auth_signing_alg_values_supported", is_list=True)
+        self.validate_metadata(claims, "revocation_endpoint", is_required=True, is_url=True)
+
+    def validate_metadata_introspection(self, claims, endpoint):
+        claims.setdefault("introspection_endpoint_auth_methods_supported",
+                          ["client_secret_post", "client_secret_basic"])
+
+        self.validate_metadata(claims, "introspection_endpoint_auth_methods_supported", is_list=True)
+        self.validate_metadata(claims, "introspection_endpoint_auth_signing_alg_values_supported", is_list=True)
+        self.validate_metadata(claims, "introspection_endpoint", is_required=True, is_url=True)
+
+    def validate_metadata_server(self):
+        """
+        Authorization servers can have metadata describing their
+        configuration.  The following authorization server metadata values
+        are used by this specification. More details can be found in
+        `RFC8414 section 2`_ :
+
+       issuer
+          REQUIRED
+
+       authorization_endpoint
+          URL of the authorization server's authorization endpoint
+          [`RFC6749#Authorization`_].  This is REQUIRED unless no grant types are supported
+          that use the authorization endpoint.
+
+       token_endpoint
+          URL of the authorization server's token endpoint [`RFC6749#Token`_].  This
+          is REQUIRED unless only the implicit grant type is supported.
+
+       scopes_supported
+          RECOMMENDED.
+
+       response_types_supported
+          REQUIRED.
+
+       Other OPTIONAL fields:
+          jwks_uri,
+          registration_endpoint,
+          response_modes_supported
+
+       grant_types_supported
+          OPTIONAL.  JSON array containing a list of the OAuth 2.0 grant
+          type values that this authorization server supports.  The array
+          values used are the same as those used with the "grant_types"
+          parameter defined by "OAuth 2.0 Dynamic Client Registration
+          Protocol" [`RFC7591`_].  If omitted, the default value is
+          "["authorization_code", "implicit"]".
+
+       token_endpoint_auth_methods_supported
+
+       token_endpoint_auth_signing_alg_values_supported
+
+       service_documentation
+
+       ui_locales_supported
+
+       op_policy_uri
+
+       op_tos_uri
+
+       revocation_endpoint
+
+       revocation_endpoint_auth_methods_supported
+
+       revocation_endpoint_auth_signing_alg_values_supported
+
+       introspection_endpoint
+
+       introspection_endpoint_auth_methods_supported
+
+       introspection_endpoint_auth_signing_alg_values_supported
+
+       code_challenge_methods_supported
+
+       Additional authorization server metadata parameters MAY also be used.
+       Some are defined by other specifications, such as OpenID Connect
+       Discovery 1.0 [`OpenID.Discovery`_].
+
+        .. _`RFC8414 section 2`: https://tools.ietf.org/html/rfc8414#section-2
+        .. _`RFC6749#Authorization`: https://tools.ietf.org/html/rfc6749#section-3.1
+        .. _`RFC6749#Token`: https://tools.ietf.org/html/rfc6749#section-3.2
+        .. _`RFC7591`: https://tools.ietf.org/html/rfc7591
+        .. _`OpenID.Discovery`: https://openid.net/specs/openid-connect-discovery-1_0.html
+        """
+        claims = copy.deepcopy(self.initial_claims)
+        self.validate_metadata(claims, "issuer", is_required=True, is_issuer=True)
+        self.validate_metadata(claims, "jwks_uri", is_url=True)
+        self.validate_metadata(claims, "scopes_supported", is_list=True)
+        self.validate_metadata(claims, "service_documentation", is_url=True)
+        self.validate_metadata(claims, "ui_locales_supported", is_list=True)
+        self.validate_metadata(claims, "op_policy_uri", is_url=True)
+        self.validate_metadata(claims, "op_tos_uri", is_url=True)
+
+        self._grant_types = []
+        for endpoint in self.endpoints:
+            if isinstance(endpoint, TokenEndpoint):
+                self.validate_metadata_token(claims, endpoint)
+            if isinstance(endpoint, AuthorizationEndpoint):
+                self.validate_metadata_authorization(claims, endpoint)
+            if isinstance(endpoint, RevocationEndpoint):
+                self.validate_metadata_revocation(claims, endpoint)
+            if isinstance(endpoint, IntrospectEndpoint):
+                self.validate_metadata_introspection(claims, endpoint)
+
+        # "grant_types_supported" is a combination of all OAuth2 grant types
+        # allowed in the current provider implementation.
+        claims.setdefault("grant_types_supported", self._grant_types)
+        self.validate_metadata(claims, "grant_types_supported", is_list=True)
+        return claims
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/pre_configured.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/pre_configured.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f6aa32b7420c4447e0b7419276143955ead1e8a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/pre_configured.py
@@ -0,0 +1,287 @@
+"""
+oauthlib.oauth2.rfc6749.endpoints.pre_configured
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various endpoints needed
+for providing OAuth 2.0 RFC6749 servers.
+"""
+
+from ..grant_types import (
+    AuthorizationCodeGrant,
+    ClientCredentialsGrant,
+    ImplicitGrant,
+    RefreshTokenGrant,
+    ResourceOwnerPasswordCredentialsGrant,
+)
+from ..tokens import BearerToken
+from .authorization import AuthorizationEndpoint
+from .introspect import IntrospectEndpoint
+from .resource import ResourceEndpoint
+from .revocation import RevocationEndpoint
+from .token import TokenEndpoint
+from oauthlib.oauth2.rfc8628.grant_types import DeviceCodeGrant
+
+
+class Server(
+    AuthorizationEndpoint, IntrospectEndpoint, TokenEndpoint, ResourceEndpoint, RevocationEndpoint
+):
+    """
+    An all-in-one endpoint featuring all four major grant types
+    and extension grants.
+    """
+
+    def __init__(
+        self,
+        request_validator,
+        token_expires_in=None,
+        token_generator=None,
+        refresh_token_generator=None,
+        *args,
+        **kwargs,
+    ):
+        """Construct a new all-grants-in-one server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.auth_grant = AuthorizationCodeGrant(request_validator)
+        self.implicit_grant = ImplicitGrant(request_validator)
+        self.password_grant = ResourceOwnerPasswordCredentialsGrant(request_validator)
+        self.credentials_grant = ClientCredentialsGrant(request_validator)
+        self.refresh_grant = RefreshTokenGrant(request_validator)
+        self.device_code_grant = DeviceCodeGrant(request_validator, **kwargs)
+
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+
+        AuthorizationEndpoint.__init__(
+            self,
+            default_response_type="code",
+            response_types={
+                "code": self.auth_grant,
+                "token": self.implicit_grant,
+                "none": self.auth_grant,
+            },
+            default_token_type=self.bearer,
+        )
+
+        TokenEndpoint.__init__(
+            self,
+            default_grant_type="authorization_code",
+            grant_types={
+                "authorization_code": self.auth_grant,
+                "password": self.password_grant,
+                "client_credentials": self.credentials_grant,
+                "refresh_token": self.refresh_grant,
+                "urn:ietf:params:oauth:grant-type:device_code": self.device_code_grant,
+            },
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer}
+        )
+        RevocationEndpoint.__init__(self, request_validator)
+        IntrospectEndpoint.__init__(self, request_validator)
+
+
+class WebApplicationServer(
+    AuthorizationEndpoint, IntrospectEndpoint, TokenEndpoint, ResourceEndpoint, RevocationEndpoint
+):
+    """An all-in-one endpoint featuring Authorization code grant and Bearer tokens."""
+
+    def __init__(
+        self,
+        request_validator,
+        token_generator=None,
+        token_expires_in=None,
+        refresh_token_generator=None,
+        **kwargs,
+    ):
+        """Construct a new web application server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.auth_grant = AuthorizationCodeGrant(request_validator)
+        self.refresh_grant = RefreshTokenGrant(request_validator)
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+        AuthorizationEndpoint.__init__(
+            self,
+            default_response_type="code",
+            response_types={"code": self.auth_grant},
+            default_token_type=self.bearer,
+        )
+        TokenEndpoint.__init__(
+            self,
+            default_grant_type="authorization_code",
+            grant_types={
+                "authorization_code": self.auth_grant,
+                "refresh_token": self.refresh_grant,
+            },
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer}
+        )
+        RevocationEndpoint.__init__(self, request_validator)
+        IntrospectEndpoint.__init__(self, request_validator)
+
+
+class MobileApplicationServer(
+    AuthorizationEndpoint, IntrospectEndpoint, ResourceEndpoint, RevocationEndpoint
+):
+    """An all-in-one endpoint featuring Implicit code grant and Bearer tokens."""
+
+    def __init__(
+        self,
+        request_validator,
+        token_generator=None,
+        token_expires_in=None,
+        refresh_token_generator=None,
+        **kwargs,
+    ):
+        """Construct a new implicit grant server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.implicit_grant = ImplicitGrant(request_validator)
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+        AuthorizationEndpoint.__init__(
+            self,
+            default_response_type="token",
+            response_types={"token": self.implicit_grant},
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer}
+        )
+        RevocationEndpoint.__init__(
+            self, request_validator, supported_token_types=["access_token"]
+        )
+        IntrospectEndpoint.__init__(
+            self, request_validator, supported_token_types=["access_token"]
+        )
+
+
+class LegacyApplicationServer(
+    TokenEndpoint, IntrospectEndpoint, ResourceEndpoint, RevocationEndpoint
+):
+    """An all-in-one endpoint featuring Resource Owner Password Credentials grant and Bearer tokens."""
+
+    def __init__(
+        self,
+        request_validator,
+        token_generator=None,
+        token_expires_in=None,
+        refresh_token_generator=None,
+        **kwargs,
+    ):
+        """Construct a resource owner password credentials grant server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.password_grant = ResourceOwnerPasswordCredentialsGrant(request_validator)
+        self.refresh_grant = RefreshTokenGrant(request_validator)
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+        TokenEndpoint.__init__(
+            self,
+            default_grant_type="password",
+            grant_types={
+                "password": self.password_grant,
+                "refresh_token": self.refresh_grant,
+            },
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer}
+        )
+        RevocationEndpoint.__init__(self, request_validator)
+        IntrospectEndpoint.__init__(self, request_validator)
+
+
+class BackendApplicationServer(
+    TokenEndpoint, IntrospectEndpoint, ResourceEndpoint, RevocationEndpoint
+):
+    """An all-in-one endpoint featuring Client Credentials grant and Bearer tokens."""
+
+    def __init__(
+        self,
+        request_validator,
+        token_generator=None,
+        token_expires_in=None,
+        refresh_token_generator=None,
+        **kwargs,
+    ):
+        """Construct a client credentials grant server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.credentials_grant = ClientCredentialsGrant(request_validator)
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+        TokenEndpoint.__init__(
+            self,
+            default_grant_type="client_credentials",
+            grant_types={"client_credentials": self.credentials_grant},
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer}
+        )
+        RevocationEndpoint.__init__(
+            self, request_validator, supported_token_types=["access_token"]
+        )
+        IntrospectEndpoint.__init__(
+            self, request_validator, supported_token_types=["access_token"]
+        )
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/resource.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/resource.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1ff5049d858311a88c4a4115f59437cf20f6243
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/resource.py
@@ -0,0 +1,84 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import logging
+
+from oauthlib.common import Request
+
+from .base import BaseEndpoint, catch_errors_and_unavailability
+
+log = logging.getLogger(__name__)
+
+
+class ResourceEndpoint(BaseEndpoint):
+
+    """Authorizes access to protected resources.
+
+    The client accesses protected resources by presenting the access
+    token to the resource server.  The resource server MUST validate the
+    access token and ensure that it has not expired and that its scope
+    covers the requested resource.  The methods used by the resource
+    server to validate the access token (as well as any error responses)
+    are beyond the scope of this specification but generally involve an
+    interaction or coordination between the resource server and the
+    authorization server::
+
+        # For most cases, returning a 403 should suffice.
+
+    The method in which the client utilizes the access token to
+    authenticate with the resource server depends on the type of access
+    token issued by the authorization server.  Typically, it involves
+    using the HTTP "Authorization" request header field [RFC2617] with an
+    authentication scheme defined by the specification of the access
+    token type used, such as [RFC6750]::
+
+        # Access tokens may also be provided in query and body
+        https://example.com/protected?access_token=kjfch2345sdf   # Query
+        access_token=sdf23409df   # Body
+    """
+
+    def __init__(self, default_token, token_types):
+        BaseEndpoint.__init__(self)
+        self._tokens = token_types
+        self._default_token = default_token
+
+    @property
+    def default_token(self):
+        return self._default_token
+
+    @property
+    def default_token_type_handler(self):
+        return self.tokens.get(self.default_token)
+
+    @property
+    def tokens(self):
+        return self._tokens
+
+    @catch_errors_and_unavailability
+    def verify_request(self, uri, http_method='GET', body=None, headers=None,
+                       scopes=None):
+        """Validate client, code etc, return body + headers"""
+        request = Request(uri, http_method, body, headers)
+        request.token_type = self.find_token_type(request)
+        request.scopes = scopes
+        token_type_handler = self.tokens.get(request.token_type,
+                                             self.default_token_type_handler)
+        log.debug('Dispatching token_type %s request to %r.',
+                  request.token_type, token_type_handler)
+        return token_type_handler.validate_request(request), request
+
+    def find_token_type(self, request):
+        """Token type identification.
+
+        RFC 6749 does not provide a method for easily differentiating between
+        different token types during protected resource access. We estimate
+        the most likely token type (if any) by asking each known token type
+        to give an estimation based on the request.
+        """
+        estimates = sorted(((t.estimate_type(request), n)
+                            for n, t in self.tokens.items()), reverse=True)
+        return estimates[0][1] if estimates else None
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/revocation.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/revocation.py
new file mode 100644
index 0000000000000000000000000000000000000000..596d0860fae67017a86b1042fcf9edb674fdf38d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/revocation.py
@@ -0,0 +1,126 @@
+"""
+oauthlib.oauth2.rfc6749.endpoint.revocation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+An implementation of the OAuth 2 `Token Revocation`_ spec (draft 11).
+
+.. _`Token Revocation`: https://tools.ietf.org/html/draft-ietf-oauth-revocation-11
+"""
+import logging
+
+from oauthlib.common import Request
+
+from ..errors import OAuth2Error
+from .base import BaseEndpoint, catch_errors_and_unavailability
+
+log = logging.getLogger(__name__)
+
+
+class RevocationEndpoint(BaseEndpoint):
+
+    """Token revocation endpoint.
+
+    Endpoint used by authenticated clients to revoke access and refresh tokens.
+    Commonly this will be part of the Authorization Endpoint.
+    """
+
+    valid_token_types = ('access_token', 'refresh_token')
+    valid_request_methods = ('POST',)
+
+    def __init__(self, request_validator, supported_token_types=None,
+            enable_jsonp=False):
+        BaseEndpoint.__init__(self)
+        self.request_validator = request_validator
+        self.supported_token_types = (
+            supported_token_types or self.valid_token_types)
+        self.enable_jsonp = enable_jsonp
+
+    @catch_errors_and_unavailability
+    def create_revocation_response(self, uri, http_method='POST', body=None,
+                                   headers=None):
+        """Revoke supplied access or refresh token.
+
+
+        The authorization server responds with HTTP status code 200 if the
+        token has been revoked successfully or if the client submitted an
+        invalid token.
+
+        Note: invalid tokens do not cause an error response since the client
+        cannot handle such an error in a reasonable way.  Moreover, the purpose
+        of the revocation request, invalidating the particular token, is
+        already achieved.
+
+        The content of the response body is ignored by the client as all
+        necessary information is conveyed in the response code.
+
+        An invalid token type hint value is ignored by the authorization server
+        and does not influence the revocation response.
+        """
+        resp_headers = {
+            'Content-Type': 'application/json',
+            'Cache-Control': 'no-store',
+            'Pragma': 'no-cache',
+        }
+        request = Request(
+            uri, http_method=http_method, body=body, headers=headers)
+        try:
+            self.validate_revocation_request(request)
+            log.debug('Token revocation valid for %r.', request)
+        except OAuth2Error as e:
+            log.debug('Client error during validation of %r. %r.', request, e)
+            response_body = e.json
+            if self.enable_jsonp and request.callback:
+                response_body = '{}({});'.format(request.callback, response_body)
+            resp_headers.update(e.headers)
+            return resp_headers, response_body, e.status_code
+
+        self.request_validator.revoke_token(request.token,
+                                            request.token_type_hint, request)
+
+        response_body = ''
+        if self.enable_jsonp and request.callback:
+            response_body = request.callback + '();'
+        return {}, response_body, 200
+
+    def validate_revocation_request(self, request):
+        """Ensure the request is valid.
+
+        The client constructs the request by including the following parameters
+        using the "application/x-www-form-urlencoded" format in the HTTP
+        request entity-body:
+
+        token (REQUIRED).  The token that the client wants to get revoked.
+
+        token_type_hint (OPTIONAL).  A hint about the type of the token
+        submitted for revocation.  Clients MAY pass this parameter in order to
+        help the authorization server to optimize the token lookup.  If the
+        server is unable to locate the token using the given hint, it MUST
+        extend its search across all of its supported token types.  An
+        authorization server MAY ignore this parameter, particularly if it is
+        able to detect the token type automatically.  This specification
+        defines two such values:
+
+                *  access_token: An Access Token as defined in [RFC6749],
+                    `section 1.4`_
+
+                *  refresh_token: A Refresh Token as defined in [RFC6749],
+                    `section 1.5`_
+
+                Specific implementations, profiles, and extensions of this
+                specification MAY define other values for this parameter using
+                the registry defined in `Section 4.1.2`_.
+
+        The client also includes its authentication credentials as described in
+        `Section 2.3`_. of [`RFC6749`_].
+
+        .. _`section 1.4`: https://tools.ietf.org/html/rfc6749#section-1.4
+        .. _`section 1.5`: https://tools.ietf.org/html/rfc6749#section-1.5
+        .. _`section 2.3`: https://tools.ietf.org/html/rfc6749#section-2.3
+        .. _`Section 4.1.2`: https://tools.ietf.org/html/draft-ietf-oauth-revocation-11#section-4.1.2
+        .. _`RFC6749`: https://tools.ietf.org/html/rfc6749
+        """
+        self._raise_on_bad_method(request)
+        self._raise_on_bad_post_request(request)
+        self._raise_on_missing_token(request)
+        self._raise_on_invalid_client(request)
+        self._raise_on_unsupported_token(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/token.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/token.py
new file mode 100644
index 0000000000000000000000000000000000000000..ab9e0918b30da3271335fbbac370d5667c9b1d61
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/endpoints/token.py
@@ -0,0 +1,119 @@
+"""
+oauthlib.oauth2.rfc6749
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC6749.
+"""
+import logging
+
+from oauthlib.common import Request
+from oauthlib.oauth2.rfc6749 import utils
+
+from .base import BaseEndpoint, catch_errors_and_unavailability
+
+log = logging.getLogger(__name__)
+
+
+class TokenEndpoint(BaseEndpoint):
+
+    """Token issuing endpoint.
+
+    The token endpoint is used by the client to obtain an access token by
+    presenting its authorization grant or refresh token.  The token
+    endpoint is used with every authorization grant except for the
+    implicit grant type (since an access token is issued directly).
+
+    The means through which the client obtains the location of the token
+    endpoint are beyond the scope of this specification, but the location
+    is typically provided in the service documentation.
+
+    The endpoint URI MAY include an "application/x-www-form-urlencoded"
+    formatted (per `Appendix B`_) query component,
+    which MUST be retained when adding additional query parameters.  The
+    endpoint URI MUST NOT include a fragment component::
+
+        https://example.com/path?query=component             # OK
+        https://example.com/path?query=component#fragment    # Not OK
+
+    Since requests to the token endpoint result in the transmission of
+    clear-text credentials (in the HTTP request and response), the
+    authorization server MUST require the use of TLS as described in
+    Section 1.6 when sending requests to the token endpoint::
+
+        # We will deny any request which URI schema is not with https
+
+    The client MUST use the HTTP "POST" method when making access token
+    requests::
+
+        # HTTP method is currently not enforced
+
+    Parameters sent without a value MUST be treated as if they were
+    omitted from the request.  The authorization server MUST ignore
+    unrecognized request parameters.  Request and response parameters
+    MUST NOT be included more than once::
+
+        # Delegated to each grant type.
+
+    .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+    """
+
+    valid_request_methods = ('POST',)
+
+    def __init__(self, default_grant_type, default_token_type, grant_types):
+        BaseEndpoint.__init__(self)
+        self._grant_types = grant_types
+        self._default_token_type = default_token_type
+        self._default_grant_type = default_grant_type
+
+    @property
+    def grant_types(self):
+        return self._grant_types
+
+    @property
+    def default_grant_type(self):
+        return self._default_grant_type
+
+    @property
+    def default_grant_type_handler(self):
+        return self.grant_types.get(self.default_grant_type)
+
+    @property
+    def default_token_type(self):
+        return self._default_token_type
+
+    @catch_errors_and_unavailability
+    def create_token_response(self, uri, http_method='POST', body=None,
+                              headers=None, credentials=None, grant_type_for_scope=None,
+                              claims=None):
+        """Extract grant_type and route to the designated handler."""
+        request = Request(
+            uri, http_method=http_method, body=body, headers=headers)
+        self.validate_token_request(request)
+        # 'scope' is an allowed Token Request param in both the "Resource Owner Password Credentials Grant"
+        # and "Client Credentials Grant" flows
+        # https://tools.ietf.org/html/rfc6749#section-4.3.2
+        # https://tools.ietf.org/html/rfc6749#section-4.4.2
+        request.scopes = utils.scope_to_list(request.scope)
+
+        request.extra_credentials = credentials
+        if grant_type_for_scope:
+            request.grant_type = grant_type_for_scope
+
+        # OpenID Connect claims, if provided.  The server using oauthlib might choose
+        # to implement the claims parameter of the Authorization Request.  In this case
+        # it should retrieve those claims and pass them via the claims argument here,
+        # as a dict.
+        if claims:
+            request.claims = claims
+
+        grant_type_handler = self.grant_types.get(request.grant_type,
+                                                  self.default_grant_type_handler)
+        log.debug('Dispatching grant_type %s request to %r.',
+                  request.grant_type, grant_type_handler)
+        return grant_type_handler.create_token_response(
+            request, self.default_token_type)
+
+    def validate_token_request(self, request):
+        self._raise_on_bad_method(request)
+        self._raise_on_bad_post_request(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/errors.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/errors.py
new file mode 100644
index 0000000000000000000000000000000000000000..be8e7a1ec6d74c00df1509d4d7a18b6213bdbf23
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/errors.py
@@ -0,0 +1,399 @@
+"""
+oauthlib.oauth2.rfc6749.errors
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Error used both by OAuth 2 clients and providers to represent the spec
+defined error responses for all four core grant types.
+"""
+import json
+import inspect
+import sys
+
+from oauthlib.common import add_params_to_uri, urlencode
+
+
+class OAuth2Error(Exception):
+    error = None
+    status_code = 400
+    description = ''
+
+    def __init__(self, description=None, uri=None, state=None,
+                 status_code=None, request=None):
+        """
+        :param description: A human-readable ASCII [USASCII] text providing
+                            additional information, used to assist the client
+                            developer in understanding the error that occurred.
+                            Values for the "error_description" parameter
+                            MUST NOT include characters outside the set
+                            x20-21 / x23-5B / x5D-7E.
+
+        :param uri: A URI identifying a human-readable web page with information
+                    about the error, used to provide the client developer with
+                    additional information about the error.  Values for the
+                    "error_uri" parameter MUST conform to the URI- Reference
+                    syntax, and thus MUST NOT include characters outside the set
+                    x21 / x23-5B / x5D-7E.
+
+        :param state: A CSRF protection value received from the client.
+
+        :param status_code:
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        if description is not None:
+            self.description = description
+
+        message = '({}) {}'.format(self.error, self.description)
+        if request:
+            message += ' ' + repr(request)
+        super().__init__(message)
+
+        self.uri = uri
+        self.state = state
+
+        if status_code:
+            self.status_code = status_code
+
+        if request:
+            self.redirect_uri = request.redirect_uri
+            self.client_id = request.client_id
+            self.scopes = request.scopes
+            self.response_type = request.response_type
+            self.response_mode = request.response_mode
+            self.grant_type = request.grant_type
+            if state is None:
+                self.state = request.state
+        else:
+            self.redirect_uri = None
+            self.client_id = None
+            self.scopes = None
+            self.response_type = None
+            self.response_mode = None
+            self.grant_type = None
+
+    def in_uri(self, uri):
+        fragment = self.response_mode == "fragment"
+        return add_params_to_uri(uri, self.twotuples, fragment)
+
+    @property
+    def twotuples(self):
+        error = [('error', self.error)]
+        if self.description:
+            error.append(('error_description', self.description))
+        if self.uri:
+            error.append(('error_uri', self.uri))
+        if self.state:
+            error.append(('state', self.state))
+        return error
+
+    @property
+    def urlencoded(self):
+        return urlencode(self.twotuples)
+
+    @property
+    def json(self):
+        return json.dumps(dict(self.twotuples))
+
+    @property
+    def headers(self):
+        if self.status_code == 401:
+            """
+            https://tools.ietf.org/html/rfc6750#section-3
+
+            All challenges defined by this specification MUST use the auth-scheme
+            value "Bearer".  This scheme MUST be followed by one or more
+            auth-param values.
+            """
+            authvalues = ['error="{}"'.format(self.error)]
+            if self.description:
+                authvalues.append('error_description="{}"'.format(self.description))
+            if self.uri:
+                authvalues.append('error_uri="{}"'.format(self.uri))
+            return {"WWW-Authenticate": "Bearer " + ", ".join(authvalues)}
+        return {}
+
+
+class TokenExpiredError(OAuth2Error):
+    error = 'token_expired'
+
+
+class InsecureTransportError(OAuth2Error):
+    error = 'insecure_transport'
+    description = 'OAuth 2 MUST utilize https.'
+
+
+class MismatchingStateError(OAuth2Error):
+    error = 'mismatching_state'
+    description = 'CSRF Warning! State not equal in request and response.'
+
+
+class MissingCodeError(OAuth2Error):
+    error = 'missing_code'
+
+
+class MissingTokenError(OAuth2Error):
+    error = 'missing_token'
+
+
+class MissingTokenTypeError(OAuth2Error):
+    error = 'missing_token_type'
+
+
+class FatalClientError(OAuth2Error):
+    """
+    Errors during authorization where user should not be redirected back.
+
+    If the request fails due to a missing, invalid, or mismatching
+    redirection URI, or if the client identifier is missing or invalid,
+    the authorization server SHOULD inform the resource owner of the
+    error and MUST NOT automatically redirect the user-agent to the
+    invalid redirection URI.
+
+    Instead the user should be informed of the error by the provider itself.
+    """
+
+
+class InvalidRequestFatalError(FatalClientError):
+    """
+    For fatal errors, the request is missing a required parameter, includes
+    an invalid parameter value, includes a parameter more than once, or is
+    otherwise malformed.
+    """
+    error = 'invalid_request'
+
+
+class InvalidRedirectURIError(InvalidRequestFatalError):
+    description = 'Invalid redirect URI.'
+
+
+class MissingRedirectURIError(InvalidRequestFatalError):
+    description = 'Missing redirect URI.'
+
+
+class MismatchingRedirectURIError(InvalidRequestFatalError):
+    description = 'Mismatching redirect URI.'
+
+
+class InvalidClientIdError(InvalidRequestFatalError):
+    description = 'Invalid client_id parameter value.'
+
+
+class MissingClientIdError(InvalidRequestFatalError):
+    description = 'Missing client_id parameter.'
+
+
+class InvalidRequestError(OAuth2Error):
+    """
+    The request is missing a required parameter, includes an invalid
+    parameter value, includes a parameter more than once, or is
+    otherwise malformed.
+    """
+    error = 'invalid_request'
+
+
+class MissingResponseTypeError(InvalidRequestError):
+    description = 'Missing response_type parameter.'
+
+
+class MissingCodeChallengeError(InvalidRequestError):
+    """
+    If the server requires Proof Key for Code Exchange (PKCE) by OAuth
+    public clients and the client does not send the "code_challenge" in
+    the request, the authorization endpoint MUST return the authorization
+    error response with the "error" value set to "invalid_request".  The
+    "error_description" or the response of "error_uri" SHOULD explain the
+    nature of error, e.g., code challenge required.
+    """
+    description = 'Code challenge required.'
+
+
+class MissingCodeVerifierError(InvalidRequestError):
+    """
+    The request to the token endpoint, when PKCE is enabled, has
+    the parameter `code_verifier` REQUIRED.
+    """
+    description = 'Code verifier required.'
+
+
+class AccessDeniedError(OAuth2Error):
+    """
+    The resource owner or authorization server denied the request.
+    """
+    error = 'access_denied'
+
+
+class UnsupportedResponseTypeError(OAuth2Error):
+    """
+    The authorization server does not support obtaining an authorization
+    code using this method.
+    """
+    error = 'unsupported_response_type'
+
+
+class UnsupportedCodeChallengeMethodError(InvalidRequestError):
+    """
+    If the server supporting PKCE does not support the requested
+    transformation, the authorization endpoint MUST return the
+    authorization error response with "error" value set to
+    "invalid_request".  The "error_description" or the response of
+    "error_uri" SHOULD explain the nature of error, e.g., transform
+    algorithm not supported.
+    """
+    description = 'Transform algorithm not supported.'
+
+
+class InvalidScopeError(OAuth2Error):
+    """
+    The requested scope is invalid, unknown, or malformed, or
+    exceeds the scope granted by the resource owner.
+
+    https://tools.ietf.org/html/rfc6749#section-5.2
+    """
+    error = 'invalid_scope'
+
+
+class ServerError(OAuth2Error):
+    """
+    The authorization server encountered an unexpected condition that
+    prevented it from fulfilling the request.  (This error code is needed
+    because a 500 Internal Server Error HTTP status code cannot be returned
+    to the client via a HTTP redirect.)
+    """
+    error = 'server_error'
+
+
+class TemporarilyUnavailableError(OAuth2Error):
+    """
+    The authorization server is currently unable to handle the request
+    due to a temporary overloading or maintenance of the server.
+    (This error code is needed because a 503 Service Unavailable HTTP
+    status code cannot be returned to the client via a HTTP redirect.)
+    """
+    error = 'temporarily_unavailable'
+
+
+class InvalidClientError(FatalClientError):
+    """
+    Client authentication failed (e.g. unknown client, no client
+    authentication included, or unsupported authentication method).
+    The authorization server MAY return an HTTP 401 (Unauthorized) status
+    code to indicate which HTTP authentication schemes are supported.
+    If the client attempted to authenticate via the "Authorization" request
+    header field, the authorization server MUST respond with an
+    HTTP 401 (Unauthorized) status code, and include the "WWW-Authenticate"
+    response header field matching the authentication scheme used by the
+    client.
+    """
+    error = 'invalid_client'
+    status_code = 401
+
+
+class InvalidGrantError(OAuth2Error):
+    """
+    The provided authorization grant (e.g. authorization code, resource
+    owner credentials) or refresh token is invalid, expired, revoked, does
+    not match the redirection URI used in the authorization request, or was
+    issued to another client.
+
+    https://tools.ietf.org/html/rfc6749#section-5.2
+    """
+    error = 'invalid_grant'
+    status_code = 400
+
+
+class UnauthorizedClientError(OAuth2Error):
+    """
+    The authenticated client is not authorized to use this authorization
+    grant type.
+    """
+    error = 'unauthorized_client'
+
+
+class UnsupportedGrantTypeError(OAuth2Error):
+    """
+    The authorization grant type is not supported by the authorization
+    server.
+    """
+    error = 'unsupported_grant_type'
+
+
+class UnsupportedTokenTypeError(OAuth2Error):
+    """
+    The authorization server does not support the hint of the
+    presented token type.  I.e. the client tried to revoke an access token
+    on a server not supporting this feature.
+    """
+    error = 'unsupported_token_type'
+
+
+class InvalidTokenError(OAuth2Error):
+    """
+    The access token provided is expired, revoked, malformed, or
+    invalid for other reasons.  The resource SHOULD respond with
+    the HTTP 401 (Unauthorized) status code.  The client MAY
+    request a new access token and retry the protected resource
+    request.
+    """
+    error = 'invalid_token'
+    status_code = 401
+    description = ("The access token provided is expired, revoked, malformed, "
+                   "or invalid for other reasons.")
+
+
+class InsufficientScopeError(OAuth2Error):
+    """
+    The request requires higher privileges than provided by the
+    access token.  The resource server SHOULD respond with the HTTP
+    403 (Forbidden) status code and MAY include the "scope"
+    attribute with the scope necessary to access the protected
+    resource.
+    """
+    error = 'insufficient_scope'
+    status_code = 403
+    description = ("The request requires higher privileges than provided by "
+                   "the access token.")
+
+
+class ConsentRequired(OAuth2Error):
+    """
+    The Authorization Server requires End-User consent.
+
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface for End-User consent.
+    """
+    error = 'consent_required'
+
+
+class LoginRequired(OAuth2Error):
+    """
+    The Authorization Server requires End-User authentication.
+
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface for End-User authentication.
+    """
+    error = 'login_required'
+
+
+class CustomOAuth2Error(OAuth2Error):
+    """
+    This error is a placeholder for all custom errors not described by the RFC.
+    Some of the popular OAuth2 providers are using custom errors.
+    """
+    def __init__(self, error, *args, **kwargs):
+        self.error = error
+        super().__init__(*args, **kwargs)
+
+
+def raise_from_error(error, params=None):
+    kwargs = {
+        'description': params.get('error_description'),
+        'uri': params.get('error_uri'),
+        'state': params.get('state')
+    }
+    for _, cls in inspect.getmembers(sys.modules[__name__], inspect.isclass):
+        if cls.error == error:
+            raise cls(**kwargs)
+    raise CustomOAuth2Error(error=error, **kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb88cfc2e9749d22780532fd75af2fc8b7c2fae2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/__init__.py
@@ -0,0 +1,11 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+from .authorization_code import AuthorizationCodeGrant
+from .client_credentials import ClientCredentialsGrant
+from .implicit import ImplicitGrant
+from .refresh_token import RefreshTokenGrant
+from .resource_owner_password_credentials import (
+    ResourceOwnerPasswordCredentialsGrant,
+)
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/authorization_code.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/authorization_code.py
new file mode 100644
index 0000000000000000000000000000000000000000..09dc619988941ea1dd83e15b4b4f11689b45bb36
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/authorization_code.py
@@ -0,0 +1,547 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import base64
+import hashlib
+import json
+import logging
+
+from oauthlib import common
+
+from .. import errors
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+def code_challenge_method_s256(verifier, challenge):
+    """
+    If the "code_challenge_method" from `Section 4.3`_ was "S256", the
+    received "code_verifier" is hashed by SHA-256, base64url-encoded, and
+    then compared to the "code_challenge", i.e.:
+
+    BASE64URL-ENCODE(SHA256(ASCII(code_verifier))) == code_challenge
+
+    How to implement a base64url-encoding
+    function without padding, based upon the standard base64-encoding
+    function that uses padding.
+
+    To be concrete, example C# code implementing these functions is shown
+    below.  Similar code could be used in other languages.
+
+    static string base64urlencode(byte [] arg)
+    {
+        string s = Convert.ToBase64String(arg); // Regular base64 encoder
+        s = s.Split('=')[0]; // Remove any trailing '='s
+        s = s.Replace('+', '-'); // 62nd char of encoding
+        s = s.Replace('/', '_'); // 63rd char of encoding
+        return s;
+    }
+
+    In python urlsafe_b64encode is already replacing '+' and '/', but preserve
+    the trailing '='. So we have to remove it.
+
+    .. _`Section 4.3`: https://tools.ietf.org/html/rfc7636#section-4.3
+    """
+    return base64.urlsafe_b64encode(
+        hashlib.sha256(verifier.encode()).digest()
+    ).decode().rstrip('=') == challenge
+
+
+def code_challenge_method_plain(verifier, challenge):
+    """
+    If the "code_challenge_method" from `Section 4.3`_ was "plain", they are
+    compared directly, i.e.:
+
+    code_verifier == code_challenge.
+
+    .. _`Section 4.3`: https://tools.ietf.org/html/rfc7636#section-4.3
+    """
+    return verifier == challenge
+
+
+class AuthorizationCodeGrant(GrantTypeBase):
+
+    """`Authorization Code Grant`_
+
+    The authorization code grant type is used to obtain both access
+    tokens and refresh tokens and is optimized for confidential clients.
+    Since this is a redirection-based flow, the client must be capable of
+    interacting with the resource owner's user-agent (typically a web
+    browser) and capable of receiving incoming requests (via redirection)
+    from the authorization server::
+
+        +----------+
+        | Resource |
+        |   Owner  |
+        |          |
+        +----------+
+             ^
+             |
+            (B)
+        +----|-----+          Client Identifier      +---------------+
+        |         -+----(A)-- & Redirection URI ---->|               |
+        |  User-   |                                 | Authorization |
+        |  Agent  -+----(B)-- User authenticates --->|     Server    |
+        |          |                                 |               |
+        |         -+----(C)-- Authorization Code ---<|               |
+        +-|----|---+                                 +---------------+
+          |    |                                         ^      v
+         (A)  (C)                                        |      |
+          |    |                                         |      |
+          ^    v                                         |      |
+        +---------+                                      |      |
+        |         |>---(D)-- Authorization Code ---------'      |
+        |  Client |          & Redirection URI                  |
+        |         |                                             |
+        |         |<---(E)----- Access Token -------------------'
+        +---------+       (w/ Optional Refresh Token)
+
+    Note: The lines illustrating steps (A), (B), and (C) are broken into
+    two parts as they pass through the user-agent.
+
+    Figure 3: Authorization Code Flow
+
+    The flow illustrated in Figure 3 includes the following steps:
+
+    (A)  The client initiates the flow by directing the resource owner's
+         user-agent to the authorization endpoint.  The client includes
+         its client identifier, requested scope, local state, and a
+         redirection URI to which the authorization server will send the
+         user-agent back once access is granted (or denied).
+
+    (B)  The authorization server authenticates the resource owner (via
+         the user-agent) and establishes whether the resource owner
+         grants or denies the client's access request.
+
+    (C)  Assuming the resource owner grants access, the authorization
+         server redirects the user-agent back to the client using the
+         redirection URI provided earlier (in the request or during
+         client registration).  The redirection URI includes an
+         authorization code and any local state provided by the client
+         earlier.
+
+    (D)  The client requests an access token from the authorization
+         server's token endpoint by including the authorization code
+         received in the previous step.  When making the request, the
+         client authenticates with the authorization server.  The client
+         includes the redirection URI used to obtain the authorization
+         code for verification.
+
+    (E)  The authorization server authenticates the client, validates the
+         authorization code, and ensures that the redirection URI
+         received matches the URI used to redirect the client in
+         step (C).  If valid, the authorization server responds back with
+         an access token and, optionally, a refresh token.
+
+    OAuth 2.0 public clients utilizing the Authorization Code Grant are
+    susceptible to the authorization code interception attack.
+
+    A technique to mitigate against the threat through the use of Proof Key for Code
+    Exchange (PKCE, pronounced "pixy") is implemented in the current oauthlib
+    implementation.
+
+    .. _`Authorization Code Grant`: https://tools.ietf.org/html/rfc6749#section-4.1
+    .. _`PKCE`: https://tools.ietf.org/html/rfc7636
+    """
+
+    default_response_mode = 'query'
+    response_types = ['code']
+
+    # This dict below is private because as RFC mention it:
+    # "S256" is Mandatory To Implement (MTI) on the server.
+    #
+    _code_challenge_methods = {
+        'plain': code_challenge_method_plain,
+        'S256': code_challenge_method_s256
+    }
+
+    def create_authorization_code(self, request):
+        """
+        Generates an authorization grant represented as a dictionary.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        grant = {'code': common.generate_token()}
+        if hasattr(request, 'state') and request.state:
+            grant['state'] = request.state
+        log.debug('Created authorization code grant %r for request %r.',
+                  grant, request)
+        return grant
+
+    def create_authorization_response(self, request, token_handler):
+        """
+        The client constructs the request URI by adding the following
+        parameters to the query component of the authorization endpoint URI
+        using the "application/x-www-form-urlencoded" format, per `Appendix B`_:
+
+        response_type
+                REQUIRED.  Value MUST be set to "code" for standard OAuth2
+                authorization flow.  For OpenID Connect it must be one of
+                "code token", "code id_token", or "code token id_token" - we
+                essentially test that "code" appears in the response_type.
+        client_id
+                REQUIRED.  The client identifier as described in `Section 2.2`_.
+        redirect_uri
+                OPTIONAL.  As described in `Section 3.1.2`_.
+        scope
+                OPTIONAL.  The scope of the access request as described by
+                `Section 3.3`_.
+        state
+                RECOMMENDED.  An opaque value used by the client to maintain
+                state between the request and callback.  The authorization
+                server includes this value when redirecting the user-agent back
+                to the client.  The parameter SHOULD be used for preventing
+                cross-site request forgery as described in `Section 10.12`_.
+
+        The client directs the resource owner to the constructed URI using an
+        HTTP redirection response, or by other means available to it via the
+        user-agent.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+        :returns: headers, body, status
+        :raises: FatalClientError on invalid redirect URI or client id.
+
+        A few examples::
+
+            >>> from your_validator import your_validator
+            >>> request = Request('https://example.com/authorize?client_id=valid'
+            ...                   '&redirect_uri=http%3A%2F%2Fclient.com%2F')
+            >>> from oauthlib.common import Request
+            >>> from oauthlib.oauth2 import AuthorizationCodeGrant, BearerToken
+            >>> token = BearerToken(your_validator)
+            >>> grant = AuthorizationCodeGrant(your_validator)
+            >>> request.scopes = ['authorized', 'in', 'some', 'form']
+            >>> grant.create_authorization_response(request, token)
+            (u'http://client.com/?error=invalid_request&error_description=Missing+response_type+parameter.', None, None, 400)
+            >>> request = Request('https://example.com/authorize?client_id=valid'
+            ...                   '&redirect_uri=http%3A%2F%2Fclient.com%2F'
+            ...                   '&response_type=code')
+            >>> request.scopes = ['authorized', 'in', 'some', 'form']
+            >>> grant.create_authorization_response(request, token)
+            (u'http://client.com/?code=u3F05aEObJuP2k7DordviIgW5wl52N', None, None, 200)
+            >>> # If the client id or redirect uri fails validation
+            >>> grant.create_authorization_response(request, token)
+            Traceback (most recent call last):
+                File "<stdin>", line 1, in <module>
+                File "oauthlib/oauth2/rfc6749/grant_types.py", line 515, in create_authorization_response
+                    >>> grant.create_authorization_response(request, token)
+                File "oauthlib/oauth2/rfc6749/grant_types.py", line 591, in validate_authorization_request
+            oauthlib.oauth2.rfc6749.errors.InvalidClientIdError
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 2.2`: https://tools.ietf.org/html/rfc6749#section-2.2
+        .. _`Section 3.1.2`: https://tools.ietf.org/html/rfc6749#section-3.1.2
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 10.12`: https://tools.ietf.org/html/rfc6749#section-10.12
+        """
+        try:
+            self.validate_authorization_request(request)
+            log.debug('Pre resource owner authorization validation ok for %r.',
+                      request)
+
+        # If the request fails due to a missing, invalid, or mismatching
+        # redirection URI, or if the client identifier is missing or invalid,
+        # the authorization server SHOULD inform the resource owner of the
+        # error and MUST NOT automatically redirect the user-agent to the
+        # invalid redirection URI.
+        except errors.FatalClientError as e:
+            log.debug('Fatal client error during validation of %r. %r.',
+                      request, e)
+            raise
+
+        # If the resource owner denies the access request or if the request
+        # fails for reasons other than a missing or invalid redirection URI,
+        # the authorization server informs the client by adding the following
+        # parameters to the query component of the redirection URI using the
+        # "application/x-www-form-urlencoded" format, per Appendix B:
+        # https://tools.ietf.org/html/rfc6749#appendix-B
+        except errors.OAuth2Error as e:
+            log.debug('Client error during validation of %r. %r.', request, e)
+            request.redirect_uri = request.redirect_uri or self.error_uri
+            redirect_uri = common.add_params_to_uri(
+                request.redirect_uri, e.twotuples,
+                fragment=request.response_mode == "fragment")
+            return {'Location': redirect_uri}, None, 302
+
+        grant = self.create_authorization_code(request)
+        for modifier in self._code_modifiers:
+            grant = modifier(grant, token_handler, request)
+        if 'access_token' in grant:
+            self.request_validator.save_token(grant, request)
+        log.debug('Saving grant %r for %r.', grant, request)
+        self.request_validator.save_authorization_code(
+            request.client_id, grant, request)
+        return self.prepare_authorization_response(
+            request, grant, {}, None, 302)
+
+    def create_token_response(self, request, token_handler):
+        """Validate the authorization code.
+
+        The client MUST NOT use the authorization code more than once. If an
+        authorization code is used more than once, the authorization server
+        MUST deny the request and SHOULD revoke (when possible) all tokens
+        previously issued based on that authorization code. The authorization
+        code is bound to the client identifier and redirection URI.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        """
+        headers = self._get_default_headers()
+        try:
+            self.validate_token_request(request)
+            log.debug('Token request validation ok for %r.', request)
+        except errors.OAuth2Error as e:
+            log.debug('Client error during validation of %r. %r.', request, e)
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request, refresh_token=self.refresh_token)
+
+        for modifier in self._token_modifiers:
+            token = modifier(token, token_handler, request)
+
+        self.request_validator.save_token(token, request)
+        self.request_validator.invalidate_authorization_code(
+            request.client_id, request.code, request)
+        headers.update(self._create_cors_headers(request))
+        return headers, json.dumps(token), 200
+
+    def validate_authorization_request(self, request):
+        """Check the authorization request for normal and fatal errors.
+
+        A normal error could be a missing response_type parameter or the client
+        attempting to access scope it is not allowed to ask authorization for.
+        Normal errors can safely be included in the redirection URI and
+        sent back to the client.
+
+        Fatal errors occur when the client_id or redirect_uri is invalid or
+        missing. These must be caught by the provider and handled, how this
+        is done is outside of the scope of OAuthLib but showing an error
+        page describing the issue is a good idea.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+
+        # First check for fatal errors
+
+        # If the request fails due to a missing, invalid, or mismatching
+        # redirection URI, or if the client identifier is missing or invalid,
+        # the authorization server SHOULD inform the resource owner of the
+        # error and MUST NOT automatically redirect the user-agent to the
+        # invalid redirection URI.
+
+        # First check duplicate parameters
+        for param in ('client_id', 'response_type', 'redirect_uri', 'scope', 'state'):
+            try:
+                duplicate_params = request.duplicate_params
+            except ValueError:
+                raise errors.InvalidRequestFatalError(description='Unable to parse query string', request=request)
+            if param in duplicate_params:
+                raise errors.InvalidRequestFatalError(description='Duplicate %s parameter.' % param, request=request)
+
+        # REQUIRED. The client identifier as described in Section 2.2.
+        # https://tools.ietf.org/html/rfc6749#section-2.2
+        if not request.client_id:
+            raise errors.MissingClientIdError(request=request)
+
+        if not self.request_validator.validate_client_id(request.client_id, request):
+            raise errors.InvalidClientIdError(request=request)
+
+        # OPTIONAL. As described in Section 3.1.2.
+        # https://tools.ietf.org/html/rfc6749#section-3.1.2
+        log.debug('Validating redirection uri %s for client %s.',
+                  request.redirect_uri, request.client_id)
+
+        # OPTIONAL. As described in Section 3.1.2.
+        # https://tools.ietf.org/html/rfc6749#section-3.1.2
+        self._handle_redirects(request)
+
+        # Then check for normal errors.
+
+        # If the resource owner denies the access request or if the request
+        # fails for reasons other than a missing or invalid redirection URI,
+        # the authorization server informs the client by adding the following
+        # parameters to the query component of the redirection URI using the
+        # "application/x-www-form-urlencoded" format, per Appendix B.
+        # https://tools.ietf.org/html/rfc6749#appendix-B
+
+        # Note that the correct parameters to be added are automatically
+        # populated through the use of specific exceptions.
+
+        request_info = {}
+        for validator in self.custom_validators.pre_auth:
+            request_info.update(validator(request))
+
+        # REQUIRED.
+        if request.response_type is None:
+            raise errors.MissingResponseTypeError(request=request)
+        # Value MUST be set to "code" or one of the OpenID authorization code including
+        # response_types "code token", "code id_token", "code token id_token"
+        elif 'code' not in request.response_type and request.response_type != 'none':
+            raise errors.UnsupportedResponseTypeError(request=request)
+
+        if not self.request_validator.validate_response_type(request.client_id,
+                                                             request.response_type,
+                                                             request.client, request):
+
+            log.debug('Client %s is not authorized to use response_type %s.',
+                      request.client_id, request.response_type)
+            raise errors.UnauthorizedClientError(request=request)
+
+        # OPTIONAL. Validate PKCE request or reply with "error"/"invalid_request"
+        # https://tools.ietf.org/html/rfc6749#section-4.4.1
+        if self.request_validator.is_pkce_required(request.client_id, request) is True and request.code_challenge is None:
+            raise errors.MissingCodeChallengeError(request=request)
+
+        if request.code_challenge is not None:
+            request_info["code_challenge"] = request.code_challenge
+
+            # OPTIONAL, defaults to "plain" if not present in the request.
+            if request.code_challenge_method is None:
+                request.code_challenge_method = "plain"
+
+            if request.code_challenge_method not in self._code_challenge_methods:
+                raise errors.UnsupportedCodeChallengeMethodError(request=request)
+            request_info["code_challenge_method"] = request.code_challenge_method
+
+        # OPTIONAL. The scope of the access request as described by Section 3.3
+        # https://tools.ietf.org/html/rfc6749#section-3.3
+        self.validate_scopes(request)
+
+        request_info.update({
+            'client_id': request.client_id,
+            'redirect_uri': request.redirect_uri,
+            'response_type': request.response_type,
+            'state': request.state,
+            'request': request
+        })
+
+        for validator in self.custom_validators.post_auth:
+            request_info.update(validator(request))
+
+        return request.scopes, request_info
+
+    def validate_token_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        # REQUIRED. Value MUST be set to "authorization_code".
+        if request.grant_type not in ('authorization_code', 'openid'):
+            raise errors.UnsupportedGrantTypeError(request=request)
+
+        for validator in self.custom_validators.pre_token:
+            validator(request)
+
+        if request.code is None:
+            raise errors.InvalidRequestError(
+                description='Missing code parameter.', request=request)
+
+        for param in ('client_id', 'grant_type', 'redirect_uri'):
+            if param in request.duplicate_params:
+                raise errors.InvalidRequestError(description='Duplicate %s parameter.' % param,
+                                                 request=request)
+
+        if self.request_validator.client_authentication_required(request):
+            # If the client type is confidential or the client was issued client
+            # credentials (or assigned other authentication requirements), the
+            # client MUST authenticate with the authorization server as described
+            # in Section 3.2.1.
+            # https://tools.ietf.org/html/rfc6749#section-3.2.1
+            if not self.request_validator.authenticate_client(request):
+                log.debug('Client authentication failed, %r.', request)
+                raise errors.InvalidClientError(request=request)
+        elif not self.request_validator.authenticate_client_id(request.client_id, request):
+            # REQUIRED, if the client is not authenticating with the
+            # authorization server as described in Section 3.2.1.
+            # https://tools.ietf.org/html/rfc6749#section-3.2.1
+            log.debug('Client authentication failed, %r.', request)
+            raise errors.InvalidClientError(request=request)
+
+        if not hasattr(request.client, 'client_id'):
+            raise NotImplementedError('Authenticate client must set the '
+                                      'request.client.client_id attribute '
+                                      'in authenticate_client.')
+
+        request.client_id = request.client_id or request.client.client_id
+
+        # Ensure client is authorized use of this grant type
+        self.validate_grant_type(request)
+
+        # REQUIRED. The authorization code received from the
+        # authorization server.
+        if not self.request_validator.validate_code(request.client_id,
+                                                    request.code, request.client, request):
+            log.debug('Client, %r (%r), is not allowed access to scopes %r.',
+                      request.client_id, request.client, request.scopes)
+            raise errors.InvalidGrantError(request=request)
+
+        # OPTIONAL. Validate PKCE code_verifier
+        challenge = self.request_validator.get_code_challenge(request.code, request)
+
+        if challenge is not None:
+            if request.code_verifier is None:
+                raise errors.MissingCodeVerifierError(request=request)
+
+            challenge_method = self.request_validator.get_code_challenge_method(request.code, request)
+            if challenge_method is None:
+                raise errors.InvalidGrantError(request=request, description="Challenge method not found")
+
+            if challenge_method not in self._code_challenge_methods:
+                raise errors.ServerError(
+                    description="code_challenge_method {} is not supported.".format(challenge_method),
+                    request=request
+                )
+
+            if not self.validate_code_challenge(challenge,
+                                                challenge_method,
+                                                request.code_verifier):
+                log.debug('request provided a invalid code_verifier.')
+                raise errors.InvalidGrantError(request=request)
+        elif self.request_validator.is_pkce_required(request.client_id, request) is True:
+            if request.code_verifier is None:
+                raise errors.MissingCodeVerifierError(request=request)
+            raise errors.InvalidGrantError(request=request, description="Challenge not found")
+
+        for attr in ('user', 'scopes'):
+            if getattr(request, attr, None) is None:
+                log.debug('request.%s was not set on code validation.', attr)
+
+        # REQUIRED, if the "redirect_uri" parameter was included in the
+        # authorization request as described in Section 4.1.1, and their
+        # values MUST be identical.
+        if request.redirect_uri is None:
+            request.using_default_redirect_uri = True
+            request.redirect_uri = self.request_validator.get_default_redirect_uri(
+                request.client_id, request)
+            log.debug('Using default redirect_uri %s.', request.redirect_uri)
+            if not request.redirect_uri:
+                raise errors.MissingRedirectURIError(request=request)
+        else:
+            request.using_default_redirect_uri = False
+            log.debug('Using provided redirect_uri %s', request.redirect_uri)
+
+        if not self.request_validator.confirm_redirect_uri(request.client_id, request.code,
+                                                           request.redirect_uri, request.client,
+                                                           request):
+            log.debug('Redirect_uri (%r) invalid for client %r (%r).',
+                      request.redirect_uri, request.client_id, request.client)
+            raise errors.MismatchingRedirectURIError(request=request)
+
+        for validator in self.custom_validators.post_token:
+            validator(request)
+
+    def validate_code_challenge(self, challenge, challenge_method, verifier):
+        if challenge_method in self._code_challenge_methods:
+            return self._code_challenge_methods[challenge_method](verifier, challenge)
+        raise NotImplementedError('Unknown challenge_method %s' % challenge_method)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/base.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..d96a2db4fae8f8a73bdda5240afe2f1080e52982
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/base.py
@@ -0,0 +1,265 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+from itertools import chain
+
+from oauthlib.common import add_params_to_uri
+from oauthlib.oauth2.rfc6749 import errors, utils
+from oauthlib.uri_validate import is_absolute_uri
+
+from ..request_validator import RequestValidator
+from ..utils import is_secure_transport
+
+log = logging.getLogger(__name__)
+
+
+class ValidatorsContainer:
+    """
+    Container object for holding custom validator callables to be invoked
+    as part of the grant type `validate_authorization_request()` or
+    `validate_authorization_request()` methods on the various grant types.
+
+    Authorization validators must be callables that take a request object and
+    return a dict, which may contain items to be added to the `request_info`
+    returned from the grant_type after validation.
+
+    Token validators must be callables that take a request object and
+    return None.
+
+    Both authorization validators and token validators may raise OAuth2
+    exceptions if validation conditions fail.
+
+    Authorization validators added to `pre_auth` will be run BEFORE
+    the standard validations (but after the critical ones that raise
+    fatal errors) as part of `validate_authorization_request()`
+
+    Authorization validators added to `post_auth` will be run AFTER
+    the standard validations as part of `validate_authorization_request()`
+
+    Token validators added to `pre_token` will be run BEFORE
+    the standard validations as part of `validate_token_request()`
+
+    Token validators added to `post_token` will be run AFTER
+    the standard validations as part of `validate_token_request()`
+
+    For example:
+
+    >>> def my_auth_validator(request):
+    ...    return {'myval': True}
+    >>> auth_code_grant = AuthorizationCodeGrant(request_validator)
+    >>> auth_code_grant.custom_validators.pre_auth.append(my_auth_validator)
+    >>> def my_token_validator(request):
+    ...     if not request.everything_okay:
+    ...         raise errors.OAuth2Error("uh-oh")
+    >>> auth_code_grant.custom_validators.post_token.append(my_token_validator)
+    """
+
+    def __init__(self, post_auth, post_token,
+                 pre_auth, pre_token):
+        self.pre_auth = pre_auth
+        self.post_auth = post_auth
+        self.pre_token = pre_token
+        self.post_token = post_token
+
+    @property
+    def all_pre(self):
+        return chain(self.pre_auth, self.pre_token)
+
+    @property
+    def all_post(self):
+        return chain(self.post_auth, self.post_token)
+
+
+class GrantTypeBase:
+    error_uri = None
+    request_validator = None
+    default_response_mode = 'fragment'
+    refresh_token = True
+    response_types = ['code']
+
+    def __init__(self, request_validator=None, **kwargs):
+        self.request_validator = request_validator or RequestValidator()
+
+        # Transforms class variables into instance variables:
+        self.response_types = self.response_types
+        self.refresh_token = self.refresh_token
+        self._setup_custom_validators(kwargs)
+        self._code_modifiers = []
+        self._token_modifiers = []
+
+        for kw, val in kwargs.items():
+            setattr(self, kw, val)
+
+    def _setup_custom_validators(self, kwargs):
+        post_auth = kwargs.get('post_auth', [])
+        post_token = kwargs.get('post_token', [])
+        pre_auth = kwargs.get('pre_auth', [])
+        pre_token = kwargs.get('pre_token', [])
+        if not hasattr(self, 'validate_authorization_request'):
+            if post_auth or pre_auth:
+                msg = ("{} does not support authorization validators. Use "
+                       "token validators instead.").format(self.__class__.__name__)
+                raise ValueError(msg)
+            # Using tuples here because they can't be appended to:
+            post_auth, pre_auth = (), ()
+        self.custom_validators = ValidatorsContainer(post_auth, post_token,
+                                                     pre_auth, pre_token)
+
+    def register_response_type(self, response_type):
+        self.response_types.append(response_type)
+
+    def register_code_modifier(self, modifier):
+        self._code_modifiers.append(modifier)
+
+    def register_token_modifier(self, modifier):
+        self._token_modifiers.append(modifier)
+
+    def create_authorization_response(self, request, token_handler):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def create_token_response(self, request, token_handler):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def add_token(self, token, token_handler, request):
+        """
+        :param token:
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        # Only add a hybrid access token on auth step if asked for
+        if request.response_type not in ["token", "code token", "id_token token", "code id_token token"]:
+            return token
+
+        token.update(token_handler.create_token(request, refresh_token=False))
+        return token
+
+    def validate_grant_type(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        client_id = getattr(request, 'client_id', None)
+        if not self.request_validator.validate_grant_type(client_id,
+                                                          request.grant_type, request.client, request):
+            log.debug('Unauthorized from %r (%r) access to grant type %s.',
+                      request.client_id, request.client, request.grant_type)
+            raise errors.UnauthorizedClientError(request=request)
+
+    def validate_scopes(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        if not request.scopes:
+            request.scopes = utils.scope_to_list(request.scope) or utils.scope_to_list(
+                self.request_validator.get_default_scopes(request.client_id, request))
+        log.debug('Validating access to scopes %r for client %r (%r).',
+                  request.scopes, request.client_id, request.client)
+        if not self.request_validator.validate_scopes(request.client_id,
+                                                      request.scopes, request.client, request):
+            raise errors.InvalidScopeError(request=request)
+
+    def prepare_authorization_response(self, request, token, headers, body, status):
+        """Place token according to response mode.
+
+        Base classes can define a default response mode for their authorization
+        response by overriding the static `default_response_mode` member.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token:
+        :param headers:
+        :param body:
+        :param status:
+        """
+        request.response_mode = request.response_mode or self.default_response_mode
+
+        if request.response_mode not in ('query', 'fragment'):
+            log.debug('Overriding invalid response mode %s with %s',
+                      request.response_mode, self.default_response_mode)
+            request.response_mode = self.default_response_mode
+
+        token_items = token.items()
+
+        if request.response_type == 'none':
+            state = token.get('state', None)
+            token_items = [('state', state)] if state else []
+
+        if request.response_mode == 'query':
+            headers['Location'] = add_params_to_uri(
+                request.redirect_uri, token_items, fragment=False)
+            return headers, body, status
+
+        if request.response_mode == 'fragment':
+            headers['Location'] = add_params_to_uri(
+                request.redirect_uri, token_items, fragment=True)
+            return headers, body, status
+
+        raise NotImplementedError(
+            'Subclasses must set a valid default_response_mode')
+
+    def _get_default_headers(self):
+        """Create default headers for grant responses."""
+        return {
+            'Content-Type': 'application/json',
+            'Cache-Control': 'no-store',
+            'Pragma': 'no-cache',
+        }
+
+    def _handle_redirects(self, request):
+        if request.redirect_uri is not None:
+            request.using_default_redirect_uri = False
+            log.debug('Using provided redirect_uri %s', request.redirect_uri)
+            if not is_absolute_uri(request.redirect_uri):
+                raise errors.InvalidRedirectURIError(request=request)
+
+            # The authorization server MUST verify that the redirection URI
+            # to which it will redirect the access token matches a
+            # redirection URI registered by the client as described in
+            # Section 3.1.2.
+            # https://tools.ietf.org/html/rfc6749#section-3.1.2
+            if not self.request_validator.validate_redirect_uri(
+                    request.client_id, request.redirect_uri, request):
+                raise errors.MismatchingRedirectURIError(request=request)
+        else:
+            request.redirect_uri = self.request_validator.get_default_redirect_uri(
+                request.client_id, request)
+            request.using_default_redirect_uri = True
+            log.debug('Using default redirect_uri %s.', request.redirect_uri)
+            if not request.redirect_uri:
+                raise errors.MissingRedirectURIError(request=request)
+            if not is_absolute_uri(request.redirect_uri):
+                raise errors.InvalidRedirectURIError(request=request)
+
+    def _create_cors_headers(self, request):
+        """If CORS is allowed, create the appropriate headers."""
+        if 'origin' not in request.headers:
+            return {}
+
+        origin = request.headers['origin']
+        if not is_secure_transport(origin):
+            log.debug('Origin "%s" is not HTTPS, CORS not allowed.', origin)
+            return {}
+        elif not self.request_validator.is_origin_allowed(
+            request.client_id, origin, request):
+            log.debug('Invalid origin "%s", CORS not allowed.', origin)
+            return {}
+        else:
+            log.debug('Valid origin "%s", injecting CORS headers.', origin)
+            return {'Access-Control-Allow-Origin': origin}
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/client_credentials.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/client_credentials.py
new file mode 100644
index 0000000000000000000000000000000000000000..35c544027ec8b89cd7a5d092e293869de8dd91a5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/client_credentials.py
@@ -0,0 +1,122 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import json
+import logging
+
+from .. import errors
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class ClientCredentialsGrant(GrantTypeBase):
+
+    """`Client Credentials Grant`_
+
+    The client can request an access token using only its client
+    credentials (or other supported means of authentication) when the
+    client is requesting access to the protected resources under its
+    control, or those of another resource owner that have been previously
+    arranged with the authorization server (the method of which is beyond
+    the scope of this specification).
+
+    The client credentials grant type MUST only be used by confidential
+    clients::
+
+        +---------+                                  +---------------+
+        :         :                                  :               :
+        :         :>-- A - Client Authentication --->: Authorization :
+        : Client  :                                  :     Server    :
+        :         :<-- B ---- Access Token ---------<:               :
+        :         :                                  :               :
+        +---------+                                  +---------------+
+
+    Figure 6: Client Credentials Flow
+
+    The flow illustrated in Figure 6 includes the following steps:
+
+    (A)  The client authenticates with the authorization server and
+            requests an access token from the token endpoint.
+
+    (B)  The authorization server authenticates the client, and if valid,
+            issues an access token.
+
+    .. _`Client Credentials Grant`: https://tools.ietf.org/html/rfc6749#section-4.4
+    """
+
+    def create_token_response(self, request, token_handler):
+        """Return token or error in JSON format.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        If the access token request is valid and authorized, the
+        authorization server issues an access token as described in
+        `Section 5.1`_.  A refresh token SHOULD NOT be included.  If the request
+        failed client authentication or is invalid, the authorization server
+        returns an error response as described in `Section 5.2`_.
+
+        .. _`Section 5.1`: https://tools.ietf.org/html/rfc6749#section-5.1
+        .. _`Section 5.2`: https://tools.ietf.org/html/rfc6749#section-5.2
+        """
+        headers = self._get_default_headers()
+        try:
+            log.debug('Validating access token request, %r.', request)
+            self.validate_token_request(request)
+        except errors.OAuth2Error as e:
+            log.debug('Client error in token request. %s.', e)
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request, refresh_token=False)
+
+        for modifier in self._token_modifiers:
+            token = modifier(token)
+
+        self.request_validator.save_token(token, request)
+
+        log.debug('Issuing token to client id %r (%r), %r.',
+                  request.client_id, request.client, token)
+        return headers, json.dumps(token), 200
+
+    def validate_token_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        for validator in self.custom_validators.pre_token:
+            validator(request)
+
+        if not getattr(request, 'grant_type', None):
+            raise errors.InvalidRequestError('Request is missing grant type.',
+                                             request=request)
+
+        if not request.grant_type == 'client_credentials':
+            raise errors.UnsupportedGrantTypeError(request=request)
+
+        for param in ('grant_type', 'scope'):
+            if param in request.duplicate_params:
+                raise errors.InvalidRequestError(description='Duplicate %s parameter.' % param,
+                                                 request=request)
+
+        log.debug('Authenticating client, %r.', request)
+        if not self.request_validator.authenticate_client(request):
+            log.debug('Client authentication failed, %r.', request)
+            raise errors.InvalidClientError(request=request)
+        elif not hasattr(request.client, 'client_id'):
+            raise NotImplementedError('Authenticate client must set the '
+                                      'request.client.client_id attribute '
+                                      'in authenticate_client.')
+        # Ensure client is authorized use of this grant type
+        self.validate_grant_type(request)
+
+        request.client_id = request.client_id or request.client.client_id
+        log.debug('Authorizing access to client %r.', request.client_id)
+        self.validate_scopes(request)
+
+        for validator in self.custom_validators.post_token:
+            validator(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/implicit.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/implicit.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd3bfeb643b1e8e77a04804ef7d3809e07355420
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/implicit.py
@@ -0,0 +1,373 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib import common
+
+from .. import errors
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class ImplicitGrant(GrantTypeBase):
+
+    """`Implicit Grant`_
+
+    The implicit grant type is used to obtain access tokens (it does not
+    support the issuance of refresh tokens) and is optimized for public
+    clients known to operate a particular redirection URI.  These clients
+    are typically implemented in a browser using a scripting language
+    such as JavaScript.
+
+    Unlike the authorization code grant type, in which the client makes
+    separate requests for authorization and for an access token, the
+    client receives the access token as the result of the authorization
+    request.
+
+    The implicit grant type does not include client authentication, and
+    relies on the presence of the resource owner and the registration of
+    the redirection URI.  Because the access token is encoded into the
+    redirection URI, it may be exposed to the resource owner and other
+    applications residing on the same device::
+
+        +----------+
+        | Resource |
+        |  Owner   |
+        |          |
+        +----------+
+             ^
+             |
+            (B)
+        +----|-----+          Client Identifier     +---------------+
+        |         -+----(A)-- & Redirection URI --->|               |
+        |  User-   |                                | Authorization |
+        |  Agent  -|----(B)-- User authenticates -->|     Server    |
+        |          |                                |               |
+        |          |<---(C)--- Redirection URI ----<|               |
+        |          |          with Access Token     +---------------+
+        |          |            in Fragment
+        |          |                                +---------------+
+        |          |----(D)--- Redirection URI ---->|   Web-Hosted  |
+        |          |          without Fragment      |     Client    |
+        |          |                                |    Resource   |
+        |     (F)  |<---(E)------- Script ---------<|               |
+        |          |                                +---------------+
+        +-|--------+
+          |    |
+         (A)  (G) Access Token
+          |    |
+          ^    v
+        +---------+
+        |         |
+        |  Client |
+        |         |
+        +---------+
+
+   Note: The lines illustrating steps (A) and (B) are broken into two
+   parts as they pass through the user-agent.
+
+   Figure 4: Implicit Grant Flow
+
+   The flow illustrated in Figure 4 includes the following steps:
+
+   (A)  The client initiates the flow by directing the resource owner's
+        user-agent to the authorization endpoint.  The client includes
+        its client identifier, requested scope, local state, and a
+        redirection URI to which the authorization server will send the
+        user-agent back once access is granted (or denied).
+
+   (B)  The authorization server authenticates the resource owner (via
+        the user-agent) and establishes whether the resource owner
+        grants or denies the client's access request.
+
+   (C)  Assuming the resource owner grants access, the authorization
+        server redirects the user-agent back to the client using the
+        redirection URI provided earlier.  The redirection URI includes
+        the access token in the URI fragment.
+
+   (D)  The user-agent follows the redirection instructions by making a
+        request to the web-hosted client resource (which does not
+        include the fragment per [RFC2616]).  The user-agent retains the
+        fragment information locally.
+
+   (E)  The web-hosted client resource returns a web page (typically an
+        HTML document with an embedded script) capable of accessing the
+        full redirection URI including the fragment retained by the
+        user-agent, and extracting the access token (and other
+        parameters) contained in the fragment.
+
+   (F)  The user-agent executes the script provided by the web-hosted
+        client resource locally, which extracts the access token.
+
+   (G)  The user-agent passes the access token to the client.
+
+    See `Section 10.3`_ and `Section 10.16`_ for important security considerations
+    when using the implicit grant.
+
+    .. _`Implicit Grant`: https://tools.ietf.org/html/rfc6749#section-4.2
+    .. _`Section 10.3`: https://tools.ietf.org/html/rfc6749#section-10.3
+    .. _`Section 10.16`: https://tools.ietf.org/html/rfc6749#section-10.16
+    """
+
+    response_types = ['token']
+    grant_allows_refresh_token = False
+
+    def create_authorization_response(self, request, token_handler):
+        """Create an authorization response.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        The client constructs the request URI by adding the following
+        parameters to the query component of the authorization endpoint URI
+        using the "application/x-www-form-urlencoded" format, per `Appendix B`_:
+
+        response_type
+                REQUIRED.  Value MUST be set to "token" for standard OAuth2 implicit flow
+                           or "id_token token" or just "id_token" for OIDC implicit flow
+
+        client_id
+                REQUIRED.  The client identifier as described in `Section 2.2`_.
+
+        redirect_uri
+                OPTIONAL.  As described in `Section 3.1.2`_.
+
+        scope
+                OPTIONAL.  The scope of the access request as described by
+                `Section 3.3`_.
+
+        state
+                RECOMMENDED.  An opaque value used by the client to maintain
+                state between the request and callback.  The authorization
+                server includes this value when redirecting the user-agent back
+                to the client.  The parameter SHOULD be used for preventing
+                cross-site request forgery as described in `Section 10.12`_.
+
+        The authorization server validates the request to ensure that all
+        required parameters are present and valid.  The authorization server
+        MUST verify that the redirection URI to which it will redirect the
+        access token matches a redirection URI registered by the client as
+        described in `Section 3.1.2`_.
+
+        .. _`Section 2.2`: https://tools.ietf.org/html/rfc6749#section-2.2
+        .. _`Section 3.1.2`: https://tools.ietf.org/html/rfc6749#section-3.1.2
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 10.12`: https://tools.ietf.org/html/rfc6749#section-10.12
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        """
+        return self.create_token_response(request, token_handler)
+
+    def create_token_response(self, request, token_handler):
+        """Return token or error embedded in the URI fragment.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        If the resource owner grants the access request, the authorization
+        server issues an access token and delivers it to the client by adding
+        the following parameters to the fragment component of the redirection
+        URI using the "application/x-www-form-urlencoded" format, per
+        `Appendix B`_:
+
+        access_token
+                REQUIRED.  The access token issued by the authorization server.
+
+        token_type
+                REQUIRED.  The type of the token issued as described in
+                `Section 7.1`_.  Value is case insensitive.
+
+        expires_in
+                RECOMMENDED.  The lifetime in seconds of the access token.  For
+                example, the value "3600" denotes that the access token will
+                expire in one hour from the time the response was generated.
+                If omitted, the authorization server SHOULD provide the
+                expiration time via other means or document the default value.
+
+        scope
+                OPTIONAL, if identical to the scope requested by the client;
+                otherwise, REQUIRED.  The scope of the access token as
+                described by `Section 3.3`_.
+
+        state
+                REQUIRED if the "state" parameter was present in the client
+                authorization request.  The exact value received from the
+                client.
+
+        The authorization server MUST NOT issue a refresh token.
+
+        .. _`Appendix B`: https://tools.ietf.org/html/rfc6749#appendix-B
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 7.1`: https://tools.ietf.org/html/rfc6749#section-7.1
+        """
+        try:
+            self.validate_token_request(request)
+
+        # If the request fails due to a missing, invalid, or mismatching
+        # redirection URI, or if the client identifier is missing or invalid,
+        # the authorization server SHOULD inform the resource owner of the
+        # error and MUST NOT automatically redirect the user-agent to the
+        # invalid redirection URI.
+        except errors.FatalClientError as e:
+            log.debug('Fatal client error during validation of %r. %r.',
+                      request, e)
+            raise
+
+        # If the resource owner denies the access request or if the request
+        # fails for reasons other than a missing or invalid redirection URI,
+        # the authorization server informs the client by adding the following
+        # parameters to the fragment component of the redirection URI using the
+        # "application/x-www-form-urlencoded" format, per Appendix B:
+        # https://tools.ietf.org/html/rfc6749#appendix-B
+        except errors.OAuth2Error as e:
+            log.debug('Client error during validation of %r. %r.', request, e)
+            return {'Location': common.add_params_to_uri(request.redirect_uri, e.twotuples,
+                                                         fragment=True)}, None, 302
+
+        # In OIDC implicit flow it is possible to have a request_type that does not include the access_token!
+        # "id_token token" - return the access token and the id token
+        # "id_token" - don't return the access token
+        token = token_handler.create_token(request, refresh_token=False) if 'token' in request.response_type.split() else {}
+
+        if request.state is not None:
+            token['state'] = request.state
+
+        for modifier in self._token_modifiers:
+            token = modifier(token, token_handler, request)
+
+        # In OIDC implicit flow it is possible to have a request_type that does
+        # not include the access_token! In this case there is no need to save a token.
+        if "token" in request.response_type.split():
+            self.request_validator.save_token(token, request)
+
+        return self.prepare_authorization_response(
+            request, token, {}, None, 302)
+
+    def validate_authorization_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        return self.validate_token_request(request)
+
+    def validate_token_request(self, request):
+        """Check the token request for normal and fatal errors.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        This method is very similar to validate_authorization_request in
+        the AuthorizationCodeGrant but differ in a few subtle areas.
+
+        A normal error could be a missing response_type parameter or the client
+        attempting to access scope it is not allowed to ask authorization for.
+        Normal errors can safely be included in the redirection URI and
+        sent back to the client.
+
+        Fatal errors occur when the client_id or redirect_uri is invalid or
+        missing. These must be caught by the provider and handled, how this
+        is done is outside of the scope of OAuthLib but showing an error
+        page describing the issue is a good idea.
+        """
+
+        # First check for fatal errors
+
+        # If the request fails due to a missing, invalid, or mismatching
+        # redirection URI, or if the client identifier is missing or invalid,
+        # the authorization server SHOULD inform the resource owner of the
+        # error and MUST NOT automatically redirect the user-agent to the
+        # invalid redirection URI.
+
+        # First check duplicate parameters
+        for param in ('client_id', 'response_type', 'redirect_uri', 'scope', 'state'):
+            try:
+                duplicate_params = request.duplicate_params
+            except ValueError:
+                raise errors.InvalidRequestFatalError(description='Unable to parse query string', request=request)
+            if param in duplicate_params:
+                raise errors.InvalidRequestFatalError(description='Duplicate %s parameter.' % param, request=request)
+
+        # REQUIRED. The client identifier as described in Section 2.2.
+        # https://tools.ietf.org/html/rfc6749#section-2.2
+        if not request.client_id:
+            raise errors.MissingClientIdError(request=request)
+
+        if not self.request_validator.validate_client_id(request.client_id, request):
+            raise errors.InvalidClientIdError(request=request)
+
+        # OPTIONAL. As described in Section 3.1.2.
+        # https://tools.ietf.org/html/rfc6749#section-3.1.2
+        self._handle_redirects(request)
+
+        # Then check for normal errors.
+
+        request_info = self._run_custom_validators(request,
+                                                   self.custom_validators.all_pre)
+
+        # If the resource owner denies the access request or if the request
+        # fails for reasons other than a missing or invalid redirection URI,
+        # the authorization server informs the client by adding the following
+        # parameters to the fragment component of the redirection URI using the
+        # "application/x-www-form-urlencoded" format, per Appendix B.
+        # https://tools.ietf.org/html/rfc6749#appendix-B
+
+        # Note that the correct parameters to be added are automatically
+        # populated through the use of specific exceptions
+
+        # REQUIRED.
+        if request.response_type is None:
+            raise errors.MissingResponseTypeError(request=request)
+        # Value MUST be one of our registered types: "token" by default or if using OIDC "id_token" or "id_token token"
+        elif not set(request.response_type.split()).issubset(self.response_types):
+            raise errors.UnsupportedResponseTypeError(request=request)
+
+        log.debug('Validating use of response_type token for client %r (%r).',
+                  request.client_id, request.client)
+        if not self.request_validator.validate_response_type(request.client_id,
+                                                             request.response_type,
+                                                             request.client, request):
+
+            log.debug('Client %s is not authorized to use response_type %s.',
+                      request.client_id, request.response_type)
+            raise errors.UnauthorizedClientError(request=request)
+
+        # OPTIONAL. The scope of the access request as described by Section 3.3
+        # https://tools.ietf.org/html/rfc6749#section-3.3
+        self.validate_scopes(request)
+
+        request_info.update({
+            'client_id': request.client_id,
+            'redirect_uri': request.redirect_uri,
+            'response_type': request.response_type,
+            'state': request.state,
+            'request': request,
+        })
+
+        request_info = self._run_custom_validators(
+            request,
+            self.custom_validators.all_post,
+            request_info
+        )
+
+        return request.scopes, request_info
+
+    def _run_custom_validators(self,
+                               request,
+                               validations,
+                               request_info=None):
+        # Make a copy so we don't modify the existing request_info dict
+        request_info = {} if request_info is None else request_info.copy()
+        # For implicit grant, auth_validators and token_validators are
+        # basically equivalent since the token is returned from the
+        # authorization endpoint.
+        for validator in validations:
+            result = validator(request)
+            if result is not None:
+                request_info.update(result)
+        return request_info
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/refresh_token.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/refresh_token.py
new file mode 100644
index 0000000000000000000000000000000000000000..43bf55ac908a7fe93ceff81b10c93a4418d8851c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/refresh_token.py
@@ -0,0 +1,139 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import json
+import logging
+
+from .. import errors, utils
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class RefreshTokenGrant(GrantTypeBase):
+
+    """`Refresh token grant`_
+
+    .. _`Refresh token grant`: https://tools.ietf.org/html/rfc6749#section-6
+    """
+
+    def __init__(self, request_validator=None,
+                 issue_new_refresh_tokens=True,
+                 **kwargs):
+        super().__init__(
+            request_validator,
+            issue_new_refresh_tokens=issue_new_refresh_tokens,
+            **kwargs)
+
+    def create_token_response(self, request, token_handler):
+        """Create a new access token from a refresh_token.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        If valid and authorized, the authorization server issues an access
+        token as described in `Section 5.1`_. If the request failed
+        verification or is invalid, the authorization server returns an error
+        response as described in `Section 5.2`_.
+
+        The authorization server MAY issue a new refresh token, in which case
+        the client MUST discard the old refresh token and replace it with the
+        new refresh token. The authorization server MAY revoke the old
+        refresh token after issuing a new refresh token to the client. If a
+        new refresh token is issued, the refresh token scope MUST be
+        identical to that of the refresh token included by the client in the
+        request.
+
+        .. _`Section 5.1`: https://tools.ietf.org/html/rfc6749#section-5.1
+        .. _`Section 5.2`: https://tools.ietf.org/html/rfc6749#section-5.2
+        """
+        headers = self._get_default_headers()
+        try:
+            log.debug('Validating refresh token request, %r.', request)
+            self.validate_token_request(request)
+        except errors.OAuth2Error as e:
+            log.debug('Client error in token request, %s.', e)
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request,
+                                           refresh_token=self.issue_new_refresh_tokens)
+
+        for modifier in self._token_modifiers:
+            token = modifier(token, token_handler, request)
+
+        self.request_validator.save_token(token, request)
+
+        log.debug('Issuing new token to client id %r (%r), %r.',
+                  request.client_id, request.client, token)
+        headers.update(self._create_cors_headers(request))
+        return headers, json.dumps(token), 200
+
+    def validate_token_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        # REQUIRED. Value MUST be set to "refresh_token".
+        if request.grant_type != 'refresh_token':
+            raise errors.UnsupportedGrantTypeError(request=request)
+
+        for validator in self.custom_validators.pre_token:
+            validator(request)
+
+        if request.refresh_token is None:
+            raise errors.InvalidRequestError(
+                description='Missing refresh token parameter.',
+                request=request)
+
+        # Because refresh tokens are typically long-lasting credentials used to
+        # request additional access tokens, the refresh token is bound to the
+        # client to which it was issued.  If the client type is confidential or
+        # the client was issued client credentials (or assigned other
+        # authentication requirements), the client MUST authenticate with the
+        # authorization server as described in Section 3.2.1.
+        # https://tools.ietf.org/html/rfc6749#section-3.2.1
+        if self.request_validator.client_authentication_required(request):
+            log.debug('Authenticating client, %r.', request)
+            if not self.request_validator.authenticate_client(request):
+                log.debug('Invalid client (%r), denying access.', request)
+                raise errors.InvalidClientError(request=request)
+            # Ensure that request.client_id is set.
+            if request.client_id is None and request.client is not None:
+                request.client_id = request.client.client_id
+        elif not self.request_validator.authenticate_client_id(request.client_id, request):
+            log.debug('Client authentication failed, %r.', request)
+            raise errors.InvalidClientError(request=request)
+
+        # Ensure client is authorized use of this grant type
+        self.validate_grant_type(request)
+
+        # REQUIRED. The refresh token issued to the client.
+        log.debug('Validating refresh token %s for client %r.',
+                  request.refresh_token, request.client)
+        if not self.request_validator.validate_refresh_token(
+                request.refresh_token, request.client, request):
+            log.debug('Invalid refresh token, %s, for client %r.',
+                      request.refresh_token, request.client)
+            raise errors.InvalidGrantError(request=request)
+
+        original_scopes = utils.scope_to_list(
+            self.request_validator.get_original_scopes(
+                request.refresh_token, request))
+
+        if request.scope:
+            request.scopes = utils.scope_to_list(request.scope)
+            if (not all(s in original_scopes for s in request.scopes)
+                and not self.request_validator.is_within_original_scope(
+                    request.scopes, request.refresh_token, request)):
+                log.debug('Refresh token %s lack requested scopes, %r.',
+                          request.refresh_token, request.scopes)
+                raise errors.InvalidScopeError(request=request)
+        else:
+            request.scopes = original_scopes
+
+        for validator in self.custom_validators.post_token:
+            validator(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/resource_owner_password_credentials.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/resource_owner_password_credentials.py
new file mode 100644
index 0000000000000000000000000000000000000000..55d928709a3b80a4a3af7b95a5854a78d312af2a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/grant_types/resource_owner_password_credentials.py
@@ -0,0 +1,198 @@
+"""
+oauthlib.oauth2.rfc6749.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import json
+import logging
+
+from .. import errors
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class ResourceOwnerPasswordCredentialsGrant(GrantTypeBase):
+
+    """`Resource Owner Password Credentials Grant`_
+
+    The resource owner password credentials grant type is suitable in
+    cases where the resource owner has a trust relationship with the
+    client, such as the device operating system or a highly privileged
+    application.  The authorization server should take special care when
+    enabling this grant type and only allow it when other flows are not
+    viable.
+
+    This grant type is suitable for clients capable of obtaining the
+    resource owner's credentials (username and password, typically using
+    an interactive form).  It is also used to migrate existing clients
+    using direct authentication schemes such as HTTP Basic or Digest
+    authentication to OAuth by converting the stored credentials to an
+    access token::
+
+            +----------+
+            | Resource |
+            |  Owner   |
+            |          |
+            +----------+
+                 v
+                 |    Resource Owner
+                (A) Password Credentials
+                 |
+                 v
+            +---------+                                  +---------------+
+            |         |>--(B)---- Resource Owner ------->|               |
+            |         |         Password Credentials     | Authorization |
+            | Client  |                                  |     Server    |
+            |         |<--(C)---- Access Token ---------<|               |
+            |         |    (w/ Optional Refresh Token)   |               |
+            +---------+                                  +---------------+
+
+    Figure 5: Resource Owner Password Credentials Flow
+
+    The flow illustrated in Figure 5 includes the following steps:
+
+    (A)  The resource owner provides the client with its username and
+            password.
+
+    (B)  The client requests an access token from the authorization
+            server's token endpoint by including the credentials received
+            from the resource owner.  When making the request, the client
+            authenticates with the authorization server.
+
+    (C)  The authorization server authenticates the client and validates
+            the resource owner credentials, and if valid, issues an access
+            token.
+
+    .. _`Resource Owner Password Credentials Grant`: https://tools.ietf.org/html/rfc6749#section-4.3
+    """
+
+    def create_token_response(self, request, token_handler):
+        """Return token or error in json format.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        If the access token request is valid and authorized, the
+        authorization server issues an access token and optional refresh
+        token as described in `Section 5.1`_.  If the request failed client
+        authentication or is invalid, the authorization server returns an
+        error response as described in `Section 5.2`_.
+
+        .. _`Section 5.1`: https://tools.ietf.org/html/rfc6749#section-5.1
+        .. _`Section 5.2`: https://tools.ietf.org/html/rfc6749#section-5.2
+        """
+        headers = self._get_default_headers()
+        try:
+            if self.request_validator.client_authentication_required(request):
+                log.debug('Authenticating client, %r.', request)
+                if not self.request_validator.authenticate_client(request):
+                    log.debug('Client authentication failed, %r.', request)
+                    raise errors.InvalidClientError(request=request)
+            elif not self.request_validator.authenticate_client_id(request.client_id, request):
+                log.debug('Client authentication failed, %r.', request)
+                raise errors.InvalidClientError(request=request)
+            log.debug('Validating access token request, %r.', request)
+            self.validate_token_request(request)
+        except errors.OAuth2Error as e:
+            log.debug('Client error in token request, %s.', e)
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request, self.refresh_token)
+
+        for modifier in self._token_modifiers:
+            token = modifier(token)
+
+        self.request_validator.save_token(token, request)
+
+        log.debug('Issuing token %r to client id %r (%r) and username %s.',
+                  token, request.client_id, request.client, request.username)
+        return headers, json.dumps(token), 200
+
+    def validate_token_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        The client makes a request to the token endpoint by adding the
+        following parameters using the "application/x-www-form-urlencoded"
+        format per Appendix B with a character encoding of UTF-8 in the HTTP
+        request entity-body:
+
+        grant_type
+                REQUIRED.  Value MUST be set to "password".
+
+        username
+                REQUIRED.  The resource owner username.
+
+        password
+                REQUIRED.  The resource owner password.
+
+        scope
+                OPTIONAL.  The scope of the access request as described by
+                `Section 3.3`_.
+
+        If the client type is confidential or the client was issued client
+        credentials (or assigned other authentication requirements), the
+        client MUST authenticate with the authorization server as described
+        in `Section 3.2.1`_.
+
+        The authorization server MUST:
+
+        o  require client authentication for confidential clients or for any
+            client that was issued client credentials (or with other
+            authentication requirements),
+
+        o  authenticate the client if client authentication is included, and
+
+        o  validate the resource owner password credentials using its
+            existing password validation algorithm.
+
+        Since this access token request utilizes the resource owner's
+        password, the authorization server MUST protect the endpoint against
+        brute force attacks (e.g., using rate-limitation or generating
+        alerts).
+
+        .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+        .. _`Section 3.2.1`: https://tools.ietf.org/html/rfc6749#section-3.2.1
+        """
+        for validator in self.custom_validators.pre_token:
+            validator(request)
+
+        for param in ('grant_type', 'username', 'password'):
+            if not getattr(request, param, None):
+                raise errors.InvalidRequestError(
+                    'Request is missing %s parameter.' % param, request=request)
+
+        for param in ('grant_type', 'username', 'password', 'scope'):
+            if param in request.duplicate_params:
+                raise errors.InvalidRequestError(description='Duplicate %s parameter.' % param, request=request)
+
+        # This error should rarely (if ever) occur if requests are routed to
+        # grant type handlers based on the grant_type parameter.
+        if not request.grant_type == 'password':
+            raise errors.UnsupportedGrantTypeError(request=request)
+
+        log.debug('Validating username %s.', request.username)
+        if not self.request_validator.validate_user(request.username,
+                                                    request.password, request.client, request):
+            raise errors.InvalidGrantError(
+                'Invalid credentials given.', request=request)
+        elif not hasattr(request.client, 'client_id'):
+            raise NotImplementedError(
+                'Validate user must set the '
+                'request.client.client_id attribute '
+                'in authenticate_client.')
+        log.debug('Authorizing access to user %r.', request.user)
+
+        # Ensure client is authorized use of this grant type
+        self.validate_grant_type(request)
+
+        if request.client:
+            request.client_id = request.client_id or request.client.client_id
+        self.validate_scopes(request)
+
+        for validator in self.custom_validators.post_token:
+            validator(request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/parameters.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/parameters.py
new file mode 100644
index 0000000000000000000000000000000000000000..8268ef927cc2d174f44a00e60cf07156fb223db7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/parameters.py
@@ -0,0 +1,528 @@
+"""
+oauthlib.oauth2.rfc6749.parameters
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module contains methods related to `Section 4`_ of the OAuth 2 RFC.
+
+.. _`Section 4`: https://tools.ietf.org/html/rfc6749#section-4
+"""
+import json
+import os
+import time
+import urllib.parse as urlparse
+
+from oauthlib.common import add_params_to_qs, add_params_to_uri
+from oauthlib.signals import scope_changed
+
+from .errors import (
+    InsecureTransportError, MismatchingStateError, MissingCodeError,
+    MissingTokenError, MissingTokenTypeError, raise_from_error,
+)
+from .tokens import OAuth2Token
+from .utils import is_secure_transport, list_to_scope, scope_to_list
+
+
+def prepare_grant_uri(uri, client_id, response_type, redirect_uri=None,
+                      scope=None, state=None, code_challenge=None, code_challenge_method='plain', **kwargs):
+    """Prepare the authorization grant request URI.
+
+    The client constructs the request URI by adding the following
+    parameters to the query component of the authorization endpoint URI
+    using the ``application/x-www-form-urlencoded`` format as defined by
+    [`W3C.REC-html401-19991224`_]:
+
+    :param uri:
+    :param client_id: The client identifier as described in `Section 2.2`_.
+    :param response_type: To indicate which OAuth 2 grant/flow is required,
+                          "code" and "token".
+    :param redirect_uri: The client provided URI to redirect back to after
+                         authorization as described in `Section 3.1.2`_.
+    :param scope: The scope of the access request as described by
+                  `Section 3.3`_.
+    :param state: An opaque value used by the client to maintain
+                  state between the request and callback.  The authorization
+                  server includes this value when redirecting the user-agent
+                  back to the client.  The parameter SHOULD be used for
+                  preventing cross-site request forgery as described in
+                  `Section 10.12`_.
+    :param code_challenge: PKCE parameter. A challenge derived from the
+                           code_verifier that is sent in the authorization
+                           request, to be verified against later.
+    :param code_challenge_method: PKCE parameter. A method that was used to derive the
+                                  code_challenge. Defaults to "plain" if not present in the request.
+    :param kwargs: Extra arguments to embed in the grant/authorization URL.
+
+    An example of an authorization code grant authorization URL:
+
+    .. code-block:: http
+
+        GET /authorize?response_type=code&client_id=s6BhdRkqt3&state=xyz
+            &code_challenge=kjasBS523KdkAILD2k78NdcJSk2k3KHG6&code_challenge_method=S256
+            &redirect_uri=https%3A%2F%2Fclient%2Eexample%2Ecom%2Fcb HTTP/1.1
+        Host: server.example.com
+
+    .. _`W3C.REC-html401-19991224`: https://tools.ietf.org/html/rfc6749#ref-W3C.REC-html401-19991224
+    .. _`Section 2.2`: https://tools.ietf.org/html/rfc6749#section-2.2
+    .. _`Section 3.1.2`: https://tools.ietf.org/html/rfc6749#section-3.1.2
+    .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+    .. _`section 10.12`: https://tools.ietf.org/html/rfc6749#section-10.12
+    """
+    if not is_secure_transport(uri):
+        raise InsecureTransportError()
+
+    params = [(('response_type', response_type)),
+              (('client_id', client_id))]
+
+    if redirect_uri:
+        params.append(('redirect_uri', redirect_uri))
+    if scope:
+        params.append(('scope', list_to_scope(scope)))
+    if state:
+        params.append(('state', state))
+    if code_challenge is not None:
+        params.append(('code_challenge', code_challenge))
+        params.append(('code_challenge_method', code_challenge_method))
+
+    for k in kwargs:
+        if kwargs[k]:
+            params.append((str(k), kwargs[k]))
+
+    return add_params_to_uri(uri, params)
+
+
+def prepare_token_request(grant_type, body='', include_client_id=True, code_verifier=None, **kwargs):
+    """Prepare the access token request.
+
+    The client makes a request to the token endpoint by adding the
+    following parameters using the ``application/x-www-form-urlencoded``
+    format in the HTTP request entity-body:
+
+    :param grant_type: To indicate grant type being used, i.e. "password",
+                       "authorization_code" or "client_credentials".
+
+    :param body: Existing request body (URL encoded string) to embed parameters
+                 into. This may contain extra parameters. Default ''.
+
+    :param include_client_id: `True` (default) to send the `client_id` in the
+                              body of the upstream request. This is required
+                              if the client is not authenticating with the
+                              authorization server as described in
+                              `Section 3.2.1`_.
+    :type include_client_id: Boolean
+
+    :param client_id: Unicode client identifier. Will only appear if
+                      `include_client_id` is True. *
+
+    :param client_secret: Unicode client secret. Will only appear if set to a
+                          value that is not `None`. Invoking this function with
+                          an empty string will send an empty `client_secret`
+                          value to the server. *
+
+    :param code: If using authorization_code grant, pass the previously
+                 obtained authorization code as the ``code`` argument. *
+
+    :param redirect_uri: If the "redirect_uri" parameter was included in the
+                         authorization request as described in
+                         `Section 4.1.1`_, and their values MUST be identical. *
+
+    :param code_verifier: PKCE parameter. A cryptographically random string that is used to correlate the
+                          authorization request to the token request.
+
+    :param kwargs: Extra arguments to embed in the request body.
+
+    Parameters marked with a `*` above are not explicit arguments in the
+    function signature, but are specially documented arguments for items
+    appearing in the generic `**kwargs` keyworded input.
+
+    An example of an authorization code token request body:
+
+    .. code-block:: http
+
+        grant_type=authorization_code&code=SplxlOBeZQQYbYS6WxSbIA
+        &redirect_uri=https%3A%2F%2Fclient%2Eexample%2Ecom%2Fcb
+
+    .. _`Section 4.1.1`: https://tools.ietf.org/html/rfc6749#section-4.1.1
+    """
+    params = [('grant_type', grant_type)]
+
+    if 'scope' in kwargs:
+        kwargs['scope'] = list_to_scope(kwargs['scope'])
+
+    # pull the `client_id` out of the kwargs.
+    client_id = kwargs.pop('client_id', None)
+    if include_client_id and client_id is not None:
+        params.append(('client_id', client_id))
+
+    # use code_verifier if code_challenge was passed in the authorization request
+    if code_verifier is not None:
+        params.append(('code_verifier', code_verifier))
+
+    # the kwargs iteration below only supports including boolean truth (truthy)
+    # values, but some servers may require an empty string for `client_secret`
+    client_secret = kwargs.pop('client_secret', None)
+    if client_secret is not None:
+        params.append(('client_secret', client_secret))
+
+    # this handles: `code`, `redirect_uri`, and other undocumented params
+    for k in kwargs:
+        if kwargs[k]:
+            params.append((str(k), kwargs[k]))
+
+    return add_params_to_qs(body, params)
+
+
+def prepare_token_revocation_request(url, token, token_type_hint="access_token",
+        callback=None, body='', **kwargs):
+    """Prepare a token revocation request.
+
+    The client constructs the request by including the following parameters
+    using the ``application/x-www-form-urlencoded`` format in the HTTP request
+    entity-body:
+
+    :param token: REQUIRED.  The token that the client wants to get revoked.
+
+    :param token_type_hint: OPTIONAL.  A hint about the type of the token
+                            submitted for revocation. Clients MAY pass this
+                            parameter in order to help the authorization server
+                            to optimize the token lookup.  If the server is
+                            unable to locate the token using the given hint, it
+                            MUST extend its search across all of its supported
+                            token types.  An authorization server MAY ignore
+                            this parameter, particularly if it is able to detect
+                            the token type automatically.
+
+    This specification defines two values for `token_type_hint`:
+
+        * access_token: An access token as defined in [RFC6749],
+             `Section 1.4`_
+
+        * refresh_token: A refresh token as defined in [RFC6749],
+             `Section 1.5`_
+
+        Specific implementations, profiles, and extensions of this
+        specification MAY define other values for this parameter using the
+        registry defined in `Section 4.1.2`_.
+
+    .. _`Section 1.4`: https://tools.ietf.org/html/rfc6749#section-1.4
+    .. _`Section 1.5`: https://tools.ietf.org/html/rfc6749#section-1.5
+    .. _`Section 4.1.2`: https://tools.ietf.org/html/rfc7009#section-4.1.2
+
+    """
+    if not is_secure_transport(url):
+        raise InsecureTransportError()
+
+    params = [('token', token)]
+
+    if token_type_hint:
+        params.append(('token_type_hint', token_type_hint))
+
+    for k in kwargs:
+        if kwargs[k]:
+            params.append((str(k), kwargs[k]))
+
+    headers = {'Content-Type': 'application/x-www-form-urlencoded'}
+
+    if callback:
+        params.append(('callback', callback))
+        return add_params_to_uri(url, params), headers, body
+    else:
+        return url, headers, add_params_to_qs(body, params)
+
+
+def parse_authorization_code_response(uri, state=None):
+    """Parse authorization grant response URI into a dict.
+
+    If the resource owner grants the access request, the authorization
+    server issues an authorization code and delivers it to the client by
+    adding the following parameters to the query component of the
+    redirection URI using the ``application/x-www-form-urlencoded`` format:
+
+    **code**
+            REQUIRED.  The authorization code generated by the
+            authorization server.  The authorization code MUST expire
+            shortly after it is issued to mitigate the risk of leaks.  A
+            maximum authorization code lifetime of 10 minutes is
+            RECOMMENDED.  The client MUST NOT use the authorization code
+            more than once.  If an authorization code is used more than
+            once, the authorization server MUST deny the request and SHOULD
+            revoke (when possible) all tokens previously issued based on
+            that authorization code.  The authorization code is bound to
+            the client identifier and redirection URI.
+
+    **state**
+            REQUIRED if the "state" parameter was present in the client
+            authorization request.  The exact value received from the
+            client.
+
+    :param uri: The full redirect URL back to the client.
+    :param state: The state parameter from the authorization request.
+
+    For example, the authorization server redirects the user-agent by
+    sending the following HTTP response:
+
+    .. code-block:: http
+
+        HTTP/1.1 302 Found
+        Location: https://client.example.com/cb?code=SplxlOBeZQQYbYS6WxSbIA
+                &state=xyz
+
+    """
+    if not is_secure_transport(uri):
+        raise InsecureTransportError()
+
+    query = urlparse.urlparse(uri).query
+    params = dict(urlparse.parse_qsl(query))
+
+    if state and params.get('state') != state:
+        raise MismatchingStateError()
+
+    if 'error' in params:
+        raise_from_error(params.get('error'), params)
+
+    if 'code' not in params:
+        raise MissingCodeError("Missing code parameter in response.")
+
+    return params
+
+
+def parse_implicit_response(uri, state=None, scope=None):
+    """Parse the implicit token response URI into a dict.
+
+    If the resource owner grants the access request, the authorization
+    server issues an access token and delivers it to the client by adding
+    the following parameters to the fragment component of the redirection
+    URI using the ``application/x-www-form-urlencoded`` format:
+
+    **access_token**
+            REQUIRED.  The access token issued by the authorization server.
+
+    **token_type**
+            REQUIRED.  The type of the token issued as described in
+            Section 7.1.  Value is case insensitive.
+
+    **expires_in**
+            RECOMMENDED.  The lifetime in seconds of the access token.  For
+            example, the value "3600" denotes that the access token will
+            expire in one hour from the time the response was generated.
+            If omitted, the authorization server SHOULD provide the
+            expiration time via other means or document the default value.
+
+    **scope**
+            OPTIONAL, if identical to the scope requested by the client,
+            otherwise REQUIRED.  The scope of the access token as described
+            by Section 3.3.
+
+    **state**
+            REQUIRED if the "state" parameter was present in the client
+            authorization request.  The exact value received from the
+            client.
+
+    :param uri:
+    :param state:
+    :param scope:
+
+    Similar to the authorization code response, but with a full token provided
+    in the URL fragment:
+
+    .. code-block:: http
+
+        HTTP/1.1 302 Found
+        Location: http://example.com/cb#access_token=2YotnFZFEjr1zCsicMWpAA
+                &state=xyz&token_type=example&expires_in=3600
+    """
+    if not is_secure_transport(uri):
+        raise InsecureTransportError()
+
+    fragment = urlparse.urlparse(uri).fragment
+    params = dict(urlparse.parse_qsl(fragment, keep_blank_values=True))
+
+    if 'scope' in params:
+        params['scope'] = scope_to_list(params['scope'])
+
+    vin, vat, v_at = parse_expires(params)
+    if vin:
+        params['expires_in'] = vin
+    elif 'expires_in' in params:
+        params.pop('expires_in')
+    if vat:
+        params['expires_at'] = vat
+    elif 'expires_at' in params:
+        params.pop('expires_at')
+
+    if state and params.get('state') != state:
+        raise ValueError("Mismatching or missing state in params.")
+
+    params = OAuth2Token(params, old_scope=scope)
+    validate_token_parameters(params)
+    return params
+
+
+def parse_token_response(body, scope=None):
+    """Parse the JSON token response body into a dict.
+
+    The authorization server issues an access token and optional refresh
+    token, and constructs the response by adding the following parameters
+    to the entity body of the HTTP response with a 200 (OK) status code:
+
+    access_token
+            REQUIRED.  The access token issued by the authorization server.
+    token_type
+            REQUIRED.  The type of the token issued as described in
+            `Section 7.1`_.  Value is case insensitive.
+    expires_in
+            RECOMMENDED.  The lifetime in seconds of the access token.  For
+            example, the value "3600" denotes that the access token will
+            expire in one hour from the time the response was generated.
+            If omitted, the authorization server SHOULD provide the
+            expiration time via other means or document the default value.
+    refresh_token
+            OPTIONAL.  The refresh token which can be used to obtain new
+            access tokens using the same authorization grant as described
+            in `Section 6`_.
+    scope
+            OPTIONAL, if identical to the scope requested by the client,
+            otherwise REQUIRED.  The scope of the access token as described
+            by `Section 3.3`_.
+
+    The parameters are included in the entity body of the HTTP response
+    using the "application/json" media type as defined by [`RFC4627`_].  The
+    parameters are serialized into a JSON structure by adding each
+    parameter at the highest structure level.  Parameter names and string
+    values are included as JSON strings.  Numerical values are included
+    as JSON numbers.  The order of parameters does not matter and can
+    vary.
+
+    :param body: The full json encoded response body.
+    :param scope: The scope requested during authorization.
+
+    For example:
+
+    .. code-block:: http
+
+        HTTP/1.1 200 OK
+        Content-Type: application/json
+        Cache-Control: no-store
+        Pragma: no-cache
+
+        {
+            "access_token":"2YotnFZFEjr1zCsicMWpAA",
+            "token_type":"example",
+            "expires_in":3600,
+            "refresh_token":"tGzv3JOkF0XG5Qx2TlKWIA",
+            "example_parameter":"example_value"
+        }
+
+    .. _`Section 7.1`: https://tools.ietf.org/html/rfc6749#section-7.1
+    .. _`Section 6`: https://tools.ietf.org/html/rfc6749#section-6
+    .. _`Section 3.3`: https://tools.ietf.org/html/rfc6749#section-3.3
+    .. _`RFC4627`: https://tools.ietf.org/html/rfc4627
+    """
+    try:
+        params = json.loads(body)
+    except ValueError:
+
+        # Fall back to URL-encoded string, to support old implementations,
+        # including (at time of writing) Facebook. See:
+        #   https://github.com/oauthlib/oauthlib/issues/267
+
+        params = dict(urlparse.parse_qsl(body))
+
+    if 'scope' in params:
+        params['scope'] = scope_to_list(params['scope'])
+
+    vin, vat, v_at = parse_expires(params)
+    if vin:
+        params['expires_in'] = vin
+    elif 'expires_in' in params:
+        params.pop('expires_in')
+    if vat:
+        params['expires_at'] = vat
+    elif 'expires_at' in params:
+        params.pop('expires_at')
+
+    params = OAuth2Token(params, old_scope=scope)
+    validate_token_parameters(params)
+    return params
+
+
+def validate_token_parameters(params):
+    """Ensures token presence, token type, expiration and scope in params."""
+    if 'error' in params:
+        raise_from_error(params.get('error'), params)
+
+    if 'access_token' not in params:
+        raise MissingTokenError(description="Missing access token parameter.")
+
+    if 'token_type' not in params and os.environ.get('OAUTHLIB_STRICT_TOKEN_TYPE'):
+        raise MissingTokenTypeError()
+
+    # If the issued access token scope is different from the one requested by
+    # the client, the authorization server MUST include the "scope" response
+    # parameter to inform the client of the actual scope granted.
+    # https://tools.ietf.org/html/rfc6749#section-3.3
+    if params.scope_changed:
+        message = 'Scope has changed from "{old}" to "{new}".'.format(
+            old=params.old_scope, new=params.scope,
+        )
+        scope_changed.send(message=message, old=params.old_scopes, new=params.scopes)
+        if not os.environ.get('OAUTHLIB_RELAX_TOKEN_SCOPE', None):
+            w = Warning(message)
+            w.token = params
+            w.old_scope = params.old_scopes
+            w.new_scope = params.scopes
+            raise w
+
+def parse_expires(params):
+    """Parse `expires_in`, `expires_at` fields from params
+
+    Parse following these rules:
+    - `expires_in` must be either integer, float or None. If a float, it is converted into an integer.
+    - `expires_at` is not in specification so it does its best to:
+      - convert into a int, else
+      - convert into a float, else
+      - reuse the same type as-is (usually string)
+    - `_expires_at` is a special internal value returned to be always an `int`, based
+    either on the presence of `expires_at`, or reuse the current time plus
+    `expires_in`. This is typically used to validate token expiry.
+
+    :param params: Dict with expires_in and expires_at optionally set
+    :return: Tuple of `expires_in`, `expires_at`, and `_expires_at`. None if not set.
+    """
+    expires_in = None
+    expires_at = None
+    _expires_at = None
+
+    if 'expires_in' in params:
+        if isinstance(params.get('expires_in'), int):
+            expires_in = params.get('expires_in')
+        elif isinstance(params.get('expires_in'), float):
+            expires_in = int(params.get('expires_in'))
+        elif isinstance(params.get('expires_in'), str):
+            try:
+                # Attempt to convert to int
+                expires_in = int(params.get('expires_in'))
+            except ValueError:
+                raise ValueError("expires_in must be an int")
+        elif params.get('expires_in') is not None:
+            raise ValueError("expires_in must be an int")
+
+    if 'expires_at' in params:
+        if isinstance(params.get('expires_at'), (float, int)):
+            expires_at = params.get('expires_at')
+            _expires_at = expires_at
+        elif isinstance(params.get('expires_at'), str):
+            try:
+                # Attempt to convert to int first, then float if int fails
+                expires_at = int(params.get('expires_at'))
+                _expires_at = expires_at
+            except ValueError:
+                try:
+                    expires_at = float(params.get('expires_at'))
+                    _expires_at = expires_at
+                except ValueError:
+                    # no change from str
+                    expires_at = params.get('expires_at')
+    if _expires_at is None and expires_in:
+        expires_at = round(time.time()) + expires_in
+        _expires_at = expires_at
+    return expires_in, expires_at, _expires_at
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/request_validator.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/request_validator.py
new file mode 100644
index 0000000000000000000000000000000000000000..6d6ebaa8e983c72c235dd1a07ff9ee778c864b06
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/request_validator.py
@@ -0,0 +1,680 @@
+"""
+oauthlib.oauth2.rfc6749.request_validator
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+log = logging.getLogger(__name__)
+
+
+class RequestValidator:
+
+    def client_authentication_required(self, request, *args, **kwargs):
+        """Determine if client authentication is required for current request.
+
+        According to the rfc6749, client authentication is required in the following cases:
+            - Resource Owner Password Credentials Grant, when Client type is Confidential or when
+              Client was issued client credentials or whenever Client provided client
+              authentication, see `Section 4.3.2`_.
+            - Authorization Code Grant, when Client type is Confidential or when Client was issued
+              client credentials or whenever Client provided client authentication,
+              see `Section 4.1.3`_.
+            - Refresh Token Grant, when Client type is Confidential or when Client was issued
+              client credentials or whenever Client provided client authentication, see
+              `Section 6`_
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Resource Owner Password Credentials Grant
+            - Refresh Token Grant
+
+        .. _`Section 4.3.2`: https://tools.ietf.org/html/rfc6749#section-4.3.2
+        .. _`Section 4.1.3`: https://tools.ietf.org/html/rfc6749#section-4.1.3
+        .. _`Section 6`: https://tools.ietf.org/html/rfc6749#section-6
+        """
+        return True
+
+    def authenticate_client(self, request, *args, **kwargs):
+        """Authenticate client through means outside the OAuth 2 spec.
+
+        Means of authentication is negotiated beforehand and may for example
+        be `HTTP Basic Authentication Scheme`_ which utilizes the Authorization
+        header.
+
+        Headers may be accesses through request.headers and parameters found in
+        both body and query can be obtained by direct attribute access, i.e.
+        request.client_id for client_id in the URL query.
+
+        The authentication process is required to contain the identification of
+        the client (i.e. search the database based on the client_id). In case the
+        client doesn't exist based on the received client_id, this method has to
+        return False and the HTTP response created by the library will contain
+        'invalid_client' message.
+
+        After the client identification succeeds, this method needs to set the
+        client on the request, i.e. request.client = client. A client object's
+        class must contain the 'client_id' attribute and the 'client_id' must have
+        a value.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Resource Owner Password Credentials Grant (may be disabled)
+            - Client Credentials Grant
+            - Refresh Token Grant
+
+        .. _`HTTP Basic Authentication Scheme`: https://tools.ietf.org/html/rfc1945#section-11.1
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def authenticate_client_id(self, client_id, request, *args, **kwargs):
+        """Ensure client_id belong to a non-confidential client.
+
+        A non-confidential client is one that is not required to authenticate
+        through other means, such as using HTTP Basic.
+
+        Note, while not strictly necessary it can often be very convenient
+        to set request.client to the client object associated with the
+        given client_id.
+
+        :param client_id: Unicode client identifier.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def confirm_redirect_uri(self, client_id, code, redirect_uri, client, request,
+                             *args, **kwargs):
+        """Ensure that the authorization process represented by this authorization
+        code began with this 'redirect_uri'.
+
+        If the client specifies a redirect_uri when obtaining code then that
+        redirect URI must be bound to the code and verified equal in this
+        method, according to RFC 6749 section 4.1.3.  Do not compare against
+        the client's allowed redirect URIs, but against the URI used when the
+        code was saved.
+
+        :param client_id: Unicode client identifier.
+        :param code: Unicode authorization_code.
+        :param redirect_uri: Unicode absolute URI.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant (during token request)
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_default_redirect_uri(self, client_id, request, *args, **kwargs):
+        """Get the default redirect URI for the client.
+
+        :param client_id: Unicode client identifier.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: The default redirect URI for the client
+
+        Method is used by:
+            - Authorization Code Grant
+            - Implicit Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_default_scopes(self, client_id, request, *args, **kwargs):
+        """Get the default scopes for the client.
+
+        :param client_id: Unicode client identifier.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: List of default scopes
+
+        Method is used by all core grant types:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Resource Owner Password Credentials Grant
+            - Client Credentials grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_original_scopes(self, refresh_token, request, *args, **kwargs):
+        """Get the list of scopes associated with the refresh token.
+
+        :param refresh_token: Unicode refresh token.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: List of scopes.
+
+        Method is used by:
+            - Refresh token grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def is_within_original_scope(self, request_scopes, refresh_token, request, *args, **kwargs):
+        """Check if requested scopes are within a scope of the refresh token.
+
+        When access tokens are refreshed the scope of the new token
+        needs to be within the scope of the original token. This is
+        ensured by checking that all requested scopes strings are on
+        the list returned by the get_original_scopes. If this check
+        fails, is_within_original_scope is called. The method can be
+        used in situations where returning all valid scopes from the
+        get_original_scopes is not practical.
+
+        :param request_scopes: A list of scopes that were requested by client.
+        :param refresh_token: Unicode refresh_token.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Refresh token grant
+        """
+        return False
+
+    def introspect_token(self, token, token_type_hint, request, *args, **kwargs):
+        """Introspect an access or refresh token.
+
+        Called once the introspect request is validated. This method should
+        verify the *token* and either return a dictionary with the list of
+        claims associated, or `None` in case the token is unknown.
+
+        Below the list of registered claims you should be interested in:
+
+        - scope : space-separated list of scopes
+        - client_id : client identifier
+        - username : human-readable identifier for the resource owner
+        - token_type : type of the token
+        - exp : integer timestamp indicating when this token will expire
+        - iat : integer timestamp indicating when this token was issued
+        - nbf : integer timestamp indicating when it can be "not-before" used
+        - sub : subject of the token - identifier of the resource owner
+        - aud : list of string identifiers representing the intended audience
+        - iss : string representing issuer of this token
+        - jti : string identifier for the token
+
+        Note that most of them are coming directly from JWT RFC. More details
+        can be found in `Introspect Claims`_ or `JWT Claims`_.
+
+        The implementation can use *token_type_hint* to improve lookup
+        efficiency, but must fallback to other types to be compliant with RFC.
+
+        The dict of claims is added to request.token after this method.
+
+        :param token: The token string.
+        :param token_type_hint: access_token or refresh_token.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        Method is used by:
+            - Introspect Endpoint (all grants are compatible)
+
+        .. _`Introspect Claims`: https://tools.ietf.org/html/rfc7662#section-2.2
+        .. _`JWT Claims`: https://tools.ietf.org/html/rfc7519#section-4
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def invalidate_authorization_code(self, client_id, code, request, *args, **kwargs):
+        """Invalidate an authorization code after use.
+
+        :param client_id: Unicode client identifier.
+        :param code: The authorization code grant (request.code).
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        Method is used by:
+            - Authorization Code Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def revoke_token(self, token, token_type_hint, request, *args, **kwargs):
+        """Revoke an access or refresh token.
+
+        :param token: The token string.
+        :param token_type_hint: access_token or refresh_token.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        Method is used by:
+            - Revocation Endpoint
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def rotate_refresh_token(self, request):
+        """Determine whether to rotate the refresh token. Default, yes.
+
+        When access tokens are refreshed the old refresh token can be kept
+        or replaced with a new one (rotated). Return True to rotate and
+        and False for keeping original.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Refresh Token Grant
+        """
+        return True
+
+    def save_authorization_code(self, client_id, code, request, *args, **kwargs):
+        """Persist the authorization_code.
+
+        The code should at minimum be stored with:
+            - the client_id (``client_id``)
+            - the redirect URI used (``request.redirect_uri``)
+            - a resource owner / user (``request.user``)
+            - the authorized scopes (``request.scopes``)
+
+        To support PKCE, you MUST associate the code with:
+            - Code Challenge (``request.code_challenge``) and
+            - Code Challenge Method (``request.code_challenge_method``)
+
+        To support OIDC, you MUST associate the code with:
+            - nonce, if present (``code["nonce"]``)
+
+        The ``code`` argument is actually a dictionary, containing at least a
+        ``code`` key with the actual authorization code:
+
+            ``{'code': 'sdf345jsdf0934f'}``
+
+        It may also have a ``claims`` parameter which, when present, will be a dict
+        deserialized from JSON as described at
+        http://openid.net/specs/openid-connect-core-1_0.html#ClaimsParameter
+        This value should be saved in this method and used again in ``.validate_code``.
+
+        :param client_id: Unicode client identifier.
+        :param code: A dict of the authorization code grant and, optionally, state.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        Method is used by:
+            - Authorization Code Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def save_token(self, token, request, *args, **kwargs):
+        """Persist the token with a token type specific method.
+
+        Currently, only save_bearer_token is supported.
+
+        :param token: A (Bearer) token dict.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        return self.save_bearer_token(token, request, *args, **kwargs)
+
+    def save_bearer_token(self, token, request, *args, **kwargs):
+        """Persist the Bearer token.
+
+        The Bearer token should at minimum be associated with:
+            - a client and it's client_id, if available
+            - a resource owner / user (request.user)
+            - authorized scopes (request.scopes)
+            - an expiration time
+            - a refresh token, if issued
+            - a claims document, if present in request.claims
+
+        The Bearer token dict may hold a number of items::
+
+            {
+                'token_type': 'Bearer',
+                'access_token': 'askfjh234as9sd8',
+                'expires_in': 3600,
+                'scope': 'string of space separated authorized scopes',
+                'refresh_token': '23sdf876234',  # if issued
+                'state': 'given_by_client',  # if supplied by client (implicit ONLY)
+            }
+
+        Note that while "scope" is a string-separated list of authorized scopes,
+        the original list is still available in request.scopes.
+
+        The token dict is passed as a reference so any changes made to the dictionary
+        will go back to the user.  If additional information must return to the client
+        user, and it is only possible to get this information after writing the token
+        to storage, it should be added to the token dictionary.  If the token
+        dictionary must be modified but the changes should not go back to the user,
+        a copy of the dictionary must be made before making the changes.
+
+        Also note that if an Authorization Code grant request included a valid claims
+        parameter (for OpenID Connect) then the request.claims property will contain
+        the claims dict, which should be saved for later use when generating the
+        id_token and/or UserInfo response content.
+
+        :param token: A Bearer token dict.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: The default redirect URI for the client
+
+        Method is used by all core grant types issuing Bearer tokens:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Resource Owner Password Credentials Grant (might not associate a client)
+            - Client Credentials grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_bearer_token(self, token, scopes, request):
+        """Ensure the Bearer token is valid and authorized access to scopes.
+
+        :param token: A string of random characters.
+        :param scopes: A list of scopes associated with the protected resource.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+
+        A key to OAuth 2 security and restricting impact of leaked tokens is
+        the short expiration time of tokens, *always ensure the token has not
+        expired!*.
+
+        Two different approaches to scope validation:
+
+            1) all(scopes). The token must be authorized access to all scopes
+                            associated with the resource. For example, the
+                            token has access to ``read-only`` and ``images``,
+                            thus the client can view images but not upload new.
+                            Allows for fine grained access control through
+                            combining various scopes.
+
+            2) any(scopes). The token must be authorized access to one of the
+                            scopes associated with the resource. For example,
+                            token has access to ``read-only-images``.
+                            Allows for fine grained, although arguably less
+                            convenient, access control.
+
+        A powerful way to use scopes would mimic UNIX ACLs and see a scope
+        as a group with certain privileges. For a restful API these might
+        map to HTTP verbs instead of read, write and execute.
+
+        Note, the request.user attribute can be set to the resource owner
+        associated with this token. Similarly the request.client and
+        request.scopes attribute can be set to associated client object
+        and authorized scopes. If you then use a decorator such as the
+        one provided for django these attributes will be made available
+        in all protected views as keyword arguments.
+
+        :param token: Unicode Bearer token
+        :param scopes: List of scopes (defined by you)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is indirectly used by all core Bearer token issuing grant types:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Resource Owner Password Credentials Grant
+            - Client Credentials Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_client_id(self, client_id, request, *args, **kwargs):
+        """Ensure client_id belong to a valid and active client.
+
+        Note, while not strictly necessary it can often be very convenient
+        to set request.client to the client object associated with the
+        given client_id.
+
+        :param client_id: Unicode client identifier.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Implicit Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_code(self, client_id, code, client, request, *args, **kwargs):
+        """Verify that the authorization_code is valid and assigned to the given
+        client.
+
+        Before returning true, set the following based on the information stored
+        with the code in 'save_authorization_code':
+
+            - request.user
+            - request.scopes
+            - request.claims (if given)
+
+        OBS! The request.user attribute should be set to the resource owner
+        associated with this authorization code. Similarly request.scopes
+        must also be set.
+
+        The request.claims property, if it was given, should assigned a dict.
+
+        If PKCE is enabled (see 'is_pkce_required' and 'save_authorization_code')
+        you MUST set the following based on the information stored:
+
+            - request.code_challenge
+            - request.code_challenge_method
+
+        :param client_id: Unicode client identifier.
+        :param code: Unicode authorization code.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_grant_type(self, client_id, grant_type, client, request, *args, **kwargs):
+        """Ensure client is authorized to use the grant_type requested.
+
+        :param client_id: Unicode client identifier.
+        :param grant_type: Unicode grant type, i.e. authorization_code, password.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Resource Owner Password Credentials Grant
+            - Client Credentials Grant
+            - Refresh Token Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_redirect_uri(self, client_id, redirect_uri, request, *args, **kwargs):
+        """Ensure client is authorized to redirect to the redirect_uri requested.
+
+        All clients should register the absolute URIs of all URIs they intend
+        to redirect to. The registration is outside of the scope of oauthlib.
+
+        :param client_id: Unicode client identifier.
+        :param redirect_uri: Unicode absolute URI.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Implicit Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_refresh_token(self, refresh_token, client, request, *args, **kwargs):
+        """Ensure the Bearer token is valid and authorized access to scopes.
+
+        OBS! The request.user attribute should be set to the resource owner
+        associated with this refresh token.
+
+        :param refresh_token: Unicode refresh token.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant (indirectly by issuing refresh tokens)
+            - Resource Owner Password Credentials Grant (also indirectly)
+            - Refresh Token Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_response_type(self, client_id, response_type, client, request, *args, **kwargs):
+        """Ensure client is authorized to use the response_type requested.
+
+        :param client_id: Unicode client identifier.
+        :param response_type: Unicode response type, i.e. code, token.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+            - Implicit Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_scopes(self, client_id, scopes, client, request, *args, **kwargs):
+        """Ensure the client is authorized access to requested scopes.
+
+        :param client_id: Unicode client identifier.
+        :param scopes: List of scopes (defined by you).
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by all core grant types:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Resource Owner Password Credentials Grant
+            - Client Credentials Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_user(self, username, password, client, request, *args, **kwargs):
+        """Ensure the username and password is valid.
+
+        OBS! The validation should also set the user attribute of the request
+        to a valid resource owner, i.e. request.user = username or similar. If
+        not set you will be unable to associate a token with a user in the
+        persistence method used (commonly, save_bearer_token).
+
+        :param username: Unicode username.
+        :param password: Unicode password.
+        :param client: Client object set by you, see ``.authenticate_client``.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Resource Owner Password Credentials Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def is_pkce_required(self, client_id, request):
+        """Determine if current request requires PKCE. Default, False.
+        This is called for both "authorization" and "token" requests.
+
+        Override this method by ``return True`` to enable PKCE for everyone.
+        You might want to enable it only for public clients.
+        Note that PKCE can also be used in addition of a client authentication.
+
+        OAuth 2.0 public clients utilizing the Authorization Code Grant are
+        susceptible to the authorization code interception attack.  This
+        specification describes the attack as well as a technique to mitigate
+        against the threat through the use of Proof Key for Code Exchange
+        (PKCE, pronounced "pixy"). See `RFC7636`_.
+
+        :param client_id: Client identifier.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Authorization Code Grant
+
+        .. _`RFC7636`: https://tools.ietf.org/html/rfc7636
+        """
+        return False
+
+    def get_code_challenge(self, code, request):
+        """Is called for every "token" requests.
+
+        When the server issues the authorization code in the authorization
+        response, it MUST associate the ``code_challenge`` and
+        ``code_challenge_method`` values with the authorization code so it can
+        be verified later.
+
+        Typically, the ``code_challenge`` and ``code_challenge_method`` values
+        are stored in encrypted form in the ``code`` itself but could
+        alternatively be stored on the server associated with the code.  The
+        server MUST NOT include the ``code_challenge`` value in client requests
+        in a form that other entities can extract.
+
+        Return the ``code_challenge`` associated to the code.
+        If ``None`` is returned, code is considered to not be associated to any
+        challenges.
+
+        :param code: Authorization code.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: code_challenge string
+
+        Method is used by:
+            - Authorization Code Grant - when PKCE is active
+
+        """
+        return None
+
+    def get_code_challenge_method(self, code, request):
+        """Is called during the "token" request processing, when a
+        ``code_verifier`` and a ``code_challenge`` has been provided.
+
+        See ``.get_code_challenge``.
+
+        Must return ``plain`` or ``S256``. You can return a custom value if you have
+        implemented your own ``AuthorizationCodeGrant`` class.
+
+        :param code: Authorization code.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: code_challenge_method string
+
+        Method is used by:
+            - Authorization Code Grant - when PKCE is active
+
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def is_origin_allowed(self, client_id, origin, request, *args, **kwargs):
+        """Indicate if the given origin is allowed to access the token endpoint
+        via Cross-Origin Resource Sharing (CORS).  CORS is used by browser-based
+        clients, such as Single-Page Applications, to perform the Authorization
+        Code Grant.
+
+        (Note:  If performing Authorization Code Grant via a public client such
+        as a browser, you should use PKCE as well.)
+
+        If this method returns true, the appropriate CORS headers will be added
+        to the response.  By default this method always returns False, meaning
+        CORS is disabled.
+
+        :param client_id: Unicode client identifier.
+        :param redirect_uri: Unicode origin.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: bool
+
+        Method is used by:
+            - Authorization Code Grant
+            - Refresh Token Grant
+
+        """
+        return False
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/tokens.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/tokens.py
new file mode 100644
index 0000000000000000000000000000000000000000..73b8c66a9621aa2b81f3adb7a97b84fc051b4142
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/tokens.py
@@ -0,0 +1,350 @@
+"""
+oauthlib.oauth2.rfc6749.tokens
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module contains methods for adding two types of access tokens to requests.
+
+- Bearer https://tools.ietf.org/html/rfc6750
+- MAC https://tools.ietf.org/html/draft-ietf-oauth-v2-http-mac-01
+"""
+import hashlib
+import hmac
+import warnings
+from binascii import b2a_base64
+from urllib.parse import urlparse
+
+from oauthlib import common
+from oauthlib.common import add_params_to_qs, add_params_to_uri
+
+from . import utils
+
+
+class OAuth2Token(dict):
+
+    def __init__(self, params, old_scope=None):
+        super().__init__(params)
+        self._new_scope = None
+        if params.get('scope'):
+            self._new_scope = set(utils.scope_to_list(params['scope']))
+        if old_scope is not None:
+            self._old_scope = set(utils.scope_to_list(old_scope))
+            if self._new_scope is None:
+                # the rfc says that if the scope hasn't changed, it's optional
+                # in params so set the new scope to the old scope
+                self._new_scope = self._old_scope
+        else:
+            self._old_scope = self._new_scope
+
+    @property
+    def scope_changed(self):
+        return self._new_scope != self._old_scope
+
+    @property
+    def old_scope(self):
+        return utils.list_to_scope(self._old_scope)
+
+    @property
+    def old_scopes(self):
+        return list(self._old_scope)
+
+    @property
+    def scope(self):
+        return utils.list_to_scope(self._new_scope)
+
+    @property
+    def scopes(self):
+        return list(self._new_scope)
+
+    @property
+    def missing_scopes(self):
+        return list(self._old_scope - self._new_scope)
+
+    @property
+    def additional_scopes(self):
+        return list(self._new_scope - self._old_scope)
+
+
+def prepare_mac_header(token, uri, key, http_method,
+                       nonce=None,
+                       headers=None,
+                       body=None,
+                       ext='',
+                       hash_algorithm='hmac-sha-1',
+                       issue_time=None,
+                       draft=0):
+    """Add an `MAC Access Authentication`_ signature to headers.
+
+    Unlike OAuth 1, this HMAC signature does not require inclusion of the
+    request payload/body, neither does it use a combination of client_secret
+    and token_secret but rather a mac_key provided together with the access
+    token.
+
+    Currently two algorithms are supported, "hmac-sha-1" and "hmac-sha-256",
+    `extension algorithms`_ are not supported.
+
+    Example MAC Authorization header, linebreaks added for clarity
+
+    Authorization: MAC id="h480djs93hd8",
+                       nonce="1336363200:dj83hs9s",
+                       mac="bhCQXTVyfj5cmA9uKkPFx1zeOXM="
+
+    .. _`MAC Access Authentication`: https://tools.ietf.org/html/draft-ietf-oauth-v2-http-mac-01
+    .. _`extension algorithms`: https://tools.ietf.org/html/draft-ietf-oauth-v2-http-mac-01#section-7.1
+
+    :param token:
+    :param uri: Request URI.
+    :param key: MAC given provided by token endpoint.
+    :param http_method: HTTP Request method.
+    :param nonce:
+    :param headers: Request headers as a dictionary.
+    :param body:
+    :param ext:
+    :param hash_algorithm: HMAC algorithm provided by token endpoint.
+    :param issue_time: Time when the MAC credentials were issued (datetime).
+    :param draft: MAC authentication specification version.
+    :return: headers dictionary with the authorization field added.
+    """
+    http_method = http_method.upper()
+    host, port = utils.host_from_uri(uri)
+
+    if hash_algorithm.lower() == 'hmac-sha-1':
+        h = hashlib.sha1
+    elif hash_algorithm.lower() == 'hmac-sha-256':
+        h = hashlib.sha256
+    else:
+        raise ValueError('unknown hash algorithm')
+
+    if draft == 0:
+        nonce = nonce or '{}:{}'.format(utils.generate_age(issue_time),
+                                          common.generate_nonce())
+    else:
+        ts = common.generate_timestamp()
+        nonce = common.generate_nonce()
+
+    sch, net, path, par, query, fra = urlparse(uri)
+
+    request_uri = path + '?' + query if query else path
+
+    # Hash the body/payload
+    if body is not None and draft == 0:
+        body = body.encode('utf-8')
+        bodyhash = b2a_base64(h(body).digest())[:-1].decode('utf-8')
+    else:
+        bodyhash = ''
+
+    # Create the normalized base string
+    base = []
+    if draft == 0:
+        base.append(nonce)
+    else:
+        base.append(ts)
+        base.append(nonce)
+    base.append(http_method.upper())
+    base.append(request_uri)
+    base.append(host)
+    base.append(port)
+    if draft == 0:
+        base.append(bodyhash)
+    base.append(ext or '')
+    base_string = '\n'.join(base) + '\n'
+
+    # hmac struggles with unicode strings - http://bugs.python.org/issue5285
+    if isinstance(key, str):
+        key = key.encode('utf-8')
+    sign = hmac.new(key, base_string.encode('utf-8'), h)
+    sign = b2a_base64(sign.digest())[:-1].decode('utf-8')
+
+    header = []
+    header.append('MAC id="%s"' % token)
+    if draft != 0:
+        header.append('ts="%s"' % ts)
+    header.append('nonce="%s"' % nonce)
+    if bodyhash:
+        header.append('bodyhash="%s"' % bodyhash)
+    if ext:
+        header.append('ext="%s"' % ext)
+    header.append('mac="%s"' % sign)
+
+    headers = headers or {}
+    headers['Authorization'] = ', '.join(header)
+    return headers
+
+
+def prepare_bearer_uri(token, uri):
+    """Add a `Bearer Token`_ to the request URI.
+    Not recommended, use only if client can't use authorization header or body.
+
+    http://www.example.com/path?access_token=h480djs93hd8
+
+    .. _`Bearer Token`: https://tools.ietf.org/html/rfc6750
+
+    :param token:
+    :param uri:
+    """
+    return add_params_to_uri(uri, [(('access_token', token))])
+
+
+def prepare_bearer_headers(token, headers=None):
+    """Add a `Bearer Token`_ to the request URI.
+    Recommended method of passing bearer tokens.
+
+    Authorization: Bearer h480djs93hd8
+
+    .. _`Bearer Token`: https://tools.ietf.org/html/rfc6750
+
+    :param token:
+    :param headers:
+    """
+    headers = headers or {}
+    headers['Authorization'] = 'Bearer %s' % token
+    return headers
+
+
+def prepare_bearer_body(token, body=''):
+    """Add a `Bearer Token`_ to the request body.
+
+    access_token=h480djs93hd8
+
+    .. _`Bearer Token`: https://tools.ietf.org/html/rfc6750
+
+    :param token:
+    :param body:
+    """
+    return add_params_to_qs(body, [(('access_token', token))])
+
+
+def random_token_generator(request, refresh_token=False):
+    """
+    :param request: OAuthlib request.
+    :type request: oauthlib.common.Request
+    :param refresh_token:
+    """
+    return common.generate_token()
+
+
+def signed_token_generator(private_pem, **kwargs):
+    """
+    :param private_pem:
+    """
+    def signed_token_generator(request):
+        request.claims = kwargs
+        return common.generate_signed_token(private_pem, request)
+
+    return signed_token_generator
+
+
+def get_token_from_header(request):
+    """
+    Helper function to extract a token from the request header.
+
+    :param request: OAuthlib request.
+    :type request: oauthlib.common.Request
+    :return: Return the token or None if the Authorization header is malformed.
+    """
+    token = None
+
+    if 'Authorization' in request.headers:
+        split_header = request.headers.get('Authorization').split()
+        if len(split_header) == 2 and split_header[0].lower() == 'bearer':
+            token = split_header[1]
+    else:
+        token = request.access_token
+
+    return token
+
+
+class TokenBase:
+    __slots__ = ()
+
+    def __call__(self, request, refresh_token=False):
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def estimate_type(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+
+class BearerToken(TokenBase):
+    __slots__ = (
+        'request_validator', 'token_generator',
+        'refresh_token_generator', 'expires_in'
+    )
+
+    def __init__(self, request_validator=None, token_generator=None,
+                 expires_in=None, refresh_token_generator=None):
+        self.request_validator = request_validator
+        self.token_generator = token_generator or random_token_generator
+        self.refresh_token_generator = (
+            refresh_token_generator or self.token_generator
+        )
+        self.expires_in = expires_in or 3600
+
+    def create_token(self, request, refresh_token=False, **kwargs):
+        """
+        Create a BearerToken, by default without refresh token.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param refresh_token:
+        """
+        if "save_token" in kwargs:
+            warnings.warn("`save_token` has been deprecated, it was not called internally."
+                          "If you do, call `request_validator.save_token()` instead.",
+                          DeprecationWarning)
+
+        expires_in = self.expires_in(request) if callable(self.expires_in) else self.expires_in
+
+        request.expires_in = expires_in
+
+        token = {
+            'access_token': self.token_generator(request),
+            'expires_in': expires_in,
+            'token_type': 'Bearer',
+        }
+
+        # If provided, include - this is optional in some cases https://tools.ietf.org/html/rfc6749#section-3.3 but
+        # there is currently no mechanism to coordinate issuing a token for only a subset of the requested scopes so
+        # all tokens issued are for the entire set of requested scopes.
+        if request.scopes is not None:
+            token['scope'] = ' '.join(request.scopes)
+
+        if refresh_token:
+            if (request.refresh_token and
+                    not self.request_validator.rotate_refresh_token(request)):
+                token['refresh_token'] = request.refresh_token
+            else:
+                token['refresh_token'] = self.refresh_token_generator(request)
+
+        token.update(request.extra_credentials or {})
+        return OAuth2Token(token)
+
+    def validate_request(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        token = get_token_from_header(request)
+        return self.request_validator.validate_bearer_token(
+            token, request.scopes, request)
+
+    def estimate_type(self, request):
+        """
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        """
+        if request.headers.get('Authorization', '').split(' ')[0].lower() == 'bearer':
+            return 9
+        elif request.access_token is not None:
+            return 5
+        else:
+            return 0
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/utils.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dc27b3dff480bbb89e113f478cec27945af8e2d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc6749/utils.py
@@ -0,0 +1,83 @@
+"""
+oauthlib.utils
+~~~~~~~~~~~~~~
+
+This module contains utility methods used by various parts of the OAuth 2 spec.
+"""
+import datetime
+import os
+from urllib.parse import quote, urlparse
+
+from oauthlib.common import urldecode
+
+
+def list_to_scope(scope):
+    """Convert a list of scopes to a space separated string."""
+    if isinstance(scope, str) or scope is None:
+        return scope
+    elif isinstance(scope, (set, tuple, list)):
+        return " ".join([str(s) for s in scope])
+    else:
+        raise ValueError("Invalid scope (%s), must be string, tuple, set, or list." % scope)
+
+
+def scope_to_list(scope):
+    """Convert a space separated string to a list of scopes."""
+    if isinstance(scope, (tuple, list, set)):
+        return [str(s) for s in scope]
+    elif scope is None:
+        return None
+    else:
+        return scope.strip().split(" ")
+
+
+def params_from_uri(uri):
+    params = dict(urldecode(urlparse(uri).query))
+    if 'scope' in params:
+        params['scope'] = scope_to_list(params['scope'])
+    return params
+
+
+def host_from_uri(uri):
+    """Extract hostname and port from URI.
+
+    Will use default port for HTTP and HTTPS if none is present in the URI.
+    """
+    default_ports = {
+        'HTTP': '80',
+        'HTTPS': '443',
+    }
+
+    sch, netloc, path, par, query, fra = urlparse(uri)
+    if ':' in netloc:
+        netloc, port = netloc.split(':', 1)
+    else:
+        port = default_ports.get(sch.upper())
+
+    return netloc, port
+
+
+def escape(u):
+    """Escape a string in an OAuth-compatible fashion.
+
+    TODO: verify whether this can in fact be used for OAuth 2
+
+    """
+    if not isinstance(u, str):
+        raise ValueError('Only unicode objects are escapable.')
+    return quote(u.encode('utf-8'), safe=b'~')
+
+
+def generate_age(issue_time):
+    """Generate a age parameter for MAC authentication draft 00."""
+    td = datetime.datetime.now() - issue_time
+    age = (td.microseconds + (td.seconds + td.days * 24 * 3600)
+           * 10 ** 6) / 10 ** 6
+    return str(age)
+
+
+def is_secure_transport(uri):
+    """Check if the uri is over ssl."""
+    if os.environ.get('OAUTHLIB_INSECURE_TRANSPORT'):
+        return True
+    return uri.lower().startswith('https://')
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..65891445e3e687f136fc12896a7d745b70b1594d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/__init__.py
@@ -0,0 +1,16 @@
+"""
+oauthlib.oauth2.rfc8628
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 Device Authorization RFC8628.
+"""
+
+from oauthlib.oauth2.rfc8628.errors import (
+    SlowDownError,
+    AuthorizationPendingError,
+    ExpiredTokenError,
+)
+import logging
+
+log = logging.getLogger(__name__)
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..130b52e3814bc40c0f483b1ab60b034d1374049c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/__init__.py
@@ -0,0 +1,8 @@
+"""
+oauthlib.oauth2.rfc8628
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming OAuth 2.0 Device Authorization RFC8628.
+"""
+from .device import DeviceClient
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/device.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/device.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee0ccf8d61897ac5dae0ecd9028f13a929006129
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/clients/device.py
@@ -0,0 +1,95 @@
+"""
+oauthlib.oauth2.rfc8628
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 Device Authorization RFC8628.
+"""
+from oauthlib.common import add_params_to_uri
+from oauthlib.oauth2 import BackendApplicationClient, Client
+from oauthlib.oauth2.rfc6749.errors import InsecureTransportError
+from oauthlib.oauth2.rfc6749.parameters import prepare_token_request
+from oauthlib.oauth2.rfc6749.utils import is_secure_transport, list_to_scope
+
+
+class DeviceClient(Client):
+
+    """A public client utilizing the device authorization workflow.
+
+    The client can request an access token using a device code and
+    a public client id associated with the device code as defined
+    in RFC8628.
+
+    The device authorization grant type can be used to obtain both
+    access tokens and refresh tokens and is intended to be used in
+    a scenario where the device being authorized does not have a
+    user interface that is suitable for performing authentication.
+    """
+
+    grant_type = 'urn:ietf:params:oauth:grant-type:device_code'
+
+    def __init__(self, client_id, **kwargs):
+        super().__init__(client_id, **kwargs)
+        self.client_secret = kwargs.get('client_secret')
+
+    def prepare_request_uri(self, uri, scope=None, **kwargs):
+        if not is_secure_transport(uri):
+            raise InsecureTransportError()
+
+        scope = self.scope if scope is None else scope
+        params = [(('client_id', self.client_id)), (('grant_type', self.grant_type))]
+
+        if self.client_secret is not None:
+            params.append(('client_secret', self.client_secret))
+
+        if scope:
+            params.append(('scope', list_to_scope(scope)))
+
+        for k,v in kwargs.items():
+            if v:
+                params.append((str(k), v))
+
+        return add_params_to_uri(uri, params)
+
+    def prepare_request_body(self, device_code, body='', scope=None,
+                             include_client_id=False, **kwargs):
+        """Add device_code to request body
+
+        The client makes a request to the token endpoint by adding the
+        device_code as a parameter using the
+        "application/x-www-form-urlencoded" format to the HTTP request
+        body.
+
+        :param body: Existing request body (URL encoded string) to embed parameters
+                     into. This may contain extra parameters. Default ''.
+        :param scope:   The scope of the access request as described by
+                        `Section 3.3`_.
+
+        :param include_client_id: `True` to send the `client_id` in the
+                                  body of the upstream request. This is required
+                                  if the client is not authenticating with the
+                                  authorization server as described in
+                                  `Section 3.2.1`_. False otherwise (default).
+        :type include_client_id: Boolean
+
+        :param kwargs:  Extra credentials to include in the token request.
+
+        The prepared body will include all provided device_code as well as
+        the ``grant_type`` parameter set to
+        ``urn:ietf:params:oauth:grant-type:device_code``::
+
+            >>> from oauthlib.oauth2 import DeviceClient
+            >>> client = DeviceClient('your_id', 'your_code')
+            >>> client.prepare_request_body(scope=['hello', 'world'])
+            'grant_type=urn:ietf:params:oauth:grant-type:device_code&scope=hello+world'
+
+        .. _`Section 3.2.1`: https://datatracker.ietf.org/doc/html/rfc6749#section-3.2.1
+        .. _`Section 3.3`: https://datatracker.ietf.org/doc/html/rfc6749#section-3.3
+        .. _`Section 3.4`: https://datatracker.ietf.org/doc/html/rfc8628#section-3.4
+        """
+
+        kwargs['client_id'] = self.client_id
+        kwargs['include_client_id'] = include_client_id
+        scope = self.scope if scope is None else scope
+        return prepare_token_request(self.grant_type, body=body, device_code=device_code,
+                                     scope=scope, **kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..dc834797cd7e0f1f3f5f0c997a2f00cd5d7c0d38
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/__init__.py
@@ -0,0 +1,10 @@
+"""
+oauthlib.oauth2.rfc8628
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 Device Authorization RFC8628.
+"""
+
+from .device_authorization import DeviceAuthorizationEndpoint
+from .pre_configured import DeviceApplicationServer
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/device_authorization.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/device_authorization.py
new file mode 100644
index 0000000000000000000000000000000000000000..3f38a540590a9d38d42e3d84a79f6acfe440cac7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/device_authorization.py
@@ -0,0 +1,232 @@
+"""
+oauthlib.oauth2.rfc8628
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OAuth 2.0 RFC8628.
+"""
+
+import logging
+from typing import Callable
+
+from oauthlib.common import Request, generate_token
+from oauthlib.oauth2.rfc6749 import errors
+from oauthlib.oauth2.rfc6749.endpoints.base import (
+    BaseEndpoint,
+    catch_errors_and_unavailability,
+)
+
+log = logging.getLogger(__name__)
+
+
+class DeviceAuthorizationEndpoint(BaseEndpoint):
+    """DeviceAuthorization endpoint - used by the client to initiate
+    the authorization flow by requesting a set of verification codes
+    from the authorization server by making an HTTP "POST" request to
+    the device authorization endpoint.
+
+    The client authentication requirements of Section 3.2.1 of [RFC6749]
+    apply to requests on this endpoint, which means that confidential
+    clients (those that have established client credentials) authenticate
+    in the same manner as when making requests to the token endpoint, and
+    public clients provide the "client_id" parameter to identify
+    themselves.
+    """
+
+    def __init__(
+        self,
+        request_validator,
+        verification_uri,
+        expires_in=1800,
+        interval=None,
+        verification_uri_complete=None,
+        user_code_generator: Callable[[None], str] = None,
+    ):
+        """
+        :param request_validator: An instance of RequestValidator.
+        :type request_validator: oauthlib.oauth2.rfc6749.RequestValidator.
+        :param verification_uri: a string containing the URL that can be polled by the client application
+        :param expires_in: a number that represents the lifetime of the `user_code` and `device_code`
+        :param interval: an option number that represents the number of seconds between each poll requests
+        :param verification_uri_complete: a string of a function that can be called with `user_data` as parameter
+        :param user_code_generator: a callable that returns a configurable user code
+        """
+        self.request_validator = request_validator
+        self._expires_in = expires_in
+        self._interval = interval
+        self._verification_uri = verification_uri
+        self._verification_uri_complete = verification_uri_complete
+        self.user_code_generator = user_code_generator
+
+        BaseEndpoint.__init__(self)
+
+    @property
+    def interval(self):
+        """The minimum amount of time in seconds that the client
+        SHOULD wait between polling requests to the token endpoint.  If no
+        value is provided, clients MUST use 5 as the default.
+        """
+        return self._interval
+
+    @property
+    def expires_in(self):
+        """The lifetime in seconds of the "device_code" and "user_code"."""
+        return self._expires_in
+
+    @property
+    def verification_uri(self):
+        """The end-user verification URI on the authorization
+        server.  The URI should be short and easy to remember as end users
+        will be asked to manually type it into their user agent.
+        """
+        return self._verification_uri
+
+    def verification_uri_complete(self, user_code):
+        if not self._verification_uri_complete:
+            return None
+        if isinstance(self._verification_uri_complete, str):
+            return self._verification_uri_complete.format(user_code=user_code)
+        if callable(self._verification_uri_complete):
+            return self._verification_uri_complete(user_code)
+        return None
+
+    @catch_errors_and_unavailability
+    def validate_device_authorization_request(self, request):
+        """Validate the device authorization request.
+
+        The client_id is required if the client is not authenticating with the
+        authorization server as described in `Section 3.2.1. of [RFC6749]`_.
+        The client identifier as described in `Section 2.2 of [RFC6749]`_.
+
+        .. _`Section 3.2.1. of [RFC6749]`: https://www.rfc-editor.org/rfc/rfc6749#section-3.2.1
+        .. _`Section 2.2 of [RFC6749]`: https://www.rfc-editor.org/rfc/rfc6749#section-2.2
+        """
+
+        # First check duplicate parameters
+        for param in ("client_id", "scope"):
+            try:
+                duplicate_params = request.duplicate_params
+            except ValueError:
+                raise errors.InvalidRequestFatalError(
+                    description="Unable to parse query string", request=request
+                )
+            if param in duplicate_params:
+                raise errors.InvalidRequestFatalError(
+                    description="Duplicate %s parameter." % param, request=request
+                )
+
+        # the "application/x-www-form-urlencoded" format, per Appendix B of [RFC6749]
+        # https://www.rfc-editor.org/rfc/rfc6749#appendix-B
+        if request.headers["Content-Type"] != "application/x-www-form-urlencoded":
+            raise errors.InvalidRequestError(
+                "Content-Type must be application/x-www-form-urlencoded",
+                request=request,
+            )
+
+        # REQUIRED. The client identifier as described in Section 2.2.
+        # https://tools.ietf.org/html/rfc6749#section-2.2
+        # TODO: extract client_id an helper validation function.
+        if not request.client_id:
+            raise errors.MissingClientIdError(request=request)
+
+        if not self.request_validator.validate_client_id(request.client_id, request):
+            raise errors.InvalidClientIdError(request=request)
+
+        # The client authentication requirements of Section 3.2.1 of [RFC6749]
+        # apply to requests on this endpoint, which means that confidential
+        # clients (those that have established client credentials) authenticate
+        # in the same manner as when making requests to the token endpoint, and
+        # public clients provide the "client_id" parameter to identify
+        # themselves.
+        self._raise_on_invalid_client(request)
+
+    @catch_errors_and_unavailability
+    def create_device_authorization_response(
+        self, uri, http_method="POST", body=None, headers=None
+    ):
+        """
+           Generate a unique device verification code and an end-user code that are valid for a limited time.
+           Include them in the HTTP response body using the "application/json" format [RFC8259] with a
+           200 (OK) status code, as described in `Section-3.2`_.
+
+           :param uri: The full URI of the token request.
+           :type uri: str
+           :param request: OAuthlib request.
+           :type request: oauthlib.common.Request
+           :param user_code_generator:
+               A callable that returns a string for the user code.
+               This allows the caller to decide how the `user_code` should be formatted.
+           :type user_code_generator: Callable[[], str]
+           :return: A tuple of three elements:
+                    1. A dict of headers to set on the response.
+                    2. The response body as a string.
+                    3. The response status code as an integer.
+           :rtype: tuple
+
+           The response contains the following parameters:
+
+           device_code
+              **REQUIRED.** The device verification code.
+
+           user_code
+              **REQUIRED.** The end-user verification code.
+
+           verification_uri
+              **REQUIRED.** The end-user verification URI on the authorization server.
+              The URI should be short and easy to remember as end users will be asked
+              to manually type it into their user agent.
+
+           verification_uri_complete
+              **OPTIONAL.** A verification URI that includes the `user_code` (or
+              other information with the same function as the `user_code`), which is
+              designed for non-textual transmission.
+
+           expires_in
+              **REQUIRED.** The lifetime in seconds of the `device_code` and `user_code`.
+
+           interval
+              **OPTIONAL.** The minimum amount of time in seconds that the client
+              SHOULD wait between polling requests to the token endpoint. If no
+              value is provided, clients MUST use 5 as the default.
+
+           **For example:**
+
+              .. code-block:: http
+
+                 HTTP/1.1 200 OK
+                 Content-Type: application/json
+                 Cache-Control: no-store
+
+                 {
+                   "device_code": "GmRhmhcxhwAzkoEqiMEg_DnyEysNkuNhszIySk9eS",
+                   "user_code": "WDJB-MJHT",
+                   "verification_uri": "https://example.com/device",
+                   "verification_uri_complete":
+                       "https://example.com/device?user_code=WDJB-MJHT",
+                   "expires_in": 1800,
+                   "interval": 5
+                 }
+
+           .. _`Section-3.2`: https://www.rfc-editor.org/rfc/rfc8628#section-3.2
+           """
+        request = Request(uri, http_method, body, headers)
+        self.validate_device_authorization_request(request)
+        log.debug("Pre resource owner authorization validation ok for %r.", request)
+
+        headers = {}
+        user_code = self.user_code_generator() if self.user_code_generator else generate_token()
+        data = {
+            "verification_uri": self.verification_uri,
+            "expires_in": self.expires_in,
+            "user_code": user_code,
+            "device_code": generate_token(),
+        }
+        if self.interval is not None:
+            data["interval"] = self.interval
+
+
+        verification_uri_complete = self.verification_uri_complete(user_code)
+        if verification_uri_complete:
+            data["verification_uri_complete"] = verification_uri_complete
+
+        return headers, data, 200
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/pre_configured.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/pre_configured.py
new file mode 100644
index 0000000000000000000000000000000000000000..6cce683304ba7d86c78533fec44862f4568f7bfc
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/endpoints/pre_configured.py
@@ -0,0 +1,36 @@
+from oauthlib.oauth2.rfc8628.endpoints.device_authorization import (
+    DeviceAuthorizationEndpoint,
+)
+
+from typing import Callable, Optional
+from oauthlib.openid.connect.core.request_validator import RequestValidator
+
+
+class DeviceApplicationServer(DeviceAuthorizationEndpoint):
+    """An all-in-one endpoint featuring Authorization code grant and Bearer tokens."""
+
+    def __init__(
+        self,
+        request_validator: RequestValidator,
+        verification_uri: str,
+        interval: int = 5,
+        verification_uri_complete: Optional[str] = None,  # noqa: FA100
+        user_code_generator: Callable[[None], str] = None,
+        **kwargs,
+    ):
+        """Construct a new web application server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.rfc8626.RequestValidator.
+        :param interval: How long the device needs to wait before polling the server
+        :param verification_uri: the verification_uri to be send back.
+        :param user_code_generator: a callable that allows the user code to be configured.
+        """
+        DeviceAuthorizationEndpoint.__init__(
+            self,
+            request_validator,
+            interval=interval,
+            verification_uri=verification_uri,
+            user_code_generator=user_code_generator,
+            verification_uri_complete=verification_uri_complete,
+        )
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/errors.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/errors.py
new file mode 100644
index 0000000000000000000000000000000000000000..a43593898ebb927d70d45f1482f1e5da465d3949
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/errors.py
@@ -0,0 +1,55 @@
+from oauthlib.oauth2.rfc6749.errors import OAuth2Error
+
+"""
+oauthlib.oauth2.rfc8628.errors
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Error used both by OAuth2 clients and providers to represent the spec
+defined error responses specific to the the device grant
+"""
+
+
+class AuthorizationPendingError(OAuth2Error):
+    """
+    For the device authorization grant;
+      The authorization request is still pending as the end user hasn't
+      yet completed the user-interaction steps (Section 3.3).  The
+      client SHOULD repeat the access token request to the token
+      endpoint (a process known as polling).  Before each new request,
+      the client MUST wait at least the number of seconds specified by
+      the "interval" parameter of the device authorization response,
+      or 5 seconds if none was provided, and respect any
+      increase in the polling interval required by the "slow_down"
+      error.
+    """
+
+    error = "authorization_pending"
+
+
+class SlowDownError(OAuth2Error):
+    """
+    A variant of "authorization_pending", the authorization request is
+    still pending and polling should continue, but the interval MUST
+    be increased by 5 seconds for this and all subsequent requests.
+    """
+
+    error = "slow_down"
+
+
+class ExpiredTokenError(OAuth2Error):
+    """
+    The "device_code" has expired, and the device authorization
+    session has concluded.  The client MAY commence a new device
+    authorization request but SHOULD wait for user interaction before
+    restarting to avoid unnecessary polling.
+    """
+
+    error = "expired_token"
+
+
+class AccessDenied(OAuth2Error):
+    """
+    The authorization request was denied.
+    """
+
+    error = "access_denied"
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..418dba775d13c97c76086b1882753165d7e154c6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/__init__.py
@@ -0,0 +1 @@
+from oauthlib.oauth2.rfc8628.grant_types.device_code import DeviceCodeGrant
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/device_code.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/device_code.py
new file mode 100644
index 0000000000000000000000000000000000000000..082daf0fccf04fdc33656ddb3f833419648949d2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/grant_types/device_code.py
@@ -0,0 +1,111 @@
+from __future__ import annotations
+import json
+
+from typing import Callable
+
+from oauthlib import common # noqa: TC001
+
+from oauthlib.oauth2.rfc6749 import errors as rfc6749_errors
+from oauthlib.oauth2.rfc6749.grant_types.base import GrantTypeBase
+
+
+class DeviceCodeGrant(GrantTypeBase):
+    def create_authorization_response(
+        self, request: common.Request, token_handler: Callable
+    ) -> tuple[dict, str, int]:
+        """
+        Validate the device flow request -> create the access token
+        -> persist the token -> return the token.
+        """
+        headers = self._get_default_headers()
+        try:
+            self.validate_token_request(request)
+        except rfc6749_errors.OAuth2Error as e:
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request, refresh_token=False)
+
+        for modifier in self._token_modifiers:
+            token = modifier(token)
+
+        self.request_validator.save_token(token, request)
+
+        return self.create_token_response(request, token_handler)
+
+    def validate_token_request(self, request: common.Request) -> None:
+        """
+        Performs the necessary check against the request to ensure
+        it's allowed to retrieve a token.
+        """
+        for validator in self.custom_validators.pre_token:
+            validator(request)
+
+        if not getattr(request, "grant_type", None):
+            raise rfc6749_errors.InvalidRequestError(
+                "Request is missing grant type.", request=request
+            )
+
+        if request.grant_type != "urn:ietf:params:oauth:grant-type:device_code":
+            raise rfc6749_errors.UnsupportedGrantTypeError(request=request)
+
+        for param in ("grant_type", "scope"):
+            if param in request.duplicate_params:
+                raise rfc6749_errors.InvalidRequestError(
+                    description=f"Duplicate {param} parameter.", request=request
+                )
+
+        if not self.request_validator.authenticate_client(request):
+            raise rfc6749_errors.InvalidClientError(request=request)
+        elif not hasattr(request.client, "client_id"):
+            raise NotImplementedError(
+                "Authenticate client must set the "
+                "request.client.client_id attribute "
+                "in authenticate_client."
+            )
+
+        # Ensure client is authorized use of this grant type
+        self.validate_grant_type(request)
+
+        request.client_id = request.client_id or request.client.client_id
+        self.validate_scopes(request)
+
+        for validator in self.custom_validators.post_token:
+            validator(request)
+
+    def create_token_response(
+        self, request: common.Request, token_handler: Callable
+    ) -> tuple[dict, str, int]:
+        """Return token or error in json format.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :param token_handler: A token handler instance, for example of type
+                              oauthlib.oauth2.BearerToken.
+
+        If the access token request is valid and authorized, the
+        authorization server issues an access token and optional refresh
+        token as described in `Section 5.1`_.  If the request failed client
+        authentication or is invalid, the authorization server returns an
+        error response as described in `Section 5.2`_.
+        .. _`Section 5.1`: https://tools.ietf.org/html/rfc6749#section-5.1
+        .. _`Section 5.2`: https://tools.ietf.org/html/rfc6749#section-5.2
+        """
+        headers = self._get_default_headers()
+        try:
+            if self.request_validator.client_authentication_required(
+                request
+            ) and not self.request_validator.authenticate_client(request):
+                raise rfc6749_errors.InvalidClientError(request=request)
+
+            self.validate_token_request(request)
+
+        except rfc6749_errors.OAuth2Error as e:
+            headers.update(e.headers)
+            return headers, e.json, e.status_code
+
+        token = token_handler.create_token(request, self.refresh_token)
+
+        self.request_validator.save_token(token, request)
+
+        return headers, json.dumps(token), 200
diff --git a/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/request_validator.py b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/request_validator.py
new file mode 100644
index 0000000000000000000000000000000000000000..70ee7824e92dae12b5b44d073f11c708ebd07577
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/oauth2/rfc8628/request_validator.py
@@ -0,0 +1,25 @@
+from oauthlib.oauth2 import RequestValidator as OAuth2RequestValidator
+
+
+class RequestValidator(OAuth2RequestValidator):
+    def client_authentication_required(self, request, *args, **kwargs):
+        """Determine if client authentication is required for current request.
+
+        According to the rfc8628, client authentication is required in the following cases:
+            - Device Authorization Request follows the, the client authentication requirements
+              of Section 3.2.1 of [RFC6749] apply to requests on this endpoint, which means that
+              confidential clients (those that have established client credentials) authenticate
+              in the same manner as when making requests to the token endpoint, and
+              public clients provide the "client_id" parameter to identify themselves,
+              see `Section 3.1`_.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - Device Authorization Request
+
+        .. _`Section 3.1`: https://www.rfc-editor.org/rfc/rfc8628#section-3.1
+        """
+        return True
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/openid/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3174374798f21cc8d5f23e67b2077f14234a1a6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/__init__.py
@@ -0,0 +1,7 @@
+"""
+oauthlib.openid
+~~~~~~~~~~~~~~
+
+"""
+from .connect.core.endpoints import Server, UserInfoEndpoint
+from .connect.core.request_validator import RequestValidator
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/__pycache__/tokens.cpython-313.pyc b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/__pycache__/tokens.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..7017ff4f3211d2007ee5d297cfff47c0a5b27fd4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/__init__.py
@@ -0,0 +1,9 @@
+"""
+oauthlib.oopenid.core
+~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various logic needed
+for consuming and providing OpenID Connect
+"""
+from .pre_configured import Server
+from .userinfo import UserInfoEndpoint
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/pre_configured.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/pre_configured.py
new file mode 100644
index 0000000000000000000000000000000000000000..17df516d17e9409dedc8902fa3a9ae38195c2067
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/pre_configured.py
@@ -0,0 +1,139 @@
+"""
+oauthlib.openid.connect.core.endpoints.pre_configured
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of various endpoints needed
+for providing OpenID Connect servers.
+"""
+
+from oauthlib.oauth2.rfc6749.endpoints import (
+    AuthorizationEndpoint,
+    IntrospectEndpoint,
+    ResourceEndpoint,
+    RevocationEndpoint,
+    TokenEndpoint,
+)
+from oauthlib.oauth2.rfc6749.grant_types import (
+    AuthorizationCodeGrant as OAuth2AuthorizationCodeGrant,
+    ClientCredentialsGrant,
+    ImplicitGrant as OAuth2ImplicitGrant,
+    ResourceOwnerPasswordCredentialsGrant,
+)
+from oauthlib.oauth2.rfc8628.grant_types import DeviceCodeGrant
+from oauthlib.oauth2.rfc6749.tokens import BearerToken
+
+from ..grant_types import (
+    AuthorizationCodeGrant,
+    HybridGrant,
+    ImplicitGrant,
+    RefreshTokenGrant,
+)
+from ..grant_types.dispatchers import (
+    AuthorizationCodeGrantDispatcher,
+    AuthorizationTokenGrantDispatcher,
+    ImplicitTokenGrantDispatcher,
+)
+from ..tokens import JWTToken
+from .userinfo import UserInfoEndpoint
+
+
+class Server(
+    AuthorizationEndpoint,
+    IntrospectEndpoint,
+    TokenEndpoint,
+    ResourceEndpoint,
+    RevocationEndpoint,
+    UserInfoEndpoint,
+):
+    """
+    An all-in-one endpoint featuring all four major grant types
+    and extension grants.
+    """
+
+    def __init__(
+        self,
+        request_validator,
+        token_expires_in=None,
+        token_generator=None,
+        refresh_token_generator=None,
+        *args,
+        **kwargs,
+    ):
+        """Construct a new all-grants-in-one server.
+
+        :param request_validator: An implementation of
+                                  oauthlib.oauth2.RequestValidator.
+        :param token_expires_in: An int or a function to generate a token
+                                 expiration offset (in seconds) given a
+                                 oauthlib.common.Request object.
+        :param token_generator: A function to generate a token from a request.
+        :param refresh_token_generator: A function to generate a token from a
+                                        request for the refresh token.
+        :param kwargs: Extra parameters to pass to authorization-,
+                       token-, resource-, and revocation-endpoint constructors.
+        """
+        self.auth_grant = OAuth2AuthorizationCodeGrant(request_validator)
+        self.implicit_grant = OAuth2ImplicitGrant(request_validator)
+        self.password_grant = ResourceOwnerPasswordCredentialsGrant(request_validator)
+        self.credentials_grant = ClientCredentialsGrant(request_validator)
+        self.refresh_grant = RefreshTokenGrant(request_validator)
+        self.openid_connect_auth = AuthorizationCodeGrant(request_validator)
+        self.openid_connect_implicit = ImplicitGrant(request_validator)
+        self.openid_connect_hybrid = HybridGrant(request_validator)
+        self.device_code_grant = DeviceCodeGrant(request_validator, **kwargs)
+
+        self.bearer = BearerToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+
+        self.jwt = JWTToken(
+            request_validator, token_generator, token_expires_in, refresh_token_generator
+        )
+
+        self.auth_grant_choice = AuthorizationCodeGrantDispatcher(
+            default_grant=self.auth_grant, oidc_grant=self.openid_connect_auth
+        )
+        self.implicit_grant_choice = ImplicitTokenGrantDispatcher(
+            default_grant=self.implicit_grant, oidc_grant=self.openid_connect_implicit
+        )
+
+        # See http://openid.net/specs/oauth-v2-multiple-response-types-1_0.html#Combinations for valid combinations
+        # internally our AuthorizationEndpoint will ensure they can appear in any order for any valid combination
+        AuthorizationEndpoint.__init__(
+            self,
+            default_response_type="code",
+            response_types={
+                "code": self.auth_grant_choice,
+                "token": self.implicit_grant_choice,
+                "id_token": self.openid_connect_implicit,
+                "id_token token": self.openid_connect_implicit,
+                "code token": self.openid_connect_hybrid,
+                "code id_token": self.openid_connect_hybrid,
+                "code id_token token": self.openid_connect_hybrid,
+                "none": self.auth_grant,
+            },
+            default_token_type=self.bearer,
+        )
+
+        self.token_grant_choice = AuthorizationTokenGrantDispatcher(
+            request_validator, default_grant=self.auth_grant, oidc_grant=self.openid_connect_auth
+        )
+
+        TokenEndpoint.__init__(
+            self,
+            default_grant_type="authorization_code",
+            grant_types={
+                "authorization_code": self.token_grant_choice,
+                "password": self.password_grant,
+                "client_credentials": self.credentials_grant,
+                "refresh_token": self.refresh_grant,
+                "urn:ietf:params:oauth:grant-type:device_code": self.device_code_grant,
+            },
+            default_token_type=self.bearer,
+        )
+        ResourceEndpoint.__init__(
+            self, default_token="Bearer", token_types={"Bearer": self.bearer, "JWT": self.jwt}
+        )
+        RevocationEndpoint.__init__(self, request_validator)
+        IntrospectEndpoint.__init__(self, request_validator)
+        UserInfoEndpoint.__init__(self, request_validator)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/userinfo.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/userinfo.py
new file mode 100644
index 0000000000000000000000000000000000000000..7aa2bbe97d34fa5afce4168256aafe1c8ce5fcae
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/endpoints/userinfo.py
@@ -0,0 +1,106 @@
+"""
+oauthlib.openid.connect.core.endpoints.userinfo
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module is an implementation of userinfo endpoint.
+"""
+import json
+import logging
+
+from oauthlib.common import Request
+from oauthlib.oauth2.rfc6749 import errors
+from oauthlib.oauth2.rfc6749.endpoints.base import (
+    BaseEndpoint, catch_errors_and_unavailability,
+)
+from oauthlib.oauth2.rfc6749.tokens import BearerToken
+
+log = logging.getLogger(__name__)
+
+
+class UserInfoEndpoint(BaseEndpoint):
+    """Authorizes access to userinfo resource.
+    """
+    def __init__(self, request_validator):
+        self.bearer = BearerToken(request_validator, None, None, None)
+        self.request_validator = request_validator
+        BaseEndpoint.__init__(self)
+
+    @catch_errors_and_unavailability
+    def create_userinfo_response(self, uri, http_method='GET', body=None, headers=None):
+        """Validate BearerToken and return userinfo from RequestValidator
+
+        The UserInfo Endpoint MUST return a
+        content-type header to indicate which format is being returned. The
+        content-type of the HTTP response MUST be application/json if the
+        response body is a text JSON object; the response body SHOULD be encoded
+        using UTF-8.
+        """
+        request = Request(uri, http_method, body, headers)
+        request.scopes = ["openid"]
+        self.validate_userinfo_request(request)
+
+        claims = self.request_validator.get_userinfo_claims(request)
+        if claims is None:
+            log.error('Userinfo MUST have claims for %r.', request)
+            raise errors.ServerError(status_code=500)
+
+        if isinstance(claims, dict):
+            resp_headers = {
+                'Content-Type': 'application/json'
+            }
+            if "sub" not in claims:
+                log.error('Userinfo MUST have "sub" for %r.', request)
+                raise errors.ServerError(status_code=500)
+            body = json.dumps(claims)
+        elif isinstance(claims, str):
+            resp_headers = {
+                'Content-Type': 'application/jwt'
+            }
+            body = claims
+        else:
+            log.error('Userinfo return unknown response for %r.', request)
+            raise errors.ServerError(status_code=500)
+        log.debug('Userinfo access valid for %r.', request)
+        return resp_headers, body, 200
+
+    def validate_userinfo_request(self, request):
+        """Ensure the request is valid.
+
+        5.3.1.  UserInfo Request
+        The Client sends the UserInfo Request using either HTTP GET or HTTP
+        POST. The Access Token obtained from an OpenID Connect Authentication
+        Request MUST be sent as a Bearer Token, per `Section 2`_ of OAuth 2.0
+        Bearer Token Usage [RFC6750].
+
+        It is RECOMMENDED that the request use the HTTP GET method and the
+        Access Token be sent using the Authorization header field.
+
+        The following is a non-normative example of a UserInfo Request:
+
+        .. code-block:: http
+
+            GET /userinfo HTTP/1.1
+            Host: server.example.com
+            Authorization: Bearer SlAV32hkKG
+
+        5.3.3. UserInfo Error Response
+        When an error condition occurs, the UserInfo Endpoint returns an Error
+        Response as defined in `Section 3`_ of OAuth 2.0 Bearer Token Usage
+        [RFC6750]. (HTTP errors unrelated to RFC 6750 are returned to the User
+        Agent using the appropriate HTTP status code.)
+
+        The following is a non-normative example of a UserInfo Error Response:
+
+        .. code-block:: http
+
+            HTTP/1.1 401 Unauthorized
+            WWW-Authenticate: Bearer error="invalid_token",
+                error_description="The Access Token expired"
+
+        .. _`Section 2`: https://datatracker.ietf.org/doc/html/rfc6750#section-2
+        .. _`Section 3`: https://datatracker.ietf.org/doc/html/rfc6750#section-3
+        """
+        if not self.bearer.validate_request(request):
+            raise errors.InvalidTokenError()
+        if "openid" not in request.scopes:
+            raise errors.InsufficientScopeError()
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/exceptions.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/exceptions.py
new file mode 100644
index 0000000000000000000000000000000000000000..291cf13776871147e9660a35254bb70a595fc791
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/exceptions.py
@@ -0,0 +1,150 @@
+"""
+oauthlib.oauth2.rfc6749.errors
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Error used both by OAuth 2 clients and providers to represent the spec
+defined error responses for all four core grant types.
+"""
+import inspect
+import sys
+
+from oauthlib.oauth2.rfc6749.errors import FatalClientError, OAuth2Error
+
+
+class FatalOpenIDClientError(FatalClientError):
+    pass
+
+
+class OpenIDClientError(OAuth2Error):
+    pass
+
+
+class InteractionRequired(OpenIDClientError):
+    """
+    The Authorization Server requires End-User interaction to proceed.
+
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface for End-User interaction.
+    """
+    error = 'interaction_required'
+    status_code = 401
+
+
+class LoginRequired(OpenIDClientError):
+    """
+    The Authorization Server requires End-User authentication.
+
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface for End-User authentication.
+    """
+    error = 'login_required'
+    status_code = 401
+
+
+class AccountSelectionRequired(OpenIDClientError):
+    """
+    The End-User is REQUIRED to select a session at the Authorization Server.
+
+    The End-User MAY be authenticated at the Authorization Server with
+    different associated accounts, but the End-User did not select a session.
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface to prompt for a session to
+    use.
+    """
+    error = 'account_selection_required'
+
+
+class ConsentRequired(OpenIDClientError):
+    """
+    The Authorization Server requires End-User consent.
+
+    This error MAY be returned when the prompt parameter value in the
+    Authentication Request is none, but the Authentication Request cannot be
+    completed without displaying a user interface for End-User consent.
+    """
+    error = 'consent_required'
+    status_code = 401
+
+
+class InvalidRequestURI(OpenIDClientError):
+    """
+    The request_uri in the Authorization Request returns an error or
+    contains invalid data.
+    """
+    error = 'invalid_request_uri'
+    description = ('The request_uri in the Authorization Request returns an '
+                  'error or contains invalid data.')
+
+
+class InvalidRequestObject(OpenIDClientError):
+    """
+    The request parameter contains an invalid Request Object.
+    """
+    error = 'invalid_request_object'
+    description = 'The request parameter contains an invalid Request Object.'
+
+
+class RequestNotSupported(OpenIDClientError):
+    """
+    The OP does not support use of the request parameter.
+    """
+    error = 'request_not_supported'
+    description = 'The request parameter is not supported.'
+
+
+class RequestURINotSupported(OpenIDClientError):
+    """
+    The OP does not support use of the request_uri parameter.
+    """
+    error = 'request_uri_not_supported'
+    description = 'The request_uri parameter is not supported.'
+
+
+class RegistrationNotSupported(OpenIDClientError):
+    """
+    The OP does not support use of the registration parameter.
+    """
+    error = 'registration_not_supported'
+    description = 'The registration parameter is not supported.'
+
+
+class InvalidTokenError(OAuth2Error):
+    """
+    The access token provided is expired, revoked, malformed, or
+    invalid for other reasons.  The resource SHOULD respond with
+    the HTTP 401 (Unauthorized) status code.  The client MAY
+    request a new access token and retry the protected resource
+    request.
+    """
+    error = 'invalid_token'
+    status_code = 401
+    description = ("The access token provided is expired, revoked, malformed, "
+                   "or invalid for other reasons.")
+
+
+class InsufficientScopeError(OAuth2Error):
+    """
+    The request requires higher privileges than provided by the
+    access token.  The resource server SHOULD respond with the HTTP
+    403 (Forbidden) status code and MAY include the "scope"
+    attribute with the scope necessary to access the protected
+    resource.
+    """
+    error = 'insufficient_scope'
+    status_code = 403
+    description = ("The request requires higher privileges than provided by "
+                   "the access token.")
+
+
+def raise_from_error(error, params=None):
+    kwargs = {
+        'description': params.get('error_description'),
+        'uri': params.get('error_uri'),
+        'state': params.get('state')
+    }
+    for _, cls in inspect.getmembers(sys.modules[__name__], inspect.isclass):
+        if cls.error == error:
+            raise cls(**kwargs)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/__init__.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8dad5f607b9856704b3f074d31f3b701ddfafd94
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/__init__.py
@@ -0,0 +1,13 @@
+"""
+oauthlib.openid.connect.core.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+from .authorization_code import AuthorizationCodeGrant
+from .base import GrantTypeBase
+from .dispatchers import (
+    AuthorizationCodeGrantDispatcher, AuthorizationTokenGrantDispatcher,
+    ImplicitTokenGrantDispatcher,
+)
+from .hybrid import HybridGrant
+from .implicit import ImplicitGrant
+from .refresh_token import RefreshTokenGrant
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diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/authorization_code.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/authorization_code.py
new file mode 100644
index 0000000000000000000000000000000000000000..6b2dcc3bdd12d27d280890494286efc5f0c9befb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/authorization_code.py
@@ -0,0 +1,43 @@
+"""
+oauthlib.openid.connect.core.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib.oauth2.rfc6749.grant_types.authorization_code import (
+    AuthorizationCodeGrant as OAuth2AuthorizationCodeGrant,
+)
+
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class AuthorizationCodeGrant(GrantTypeBase):
+
+    def __init__(self, request_validator=None, **kwargs):
+        self.proxy_target = OAuth2AuthorizationCodeGrant(
+            request_validator=request_validator, **kwargs)
+        self.custom_validators.post_auth.append(
+            self.openid_authorization_validator)
+        self.register_token_modifier(self.add_id_token)
+
+    def add_id_token(self, token, token_handler, request):
+        """
+        Construct an initial version of id_token, and let the
+        request_validator sign or encrypt it.
+
+        The authorization_code version of this method is used to
+        retrieve the nonce accordingly to the code storage.
+        """
+        # Treat it as normal OAuth 2 auth code request if openid is not present
+        if not request.scopes or 'openid' not in request.scopes:
+            return token
+
+        nonce = self.request_validator.get_authorization_code_nonce(
+            request.client_id,
+            request.code,
+            request.redirect_uri,
+            request
+        )
+        return super().add_id_token(token, token_handler, request, nonce=nonce)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/base.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..29d583eb1c0677a5167ddccee274d596e3b1aca7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/base.py
@@ -0,0 +1,330 @@
+import base64
+import hashlib
+import logging
+import time
+from json import loads
+
+from oauthlib.oauth2.rfc6749.errors import (
+    ConsentRequired, InvalidRequestError, LoginRequired,
+)
+
+log = logging.getLogger(__name__)
+
+
+class GrantTypeBase:
+
+    # Just proxy the majority of method calls through to the
+    # proxy_target grant type handler, which will usually be either
+    # the standard OAuth2 AuthCode or Implicit grant types.
+    def __getattr__(self, attr):
+        return getattr(self.proxy_target, attr)
+
+    def __setattr__(self, attr, value):
+        proxied_attrs = {'refresh_token', 'response_types'}
+        if attr in proxied_attrs:
+            setattr(self.proxy_target, attr, value)
+        else:
+            super(OpenIDConnectBase, self).__setattr__(attr, value)
+
+    def validate_authorization_request(self, request):
+        """Validates the OpenID Connect authorization request parameters.
+
+        :returns: (list of scopes, dict of request info)
+        """
+        return self.proxy_target.validate_authorization_request(request)
+
+    def _inflate_claims(self, request):
+        # this may be called multiple times in a single request so make sure we only de-serialize the claims once
+        if request.claims and not isinstance(request.claims, dict):
+            # specific claims are requested during the Authorization Request and may be requested for inclusion
+            # in either the id_token or the UserInfo endpoint response
+            # see http://openid.net/specs/openid-connect-core-1_0.html#ClaimsParameter
+            try:
+                request.claims = loads(request.claims)
+            except Exception as ex:
+                raise InvalidRequestError(description="Malformed claims parameter",
+                                          uri="http://openid.net/specs/openid-connect-core-1_0.html#ClaimsParameter")
+
+    def id_token_hash(self, value, hashfunc=hashlib.sha256):
+        """
+        Its value is the base64url encoding of the left-most half of the
+        hash of the octets of the ASCII representation of the access_token
+        value, where the hash algorithm used is the hash algorithm used in
+        the alg Header Parameter of the ID Token's JOSE Header.
+
+        For instance, if the alg is RS256, hash the access_token value
+        with SHA-256, then take the left-most 128 bits and
+        base64url-encode them.
+        For instance, if the alg is HS512, hash the code value with
+        SHA-512, then take the left-most 256 bits and base64url-encode
+        them. The c_hash value is a case-sensitive string.
+
+        Example of hash from OIDC specification (bound to a JWS using RS256):
+
+        code:
+        Qcb0Orv1zh30vL1MPRsbm-diHiMwcLyZvn1arpZv-Jxf_11jnpEX3Tgfvk
+
+        c_hash:
+        LDktKdoQak3Pk0cnXxCltA
+        """
+        digest = hashfunc(value.encode()).digest()
+        left_most = len(digest) // 2
+        return base64.urlsafe_b64encode(digest[:left_most]).decode().rstrip("=")
+
+    def add_id_token(self, token, token_handler, request, nonce=None):
+        """
+        Construct an initial version of id_token, and let the
+        request_validator sign or encrypt it.
+
+        The initial version can contain the fields below, accordingly
+        to the spec:
+        - aud
+        - iat
+        - nonce
+        - at_hash
+        - c_hash
+        """
+        # Treat it as normal OAuth 2 auth code request if openid is not present
+        if not request.scopes or 'openid' not in request.scopes:
+            return token
+
+        # Only add an id token on auth/token step if asked for.
+        if request.response_type and 'id_token' not in request.response_type:
+            return token
+
+        # Implementation mint its own id_token without help.
+        id_token = self.request_validator.get_id_token(token, token_handler, request)
+        if id_token:
+            token['id_token'] = id_token
+            return token
+
+        # Fallback for asking some help from oauthlib framework.
+        # Start with technicals fields bound to the specification.
+        id_token = {}
+        id_token['aud'] = request.client_id
+        id_token['iat'] = int(time.time())
+
+        # nonce is REQUIRED when response_type value is:
+        # - id_token token (Implicit)
+        # - id_token (Implicit)
+        # - code id_token (Hybrid)
+        # - code id_token token (Hybrid)
+        #
+        # nonce is OPTIONAL when response_type value is:
+        # - code (Authorization Code)
+        # - code token (Hybrid)
+        if nonce is not None:
+            id_token["nonce"] = nonce
+
+        # at_hash is REQUIRED when response_type value is:
+        # - id_token token (Implicit)
+        # - code id_token token (Hybrid)
+        #
+        # at_hash is OPTIONAL when:
+        # - code (Authorization code)
+        # - code id_token (Hybrid)
+        # - code token (Hybrid)
+        #
+        # at_hash MAY NOT be used when:
+        # - id_token (Implicit)
+        if "access_token" in token:
+            id_token["at_hash"] = self.id_token_hash(token["access_token"])
+
+        # c_hash is REQUIRED when response_type value is:
+        # - code id_token (Hybrid)
+        # - code id_token token (Hybrid)
+        #
+        # c_hash is OPTIONAL for others.
+        if "code" in token:
+            id_token["c_hash"] = self.id_token_hash(token["code"])
+
+        # Call request_validator to complete/sign/encrypt id_token
+        token['id_token'] = self.request_validator.finalize_id_token(id_token, token, token_handler, request)
+
+        return token
+
+    def openid_authorization_validator(self, request):
+        """Perform OpenID Connect specific authorization request validation.
+
+        nonce
+                OPTIONAL. String value used to associate a Client session with
+                an ID Token, and to mitigate replay attacks. The value is
+                passed through unmodified from the Authentication Request to
+                the ID Token. Sufficient entropy MUST be present in the nonce
+                values used to prevent attackers from guessing values
+
+        display
+                OPTIONAL. ASCII string value that specifies how the
+                Authorization Server displays the authentication and consent
+                user interface pages to the End-User. The defined values are:
+
+                    page - The Authorization Server SHOULD display the
+                    authentication and consent UI consistent with a full User
+                    Agent page view. If the display parameter is not specified,
+                    this is the default display mode.
+
+                    popup - The Authorization Server SHOULD display the
+                    authentication and consent UI consistent with a popup User
+                    Agent window. The popup User Agent window should be of an
+                    appropriate size for a login-focused dialog and should not
+                    obscure the entire window that it is popping up over.
+
+                    touch - The Authorization Server SHOULD display the
+                    authentication and consent UI consistent with a device that
+                    leverages a touch interface.
+
+                    wap - The Authorization Server SHOULD display the
+                    authentication and consent UI consistent with a "feature
+                    phone" type display.
+
+                The Authorization Server MAY also attempt to detect the
+                capabilities of the User Agent and present an appropriate
+                display.
+
+        prompt
+                OPTIONAL. Space delimited, case sensitive list of ASCII string
+                values that specifies whether the Authorization Server prompts
+                the End-User for reauthentication and consent. The defined
+                values are:
+
+                    none - The Authorization Server MUST NOT display any
+                    authentication or consent user interface pages. An error is
+                    returned if an End-User is not already authenticated or the
+                    Client does not have pre-configured consent for the
+                    requested Claims or does not fulfill other conditions for
+                    processing the request. The error code will typically be
+                    login_required, interaction_required, or another code
+                    defined in Section 3.1.2.6. This can be used as a method to
+                    check for existing authentication and/or consent.
+
+                    login - The Authorization Server SHOULD prompt the End-User
+                    for reauthentication. If it cannot reauthenticate the
+                    End-User, it MUST return an error, typically
+                    login_required.
+
+                    consent - The Authorization Server SHOULD prompt the
+                    End-User for consent before returning information to the
+                    Client. If it cannot obtain consent, it MUST return an
+                    error, typically consent_required.
+
+                    select_account - The Authorization Server SHOULD prompt the
+                    End-User to select a user account. This enables an End-User
+                    who has multiple accounts at the Authorization Server to
+                    select amongst the multiple accounts that they might have
+                    current sessions for. If it cannot obtain an account
+                    selection choice made by the End-User, it MUST return an
+                    error, typically account_selection_required.
+
+                The prompt parameter can be used by the Client to make sure
+                that the End-User is still present for the current session or
+                to bring attention to the request. If this parameter contains
+                none with any other value, an error is returned.
+
+        max_age
+                OPTIONAL. Maximum Authentication Age. Specifies the allowable
+                elapsed time in seconds since the last time the End-User was
+                actively authenticated by the OP. If the elapsed time is
+                greater than this value, the OP MUST attempt to actively
+                re-authenticate the End-User. (The max_age request parameter
+                corresponds to the OpenID 2.0 PAPE [OpenID.PAPE] max_auth_age
+                request parameter.) When max_age is used, the ID Token returned
+                MUST include an auth_time Claim Value.
+
+        ui_locales
+                OPTIONAL. End-User's preferred languages and scripts for the
+                user interface, represented as a space-separated list of BCP47
+                [RFC5646] language tag values, ordered by preference. For
+                instance, the value "fr-CA fr en" represents a preference for
+                French as spoken in Canada, then French (without a region
+                designation), followed by English (without a region
+                designation). An error SHOULD NOT result if some or all of the
+                requested locales are not supported by the OpenID Provider.
+
+        id_token_hint
+                OPTIONAL. ID Token previously issued by the Authorization
+                Server being passed as a hint about the End-User's current or
+                past authenticated session with the Client. If the End-User
+                identified by the ID Token is logged in or is logged in by the
+                request, then the Authorization Server returns a positive
+                response; otherwise, it SHOULD return an error, such as
+                login_required. When possible, an id_token_hint SHOULD be
+                present when prompt=none is used and an invalid_request error
+                MAY be returned if it is not; however, the server SHOULD
+                respond successfully when possible, even if it is not present.
+                The Authorization Server need not be listed as an audience of
+                the ID Token when it is used as an id_token_hint value. If the
+                ID Token received by the RP from the OP is encrypted, to use it
+                as an id_token_hint, the Client MUST decrypt the signed ID
+                Token contained within the encrypted ID Token. The Client MAY
+                re-encrypt the signed ID token to the Authentication Server
+                using a key that enables the server to decrypt the ID Token,
+                and use the re-encrypted ID token as the id_token_hint value.
+
+        login_hint
+                OPTIONAL. Hint to the Authorization Server about the login
+                identifier the End-User might use to log in (if necessary).
+                This hint can be used by an RP if it first asks the End-User
+                for their e-mail address (or other identifier) and then wants
+                to pass that value as a hint to the discovered authorization
+                service. It is RECOMMENDED that the hint value match the value
+                used for discovery. This value MAY also be a phone number in
+                the format specified for the phone_number Claim. The use of
+                this parameter is left to the OP's discretion.
+
+        acr_values
+                OPTIONAL. Requested Authentication Context Class Reference
+                values. Space-separated string that specifies the acr values
+                that the Authorization Server is being requested to use for
+                processing this Authentication Request, with the values
+                appearing in order of preference. The Authentication Context
+                Class satisfied by the authentication performed is returned as
+                the acr Claim Value, as specified in Section 2. The acr Claim
+                is requested as a Voluntary Claim by this parameter.
+        """
+
+        # Treat it as normal OAuth 2 auth code request if openid is not present
+        if not request.scopes or 'openid' not in request.scopes:
+            return {}
+
+        prompt = request.prompt if request.prompt else []
+        if hasattr(prompt, 'split'):
+            prompt = prompt.strip().split()
+        prompt = set(prompt)
+
+        if 'none' in prompt:
+
+            if len(prompt) > 1:
+                msg = "Prompt none is mutually exclusive with other values."
+                raise InvalidRequestError(request=request, description=msg)
+
+            if not self.request_validator.validate_silent_login(request):
+                raise LoginRequired(request=request)
+
+            if not self.request_validator.validate_silent_authorization(request):
+                raise ConsentRequired(request=request)
+
+        self._inflate_claims(request)
+
+        if not self.request_validator.validate_user_match(
+                request.id_token_hint, request.scopes, request.claims, request):
+            msg = "Session user does not match client supplied user."
+            raise LoginRequired(request=request, description=msg)
+
+        ui_locales = request.ui_locales if request.ui_locales else []
+        if hasattr(ui_locales, 'split'):
+            ui_locales = ui_locales.strip().split()
+
+        request_info = {
+            'display': request.display,
+            'nonce': request.nonce,
+            'prompt': prompt,
+            'ui_locales': ui_locales,
+            'id_token_hint': request.id_token_hint,
+            'login_hint': request.login_hint,
+            'claims': request.claims
+        }
+
+        return request_info
+
+
+OpenIDConnectBase = GrantTypeBase
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/dispatchers.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/dispatchers.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e0739684f107801ff094f98190efcd17ae438c1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/dispatchers.py
@@ -0,0 +1,101 @@
+import logging
+
+log = logging.getLogger(__name__)
+
+
+class Dispatcher:
+    default_grant = None
+    oidc_grant = None
+
+
+class AuthorizationCodeGrantDispatcher(Dispatcher):
+    """
+    This is an adapter class that will route simple Authorization Code
+    requests, those that have `response_type=code` and a scope including
+    `openid` to either the `default_grant` or the `oidc_grant` based on
+    the scopes requested.
+    """
+    def __init__(self, default_grant=None, oidc_grant=None):
+        self.default_grant = default_grant
+        self.oidc_grant = oidc_grant
+
+    def _handler_for_request(self, request):
+        handler = self.default_grant
+
+        if request.scopes and "openid" in request.scopes:
+            handler = self.oidc_grant
+
+        log.debug('Selecting handler for request %r.', handler)
+        return handler
+
+    def create_authorization_response(self, request, token_handler):
+        """Read scope and route to the designated handler."""
+        return self._handler_for_request(request).create_authorization_response(request, token_handler)
+
+    def validate_authorization_request(self, request):
+        """Read scope and route to the designated handler."""
+        return self._handler_for_request(request).validate_authorization_request(request)
+
+
+class ImplicitTokenGrantDispatcher(Dispatcher):
+    """
+    This is an adapter class that will route simple Authorization
+    requests, those that have `id_token` in `response_type` and a scope
+    including `openid` to either the `default_grant` or the `oidc_grant`
+    based on the scopes requested.
+    """
+    def __init__(self, default_grant=None, oidc_grant=None):
+        self.default_grant = default_grant
+        self.oidc_grant = oidc_grant
+
+    def _handler_for_request(self, request):
+        handler = self.default_grant
+
+        if request.scopes and "openid" in request.scopes and 'id_token' in request.response_type:
+            handler = self.oidc_grant
+
+        log.debug('Selecting handler for request %r.', handler)
+        return handler
+
+    def create_authorization_response(self, request, token_handler):
+        """Read scope and route to the designated handler."""
+        return self._handler_for_request(request).create_authorization_response(request, token_handler)
+
+    def validate_authorization_request(self, request):
+        """Read scope and route to the designated handler."""
+        return self._handler_for_request(request).validate_authorization_request(request)
+
+
+class AuthorizationTokenGrantDispatcher(Dispatcher):
+    """
+    This is an adapter class that will route simple Token requests, those that authorization_code have a scope
+    including 'openid' to either the default_grant or the oidc_grant based on the scopes requested.
+    """
+    def __init__(self, request_validator, default_grant=None, oidc_grant=None):
+        self.default_grant = default_grant
+        self.oidc_grant = oidc_grant
+        self.request_validator = request_validator
+
+    def _handler_for_request(self, request):
+        handler = self.default_grant
+        scopes = ()
+        parameters = dict(request.decoded_body)
+        client_id = parameters.get('client_id')
+        code = parameters.get('code')
+        redirect_uri = parameters.get('redirect_uri')
+
+        # If code is not present fallback to `default_grant` which will
+        # raise an error for the missing `code` in `create_token_response` step.
+        if code:
+            scopes = self.request_validator.get_authorization_code_scopes(client_id, code, redirect_uri, request)
+
+        if 'openid' in scopes:
+            handler = self.oidc_grant
+
+        log.debug('Selecting handler for request %r.', handler)
+        return handler
+
+    def create_token_response(self, request, token_handler):
+        """Read scope and route to the designated handler."""
+        handler = self._handler_for_request(request)
+        return handler.create_token_response(request, token_handler)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/hybrid.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/hybrid.py
new file mode 100644
index 0000000000000000000000000000000000000000..9c1fc702f9496c592b06437e774c5d492c1b7de3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/hybrid.py
@@ -0,0 +1,62 @@
+"""
+oauthlib.openid.connect.core.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib.oauth2.rfc6749.errors import InvalidRequestError
+from oauthlib.oauth2.rfc6749.grant_types.authorization_code import (
+    AuthorizationCodeGrant as OAuth2AuthorizationCodeGrant,
+)
+
+from ..request_validator import RequestValidator
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class HybridGrant(GrantTypeBase):
+
+    def __init__(self, request_validator=None, **kwargs):
+        self.request_validator = request_validator or RequestValidator()
+
+        self.proxy_target = OAuth2AuthorizationCodeGrant(
+            request_validator=request_validator, **kwargs)
+        # All hybrid response types should be fragment-encoded.
+        self.proxy_target.default_response_mode = "fragment"
+        self.register_response_type('code id_token')
+        self.register_response_type('code token')
+        self.register_response_type('code id_token token')
+        self.custom_validators.post_auth.append(
+            self.openid_authorization_validator)
+        # Hybrid flows can return the id_token from the authorization
+        # endpoint as part of the 'code' response
+        self.register_code_modifier(self.add_token)
+        self.register_code_modifier(self.add_id_token)
+        self.register_token_modifier(self.add_id_token)
+
+    def add_id_token(self, token, token_handler, request):
+        return super().add_id_token(token, token_handler, request, nonce=request.nonce)
+
+    def openid_authorization_validator(self, request):
+        """Additional validation when following the Authorization Code flow.
+        """
+        request_info = super().openid_authorization_validator(request)
+        if not request_info:  # returns immediately if OAuth2.0
+            return request_info
+
+        # REQUIRED if the Response Type of the request is `code
+        # id_token` or `code id_token token` and OPTIONAL when the
+        # Response Type of the request is `code token`. It is a string
+        # value used to associate a Client session with an ID Token,
+        # and to mitigate replay attacks. The value is passed through
+        # unmodified from the Authentication Request to the ID
+        # Token. Sufficient entropy MUST be present in the `nonce`
+        # values used to prevent attackers from guessing values. For
+        # implementation notes, see Section 15.5.2.
+        if request.response_type in ["code id_token", "code id_token token"] and not request.nonce:
+            raise InvalidRequestError(
+                request=request,
+                description='Request is missing mandatory nonce parameter.'
+            )
+        return request_info
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/implicit.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/implicit.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4fe6049bc29a8d9b202b9e0244a1b6c559d99d6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/implicit.py
@@ -0,0 +1,51 @@
+"""
+oauthlib.openid.connect.core.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib.oauth2.rfc6749.errors import InvalidRequestError
+from oauthlib.oauth2.rfc6749.grant_types.implicit import (
+    ImplicitGrant as OAuth2ImplicitGrant,
+)
+
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class ImplicitGrant(GrantTypeBase):
+
+    def __init__(self, request_validator=None, **kwargs):
+        self.proxy_target = OAuth2ImplicitGrant(
+            request_validator=request_validator, **kwargs)
+        self.register_response_type('id_token')
+        self.register_response_type('id_token token')
+        self.custom_validators.post_auth.append(
+            self.openid_authorization_validator)
+        self.register_token_modifier(self.add_id_token)
+
+    def add_id_token(self, token, token_handler, request):
+        if 'state' not in token and request.state:
+            token['state'] = request.state
+        return super().add_id_token(token, token_handler, request, nonce=request.nonce)
+
+    def openid_authorization_validator(self, request):
+        """Additional validation when following the implicit flow.
+        """
+        request_info = super().openid_authorization_validator(request)
+        if not request_info:  # returns immediately if OAuth2.0
+            return request_info
+
+        # REQUIRED. String value used to associate a Client session with an ID
+        # Token, and to mitigate replay attacks. The value is passed through
+        # unmodified from the Authentication Request to the ID Token.
+        # Sufficient entropy MUST be present in the nonce values used to
+        # prevent attackers from guessing values. For implementation notes, see
+        # Section 15.5.2.
+        if not request.nonce:
+            raise InvalidRequestError(
+                request=request,
+                description='Request is missing mandatory nonce parameter.'
+            )
+        return request_info
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/refresh_token.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/refresh_token.py
new file mode 100644
index 0000000000000000000000000000000000000000..43e4499c53c77a7f1486981f84e7fe49cf71f545
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/grant_types/refresh_token.py
@@ -0,0 +1,34 @@
+"""
+oauthlib.openid.connect.core.grant_types
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib.oauth2.rfc6749.grant_types.refresh_token import (
+    RefreshTokenGrant as OAuth2RefreshTokenGrant,
+)
+
+from .base import GrantTypeBase
+
+log = logging.getLogger(__name__)
+
+
+class RefreshTokenGrant(GrantTypeBase):
+
+    def __init__(self, request_validator=None, **kwargs):
+        self.proxy_target = OAuth2RefreshTokenGrant(
+            request_validator=request_validator, **kwargs)
+        self.register_token_modifier(self.add_id_token)
+
+    def add_id_token(self, token, token_handler, request):
+        """
+        Construct an initial version of id_token, and let the
+        request_validator sign or encrypt it.
+
+        The authorization_code version of this method is used to
+        retrieve the nonce accordingly to the code storage.
+        """
+        if not self.request_validator.refresh_id_token(request):
+            return token
+
+        return super().add_id_token(token, token_handler, request)
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/request_validator.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/request_validator.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3cea79b774d58cae6cc99be28334f76e1d67b56
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/request_validator.py
@@ -0,0 +1,320 @@
+"""
+oauthlib.openid.connect.core.request_validator
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import logging
+
+from oauthlib.oauth2.rfc6749.request_validator import (
+    RequestValidator as OAuth2RequestValidator,
+)
+
+log = logging.getLogger(__name__)
+
+
+class RequestValidator(OAuth2RequestValidator):
+
+    def get_authorization_code_scopes(self, client_id, code, redirect_uri, request):
+        """ Extracts scopes from saved authorization code.
+
+        The scopes returned by this method is used to route token requests
+        based on scopes passed to Authorization Code requests.
+
+        With that the token endpoint knows when to include OpenIDConnect
+        id_token in token response only based on authorization code scopes.
+
+        Only code param should be sufficient to retrieve grant code from
+        any storage you are using, `client_id` and `redirect_uri` can have a
+        blank value `""` don't forget to check it before using those values
+        in a select query if a database is used.
+
+        :param client_id: Unicode client identifier
+        :param code: Unicode authorization code grant
+        :param redirect_uri: Unicode absolute URI
+        :return: A list of scope
+
+        Method is used by:
+            - Authorization Token Grant Dispatcher
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_authorization_code_nonce(self, client_id, code, redirect_uri, request):
+        """ Extracts nonce from saved authorization code.
+
+        If present in the Authentication Request, Authorization
+        Servers MUST include a nonce Claim in the ID Token with the
+        Claim Value being the nonce value sent in the Authentication
+        Request. Authorization Servers SHOULD perform no other
+        processing on nonce values used. The nonce value is a
+        case-sensitive string.
+
+        Only code param should be sufficient to retrieve grant code from
+        any storage you are using. However, `client_id` and `redirect_uri`
+        have been validated and can be used also.
+
+        :param client_id: Unicode client identifier
+        :param code: Unicode authorization code grant
+        :param redirect_uri: Unicode absolute URI
+        :return: Unicode nonce
+
+        Method is used by:
+            - Authorization Token Grant Dispatcher
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_jwt_bearer_token(self, token, token_handler, request):
+        """Get JWT Bearer token or OpenID Connect ID token
+
+        If using OpenID Connect this SHOULD call `oauthlib.oauth2.RequestValidator.get_id_token`
+
+        :param token: A Bearer token dict
+        :param token_handler: the token handler (BearerToken class)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :return: The JWT Bearer token or OpenID Connect ID token (a JWS signed JWT)
+
+        Method is used by JWT Bearer and OpenID Connect tokens:
+            - JWTToken.create_token
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_id_token(self, token, token_handler, request):
+        """Get OpenID Connect ID token
+
+        This method is OPTIONAL and is NOT RECOMMENDED.
+        `finalize_id_token` SHOULD be implemented instead. However, if you
+        want a full control over the minting of the `id_token`, you
+        MAY want to override `get_id_token` instead of using
+        `finalize_id_token`.
+
+        In the OpenID Connect workflows when an ID Token is requested this method is called.
+        Subclasses should implement the construction, signing and optional encryption of the
+        ID Token as described in the OpenID Connect spec.
+
+        In addition to the standard OAuth2 request properties, the request may also contain
+        these OIDC specific properties which are useful to this method:
+
+            - nonce, if workflow is implicit or hybrid and it was provided
+            - claims, if provided to the original Authorization Code request
+
+        The token parameter is a dict which may contain an ``access_token`` entry, in which
+        case the resulting ID Token *should* include a calculated ``at_hash`` claim.
+
+        Similarly, when the request parameter has a ``code`` property defined, the ID Token
+        *should* include a calculated ``c_hash`` claim.
+
+        http://openid.net/specs/openid-connect-core-1_0.html (sections `3.1.3.6`_, `3.2.2.10`_, `3.3.2.11`_)
+
+        .. _`3.1.3.6`: http://openid.net/specs/openid-connect-core-1_0.html#CodeIDToken
+        .. _`3.2.2.10`: http://openid.net/specs/openid-connect-core-1_0.html#ImplicitIDToken
+        .. _`3.3.2.11`: http://openid.net/specs/openid-connect-core-1_0.html#HybridIDToken
+
+        :param token: A Bearer token dict
+        :param token_handler: the token handler (BearerToken class)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :return: The ID Token (a JWS signed JWT)
+        """
+        return None
+
+    def finalize_id_token(self, id_token, token, token_handler, request):
+        """Finalize OpenID Connect ID token & Sign or Encrypt.
+
+        In the OpenID Connect workflows when an ID Token is requested
+        this method is called.  Subclasses should implement the
+        construction, signing and optional encryption of the ID Token
+        as described in the OpenID Connect spec.
+
+        The `id_token` parameter is a dict containing a couple of OIDC
+        technical fields related to the specification. Prepopulated
+        attributes are:
+
+        - `aud`, equals to `request.client_id`.
+        - `iat`, equals to current time.
+        - `nonce`, if present, is equals to the `nonce` from the
+          authorization request.
+        - `at_hash`, hash of `access_token`, if relevant.
+        - `c_hash`, hash of `code`, if relevant.
+
+        This method MUST provide required fields as below:
+
+        - `iss`, REQUIRED. Issuer Identifier for the Issuer of the response.
+        - `sub`, REQUIRED. Subject Identifier
+        - `exp`, REQUIRED. Expiration time on or after which the ID
+          Token MUST NOT be accepted by the RP when performing
+          authentication with the OP.
+
+        Additional claims must be added, note that `request.scope`
+        should be used to determine the list of claims.
+
+        More information can be found at `OpenID Connect Core#Claims`_
+
+        .. _`OpenID Connect Core#Claims`: https://openid.net/specs/openid-connect-core-1_0.html#Claims
+
+        :param id_token: A dict containing technical fields of id_token
+        :param token: A Bearer token dict
+        :param token_handler: the token handler (BearerToken class)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :return: The ID Token (a JWS signed JWT or JWE encrypted JWT)
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_jwt_bearer_token(self, token, scopes, request):
+        """Ensure the JWT Bearer token or OpenID Connect ID token are valids and authorized access to scopes.
+
+        If using OpenID Connect this SHOULD call `oauthlib.oauth2.RequestValidator.get_id_token`
+
+        If not using OpenID Connect this can `return None` to avoid 5xx rather 401/3 response.
+
+        OpenID connect core 1.0 describe how to validate an id_token:
+            - http://openid.net/specs/openid-connect-core-1_0.html#IDTokenValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#ImplicitIDTValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#HybridIDTValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#HybridIDTValidation2
+
+        :param token: Unicode Bearer token
+        :param scopes: List of scopes (defined by you)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is indirectly used by all core OpenID connect JWT token issuing grant types:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Hybrid Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_id_token(self, token, scopes, request):
+        """Ensure the id token is valid and authorized access to scopes.
+
+        OpenID connect core 1.0 describe how to validate an id_token:
+            - http://openid.net/specs/openid-connect-core-1_0.html#IDTokenValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#ImplicitIDTValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#HybridIDTValidation
+            - http://openid.net/specs/openid-connect-core-1_0.html#HybridIDTValidation2
+
+        :param token: Unicode Bearer token
+        :param scopes: List of scopes (defined by you)
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is indirectly used by all core OpenID connect JWT token issuing grant types:
+            - Authorization Code Grant
+            - Implicit Grant
+            - Hybrid Grant
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_silent_authorization(self, request):
+        """Ensure the logged in user has authorized silent OpenID authorization.
+
+        Silent OpenID authorization allows access tokens and id tokens to be
+        granted to clients without any user prompt or interaction.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - OpenIDConnectAuthCode
+            - OpenIDConnectImplicit
+            - OpenIDConnectHybrid
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_silent_login(self, request):
+        """Ensure session user has authorized silent OpenID login.
+
+        If no user is logged in or has not authorized silent login, this
+        method should return False.
+
+        If the user is logged in but associated with multiple accounts and
+        not selected which one to link to the token then this method should
+        raise an oauthlib.oauth2.AccountSelectionRequired error.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - OpenIDConnectAuthCode
+            - OpenIDConnectImplicit
+            - OpenIDConnectHybrid
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def validate_user_match(self, id_token_hint, scopes, claims, request):
+        """Ensure client supplied user id hint matches session user.
+
+        If the sub claim or id_token_hint is supplied then the session
+        user must match the given ID.
+
+        :param id_token_hint: User identifier string.
+        :param scopes: List of OAuth 2 scopes and OpenID claims (strings).
+        :param claims: OpenID Connect claims dict.
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            - OpenIDConnectAuthCode
+            - OpenIDConnectImplicit
+            - OpenIDConnectHybrid
+        """
+        raise NotImplementedError('Subclasses must implement this method.')
+
+    def get_userinfo_claims(self, request):
+        """Return the UserInfo claims in JSON or Signed or Encrypted.
+
+        The UserInfo Claims MUST be returned as the members of a JSON object
+         unless a signed or encrypted response was requested during Client
+         Registration. The Claims defined in Section 5.1 can be returned, as can
+         additional Claims not specified there.
+
+        For privacy reasons, OpenID Providers MAY elect to not return values for
+        some requested Claims.
+
+        If a Claim is not returned, that Claim Name SHOULD be omitted from the
+        JSON object representing the Claims; it SHOULD NOT be present with a
+        null or empty string value.
+
+        The sub (subject) Claim MUST always be returned in the UserInfo
+        Response.
+
+        Upon receipt of the UserInfo Request, the UserInfo Endpoint MUST return
+        the JSON Serialization of the UserInfo Response as in Section 13.3 in
+        the HTTP response body unless a different format was specified during
+        Registration [OpenID.Registration].
+
+        If the UserInfo Response is signed and/or encrypted, then the Claims are
+        returned in a JWT and the content-type MUST be application/jwt. The
+        response MAY be encrypted without also being signed. If both signing and
+        encryption are requested, the response MUST be signed then encrypted,
+        with the result being a Nested JWT, as defined in [JWT].
+
+        If signed, the UserInfo Response SHOULD contain the Claims iss (issuer)
+        and aud (audience) as members. The iss value SHOULD be the OP's Issuer
+        Identifier URL. The aud value SHOULD be or include the RP's Client ID
+        value.
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: Claims as a dict OR JWT/JWS/JWE as a string
+
+        Method is used by:
+            UserInfoEndpoint
+        """
+
+    def refresh_id_token(self, request):
+        """Whether the id token should be refreshed. Default, True
+
+        :param request: OAuthlib request.
+        :type request: oauthlib.common.Request
+        :rtype: True or False
+
+        Method is used by:
+            RefreshTokenGrant
+        """
+        return True
diff --git a/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/tokens.py b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/tokens.py
new file mode 100644
index 0000000000000000000000000000000000000000..3ab35492434d31f1f45741233b9ceb31eb54b96a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/oauthlib/openid/connect/core/tokens.py
@@ -0,0 +1,45 @@
+"""
+authlib.openid.connect.core.tokens
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This module contains methods for adding JWT tokens to requests.
+"""
+from oauthlib.oauth2.rfc6749.tokens import (
+    TokenBase, get_token_from_header, random_token_generator,
+)
+
+
+class JWTToken(TokenBase):
+    __slots__ = (
+        'request_validator', 'token_generator',
+        'refresh_token_generator', 'expires_in'
+    )
+
+    def __init__(self, request_validator=None, token_generator=None,
+                 expires_in=None, refresh_token_generator=None):
+        self.request_validator = request_validator
+        self.token_generator = token_generator or random_token_generator
+        self.refresh_token_generator = (
+            refresh_token_generator or self.token_generator
+        )
+        self.expires_in = expires_in or 3600
+
+    def create_token(self, request, refresh_token=False):
+        """Create a JWT Token, using requestvalidator method."""
+
+        expires_in = self.expires_in(request) if callable(self.expires_in) else self.expires_in
+
+        request.expires_in = expires_in
+
+        return self.request_validator.get_jwt_bearer_token(None, None, request)
+
+    def validate_request(self, request):
+        token = get_token_from_header(request)
+        return self.request_validator.validate_jwt_bearer_token(
+            token, request.scopes, request)
+
+    def estimate_type(self, request):
+        token = get_token_from_header(request)
+        if token and token.startswith('ey') and token.count('.') in (2, 4):
+            return 10
+        return 0
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/KeyValue.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/KeyValue.py
new file mode 100644
index 0000000000000000000000000000000000000000..b97c226892b1109e1817080bdf13684f7929b098
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/KeyValue.py
@@ -0,0 +1,78 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: CalTableFlatBuffers
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+
+np = import_numpy()
+
+
+class KeyValue:
+    __slots__ = ["_tab"]
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):  # noqa: N802
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = KeyValue()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsKeyValue(cls, buf, offset=0):  # noqa: N802
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+
+    # KeyValue
+    def Init(self, buf, pos):  # noqa: N802
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # KeyValue
+    def Key(self):  # noqa: N802
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # KeyValue
+    def Value(self):  # noqa: N802
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+
+def Start(builder):  # noqa: N802
+    builder.StartObject(2)
+
+
+def KeyValueStart(builder):  # noqa: N802
+    """This method is deprecated. Please switch to Start."""
+    return Start(builder)
+
+
+def AddKey(builder, key):  # noqa: N802
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(key), 0)
+
+
+def KeyValueAddKey(builder, key):  # noqa: N802
+    """This method is deprecated. Please switch to AddKey."""
+    return AddKey(builder, key)
+
+
+def AddValue(builder, value):  # noqa: N802
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(value), 0)
+
+
+def KeyValueAddValue(builder, value):  # noqa: N802
+    """This method is deprecated. Please switch to AddValue."""
+    return AddValue(builder, value)
+
+
+def End(builder):  # noqa: N802
+    return builder.EndObject()
+
+
+def KeyValueEnd(builder):  # noqa: N802
+    """This method is deprecated. Please switch to End."""
+    return End(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b57c84c4485049e9f5c1ef6257b5c55eace6006
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py
@@ -0,0 +1,90 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: CalTableFlatBuffers
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+
+np = import_numpy()
+
+
+class TrtTable:
+    __slots__ = ["_tab"]
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):  # noqa: N802
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = TrtTable()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsTrtTable(cls, buf, offset=0):  # noqa: N802
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+
+    # TrtTable
+    def Init(self, buf, pos):  # noqa: N802
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # TrtTable
+    def Dict(self, j):  # noqa: N802
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from onnxruntime.quantization.CalTableFlatBuffers.KeyValue import KeyValue  # noqa: PLC0415
+
+            obj = KeyValue()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # TrtTable
+    def DictLength(self):  # noqa: N802
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # TrtTable
+    def DictIsNone(self):  # noqa: N802
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+
+def Start(builder):  # noqa: N802
+    builder.StartObject(1)
+
+
+def TrtTableStart(builder):  # noqa: N802
+    """This method is deprecated. Please switch to Start."""
+    return Start(builder)
+
+
+def AddDict(builder, dict):  # noqa: N802
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(dict), 0)
+
+
+def TrtTableAddDict(builder, dict):  # noqa: N802
+    """This method is deprecated. Please switch to AddDict."""
+    return AddDict(builder, dict)
+
+
+def StartDictVector(builder, numElems):  # noqa: N802
+    return builder.StartVector(4, numElems, 4)
+
+
+def TrtTableStartDictVector(builder, numElems):  # noqa: N802
+    """This method is deprecated. Please switch to Start."""
+    return StartDictVector(builder, numElems)
+
+
+def End(builder):  # noqa: N802
+    return builder.EndObject()
+
+
+def TrtTableEnd(builder):  # noqa: N802
+    """This method is deprecated. Please switch to End."""
+    return End(builder)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..c861e1332269018fd9a863ed31aa5cb80573309a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/__init__.py
@@ -0,0 +1,2 @@
+from .preprocess import qnn_preprocess_model  # noqa: F401
+from .quant_config import get_qnn_qdq_config  # noqa: F401
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_lpnorm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_lpnorm.py
new file mode 100644
index 0000000000000000000000000000000000000000..0eb140f892f330c8414664cb2fc7921041fd99cf
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_lpnorm.py
@@ -0,0 +1,132 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import onnx
+
+from ...fusions import Fusion
+from ...onnx_model import ONNXModel
+
+
+class FusionLpNormalization(Fusion):
+    def __init__(self, model: ONNXModel, epsilon: float = 1e-12):
+        super().__init__(model, "LpNormalization", "ReduceL2")
+        self.epsilon = epsilon
+
+    def fuse(
+        self,
+        reduce_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """
+        Interface function that tries to fuse a node sequence containing a ReduceL2 node into a single
+        LpNormalization node.
+
+        Pattern 1:
+                    [root] --> ReduceL2 -----> Clip  --> Expand ----> Div -->
+                       |      (axis=-1)    (min=epsilon) (shape=root)  ^
+                       |   (keepdims=True)                             |
+                       |                                               |
+                       +-----------------------------------------------+
+        Notes:
+          - ReduceL2 must use the last axis, and keepdims == True
+          - Clip must only have a min attribute that is ~1e-12
+          - Expand must restore the shape to root.shape
+          - The output of Expand must be the second input to Div.
+        """
+        if reduce_node.output[0] not in input_name_to_nodes:
+            return
+
+        # ReduceL2 must have one Clip child
+        children = input_name_to_nodes[reduce_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Clip":
+            return
+
+        # ReduceL2 must have keepdims == True
+        keepdims = self.get_node_attribute(reduce_node, "keepdims")
+        if not keepdims:
+            return
+
+        # ReduceL2 axes must refer only to the last dimension.
+        # Axes became an input in opset 18. Before then, axes was an attribute
+        reduce_input_ttype = self.model.get_tensor_type(reduce_node.input[0])
+        if not reduce_input_ttype:
+            return
+
+        reduce_input_shape = self.tensor_shape_to_list(reduce_input_ttype)
+        if not reduce_input_shape:
+            return
+
+        axes = self.get_node_attribute(reduce_node, "axes")
+        if not axes and len(reduce_node.input) > 1:
+            axes = self.model.get_constant_value(reduce_node.input[1])
+
+        if not axes or len(axes) != 1:
+            return
+
+        last_dim = len(reduce_input_shape) - 1
+        if axes[0] != -1 and axes[0] != last_dim:
+            return
+
+        # Clip node must have a min attribute approximately equal to 1e-12
+        clip_node = children[0]
+        clip_min = self.get_node_attribute(clip_node, "min")
+        if clip_min is None and len(clip_node.input) > 1:
+            clip_min = self.model.get_constant_value(clip_node.input[1])
+
+        clip_max = self.get_node_attribute(clip_node, "max")  # TODO: clip_max could be FLOAT_MAX
+        if clip_max is None and len(clip_node.input) > 2:
+            clip_max = self.model.get_constant_value(clip_node.input[2])
+
+        if not (clip_max is None and clip_min is not None and clip_min > 0 and abs(clip_min - self.epsilon) < 1e-13):
+            return
+
+        if clip_node.output[0] not in input_name_to_nodes:
+            return
+
+        # Clip must have a single Expand child.
+        children = input_name_to_nodes[clip_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Expand":
+            return
+
+        expand_node = children[0]
+        if expand_node.output[0] not in input_name_to_nodes:
+            return
+
+        # Expand must have a single Div child
+        children = input_name_to_nodes[expand_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Div":
+            return
+
+        div_node = children[0]
+
+        # The first input to Div must be the root of the subgraph (i.e., reduce_node.input[0])
+        # The second input to Div must be the output of the Expand.
+        # As long as these two inputs go to the same Div node, then ONNX validation will ensure that
+        # their shapes match.
+        if div_node.input[0] != reduce_node.input[0]:
+            return
+        if div_node.input[1] != expand_node.output[0]:
+            return
+
+        subgraph_input = reduce_node.input[0]
+        subgraph_output = div_node.output[0]
+
+        subgraph_nodes = [reduce_node, clip_node, expand_node, div_node]
+        if not self.is_safe_to_fuse_nodes(subgraph_nodes, [subgraph_output], input_name_to_nodes, output_name_to_node):
+            return
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+        fused_node = onnx.helper.make_node(
+            self.fused_op_type,
+            name=self.create_unique_node_name(),
+            inputs=[subgraph_input],
+            outputs=[subgraph_output],
+            p=2,
+            axis=-1,
+        )
+        self.nodes_to_add.append(fused_node)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_spacetodepth.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_spacetodepth.py
new file mode 100644
index 0000000000000000000000000000000000000000..6ea9f6eee5a51f38ca4d1a8ec3e3a8416b6bdfaf
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/fusion_spacetodepth.py
@@ -0,0 +1,162 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+"""Define SpaceToDepth fusion."""
+
+import onnx
+
+from ... import fusions, onnx_model
+
+
+class FusionSpaceToDepth(fusions.Fusion):
+    """Fusion for SpaceToDepth."""
+
+    def __init__(self, model: onnx_model.ONNXModel):
+        """Initialize.
+
+        Args:
+            model: An onnx_model.ONNXModel instance.
+        """
+        super().__init__(model, "SpaceToDepth", "Reshape")
+
+    def _fuse_yolo(
+        self,
+        node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """Fuse for early version of YOLO.
+
+        Pattern:
+
+                |     [N, C, H, W]
+             Reshape
+                |     [N, C, H/blk, blk, W/blk, blk]
+            Transpose
+                |     [N, C, H/blk, W/blk, blk, blk]
+             Reshape
+                |     [N, C, H/blk * W/blk, blk * blk]
+            Transpose
+                |     [N, C, blk * blk, H/blk * W/blk]
+             Reshape
+                |     [N, C, blk * blk, H/blk, W/blk]
+            Transpose
+                |     [N, blk * blk, C, H/blk, W/blk]
+             Reshape
+                |     [N, blk * blk * C, H/blk, W/blk]
+
+        This sequence can be fused into a single SpaceToDepth with blocksize `blk`. Note that unlike DepthToSpace
+        supporting DCR or CRD mode, SpaceToDepth only supports DCR mode in its latest opset version (13), which matches
+        the pattern here.
+        """
+        reshape_node1 = node
+
+        def get_target_child(parent_node, target_op_type):
+            """Get target child of given node."""
+            if parent_node.output[0] not in input_name_to_nodes:
+                return None
+
+            children = input_name_to_nodes[parent_node.output[0]]
+            if len(children) > 1 or children[0].op_type != target_op_type:
+                return None
+
+            return children[0]
+
+        if (
+            (transpose_node1 := get_target_child(reshape_node1, "Transpose")) is None
+            or (reshape_node2 := get_target_child(transpose_node1, "Reshape")) is None
+            or (transpose_node2 := get_target_child(reshape_node2, "Transpose")) is None
+            or (reshape_node3 := get_target_child(transpose_node2, "Reshape")) is None
+            or (transpose_node3 := get_target_child(reshape_node3, "Transpose")) is None
+            or (reshape_node4 := get_target_child(transpose_node3, "Reshape")) is None
+        ):
+            return False
+
+        def get_tensor_shape(tensor_name):
+            """Get shape for given tensor name."""
+            tensor_type = self.model.get_tensor_type(tensor_name)
+            if not tensor_type:
+                return None
+
+            tensor_shape = self.tensor_shape_to_list(tensor_type)
+            if not tensor_shape:
+                return None
+
+            return tensor_shape
+
+        if (
+            (input_shape := get_tensor_shape(reshape_node1.input[0])) is None
+            or (reshape_shape1 := get_tensor_shape(reshape_node1.output[0])) is None
+            or (reshape_shape2 := get_tensor_shape(reshape_node2.output[0])) is None
+            or (reshape_shape3 := get_tensor_shape(reshape_node3.output[0])) is None
+            or (reshape_shape4 := get_tensor_shape(reshape_node4.output[0])) is None
+        ):
+            return False
+
+        transpose_perm1 = self.get_node_attribute(transpose_node1, "perm")
+        transpose_perm2 = self.get_node_attribute(transpose_node2, "perm")
+        transpose_perm3 = self.get_node_attribute(transpose_node3, "perm")
+
+        # Check rank.
+        if (
+            len(input_shape) != 4
+            or len(reshape_shape1) != 6
+            or len(reshape_shape2) != 4
+            or len(reshape_shape3) != 5
+            or len(reshape_shape4) != 4
+        ):
+            return False
+
+        # Check shape and perm.
+        batch, channel, height, width = input_shape
+        blocksize = reshape_shape1[3]
+        if (
+            reshape_shape1 != [batch, channel, height // blocksize, blocksize, width // blocksize, blocksize]
+            or transpose_perm1 != [0, 1, 2, 4, 3, 5]
+            or reshape_shape2 != [batch, channel, (height // blocksize) * (width // blocksize), blocksize**2]
+            or transpose_perm2 != [0, 1, 3, 2]
+            or reshape_shape3 != [batch, channel, blocksize**2, height // blocksize, width // blocksize]
+            or transpose_perm3 != [0, 2, 1, 3, 4]
+            or reshape_shape4 != [batch, blocksize**2 * channel, height // blocksize, width // blocksize]
+        ):
+            return False
+
+        self.nodes_to_remove.extend(
+            [
+                reshape_node1,
+                transpose_node1,
+                reshape_node2,
+                transpose_node2,
+                reshape_node3,
+                transpose_node3,
+                reshape_node4,
+            ]
+        )
+
+        s2d_node = onnx.helper.make_node(
+            self.fused_op_type,
+            name=self.create_unique_node_name(),
+            inputs=[reshape_node1.input[0]],
+            outputs=[reshape_node4.output[0]],
+            blocksize=blocksize,
+        )
+        self.nodes_to_add.append(s2d_node)
+
+        return True
+
+    def fuse(
+        self,
+        node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """Fuse a sequence of Reshape and Transpose nodes into a single SpaceToDepth node.
+
+        Args:
+            node: An onnx.NodeProto matching the specified search type (i.e., Reshape).
+            input_name_to_nodes: A dict mapping tensor name to consumed nodes.
+            output_name_to_node: A dict mapping tensor name to produced node.
+        """
+        self._fuse_yolo(node, input_name_to_nodes, output_name_to_node)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/mixed_precision_overrides_utils.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/mixed_precision_overrides_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..5757a302cbce5a4a8bd260af0017fb152e95f994
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/mixed_precision_overrides_utils.py
@@ -0,0 +1,413 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+
+import onnx
+
+from ...quant_utils import QuantType
+from ...tensor_quant_overrides import QuantTypeInfo, TensorQuantOverridesHelper
+
+
+@dataclass
+class TensorTypeRequest:
+    """
+    Bundles desired quantization type requests for a tensor. A distinction is made between the
+    produced type and the consumed type.
+    """
+
+    # The tensor's quant type at the producer end. If None, assumed to be the default activation quant type.
+    producer: QuantTypeInfo | None
+
+    # The tensor's quant type received by a set of consumer nodes.
+    # If None, assumed to be the default activation quant type for all consumers.
+    # consumers[1] is a set of consumer node names.
+    consumers: tuple[QuantTypeInfo, set[str]] | None
+
+
+class MixedPrecisionTensorQuantOverridesFixer:
+    """
+    Helper that generates tensor quantization overrides for mixed-precision QDQ models.
+
+    Specifically, this helper fixes an initial set of quantization overrides that assign a non-default
+    activation quantization type to one or more tensors by doing the following:
+     - Inferring which other tensors need to be overridden to the non-default activation quantization type.
+     - Inserting quantization data type conversions.
+
+    Example:
+    --------
+
+    Float model:
+
+    input_0 --> Op1 --> Op3 --> Op5 --> Op6 --> output_0
+                                 ^
+                                 |
+    input_1 --> Op2 -+-> Op4 ----+
+                     |
+                     +-> Op7 --> output_1
+                     |
+                     +-> Op8 --> output_2
+
+    If we'd like to quantize this model to uint8 precision, but would like to make sure tensor "Op4_out"
+    is quantized to 16-bit, then we would specify the following initial tensor quantization overrides:
+
+    ```
+    init_overrides = {"Op4_out": [{"quant_type": QuantType.QUInt16}]}
+    ```
+
+    These initial overrides may not create a valid model because Op4 and Op5 may require both the input and output
+    to be the same type (e.g., uint16). This helper fixes the overrides so that input/output data types
+    are valid:
+
+    ```
+    overrides = TensorQuantOverridesHelper(init_overrides)
+
+    fixer = MixedPrecisionTensorQuantOverridesFixer.create_from_model(overrides, model, QuantType.QUInt8)
+    fixer.apply(
+        default_activation_qtype=QuantType.QUInt8,
+        default_activation_symmetric=False,
+    )
+    ```
+
+    The above snippet generates the following "fixed" overrides (get via overrides.get_dict()):
+
+    {
+      "Op2_out": [{"quant_type": QUInt8, "convert": {"quant_type": QUInt16, "recv_nodes": {"Op4"}}}],
+      "Op3_out": [{"quant_type": QUInt8, "convert": {"quant_type": QUInt16, "recv_nodes": {"Op5"}}}],
+      "Op4_out": [{"quant_type": QUInt16}],
+      "Op5_out": [{"quant_type": QUInt16, "convert": {"quant_type": QUInt8, "recv_nodes": {"Op6"}}}]
+    }
+
+    How to interpret the fixed overrides:
+    - Op2's output is consumed by Op4, Op7, and Op8. Op4 consumes the converted u16 type,
+      but Op7 and Op8 consume the original u8 type.
+    - Op3's output is converted from u8 to u16. Op5 consumes the converted u16 type.
+    - Op4's output is just u16 (not converted). All consumers of Op4_out get the u16 type.
+    - Op5's output is converted from u16 to u8. Op6 consumes the u8 type.
+    """
+
+    def __init__(
+        self,
+        overrides: TensorQuantOverridesHelper,
+        producers: dict[str, onnx.NodeProto],
+        consumers: dict[str, list[onnx.NodeProto]],
+        value_infos: dict[str, onnx.ValueInfoProto],
+        initializers: dict[str, onnx.TensorProto],
+    ):
+        """
+        Params:
+            overrides: The initial tensor quantization overrides to fix.
+            producers: Dictionary that maps a tensor name to the producer node that generates the tensor.
+            consumers: Dictionary that maps a tensor name to the consumer nodes that take the tensor as input.
+            value_infos: Dictionary that maps a tensor name to its onnx.ValueInfoProto.
+            initializers: Dictionary that maps an initializer name to its onnx.TensorProto.
+        """
+        self.overrides = overrides
+        self.consumers = consumers
+        self.producers = producers
+        self.value_infos = value_infos
+        self.initializers = initializers
+
+    @staticmethod
+    def create_from_model(
+        overrides: TensorQuantOverridesHelper, model: onnx.ModelProto, default_activation_qtype: QuantType
+    ) -> MixedPrecisionTensorQuantOverridesFixer:
+        """
+        Helper function that creates an instance of this class from a loaded ONNX model.
+
+        Params:
+            overrides: The initial tensor quantization overrides to fix.
+            model: Loaded ONNX model
+            default_activation_qtype: The intended default activation quantization type.
+                                      Used to validate the initial overrides.
+
+        Returns:
+            Initialized MixedPrecisionTensorQuantOverridesFixer object
+        """
+        model = onnx.shape_inference.infer_shapes(model)  # Need to infer shapes to get value_infos
+
+        # Build dictionaries that enable convenient lookups of initializers and value_infos by name.
+        initializers = {initializer.name: initializer for initializer in model.graph.initializer}
+        value_infos = {vi.name: vi for vi in model.graph.value_info}
+        value_infos.update({ot.name: ot for ot in model.graph.output})
+        value_infos.update({it.name: it for it in model.graph.input})
+
+        # Ensure that the user-provided initial overrides are actually valid.
+        valid, err = overrides.is_valid(initializers, set(value_infos), default_activation_qtype)
+        if not valid:
+            pprint_overrides = overrides.pprint_str(indent=4)
+            logging.error(f"Provided invalid tensor quantization overrides:\n{pprint_overrides}")
+            raise ValueError(err)
+
+        consumers = {}
+        producers = {}
+
+        # Build dictionaries that map a tensor name to the consumer or producer nodes.
+        for node in model.graph.node:
+            for input_name in node.input:
+                if input_name:
+                    if input_name not in consumers:
+                        consumers[input_name] = []
+
+                    consumers[input_name].append(node)
+
+            for output_name in node.output:
+                producers[output_name] = node
+
+        return MixedPrecisionTensorQuantOverridesFixer(overrides, producers, consumers, value_infos, initializers)
+
+    def apply(
+        self,
+        default_activation_qtype: QuantType,
+        default_activation_symmetric: bool,
+    ):
+        """
+        Fixes the initial tensor quantization overrides (in-place) for use in mixed-precision QDQ models.
+
+        Params:
+            default_activation_qtype: The intended default activation quantization type.
+            default_activation_symmetric: The intended default symmetry used to quantize activations.
+        """
+        type_requests = self.get_desired_tensor_types(default_activation_qtype, default_activation_symmetric)
+
+        # Use type requests to "fix" tensor quantization overrides by adding
+        # quantization type conversions where necessary.
+        for tensor_name, type_req in type_requests.items():
+            all_consumers = {node.name for node in self.consumers.get(tensor_name, [])}
+            has_producer_req = type_req.producer is not None
+            has_consumer_req = bool(type_req.consumers)
+
+            # Only producer type: Add conversion back to default activation type
+            if has_producer_req and not has_consumer_req:
+                self._update_converted_tensor(
+                    tensor_name, type_req.producer, QuantTypeInfo(default_activation_qtype), all_consumers
+                )
+            # Only consumers
+            elif not has_producer_req and has_consumer_req:
+                prod_type_info = self.overrides.get_node_output_qtype_info(tensor_name, default_activation_qtype)
+                consumer_type_info = type_req.consumers[0]
+
+                if prod_type_info != consumer_type_info:
+                    self._update_converted_tensor(
+                        tensor_name, prod_type_info, consumer_type_info, type_req.consumers[1]
+                    )
+                else:
+                    if not self._check_nodes_are_not_convert_consumers(tensor_name, type_req.consumers[1]):
+                        raise ValueError(
+                            f"Tensor override for '{tensor_name}' converts the type for consumers that need the original type."
+                        )
+            # Both producer and consumers
+            elif has_producer_req and has_consumer_req:
+                prod_type_info = type_req.producer
+                consumer_type_info = type_req.consumers[0]
+
+                if prod_type_info != consumer_type_info:
+                    self._update_converted_tensor(
+                        tensor_name, prod_type_info, consumer_type_info, type_req.consumers[1]
+                    )
+                else:
+                    consumers_for_original_type = all_consumers.difference(type_req.consumers[1])
+
+                    if len(consumers_for_original_type) == 0:
+                        # All consumers want the overridden type, so no need for convert nodes!
+                        # Just add the override to the new new if not already present.
+                        if tensor_name not in self.overrides:
+                            self.overrides[tensor_name] = [{}]
+                            prod_type_info.save_to_dict(self.overrides[tensor_name][0])
+
+                        assert "convert" not in self.overrides[tensor_name][0]
+                    else:
+                        # Some consumers don't want the overridden type.
+                        self._update_converted_tensor(
+                            tensor_name,
+                            prod_type_info,
+                            QuantTypeInfo(default_activation_qtype),
+                            consumers_for_original_type,
+                        )
+            else:
+                raise ValueError(f"TypeRequest for tensor {tensor_name} has no producer or consumers.")
+
+        # Done. Check if the overrides are valid.
+        valid, err = self.overrides.is_valid(self.initializers, set(self.value_infos), default_activation_qtype)
+        if not valid:
+            pprint_overrides = self.overrides.pprint_str(indent=4)
+            logging.error(
+                f"Generated invalid tensor quantization overrides for mixed-precision QDQ model:\n{pprint_overrides}"
+            )
+            raise ValueError(err)
+
+    def get_desired_tensor_types(
+        self,
+        default_activation_qtype: QuantType,
+        default_activation_symmetric: bool,
+    ) -> dict[str, TensorTypeRequest]:
+        """
+        Iterates through the initial tensor quantization overrides and builds a set of TensorTypeRequests objects
+        that describe the quantization types required at each tensor. These TensorTypeRequests objects are ultimately
+        used to generated the "fixed" overrides.
+
+        Params:
+            default_activation_qtype: The intended default activation quantization type.
+            default_activation_symmetric: The intended default symmetry used to quantize activations.
+
+        Returns:
+            TensorTypeRequest objects as a dict that maps a tensor name to its requested types.
+        """
+        type_requests = {}
+        default_activation_type_info = QuantTypeInfo(default_activation_qtype, default_activation_symmetric)
+
+        # Scan tensor overrides for type conversion requests.
+        for tensor_name, override_list in self.overrides.items():
+            if not self.__is_tensor_quantizable(tensor_name):
+                continue  # Skip non-quantizable tensors (e.g., not a float)
+
+            if tensor_name in self.initializers:
+                continue  # Skip initializers
+
+            if not override_list or len(override_list) > 1:
+                continue  # Skip per-channel stuff
+
+            override_dict = override_list[0]
+            quant_type_info = QuantTypeInfo.load_from_dict(override_dict, default_activation_type_info.quant_type)
+            producer_node = self.producers.get(tensor_name)  # None if this is a model input
+
+            if quant_type_info != default_activation_type_info and "convert" not in override_dict:
+                if producer_node is not None:
+                    self._add_type_requests_for_node(type_requests, quant_type_info, producer_node)
+
+                # Find all consumer nodes of `tensor_name` and update their inputs/outputs to the new type.
+                for consumer_node in self.consumers.get(tensor_name, []):
+                    self._add_type_requests_for_node(type_requests, quant_type_info, consumer_node)
+
+        return type_requests
+
+    def _add_type_requests_for_node(
+        self,
+        type_requests: dict[str, TensorTypeRequest],
+        quant_type_info: QuantTypeInfo,
+        node: onnx.NodeProto,
+    ):
+        """
+        Adds TensorTypeRequest objects for a given node, assuming that we want all its inputs and outputs
+        to have the same quantization type (as specified by the `quant_type_info` parameter).
+
+        Params:
+            type_requests: Dictionary of type requests to append to for this node.
+            quant_type_info: The quantization type to use for inputs and outputs.
+            node: The node for which the TensorTypeRequest objects are created and added to type_requests.
+        """
+        # Add output side
+        for output_name in node.output:
+            if not self.__is_tensor_quantizable(output_name):
+                continue
+
+            if output_name not in type_requests:
+                type_requests[output_name] = TensorTypeRequest(quant_type_info, None)
+            else:
+                if (
+                    type_requests[output_name].producer is not None
+                    and type_requests[output_name].producer != quant_type_info
+                ):
+                    raise ValueError(f"Tensor {output_name} has multiple types.")
+
+                type_requests[output_name].producer = quant_type_info
+
+        # Add the consumer side
+        for input_name in node.input:
+            if input_name and input_name not in self.initializers and self.__is_tensor_quantizable(input_name):
+                if input_name not in type_requests:
+                    type_requests[input_name] = TensorTypeRequest(None, None)
+
+                if type_requests[input_name].consumers is None:
+                    type_requests[input_name].consumers = (quant_type_info, set())
+
+                if type_requests[input_name].consumers[0] != quant_type_info:
+                    raise ValueError(f"Tensor {input_name} has consumers requesting different types.")
+
+                if not node.name:
+                    raise ValueError(
+                        f"Node of type {node.op_type} with output 0 {node.output[0]} does not have a name!"
+                    )
+
+                type_requests[input_name].consumers[1].add(node.name)
+
+    def _update_converted_tensor(
+        self,
+        tensor_name: str,
+        producer_type_info: QuantTypeInfo,
+        consumer_type_info: QuantTypeInfo,
+        consumer_names: set[str],
+    ):
+        """
+        Updates the tensor quantization overrides for a tensor that is converted from one type to another.
+
+        Params:
+            tensor_name: The name of the tensor for which to update overrides.
+            producer_type_info: Info for the tensor's produced type.
+            consumer_type_info: Info for the tensor's consumed (i.e., converted) type.
+            consumer_names: Nodes names of consumers that consume the converted type.
+        """
+        if tensor_name not in self.overrides or not self.overrides[tensor_name]:
+            self.overrides[tensor_name] = [{}]
+            producer_type_info.save_to_dict(self.overrides[tensor_name][0])
+
+        overrides = self.overrides[tensor_name][0]
+        if producer_type_info != QuantTypeInfo.load_from_dict(overrides):
+            raise ValueError(f"Desired producer quant_type for {tensor_name} doesn't match existing type.")
+
+        if consumer_names:
+            if "convert" not in overrides:
+                overrides["convert"] = {}
+                consumer_type_info.save_to_dict(overrides["convert"])
+
+            convert_dict = overrides["convert"]
+            if consumer_type_info != QuantTypeInfo.load_from_dict(convert_dict):
+                raise ValueError(f"Desired consumer quant_type for {tensor_name} doesn't match existing type.")
+
+            if "recv_nodes" not in convert_dict:
+                convert_dict["recv_nodes"] = set()
+
+            convert_dict["recv_nodes"].update(consumer_names)
+
+    def _check_nodes_are_not_convert_consumers(self, tensor_name: str, node_names: set[str]):
+        """
+        Returns true if the given nodes do not consume/receive a converted quantization type.
+
+        Params:
+            tensor_name: The name of the tensor to check.
+            node_names: Set of node names that should not be consumers of the converted type.
+        """
+        if tensor_name not in self.overrides or not self.overrides[tensor_name]:
+            return True
+
+        overrides = self.overrides[tensor_name][0]
+
+        if "convert" not in overrides:
+            return True
+
+        convert_dict = overrides["convert"]
+
+        if "recv_nodes" not in convert_dict:
+            return False
+
+        return not convert_dict["recv_nodes"].intersection(node_names)
+
+    def __is_tensor_quantizable(self, tensor_name):
+        weight = self.initializers.get(tensor_name)
+        if weight is not None:
+            if weight.data_type in (onnx.TensorProto.FLOAT, onnx.TensorProto.FLOAT16):
+                return True
+        elif tensor_name in self.value_infos:
+            vi = self.value_infos[tensor_name]
+            if vi.type.HasField("tensor_type") and vi.type.tensor_type.elem_type in (
+                onnx.TensorProto.FLOAT,
+                onnx.TensorProto.FLOAT16,
+            ):
+                return True
+
+        return False
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/preprocess.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/preprocess.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff7b8d3d2abc07fb7ecdc9966a5c9a102b550e8e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/preprocess.py
@@ -0,0 +1,353 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import logging
+import tempfile
+from pathlib import Path
+
+import onnx
+
+from ....tools.onnx_model_utils import fix_output_shapes, make_input_shape_fixed, optimize_model
+from ....tools.remove_initializer_from_input import remove_initializer_from_input
+from ...fusions import FusionGelu, FusionLayerNormalization
+from ...onnx_model import ONNXModel
+from .fusion_lpnorm import FusionLpNormalization
+from .fusion_spacetodepth import FusionSpaceToDepth
+
+
+def qnn_preprocess_model(
+    model_input: str | Path | onnx.ModelProto,
+    model_output: str | Path,
+    exclude_initializer_from_input: bool = False,
+    fuse_layernorm: bool = False,
+    save_as_external_data: bool = False,
+    all_tensors_to_one_file: bool = False,
+    external_data_location: str | None = None,
+    external_data_size_threshold: int = 1024,
+    external_data_convert_attribute: bool = False,
+    inputs_to_make_channel_last: list[str] | None = None,
+    outputs_to_make_channel_last: list[str] | None = None,
+    dynamic_input_shapes: list[tuple[str, str]] | None = None,
+) -> bool:
+    """
+    If necessary, this method creates a new "pre-processed" model in preparation for
+    quantization of a model to be used in QNN EP. Returns true if a new model was created.
+
+    This method perfoms the following operations:
+    - Fuse Erf sequence into a single Gelu node.
+    - Fuse ReduceL2 sequence into a single LpNormalization node (p == 2).
+    - (Optional) Fuse ReduceMean sequence into a single LayerNormalization node.
+
+    Args:
+        model_input: Path to the input model file or ModelProto.
+        model_output: Path the output model file, which is only created if this method returns True.
+        exclude_initializer_from_input: A bool specifying whether to exclude initializer from input.
+            Defaults to False.
+        fuse_layernorm: True if ReduceMean sequences should be fused into LayerNormalization nodes.
+            Defaults to False.
+        save_as_external_data: True if output model should be saved with external data. Defaults to false.
+        all_tensors_to_one_file: Effective only if save_as_external_data is true. Defaults to false.
+            If true, save all tensors to one external file specified by external_data_location.
+            If false, save each tensor to a file named with the tensor name.
+        external_data_location: Effective only if save_as_external_data is true. Defaults to None.
+            Specify the external file to which all tensors are saved. Path is relative
+            to the model path. If not specified, the model's name is used.
+        external_data_size_threshold: Effective only if save_as_external_data is true. Defaults to 1024.
+            Tensors with a data size >= external_data_size_threshold are converted to external data.
+            To convert every tensor with raw data to external data, set to 0.
+        external_data_convert_attribute: Effective only if save_as_external_data is true. Defaults to false.
+            If true, convert all tensors to external data.
+            If false, convert only non-attribute tensors to external data.
+        inputs_to_make_channel_last: List of graph input names to transpose to be "channel-last". For example,
+            if "input0" originally has the shape (N, C, D1, D2, ..., Dn), the resulting model will change input0's
+            shape to (N, D1, D2, ..., Dn, C) and add a transpose node after it.
+
+            Original:
+                input0 (N, C, D1, D2, ..., Dn) --> <Nodes>
+
+            Updated:
+                input0 (N, D1, D2, ..., Dn, C) --> Transpose --> input0_chanfirst (N, C, D1, D2, ..., Dn) --> <Nodes>
+
+            This can potentially improve inference latency for QDQ models running on QNN EP because the
+            additional transpose node may allow other transpose nodes inserted during ORT layout transformation
+            to cancel out.
+        outputs_to_make_channel_last: List of graph output names to transpose to be "channel-last". For example,
+            if "output0" originally has the shape (N, C, D1, D2, ..., Dn), the resulting model will change output0's
+            shape to (N, D1, D2, ..., Dn, C) and add a transpose node before it.
+
+            Original:
+                <Nodes> --> output0 (N, C, D1, D2, ..., Dn)
+
+            Updated:
+                <Nodes> --> output0_chanfirst (N, C, D1, D2, ..., Dn) --> Transpose --> output0 (N, D1, D2, ..., Dn, C)
+
+            This can potentially improve inference latency for QDQ models running on QNN EP because the
+            additional transpose node may allow other transpose nodes inserted during ORT layout transformation
+            to cancel out.
+        dynamic_input_shapes: A list of tuples specifying model input name to and its static shape in comma seprated
+            format, for example: [('input', '1,3,256,256')]. Defaults to None.
+    """
+    modified = False
+    model = model_input if isinstance(model_input, onnx.ModelProto) else onnx.load_model(model_input)
+    model = save_and_reload_optimize_model(model, shape_infer=True)
+    onnx_model = ONNXModel(model)
+
+    # Optionally, fix the dynamic input shapes.
+    if dynamic_input_shapes:
+        for input_name, input_shape_str in dynamic_input_shapes:
+            input_shape = [int(i) for i in input_shape_str.split(",")]
+            make_input_shape_fixed(onnx_model.graph(), input_name, input_shape)
+        fix_output_shapes(onnx_model.model)
+        modified = True
+
+    # Exclude initializer from input if model.ir_version >= 4
+    if exclude_initializer_from_input:
+        modified |= remove_initializer_from_input(onnx_model.model)
+
+    # Fuse Erf sequence into a single Gelu
+    fusion_gelu = FusionGelu(onnx_model)
+    if fusion_gelu.apply():
+        modified = True
+
+    # Fuse ReduceL2 sequence into a single LpNormalization node with p == 2.
+    fusion_lpnorm = FusionLpNormalization(onnx_model)
+    if fusion_lpnorm.apply():
+        modified = True
+
+    # Fuse Reshape/Transpose sequence into a single SpaceToDepth.
+    fusion_s2d = FusionSpaceToDepth(onnx_model)
+    if fusion_s2d.apply():
+        modified = True
+
+    # Optionally, fuse ReduceMean sequence into a single LayerNormalization node.
+    if fuse_layernorm:
+        onnx_opset = next(x for x in model.opset_import if x.domain == "" or x.domain == "ai.onnx")
+
+        # Need opset >= 17 to use LayerNormalization.
+        if onnx_opset.version < 17:
+            logging.warning(
+                "Unable to fuse ReduceMean sequence into a LayerNormalization node. "
+                "ONNX model must use an opset >= 17 in order to use LayerNormalization, "
+                f"but found version {onnx_opset.version}. Please use onnx.version_converter to update your model."
+            )
+        else:
+            fusion_layernorm = FusionLayerNormalization(onnx_model)
+            if fusion_layernorm.apply():
+                modified = True
+
+    # Optionally, transpose inputs and/or outputs to make them "channel-last".
+    if inputs_to_make_channel_last or outputs_to_make_channel_last:
+        transpose_node_prefix = "Transpose_channel_"
+        transpose_node_suffix: int = onnx_model.get_largest_node_name_suffix(transpose_node_prefix) + 1
+        update_io_to_channel_last(
+            onnx_model.model,
+            inputs_to_make_channel_last,
+            outputs_to_make_channel_last,
+            transpose_node_name_prefix=transpose_node_prefix,
+            transpose_node_name_start_suffix=transpose_node_suffix,
+        )
+        modified = True
+
+    # Make sure all nodes have a name.
+    unnamed_node_prefix = "qnn_preproc_node_"
+    available_suffix = onnx_model.get_largest_node_name_suffix(unnamed_node_prefix) + 1
+    for node in onnx_model.model.graph.node:
+        if node.op_type != "Constant" and not node.name:
+            new_node_name = f"{unnamed_node_prefix}{available_suffix!s}"
+            available_suffix += 1
+            node.name = new_node_name
+            modified = True
+            logging.warning(f"Node of type {node.op_type} does not have a name. Renamed to {new_node_name}.")
+
+    if modified:
+        onnx_model.topological_sort()
+        onnx.save_model(
+            model,
+            model_output,
+            save_as_external_data=save_as_external_data,
+            all_tensors_to_one_file=all_tensors_to_one_file,
+            location=external_data_location,
+            size_threshold=external_data_size_threshold,
+            convert_attribute=external_data_convert_attribute,
+        )
+
+    return modified
+
+
+def save_and_reload_optimize_model(model: onnx.ModelProto, shape_infer: bool) -> onnx.ModelProto:
+    with tempfile.TemporaryDirectory(prefix="ort.qnn_preproc.") as qnn_preproc_tmp_dir:
+        model_in_path = Path(qnn_preproc_tmp_dir).joinpath("qnn_proc_input.onnx")
+        onnx.save_model(model, model_in_path, save_as_external_data=True)
+        if shape_infer:
+            model_infer_path = Path(qnn_preproc_tmp_dir).joinpath("qnn_proc_infer.onnx")
+            onnx.shape_inference.infer_shapes_path(str(model_in_path), str(model_infer_path))
+            model_in_path = model_infer_path
+        model_out_path = Path(qnn_preproc_tmp_dir).joinpath("qnn_proc_output.onnx")
+        optimize_model(model_in_path, model_out_path)
+        ret_model = onnx.load_model(model_out_path)
+        ret_metaprops = {"onnx.infer": "onnxruntime.tools.qnn.preprocess"}
+        if ret_model.metadata_props:
+            ret_metaprops.update(ret_model.metadata_props)
+        onnx.helper.set_model_props(ret_model, ret_metaprops)
+        return ret_model
+
+
+class InputOutputNameMap:
+    def __init__(
+        self,
+        orig_tensor_names: set[str],
+        orig_graph_inputs: dict[str, onnx.ValueInfoProto],
+        orig_graph_outputs: dict[str, onnx.ValueInfoProto],
+    ):
+        self.orig_tensor_names = orig_tensor_names
+        self.orig_graph_inputs = orig_graph_inputs
+        self.orig_graph_outputs = orig_graph_outputs
+        self.updated_io_names = {}
+        self.new_value_infos = []
+
+    def get_new_name(self, orig_name: str):
+        if orig_name in self.updated_io_names:
+            return self.updated_io_names[orig_name]
+
+        # Make a new tensor name that is unique among all tensors in the graph.
+        prefix: str = f"{orig_name}_channel_first_"
+        suffix: int = -1
+        for tensor_name in self.orig_tensor_names:
+            if tensor_name.startswith(prefix) and tensor_name[len(prefix) :].isdigit():
+                index = int(tensor_name[len(prefix) :])
+                suffix = max(suffix, index)
+
+        suffix += 1  # This is the first available suffix.
+        new_name = f"{prefix}{suffix!s}"
+
+        # Add new value_info objects for these new tensors.
+        orig_value_info = self.orig_graph_inputs.get(orig_name) or self.orig_graph_outputs[orig_name]
+        value_info_proto = onnx.ValueInfoProto()
+        value_info_proto.CopyFrom(orig_value_info)
+        value_info_proto.name = new_name
+        self.new_value_infos.append(value_info_proto)
+
+        self.updated_io_names[orig_name] = new_name
+        return self.updated_io_names[orig_name]
+
+
+def update_io_to_channel_last(
+    model: onnx.ModelProto,
+    inputs_to_update: list[str] | None,
+    outputs_to_update: list[str] | None,
+    transpose_node_name_prefix: str = "Transpose_channel_",
+    transpose_node_name_start_suffix: int = 0,
+):
+    inputs_to_update = set(inputs_to_update or [])
+    outputs_to_update = set(outputs_to_update or [])
+
+    if not inputs_to_update and not outputs_to_update:
+        return
+
+    graph = model.graph
+    orig_graph_inputs = {ginput.name: ginput for ginput in graph.input}
+    orig_graph_outputs = {goutput.name: goutput for goutput in graph.output}
+
+    # Check that the user passed in actual input and output names.
+    for input_name in inputs_to_update:
+        if input_name not in orig_graph_inputs:
+            raise ValueError(f"{input_name} is not a graph input")
+
+    for output_name in outputs_to_update:
+        if output_name not in orig_graph_outputs:
+            raise ValueError(f"{output_name} is not a graph output")
+
+    orig_tensor_names = set()
+    orig_tensor_names.update(set(orig_graph_inputs))
+    orig_tensor_names.update(set(orig_graph_outputs))
+    orig_tensor_names.update(input_name for node in graph.node for input_name in node.input if input_name)
+
+    # Maps original input (or output) name to its updated name used within the graph.
+    io_map = InputOutputNameMap(orig_tensor_names, orig_graph_inputs, orig_graph_outputs)
+
+    # Update each node's inputs/outputs to use the transposed versions.
+    for node in graph.node:
+        for i in range(len(node.input)):
+            if node.input[i] and node.input[i] in inputs_to_update:
+                node.input[i] = io_map.get_new_name(node.input[i])
+            elif node.input[i] and node.input[i] in outputs_to_update:
+                node.input[i] = io_map.get_new_name(node.input[i])
+
+        for i in range(len(node.output)):
+            if node.output[i] in outputs_to_update:
+                node.output[i] = io_map.get_new_name(node.output[i])
+
+    # Update graph inputs to channel-last and a Transpose (to channel-first) after each.
+    for g_input_name in inputs_to_update:
+        g_input = orig_graph_inputs[g_input_name]
+
+        if not g_input.type.HasField("tensor_type") or not g_input.type.tensor_type.HasField("shape"):
+            raise ValueError(f"Expected input {g_input.name} to have a tensor_type with a shape")
+
+        input_shape = g_input.type.tensor_type.shape
+        input_rank = len(input_shape.dim)
+
+        if input_rank < 3:
+            raise ValueError(f"Expected input {g_input.name} to be of rank >= 3")
+
+        channel_dim = onnx.TensorShapeProto.Dimension()
+        channel_dim.CopyFrom(input_shape.dim[1])
+        for i in range(1, input_rank - 1):
+            input_shape.dim[i].CopyFrom(input_shape.dim[i + 1])
+        input_shape.dim[input_rank - 1].CopyFrom(channel_dim)
+
+        transpose_perm = list(range(input_rank))
+        for i in range(input_rank):
+            transpose_perm[i] = i if i < 1 else i - 1
+        transpose_perm[1] = input_rank - 1
+
+        transpose_node = onnx.helper.make_node(
+            "Transpose",
+            name=f"{transpose_node_name_prefix}{transpose_node_name_start_suffix!s}",
+            inputs=[g_input.name],
+            outputs=[io_map.get_new_name(g_input.name)],
+            perm=transpose_perm,
+        )
+        transpose_node_name_start_suffix += 1
+
+        graph.node.extend([transpose_node])
+
+    # Update graph outputs to channel-last and a Transpose (from channel-first) before each.
+    for g_output_name in outputs_to_update:
+        g_output = orig_graph_outputs[g_output_name]
+        if not g_output.type.HasField("tensor_type") or not g_output.type.tensor_type.HasField("shape"):
+            raise ValueError(f"Expected output {g_output.name} to have a tensor_type with a shape")
+
+        output_shape = g_output.type.tensor_type.shape
+        output_rank = len(output_shape.dim)
+
+        if output_rank < 3:
+            raise ValueError(f"Expected output {g_output.name} to be of rank >= 3")
+
+        channel_dim = onnx.TensorShapeProto.Dimension()
+        channel_dim.CopyFrom(output_shape.dim[1])
+        for i in range(1, output_rank - 1):
+            output_shape.dim[i].CopyFrom(output_shape.dim[i + 1])
+        output_shape.dim[output_rank - 1].CopyFrom(channel_dim)
+
+        transpose_perm = list(range(output_rank))
+        for i in range(output_rank):
+            transpose_perm[i] = i if i == 0 else i + 1
+        transpose_perm[output_rank - 1] = 1
+
+        transpose_node = onnx.helper.make_node(
+            "Transpose",
+            name=f"{transpose_node_name_prefix}{transpose_node_name_start_suffix!s}",
+            inputs=[io_map.get_new_name(g_output.name)],
+            outputs=[g_output.name],
+            perm=transpose_perm,
+        )
+        transpose_node_name_start_suffix += 1
+
+        graph.node.extend([transpose_node])
+
+    graph.value_info.extend(io_map.new_value_infos)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/quant_config.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/quant_config.py
new file mode 100644
index 0000000000000000000000000000000000000000..0a23a263555920bdac3b10bb016ebc49438715ca
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/execution_providers/qnn/quant_config.py
@@ -0,0 +1,389 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import copy
+import logging
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import onnx
+
+from ...calibrate import CalibrationDataReader, CalibrationMethod
+from ...quant_utils import QuantType
+from ...quantize import StaticQuantConfig
+from ...tensor_quant_overrides import TensorQuantOverridesHelper
+from .mixed_precision_overrides_utils import MixedPrecisionTensorQuantOverridesFixer
+
+Q16_TYPES = {QuantType.QInt16, QuantType.QUInt16}
+Q8_TYPES = {QuantType.QInt8, QuantType.QUInt8}
+Q4_TYPES = {QuantType.QInt4, QuantType.QUInt4}
+OP_TYPES_TO_EXCLUDE = {"Cast"}
+MODEL_SIZE_THRESHOLD = 2147483648  # Quant model should use external data if >= 2GB
+
+
+def warn_unable_to_override(
+    node: onnx.NodeProto,
+    what_str: str,
+    tensor_name: str,
+    io_kind: str,
+):
+    logging.warning(
+        f"Unable to override {what_str} for {node.op_type} node's {io_kind} "
+        "because it has already been overridden! Check the initial quantization overrides provided "
+        "to get_qnn_qdq_config() if the generated QDQ model does not run on QNN EP. "
+        f"Node name: {node.name}, {io_kind} name: {tensor_name}"
+    )
+
+
+def get_qnn_qdq_config(
+    model_input: str | Path | onnx.ModelProto,
+    calibration_data_reader: CalibrationDataReader,
+    calibrate_method: CalibrationMethod = CalibrationMethod.MinMax,
+    activation_type: QuantType = QuantType.QUInt8,
+    weight_type: QuantType = QuantType.QUInt8,
+    per_channel: bool = False,
+    init_overrides: dict[str, list[dict[str, Any]]] | None = None,
+    add_qtype_converts: bool = True,
+    activation_symmetric: bool = False,
+    weight_symmetric: bool | None = None,
+    keep_removable_activations: bool = False,
+    stride: int | None = None,
+    calibration_providers: list[str] | None = None,
+    op_types_to_quantize: list[str] | None = None,
+    nodes_to_exclude: list[str] | None = None,
+) -> StaticQuantConfig:
+    """
+    Returns a static quantization configuration suitable for running QDQ models on QNN EP.
+    This is done primarily by setting tensor-level quantization overrides.
+
+    Params:
+        model_input: Path to the input model file or ModelProto.
+        calibration_data_reader: Calibration data reader.
+        calibrate_methode: The calibration method. Defaults to MinMax.
+        activation_type: The default activation quantization type. Defaults to QUInt8.
+        weight_type: The default weight quantization type. Defaults to QUInt8.
+        per_channel: Global option that determines if a fixed set of operator types should be quantized per-channel.
+            Defaults to false. Alternatively, use the tensor-level `init_overrides` to select individual operators
+            and their quantization axes.
+
+            If set, the quantization tool uses per-channel quantization for the following operator types and inputs:
+                - Conv:
+                    - input[1] on axis 0
+                    - input[2] (bias) on axis 0
+                - ConvTranspose:
+                    - input[1] on axis 1
+                    - input[2] (bias) on axis 0
+        init_overrides: Initial tensor-level quantization overrides. Defaults to None. This function updates of a copy
+            of these overrides with any necessary adjustments and includes them in the returned
+            configuration object (i.e., config.extra_options['TensorQuantOverrides']).
+
+            The key is a tensor name and the value is a list of dictionaries. For per-tensor quantization, the list
+            contains a single dictionary. For per-channel quantization, the list contains either a dictionary for
+            each channel in the tensor or a single dictionary that is assumed to apply to all channels. An 'axis'
+            key must be present in the first dictionary for per-channel quantization.
+
+            Each dictionary contains optional overrides with the following keys and values.
+                'quant_type' = QuantType : The tensor's quantization data type.
+                'axis' = Int             : The per-channel axis. Must be present for per-channel weights.
+                'scale' =  Float         : The scale value to use. Must also specify `zero_point` if set.
+                'zero_point' = Int       : The zero-point value to use. Must also specify `scale` is set.
+                'symmetric' = Bool       : If the tensor should use symmetric quantization. Invalid if also
+                                            set `scale` or `zero_point`.
+                'reduce_range' = Bool    : If the quantization range should be reduced. Invalid if also
+                                            set `scale` or `zero_point`. Only valid for initializers.
+                'rmax' = Float           : Override the maximum real tensor value in calibration data.
+                                            Invalid if also set `scale` or `zero_point`.
+                'rmin' = Float           : Override the minimum real tensor value in calibration data.
+                                            Invalid if also set `scale` or `zero_point`.
+                'convert' = Dict         : A nested dictionary with the same keys for an activation
+                                           tensor that should be converted to another quantization type.
+                'convert["recv_nodes"] = Set : Set of node names that consume the converted activation,
+                                               other nodes get the original type. If not specified,
+                                               assume all consumer nodes get the converted type.
+        add_qtype_converts: True if this function should automatically add "convert" entries to the provided
+            `init_overrides` to ensure that operators use valid input/output types (activations only).
+            Ex: if you override the output of an Add to 16-bit, this option ensures that the activation inputs
+            of the Add are also up-converted to 16-bit and that data types for surrounding ops are converted
+            appropriately. Refer to the documentation in mixed_precision_overrides_utils.py for additional details.
+        activation_symmetric: True if activations should be quantized symmetrically (i.e, rmax == -rmin) by default.
+            Defaults to false. For int8 and int16, this results in zero-point values of 0. For uint8 and uin16,
+            the zero-point values are 128 and 32,768, respectively.
+        weight_symmetric: True if weights should be quantized symmetrically (i.e., rmax == -rmin) by default.
+            Defaults to None. If set to None, weight_symmetric is assumed true if the weight_type is a signed int.
+        keep_removable_activations: Defaults to false. If true, "removable" activations (e.g., Clip or Relu) will not
+                        be removed, and will be explicitly represented in the QDQ model. If false, these activations
+                        are automatically removed if activations are asymmetrically quantized. Keeping these activations
+                        is necessary if optimizations or EP transformations will later remove
+                        QuantizeLinear/DequantizeLinear operators from the model.
+        calibration_providers: Execution providers to run the session during calibration. Default is None which uses
+            [ "CPUExecutionProvider" ].
+        op_types_to_quantize: If set to None, all operator types will be quantized except for OP_TYPES_TO_EXCLUDE
+        nodes_to_exclude: List of nodes names to exclude from quantization. The nodes in this list will be excluded from
+            quantization when it is not None.
+
+    Returns:
+        A StaticQuantConfig object
+    """
+    if weight_symmetric is None:
+        weight_symmetric = weight_type in {QuantType.QInt8, QuantType.QInt16}
+
+    model = (
+        model_input
+        if isinstance(model_input, onnx.ModelProto)
+        else onnx.load_model(model_input, load_external_data=False)
+    )
+
+    op_types = set()
+    model_has_external_data = False
+    name_to_initializer = {}
+
+    # Build map of initializers (name -> initializer) and
+    # check if the model has external data.
+    for initializer in model.graph.initializer:
+        name_to_initializer[initializer.name] = initializer
+        if onnx.external_data_helper.uses_external_data(initializer):
+            model_has_external_data = True
+
+    overrides_helper = TensorQuantOverridesHelper(copy.deepcopy(init_overrides) if init_overrides else {})
+
+    if not overrides_helper.empty() and add_qtype_converts:
+        # Fix mixed-precision overrides.
+        overrides_fixer = MixedPrecisionTensorQuantOverridesFixer.create_from_model(
+            overrides_helper, model, activation_type
+        )
+        overrides_fixer.apply(activation_type, activation_symmetric)
+
+    # Setup quantization overrides for specific operator types to ensure compatibility with QNN EP.
+    qnn_compat = QnnCompatibilityOverrides(
+        activation_type,
+        weight_type,
+        activation_symmetric,
+        weight_symmetric,
+        per_channel,
+        overrides_helper,
+        name_to_initializer,
+    )
+
+    op_types_to_quantize_set = set(op_types_to_quantize) if op_types_to_quantize else None
+    nodes_to_exclude_set = set(nodes_to_exclude) if nodes_to_exclude else None
+
+    for node in model.graph.node:
+        if op_types_to_quantize_set and node.op_type not in op_types_to_quantize_set:
+            continue
+        if nodes_to_exclude_set and node.name in nodes_to_exclude_set:
+            continue
+        op_types.add(node.op_type)
+        qnn_compat.process_node(node)
+
+    extra_options = {
+        "MinimumRealRange": 0.0001,
+        "DedicatedQDQPair": False,  # Let ORT optimizer duplicate DQ nodes
+        "QDQKeepRemovableActivations": keep_removable_activations,
+        "TensorQuantOverrides": overrides_helper.get_dict(),
+        "ActivationSymmetric": activation_symmetric,
+        "WeightSymmetric": weight_symmetric,
+        "CalibStridedMinMax": stride,
+    }
+
+    # ONNX opset < 21 does not support 16-bit quantization, so must use 'com.microsoft' domain
+    # on Q/DQ operators if using 16-bit or 4-bit quantization.
+    onnx_opset = next(x for x in model.opset_import if x.domain == "" or x.domain == "ai.onnx")
+    if onnx_opset.version < 21:
+        opset21_types = Q16_TYPES.union(Q4_TYPES)
+        overrides_have_opset21_types = any(t in opset21_types for t in overrides_helper.get_quant_types())
+        if activation_type in opset21_types or weight_type in opset21_types or overrides_have_opset21_types:
+            extra_options["UseQDQContribOps"] = True
+
+    return StaticQuantConfig(
+        calibration_data_reader,
+        calibrate_method=calibrate_method,
+        activation_type=activation_type,
+        weight_type=weight_type,
+        op_types_to_quantize=(
+            op_types_to_quantize if op_types_to_quantize else list(op_types.difference(OP_TYPES_TO_EXCLUDE))
+        ),
+        nodes_to_exclude=nodes_to_exclude,
+        per_channel=per_channel,
+        use_external_data_format=(model_has_external_data or model.ByteSize() >= MODEL_SIZE_THRESHOLD),
+        calibration_providers=calibration_providers,
+        extra_options=extra_options,
+    )
+
+
+class QnnCompatibilityOverrides:
+    """
+    Helper that processes nodes to generate quantization overrides that make the resulting QDQ model
+    compatible with QNN EP.
+    """
+
+    def __init__(
+        self,
+        default_activation_qtype: QuantType,
+        default_weight_qtype: QuantType,
+        activation_symmetric: bool,
+        weight_symmetric: bool,
+        per_channel: bool,
+        overrides: TensorQuantOverridesHelper,
+        initializers: dict[str, onnx.TensorProto],
+    ):
+        self.default_activation_qtype = default_activation_qtype
+        self.default_weight_qtype = default_weight_qtype
+        self.activation_symmetric = activation_symmetric
+        self.weight_symmetric = weight_symmetric
+        self.per_channel = per_channel
+        self.overrides = overrides
+        self.initializers = initializers
+
+        self.process_fns = {
+            "MatMul": self._process_matmul,
+            "LayerNormalization": self._process_layernorm,
+            "Sigmoid": self._process_sigmoid,
+            "Tanh": self._process_tanh,
+        }
+
+    def process_node(self, node: onnx.NodeProto):
+        process_fn = self.process_fns.get(node.op_type)
+
+        if process_fn is not None:
+            process_fn(node)
+
+    def _make_static_inputs_use_default_weight_type(self, node: onnx.NodeProto):
+        """
+        Overrides initializer input(s) to use the default weight type if:
+        - The default weight type is 8-bit
+        - One of the inputs is a 16-bit activation
+        - The other input is an initializer (per-tensor quantized)
+
+        This is necessary because the quantization tool does not assign MatMul or LayerNorm initializer
+        inputs the default weight type. Instead, it assigns the default activation type.
+        """
+        if self.default_weight_qtype not in Q8_TYPES:
+            return
+
+        input_16bit_act_name = None
+        input_weight_name = None
+
+        # Loop through first 2 inputs to find a 16-bit activation and a (per-tensor) weight.
+        for i in range(2):
+            input_name = node.input[i]
+            if not input_name:
+                continue
+
+            is_weight = input_name in self.initializers
+            qtype_info = self.overrides.get_node_input_qtype_info(
+                input_name,
+                node.name,
+                default_qtype=None if is_weight else self.default_activation_qtype,
+            )
+
+            if qtype_info.axis is not None:
+                return  # Don't process MatMul with a per-channel quantized input.
+
+            if (
+                is_weight
+                and qtype_info.quant_type == self.default_weight_qtype
+                and qtype_info.symmetric == self.weight_symmetric
+            ):
+                return  # Return. Weight is already overridden to use the desired weight type.
+
+            if is_weight:
+                input_weight_name = input_name
+            elif qtype_info.quant_type in Q16_TYPES:
+                input_16bit_act_name = input_name
+
+        # Override initializer input to use the default weight type.
+        if input_16bit_act_name and input_weight_name:
+            did_update = self.overrides.update_tensor_overrides(
+                input_weight_name,
+                {"quant_type": self.default_weight_qtype, "symmetric": self.weight_symmetric},
+                overwrite=False,
+            )
+
+            if not did_update:
+                warn_unable_to_override(node, "quant_type/symmetric", input_weight_name, "input weight")
+
+    def _process_matmul(self, node: onnx.NodeProto):
+        assert node.op_type == "MatMul", f"Expected MatMul, but got {node.op_type}"
+
+        if not self.per_channel:
+            self._make_static_inputs_use_default_weight_type(node)
+            return
+
+        # QNN does not support per-channel MatMul. However, the ORT quantization tool attempts to use per-channel
+        # quantization for MatMul by default *if* the global per_channel setting is enabled. So, we need to
+        # provide explicit per-tensor quantization overrides for MatMul if per_channel is enabled and
+        # the user did not provide any other overrides.
+        for input_name in node.input:
+            is_weight_no_overrides = input_name in self.initializers and input_name not in self.overrides
+            if is_weight_no_overrides:
+                self.overrides.update_tensor_overrides(
+                    input_name,
+                    {"quant_type": self.default_weight_qtype, "symmetric": self.weight_symmetric},
+                )
+
+    def _process_layernorm(self, node: onnx.NodeProto):
+        assert node.op_type == "LayerNormalization", f"Expected LayerNormalization, but got {node.op_type}"
+
+        if not self.per_channel:
+            self._make_static_inputs_use_default_weight_type(node)
+
+    def _process_sigmoid(self, node: onnx.NodeProto):
+        """
+        Overrides 16-bit Sigmoid's output scale and zero-point as per QNN requirements.
+        """
+        assert node.op_type == "Sigmoid", f"Expected Sigmoid, but got {node.op_type}"
+        output_type = self.overrides.get_node_output_qtype_info(
+            node.output[0], self.default_activation_qtype
+        ).quant_type
+
+        if output_type == QuantType.QUInt16:
+            self.overrides.update_tensor_overrides(
+                node.output[0],
+                {
+                    "quant_type": output_type,
+                    "scale": np.array(1.0 / 65536.0, dtype=np.float32),
+                    "zero_point": np.array(0, dtype=np.uint16),
+                },
+            )
+        elif output_type == QuantType.QInt16:
+            self.overrides.update_tensor_overrides(
+                node.output[0],
+                {
+                    "quant_type": output_type,
+                    "scale": np.array(1.0 / 32768.0, dtype=np.float32),
+                    "zero_point": np.array(0, dtype=np.int16),
+                },
+            )
+
+    def _process_tanh(self, node: onnx.NodeProto):
+        """
+        Overrides 16-bit Tanh's output scale and zero-point as per QNN requirements.
+        """
+        assert node.op_type == "Tanh", f"Expected Tanh, but got {node.op_type}"
+        output_type = self.overrides.get_node_output_qtype_info(
+            node.output[0], self.default_activation_qtype
+        ).quant_type
+
+        if output_type == QuantType.QUInt16:
+            self.overrides.update_tensor_overrides(
+                node.output[0],
+                {
+                    "quant_type": output_type,
+                    "scale": np.array(1.0 / 32768.0, dtype=np.float32),
+                    "zero_point": np.array(32768, dtype=np.uint16),
+                },
+            )
+        elif output_type == QuantType.QInt16:
+            self.overrides.update_tensor_overrides(
+                node.output[0],
+                {
+                    "quant_type": output_type,
+                    "scale": np.array(1.0 / 32768.0, dtype=np.float32),
+                    "zero_point": np.array(0, dtype=np.int16),
+                },
+            )
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b5299c8377a5496e45271a081740740d170122e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/__init__.py
@@ -0,0 +1,4 @@
+from .fusion import Fusion  # noqa: F401
+from .fusion_gelu import FusionGelu  # noqa: F401
+from .fusion_layernorm import FusionLayerNormalization  # noqa: F401
+from .replace_upsample_with_resize import ReplaceUpsampleWithResize  # noqa: F401
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion.py
new file mode 100644
index 0000000000000000000000000000000000000000..6c7e04fc7f46593bbc4f4d271062878f3d250f1f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion.py
@@ -0,0 +1,311 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+from collections import deque
+
+import onnx
+
+from ..onnx_model import ONNXModel
+
+
+class Fusion:
+    """
+    Base class for fusions.
+    """
+
+    def __init__(self, model: ONNXModel, fused_op_type: str, search_op_type: str):
+        self.search_op_type: str = search_op_type
+        self.fused_op_type: str = fused_op_type
+        self.model: ONNXModel = model
+        self.nodes_to_remove: list = []
+        self.nodes_to_add: list = []
+
+        self._new_node_name_prefix = self.fused_op_type + "_fused_" + self.search_op_type + "_"
+        self._new_node_name_suffix = None  # int|None used to create unique node names for the fused ops.
+
+    def fuse(
+        self,
+        node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """
+        Interface function for derived fusion classes. Tries to fuse a node sequence containing
+        the specified node.
+        """
+        raise NotImplementedError
+
+    def apply(self) -> bool:
+        """
+        Apply graph fusion on the entire model graph.
+        """
+        input_name_to_nodes = self.model.input_name_to_nodes()
+        output_name_to_node = self.model.output_name_to_node()
+
+        for node in self.model.nodes():
+            if node.op_type == self.search_op_type:
+                self.fuse(node, input_name_to_nodes, output_name_to_node)
+
+        self.model.remove_nodes(self.nodes_to_remove)
+        self.model.add_nodes(self.nodes_to_add)
+
+        graph_updated = bool(self.nodes_to_remove or self.nodes_to_add)
+
+        if graph_updated:
+            self.model.remove_unused_constant()
+
+        return graph_updated
+
+    def create_unique_node_name(self):
+        prefix = self._new_node_name_prefix
+
+        if self._new_node_name_suffix is None:
+            largest_suffix: int = self.model.get_largest_node_name_suffix(prefix)
+            self._new_node_name_suffix = largest_suffix + 1
+
+        new_name = f"{prefix}{self._new_node_name_suffix!s}"
+        self._new_node_name_suffix += 1
+
+        return new_name
+
+    @staticmethod
+    def is_safe_to_fuse_nodes(
+        nodes_to_remove: list[onnx.NodeProto],
+        keep_outputs: list[str],
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ) -> bool:
+        for node_to_remove in nodes_to_remove:
+            for output_to_remove in node_to_remove.output:
+                if output_to_remove in keep_outputs:
+                    continue
+
+                if output_to_remove in input_name_to_nodes:
+                    for impacted_node in input_name_to_nodes[output_to_remove]:
+                        if impacted_node not in nodes_to_remove:
+                            # Not safe to remove nodes since output is used by impacted_node
+                            return False
+        return True
+
+    @staticmethod
+    def get_node_attribute(node: onnx.NodeProto, attribute_name: str):
+        for attr in node.attribute:
+            if attr.name == attribute_name:
+                value = onnx.helper.get_attribute_value(attr)
+                return value
+        return None
+
+    @staticmethod
+    def input_index(node_output: str, child_node: onnx.NodeProto) -> int:
+        for index, input_name in enumerate(child_node.input):
+            if input_name == node_output:
+                return index
+        return -1
+
+    @staticmethod
+    def tensor_shape_to_list(tensor_type) -> list[int]:
+        shape_list = []
+        for d in tensor_type.shape.dim:
+            if d.HasField("dim_value"):
+                shape_list.append(d.dim_value)  # known dimension
+            elif d.HasField("dim_param"):
+                shape_list.append(d.dim_param)  # unknown dimension with symbolic name
+            else:
+                shape_list.append("?")  # shall not happen
+        return shape_list
+
+    def get_constant_input(self, node: onnx.NodeProto):
+        for i, inp in enumerate(node.input):
+            value = self.model.get_constant_value(inp)
+            if value is not None:
+                return i, value
+
+        return None, None
+
+    def find_constant_input(self, node: onnx.NodeProto, expected_value: float, delta: float = 0.000001) -> int:
+        i, value = self.get_constant_input(node)
+        if value is not None and value.size == 1 and abs(value - expected_value) < delta:
+            return i
+
+        return -1
+
+    def has_constant_input(self, node: onnx.NodeProto, expected_value: float, delta: float = 0.000001) -> bool:
+        return self.find_constant_input(node, expected_value, delta) >= 0
+
+    def is_constant_with_specified_rank(self, output_name: str, rank: int) -> bool:
+        value = self.model.get_constant_value(output_name)
+        if value is None:
+            return False  # Not an initializer
+
+        if len(value.shape) != rank:
+            return False  # Wrong dimensions
+
+        return True
+
+    def match_first_parent(
+        self,
+        node: onnx.NodeProto,
+        parent_op_type: str,
+        output_name_to_node: dict[str, onnx.NodeProto] | None = None,
+        exclude: list[onnx.NodeProto] = [],  # noqa: B006
+    ) -> tuple[onnx.NodeProto | None, int | None]:
+        """
+        Find parent node based on constraints on op_type.
+
+        Args:
+            node: current node.
+            parent_op_type (str): constraint of parent node op_type.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+
+        Returns:
+            parent: The matched parent node. None if not found.
+            index: The input index of matched parent node. None if not found.
+        """
+        if output_name_to_node is None:
+            output_name_to_node = self.model.output_name_to_node()
+
+        for i, inp in enumerate(node.input):
+            if inp in output_name_to_node:
+                parent = output_name_to_node[inp]
+                if parent.op_type == parent_op_type and parent not in exclude:
+                    return parent, i
+
+        return None, None
+
+    def match_parent(
+        self,
+        node: onnx.NodeProto,
+        parent_op_type: str,
+        input_index: int | None = None,
+        output_name_to_node: dict[str, onnx.NodeProto] | None = None,
+        exclude: list[onnx.NodeProto] = [],  # noqa: B006
+        return_indice: list[int] | None = None,
+    ) -> onnx.NodeProto | None:
+        """
+        Find parent node based on constraints on op_type and index.
+        When input_index is None, we will find the first parent node based on constraints,
+        and return_indice will be appended the corresponding input index.
+
+        Args:
+            node (str): current node name.
+            parent_op_type (str): constraint of parent node op_type.
+            input_index (int or None): only check the parent given input index of current node.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+            return_indice (list): a list to append the input index when input_index is None.
+
+        Returns:
+            parent: The matched parent node.
+        """
+        assert node is not None
+        assert input_index is None or input_index >= 0
+
+        if output_name_to_node is None:
+            output_name_to_node = self.model.output_name_to_node()
+
+        if input_index is None:
+            parent, index = self.match_first_parent(node, parent_op_type, output_name_to_node, exclude)
+            if return_indice is not None:
+                return_indice.append(index)
+            return parent
+
+        if input_index >= len(node.input):
+            # Input index out of bounds.
+            return None
+
+        parent = self.model.get_parent(node, input_index, output_name_to_node)
+        if parent is not None and parent.op_type == parent_op_type and parent not in exclude:
+            return parent
+
+        return None
+
+    def match_parent_path(
+        self,
+        node: onnx.NodeProto,
+        parent_op_types: list[str],
+        parent_input_index: list[int] | None = None,
+        output_name_to_node: dict[str, onnx.NodeProto] | None = None,
+        return_indice: list[int] | None = None,
+    ) -> list[onnx.NodeProto] | None:
+        """
+        Find a sequence of input edges based on constraints on parent op_type and index.
+        When input_index is None, we will find the first parent node based on constraints,
+        and return_indice will be appended the corresponding input index.
+
+        Args:
+            node (str): current node name.
+            parent_op_types (str): constraint of parent node op_type of each input edge.
+            parent_input_index (list): constraint of input index of each input edge. None means no constraint.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            return_indice (list): a list to append the input index
+                                  When there is no constraint on input index of an edge.
+
+        Returns:
+            parents: a list of matched parent node.
+        """
+        if parent_input_index is not None:
+            assert len(parent_input_index) == len(parent_op_types)
+
+        if output_name_to_node is None:
+            output_name_to_node = self.model.output_name_to_node()
+
+        current_node = node
+        matched_parents = []
+        for i, op_type in enumerate(parent_op_types):
+            matched_parent = self.match_parent(
+                current_node,
+                op_type,
+                parent_input_index[i] if parent_input_index is not None else None,
+                output_name_to_node,
+                exclude=[],
+                return_indice=return_indice,
+            )
+            if matched_parent is None:
+                return None
+
+            matched_parents.append(matched_parent)
+            current_node = matched_parent
+
+        return matched_parents
+
+    def match_parent_paths(
+        self,
+        node: onnx.NodeProto,
+        paths: list[tuple[list[str], list[int]]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ) -> tuple[int, list[onnx.NodeProto] | None, list[int] | None]:
+        """
+        Find a matching parent path to the given node.
+        """
+        for i, path in enumerate(paths):
+            return_indice = []
+            matched = self.match_parent_path(node, path[0], path[1], output_name_to_node, return_indice)
+            if matched:
+                return i, matched, return_indice
+        return -1, None, None
+
+    def find_first_child_by_type(
+        self,
+        node: onnx.NodeProto,
+        child_type: str,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]] | None = None,
+        recursive: bool = True,
+    ) -> onnx.NodeProto | None:
+        children = self.model.get_children(node, input_name_to_nodes)
+        dq = deque(children)
+        while len(dq) > 0:
+            current_node = dq.pop()
+            if current_node.op_type == child_type:
+                return current_node
+
+            if recursive:
+                children = self.model.get_children(current_node, input_name_to_nodes)
+                for child in children:
+                    dq.appendleft(child)
+
+        return None
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_gelu.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_gelu.py
new file mode 100644
index 0000000000000000000000000000000000000000..8507454a5ab910a800f5d5632b2d1bf79b01fa93
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_gelu.py
@@ -0,0 +1,272 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import onnx
+
+from ..onnx_model import ONNXModel
+from .fusion import Fusion
+
+
+class FusionGelu(Fusion):
+    def __init__(self, model: ONNXModel):
+        super().__init__(model, "Gelu", "Erf")
+
+    def fuse(
+        self,
+        erf_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """
+        Interface function that tries to fuse a node sequence containing an Erf node into a single
+        Gelu node.
+        """
+        if (
+            self.fuse_1(erf_node, input_name_to_nodes, output_name_to_node)
+            or self.fuse_2(erf_node, input_name_to_nodes, output_name_to_node)
+            or self.fuse_3(erf_node, input_name_to_nodes, output_name_to_node)
+        ):
+            self.model.set_opset_import("com.microsoft", 1)
+
+    def fuse_1(
+        self,
+        erf_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ) -> bool:
+        """
+        This pattern is from PyTorch model
+        Fuse Gelu with Erf into one node:
+        Pattern 1:
+                       +-------Mul(0.5)---------------------+
+                       |                                    |
+                       |                                    v
+                    [root] --> Div -----> Erf  --> Add --> Mul -->
+                              (B=1.4142...)       (1)
+
+        Pattern 2:
+                       +------------------------------------+
+                       |                                    |
+                       |                                    v
+                    [root] --> Div -----> Erf  --> Add --> Mul -->Mul -->
+                              (B=1.4142...)       (1)            (0.5)
+
+        Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine.
+        """
+        if erf_node.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[erf_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Add":
+            return False
+        add_after_erf = children[0]
+
+        if not self.has_constant_input(add_after_erf, 1):
+            return False
+
+        if add_after_erf.output[0] not in input_name_to_nodes:
+            return False
+
+        children = input_name_to_nodes[add_after_erf.output[0]]
+        if len(children) != 1 or children[0].op_type != "Mul":
+            return False
+
+        mul_after_erf = children[0]
+
+        div = self.match_parent(erf_node, "Div", 0, output_name_to_node)
+        if div is None:
+            return False
+
+        if self.find_constant_input(div, 1.4142, delta=0.001) != 1:
+            return False
+
+        subgraph_input = div.input[0]
+
+        another = 1 if mul_after_erf.input[0] == add_after_erf.output[0] else 0
+        if subgraph_input == mul_after_erf.input[another]:  # pattern 2
+            children = input_name_to_nodes[mul_after_erf.output[0]]
+            if len(children) != 1 or children[0].op_type != "Mul":
+                return False
+            mul_half = children[0]
+            if not self.has_constant_input(mul_half, 0.5):
+                return False
+            subgraph_output = mul_half.output[0]
+        else:  # pattern 1
+            mul_half = self.match_parent(mul_after_erf, "Mul", another, output_name_to_node)
+            if mul_half is None:
+                return False
+
+            if not self.has_constant_input(mul_half, 0.5):
+                return False
+
+            if subgraph_input not in mul_half.input:
+                return False
+
+            subgraph_output = mul_after_erf.output[0]
+
+        subgraph_nodes = [div, erf_node, add_after_erf, mul_after_erf, mul_half]
+        if not self.is_safe_to_fuse_nodes(subgraph_nodes, [subgraph_output], input_name_to_nodes, output_name_to_node):
+            return False
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+        fused_node = onnx.helper.make_node(
+            "Gelu", name=self.create_unique_node_name(), inputs=[subgraph_input], outputs=[subgraph_output]
+        )
+        fused_node.domain = "com.microsoft"
+        self.nodes_to_add.append(fused_node)
+        return True
+
+    def fuse_2(
+        self,
+        erf_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ) -> bool:
+        """
+        This pattern is from Keras model
+        Fuse Gelu with Erf into one node:
+                       +------------------------------------------+
+                       |                                          |
+                       |                                          v
+                    [root] --> Div -----> Erf  --> Add --> Mul -->Mul
+                              (B=1.4142...)       (A=1)   (A=0.5)
+
+        Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine.
+        """
+        if erf_node.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[erf_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Add":
+            return False
+        add_after_erf = children[0]
+
+        if not self.has_constant_input(add_after_erf, 1):
+            return False
+
+        if add_after_erf.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[add_after_erf.output[0]]
+        if len(children) != 1 or children[0].op_type != "Mul":
+            return False
+        mul_after_erf = children[0]
+
+        if not self.has_constant_input(mul_after_erf, 0.5):
+            return False
+
+        if mul_after_erf.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[mul_after_erf.output[0]]
+        if len(children) != 1 or children[0].op_type != "Mul":
+            return False
+        mul = children[0]
+
+        div = self.match_parent(erf_node, "Div", 0, output_name_to_node)
+        if div is None:
+            return False
+
+        sqrt_node = None
+        if self.find_constant_input(div, 1.4142, delta=0.001) != 1:
+            sqrt_node = self.match_parent(div, "Sqrt", 1, output_name_to_node)
+            if sqrt_node is None:
+                return False
+            if not self.has_constant_input(sqrt_node, 2.0):
+                return False
+
+        subgraph_input = div.input[0]
+
+        if subgraph_input not in mul.input:
+            return False
+
+        subgraph_nodes = [div, erf_node, add_after_erf, mul_after_erf, mul]
+        if sqrt_node:
+            subgraph_nodes.append(sqrt_node)
+
+        if not self.is_safe_to_fuse_nodes(subgraph_nodes, [mul.output[0]], input_name_to_nodes, output_name_to_node):
+            return False
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+        fused_node = onnx.helper.make_node(
+            "Gelu", name=self.create_unique_node_name(), inputs=[subgraph_input], outputs=[mul.output[0]]
+        )
+        fused_node.domain = "com.microsoft"
+        self.nodes_to_add.append(fused_node)
+        return True
+
+    def fuse_3(
+        self,
+        erf_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ) -> bool:
+        """
+        This pattern is from TensorFlow model
+        Fuse Gelu with Erf into one node:
+                       +----------------------------------------------+
+                       |                                              |
+                       |                                              v
+                    [root] --> Mul -----> Erf    -->   Add --> Mul -->Mul
+                               (A=0.7071067690849304)  (B=1)  (B=0.5)
+
+        Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine.
+        """
+
+        if erf_node.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[erf_node.output[0]]
+        if len(children) != 1 or children[0].op_type != "Add":
+            return False
+        add_after_erf = children[0]
+
+        if not self.has_constant_input(add_after_erf, 1):
+            return False
+
+        if add_after_erf.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[add_after_erf.output[0]]
+        if len(children) != 1 or children[0].op_type != "Mul":
+            return False
+        mul_half = children[0]
+
+        if not self.has_constant_input(mul_half, 0.5):
+            return False
+
+        first_mul = self.match_parent(erf_node, "Mul", 0, output_name_to_node)
+        if first_mul is None:
+            return False
+
+        i = self.find_constant_input(first_mul, 0.7071067690849304, delta=0.001)
+        if i < 0:
+            return False
+
+        root_input_index = 1 - i
+        subgraph_input = first_mul.input[root_input_index]
+
+        if mul_half.output[0] not in input_name_to_nodes:
+            return False
+        children = input_name_to_nodes[mul_half.output[0]]
+        if len(children) != 1 or children[0].op_type != "Mul":
+            return False
+        last_mul = children[0]
+
+        if not (last_mul.input[0] == subgraph_input or last_mul.input[1] == subgraph_input):
+            return False
+
+        subgraph_nodes = [first_mul, erf_node, add_after_erf, mul_half, last_mul]
+        if not self.is_safe_to_fuse_nodes(
+            subgraph_nodes,
+            [last_mul.output[0]],
+            input_name_to_nodes,
+            output_name_to_node,
+        ):
+            return False
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+        fused_node = onnx.helper.make_node(
+            "Gelu", name=self.create_unique_node_name(), inputs=[subgraph_input], outputs=[last_mul.output[0]]
+        )
+        fused_node.domain = "com.microsoft"
+        self.nodes_to_add.append(fused_node)
+        return True
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_layernorm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_layernorm.py
new file mode 100644
index 0000000000000000000000000000000000000000..e0ef02ca0862d22b04ac8a401345d1c0a8d9202e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/fusion_layernorm.py
@@ -0,0 +1,146 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import onnx
+
+from ..onnx_model import ONNXModel
+from .fusion import Fusion
+
+
+class FusionLayerNormalization(Fusion):
+    def __init__(self, model: ONNXModel):
+        super().__init__(model, "LayerNormalization", "ReduceMean")
+
+    def fuse(
+        self,
+        reduce_mean_node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """
+        Interface function that tries to fuse a node sequence containing a ReduceMean node into a single
+        LayerNormalization node.
+
+              +----------------------+
+              |                      |
+              |                      v
+          [Root] --> ReduceMean -->  Sub  --> Pow --> ReduceMean --> Add --> Sqrt --> Div --> Mul --> Add
+                     (axis=2 or -1)  |      (Y=2)   (axis=2 or -1)  (E-6 or E-12 or 0) ^
+                                     |                                                 |
+                                     +-------------------------------------------------+
+
+         Or, using Mul instead of Pow:
+
+              +----------------------+
+              |                      |
+              |                      v
+          [Root] --> ReduceMean -->  Sub  --> Mul --> ReduceMean --> Add --> Sqrt --> Div --> Mul --> Add
+                     (axis=2 or -1)  |     (in0=in1)   (axis=2 or -1)  (E-6 or E-12 or 0) ^
+                                     |                                                 |
+                                     +-------------------------------------------------+
+
+         It also handles cases of duplicated sub nodes exported from older version of PyTorch:
+
+              +----------------------+
+              |                      v
+              |           +-------> Sub-----------------------------------------------+
+              |           |                                                           |
+              |           |                                                           v
+          [Root] --> ReduceMean -->  Sub  --> (Pow or Mul) --> ReduceMean --> Add --> Sqrt --> Div  --> Mul --> Add
+              |                      ^
+              |                      |
+              +----------------------+
+        """
+        children = self.model.get_children(reduce_mean_node, input_name_to_nodes)
+        if len(children) == 0 or len(children) > 2:
+            return
+
+        root_input = reduce_mean_node.input[0]
+
+        if children[0].op_type != "Sub" or children[0].input[0] != root_input:
+            return
+
+        if len(children) == 2:
+            if children[1].op_type != "Sub" or children[1].input[0] != root_input:
+                return
+
+        div_node = None
+        for child in children:
+            div_node = self.find_first_child_by_type(child, "Div", input_name_to_nodes, recursive=False)
+            if div_node is not None:
+                break
+        if div_node is None:
+            return
+
+        path_id, parent_nodes, _ = self.match_parent_paths(
+            div_node,
+            [
+                (["Sqrt", "Add", "ReduceMean", "Pow", "Sub"], [1, 0, 0, 0, 0]),
+                (["Sqrt", "Add", "ReduceMean", "Pow", "Cast", "Sub"], [1, 0, 0, 0, 0, 0]),
+                (["Sqrt", "Add", "ReduceMean", "Mul", "Sub"], [1, 0, 0, 0, 0]),
+                (["Sqrt", "Add", "ReduceMean", "Mul", "Cast", "Sub"], [1, 0, 0, 0, 0, 0]),
+            ],
+            output_name_to_node,
+        )
+        if path_id < 0:
+            return
+
+        sub_node = parent_nodes[-1]
+        if sub_node not in children:
+            return
+
+        second_add_node = parent_nodes[1]
+        i, add_weight = self.get_constant_input(second_add_node)
+        if add_weight is None or add_weight <= 0 or add_weight > 1.0e-4:
+            # Skip fusion since epsilon value is not expected.
+            return
+
+        pow_or_mul_node = parent_nodes[3]
+        if pow_or_mul_node.op_type == "Pow" and self.find_constant_input(pow_or_mul_node, 2.0) != 1:
+            return
+        elif pow_or_mul_node.op_type == "Mul" and pow_or_mul_node.input[0] != pow_or_mul_node.input[1]:
+            return
+
+        mul_node = input_name_to_nodes[div_node.output[0]][0]
+        if mul_node.op_type != "Mul":
+            return
+
+        last_add_node = input_name_to_nodes[mul_node.output[0]][0]
+        if last_add_node.op_type != "Add":
+            return
+
+        subgraph_nodes = [reduce_mean_node]
+        subgraph_nodes.extend(children)
+        subgraph_nodes.extend(parent_nodes[:-1])
+
+        subgraph_nodes.extend([last_add_node, mul_node, div_node])
+        if not self.is_safe_to_fuse_nodes(
+            subgraph_nodes,
+            last_add_node.output,
+            input_name_to_nodes,
+            output_name_to_node,
+        ):
+            return
+
+        weight_input = mul_node.input[1 - self.input_index(div_node.output[0], mul_node)]
+        if not self.is_constant_with_specified_rank(weight_input, 1):
+            return
+
+        bias_input = last_add_node.input[1 - self.input_index(mul_node.output[0], last_add_node)]
+        if not self.is_constant_with_specified_rank(bias_input, 1):
+            return
+
+        self.nodes_to_remove.extend(subgraph_nodes)
+
+        normalize_node = onnx.helper.make_node(
+            "LayerNormalization",
+            name=self.create_unique_node_name(),
+            inputs=[reduce_mean_node.input[0], weight_input, bias_input],
+            outputs=[last_add_node.output[0]],
+        )
+        normalize_node.attribute.extend([onnx.helper.make_attribute("epsilon", float(add_weight))])
+        self.nodes_to_add.append(normalize_node)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/replace_upsample_with_resize.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/replace_upsample_with_resize.py
new file mode 100644
index 0000000000000000000000000000000000000000..323bed9dd1eb669b821020d0b1791ec4b94d9c0a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/fusions/replace_upsample_with_resize.py
@@ -0,0 +1,96 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import numpy as np
+import onnx
+
+from ..onnx_model import ONNXModel
+from .fusion import Fusion
+
+
+class ReplaceUpsampleWithResize(Fusion):
+    """Replace Upsample with Resize."""
+
+    def __init__(self, model: ONNXModel, opset):
+        """Initialize."""
+        super().__init__(model, "Resize", "Upsample")
+        self.opset = opset
+
+    def fuse(
+        self,
+        node: onnx.NodeProto,
+        input_name_to_nodes: dict[str, list[onnx.NodeProto]],
+        output_name_to_node: dict[str, onnx.NodeProto],
+    ):
+        """Replace Upsample with Resize."""
+        mode = None
+        for attr in node.attribute:
+            if attr.name == "mode":
+                mode = attr.s.decode("utf-8")
+                break
+
+        scales_input = None
+        if self.opset > 7:
+            scales_input = node.input[1] if len(node.input) > 1 else ""
+            resize_inputs = [node.input[0], node.name + "_roi", scales_input]
+        else:
+            if self.opset == 7:
+                for attr in node.attribute:
+                    if attr.name == "scales":
+                        scales_input = attr.floats
+                        break
+
+                scales_input = np.array(list(scales_input), np.float32)
+            else:
+                h_scale = 1
+                w_scale = 1
+                for attr in node.attribute:
+                    if attr.name == "height_scale":
+                        h_scale = attr.float
+                    elif attr.name == "width_scale":
+                        w_scale = attr.float
+
+                scales_input = np.array([1, 1, h_scale, w_scale], np.float32)
+
+            scales_tensor = onnx.helper.make_tensor(
+                name=node.name + "_scales",
+                data_type=onnx.TensorProto.FLOAT,
+                dims=scales_input.shape,
+                vals=scales_input.flatten().tolist(),
+            )
+
+            scales_node = onnx.helper.make_node(
+                "Constant", inputs=[], outputs=[node.name + "_scales"], value=scales_tensor
+            )
+
+            self.nodes_to_add.append(scales_node)
+
+            resize_inputs = [node.input[0], node.name + "_roi", node.name + "_scales"]
+
+        roi_tensor = onnx.helper.make_tensor(
+            name=node.name + "_roi",
+            data_type=onnx.TensorProto.FLOAT,
+            dims=(len(scales_input) * 2,),
+            vals=[0] * len(scales_input) + [1] * len(scales_input),
+        )
+
+        roi_node = onnx.helper.make_node("Constant", inputs=[], outputs=[node.name + "_roi"], value=roi_tensor)
+
+        resize_node = onnx.helper.make_node(
+            op_type="Resize", inputs=resize_inputs, outputs=node.output, mode=mode, nearest_mode="floor"
+        )
+
+        self.nodes_to_remove.append(node)
+        self.nodes_to_add.append(roi_node)
+        self.nodes_to_add.append(resize_node)
+
+    def apply(self) -> bool:
+        """Apply."""
+        if super().apply():
+            self.model.topological_sort()
+            return True
+        return False
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd64b471046035200143b3ed126312d78f0f8e3f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/__init__.py
@@ -0,0 +1 @@
+from .weight_only import gptq_quantize, rtn_quantize  # noqa: F401
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/onnx_model.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/onnx_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..75e5332cfa254ec6c96e5d2292e5a5e9807519d0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/onnx_model.py
@@ -0,0 +1,1236 @@
+#
+#  The implementation of this file is based on:
+# https://github.com/intel/neural-compressor/tree/master/neural_compressor
+#
+# Copyright (c) 2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Class for ONNX model."""
+
+import copy
+import logging
+import os
+from collections import deque
+from pathlib import Path
+
+import onnx
+import onnx.external_data_helper
+import onnx_ir as ir
+
+from .util import MAXIMUM_PROTOBUF, find_by_name
+
+logger = logging.getLogger("neural_compressor")
+
+# TODO: Check https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/python/tools/quantization/onnx_model.py to see if we can integrate with it.
+
+
+class ONNXModel:
+    """Build ONNX model."""
+
+    def __init__(self, model, **kwargs):
+        """Initialize an ONNX model.
+
+        Args:
+            model (str or ModelProto): path to onnx model or loaded ModelProto model object.
+            ignore_warning (bool): ignore large model warning. Default is False.
+            load_external_data (bool): load external data for large model. Default is True.
+        """
+        self._model = model if not isinstance(model, str) else onnx.load(model, load_external_data=False)
+        self._model_path = None if not isinstance(model, str) else model
+
+        self.check_is_large_model()
+        if self._is_large_model and self._model_path is None and not kwargs.get("ignore_warning", False):
+            logger.warning("Model size > 2GB. Please use model path instead of onnx model object to quantize")
+
+        if self._is_large_model and isinstance(model, str) and kwargs.get("load_external_data", True):
+            onnx.external_data_helper.load_external_data_for_model(self._model, os.path.dirname(self._model_path))
+
+        self._config = None
+        if isinstance(model, str) and os.path.exists(Path(model).parent.joinpath("config.json").as_posix()):
+            from transformers import AutoConfig  # noqa: PLC0415
+
+            self._config = AutoConfig.from_pretrained(Path(model).parent.as_posix())
+
+        self.node_name_counter = {}
+        self._output_name_to_node = {}
+        self._input_name_to_nodes = {}
+        self._get_input_name_to_nodes(self._model.graph.node)
+        self._get_output_name_to_node(self._model.graph.node)
+        self._graph_info = {}
+        self._get_graph_info()
+        self._q_config = None
+
+    def check_is_large_model(self):
+        """Check model > 2GB."""
+        ir_graph = ir.from_proto(self._model.graph)
+        initializer_size = sum(
+            v.const_value.nbytes for v in ir_graph.initializers.values() if v.const_value is not None
+        )
+        self._is_large_model = initializer_size > MAXIMUM_PROTOBUF
+
+    @property
+    def is_large_model(self):
+        """Check the onnx model is over 2GB."""
+        return self._is_large_model
+
+    @property
+    def model_path(self):
+        """Return model path."""
+        return self._model_path
+
+    @model_path.setter
+    def model_path(self, path):
+        """Set model path."""
+        self._model_path = path
+
+    def framework(self):
+        """Return framework."""
+        return "onnxruntime"
+
+    @property
+    def q_config(self):
+        """Return q_config."""
+        return self._q_config
+
+    @q_config.setter
+    def q_config(self, q_config):
+        """Set q_config."""
+        self._q_config = q_config
+
+    @property
+    def hf_config(self):
+        """Return huggingface config if model is Transformer-based."""
+        return self._config
+
+    @property
+    def model(self):
+        """Return model itself."""
+        return self._model
+
+    @model.setter
+    def model(self, model):
+        """Set model itself."""
+        self._model = model
+        self._graph_info = {}
+        self._get_graph_info()
+        self._output_name_to_node = {}
+        self._input_name_to_nodes = {}
+        self._get_input_name_to_nodes(self._model.graph.node)
+        self._get_output_name_to_node(self._model.graph.node)
+
+    def input(self):
+        """Return input of model."""
+        return [i.name for i in self._model.graph.input]
+
+    def output(self):
+        """Return output of model."""
+        return [i.name for i in self._model.graph.output]
+
+    def update(self):
+        """Update model info."""
+        self._graph_info = {}
+        self._get_graph_info()
+        self._output_name_to_node = {}
+        self._input_name_to_nodes = {}
+        self._get_input_name_to_nodes(self._model.graph.node)
+        self._get_output_name_to_node(self._model.graph.node)
+
+    @property
+    def graph_info(self):
+        """Return ORT Graph Info object holding information about backend graph."""
+        return self._graph_info
+
+    def _get_graph_info(self):
+        """Update graph info."""
+        for node in self._model.graph.node:
+            self.graph_info.update({node.name: node.op_type})
+
+    def save(self, root):
+        """Save ONNX model."""
+        if os.path.split(root)[0] != "" and not os.path.exists(os.path.split(root)[0]):
+            raise ValueError('"root" directory does not exists.')
+        if self.is_large_model:
+            onnx.external_data_helper.load_external_data_for_model(self._model, os.path.split(self._model_path)[0])
+            onnx.save_model(
+                self._model,
+                root,
+                save_as_external_data=True,
+                all_tensors_to_one_file=True,
+                location=root.split("/")[-1] + "_data",
+                size_threshold=1024,
+                convert_attribute=False,
+            )
+        else:
+            onnx.save(self._model, root)
+
+        if self._config is not None:
+            model_type = "" if not hasattr(self._config, "model_type") else self._config.model_type
+            self._config.__class__.model_type = model_type
+            output_config_file = Path(root).parent.joinpath("config.json").as_posix()
+            self._config.to_json_file(output_config_file, use_diff=False)
+
+    def nodes(self):
+        """Return model nodes."""
+        return self._model.graph.node
+
+    def initializer(self):
+        """Return model initializer."""
+        return self._model.graph.initializer
+
+    def graph(self):
+        """Return model graph."""
+        return self._model.graph
+
+    def ir_version(self):
+        """Return model ir_version."""
+        return self._model.ir_version
+
+    def opset_import(self):
+        """Return model opset_import."""
+        return self._model.opset_import
+
+    def remove_node(self, node):
+        """Remove a node from model."""
+        if node in self._model.graph.node:
+            self._model.graph.node.remove(node)
+
+    def remove_nodes(self, nodes_to_remove):
+        """Remove nodes from model."""
+        for node in nodes_to_remove:
+            self.remove_node(node)
+
+    def add_node(self, node):
+        """Add a node to model."""
+        self._model.graph.node.extend([node])
+
+    def add_nodes(self, nodes_to_add):
+        """Add nodes to model."""
+        self._model.graph.node.extend(nodes_to_add)
+
+    def add_initializer(self, tensor):
+        """Add a initializer to model."""
+        if find_by_name(tensor.name, self._model.graph.initializer) is None:
+            self._model.graph.initializer.extend([tensor])
+
+    def add_initializers(self, tensors):
+        """Add initializers to model."""
+        for tensor in tensors:
+            self.add_initializer(tensor)
+
+    def get_initializer(self, name):
+        """Get an initializer by name."""
+        for tensor in self._model.graph.initializer:
+            if tensor.name == name:
+                return tensor
+        return None
+
+    def get_initializer_share_num(self, name):
+        """Get the number of shares of initializer."""
+        num = 0
+        if self.get_initializer(name) is None:
+            return num
+
+        for node in self.nodes():
+            if name in node.input:
+                num += 1
+        return num
+
+    def get_node(self, name):
+        """Get a node by name."""
+        for node in self._model.graph.node:
+            if node.name == name:
+                return node
+        return None
+
+    def remove_initializer(self, tensor):
+        """Remove an initializer from model."""
+        if tensor in self._model.graph.initializer:
+            self._model.graph.initializer.remove(tensor)
+
+    def remove_initializers(self, init_to_remove):
+        """Remove initializers from model."""
+        for initializer in init_to_remove:
+            self.remove_initializer(initializer)
+
+    def set_initializer(self, tensor, array, raw=False):
+        """Update initializer."""
+        old_tensor = self.get_initializer(tensor)
+        self.remove_initializer(old_tensor)
+        dims = old_tensor.dims
+        data_type = old_tensor.data_type
+        new_tensor = (
+            onnx.helper.make_tensor(tensor, data_type, dims, array.flatten().tolist())
+            if not raw
+            else onnx.helper.make_tensor(tensor, data_type, dims, array.tostring(), raw=raw)
+        )
+        self.add_initializer(new_tensor)
+
+    @property
+    def input_name_to_nodes(self):
+        """Return input names of nodes."""
+        return self._input_name_to_nodes
+
+    def _get_input_name_to_nodes(self, nodes):
+        """Get input names of nodes."""
+        for node in nodes:
+            attrs = [
+                attr
+                for attr in node.attribute
+                if attr.type == onnx.AttributeProto.GRAPH or attr.type == onnx.AttributeProto.GRAPHS
+            ]
+            if len(attrs) > 0:
+                for attr in attrs:
+                    self._get_input_name_to_nodes(attr.g.node)
+            for input_name in node.input:
+                if len(input_name.strip()) != 0:
+                    if input_name not in self._input_name_to_nodes:
+                        self._input_name_to_nodes[input_name] = [node]
+                    else:
+                        self._input_name_to_nodes[input_name].append(node)
+
+    @property
+    def output_name_to_node(self):
+        """Return output names of nodes."""
+        return self._output_name_to_node
+
+    def _get_output_name_to_node(self, nodes):
+        """Get output names of nodes."""
+        for node in nodes:
+            attrs = [
+                attr
+                for attr in node.attribute
+                if attr.type == onnx.AttributeProto.GRAPH or attr.type == onnx.AttributeProto.GRAPHS
+            ]
+            if len(attrs) > 0:
+                for attr in attrs:
+                    self._get_output_name_to_node(attr.g.node)
+            for output_name in node.output:
+                if len(output_name.strip()) != 0:
+                    self._output_name_to_node[output_name] = node
+
+    def get_siblings(self, node):
+        """Get siblings nodes."""
+        siblings = []
+        for parent in self.get_parents(node):
+            for child in self.get_children(parent):
+                if child.name != node.name:
+                    siblings.append(child)
+        return siblings
+
+    def get_children(self, node, input_name_to_nodes=None):
+        """Get children nodes."""
+        if input_name_to_nodes is None:
+            input_name_to_nodes = self._input_name_to_nodes
+
+        children = []
+        for output in node.output:
+            if output in input_name_to_nodes:
+                for child in input_name_to_nodes[output]:
+                    children.append(child)  # noqa:  PERF402
+        return children
+
+    def get_parents(self, node, output_name_to_node=None):
+        """Get parents nodes."""
+        if output_name_to_node is None:
+            output_name_to_node = self._output_name_to_node
+
+        parents = []
+        for input in node.input:
+            if input in output_name_to_node:
+                parents.append(output_name_to_node[input])
+        return parents
+
+    def get_parent(self, node, idx, output_name_to_node=None):
+        """Get parent node by idx."""
+        if output_name_to_node is None:
+            output_name_to_node = self._output_name_to_node
+
+        if len(node.input) <= idx:
+            return None
+
+        input = node.input[idx]
+        if input not in output_name_to_node:
+            return None
+
+        return output_name_to_node[input]
+
+    def find_node_by_name(self, node_name, new_nodes_list, graph):
+        """Find out node by name."""
+        graph_nodes_list = list(graph.node)  # deep copy
+        graph_nodes_list.extend(new_nodes_list)
+        node = find_by_name(node_name, graph_nodes_list)
+        return node
+
+    def find_nodes_by_initializer(self, graph, initializer):
+        """Find all nodes with given initializer as an input."""
+        nodes = []
+        for node in graph.node:
+            for node_input in node.input:
+                if node_input == initializer.name:
+                    nodes.append(node)
+        return nodes
+
+    def get_scale_zero(self, tensor):
+        """Help function to get scale and zero_point."""
+        if not tensor.endswith("_quantized"):
+            logger.debug(f"Find {tensor} in the quantized graph is not quantized.")
+            return None, None
+
+        def _searcher(tensor_name):
+            """Search scale and zero point tensor recursively."""
+            node = self._input_name_to_nodes[tensor_name][0]
+            parent = self._output_name_to_node.get(tensor_name, None)
+            direct_int8 = ["Reshape", "Transpose", "Squeeze", "Unsqueeze", "MaxPool", "Pad", "Split"]
+            if parent is not None and parent.op_type in direct_int8:
+                fp32_tensor_name = (
+                    parent.input[0]
+                    .replace("_quantized", "")
+                    .replace("_QuantizeLinear", "")
+                    .replace("_QuantizeInput", "")
+                )
+            elif node.op_type in ["Gather"]:  # pragma: no cover
+                fp32_tensor_name = (
+                    node.output[0]
+                    .replace("_quantized", "")
+                    .replace("_QuantizeLinear", "")
+                    .replace("_QuantizeInput", "")
+                )
+            else:
+                fp32_tensor_name = (
+                    tensor_name.replace("_quantized", "").replace("_QuantizeLinear", "").replace("_QuantizeInput", "")
+                )
+            scale = fp32_tensor_name + "_scale"
+            scale_tensor = self.get_initializer(scale)
+            zo = fp32_tensor_name + "_zero_point"
+            zo_tensor = self.get_initializer(zo)
+
+            if scale_tensor is None or zo_tensor is None:
+                if parent is not None:
+                    scale_tensor, zo_tensor = _searcher(parent.input[0])
+            return scale_tensor, zo_tensor
+
+        node = self._input_name_to_nodes[tensor][0]
+        # TODO check if scale_tensor and zero_point is needed
+        # for bias of qlinearconv, scale and zero_point is not needed
+        if (node.op_type == "QLinearConv" and tensor == node.input[-1]) or (
+            node.op_type == "QGemm" and tensor == node.input[-3]
+        ):
+            return None, None
+        else:
+            scale_tensor, zo_tensor = _searcher(tensor)
+            assert scale_tensor, f"missing scale for tensor {tensor}"
+            assert zo_tensor, f"missing zero point for tensor {tensor}"
+            return scale_tensor, zo_tensor
+
+    def save_model_to_file(self, output_path, use_external_data_format=False):
+        """Save model to external data, which is needed for model size > 2GB."""
+        if use_external_data_format:
+            onnx.external_data_helper.convert_model_to_external_data(
+                self._model, all_tensors_to_one_file=True, location=Path(output_path).name + ".data"
+            )
+        onnx.save_model(self._model, output_path)
+
+    @staticmethod
+    def replace_node_input(node, old_input_name, new_input_name):
+        """Replace input of a node."""
+        assert isinstance(old_input_name, str) and isinstance(new_input_name, str)
+        for j in range(len(node.input)):
+            if node.input[j] == old_input_name:
+                node.input[j] = new_input_name
+
+    def replace_input_of_all_nodes(self, old_input_name, new_input_name, white_optype=None, black_optype=None):
+        """Replace inputs of all nodes."""
+        if white_optype is None:
+            white_optype = []
+        if black_optype is None:
+            black_optype = []
+        if len(white_optype) > 0:
+            for node in self.model.graph.node:
+                if node.op_type in white_optype:
+                    ONNXModel.replace_node_input(node, old_input_name, new_input_name)
+        else:
+            for node in self.model.graph.node:
+                if node.op_type not in black_optype:
+                    ONNXModel.replace_node_input(node, old_input_name, new_input_name)
+
+    @staticmethod
+    def replace_node_output(node, old_output_name, new_output_name):
+        """Replace output of a node."""
+        assert isinstance(old_output_name, str) and isinstance(new_output_name, str)
+        for j in range(len(node.output)):
+            if node.output[j] == old_output_name:
+                node.output[j] = new_output_name
+
+    def replace_output_of_all_nodes(self, old_output_name, new_output_name, white_optype=None, black_optype=None):
+        """Replace outputs of all nodes."""
+        if white_optype is None:
+            white_optype = []
+        if black_optype is None:
+            black_optype = []
+        if len(white_optype) > 0:
+            for node in self.model.graph.node:
+                if node.op_type in white_optype:
+                    ONNXModel.replace_node_output(node, old_output_name, new_output_name)
+        else:
+            for node in self.model.graph.node:
+                if node.op_type not in black_optype:
+                    ONNXModel.replace_node_output(node, old_output_name, new_output_name)
+
+    def remove_unused_nodes(self):
+        """Remove unused nodes."""
+        unused_nodes = []
+        nodes = self.nodes()
+        for node in nodes:
+            if (
+                node.op_type == "Constant"
+                and node.output[0] not in self._model.graph.output
+                and node.output[0] not in self._input_name_to_nodes
+            ):
+                unused_nodes.append(node)
+            elif (
+                node.op_type == "QuantizeLinear"
+                and len(self.get_children(node)) == 1
+                and self.get_children(node)[0].op_type == "DequantizeLinear"
+                and node.input[0] not in self._output_name_to_node
+                and self.get_children(node)[0].output[0] not in self._input_name_to_nodes
+            ):
+                unused_nodes.append(node)
+                unused_nodes.extend(self.get_children(node))
+            else:
+                # remove the node if it does not serve as the input or output of any other nodes
+                unused = True
+                for output in node.output:
+                    if output in self._input_name_to_nodes or output in self.output():
+                        unused = False
+                        break
+                for input in node.input:
+                    if self.get_initializer(input) is not None:
+                        continue
+                    elif input in self._output_name_to_node or input in self.input():
+                        unused = False
+                        break
+                if unused:
+                    unused_nodes.append(node)
+        self.remove_nodes(unused_nodes)
+
+        ununsed_weights = []
+        for w in self._model.graph.initializer:
+            if w.name not in self._input_name_to_nodes and w.name not in self._model.graph.output:
+                ununsed_weights.append(w)
+                # Remove from graph.input
+                for graph_input in self.graph().input:
+                    if graph_input.name == w.name:
+                        self.graph().input.remove(graph_input)
+
+        self.remove_initializers(ununsed_weights)
+        self.update()
+
+    def topological_sort(self, enable_subgraph=False):
+        """Topological sort the model."""
+
+        if not enable_subgraph:
+            input_name_to_nodes = {}
+            output_name_to_node = {}
+            for node in self.model.graph.node:
+                for input_name in node.input:
+                    if len(input_name.strip()) != 0:
+                        if input_name not in input_name_to_nodes:
+                            input_name_to_nodes[input_name] = [node]
+                        else:
+                            input_name_to_nodes[input_name].append(node)
+                for output_name in node.output:
+                    if len(output_name.strip()) != 0:
+                        output_name_to_node[output_name] = node
+        else:  # pragma: no cover
+            input_name_to_nodes = self._input_name_to_nodes
+            output_name_to_node = self._output_name_to_node
+
+        all_nodes = {}
+        q = deque()
+        wait = deque()
+        for inp in self.model.graph.input:
+            q.extend(input_name_to_nodes[inp.name])
+        for n in self.model.graph.node:
+            if all(i not in output_name_to_node and i not in self.input() for i in n.input):
+                q.append(n)
+
+        while q:
+            n = q.popleft()
+            if not all(output_name_to_node[i].name in all_nodes for i in n.input if i in output_name_to_node):
+                if n not in wait:
+                    wait.append(n)
+                continue
+
+            all_nodes[n.name] = n
+            for out in n.output:
+                if out in input_name_to_nodes:
+                    q.extend([i for i in input_name_to_nodes[out] if i.name not in all_nodes and i not in q])
+            if len(q) == 0 and len(wait) != 0:
+                q = copy.deepcopy(wait)
+                wait.clear()
+        nodes = [i[1] for i in all_nodes.items()]
+        assert len(list({n.name for n in nodes})) == len(list({n.name for n in self.model.graph.node}))
+        self.model.graph.ClearField("node")
+        self.model.graph.node.extend(nodes)
+
+    def get_nodes_chain(self, start, stop, result_chain=None):
+        """Get nodes chain with given start node and stop node."""
+        if result_chain is None:
+            result_chain = []
+        # process start node list
+        start_node = deque()
+        for node in start:
+            if isinstance(node, str):
+                start_node.append(node)
+            elif isinstance(node, onnx.NodeProto):
+                start_node.append(node.name)
+            else:
+                assert False, "'get_nodes_chain' function only support list[string]or list[NodeProto] params"  # noqa: B011
+
+        # process stop node list
+        stop_node = []
+        for node in stop:
+            if isinstance(node, str):
+                stop_node.append(node)
+            elif isinstance(node, onnx.NodeProto):
+                stop_node.append(node.name)
+            else:
+                assert False, "'get_nodes_chain' function only support list[string]or list[NodeProto] params"  # noqa: B011
+
+        while start_node:
+            node_name = start_node.popleft()
+            if node_name in stop_node:
+                continue
+            if node_name not in result_chain:
+                result_chain.append(node_name)
+            else:
+                continue
+
+            node = find_by_name(node_name, list(self.model.graph.node))
+            for parent in self.get_parents(node):
+                start_node.append(parent.name)
+
+        return result_chain
+
+    def find_split_node_for_layer_wise_quantization(self):
+        """Find split node for layer wise quantization."""
+        # find split nodes of decoder blocks
+        # embed -> decoder.0 -(split_node)-> ... -(split_node)-> decoder.n -(split_node)-> norm -> head
+        # after split: embed -> decoder.0,
+        #              decoder.1,
+        #              decoder.2,
+        #              ...,
+        #              decoder.n,
+        #              norm -> head
+        start_nodes = []
+        for node in self._model.graph.node:
+            start_node, qkv_nodes_list = None, None
+            if node.op_type == "SkipLayerNormalization":
+                start_node = node
+                qkv_nodes_list = [
+                    self.match_parent_path(
+                        start_node,
+                        ["MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [None, 0, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+                        [1, 1, 0, 0, 0],
+                    ),
+                ]
+            if node.op_type == "Add":
+                start_node = node
+                qkv_nodes_list = [
+                    # match base attention structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+                        [0, None, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node, ["Add", "MatMul", "Reshape", "Transpose", "MatMul"], [1, None, 0, 0, 0]
+                    ),
+                    # match gpt attention no past structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Reshape", "Gemm", "Reshape", "Reshape", "Transpose", "MatMul"],
+                        [None, 0, 0, 0, 0, 0],
+                        output_name_to_node=self.output_name_to_node,
+                        return_indice=[],
+                    ),
+                    # match bart attention structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [0, None, 0, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [1, None, 0, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["MatMul", "Mul", "MatMul", "Mul", "Div", "Add"],
+                        [None, 0, None, 0, None, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["MatMul", "Mul", "MatMul", "SimplifiedLayerNormalization", "Add"],
+                        [None, 0, None, 0, 0],
+                    ),
+                ]
+            if not start_node:
+                continue
+            if not any(qkv_nodes_list):
+                continue
+            start_nodes.append(start_node)
+        return start_nodes
+
+    def find_qkv_in_attention(self, find_all=False):
+        """Find qkv MatMul in Attention.
+
+        Args:
+            find_all (bool, optional): find all qkv MatMul. Defaults to False
+
+        Returns:
+            qkv (list): qkv MatMul list
+        """
+        qkv = []
+        for node in self._model.graph.node:
+            if node.op_type == "Attention":
+                qkv.append([node.name])
+                continue
+            start_node, qkv_nodes_list = None, None
+            if node.op_type == "SkipLayerNormalization":
+                start_node = node
+                qkv_nodes_list = [
+                    self.match_parent_path(
+                        start_node,
+                        ["MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [None, 0, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+                        [1, 1, 0, 0, 0],
+                    ),
+                ]
+            if node.op_type == "Add":
+                start_node = node
+                qkv_nodes_list = [
+                    # match base attention structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+                        [0, None, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node, ["Add", "MatMul", "Reshape", "Transpose", "MatMul"], [1, None, 0, 0, 0]
+                    ),
+                    # match gpt attention no past structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Reshape", "Gemm", "Reshape", "Reshape", "Transpose", "MatMul"],
+                        [None, 0, 0, 0, 0, 0],
+                        output_name_to_node=self.output_name_to_node,
+                        return_indice=[],
+                    ),
+                    # match bart attention structure
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [0, None, 0, 0, 0, 0],
+                    ),
+                    self.match_parent_path(
+                        start_node,
+                        ["Add", "MatMul", "Reshape", "Transpose", "Reshape", "MatMul"],
+                        [1, None, 0, 0, 0, 0],
+                    ),
+                ]
+            if not start_node:
+                continue
+            if not any(qkv_nodes_list):
+                continue
+            qkv_nodes = [qkv for qkv in qkv_nodes_list if qkv is not None][-1]
+            other_inputs = []
+            for input in start_node.input:
+                if input not in self.output_name_to_node:
+                    continue
+                if input == qkv_nodes[0].output[0]:
+                    continue
+                other_inputs.append(input)
+            if len(other_inputs) != 1:
+                continue
+            root_input = other_inputs[0]
+            input_name_to_nodes = self.input_name_to_nodes
+            children = input_name_to_nodes[root_input]
+            children_types = [child.op_type for child in children]
+            if children_types.count("MatMul") == 3:
+                qkv.append([child.name for child in children if child.op_type == "MatMul"])
+                if not find_all:
+                    break
+        return qkv
+
+    def find_ffn_matmul(self, attention_index, attention_matmul_list, block_len):
+        """Find MatMul in FFN.
+
+        Args:
+            attention_index (list): index of Attention
+            attention_matmul_list (list): list of Attention and MatMul nodes
+            block_len (int): block length
+
+        Returns:
+            list: list of MatMul in FFN
+        """
+        ffn_matmul = []
+        for idx in range(len(attention_index)):
+            if idx != len(attention_index) - 1:
+                index = attention_index[idx + 1]
+                if index - 2 >= 0:
+                    ffn_matmul.append([attention_matmul_list[index - 2], attention_matmul_list[index - 1]])
+            else:
+                index = attention_index[idx]
+                if index + block_len - 1 < len(attention_matmul_list):
+                    ffn_matmul.append(
+                        [attention_matmul_list[index + block_len - 2], attention_matmul_list[index + block_len - 1]]
+                    )
+        return ffn_matmul
+
+    def export(self, save_path, conf):
+        """Export Qlinear to QDQ model."""
+        from neural_compressor.config import ONNXQlinear2QDQConfig  # noqa: PLC0415
+        from neural_compressor.utils.export import onnx_qlinear_to_qdq  # noqa: PLC0415
+
+        if isinstance(conf, ONNXQlinear2QDQConfig):
+            add_nodes, remove_nodes, inits = onnx_qlinear_to_qdq(self._model, self._input_name_to_nodes)
+            self.add_nodes(add_nodes)
+            self.remove_nodes(remove_nodes)
+            self.add_initializers(inits)
+            self.update()
+            self.remove_unused_nodes()
+            self.topological_sort()
+            self.save(save_path)
+        else:
+            logger.warning("Unsupported config for export, only ONNXQlinear2QDQConfig is supported!")
+            exit(0)
+
+    def add_tensors_to_outputs(self, tensor_names):
+        """Add the tensors to the model outputs to gets their values.
+
+        Args:
+            tensor_names: The names of tensors to be dumped.
+        """
+        added_outputs = []
+        for tensor in tensor_names:
+            if tensor not in self.output():
+                added_tensor = onnx.helper.ValueInfoProto()
+                added_tensor.name = tensor
+                added_outputs.append(added_tensor)
+        self._model.graph.output.extend(added_outputs)  # pylint: disable=no-member
+
+    def remove_tensors_from_outputs(self, tensor_names):
+        """Remove the tensors from the model outputs.
+
+        Args:
+            tensor_names: The names of tensors to be removed.
+        """
+        removed_outputs = []
+        for tensor in tensor_names:
+            if tensor in self.output():
+                removed_outputs.append(self._model.graph.output[self.output().index(tensor)])
+        for output in removed_outputs:
+            self._model.graph.output.remove(output)
+
+    def match_first_parent(self, node, parent_op_type, output_name_to_node, exclude=None):
+        """Find parent node based on constraints on op_type.
+
+        Args:
+            node (str): current node name.
+            parent_op_type (str): constraint of parent node op_type.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+
+        Returns:
+            parent: The matched parent node. None if not found.
+            index: The input index of matched parent node. None if not found.
+        """
+        if exclude is None:
+            exclude = []
+        for i, input in enumerate(node.input):
+            if input in output_name_to_node:
+                parent = output_name_to_node[input]
+                if parent.op_type == parent_op_type and parent not in exclude:
+                    return parent, i
+        return None, None
+
+    def match_parent(
+        self,
+        node,
+        parent_op_type,
+        input_index=None,
+        output_name_to_node=None,
+        exclude=None,
+        return_indice=None,
+    ):
+        """Find parent node based on constraints on op_type and index.
+
+        Args:
+            node (str): current node name.
+            parent_op_type (str): constraint of parent node op_type.
+            input_index (int or None): only check the parent given input index of current node.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+            return_indice (list): a list to append the input index when input_index is None.
+
+        Returns:
+            parent: The matched parent node.
+        """
+        assert node is not None
+        assert input_index is None or input_index >= 0
+        if exclude is None:
+            exclude = []
+        if output_name_to_node is None:
+            output_name_to_node = self._output_name_to_node
+
+        if input_index is None:
+            parent, index = self.match_first_parent(node, parent_op_type, output_name_to_node, exclude)
+            if return_indice is not None:
+                return_indice.append(index)
+            return parent
+
+        if input_index >= len(node.input):
+            return None
+
+        parent = self.get_parent(node, input_index, output_name_to_node)
+        if parent is not None and parent.op_type == parent_op_type and parent not in exclude:
+            return parent
+
+        return None
+
+    def match_parent_path(
+        self,
+        node,
+        parent_op_types,
+        parent_input_index,
+        output_name_to_node=None,
+        return_indice=None,
+    ):
+        """Find a sequence of input edges based on constraints on parent op_type and index.
+
+        Args:
+            node (str): current node name.
+            parent_op_types (str): constraint of parent node op_type of each input edge.
+            parent_input_index (list): constraint of input index of each input edge.
+                                       None means no constraint.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            return_indice (list): a list to append the input index when there is
+                                  no constraint on input index of an edge.
+
+        Returns:
+            parents: a list of matched parent node.
+        """
+        assert len(parent_input_index) == len(parent_op_types)
+
+        if output_name_to_node is None:
+            output_name_to_node = self._output_name_to_node
+
+        current_node = node
+        matched_parents = []
+        for i, op_type in enumerate(parent_op_types):
+            matched_parent = self.match_parent(
+                current_node,
+                op_type,
+                parent_input_index[i],
+                output_name_to_node,
+                exclude=[],
+                return_indice=return_indice,
+            )
+            if matched_parent is None:
+                return None
+
+            matched_parents.append(matched_parent)
+            current_node = matched_parent
+
+        return matched_parents
+
+    def is_smoothquant_model(self):
+        """Check the model is smooth quantized or not.
+
+        Returns:
+            bool: the model is smooth quantized or not.
+        """
+        for init in self.model.graph.initializer:  # noqa: SIM110
+            if "_smooth_scale" in init.name:
+                return True
+        return False
+
+    def find_split_nodes(self):
+        """Find split nodes for layer-wise quantization."""
+        split_nodes = self.find_split_node_for_layer_wise_quantization()
+        return split_nodes
+
+    def split_model_with_node(
+        self, split_node_name, path_of_model_to_split, shape_infer=True, save_both_split_models=True
+    ):
+        """Split model into two parts at a given node.
+
+        Args:
+            split_node_name (str): name of the node where the model is split at>
+            path_of_model_to_split (str): path of model to be split.
+            shape_infer (bool): do shape inference. Default is True.
+            save_both_split_models (bool): whether to save the two split models.
+                False means only save the first split model.
+                True means save both the two split models.
+                Default id True.
+
+        Returns:
+            tuple: the first split model, the second split model
+        """
+        # origin model : ... -> node_1 -> split_node -> node_2 -> ...
+        # split model 1: ... -> node_1 -> split_node
+        # split model 2: node_2 -> ...
+
+        split_model_part_1 = onnx.ModelProto()
+        split_model_part_1.CopyFrom(self._model)
+        split_model_part_1.graph.ClearField("node")
+
+        split_model_part_2 = onnx.ModelProto()
+        split_model_part_2.CopyFrom(self._model)
+        split_model_part_2.graph.ClearField("node")
+
+        split_node_output = None
+        part_idx = 1
+        for node in self._model.graph.node:
+            if part_idx == 1:
+                split_model_part_1.graph.node.append(node)
+            elif part_idx == 2:
+                split_model_part_2.graph.node.append(node)
+
+            if node.name == split_node_name:
+                split_node_output = node.output
+                part_idx = 2
+
+        assert len(split_node_output) == 1, (
+            f"Only support split at node with 1 output tensor, while current split node {split_node_name} has {len(split_node_output)} output tensors"
+        )
+        split_tensor_name = split_node_output[0]
+
+        # infer shape of the model to be split
+        if shape_infer:
+            try:
+                from neural_compressor.adaptor.ox_utils.util import infer_shapes  # noqa: PLC0415
+
+                self._model = infer_shapes(self._model, auto_merge=True, base_dir=os.path.dirname(self._model_path))
+            except Exception as e:  # pragma: no cover
+                logger.error(
+                    "Shape infer fails for layer-wise quantization. "
+                    "We would recommend checking the graph optimization level of your model "
+                    "and setting it to 'DISABLE_ALL' or 'ENABLE_BASIC', "
+                    "as this may help avoid this error."
+                )
+                raise e
+
+        split_tensor_type, split_tensor_shape = self._get_output_type_shape_by_tensor_name(split_tensor_name)
+        split_tensor = onnx.helper.make_tensor_value_info(split_tensor_name, split_tensor_type, split_tensor_shape)
+
+        split_model_part_1 = ONNXModel(split_model_part_1, ignore_warning=True)
+        split_model_part_2 = ONNXModel(split_model_part_2, ignore_warning=True)
+
+        # remove unused input & output
+        split_model_part_1._remove_unused_input_output()
+        split_model_part_2._remove_unused_input_output()
+
+        split_model_part_1.model.graph.output.append(split_tensor)
+        split_model_part_2.model.graph.input.append(split_tensor)
+
+        insert_output_for_model_1 = []
+        insert_input_for_model_2 = []
+        for output in split_model_part_1.output_name_to_node:
+            if output in split_model_part_2.input_name_to_nodes:
+                output_type, output_shape = self._get_output_type_shape_by_tensor_name(output)
+                output_tensor = onnx.helper.make_tensor_value_info(output, output_type, output_shape)
+                if output_tensor not in split_model_part_1.model.graph.output:
+                    insert_output_for_model_1.append(output_tensor)
+                if output_tensor not in split_model_part_2.model.graph.input:
+                    insert_input_for_model_2.append(output_tensor)
+
+        # insert model 1 output
+        for output in insert_output_for_model_1:
+            split_model_part_1.model.graph.output.append(output)
+
+        # insert model 2 input
+        for input in insert_input_for_model_2:
+            split_model_part_2.model.graph.input.append(input)
+
+        # remove unused init
+        split_model_part_1.remove_unused_init()
+        split_model_part_2.remove_unused_init()
+
+        split_model_part_1.update()
+        split_model_part_2.update()
+
+        dir_of_model_to_split = os.path.dirname(path_of_model_to_split)
+
+        split_model_part_1.load_model_initializer_by_tensor(dir_of_model_to_split)
+        split_model_part_1_path = os.path.join(dir_of_model_to_split, "split_model_part_1.onnx")
+        split_model_part_1.model_path = split_model_part_1_path
+        split_model_part_1._save_split_model(split_model_part_1_path)
+        split_model_part_1.check_is_large_model()
+        logger.debug(f"save split model part 1 to {split_model_part_1_path} for layer wise quantization")
+
+        if save_both_split_models:
+            split_model_part_2.load_model_initializer_by_tensor(dir_of_model_to_split)
+            split_model_part_2_path = os.path.join(dir_of_model_to_split, "split_model_part_2.onnx")
+            split_model_part_2.model_path = split_model_part_2_path
+            split_model_part_2._save_split_model(split_model_part_2_path)
+            split_model_part_2.check_is_large_model()
+            logger.debug(f"save split model part 2 to {split_model_part_2_path} for layer wise quantization")
+            return split_model_part_1, split_model_part_2
+        else:
+            return split_model_part_1, split_model_part_2
+
+    def _save_split_model(self, save_path):
+        """Save split model as external data for layer wise quantization.
+
+        Args:
+            save_path (str): the path to save the split model
+        """
+        if os.path.exists(save_path + "_data"):
+            os.remove(save_path + "_data")
+        onnx.save_model(
+            self._model,
+            save_path,
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            location=save_path.split("/")[-1] + "_data",
+            size_threshold=1024,
+            convert_attribute=False,
+        )
+
+    def _get_output_type_shape_by_tensor_name(self, tensor_name):
+        """Get output type and shape with a tensor name.
+
+        Args:
+            tensor_name (str): name of a tensor
+
+        Returns:
+            tuple: output type and shape
+        """
+        elem_type = onnx.TensorProto.FLOAT
+        shape = None
+        for output in self._model.graph.value_info:
+            if output.name == tensor_name:
+                elem_type = output.type.tensor_type.elem_type
+                shape = [
+                    dim.dim_value if dim.HasField("dim_value") else -1 for dim in output.type.tensor_type.shape.dim
+                ]
+                break
+        return elem_type, shape
+
+    def _remove_unused_input_output(self):
+        """Remove unused input & output for split model."""
+        remove_outputs = []
+        remove_inputs = []
+        for output in self._model.graph.output:
+            if output.name not in self.output_name_to_node:
+                remove_outputs.append(output)
+
+        for input in self._model.graph.input:
+            if input.name not in self.input_name_to_nodes:
+                remove_inputs.append(input)
+
+        for output in remove_outputs:
+            self._model.graph.output.remove(output)
+        for input in remove_inputs:
+            self._model.graph.input.remove(input)
+
+    def remove_unused_init(self):
+        """Remove unused init."""
+        remov_inits = []
+        for init in self._model.graph.initializer:
+            if init.name not in self.input_name_to_nodes:
+                remov_inits.append(init)
+        self.remove_initializers(remov_inits)
+
+    def load_model_initializer_by_tensor(self, data_path=None):
+        """Load model initializer by tensor.
+
+        Args:
+            data_path (str, optional): the directory of saved initializer. Defaults to None.
+        """
+        if data_path is None:
+            data_path = os.path.dirname(self._model_path)
+        for init in self._model.graph.initializer:
+            if init.HasField("data_location") and init.data_location == onnx.TensorProto.EXTERNAL:
+                onnx.external_data_helper.load_external_data_for_tensor(init, data_path)
+
+    def write_external_data_to_new_location(self, external_data_location="external.data", overwrite=False):
+        """Write external data of merged quantized model to new location to save memory.
+
+        Args:
+            external_data_location (str, optional): external data location of merged quantized model.
+                                                    Defaults to "external.data".
+            overwrite (bool, optional): if True, remove existed externa data. Defaults to False.
+        """
+        if overwrite and os.path.exists(os.path.join(os.path.dirname(self._model_path), external_data_location)):
+            os.remove(os.path.join(os.path.dirname(self._model_path), external_data_location))
+        self.load_model_initializer_by_tensor()
+        onnx.external_data_helper.convert_model_to_external_data(self._model, location=external_data_location)
+        # TODO : if init is already saved, skip write it
+        onnx.external_data_helper.write_external_data_tensors(self._model, filepath=os.path.dirname(self._model_path))
+
+    def merge_split_models(self, to_merge_model):
+        """Merge two split model into final model."""
+        to_merge_model.write_external_data_to_new_location()
+        self.add_nodes(list(to_merge_model.nodes()))
+        self.add_initializers(list(to_merge_model.initializer()))
+        self.update()
+
+        # add new output
+        for output in to_merge_model.graph().output:
+            if output.name not in self.output():
+                self._model.graph.output.append(output)
+
+        # remove unused output
+        remove_output = []
+        for output in self._model.graph.output:
+            if output.name in to_merge_model.input():
+                remove_output.append(output)
+        for output in remove_output:
+            self._model.graph.output.remove(output)
+
+        # add new input
+        for input in to_merge_model.graph().input:
+            if (
+                input.name not in self.input()
+                and input.name not in self.output()
+                and input.name not in self.output_name_to_node
+            ):
+                self._model.graph.input.append(input)
+
+    def re_org_output(self, origin_output):
+        """Re-org output of merged model for layer-wise quantization."""
+        outputs = {}
+        tmp_remove = []
+        for output in self._model.graph.output:
+            outputs[output.name] = output
+            tmp_remove.append(output)
+
+        for output in tmp_remove:
+            self._model.graph.output.remove(output)
+
+        for out_name in origin_output:
+            self._model.graph.output.append(outputs[out_name])
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/util.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/util.py
new file mode 100644
index 0000000000000000000000000000000000000000..341e13dc067c95a2eea667b9ea2b874da551e28a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/util.py
@@ -0,0 +1,80 @@
+#
+#  The implementation of this file is based on:
+# https://github.com/intel/neural-compressor/tree/master/neural_compressor
+#
+# Copyright (c) 2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Helper classes or functions for onnxrt adaptor."""
+
+import importlib
+import logging
+
+import numpy as np
+
+logger = logging.getLogger("neural_compressor")
+
+
+MAXIMUM_PROTOBUF = 2147483648
+
+
+def simple_progress_bar(total, i):
+    """Progress bar for cases where tqdm can't be used."""
+    progress = i / total
+    bar_length = 20
+    bar = "#" * int(bar_length * progress)
+    spaces = " " * (bar_length - len(bar))
+    percentage = progress * 100
+    print(f"\rProgress: [{bar}{spaces}] {percentage:.2f}%", end="")
+
+
+def find_by_name(name, item_list):
+    """Helper function to find item by name in a list."""
+    items = []
+    for item in item_list:
+        assert hasattr(item, "name"), f"{item} should have a 'name' attribute defined"  # pragma: no cover
+        if item.name == name:
+            items.append(item)
+    if len(items) > 0:
+        return items[0]
+    else:
+        return None
+
+
+def to_numpy(data):
+    """Convert to numpy ndarrays."""
+    import torch  # noqa: PLC0415
+
+    if not isinstance(data, np.ndarray):
+        if not importlib.util.find_spec("torch"):
+            logger.error(
+                "Please install torch to enable subsequent data type check and conversion, "
+                "or reorganize your data format to numpy array."
+            )
+            exit(0)
+        if isinstance(data, torch.Tensor):
+            if data.dtype is torch.bfloat16:  # pragma: no cover
+                return data.detach().cpu().to(torch.float32).numpy()
+            if data.dtype is torch.chalf:  # pragma: no cover
+                return data.detach().cpu().to(torch.cfloat).numpy()
+            return data.detach().cpu().numpy()
+        else:
+            try:
+                return np.array(data)
+            except Exception:
+                assert False, (  # noqa: B011
+                    f"The input data for onnx model is {type(data)}, which is not supported to convert to numpy ndarrays."
+                )
+    else:
+        return data
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/weight_only.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/weight_only.py
new file mode 100644
index 0000000000000000000000000000000000000000..080d77ad0871a70a5522e69d703a29210e50866b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/neural_compressor/weight_only.py
@@ -0,0 +1,932 @@
+#
+#  The implementation of this file is based on:
+# https://github.com/intel/neural-compressor/tree/master/neural_compressor
+#
+# Copyright (c) 2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# Modifications:
+# Add k-quant quantization method.
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+"""WeightOnly for onnxrt adaptor."""
+
+import copy
+import logging
+import os
+import sys
+
+import numpy as np
+import onnx
+from onnx import numpy_helper
+from onnx.helper import np_dtype_to_tensor_dtype
+
+import onnxruntime as ort
+
+from .onnx_model import ONNXModel
+from .util import simple_progress_bar
+
+logger = logging.getLogger("neural_compressor")
+
+
+def make_matmul_weight_only_node(
+    node,
+    weight_shape,
+    num_bits,
+    group_size,
+    k_blocks,
+    q_weight,
+    scale,
+    zero_point,
+    accuracy_level=0,
+):  # pragma: no cover
+    """Build MatMulNBits node.
+
+    Args:
+        node: original matmul node
+        weight_shape: original weight shape
+        num_bits (int): num_bits
+        group_size (int): how many elements share one scale/zp
+        k_blocks (int): block number
+        q_weight (array): quantized weight
+        scale (array): scale
+        zero_point (array): zero point
+        accuracy_level (int): accuracy level. Support 0 (unset), 1(fp32), 2(fp16), 3(bf16), or 4(int8).
+
+    Returns:
+        matmul_weight_only_node: MatMulNBits node
+        new_inits: initializers of the new node
+    """
+    blob_size = group_size * num_bits // 8
+    packed = np.zeros((q_weight.shape[0], blob_size), dtype="uint8")
+    q_weight_name = node.input[1] + f"_Q{num_bits!s}G{group_size!s}"
+    input_names = [node.input[0], q_weight_name]
+    new_inits = []
+    kwargs = {}
+
+    op_type = "MatMulNBits"
+
+    # pack quantized weight
+    if num_bits == 4:
+        q_weight_pairs = q_weight[:, ::2] | q_weight[:, 1::2] << 4
+        packed[:, :] = q_weight_pairs[:, :blob_size]
+    elif num_bits == 8:
+        packed = q_weight
+    else:
+        logger.error(f"MatMulNBits does not have kernel support for num_bits = {num_bits}.")
+
+    packed = np.reshape(packed, (-1, k_blocks, blob_size))
+
+    # build scale tensor
+    scale = np.reshape(scale, (-1, k_blocks))
+    assert scale.dtype == np.float32 or scale.dtype == np.float16
+    scale_tensor = onnx.helper.make_tensor(
+        name=node.input[1] + "_scale",
+        data_type=np_dtype_to_tensor_dtype(scale.dtype),
+        dims=scale.shape,
+        vals=scale.tobytes(),
+        raw=True,
+    )
+    input_names.append(scale_tensor.name)
+    new_inits.append(scale_tensor)
+
+    # build zero_point tensor
+    if zero_point is not None:
+        if num_bits == 8:
+            packed_zp = zero_point.astype("uint8")
+        elif num_bits == 4:
+            # For 4-bit case, the default zeros is 0x8. So it is 0x88 = 136 if we fill lower/higher 4 bits with 0x8.
+            packed_zp = np.full((zero_point.shape[0] + 1) // 2, 136, dtype="uint8")
+            # create an index array
+            idx = np.arange(zero_point.shape[0] // k_blocks * k_blocks).reshape(-1)
+            # separate odd and even indices
+            even_idx = idx[::2]
+            odd_idx = idx[1::2]
+            # vectorized operation for even and odd indices
+            packed_zp[even_idx // 2] = (packed_zp[even_idx // 2] & 0xF0) | zero_point[even_idx].ravel()
+            packed_zp[odd_idx // 2] = (packed_zp[odd_idx // 2] & 0x0F) | (zero_point[odd_idx].ravel() << 4)
+        else:
+            raise ValueError(f"MatMulNBits does not have kernel support for num_bits = {num_bits}.")
+
+        packed_zp = np.reshape(packed_zp, (weight_shape[1], -1))
+        zp_tensor = onnx.helper.make_tensor(
+            name=node.input[1] + "_zp", data_type=2, dims=packed_zp.shape, vals=packed_zp.tobytes(), raw=True
+        )
+        input_names.append(zp_tensor.name)
+        new_inits.append(zp_tensor)
+
+    # set kwargs
+    kwargs["K"] = weight_shape[0]
+    kwargs["N"] = weight_shape[1]
+    kwargs["bits"] = num_bits
+    kwargs["block_size"] = group_size
+    if accuracy_level > 0:
+        # require onnxruntime > 1.16.3
+        kwargs["accuracy_level"] = accuracy_level
+
+    q_weight_tensor = onnx.helper.make_tensor(
+        name=q_weight_name,
+        data_type=2,
+        dims=packed.shape,
+        vals=packed.tobytes(),
+        raw=True,
+    )
+    new_inits.append(q_weight_tensor)
+
+    matmul_weight_only_node = onnx.helper.make_node(
+        op_type,
+        inputs=input_names,
+        outputs=node.output,
+        name=node.name + "_Q" + str(num_bits) if node.name else "_Q" + str(num_bits),
+        domain="com.microsoft",
+        **kwargs,
+    )
+    return matmul_weight_only_node, new_inits
+
+
+def quant_tensor(data, num_bits=4, group_size=32, scheme="asym", dtype="int", ratio=1.0):
+    """Quantize tensor per group.
+
+    Args:
+        data : input weight
+        num_bits (int, optional): num_bits. Defaults to 4.
+        group_size (int, optional): how many elements share one scale/zp. Defaults to 4.
+        scheme (str, optional): quantization scheme. Defaults to "asym".
+        dtype (str, optional): data type. Defaults to "int".
+        ratio (float, optional): percentile of clip. Defaults to 1.0.
+
+    Returns:
+        output: quantized weight
+        scale: scale
+        zero_point: zero point
+    """
+    data = np.reshape(data, (-1, group_size))
+    if scheme == "asym" or dtype == "uint":
+        maxq = 2**num_bits - 1
+        minq = 0
+    elif scheme == "sym":
+        maxq = 2 ** (num_bits - 1) - 1 if num_bits != 1 else 0
+        minq = -(2 ** (num_bits - 1)) if num_bits != 1 else -1
+
+    rmin = np.min(data, axis=1, keepdims=True) * ratio
+    rmax = np.max(data, axis=1, keepdims=True) * ratio
+    if scheme == "sym":
+        max_range = np.maximum(np.abs(rmin), np.abs(rmax))
+        scale = np.ones(rmax.shape)
+        mask = max_range > 0
+        scale[mask] = (max_range[mask] * 2.0).astype(np.float64) / (maxq - minq)
+        zero_point = (
+            np.zeros(scale.shape) if dtype == "int" else np.ones(rmax.shape, dtype="uint8") * (1 << (num_bits - 1))
+        )
+    else:
+        scale = np.ones(rmax.shape)
+        scale[rmin != rmax] = np.array(
+            [float(i) / (maxq - minq) for i in (rmax - rmin)[rmin != rmax].flatten().tolist()]
+        )
+        zero_point = (
+            ((np.zeros(scale.shape) - rmin) / scale).round()
+            if dtype == "int"
+            else np.maximum(0, np.minimum(maxq, ((np.zeros(scale.shape) - rmin) / scale).round())).astype("uint8")
+        )
+
+    q_weight = np.empty_like(data, dtype=scale.dtype)
+    np.divide(data, scale, out=q_weight)
+    np.add(q_weight, zero_point, out=q_weight)
+    np.round(q_weight, out=q_weight)
+    np.clip(q_weight, minq, maxq, out=q_weight)
+
+    return q_weight, scale, zero_point
+
+
+def quant_tensor_k_quant_cpu(data, num_bits=4, group_size=32):
+    """Quantize tensor per group based on k quant.
+
+    Ref: https://github.com/ggml-org/llama.cpp/blob/64eda5deb9859e87a020e56bab5d2f9ca956f1de/ggml/src/ggml-quants.c
+
+    Args:
+        data : input weight
+        num_bits (int, optional): num_bits. Defaults to 4.
+        group_size (int, optional): how many elements share one scale/zp. Defaults to 32.
+
+    Returns:
+        output: quantized weight
+        scale: scale
+        zero_point: zero point
+    """
+    data = np.reshape(data, (-1, group_size)).astype(np.float32)  # nb = data.shape[0], (nb, group_size)
+    maxq = 2**num_bits - 1
+    minq = 0
+    sum_x2 = np.sum(data**2, axis=1, keepdims=True)  # (nb, 1)
+    av_x = np.sqrt(sum_x2 / group_size)  # (nb, 1)
+    weights = np.add(av_x, np.abs(data))  # (nb, group_size)
+    rmin = np.min(data, axis=1, keepdims=True)  # (nb, 1)
+    rmax = np.max(data, axis=1, keepdims=True)  # (nb, 1)
+    sum_w = np.sum(weights, axis=1, keepdims=True)  # (nb, 1)
+    sum_x = np.sum(weights * data, axis=1, keepdims=True)  # (nb, group_size)
+    iscale = np.ones(rmax.shape, dtype=data.dtype)  # (nb, 1)
+    mask = rmin != rmax
+    iscale[mask] = (maxq - minq) / (rmax[mask] - rmin[mask])
+    scale = 1 / iscale
+    quant_data = np.clip(np.round(iscale * (data - rmin)), minq, maxq)  # (nb, group_size)
+    diff = scale * quant_data + rmin - data  # (nb, group_size)
+    best_mad = np.sum(weights * diff**2, axis=1, keepdims=True)  # (nb, 1)
+    nstep = 20
+    rdelta = 0.1
+    # nstep * rdelta = -2 * rrmin, maxq - minq = 2**num_bits - 1
+    rrmin = -1
+    for is_ in range(nstep):
+        iscale_new = np.ones(rmax.shape, dtype=data.dtype)  # (nb, 1)
+        factor = np.array([rrmin + rdelta * is_ + maxq - minq]).astype(data.dtype)[0]
+        mask = rmin != rmax
+        iscale_new[mask] = factor / (rmax[mask] - rmin[mask])
+        quant_data_new = np.clip(np.round(iscale_new * (data - rmin)), minq, maxq)  # (nb, group_size)
+        mul_weights_quant_data_new = weights * quant_data_new
+        sum_l = np.sum(mul_weights_quant_data_new, axis=1, keepdims=True)  # (nb, 1)
+        sum_l2 = np.sum(mul_weights_quant_data_new * quant_data_new, axis=1, keepdims=True)  # (nb, 1)
+        sum_xl = np.sum(mul_weights_quant_data_new * data, axis=1, keepdims=True)  # (nb, 1)
+        D = np.subtract(sum_w * sum_l2, sum_l**2)  # noqa: N806
+
+        this_scale = (sum_w * sum_xl - sum_x * sum_l) / D  # (nb, 1)
+        this_min = (sum_l2 * sum_x - sum_l * sum_xl) / D  # (nb, 1)
+
+        diff = this_scale * quant_data_new + this_min - data  # (nb, group_size)
+        mad = np.sum(weights * diff**2, axis=1, keepdims=True)  # (nb, 1)
+
+        mad_1 = np.array(mad)
+        best_mad_1 = np.array(best_mad)
+        idx_to_replace = np.where(mad_1 < best_mad_1)[0]
+        quant_data[idx_to_replace, :] = quant_data_new[idx_to_replace, :]
+        best_mad[idx_to_replace] = mad[idx_to_replace]
+        scale[idx_to_replace] = this_scale[idx_to_replace]
+        rmin[idx_to_replace] = this_min[idx_to_replace]
+
+    zero_point = np.clip(((-rmin) / scale).round(), 0, maxq).astype("uint8")
+    scale = scale.astype(np.float64)
+    q_weight = np.empty_like(data, dtype=scale.dtype)
+    np.divide(data, scale, out=q_weight)
+    np.add(q_weight, zero_point, out=q_weight)
+    np.round(q_weight, out=q_weight)
+    np.clip(q_weight, minq, maxq, out=q_weight)
+
+    return q_weight, scale, zero_point
+
+
+def quant_tensor_k_quant_cuda(data, num_bits=4, group_size=32):
+    """Quantize tensor per group based on k quant.
+
+    Ref: https://github.com/ggml-org/llama.cpp/blob/64eda5deb9859e87a020e56bab5d2f9ca956f1de/ggml/src/ggml-quants.c
+
+    Args:
+        data : input weight
+        num_bits (int, optional): num_bits. Defaults to 4.
+        group_size (int, optional): how many elements share one scale/zp. Defaults to 4.
+
+    Returns:
+        output: quantized weight
+        scale: scale
+        zero_point: zero point
+    """
+    try:
+        import cupy as cp  # noqa: PLC0415
+        import torch  # noqa: PLC0415
+
+        if torch.cuda.is_available():
+            data = cp.asarray(data)
+            data = data.reshape((-1, group_size)).astype(cp.float32)  # nb = data.shape[0], (nb, group_size)
+            maxq = 2**num_bits - 1
+            minq = 0
+            sum_x2 = cp.sum(data**2, axis=1, keepdims=True)  # (nb, 1)
+            av_x = cp.sqrt(sum_x2 / group_size)  # (nb, 1)
+            weights = cp.add(av_x, cp.abs(data))  # (nb, group_size)
+            rmin = cp.min(data, axis=1, keepdims=True)  # (nb, 1)
+            rmax = cp.max(data, axis=1, keepdims=True)  # (nb, 1)
+            sum_w = cp.sum(weights, axis=1, keepdims=True)  # (nb, 1)
+            sum_x = cp.sum(weights * data, axis=1, keepdims=True)  # (nb, group_size)
+            iscale = cp.ones(rmax.shape, dtype=data.dtype)  # (nb, 1)
+            mask = rmin != rmax
+            iscale[mask] = (maxq - minq) / (rmax[mask] - rmin[mask])
+            scale = 1 / iscale
+            quant_data = cp.clip(cp.round(iscale * (data - rmin)), minq, maxq)  # (nb, group_size)
+            diff = scale * quant_data + rmin - data  # (nb, group_size)
+            best_mad = cp.sum(weights * diff**2, axis=1, keepdims=True)  # (nb, 1)
+            nstep = 20
+            rdelta = 0.1
+            rrmin = -1
+            for is_ in range(nstep):
+                iscale_new = cp.ones(rmax.shape, dtype=data.dtype)  # (nb, 1)
+                factor = cp.array([rrmin + rdelta * is_ + maxq - minq]).astype(data.dtype)[0]
+                mask = rmin != rmax
+                iscale_new[mask] = factor / (rmax[mask] - rmin[mask])
+                quant_data_new = cp.clip(cp.round(iscale_new * (data - rmin)), minq, maxq)  # (nb, group_size)
+                mul_weights_quant_data_new = weights * quant_data_new
+                sum_l = cp.sum(mul_weights_quant_data_new, axis=1, keepdims=True)  # (nb, 1)
+                sum_l2 = cp.sum(mul_weights_quant_data_new * quant_data_new, axis=1, keepdims=True)  # (nb, 1)
+                sum_xl = cp.sum(mul_weights_quant_data_new * data, axis=1, keepdims=True)  # (nb, 1)
+                D = cp.subtract(sum_w * sum_l2, sum_l**2)  # noqa: N806
+
+                this_scale = (sum_w * sum_xl - sum_x * sum_l) / D  # (nb, 1)
+                this_min = (sum_l2 * sum_x - sum_l * sum_xl) / D  # (nb, 1)
+
+                diff = this_scale * quant_data_new + this_min - data  # (nb, group_size)
+                mad = cp.sum(weights * diff**2, axis=1, keepdims=True)  # (nb, 1)
+
+                mad_1 = cp.array(mad)
+                best_mad_1 = cp.array(best_mad)
+                idx_to_replace = cp.where(mad_1 < best_mad_1)[0]
+                quant_data[idx_to_replace, :] = quant_data_new[idx_to_replace, :]
+                best_mad[idx_to_replace] = mad[idx_to_replace]
+                scale[idx_to_replace] = this_scale[idx_to_replace]
+                rmin[idx_to_replace] = this_min[idx_to_replace]
+
+            zero_point = cp.clip(((-rmin) / scale).round(), 0, maxq).astype("uint8")
+            scale = scale.astype(cp.float64)
+            q_weight = cp.empty_like(data, dtype=scale.dtype)
+            cp.divide(data, scale, out=q_weight)
+            cp.add(q_weight, zero_point, out=q_weight)
+            cp.round(q_weight, out=q_weight)
+            cp.clip(q_weight, minq, maxq, out=q_weight)
+
+            return q_weight.get(), scale.get(), zero_point.get()
+        else:
+            logger.warning(
+                "Try to use k-quant quantization on CUDA. However, CUDA is not available."
+                "Fall back to k-quant quantization on CPU."
+            )
+            return quant_tensor_k_quant_cpu(data, num_bits, group_size)
+    except ImportError:
+        logger.info(
+            "Now we are using k-quant quantization on cpu, which is time consuming."
+            "Please consider install cupy to speed up on CUDA. See https://cupy.dev/"
+            "Please also install torch to check CUDA availability."
+        )
+        return quant_tensor_k_quant_cpu(data, num_bits, group_size)
+
+
+def qdq_tensor(data, num_bits=4, group_size=32, scheme="asym", dtype="int", ratio=1.0):
+    """Quant dequant tensor per group.
+
+    Args:
+        data : input weight
+        num_bits (int, optional): num_bits. Defaults to 4.
+        group_size (int, optional): how many elements share one scale/zp. Defaults to 4.
+        scheme (str, optional): quantization scheme. Defaults to "asym".
+        dtype (str, optional): data type. Defaults to "int".
+        ratio (float, optional): percentile of clip. Defaults to 1.0.
+
+    Returns:
+        output: quant-dequant weight
+    """
+    org_shape = data.shape
+    weight, scale, zp = quant_tensor(data, num_bits, group_size, scheme, dtype, ratio)
+    return np.reshape(scale * (weight - zp), org_shape)
+
+
+def pad_tensor(weight, group_size, k_blocks):
+    """Pad tensor rowi so that it can be is divisible by group_size.
+
+    Args:
+        weight (array): weight
+        group_size (int): how many elements share one scale/zp
+        k_blocks (int): the number of block
+
+    Returns:
+        weight: paded weight
+    """
+    if group_size == -1:
+        return weight
+
+    org_w_shape = weight.shape
+    padded_rows = k_blocks * group_size
+    pad_len = padded_rows - org_w_shape[0]
+
+    if pad_len > 0:
+        weight = np.pad(weight, ((0, pad_len), (0, 0)), "constant")
+
+    return weight
+
+
+def rtn_quantize(
+    model,
+    weight_config={},  # noqa: B006
+    num_bits=4,
+    group_size=32,
+    scheme="asym",
+    ratios={},  # noqa: B006
+    accuracy_level=0,
+    providers=["CPUExecutionProvider"],  # noqa: B006
+    algorithm="k_quant",
+):
+    """Quant the model with round to nearst method.
+
+    Args:
+        model (ModelProto or ONNXModel): onnx model
+        weight_config (dict): quantization config
+                For example,
+                weight_config = {
+                    'fc2':
+                        {
+                            'bits': 4,
+                            'group_size': 32,
+                            'scheme': 'sym',
+                            'algorithm': 'RTN'
+                        }
+                }
+        num_bits (int, optional): num_bits. Default is 4.
+        group_size (int, optional): how many elements share one scale/zp. Default is 32.
+        scheme (str, optional): sym or asym. Defaults to "asym".
+        ratios (dict, optional): percentile of clip. Defaults to {}.
+        accuracy_level (int): accuracy level. Support 0 (unset),1(fp32), 2(fp16), 3(bf16), or 4(int8).
+        providers (list): providers to use
+
+    Returns:
+        model: fake quantized ONNXModel
+    """
+    model = ONNXModel(model)
+    base_dir = os.path.dirname(model.model_path) if model.model_path is not None else ""
+    new_nodes = []
+    remove_nodes = []
+    total_num = len([i for i in model.nodes() if i.op_type in ["MatMul"]])
+    curr_id = 0
+    for node in model.nodes():
+        if node.op_type in ["MatMul"]:
+            curr_id += 1
+            simple_progress_bar(total_num, curr_id)
+        if (
+            node.op_type in ["MatMul"]
+            and model.get_initializer(node.input[1]) is not None
+            and weight_config.get(node.name, {}) != "fp32"
+        ):
+            weight_tensor = model.get_initializer(node.input[1])
+            weight = numpy_helper.to_array(weight_tensor, base_dir=base_dir).copy()
+            if len(weight.shape) != 2:
+                continue
+
+            dtype = weight.dtype
+
+            if node.name in weight_config:
+                num_bits = weight_config[node.name]["bits"]
+                group_size = weight_config[node.name]["group_size"]
+                scheme = weight_config[node.name]["scheme"]
+
+            org_w_shape = weight.shape  # ic, oc
+            group_size = group_size if group_size != -1 else org_w_shape[0]
+
+            k_blocks = (org_w_shape[0] - 1) // group_size + 1
+            init_share_num = model.get_initializer_share_num(node.input[1])
+
+            weight = pad_tensor(weight, group_size, k_blocks)
+
+            satisfy_MatMulNBits_condition = num_bits == 4 or num_bits == 8  # noqa: N806
+
+            if satisfy_MatMulNBits_condition:  # pragma: no cover
+                if algorithm == "k_quant":
+                    q_weight, scale, zp = quant_tensor_k_quant_cuda(weight.T, num_bits, group_size)
+                else:
+                    q_weight, scale, zp = quant_tensor(
+                        weight.T, num_bits, group_size, scheme, "uint", ratios.get(node.input[1], 1)
+                    )
+
+                q_matmul_node, new_inits = make_matmul_weight_only_node(
+                    node=node,
+                    weight_shape=org_w_shape,
+                    num_bits=num_bits,
+                    group_size=group_size,
+                    k_blocks=k_blocks,
+                    q_weight=q_weight.astype("uint8"),
+                    scale=scale.astype(dtype),
+                    zero_point=zp if scheme == "asym" or algorithm == "k_quant" else None,
+                    accuracy_level=accuracy_level,
+                )
+
+                model.add_initializers(new_inits)
+                remove_nodes.append(node)
+                new_nodes.append(q_matmul_node)
+            else:
+                q_weight = qdq_tensor(weight.T, num_bits, group_size, scheme, "int", ratios.get(node.input[1], 1))
+                q_weight = np.reshape(q_weight, (org_w_shape[1], -1))
+                q_weight = np.transpose(q_weight)
+                q_weight = q_weight[: org_w_shape[0], :].astype(dtype)
+                q_weight_tensor = onnx.helper.make_tensor(
+                    name=node.input[1] + f"_Q{num_bits!s}G{group_size!s}",
+                    data_type=np_dtype_to_tensor_dtype(dtype),
+                    dims=weight.shape,
+                    vals=q_weight.tobytes(),
+                    raw=True,
+                )
+                model.add_initializer(q_weight_tensor)
+                node.input[1] = q_weight_tensor.name
+            if init_share_num == 1:
+                model.remove_initializer(weight_tensor)
+
+    model.add_nodes(new_nodes)
+    model.remove_nodes(remove_nodes)
+    model.topological_sort()
+    return model
+
+
+def get_weight_scale(weight, group_size):
+    """Get the scale of weight."""
+    org_shape = weight.shape
+    weight = np.reshape(weight, (-1, group_size)) if group_size != -1 else weight
+    scale = np.mean(np.reshape(np.abs(weight) / np.max(np.abs(weight), axis=1, keepdims=True), org_shape), axis=0)
+    return scale
+
+
+def prepare_inputs(model, n_samples, dataloader, providers):
+    """Prepare inputs for weight only quantization.
+
+    Args:
+        model (ModelProto or ONNXModel): onnx model
+        n_samples (int, optional): calibration sample number. -1 means all samples.
+        dataloader (object): dataloader for calibration.
+        providers (list): providers to use
+
+    Returns:
+        inputs: prepared inputs.
+        so: session options
+    """
+    from importlib.util import find_spec  # noqa: PLC0415
+
+    from .util import to_numpy  # noqa: PLC0415
+
+    so = ort.SessionOptions()
+    if sys.version_info < (3, 11) and find_spec("onnxruntime_extensions"):  # pragma: no cover
+        from onnxruntime_extensions import get_library_path  # noqa: PLC0415
+
+        so.register_custom_ops_library(get_library_path())
+    if model.is_large_model:
+        onnx.save_model(
+            model.model,
+            model.model_path + "_augment.onnx",
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            convert_attribute=False,
+        )
+
+    session = (
+        ort.InferenceSession(model.model.SerializeToString(), so, providers=providers)
+        if not model.is_large_model
+        else ort.InferenceSession(model.model_path + "_augment.onnx", so, providers=providers)
+    )
+    inputs_names = [i.name for i in session.get_inputs()]
+    del session
+
+    inputs = []
+    for i, data in enumerate(dataloader):
+        if n_samples != -1 and ((i + 1) * dataloader.batch_size) > n_samples:
+            break
+        if len(inputs_names) != 1 or isinstance(data[0], dict):
+            assert len(data[0]) == len(inputs_names), (
+                f"Input number mismatch, require {len(inputs_names)} but get {len(data[0])}"
+            )
+
+        if isinstance(data[0], dict):
+            inputs.append(dict([(name, to_numpy(inp_data)) for name, inp_data in data[0].items()]))  # noqa: C404
+        elif isinstance(data[0], np.ndarray):  # pragma: no cover
+            inputs.append(dict([(name, inp) for name, inp in zip(inputs_names, [data[0]], strict=False)]))  # noqa: C404
+        else:  # pragma: no cover
+            inputs.append(dict([(name, to_numpy(inp)) for name, inp in zip(inputs_names, data[0], strict=False)]))  # noqa: C404
+    return inputs, so
+
+
+def gptq(
+    W,
+    H,
+    num_bits=4,
+    group_size=32,
+    scheme="asym",
+    blocksize=128,
+    percdamp=0.01,
+    actorder=False,
+    mse=False,
+    perchannel=True,
+):
+    """Quant the weight with GPTQ method.
+
+    Args:
+        W (array): weight.
+        H (array): Hessian matrix.
+        num_bits (int, optional): num_bits. Default is 4.
+        group_size (int, optional): how many elements share one scale/zp. Default is 32.
+        scheme (str, optional): sym or asym. Defaults to "asym".
+        blocksize (int, optional): blocksize to quantize weight.
+        percdamp (float, optional): percent of the average Hessian diagonal to use for dampening.
+        actorder (bool, optional): whether rearrange Hessian matrix considering the diag's value.
+        mse (bool, optional): whether get scale and zero point with mse error.
+        perchannel (bool, optional): whether quantize weight per-channel.
+
+    Returns:
+        Q: fake quantized weight
+    """
+    maxq = 2**num_bits - 1
+    grid = 100
+    maxshrink = 0.8
+    norm = 2.4
+
+    def find_params(weight):
+        org_shape = weight.shape
+        # find zp, scale
+        if not perchannel:
+            weight = np.expand_dims(weight.flatten(), axis=1)
+        tmp = np.zeros(weight.shape[1])
+        xmin = np.minimum(np.min(weight, axis=0), tmp)
+        xmax = np.maximum(np.max(weight, axis=0), tmp)
+        if scheme == "sym":
+            xmax = np.maximum(np.abs(xmin), xmax)
+            tmp = xmin < 0
+            if np.any(tmp):
+                xmin[tmp] = -xmax[tmp]
+        tmp = (xmin == 0) & (xmax == 0)
+        xmin[tmp] = -1
+        xmax[tmp] = +1
+
+        scale = (xmax - xmin) / maxq
+        if scheme == "sym":
+            zero = np.ones(scale.shape) * (maxq + 1) / 2
+        else:
+            zero = np.round(-xmin / scale)
+        if mse:
+            best = np.ones([weight.shape[1]]) * float("inf")
+            for i in range(int(maxshrink * grid)):
+                p = 1 - i / grid
+                xmin1 = p * xmin
+                xmax1 = p * xmax
+                scale1 = (xmax1 - xmin1) / maxq
+                zero1 = np.round(-xmin1 / scale1) if scheme != "sym" else zero
+                q = np.clip(np.round(weight / scale1) + zero1, 0, maxq)
+                q -= weight
+                q = np.power(np.abs(q), norm)
+                err = np.sum(q, 0)
+                tmp = err < best
+                if np.any(tmp):
+                    best[tmp] = err[tmp]
+                    scale[tmp] = scale1[tmp]
+                    zero[tmp] = zero1[tmp]
+        if not perchannel:
+            tmp = org_shape[1]
+            scale = np.repeat(scale, tmp)
+            zero = np.repeat(zero, tmp)
+        shape = [-1] + [1] * (len(org_shape) - 1)
+        scale = np.reshape(scale, shape)
+        zero = np.reshape(zero, shape)
+        return scale, zero
+
+    shape = W.shape
+    scale, zp = find_params(W)
+    dead = np.diag(H) == 0
+    H[dead, dead] = 1
+    W[dead, :] = 0  # such channel makes no contribution to quantization computation
+
+    # rearrange considering the diag's value
+    if actorder:
+        perm = np.argsort(np.diag(H))[::-1]
+        W = W[perm, :]  # noqa: N806
+        H = H[perm, :][:, perm]  # noqa: N806
+    Losses = np.zeros_like(W)  # noqa: N806
+    Q = np.zeros_like(W)  # noqa: N806
+    damp = percdamp * np.mean(np.diag(H))
+    diag = np.arange(shape[0])
+    H[diag, diag] += damp  # add a average value of
+    H = np.linalg.cholesky(np.linalg.inv(H)).T  # noqa: N806
+    Hinv = H  # noqa: N806
+    for i1 in range(0, shape[0], blocksize):
+        i2 = min(i1 + blocksize, shape[0])
+        count = i2 - i1
+
+        W1 = copy.deepcopy(W[i1:i2, :])  # noqa: N806
+        Q1 = np.zeros_like(W1)  # noqa: N806
+        Err1 = np.zeros_like(W1)  # noqa: N806
+        Losses1 = np.zeros_like(W1)  # noqa: N806
+        Hinv1 = Hinv[i1:i2, i1:i2]  # noqa: N806
+
+        for i in range(count):  # within a block, channel wise
+            w = W1[i, :]
+            d = Hinv1[i, i]
+
+            if group_size != -1:
+                if (i1 + i) % group_size == 0:
+                    scale, zp = find_params(W[(i1 + i) : (i1 + i + group_size), :])
+
+            q = (scale * (np.clip(np.round(w[:, np.newaxis] / scale) + zp, 0, maxq) - zp)).flatten()
+            Q1[i, :] = q
+            Losses1[i, :] = (w - q) ** 2 / d**2
+
+            err1 = (w - q) / d
+            W1[i:, :] -= np.matmul(np.expand_dims(Hinv1[i:, i], axis=1), np.expand_dims(err1, axis=0))
+            Err1[i, :] = err1
+
+        Q[i1:i2, :] = Q1
+        Losses[i1:i2, :] = Losses1 / 2
+
+        W[i2:, :] -= np.matmul(Hinv[i2:, i1:i2], Err1)
+
+    if actorder:
+        invperm = np.argsort(perm)
+        Q = Q[invperm, :]  # noqa: N806
+
+    Q = np.reshape(Q, W.shape)  # noqa: N806
+    del W
+    return Q
+
+
+def gptq_quantize(
+    model,
+    dataloader,
+    weight_config={},  # noqa: B006
+    num_bits=4,
+    group_size=32,
+    scheme="asym",
+    n_samples=128,
+    percdamp=0.01,
+    blocksize=128,
+    actorder=False,
+    mse=False,
+    perchannel=True,
+    accuracy_level=0,
+    providers=["CPUExecutionProvider"],  # noqa: B006
+):
+    """Quant the model with GPTQ method.
+
+    Args:
+        model (ModelProto or ONNXModel): onnx model
+        dataloader (object): dataloader for calibration.
+        weight_config (dict): quantization config
+                For example,
+                weight_config = {
+                    'fc2':
+                        {
+                            'bits': 4,
+                            'group_size': 32,
+                            'scheme': 'sym',
+                            'algorithm': 'GPTQ'
+                        }
+                }
+        num_bits (int, optional): num_bits. Default is 4.
+        group_size (int, optional): how many elements share one scale/zp. Default is 32.
+        scheme (str, optional): sym or asym. Defaults to "asym".
+        n_samples (int, optional): calibration sample number.
+        percdamp (float, optional): percent of the average Hessian diagonal to use for dampening.
+        blocksize (int, optional): blocksize to quantize weight.
+        actorder (bool, optional): whether rearrange Hessian matrix considering the diag's value.
+        mse (bool, optional): whether get scale and zero point with mse error.
+        perchannel (bool, optional): whether quantize weight per-channel.
+        accuracy_level (int): accuracy level. Support 0 (unset), 1(fp32), 2(fp16), 3(bf16), or 4(int8).
+        providers (list): providers to use
+
+    Returns:
+        model: fake quantized ONNXModel
+    """
+    model = ONNXModel(model)
+    base_dir = os.path.dirname(model.model_path) if model.model_path is not None else ""
+
+    inputs, so = prepare_inputs(model, n_samples, dataloader, providers)
+    del dataloader
+    org_output = copy.deepcopy(model.model.graph.output)
+    model.remove_tensors_from_outputs([i.name for i in org_output])
+    output_names = []
+    for node in model.nodes():
+        if (
+            node.op_type in ["MatMul"]
+            and weight_config.get(node.name, {}) != "fp32"
+            and weight_config.get(node.name, {}).get("algorithm", "GPTQ") == "GPTQ"
+        ):
+            output_names.append(node.input[0])
+    output_names = list(set(output_names))
+    model.add_tensors_to_outputs(output_names)
+    if model.is_large_model:
+        onnx.save_model(
+            model.model,
+            model.model_path + "_augment.onnx",
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            convert_attribute=False,
+        )
+
+    session = (
+        ort.InferenceSession(model.model.SerializeToString(), so, providers=providers)
+        if not model.is_large_model
+        else ort.InferenceSession(model.model_path + "_augment.onnx", so, providers=providers)
+    )
+
+    for idx, input_name in enumerate(output_names):
+        simple_progress_bar(len(output_names), idx + 1)
+        node_list = []
+        weights = []
+
+        for node in model.input_name_to_nodes[input_name]:
+            if (
+                node.op_type in ["MatMul"]
+                and weight_config.get(node.name, {}) != "fp32"
+                and weight_config.get(node.name, {}).get("algorithm", "GPTQ") == "GPTQ"
+                and model.get_initializer(node.input[1]) is not None
+            ):
+                weight = numpy_helper.to_array(
+                    model.get_initializer(model.get_node(node.name).input[1]), base_dir
+                ).copy()
+                if len(weight.shape) != 2:
+                    continue
+
+                weights.append(weight)
+                node_list.append(model.get_node(node.name))
+
+        if len(weights) == 0:
+            continue
+
+        Hs = [np.zeros((i.shape[0], i.shape[0])) for i in weights]  # noqa: N806
+        nsamples = 0
+        for data in inputs:
+            inp = session.run([input_name], data)[0]
+            tmp = inp.shape[0]
+            inp = np.reshape(inp, (-1, inp.shape[-1]))
+            Hs = [i * (nsamples / (nsamples + tmp)) for i in Hs]  # noqa: N806
+            nsamples += tmp
+            inp = np.sqrt(2 / nsamples) * inp
+            Hs = [i + np.matmul(inp.T, inp) for i in Hs]  # noqa: N806
+
+        for (
+            node,
+            weight,
+            H,  # noqa: N806
+        ) in zip(node_list, weights, Hs, strict=False):
+            if node.name in weight_config:
+                num_bits = weight_config[node.name]["bits"]
+                group_size = weight_config[node.name]["group_size"]
+                scheme = weight_config[node.name]["scheme"]
+            group_size = group_size if group_size != -1 else weight.shape[0]
+            dtype = weight.dtype
+
+            q_weight = gptq(
+                weight,
+                H,
+                num_bits=num_bits,
+                group_size=group_size,
+                scheme=scheme,
+                blocksize=blocksize,
+                percdamp=percdamp,
+                actorder=actorder,
+                mse=mse,
+                perchannel=perchannel,
+            )
+
+            weight_tensor = model.get_initializer(node.input[1])
+            init_share_num = model.get_initializer_share_num(node.input[1])
+
+            satisfy_MatMulNBits_condition = num_bits == 4  # noqa: N806
+
+            if satisfy_MatMulNBits_condition:  # pragma: no cover
+                org_shape = weight.shape
+                k_blocks = (org_shape[0] + group_size - 1) // group_size
+                q_weight = pad_tensor(q_weight, group_size, k_blocks)
+                q_weight, scale, zp = quant_tensor(q_weight.T, num_bits, group_size, scheme, "uint")
+                q_matmul_node, new_inits = make_matmul_weight_only_node(
+                    node=node,
+                    weight_shape=org_shape,
+                    num_bits=num_bits,
+                    group_size=group_size,
+                    k_blocks=k_blocks,
+                    q_weight=q_weight.astype("uint8"),
+                    scale=scale.astype(dtype),
+                    zero_point=zp if scheme == "asym" else None,
+                    accuracy_level=accuracy_level,
+                )
+
+                model.add_initializers(new_inits)
+                model.remove_node(node)
+                model.add_node(q_matmul_node)
+            else:
+                q_weight_tensor = onnx.helper.make_tensor(
+                    name=node.input[1] + f"_Q{num_bits!s}G{group_size!s}",
+                    data_type=np_dtype_to_tensor_dtype(dtype),
+                    dims=q_weight.shape,
+                    vals=q_weight.astype(dtype).tobytes(),
+                    raw=True,
+                )
+                model.add_initializer(q_weight_tensor)
+                node.input[1] = q_weight_tensor.name
+            if init_share_num == 1:
+                model.remove_initializer(weight_tensor)
+
+    model.remove_tensors_from_outputs(output_names)
+    model.model.graph.output.MergeFrom(org_output)
+
+    model.topological_sort()
+
+    # reload external data to prevent external data file path errors
+    if model.is_large_model:
+        from onnx.external_data_helper import load_external_data_for_model  # noqa: PLC0415
+
+        load_external_data_for_model(model.model, os.path.split(model.model_path)[0])
+
+    return model
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..52f9d0d0a02fce26760fe5f59da58edfadb5ca52
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/__init__.py
@@ -0,0 +1,2 @@
+# from .base_operator import QuantOperatorBase
+# from .matmul import MatMulInteger
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index 0000000000000000000000000000000000000000..05d2143524bf2c8d6a54f1f79f62ff2eec602433
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/activation.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/activation.py
new file mode 100644
index 0000000000000000000000000000000000000000..81927f0390414593cc550329f050c20dff407b50
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/activation.py
@@ -0,0 +1,119 @@
+import onnx
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QLinearActivation(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def QuantizeClipRelu(self):  # noqa: N802
+        node = self.node
+        assert node.op_type == "Relu" or node.op_type == "Clip"
+
+        # When mode is QLinearOps, the output quantization params are calculated based on outputs from
+        # activation nodes, therefore these nodes can be removed from the graph if they follow a quantized op.
+        # If input to this node is not quantized then keep this node
+        # If activation is symmetric, not quantize the op and simply return
+        if node.input[0] not in self.quantizer.quantized_value_map or self.quantizer.is_activation_symmetric:
+            return super().quantize()
+
+        quantized_value = self.quantizer.quantized_value_map[node.input[0]]
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_value
+
+    def quantize(self):
+        node = self.node
+        if node.op_type == "Relu" or node.op_type == "Clip":
+            self.QuantizeClipRelu()
+            return
+
+        nnapi_sigmoid_option = "extra.Sigmoid.nnapi"
+        sigmoid_nnapi_mode = (
+            node.op_type == "Sigmoid"
+            and nnapi_sigmoid_option in self.quantizer.extra_options
+            and self.quantizer.extra_options[nnapi_sigmoid_option]
+        )
+        use_scale = 1 / 256.0 if sigmoid_nnapi_mode else None
+        use_zeropoint = 0 if sigmoid_nnapi_mode else None
+
+        # No assert on op_type as it is controlled by registry
+        # only try to quantize when given quantization parameters for it
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0], use_scale, use_zeropoint)
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        qlinear_activation_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qlinear_activation_name = ""
+        if node.name:
+            qlinear_activation_name = node.name + "_quant"
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        qlinear_activation_inputs = [
+            quantized_input_names[0],
+            scale_names[0],
+            zero_point_names[0],
+            output_scale_name,
+            output_zp_name,
+        ]
+
+        qlinear_activation_node = onnx.helper.make_node(
+            "QLinear" + node.op_type,
+            qlinear_activation_inputs,
+            [qlinear_activation_output],
+            qlinear_activation_name,
+            **kwargs,
+        )
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            qlinear_activation_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        nodes.append(qlinear_activation_node)
+        self.quantizer.new_nodes += nodes
+
+
+class QDQRemovableActivation(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        # If input to this node is not quantized then keep this node
+        if not self.quantizer.is_tensor_quantized(node.input[0]):
+            return
+
+        if (
+            not self.quantizer.is_activation_symmetric
+            and not self.quantizer.qdq_keep_removable_activations
+            and self.quantizer.try_replacing_upstream_output(node.input[0], node.output[0])
+        ):
+            self.quantizer.remove_node(self.node)
+        else:
+            self.quantizer.quantize_activation_tensor(node.input[0])
+
+        if not self.disable_qdq_for_node_output:
+            self.quantizer.quantize_activation_tensor(node.output[0])
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/argmax.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/argmax.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a3484f867a59ddc1f02b6b8bb45118d244956b3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/argmax.py
@@ -0,0 +1,18 @@
+from .base_operator import QuantOperatorBase
+
+
+# Use the quantized tensor as input without DQ.
+class QArgMax(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        quantized_input_value = self.quantizer.find_quantized_value(node.input[0])
+        if quantized_input_value is None:
+            self.quantizer.new_nodes += [node]
+            return
+
+        node.input[0] = quantized_input_value.q_name
+        self.quantizer.new_nodes += [node]
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/attention.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/attention.py
new file mode 100644
index 0000000000000000000000000000000000000000..4220a4e15bc45161fc0f41a5331e9c39003ebbc2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/attention.py
@@ -0,0 +1,73 @@
+import onnx
+from onnx import onnx_pb as onnx_proto  # noqa: F401
+
+from ..quant_utils import attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+"""
+    Quantize Attention
+"""
+
+
+class AttentionQuant(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def should_quantize(self):
+        return self.quantizer.should_quantize_node(self.node)
+
+    def quantize(self):
+        """
+        parameter node: Attention node.
+        parameter new_nodes_list: List of new nodes created before processing this node.
+        return: a list of nodes in topological order that represents quantized Attention node.
+        """
+        node = self.node
+        assert node.op_type == "Attention"
+
+        # TODO This is a temporary fix to stop exporting QAttention with qkv_hidden_sizes
+        # attribute. This needs to be removed once the QAttention for varied q,k,v sizes
+        # is implemented
+        for attr in node.attribute:
+            if attr.name == "qkv_hidden_sizes":
+                return super().quantize()
+
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        (
+            quantized_input_names_weight,
+            zero_point_names_weight,
+            scale_names_weight,
+            nodes_weight,
+        ) = self.quantizer.quantize_weight(node, [1], reduce_range=True, op_level_per_channel=True)
+        quantized_input_names.extend(quantized_input_names_weight)
+        zero_point_names.extend(zero_point_names_weight)
+        scale_names.extend(scale_names_weight)
+        nodes.extend(nodes_weight)
+
+        if quantized_input_names is None:
+            return super().quantize()
+
+        qattention_name = "" if not node.name else node.name + "_quant"
+
+        inputs = []
+        inputs.extend(quantized_input_names)
+        inputs.extend([node.input[2]])
+        inputs.extend(scale_names)
+        inputs.extend([node.input[3] if len(node.input) > 3 else ""])
+        inputs.extend(zero_point_names)
+        inputs.extend([node.input[4] if len(node.input) > 4 else ""])
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        qattention_node = onnx.helper.make_node("QAttention", inputs, node.output, qattention_name, **kwargs)
+        nodes.append(qattention_node)
+
+        self.quantizer.new_nodes += nodes
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/base_operator.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/base_operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..e4895bd807a37a52fc8b1c465909575f3f7b25e2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/base_operator.py
@@ -0,0 +1,26 @@
+class QuantOperatorBase:
+    def __init__(self, onnx_quantizer, onnx_node):
+        self.quantizer = onnx_quantizer
+        self.node = onnx_node
+
+    def should_quantize(self):
+        if not self.quantizer.should_quantize_node(self.node):
+            return False
+
+        return self.quantizer.is_float_tensor(self.node.input[0])
+
+    def quantize(self):
+        """
+        Given a node which does not support quantization, this method checks whether the input to
+        this node is quantized and adds a DequantizeLinear node to dequantize this input back to FP32
+            parameter node: Current node
+            parameter new_nodes_list: List of new nodes created before processing current node
+            return: List of new nodes created
+        """
+        for _, node_input in enumerate(self.node.input):
+            dequantize_node = self.quantizer._dequantize_value(node_input)
+            if dequantize_node is not None:
+                self.quantizer.new_nodes.append(dequantize_node)
+
+        # Append the original node
+        self.quantizer.new_nodes.append(self.node)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/binary_op.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/binary_op.py
new file mode 100644
index 0000000000000000000000000000000000000000..85da759750b41d722c26645999294ef46c3a4773
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/binary_op.py
@@ -0,0 +1,72 @@
+import onnx
+from onnx import onnx_pb as onnx_proto  # noqa: F401
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+
+class QLinearBinaryOp(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0, 1])
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        qlinear_binary_math_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qlinear_binary_math_name = node.name + "_quant" if node.name else ""
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        qlinear_binary_math_inputs = []
+        # Input 0
+        qlinear_binary_math_inputs.append(quantized_input_names[0])
+        qlinear_binary_math_inputs.append(scale_names[0])
+        qlinear_binary_math_inputs.append(zero_point_names[0])
+        # Input 1
+        qlinear_binary_math_inputs.append(quantized_input_names[1])
+        qlinear_binary_math_inputs.append(scale_names[1])
+        qlinear_binary_math_inputs.append(zero_point_names[1])
+
+        # Output
+        qlinear_binary_math_inputs.append(output_scale_name)
+        qlinear_binary_math_inputs.append(output_zp_name)
+
+        qlinear_binary_math_node = onnx.helper.make_node(
+            "QLinear" + node.op_type,
+            qlinear_binary_math_inputs,
+            [qlinear_binary_math_output],
+            qlinear_binary_math_name,
+            **kwargs,
+        )
+        nodes.append(qlinear_binary_math_node)
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            qlinear_binary_math_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        self.quantizer.new_nodes += nodes
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/concat.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/concat.py
new file mode 100644
index 0000000000000000000000000000000000000000..523eef72018209d8aad07e9bebddd2284fb82297
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/concat.py
@@ -0,0 +1,62 @@
+import onnx
+
+from ..quant_utils import (  # noqa: F401
+    TENSOR_NAME_QUANT_SUFFIX,
+    QuantizedValue,
+    QuantizedValueType,
+    attribute_to_kwarg,
+    ms_domain,
+)
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase  # noqa: F401
+
+
+class QLinearConcat(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        (
+            q_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [*range(len(node.input))])
+        if not data_found or q_input_names is None:
+            return super().quantize()
+
+        # Create an entry for output quantized value
+        quantized_input_value = self.quantizer.quantized_value_map[node.input[0]]
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+            output_scale_name,
+            output_zp_name,
+            quantized_input_value.value_type,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        qnode_name = node.name + "_quant" if node.name else ""
+
+        qlconcat_inputs = [output_scale_name, output_zp_name]
+        for i in range(len(q_input_names)):
+            qlconcat_inputs.extend([q_input_names[i], scale_names[i], zero_point_names[i]])
+        qlconcat_node = onnx.helper.make_node(
+            "QLinearConcat", qlconcat_inputs, [quantized_output_value.q_name], qnode_name, **kwargs
+        )
+
+        self.quantizer.new_nodes += nodes
+        self.quantizer.new_nodes += [qlconcat_node]
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/conv.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/conv.py
new file mode 100644
index 0000000000000000000000000000000000000000..61b5e37c66823ea9d8ac448a0233567d43c0d722
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/conv.py
@@ -0,0 +1,260 @@
+import numpy as np
+import onnx
+from onnx import onnx_pb as onnx_proto
+
+from ..quant_utils import (
+    TENSOR_NAME_QUANT_SUFFIX,
+    QuantizedValue,
+    QuantizedValueType,
+    attribute_to_kwarg,
+    find_by_name,
+    get_mul_node,
+)
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class ConvInteger(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def add_bias(self, nodes, scaled_output):
+        """
+        Given a node, this function handles bias add by adding a "reshape" node on bias and an "add" node
+            parameter nodes: new nodes would be appended into nodes
+            parameter node: current node (Conv)
+            parameter scaled_output: output of quant conv without bias
+            parameter output: output of Conv
+            parameter bias_name: bias of Conv
+            return: the name of output
+        """
+        node = self.node
+        model = self.quantizer.model
+        # Add tensors for the shape to be reshaped to
+        weight = find_by_name(node.input[1], model.initializer())
+        if weight is None:
+            raise ValueError(f"Expected {node.input[1]} to be an initializer")
+
+        # Add reshape for correct broadcase
+        output = node.output[0]
+        reshape_input_data = node.input[2]  # bias of Conv
+        reshape_input_shape = output + "_bias_reshape_shape"
+        reshape_output = output + "_bias_reshape_output"
+
+        shape = np.ones((len(weight.dims)), dtype=np.int64)
+        shape[1] = -1
+        init_shape = onnx.helper.make_tensor(
+            reshape_input_shape, onnx_proto.TensorProto.INT64, [len(weight.dims)], shape
+        )
+        model.add_initializer(init_shape)
+
+        reshape_node = onnx.helper.make_node("Reshape", [reshape_input_data, reshape_input_shape], [reshape_output])
+        nodes.append(reshape_node)
+
+        # Add an Add operation for bias
+        add_node = onnx.helper.make_node("Add", [scaled_output, reshape_output], [output], output + "_bias_add")
+        nodes.append(add_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Conv"
+        #  Get Quantized from both activation(input[0]) and weight(input[1])
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        (
+            quantized_input_names_weight,
+            zero_point_names_weight,
+            scale_names_weight,
+            nodes_weight,
+        ) = self.quantizer.quantize_weight(node, [1], reduce_range=self.quantizer.reduce_range)
+        quantized_input_names.extend(quantized_input_names_weight)
+        zero_point_names.extend(zero_point_names_weight)
+        scale_names.extend(scale_names_weight)
+        nodes.extend(nodes_weight)
+
+        conv_integer_output = node.output[0] + "_output_quantized"
+        conv_integer_name = node.name + "_quant" if node.name else ""
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        conv_integer_node = onnx.helper.make_node(
+            "ConvInteger", quantized_input_names + zero_point_names, [conv_integer_output], conv_integer_name, **kwargs
+        )
+        nodes.append(conv_integer_node)
+
+        # Add cast operation to cast convInteger output to float.
+        onnx_type = self.quantizer.get_tensor_type(node.output[0], mandatory=True)
+        cast_op_output = conv_integer_output + "_cast_output"
+        cast_node = onnx.helper.make_node(
+            "Cast",
+            [conv_integer_output],
+            [cast_op_output],
+            conv_integer_output + "_cast",
+            to=onnx_type,  # TODO: FLOAT ot FLOAT16
+        )
+        nodes.append(cast_node)
+
+        # Add mul operation to multiply scales of two inputs.
+        assert len(scale_names) == 2
+        if conv_integer_name:
+            scales_mul_op = conv_integer_name + "_scales_mul"
+        else:
+            scales_mul_op = scale_names[0] + "_" + scale_names[1] + "_mul"
+
+        scales_mul_node = find_by_name(scales_mul_op, self.quantizer.new_nodes)
+        if scales_mul_node is None:
+            scales_mul_node = get_mul_node(scale_names, scales_mul_op + ":0", scales_mul_op)
+            nodes.append(scales_mul_node)
+
+        scales_mul_op_output = scales_mul_node.output[0]
+
+        has_bias = len(node.input) == 3
+        scaled_output_name = node.output[0] if not has_bias else node.output[0] + "quant_scaled_output"
+
+        # Add mul operation to multiply mul_scales_op result with output of ConvInteger
+        # and make the output of this node the same as output of original conv node.
+        output_scale_mul_op = conv_integer_name + "_output_scale_mul" if conv_integer_name else ""
+        nodes.append(
+            get_mul_node(
+                [cast_op_output, scales_mul_op_output],
+                scaled_output_name,
+                output_scale_mul_op,
+            )
+        )
+
+        if has_bias:
+            self.add_bias(nodes, scaled_output_name)
+
+        self.quantizer.new_nodes += nodes
+
+
+class QLinearConv(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Conv"
+
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+
+        if self.quantizer.is_input_a_initializer(node.input[1]) and self.quantizer.is_per_channel():
+            (
+                quantized_input_names,
+                zero_point_names,
+                scale_names,
+                nodes,
+            ) = self.quantizer.quantize_activation(node, [0])
+            quant_weight_tuple = self.quantizer.quantize_weight_per_channel(
+                node.input[1],
+                onnx_proto.TensorProto.INT8,
+                0,  # self.quantizer.weight_qType?
+            )
+            quantized_input_names.append(quant_weight_tuple[0])
+            zero_point_names.append(quant_weight_tuple[1])
+            scale_names.append(quant_weight_tuple[2])
+        else:
+            (
+                quantized_input_names,
+                zero_point_names,
+                scale_names,
+                nodes,
+            ) = self.quantizer.quantize_activation(node, [0])
+
+            (
+                quantized_input_names_weight,
+                zero_point_names_weight,
+                scale_names_weight,
+                nodes_weight,
+            ) = self.quantizer.quantize_weight(node, [1], reduce_range=self.quantizer.reduce_range)
+            quantized_input_names.extend(quantized_input_names_weight)
+            zero_point_names.extend(zero_point_names_weight)
+            scale_names.extend(scale_names_weight)
+            nodes.extend(nodes_weight)
+
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        quantized_bias_name = ""
+        bias_present = False
+        if len(node.input) == 3:
+            if self.quantizer.weight_qType == onnx_proto.TensorProto.FLOAT8E4M3FN:
+                raise RuntimeError("Quantization to FLOAT8E4M3FN for operator Conv is not supported.")
+            quantized_bias_name = self.quantizer.quantize_bias_static(node.input[2], node.input[0], node.input[1])
+            bias_present = True
+
+        qlinear_conv_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qlinear_conv_name = node.name + "_quant" if node.name else ""
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        qlinear_conv_inputs = []
+        # Input 0
+        qlinear_conv_inputs.append(quantized_input_names[0])
+        qlinear_conv_inputs.append(scale_names[0])
+        qlinear_conv_inputs.append(zero_point_names[0])
+        # Input 1
+        qlinear_conv_inputs.append(quantized_input_names[1])
+        qlinear_conv_inputs.append(scale_names[1])
+        qlinear_conv_inputs.append(zero_point_names[1])
+
+        # Output
+        qlinear_conv_inputs.append(output_scale_name)
+        qlinear_conv_inputs.append(output_zp_name)
+
+        if bias_present:
+            qlinear_conv_inputs.append(quantized_bias_name)
+
+        qlinear_conv_node = onnx.helper.make_node(
+            "QLinearConv", qlinear_conv_inputs, [qlinear_conv_output], qlinear_conv_name, **kwargs
+        )
+        nodes.append(qlinear_conv_node)
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            qlinear_conv_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        self.quantizer.new_nodes += nodes
+
+
+class QDQConv(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Conv" or node.op_type == "ConvTranspose"
+
+        self.quantizer.quantize_activation_tensor(node.input[0])
+        if not self.disable_qdq_for_node_output:
+            self.quantizer.quantize_activation_tensor(node.output[0])
+
+        is_weight_per_channel, weight_axis = self.quantizer.is_tensor_per_channel(
+            node.input[1], default_axis=0 if node.op_type == "Conv" else 1
+        )
+        if is_weight_per_channel:
+            self.quantizer.quantize_weight_tensor_per_channel(node.input[1], weight_axis)
+        else:
+            self.quantizer.quantize_weight_tensor(node.input[1])
+
+        if len(node.input) == 3:
+            self.quantizer.quantize_bias_tensor(node.name, node.input[2], node.input[0], node.input[1])
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/direct_q8.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/direct_q8.py
new file mode 100644
index 0000000000000000000000000000000000000000..33dcc8ac9b784736c76569610143f3f95866997c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/direct_q8.py
@@ -0,0 +1,78 @@
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+# For operators that support 8bits operations directly, and output could
+# reuse input[0]'s type, zeropoint, scale; For example,Transpose, Reshape, etc.
+class Direct8BitOp(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        if not self.quantizer.force_quantize_no_input_check:
+            # Keep backward compatibility
+            # Quantize when input[0] is quantized already. Otherwise keep it.
+            quantized_input_value = self.quantizer.find_quantized_value(node.input[0])
+            if quantized_input_value is None:
+                self.quantizer.new_nodes += [node]
+                return
+
+            quantized_output_value = QuantizedValue(
+                node.output[0],
+                node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+                quantized_input_value.scale_name,
+                quantized_input_value.zp_name,
+                quantized_input_value.value_type,
+            )
+            self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+            node.input[0] = quantized_input_value.q_name
+            node.output[0] = quantized_output_value.q_name
+            self.quantizer.new_nodes += [node]
+
+        else:
+            # Force quantize those ops if possible, use exclude node list if this is not you want
+            if not self.quantizer.is_valid_quantize_weight(node.input[0]):
+                super().quantize()
+                return
+
+            (
+                quantized_input_names,
+                zero_point_names,
+                scale_names,
+                nodes,
+            ) = self.quantizer.quantize_activation(node, [0])
+            if quantized_input_names is None:
+                return super().quantize()
+
+            # Create an entry for output quantized value
+            quantized_output_value = QuantizedValue(
+                node.output[0],
+                node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+                scale_names[0],
+                zero_point_names[0],
+                QuantizedValueType.Input,
+            )
+            self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+            node.input[0] = quantized_input_names[0]
+            node.output[0] = quantized_output_value.q_name
+            nodes.append(node)
+
+            self.quantizer.new_nodes += nodes
+
+
+class QDQDirect8BitOp(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        if self.quantizer.force_quantize_no_input_check:
+            self.quantizer.quantize_activation_tensor(self.node.input[0])
+            if not self.disable_qdq_for_node_output:
+                self.quantizer.quantize_output_same_as_input(self.node.output[0], self.node.input[0], self.node.name)
+        elif self.quantizer.is_tensor_quantized(self.node.input[0]) and not self.disable_qdq_for_node_output:
+            self.quantizer.quantize_output_same_as_input(self.node.output[0], self.node.input[0], self.node.name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/embed_layernorm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/embed_layernorm.py
new file mode 100644
index 0000000000000000000000000000000000000000..074cf2e72fbd5b2a2a2af6a8e007ef4484ecfa25
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/embed_layernorm.py
@@ -0,0 +1,121 @@
+import logging
+
+import onnx
+from onnx import onnx_pb as onnx_proto  # noqa: F401
+
+from ..quant_utils import attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+"""
+Quantizes the EmbedLayerNorm fused ONNXRuntime Op.
+
+This Quant operator keeps the input and segment IDs at int32 but will quantize all initializer and
+weight inputs associated with the node to uint8.
+"""
+
+
+class EmbedLayerNormalizationQuant(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def should_quantize(self):
+        return self.quantizer.should_quantize_node(self.node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "EmbedLayerNormalization"
+
+        if len(node.output) > 2:
+            logging.info(f"Quantization is not applied to {node.name} since it has 3 outputs")
+            return super().quantize()
+
+        """
+        Pre-quantization EmbedLayerNorm inputs:
+        [0] input_ids (int32)
+        [1] segment_ids (int32)
+        [2] word_embedding (float32)
+        [3] position_embedding (float32)
+        [4] segment_embedding (float32)
+        [5] gamma (float32)
+        [6] beta (float32)
+        [7] mask (int32) (optional)
+        """
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [2, 3, 4, 5, 6])
+        if quantized_input_names is None:
+            return super().quantize()
+
+        qembed_layer_norm_name = "" if not node.name else node.name + "_quant"
+
+        """
+        Quantized Input Tensor List
+        [0] input_ids (int32)
+        [1] segment_ids (int32)
+        [2] word_embedding (uint8)
+        [3] position_embedding (uint8)
+        [4] segment_embedding (uint8)
+        [5] gamma (uint8)
+        [6] beta (uint8)
+        [7] mask (int32) (optional)
+        [8] word_embedding_scale (float)
+        [9] position_embedding_scale (float)
+        [10] segment_embedding_scale (float)
+        [11] gamma_scale (float)
+        [12] beta_scale (float)
+        [13] word_embedding_zero_point (uint8)
+        [14] position_embedding_zero_point (uint8)
+        [15] segment_embedding_zero_point (uint8)
+        [16] gamma_zero_point (uint8)
+        [17] beta_zero_point (uint8)
+        """
+        inputs = []
+        # 'input_ids'
+        inputs.extend([node.input[0]])
+        # 'segment_ids'
+        inputs.extend([node.input[1]])
+        # 'word_embedding_quant'
+        inputs.extend([quantized_input_names[0]])
+        # 'position_embedding_quant'
+        inputs.extend([quantized_input_names[1]])
+        # 'segment_embedding_quant'
+        inputs.extend([quantized_input_names[2]])
+        # 'gamma_quant'
+        inputs.extend([quantized_input_names[3]])
+        # 'beta_quant'
+        inputs.extend([quantized_input_names[4]])
+        # 'mask' (optional)
+        inputs.extend([node.input[7] if len(node.input) > 7 else ""])
+
+        # Add all scales:
+        inputs.extend([scale_names[0]])
+        inputs.extend([scale_names[1]])
+        inputs.extend([scale_names[2]])
+        inputs.extend([scale_names[3]])
+        inputs.extend([scale_names[4]])
+
+        # Add all zero points:
+        inputs.extend([zero_point_names[0]])
+        inputs.extend([zero_point_names[1]])
+        inputs.extend([zero_point_names[2]])
+        inputs.extend([zero_point_names[3]])
+        inputs.extend([zero_point_names[4]])
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        qembed_layer_norm_node = onnx.helper.make_node(
+            "QEmbedLayerNormalization",
+            inputs,
+            node.output,
+            qembed_layer_norm_name,
+            **kwargs,
+        )
+        nodes.append(qembed_layer_norm_node)
+
+        self.quantizer.new_nodes += nodes
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gather.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gather.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b0e97c43bdf1220f6cb8bc3bd34306f131a1cae
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gather.py
@@ -0,0 +1,64 @@
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+"""
+    Quantize Gather
+"""
+
+
+class GatherQuant(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def should_quantize(self):
+        if not self.quantizer.should_quantize_node(self.node):
+            return False
+
+        return self.quantizer.is_valid_quantize_weight(self.node.input[0])
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Gather"
+
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+        if quantized_input_names is None:
+            return super().quantize()
+
+        gather_new_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            gather_new_output,
+            scale_names[0],
+            zero_point_names[0],
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        node.output[0] = gather_new_output
+        node.input[0] = quantized_input_names[0]
+        nodes.append(node)
+
+        self.quantizer.new_nodes += nodes
+
+
+class QDQGather(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Gather" or node.op_type == "GatherElements"
+
+        if self.quantizer.is_valid_quantize_weight(node.input[0]) or self.quantizer.force_quantize_no_input_check:
+            self.quantizer.quantize_activation_tensor(node.input[0])
+            self.quantizer.quantize_output_same_as_input(node.output[0], node.input[0], node.name)
+        elif self.quantizer.is_tensor_quantized(node.input[0]):
+            self.quantizer.quantize_output_same_as_input(node.output[0], node.input[0], node.name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gavgpool.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gavgpool.py
new file mode 100644
index 0000000000000000000000000000000000000000..49f139d74fe76790f280f0ab7c220a3527144422
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gavgpool.py
@@ -0,0 +1,62 @@
+import onnx
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+
+class QGlobalAveragePool(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "GlobalAveragePool"
+
+        # If input to this node is not quantized then keep this node.
+        if node.input[0] not in self.quantizer.quantized_value_map:
+            return super().quantize()
+
+        quantized_input_value = self.quantizer.quantized_value_map[node.input[0]]
+
+        # Create an entry for output quantized value.
+        quantized_input_value = self.quantizer.quantized_value_map[node.input[0]]
+        (
+            data_found,
+            output_scale_name_from_parameter,
+            output_zp_name_from_parameter,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        # Just use input scale and zp if parameters for output is not specified.
+        output_scale_name = output_scale_name_from_parameter if data_found else quantized_input_value.scale_name
+        output_zp_name = output_zp_name_from_parameter if data_found else quantized_input_value.zp_name
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        kwargs["channels_last"] = 0
+        qnode_name = node.name + "_quant" if node.name else ""
+
+        qnode = onnx.helper.make_node(
+            "QLinear" + node.op_type,
+            [
+                quantized_input_value.q_name,
+                quantized_input_value.scale_name,
+                quantized_input_value.zp_name,
+                output_scale_name,
+                output_zp_name,
+            ],
+            [quantized_output_value.q_name],
+            qnode_name,
+            **kwargs,
+        )
+        self.quantizer.new_nodes += [qnode]
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gemm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gemm.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4bd293af5e0afc9c99036213337635e86528cc7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/gemm.py
@@ -0,0 +1,172 @@
+import logging
+
+import numpy as np  # noqa: F401
+import onnx
+
+from ..quant_utils import (
+    TENSOR_NAME_QUANT_SUFFIX,
+    QuantizedValue,
+    QuantizedValueType,
+    attribute_to_kwarg,
+    find_by_name,  # noqa: F401
+    get_mul_node,  # noqa: F401
+    ms_domain,
+)
+from .base_operator import QuantOperatorBase  # noqa: F401
+from .matmul import QOpMatMul
+from .qdq_base_operator import QDQOperatorBase
+
+
+def is_B_transposed(gemm_node):  # noqa: N802
+    transB_attribute = [attr for attr in gemm_node.attribute if attr.name == "transB"]  # noqa: N806
+    if transB_attribute:
+        return onnx.helper.get_attribute_value(transB_attribute[0]) > 0
+
+    return False
+
+
+def get_beta(gemm_node):
+    beta_attribute = [attr for attr in gemm_node.attribute if attr.name == "beta"]
+    if beta_attribute:
+        return onnx.helper.get_attribute_value(beta_attribute[0])
+
+    return 1.0
+
+
+def set_default_beta(gemm_node):
+    beta_attribute = [attr for attr in gemm_node.attribute if attr.name == "beta"]
+    if beta_attribute:
+        beta_attribute[0].f = 1.0
+
+    return 1.0
+
+
+class QLinearGemm(QOpMatMul):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Gemm"
+
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+
+        if self.quantizer.is_input_a_initializer(node.input[1]) and self.quantizer.is_per_channel():
+            (
+                quantized_input_names,
+                zero_point_names,
+                scale_names,
+                nodes,
+            ) = self.quantizer.quantize_activation(node, [0])
+            quant_weight_tuple = self.quantizer.quantize_weight_per_channel(
+                node.input[1],
+                self.quantizer.weight_qType,
+                0 if is_B_transposed(node) else 1,
+            )
+            quantized_input_names.append(quant_weight_tuple[0])
+            zero_point_names.append(quant_weight_tuple[1])
+            scale_names.append(quant_weight_tuple[2])
+        else:
+            #  Get Quantized from both activation(input[0]) and weight(input[1])
+            (
+                quantized_input_names,
+                zero_point_names,
+                scale_names,
+                nodes,
+            ) = self.quantizer.quantize_activation(node, [0])
+
+            (
+                quantized_input_names_weight,
+                zero_point_names_weight,
+                scale_names_weight,
+                nodes_weight,
+            ) = self.quantizer.quantize_weight(node, [1], reduce_range=self.quantizer.reduce_range)
+            quantized_input_names.extend(quantized_input_names_weight)
+            zero_point_names.extend(zero_point_names_weight)
+            scale_names.extend(scale_names_weight)
+            nodes.extend(nodes_weight)
+
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        quantized_bias_name = ""
+        if len(node.input) == 3:
+            if not self.quantizer.is_input_a_initializer(node.input[2]):
+                return super().quantize()
+
+            # Note: if the quantized type is float 8, the bias is converted into float 16.
+            # cublasLtMatMul only supports (b)float16 or float32 bias.
+            quantized_bias_name = self.quantizer.quantize_bias_static(
+                node.input[2], node.input[0], node.input[1], get_beta(self.node)
+            )
+
+        qgemm_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qgemm_name = node.name + "_quant" if node.name else ""
+
+        kwargs = {}
+        for attribute in node.attribute:
+            if attribute.name != "beta":
+                kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        # generate input
+        qgemm_inputs = []
+        for i in range(2):
+            qgemm_inputs.extend([quantized_input_names[i], scale_names[i], zero_point_names[i]])
+
+        qgemm_inputs.extend([quantized_bias_name, output_scale_name, output_zp_name])
+
+        qgemm_node = onnx.helper.make_node("QGemm", qgemm_inputs, [qgemm_output], qgemm_name, **kwargs)
+        nodes.append(qgemm_node)
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            qgemm_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+            node_type=node.op_type,
+            node_qtype=self.quantizer.weight_qType,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        self.quantizer.new_nodes += nodes
+
+
+class QDQGemm(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Gemm"
+
+        self.quantizer.quantize_activation_tensor(node.input[0])
+        if not self.disable_qdq_for_node_output:
+            self.quantizer.quantize_activation_tensor(node.output[0])
+
+        is_weight_per_channel, weight_axis = self.quantizer.is_tensor_per_channel(
+            node.input[1], default_axis=0 if is_B_transposed(node) else 1
+        )
+        if is_weight_per_channel:
+            self.quantizer.quantize_weight_tensor_per_channel(node.input[1], weight_axis)
+        else:
+            self.quantizer.quantize_weight_tensor(node.input[1])
+
+        if len(node.input) == 3:
+            if self.quantizer.is_input_a_initializer(node.input[2]):
+                self.quantizer.quantize_bias_tensor(
+                    node.name, node.input[2], node.input[0], node.input[1], get_beta(self.node)
+                )
+                set_default_beta(self.node)
+            else:
+                logging.warning(
+                    f"Bias of Gemm node '{self.node.name}' is not constant. Please exclude this node for better performance."
+                )
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/lstm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/lstm.py
new file mode 100644
index 0000000000000000000000000000000000000000..1de80fc1ecd20e2a005e0abb1a3d2e934219f1ee
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/lstm.py
@@ -0,0 +1,121 @@
+import numpy
+import onnx
+from onnx import onnx_pb as onnx_proto
+
+from ..quant_utils import QuantType, attribute_to_kwarg, ms_domain  # noqa: F401
+from .base_operator import QuantOperatorBase
+
+"""
+    Quantize LSTM
+"""
+
+
+class LSTMQuant(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        """
+        parameter node: LSTM node.
+        parameter new_nodes_list: List of new nodes created before processing this node.
+        return: a list of nodes in topological order that represents quantized Attention node.
+        """
+        node = self.node
+        assert node.op_type == "LSTM"
+
+        if not self.quantizer.is_valid_quantize_weight(node.input[1]) or not self.quantizer.is_valid_quantize_weight(
+            node.input[2]
+        ):
+            super().quantize()
+            return
+
+        model = self.quantizer.model
+        W = model.get_initializer(node.input[1])  # noqa: N806
+        R = model.get_initializer(node.input[2])  # noqa: N806
+
+        if len(W.dims) != 3 or len(R.dims) != 3:
+            super().quantize()
+            return
+
+        [W_num_dir, W_4_hidden_size, W_input_size] = W.dims  # noqa: N806
+        [R_num_dir, R_4_hidden_size, R_hidden_size] = R.dims  # noqa: N806
+
+        if self.quantizer.is_per_channel():
+            del W.dims[0]
+            del R.dims[0]
+            W.dims[0] = W_num_dir * W_4_hidden_size
+            R.dims[0] = R_num_dir * R_4_hidden_size
+
+        quant_input_weight_tuple = self.quantizer.quantize_weight_per_channel(
+            node.input[1],
+            onnx_proto.TensorProto.INT8,
+            0,  # self.quantizer.weight_qType?
+        )
+        quant_recurrent_weight_tuple = self.quantizer.quantize_weight_per_channel(
+            node.input[2],
+            onnx_proto.TensorProto.INT8,
+            0,  # self.quantizer.weight_qType?
+        )
+
+        W_quant_weight = model.get_initializer(quant_input_weight_tuple[0])  # noqa: N806
+        R_quant_weight = model.get_initializer(quant_recurrent_weight_tuple[0])  # noqa: N806
+
+        W_quant_array = onnx.numpy_helper.to_array(W_quant_weight)  # noqa: N806
+        R_quant_array = onnx.numpy_helper.to_array(R_quant_weight)  # noqa: N806
+
+        W_quant_array = numpy.reshape(W_quant_array, (W_num_dir, W_4_hidden_size, W_input_size))  # noqa: N806
+        R_quant_array = numpy.reshape(R_quant_array, (R_num_dir, R_4_hidden_size, R_hidden_size))  # noqa: N806
+
+        W_quant_array = numpy.transpose(W_quant_array, (0, 2, 1))  # noqa: N806
+        R_quant_array = numpy.transpose(R_quant_array, (0, 2, 1))  # noqa: N806
+
+        W_quant_tranposed = onnx.numpy_helper.from_array(W_quant_array, quant_input_weight_tuple[0])  # noqa: N806
+        R_quant_tranposed = onnx.numpy_helper.from_array(R_quant_array, quant_recurrent_weight_tuple[0])  # noqa: N806
+
+        model.remove_initializers([W_quant_weight, R_quant_weight])
+        model.add_initializer(W_quant_tranposed)
+        model.add_initializer(R_quant_tranposed)
+
+        W_quant_zp = model.get_initializer(quant_input_weight_tuple[1])  # noqa: N806
+        R_quant_zp = model.get_initializer(quant_recurrent_weight_tuple[1])  # noqa: N806
+        W_quant_scale = model.get_initializer(quant_input_weight_tuple[2])  # noqa: N806
+        R_quant_scale = model.get_initializer(quant_recurrent_weight_tuple[2])  # noqa: N806
+
+        if self.quantizer.is_per_channel():
+            W_quant_zp.dims[:] = [W_num_dir, W_4_hidden_size]
+            R_quant_zp.dims[:] = [R_num_dir, R_4_hidden_size]
+            W_quant_scale.dims[:] = [W_num_dir, W_4_hidden_size]
+            R_quant_scale.dims[:] = [R_num_dir, R_4_hidden_size]
+
+        inputs = []
+        input_len = len(node.input)
+        inputs.extend([node.input[0]])
+        inputs.extend([quant_input_weight_tuple[0], quant_recurrent_weight_tuple[0]])
+        inputs.extend([node.input[3] if input_len > 3 else ""])
+        inputs.extend([node.input[4] if input_len > 4 else ""])
+        inputs.extend([node.input[5] if input_len > 5 else ""])
+        inputs.extend([node.input[6] if input_len > 6 else ""])
+        inputs.extend([node.input[7] if input_len > 7 else ""])
+        inputs.extend(
+            [
+                quant_input_weight_tuple[2],
+                quant_input_weight_tuple[1],
+                quant_recurrent_weight_tuple[2],
+                quant_recurrent_weight_tuple[1],
+            ]
+        )
+
+        kwargs = {}
+        for attribute in node.attribute:
+            if attribute.name == "layout":
+                continue
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        quant_lstm_name = "" if not node.name else node.name + "_quant"
+        quant_lstm_node = onnx.helper.make_node("DynamicQuantizeLSTM", inputs, node.output, quant_lstm_name, **kwargs)
+        self.quantizer.new_nodes.append(quant_lstm_node)
+
+        dequantize_node = self.quantizer._dequantize_value(node.input[0])
+        if dequantize_node is not None:
+            self.quantizer.new_nodes.append(dequantize_node)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/matmul.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/matmul.py
new file mode 100644
index 0000000000000000000000000000000000000000..591cb2bbdbf307225ed7a66fd9c9224a55895b01
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/matmul.py
@@ -0,0 +1,231 @@
+import itertools
+import logging
+
+import onnx
+from onnx import onnx_pb as onnx_proto
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, find_by_name, get_mul_node
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QOpMatMul(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def should_quantize(self):
+        if not self.quantizer.should_quantize_node(self.node):
+            logging.debug(f"Ignore MatMul {self.node.name}]")
+            return False
+
+        if (not self.quantizer.is_float_tensor(self.node.input[1])) and (
+            not self.quantizer.is_float_tensor(self.node.input[0])
+        ):
+            logging.info(f"Ignore MatMul due to non float inputs {self.node.name}]")
+            return False
+
+        # do not quantize non-constant B matrices for matmul
+        if self.quantizer.q_matmul_const_b_only:
+            if not self.quantizer.find_initializer_in_path(self.node.input[1]):
+                logging.info(f"Ignore MatMul due to non constant B: {self.quantizer.graph_scope}[{self.node.name}]")
+                return False
+        return True
+
+
+"""
+    Used when quantize mode is QuantizationMode.IntegerOps.
+"""
+
+
+class MatMulInteger(QOpMatMul):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "MatMul"
+        #  Get Quantized from both activation(input[0]) and weight(input[1])
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        (
+            quantized_input_names_weight,
+            zero_point_names_weight,
+            scale_names_weight,
+            nodes_weight,
+        ) = self.quantizer.quantize_weight(node, [1], reduce_range=True, op_level_per_channel=True)
+        quantized_input_names.extend(quantized_input_names_weight)
+        zero_point_names.extend(zero_point_names_weight)
+        scale_names.extend(scale_names_weight)
+        nodes.extend(nodes_weight)
+
+        matmul_integer_output = node.output[0] + "_output_quantized"
+        matmul_integer_name = node.name + "_quant" if node.name else ""
+        matmul_integer_node = onnx.helper.make_node(
+            "MatMulInteger",
+            quantized_input_names + zero_point_names,
+            [matmul_integer_output],
+            matmul_integer_name,
+        )
+        nodes.append(matmul_integer_node)
+
+        # Add cast operation to cast matmulInteger output to float.
+        cast_op_output = matmul_integer_output + "_cast_output"
+        otype = self.quantizer.get_tensor_type(node.output[0], mandatory=True)
+        cast_node = onnx.helper.make_node(
+            "Cast",
+            [matmul_integer_output],
+            [cast_op_output],
+            matmul_integer_output + "_cast",
+            to=otype,
+        )
+        nodes.append(cast_node)
+
+        # Add mul operation to multiply scales of two inputs.
+        assert len(scale_names) == 2
+        scales_mul_op = (
+            matmul_integer_name + "_scales_mul"
+            if matmul_integer_name
+            else scale_names[0] + "_" + scale_names[1] + "_mul"
+        )
+
+        scales_mul_node = find_by_name(scales_mul_op, self.quantizer.new_nodes)
+        if scales_mul_node is None:
+            scales_mul_node = get_mul_node(scale_names, scales_mul_op + ":0", scales_mul_op)
+            nodes.append(scales_mul_node)
+
+        scales_mul_op_output = scales_mul_node.output[0]
+
+        # Add mul operation to multiply mul_scales_op result with output of MatMulInteger
+        # and make the output of this node the same as output of original matmul node.
+        output_scale_mul_op = ""
+        if matmul_integer_name:
+            output_scale_mul_op = matmul_integer_name + "_output_scale_mul"
+        nodes.append(
+            get_mul_node(
+                [cast_op_output, scales_mul_op_output],
+                node.output[0],
+                output_scale_mul_op,
+            )
+        )
+        self.quantizer.new_nodes += nodes
+
+
+"""
+    Used when quantize mode is QuantizationMode.QLinearOps
+"""
+
+
+class QLinearMatMul(QOpMatMul):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "MatMul"
+        #  Get Quantized from both activation(input[0]) and weight(input[1])
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        (
+            quantized_input_names_weight,
+            zero_point_names_weight,
+            scale_names_weight,
+            nodes_weight,
+        ) = self.quantizer.quantize_weight(node, [1], reduce_range=True, op_level_per_channel=True)
+        quantized_input_names.extend(quantized_input_names_weight)
+        zero_point_names.extend(zero_point_names_weight)
+        scale_names.extend(scale_names_weight)
+
+        nodes.extend(nodes_weight)
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        qlinear_matmul_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qlinear_matmul_name = node.name + "_quant" if node.name else ""
+
+        qlinear_matmul_inputs = []
+        # Input 0
+        qlinear_matmul_inputs.append(quantized_input_names[0])
+        qlinear_matmul_inputs.append(scale_names[0])
+        qlinear_matmul_inputs.append(zero_point_names[0])
+        # Input 1
+        qlinear_matmul_inputs.append(quantized_input_names[1])
+        qlinear_matmul_inputs.append(scale_names[1])
+        qlinear_matmul_inputs.append(zero_point_names[1])
+        # Output quantization parameter
+        qlinear_matmul_inputs.append(output_scale_name)
+        qlinear_matmul_inputs.append(output_zp_name)
+
+        domain = (
+            "com.microsoft"
+            if self.quantizer.weight_qType
+            in {
+                onnx_proto.TensorProto.FLOAT8E4M3FN,
+                onnx_proto.TensorProto.FLOAT8E4M3FNUZ,
+                onnx_proto.TensorProto.FLOAT8E5M2,
+                onnx_proto.TensorProto.FLOAT8E5M2FNUZ,
+            }
+            else ""
+        )
+        qlinear_matmul_node = onnx.helper.make_node(
+            "QLinearMatMul",
+            qlinear_matmul_inputs,
+            [qlinear_matmul_output],
+            qlinear_matmul_name,
+            domain=domain,
+        )
+        nodes.append(qlinear_matmul_node)
+
+        # Create an entry for this quantized value
+        q_output = QuantizedValue(
+            node.output[0],
+            qlinear_matmul_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        self.quantizer.new_nodes += nodes
+
+
+class QDQMatMul(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "MatMul"
+
+        if self.disable_qdq_for_node_output:
+            nodes_to_iterate = node.input
+        else:
+            nodes_to_iterate = itertools.chain(node.input, node.output)
+
+        for tensor_name in nodes_to_iterate:
+            if find_by_name(tensor_name, self.quantizer.model.initializer()):
+                is_per_channel, channel_axis = self.quantizer.is_tensor_per_channel(
+                    tensor_name, default_axis=1, op_type=node.op_type
+                )
+                if is_per_channel:
+                    self.quantizer.quantize_weight_tensor_per_channel(tensor_name, channel_axis)
+                else:
+                    self.quantizer.quantize_weight_tensor(tensor_name)
+            else:
+                self.quantizer.quantize_activation_tensor(tensor_name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/maxpool.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/maxpool.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb689b0aa5d9e8395e2d32f75d57a84a21794074
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/maxpool.py
@@ -0,0 +1,34 @@
+from .direct_q8 import Direct8BitOp, QDQDirect8BitOp
+
+
+class QMaxPool(Direct8BitOp):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "MaxPool"
+
+        # if version is less than 12, go to normal quantize.
+        if self.quantizer.opset_version < 12:
+            super(Direct8BitOp, self).quantize()
+            return
+
+        # Direct 8bits op
+        return super().quantize()
+
+
+class QDQMaxPool(QDQDirect8BitOp):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "MaxPool"
+
+        # if version is less than 12, just no change
+        if self.quantizer.opset_version < 12:
+            return
+
+        # Direct 8bits op
+        return super().quantize()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/norm.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/norm.py
new file mode 100644
index 0000000000000000000000000000000000000000..d2b5147a61654a1a0e1b0ce63318939fd89c6733
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/norm.py
@@ -0,0 +1,40 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QDQNormalization(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type in {"InstanceNormalization", "LayerNormalization", "BatchNormalization"}
+
+        # Input
+        self.quantizer.quantize_activation_tensor(node.input[0])
+
+        # Scale
+        scale_is_initializer = self.quantizer.is_input_a_initializer(node.input[1])
+        scale_is_per_channel, scale_channel_axis = self.quantizer.is_tensor_per_channel(
+            node.input[1], default_axis=1, op_type=node.op_type
+        )
+
+        if scale_is_per_channel:
+            self.quantizer.quantize_weight_tensor_per_channel(node.input[1], axis=scale_channel_axis)
+        elif scale_is_initializer:
+            self.quantizer.quantize_weight_tensor(node.input[1])
+        else:
+            self.quantizer.quantize_activation_tensor(node.input[1])
+
+        # Bias
+        if len(node.input) > 2 and node.input[2]:
+            self.quantizer.quantize_bias_tensor(node.name, node.input[2], node.input[0], node.input[1])
+
+        # Output
+        if not self.disable_qdq_for_node_output:
+            for output_name in node.output:
+                self.quantizer.quantize_activation_tensor(output_name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pad.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pad.py
new file mode 100644
index 0000000000000000000000000000000000000000..2d5c8344a774c4814c23f2f4c379bbe80f1b5a3e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pad.py
@@ -0,0 +1,172 @@
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+from typing import Any
+
+import numpy as np
+import onnx
+
+from ..quant_utils import (
+    TENSOR_NAME_QUANT_SUFFIX,
+    QuantizedValue,
+    QuantizedValueType,
+    attribute_to_kwarg,
+    quantize_nparray,
+)
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QPad(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Pad"
+
+        # Only after version 11, it has the optional constant_value
+        # If input[0] is not quantized, do not quanitize this node
+        if (self.quantizer.opset_version < 11) or (node.input[0] not in self.quantizer.quantized_value_map):
+            super().quantize()
+            return
+        quantized_input_value = self.quantizer.quantized_value_map[node.input[0]]
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kv = attribute_to_kwarg(attribute)
+            kwargs.update(kv)
+
+        if "mode" not in kwargs or kwargs["mode"] == b"constant":
+            if len(node.input) > 2 and node.input[2] != "":  # There is 3rd input 'constant_value'
+                zp_tensor = self.quantizer.model.get_initializer(quantized_input_value.zp_name)
+                scale_tensor = self.quantizer.model.get_initializer(quantized_input_value.scale_name)
+                if zp_tensor is None or scale_tensor is None:
+                    super().quantize()
+                    return
+
+                padding_constant_initializer = self.quantizer.model.get_initializer(node.input[2])
+                if padding_constant_initializer is not None:
+                    zp_array = onnx.numpy_helper.to_array(zp_tensor)
+                    zp_value = zp_array.item() if zp_array.ndim == 0 else zp_array[0]
+                    scale_array = onnx.numpy_helper.to_array(scale_tensor)
+                    scale_value = scale_array.item() if scale_array.ndim == 0 else scale_array[0]
+                    padding_constant_array = onnx.numpy_helper.to_array(padding_constant_initializer)
+                    quantized_padding_constant_array = quantize_nparray(
+                        self.quantizer.activation_qType,
+                        padding_constant_array,
+                        scale_value,
+                        zp_value,
+                    )
+                    quantized_padding_constant_name = node.input[2] + TENSOR_NAME_QUANT_SUFFIX
+                    quantized_padding_constant_initializer = onnx.numpy_helper.from_array(
+                        quantized_padding_constant_array,
+                        quantized_padding_constant_name,
+                    )
+                    # Suppose this padding constant initializer only used by the node
+                    self.quantizer.model.remove_initializer(padding_constant_initializer)
+                    self.quantizer.model.add_initializer(quantized_padding_constant_initializer)
+                    node.input[2] = quantized_padding_constant_name
+                else:
+                    # TODO: check quantize_inputs after sub graph is supported
+                    pad_value_qnodes = self.quantizer._get_quantize_input_nodes(
+                        node,
+                        2,
+                        self.quantizer.activation_qType,
+                        quantized_input_value.scale_name,
+                        quantized_input_value.zp_name,
+                        initial_type=scale_tensor.data_type,
+                    )
+                    self.quantizer.new_nodes.extend(pad_value_qnodes)
+                    node.input[2] = pad_value_qnodes[0].output[0]
+            else:
+                # In quantized format, the `zero` before quantization is mapped
+                # to quantized_input_value.zp_name. Thus, padding 0 to
+                # original tensor should become padding zero point to quantized
+                # tensor.
+                if len(node.input) == 2:
+                    # Feed quantization's zero point to padding node.
+                    node.input.append(quantized_input_value.zp_name)
+                else:
+                    # Assign quantization's zero point to padding node.
+                    assert node.input[2] == ""
+                    node.input[2] = quantized_input_value.zp_name
+
+        # Create an entry for output quantized value
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            node.output[0] + TENSOR_NAME_QUANT_SUFFIX,
+            quantized_input_value.scale_name,
+            quantized_input_value.zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        node.input[0] = quantized_input_value.q_name
+        node.output[0] = quantized_output_value.q_name
+        self.quantizer.new_nodes += [node]
+
+
+class QDQPad(QDQOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def _get_pad_const_val(self, attrs_dict: dict[str, Any]) -> np.ndarray | None:
+        """
+        Returns the Pad's constant padding value. Returns `None` if the padding value is
+        not constant (i.e., comes from a dynamic input).
+        """
+        const_val = None
+        onnx_tensor_type = self.quantizer.model.get_tensor_type(self.node.input[0])
+        if onnx_tensor_type is None:
+            return None
+
+        np_dtype = onnx.helper.tensor_dtype_to_np_dtype(onnx_tensor_type.elem_type)
+        if self.quantizer.opset_version < 11:
+            const_val = np.array(attrs_dict.get("value", 0), dtype=np_dtype)
+        elif len(self.node.input) >= 3 and self.node.input[2]:
+            const_val = self.quantizer.model.get_constant_value(self.node.input[2])
+        else:
+            const_val = np.array(0, dtype=np_dtype)
+
+        return const_val
+
+    def _should_quantize_output_same_as_input(self) -> bool:
+        """
+        Returns true if Pad's output should use the same quantization parameters as input[0]
+        """
+        attrs_dict = {}
+        for attribute in self.node.attribute:
+            kv = attribute_to_kwarg(attribute)
+            attrs_dict.update(kv)
+
+        pad_mode = attrs_dict.get("mode", b"constant")
+        if pad_mode in (b"reflect", b"edge", b"wrap"):
+            # These modes pad the output with a value that already exists in the input.
+            # So, we can quantize the output the same as the input.
+            return True
+
+        # For 'constant' mode, if padding with 0, we can also quantize the output the same as the input
+        # because our quantization floating-point range always includes 0.
+        if pad_mode == b"constant":
+            pad_val = self._get_pad_const_val(attrs_dict)
+            if pad_val is not None and pad_val.dtype in (np.float32, np.float16):
+                return float(pad_val.item()) == 0
+
+        return False
+
+    def quantize(self):
+        assert self.node.op_type == "Pad"
+
+        for input_name in self.node.input:
+            if input_name:
+                self.quantizer.quantize_activation_tensor(input_name)
+
+        if not self.disable_qdq_for_node_output:
+            if self._should_quantize_output_same_as_input():
+                self.quantizer.quantize_output_same_as_input(self.node.output[0], self.node.input[0], self.node.name)
+            else:
+                self.quantizer.quantize_activation_tensor(self.node.output[0])
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pooling.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pooling.py
new file mode 100644
index 0000000000000000000000000000000000000000..7595e756eeedbb144fe6ebd954fd09f05ad32516
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/pooling.py
@@ -0,0 +1,67 @@
+import onnx
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+
+class QLinearPool(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+
+        # only try to quantize when given quantization parameters for it
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+
+        # get quantized input tensor names, quantize input if needed
+        (
+            quantized_input_names,
+            input_zero_point_names,
+            input_scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        # Create an entry for output quantized value.
+        qlinear_output_name = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            qlinear_output_name,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        # Create qlinear pool node for given type (AveragePool, etc)
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        qlinear_node_name = node.name + "_quant" if node.name else ""
+        qnode = onnx.helper.make_node(
+            "QLinear" + node.op_type,
+            [
+                quantized_input_names[0],
+                input_scale_names[0],
+                input_zero_point_names[0],
+                output_scale_name,
+                output_zp_name,
+            ],
+            [qlinear_output_name],
+            qlinear_node_name,
+            **kwargs,
+        )
+
+        # add all newly created nodes
+        nodes.append(qnode)
+        self.quantizer.new_nodes += nodes
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/qdq_base_operator.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/qdq_base_operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..0ad2829b607aa49176375534edc23d877f0b3375
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/qdq_base_operator.py
@@ -0,0 +1,22 @@
+import itertools
+
+from ..quant_utils import QuantizedValue, QuantizedValueType, attribute_to_kwarg, quantize_nparray  # noqa: F401
+from .base_operator import QuantOperatorBase  # noqa: F401
+
+
+class QDQOperatorBase:
+    def __init__(self, onnx_quantizer, onnx_node):
+        self.quantizer = onnx_quantizer
+        self.node = onnx_node
+        self.disable_qdq_for_node_output = onnx_node.op_type in onnx_quantizer.op_types_to_exclude_output_quantization
+
+    def quantize(self):
+        node = self.node
+
+        if self.disable_qdq_for_node_output:
+            tensors_to_quantize = node.input
+        else:
+            tensors_to_quantize = itertools.chain(node.input, node.output)
+
+        for tensor_name in tensors_to_quantize:
+            self.quantizer.quantize_activation_tensor(tensor_name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/resize.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/resize.py
new file mode 100644
index 0000000000000000000000000000000000000000..1604965025a3035f42a4438d0d971be94eb5305f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/resize.py
@@ -0,0 +1,34 @@
+from .direct_q8 import Direct8BitOp, QDQDirect8BitOp
+
+
+class QResize(Direct8BitOp):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Resize"
+
+        # if version is less than 11, go to normal quantize.
+        if self.quantizer.opset_version < 11:
+            super(Direct8BitOp, self).quantize()
+            return
+
+        # Direct 8bits op
+        return super().quantize()
+
+
+class QDQResize(QDQDirect8BitOp):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Resize"
+
+        # if version is less than 11, just keep this node
+        if self.quantizer.opset_version < 11:
+            return
+
+        # Direct 8bits op
+        return super().quantize()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/softmax.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/softmax.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e34fd742755c41f7ad6508f0e071294beb3b3b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/softmax.py
@@ -0,0 +1,74 @@
+import onnx
+import onnx.helper
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+
+
+class QLinearSoftmax(QuantOperatorBase):
+    def quantize(self):
+        node = self.node
+        # set limitations for softmax output scale and zp, because the output of softmax is always 0-1
+        if self.quantizer.activation_qType == onnx.onnx_pb.TensorProto.UINT8:
+            out_scale = 1 / 256.0
+            out_zero_point = 0
+        else:
+            out_scale = 1 / 256.0
+            out_zero_point = -128
+        # only try to quantize when given quantization parameters for it
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0], out_scale, out_zero_point)
+
+        # get quantized input tensor names, quantize input if needed
+        (
+            quantized_input_names,
+            input_zero_point_names,
+            input_scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+
+        if not data_found or quantized_input_names is None:
+            return super().quantize()
+
+        # Create an entry for output quantized value.
+        qlinear_output_name = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        quantized_output_value = QuantizedValue(
+            node.output[0],
+            qlinear_output_name,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = quantized_output_value
+
+        # Create qlinear softmax node for given type
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+        # make qlinearsoft has the real opset_version, its default SinceVersion would be 1
+        kwargs["opset"] = self.quantizer.opset_version
+        qlinear_node_name = node.name + "_quant" if node.name else ""
+        qnode = onnx.helper.make_node(
+            "QLinear" + node.op_type,
+            [
+                quantized_input_names[0],
+                input_scale_names[0],
+                input_zero_point_names[0],
+                output_scale_name,
+                output_zp_name,
+            ],
+            [qlinear_output_name],
+            qlinear_node_name,
+            **kwargs,
+        )
+
+        # add all newly created nodes
+        nodes.append(qnode)
+        self.quantizer.new_nodes += nodes
+        return None
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/split.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/split.py
new file mode 100644
index 0000000000000000000000000000000000000000..2fd8e9f1655a5b69c8385c6c0b115a312dccbe9d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/split.py
@@ -0,0 +1,63 @@
+import onnx
+
+from ..quant_utils import QuantizedValue, QuantizedValueType, attribute_to_kwarg
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QSplit(QuantOperatorBase):
+    def __init__(self, onnx_quantizer, onnx_node):
+        super().__init__(onnx_quantizer, onnx_node)
+
+    def quantize(self):
+        node = self.node
+        (
+            quantized_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [0])
+        if quantized_input_names is None:
+            return super().quantize()
+
+        quantized_node_name = ""
+        if node.name:
+            quantized_node_name = node.name + "_quant"
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+
+        # Output just derive the scale/zero from input
+        quantized_output_names = []
+        for output_name in node.output:
+            quantized_output_name = output_name + "quantized"
+            quantized_output_names.append(quantized_output_name)
+            q_output = QuantizedValue(
+                output_name,
+                quantized_output_name,
+                scale_names[0],
+                zero_point_names[0],
+                QuantizedValueType.Input,
+            )
+            self.quantizer.quantized_value_map[output_name] = q_output
+
+        if len(node.input) > 1:
+            quantized_input_names.extend(node.input[1:])
+        quantized_node = onnx.helper.make_node(
+            node.op_type, quantized_input_names, quantized_output_names, quantized_node_name, **kwargs
+        )
+
+        nodes.append(quantized_node)
+        self.quantizer.new_nodes += nodes
+
+
+class QDQSplit(QDQOperatorBase):
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Split"
+
+        if not self.quantizer.is_tensor_quantized(node.input[0]):
+            self.quantizer.quantize_activation_tensor(node.input[0])
+        if not self.disable_qdq_for_node_output:
+            for output in node.output:
+                self.quantizer.quantize_output_same_as_input(output, node.input[0], node.name)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/where.py b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/where.py
new file mode 100644
index 0000000000000000000000000000000000000000..993be45ee8cfa99a0f4efd3d712a5c768e2a6fd2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/quantization/operators/where.py
@@ -0,0 +1,87 @@
+import onnx
+
+from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain
+from .base_operator import QuantOperatorBase
+from .qdq_base_operator import QDQOperatorBase
+
+
+class QLinearWhere(QuantOperatorBase):
+    def should_quantize(self):
+        return True
+
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Where"
+        if not self.quantizer.force_quantize_no_input_check:
+            self.quantizer.new_nodes += [node]
+            return
+        (
+            data_found,
+            output_scale_name,
+            output_zp_name,
+            _,
+            _,
+        ) = self.quantizer._get_quantization_params(node.output[0])
+        (
+            q_input_names,
+            zero_point_names,
+            scale_names,
+            nodes,
+        ) = self.quantizer.quantize_activation(node, [1, 2])
+        if not data_found or q_input_names is None:
+            return super().quantize()
+        qlinear_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX
+        qlinear_output_name = node.name + "_quant" if node.name else ""
+
+        q_output = QuantizedValue(
+            node.output[0],
+            qlinear_output,
+            output_scale_name,
+            output_zp_name,
+            QuantizedValueType.Input,
+        )
+        self.quantizer.quantized_value_map[node.output[0]] = q_output
+
+        kwargs = {}
+        for attribute in node.attribute:
+            kwargs.update(attribute_to_kwarg(attribute))
+        kwargs["domain"] = ms_domain
+
+        qlwhere_inputs = [
+            node.input[0],
+            q_input_names[0],
+            scale_names[0],
+            zero_point_names[0],
+            q_input_names[1],
+            scale_names[1],
+            zero_point_names[1],
+            output_scale_name,
+            output_zp_name,
+        ]
+        qlwhere_node = onnx.helper.make_node(
+            "QLinearWhere", qlwhere_inputs, [qlinear_output], qlinear_output_name, **kwargs
+        )
+
+        self.quantizer.new_nodes += nodes
+        self.quantizer.new_nodes += [qlwhere_node]
+
+
+class QDQWhere(QDQOperatorBase):
+    def quantize(self):
+        node = self.node
+        assert node.op_type == "Where"
+        if self.quantizer.force_quantize_no_input_check:
+            if not self.quantizer.is_tensor_quantized(node.input[1]):
+                self.quantizer.quantize_activation_tensor(node.input[1])
+            if not self.quantizer.is_tensor_quantized(node.input[2]):
+                self.quantizer.quantize_activation_tensor(node.input[2])
+            if not self.disable_qdq_for_node_output:
+                for output in node.output:
+                    self.quantizer.quantize_activation_tensor(output)
+        elif (
+            self.quantizer.is_tensor_quantized(node.input[1])
+            and self.quantizer.is_tensor_quantized(node.input[2])
+            and not self.disable_qdq_for_node_output
+        ):
+            for output in node.output:
+                self.quantizer.quantize_activation_tensor(output)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_mlprogram_ops.md b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_mlprogram_ops.md
new file mode 100644
index 0000000000000000000000000000000000000000..f1bd98c4cc89516116461709e29ddcf211eedb66
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_mlprogram_ops.md
@@ -0,0 +1,55 @@
+<!--
+Keep in sync with doco generated from /docs/execution-providers/CoreML-ExecutionProvider.md on the gh_pages branch
+-->
+|Operator|Note|
+|--------|------|
+|ai.onnx:Add||
+|ai.onnx:Argmax||
+|ai.onnx:AveragePool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.|
+|ai.onnx:Cast||
+|ai.onnx:Clip||
+|ai.onnx:Concat||
+|ai.onnx:Conv|Only 1D/2D Conv is supported.<br/>Bias if provided must be constant.|
+|ai.onnx:ConvTranspose|Weight and bias must be constant.<br/>padding_type of SAME_UPPER/SAME_LOWER is not supported.<br/>kernel_shape must have default values.<br/>output_shape is not supported.<br/>output_padding must have default values.|
+|ai.onnx:DepthToSpace|If 'mode' is 'CRD' the input must have a fixed shape.|
+|ai.onnx:Div||
+|ai.onnx:Elu||
+|ai.onnx:Erf||
+|ai.onnx:Exp||
+|ai.onnx:Gemm|Input B must be constant.|
+|ai.onnx:Gelu||
+|ai.onnx:GlobalAveragePool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.|
+|ai.onnx:GlobalMaxPool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.|
+|ai.onnx:GridSample|4D input.<br/>'mode' of 'linear' or 'zeros'.<br/>(mode==linear && padding_mode==reflection && align_corners==0) is not supported.|
+|ai.onnx:GroupNormalization||
+|ai.onnx:HardSigmoid||
+|ai.onnx:InstanceNormalization||
+|ai.onnx:LayerNormalization||
+|ai.onnx:LeakyRelu||
+|ai.onnx:MatMul|Only support for transA == 0, alpha == 1.0 and beta == 1.0 is currently implemented.|
+|ai.onnx:MaxPool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.|
+|ai.onnx:Max||
+|ai.onnx:Mul||
+|ai.onnx:Pow|Only supports cases when both inputs are fp32.|
+|ai.onnx:PRelu||
+|ai.onnx:Reciprocal|this ask for a `epislon` (default 1e-4) where onnx don't provide|
+|ai.onnx:ReduceSum||
+|ai.onnx:ReduceMean||
+|ai.onnx:ReduceMax||
+|ai.onnx:Relu||
+|ai.onnx:Reshape||
+|ai.onnx:Resize|See [resize_op_builder.cc](https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/core/providers/coreml/builders/impl/resize_op_builder.cc) implementation. There are too many permutations to describe the valid combinations.|
+|ai.onnx:Round||
+|ai.onnx:Shape||
+|ai.onnx:Slice|starts/ends/axes/steps must be constant initializers.|
+|ai.onnx:Softplus||
+|ai.onnx:Split|If provided, `splits` must be constant.|
+|ai.onnx:Sub||
+|ai.onnx:Sigmoid||
+|ai.onnx:Softmax||
+|ai.onnx:Sqrt||
+|ai.onnx:Squeeze||
+|ai.onnx:Tanh||
+|ai.onnx:Transpose||
+|ai.onnx:Unsqueeze||
+|com.microsoft:QuickGelu|Produced by ORT's `QuickGeluFusion` optimizer pass. Decomposed into `mul` / `sigmoid` / `mul`.|
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_neuralnetwork_ops.md b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_neuralnetwork_ops.md
new file mode 100644
index 0000000000000000000000000000000000000000..d32dcc44011abe55fabbe5414100ee696243fea2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/coreml_supported_neuralnetwork_ops.md
@@ -0,0 +1,43 @@
+<!--
+Keep in sync with doco generated from /docs/execution-providers/CoreML-ExecutionProvider.md on the gh_pages branch
+-->
+|Operator|Note|
+|--------|------|
+|ai.onnx:Add||
+|ai.onnx:ArgMax||
+|ai.onnx:AveragePool|Only 2D Pool is supported.|
+|ai.onnx:BatchNormalization||
+|ai.onnx:Cast||
+|ai.onnx:Clip||
+|ai.onnx:Concat||
+|ai.onnx:Conv|Only 1D/2D Conv is supported.<br/>Weights and bias should be constant.|
+|ai.onnx:DepthToSpace|Only DCR mode DepthToSpace is supported.|
+|ai.onnx:Div||
+|ai.onnx:Flatten||
+|ai.onnx:Gather|Input `indices` with scalar value is not supported.|
+|ai.onnx:Gemm|Input B should be constant.|
+|ai.onnx:GlobalAveragePool|Only 2D Pool is supported.|
+|ai.onnx:GlobalMaxPool|Only 2D Pool is supported.|
+|ai.onnx:LeakyRelu||
+|ai.onnx:LRN||
+|ai.onnx:MatMul|Input B should be constant.|
+|ai.onnx:MaxPool|Only 2D Pool is supported.|
+|ai.onnx:Mul||
+|ai.onnx:Pad|Only constant mode and last two dim padding is supported.<br/>Input pads and constant_value should be constant.<br/>If provided, axes should be constant.|
+|ai.onnx:Pow|Only supports cases when both inputs are fp32.|
+|ai.onnx:PRelu|Input slope should be constant.<br/>Input slope should either have shape [C, 1, 1] or have 1 element.|
+|ai.onnx:Reciprocal||
+|ai.onnx.ReduceSum||
+|ai.onnx:Relu||
+|ai.onnx:Reshape||
+|ai.onnx:Resize|4D input.<br/>`coordinate_transformation_mode` == `asymmetric`.<br/>`mode` == `linear` or `nearest`.<br/>`nearest_mode` == `floor`.<br/>`exclude_outside` == false<br/>`scales` or `sizes` must be constant.|
+|ai.onnx:Shape|Attribute `start` with non-default value is not supported.<br/>Attribute `end` is not supported.|
+|ai.onnx:Sigmoid||
+|ai.onnx:Slice|Inputs `starts`, `ends`, `axes`, and `steps` should be constant. Empty slice is not supported.|
+|ai.onnx:Softmax||
+|ai.onnx:Split|If provided, `splits` must be constant.|
+|ai.onnx:Squeeze||
+|ai.onnx:Sqrt||
+|ai.onnx:Sub||
+|ai.onnx:Tanh||
+|ai.onnx:Transpose||
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/nnapi_supported_ops.md b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/nnapi_supported_ops.md
new file mode 100644
index 0000000000000000000000000000000000000000..9c417760bb7a05f167dd7e6963cd09f04410e19f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/nnapi_supported_ops.md
@@ -0,0 +1,58 @@
+<!--
+Keep in sync with doco generated from /docs/execution-providers/NNAPI-ExecutionProvider.md on the gh_pages branch
+-->
+|Operator|Note|
+|--------|------|
+|ai.onnx:Abs||
+|ai.onnx:Add||
+|ai.onnx:AveragePool|Only 2D Pool is supported.|
+|ai.onnx:BatchNormalization||
+|ai.onnx:Cast||
+|ai.onnx:Clip||
+|ai.onnx:Concat||
+|ai.onnx:Conv|Only 2D Conv is supported.<br/>Weights and bias should be constant.|
+|ai.onnx:DepthToSpace|Only DCR mode DepthToSpace is supported.|
+|ai.onnx:DequantizeLinear|All quantization scales and zero points should be constant.|
+|ai.onnx:Div||
+|ai.onnx:Elu||
+|ai.onnx:Exp||
+|ai.onnx:Flatten||
+|ai.onnx:Floor||
+|ai.onnx:Gather|Input indices should be constant if not int32 type.|
+|ai.onnx:Gemm|If input B is not constant, transB should be 1.|
+|ai.onnx:GlobalAveragePool|Only 2D Pool is supported.|
+|ai.onnx:GlobalMaxPool|Only 2D Pool is supported.|
+|ai.onnx:Identity||
+|ai.onnx:LeakyRelu||
+|ai.onnx:Log||
+|ai.onnx:LRN||
+|ai.onnx:MatMul||
+|ai.onnx:MaxPool|Only 2D Pool is supported.|
+|ai.onnx:Max||
+|ai.onnx:Min||
+|ai.onnx:Mul||
+|ai.onnx:Neg||
+|ai.onnx:Pad|Only constant mode Pad is supported.<br/>Input pads and constant_value should be constant.<br/>Input pads values should be non-negative.|
+|ai.onnx:Pow||
+|ai.onnx:PRelu||
+|ai.onnx:QLinearConv|Only 2D Conv is supported.<br/>Weights and bias should be constant.<br/>All quantization scales and zero points should be constant.|
+|ai.onnx:QLinearMatMul|All quantization scales and zero points should be constant.|
+|ai.onnx:QuantizeLinear|All quantization scales and zero points should be constant.|
+|ai.onnx:ReduceMean||
+|ai.onnx:Relu||
+|ai.onnx:Reshape||
+|ai.onnx:Resize|Only 2D Resize is supported.|
+|ai.onnx:Sigmoid||
+|ai.onnx:Sin||
+|ai.onnx:Slice||
+|ai.onnx:Softmax||
+|ai.onnx:Split|Number of splits must evenly divide split axis size. Input split should be constant if provided.|
+|ai.onnx:Sqrt||
+|ai.onnx:Squeeze|Input axes should be constant.|
+|ai.onnx:Sub||
+|ai.onnx:Tanh||
+|ai.onnx:Transpose||
+|ai.onnx:Unsqueeze|Input axes should be constant.|
+|com.microsoft:QLinearAdd|All quantization scales and zero points should be constant.|
+|com.microsoft:QLinearAveragePool|Only 2D Pool is supported.<br/>All quantization scales and zero points should be constant.|
+|com.microsoft:QLinearSigmoid|All quantization scales and zero points should be constant.|
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/usability_checker.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/usability_checker.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ac6e776378dc0ce6324fe139b7652181e83e1c2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/mobile_helpers/usability_checker.py
@@ -0,0 +1,738 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+from __future__ import annotations
+
+import argparse
+import logging
+import os
+import pathlib
+import tempfile
+from collections import deque
+from enum import IntEnum
+
+import onnx
+
+from ..onnx_model_utils import ModelProtoWithShapeInfo, get_producer_consumer_maps, is_fixed_size_tensor, optimize_model
+
+
+class _SupportedOpsChecker:
+    """
+    Class to process the md file with list of supported ops and caveats for an execution provider.
+    e.g. /tools/ci_build/github/android/nnapi_supported_ops.md
+         /tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md
+         /tools/ci_build/github/apple/coreml_supported_neuralnetwork_ops.md
+    """
+
+    def __init__(self, filename):
+        self._filename = filename
+        self._ops = {}  # op to caveats
+        self._ops_seen = set()
+
+        with open(filename) as f:
+            for line in f:
+                # we're looking for a markdown table with 2 columns. first is op name. second is caveats
+                # op name is domain:op
+                if line.startswith("|"):
+                    pieces = line.strip().split("|")
+                    if len(pieces) == 4:  # pre-first '|'. op, caveat, post-last '|'
+                        domain_op = pieces[1]
+                        caveat = pieces[2]
+                        caveat = caveat.replace("<br/>", " ")  # remove some HTML tags
+                        # skip lines that don't have the ':' which separates the domain and op
+                        # e.g. the table header will fail this check
+                        if ":" in domain_op:
+                            self._ops[domain_op] = caveat
+
+    def is_op_supported(self, node):
+        domain = node.domain if node.domain else "ai.onnx"
+        domain_op = domain + ":" + node.op_type
+
+        is_supported = domain_op in self._ops
+        if is_supported:
+            self._ops_seen.add(domain_op)
+
+        return is_supported
+
+    def get_caveats(self):
+        caveats = []
+        for op in sorted(self._ops_seen):
+            caveat = self._ops[op]
+            if caveat:
+                caveats.append(f"{op}:{caveat}")
+
+        return caveats
+
+
+class PartitioningInfo:
+    class TryWithEP(IntEnum):
+        NO = (0,)
+        MAYBE = (1,)
+        YES = 2
+
+    def __init__(
+        self,
+        num_nodes: int,
+        num_supported_nodes: int,
+        num_partitions: int,
+        supported_ops_checker: _SupportedOpsChecker,
+        supported_groups: list[onnx.NodeProto],
+        unsupported_ops: set[str],
+        nodes_unsupported_due_to_op: int,
+        nodes_unsupported_due_to_dynamic_input: int,
+        num_unsupported_nodes_due_to_rank: int,
+        ops_with_unsupported_rank: set[str],
+    ):
+        self.num_nodes = num_nodes
+        self.num_supported_nodes = num_supported_nodes
+        self.num_partitions = num_partitions
+        self.supported_ops_checker = supported_ops_checker
+        self.supported_groups = supported_groups
+        self.unsupported_ops = unsupported_ops
+        self.nodes_unsupported_due_to_op = nodes_unsupported_due_to_op
+        self.nodes_unsupported_due_to_dynamic_input = nodes_unsupported_due_to_dynamic_input
+        self.num_unsupported_nodes_due_to_rank = num_unsupported_nodes_due_to_rank
+        self.ops_with_unsupported_rank = ops_with_unsupported_rank
+
+        self.num_subgraphs = 0
+        self.num_nodes_in_subgraphs = 0
+
+    def merge(self, other: PartitioningInfo):
+        """
+        Merge the information from another PartitioningInfo instance into this one.
+        """
+        self.num_nodes += other.num_nodes
+        self.num_supported_nodes += other.num_supported_nodes
+        self.num_partitions += other.num_partitions
+        self.supported_groups.extend(other.supported_groups)
+        self.unsupported_ops.update(other.unsupported_ops)
+        self.nodes_unsupported_due_to_op += other.nodes_unsupported_due_to_op
+        self.nodes_unsupported_due_to_dynamic_input += other.nodes_unsupported_due_to_dynamic_input
+        self.num_unsupported_nodes_due_to_rank += other.num_unsupported_nodes_due_to_rank
+        self.ops_with_unsupported_rank.update(other.ops_with_unsupported_rank)
+
+        # hard assumption that we merge into the main graph partitioning info
+        self.num_subgraphs += 1
+        self.num_nodes_in_subgraphs += other.num_nodes
+
+    def suitability(self):
+        # semi-arbitrary choices that err on the side of MAYBE.
+        # having 1 partition is always preferred, but if that is small it may not be useful.
+        # having 2 partitions may be okay if they cover most nodes
+        # more than 2 partitions and the device copy cost is almost guaranteed to outweigh the benefit of using the NPU
+        # NOTE: This assumes the EP is not CPU based and there is device copy overhead to consider
+        pct_supported = self.num_supported_nodes / self.num_nodes * 100
+        if self.num_partitions == 1:
+            if pct_supported > 75:
+                return PartitioningInfo.TryWithEP.YES
+            elif pct_supported > 50:
+                return PartitioningInfo.TryWithEP.MAYBE
+            else:
+                return PartitioningInfo.TryWithEP.NO
+
+        if self.num_partitions == 2:
+            if pct_supported > 75:
+                return PartitioningInfo.TryWithEP.MAYBE
+            else:
+                return PartitioningInfo.TryWithEP.NO
+
+        return PartitioningInfo.TryWithEP.NO
+
+    def print_analysis(self, logger: logging.Logger, ep_name: str):
+        """
+        Analyze the partitioning information and log the analysis
+        :param logger: Logger to use
+        :param ep_name: Execution provider name to use in the log messages
+        """
+
+        logger.info(
+            f"{self.num_partitions} partitions with a total of {self.num_supported_nodes}/{self.num_nodes} "
+            f"nodes can be handled by the {ep_name} EP."
+        )
+
+        if self.supported_groups:
+            logger.info(
+                f"\tPartition sizes: [{', '.join([str(len(partition)) for partition in self.supported_groups])}]"
+            )
+
+            # dump full groups if debug output is enabled
+            for group in self.supported_groups:
+                logger.debug(f"Nodes in group: {','.join([f'{node.op_type}:{node.name}' for node in group])}")
+
+        logger.info(f"Unsupported nodes due to operator={self.nodes_unsupported_due_to_op}")
+        if self.unsupported_ops:
+            logger.info(f"\tUnsupported ops: {','.join(sorted(self.unsupported_ops))}")
+
+        caveats = self.supported_ops_checker.get_caveats()
+        if caveats:
+            indent = " " * 5
+            logger.info(
+                "\tCaveats that have not been checked and may result in a node not actually being supported:  "
+                f"{''.join([os.linesep + indent + caveat for caveat in caveats])}"
+            )
+
+        if self.nodes_unsupported_due_to_dynamic_input:
+            logger.info(
+                "Unsupported nodes due to input having a dynamic shape=%d",
+                self.nodes_unsupported_due_to_dynamic_input,
+            )
+
+        if self.num_unsupported_nodes_due_to_rank:
+            logger.info(f"Unsupported nodes due to rank of input data={self.num_unsupported_nodes_due_to_rank}")
+            logger.info(f"\tOps with unsupported rank: {','.join(sorted(self.ops_with_unsupported_rank))}")
+
+        if self.num_subgraphs > 0:
+            # TODO: CoreML has a flag. NNAPI doesn't. Either should be able to support a subgraph when treated as a
+            # separate graph (only extra detail would be making sure implicit inputs are handled).
+            # Merging the subgraph into the parent graph would be more complex.
+            #   e.g. for CoreML we could potentially convert Loop to while_loop and If to cond if the subgraphs in the
+            #        control flow node are fully supported.
+            #        NNAPI also has While and If.
+
+            # It most likely will be necessary to support merging in If nodes with fully supported subgraphs,
+            # as the subgraphs in those are often very simple, so the performance cost of going to the CPU EP and back
+            # is high.
+            logger.info(
+                f"{self.num_nodes_in_subgraphs} nodes are in {self.num_subgraphs} subgraphs. "
+                "Check EP as to whether subgraphs are supported."
+            )
+
+        pct_nodes_using_ep = self.num_supported_nodes / self.num_nodes * 100
+        if self.num_partitions == 0:
+            logger.info(f"{ep_name} cannot run any nodes in this model.")
+        elif self.num_partitions == 1:
+            if pct_nodes_using_ep > 75:
+                logger.info(
+                    f"{ep_name} should work well for this model as there is one partition "
+                    f"covering {pct_nodes_using_ep:.1f}% of the nodes in the model."
+                )
+            elif pct_nodes_using_ep > 50:
+                logger.info(
+                    f"{ep_name} may work well for this model, however only {pct_nodes_using_ep:.1f}% of nodes "
+                    "will use it. Performance testing is required to validate."
+                )
+            else:
+                logger.info(
+                    f"{ep_name} will probably not work will for this model as only {pct_nodes_using_ep:.2f}% "
+                    "of nodes will use it."
+                )
+
+        elif self.num_partitions == 2 and pct_nodes_using_ep > 75:
+            logger.info(
+                f"{ep_name} can be considered for this model as there are two partitions "
+                f"covering {pct_nodes_using_ep:.1f}% of the nodes. "
+                "Performance testing is required to validate."
+            )
+        else:
+            logger.info(
+                f"{ep_name} is not recommended with this model as there are {self.num_partitions} partitions "
+                f"covering {pct_nodes_using_ep:.1f}% of the nodes in the model. "
+                "This will most likely result in worse performance than just using the CPU EP."
+            )
+
+
+def _check_partitioning_for_graph(
+    graph: onnx.GraphProto,
+    node_to_producers: dict[onnx.NodeProto, set[onnx.NodeProto]],
+    node_to_consumers: dict[onnx.NodeProto, set[onnx.NodeProto]],
+    supported_ops_checker: _SupportedOpsChecker,
+    outer_scope_initializers: set[str],
+    require_fixed_input_sizes: bool,
+    value_info: dict[str, onnx.ValueInfoProto],
+    max_rank: int = 999,  # max rank if EP has a limitation
+):
+    # initializers have fixed sizes.
+    initializers = [i.name for i in graph.initializer]
+
+    def _is_fixed_shape_value(value):
+        if value in value_info:
+            return is_fixed_size_tensor(value_info[value])
+
+        if value in initializers or value in outer_scope_initializers:
+            return True
+
+        # if something has an unknown shape (e.g. something downstream of a Reshape with dynamic input for the shape)
+        # it won't have an entry in value_info
+        return False
+
+    #
+    # Replicate logic from /onnxruntime/core/providers/partitioning_utils.cc:CreateSupportedPartitionNodeGroups
+    # to roughly estimate number of partitions for nodes that is_node_supported_fn returns true for.
+    #
+    # We keep the structure and variable names as close as possible to the C++ implementation to simplify keeping them
+    # in sync if future updates are needed.
+    #
+    # NOTE: CreateSupportedPartitionNodeGroups was recently updated to be QDQ aware so that partitions did not split
+    # QDQ node groups. This code does not need to be QDQ aware as splitting a QDQ node group does not affect the total
+    # number of partitions or supported nodes.
+    #
+
+    # we don't currently support a callback for additional group closure checks in the python implementation
+    on_group_closed_fn = None
+
+    supported_groups = []
+    # number of inputs from unprocessed nodes (in-degree) per node
+    in_degree = {}
+    # nodes that are ready to process
+    nodes_to_process = deque()  # deque of Node instances
+    # nodes that will be processed when considering the next partition node group
+    nodes_to_process_with_next_group = deque()
+
+    # initialize in-degrees and find root nodes
+    for node in graph.node:
+        node_input_edge_count = len(node_to_producers[node]) if node in node_to_producers else 0
+        in_degree[node] = node_input_edge_count
+        if node_input_edge_count == 0:
+            # node is only dependent on graph input or initializers
+            nodes_to_process.append(node)
+
+    supported_group = []
+    # the partition node group's border is the aggregate of its nodes' output nodes
+    supported_group_border = set()
+    num_supported_nodes = 0
+    num_unsupported_nodes_due_to_op = 0
+    num_unsupported_nodes_due_to_dynamic_input = 0
+    num_unsupported_nodes_due_to_rank = 0
+    unsupported_ops = set()
+    ops_with_unsupported_rank = set()
+
+    def close_group():
+        if supported_group:
+            keep_partition = not on_group_closed_fn or on_group_closed_fn(supported_group)
+
+            if keep_partition:
+                supported_groups.append(supported_group.copy())
+
+            supported_group.clear()
+            supported_group_border.clear()
+
+    while nodes_to_process or nodes_to_process_with_next_group:
+        if not nodes_to_process:
+            close_group()
+            nodes_to_process = nodes_to_process_with_next_group
+            nodes_to_process_with_next_group = deque()
+            continue
+
+        node = nodes_to_process.popleft()
+
+        is_op_supported = supported_ops_checker.is_op_supported(node)
+        is_input_shape_supported = not require_fixed_input_sizes or all(_is_fixed_shape_value(i) for i in node.input)
+
+        is_rank_supported = True
+        if value_info:
+            for node_input in node.input:
+                if node_input and node_input in value_info and value_info[node_input].type.HasField("tensor_type"):
+                    input_rank = len(value_info[node_input].type.tensor_type.shape.dim)
+                    if input_rank > max_rank:
+                        is_rank_supported = False
+                        break
+
+        # special-case if we can infer the rank from the length of the 'perms' Transpose attribute
+        # e.g. this works with SegmentAnything where dynamic Reshape operators result in no shape info.
+        if node.op_type == "Transpose" and len(node.attribute[0].ints) > max_rank:
+            is_rank_supported = False
+
+        is_node_supported = is_op_supported and is_input_shape_supported and is_rank_supported
+
+        if not is_node_supported:
+            if node in supported_group_border:
+                # an unsupported node on the border will be processed after the current partition node group
+                # so skip any additional processing/counting here
+                nodes_to_process_with_next_group.append(node)
+                continue
+
+            if not is_op_supported:
+                unsupported_ops.add(f"{node.domain if node.domain else 'ai.onnx'}:{node.op_type}")
+                num_unsupported_nodes_due_to_op += 1
+
+            if not is_input_shape_supported:
+                num_unsupported_nodes_due_to_dynamic_input += 1
+
+            if not is_rank_supported:
+                num_unsupported_nodes_due_to_rank += 1
+                ops_with_unsupported_rank.add(f"{node.domain if node.domain else 'ai.onnx'}:{node.op_type}")
+
+        if is_node_supported:
+            num_supported_nodes += 1
+
+            # add node to the partition node group
+            supported_group.append(node)
+
+            # remove node from the border and add its outputs to the border
+            if node in supported_group_border:  # noqa: FURB132
+                supported_group_border.remove(node)
+
+            # for each consumer node add to supported_group_border
+            if node in node_to_consumers:
+                for consumer in node_to_consumers[node]:
+                    supported_group_border.add(consumer)
+
+        # adjust in-degrees of the node outputs and add any new nodes to process
+        if node in node_to_consumers:
+            for consumer in node_to_consumers[node]:
+                consumer_node_in_degree = in_degree[consumer]
+                consumer_node_in_degree -= 1
+                if consumer_node_in_degree == 0:
+                    nodes_to_process.append(consumer)
+
+                in_degree[consumer] = consumer_node_in_degree
+
+    close_group()
+
+    num_nodes = len(graph.node)
+    num_partitions = len(supported_groups)
+
+    info = PartitioningInfo(
+        num_nodes,
+        num_supported_nodes,
+        num_partitions,
+        supported_ops_checker,
+        supported_groups,
+        unsupported_ops,
+        num_unsupported_nodes_due_to_op,
+        num_unsupported_nodes_due_to_dynamic_input,
+        num_unsupported_nodes_due_to_rank,
+        ops_with_unsupported_rank,
+    )
+
+    return info
+
+
+def check_partitioning(
+    main_graph: onnx.GraphProto,
+    supported_ops_checker: _SupportedOpsChecker,
+    require_fixed_input_sizes: bool,
+    max_rank: int = 999,
+) -> PartitioningInfo:
+    """
+    Estimate the partitions the graph will be split into for nodes that is_node_supported_fn returns true for.
+
+    The check on whether a node is supported is purely based on the operator type. Additional limitations
+    (e.g. NNAPI EP only supports 2D Conv) are not checked, so partitions may not be 100% accurate. The limitations
+    for operators in the partitions are printed so the user can manually check.
+    :param main_graph: Graph to process
+    :param supported_ops_checker: Checker with info on supported ops.
+    :param require_fixed_input_sizes: If True, require that the inputs to a potentially supported node are fixed size
+                                      tensors for it to be considered as supported. This requires
+                                      onnx.shape_inference.infer_shapes to have been run on the model to populate the
+                                      shape information.
+                                      If False, shapes are ignored during the check.
+    :param max_rank: Set if EP has a limitation on the rank of tensors it supports.
+    :return PartitioningInfo instance with details
+    """
+
+    if require_fixed_input_sizes and len(main_graph.value_info) == 0 and len(main_graph.node) > 1:
+        raise ValueError("Run onnx.shape_inference.infer_shapes on the model to populate the shape information.")
+
+    # create lookup map from ValueInfo for efficiency
+    def _update_value_info(graph: onnx.GraphProto, value_to_shape: dict[str, onnx.ValueInfoProto]):
+        for v in graph.input:
+            value_to_shape[v.name] = v
+        for v in graph.output:
+            value_to_shape[v.name] = v
+        for v in graph.value_info:
+            value_to_shape[v.name] = v
+
+    # the producer/consumer maps are for the entire model
+    node_to_producers, node_to_consumers = get_producer_consumer_maps(main_graph)
+
+    def _check_graph(
+        graph: onnx.GraphProto,
+        outer_scope_value_info: dict[str, onnx.ValueInfoProto] | None,
+        outer_scope_initializers: set[str] | None = None,
+        partitioning_info: PartitioningInfo | None = None,
+    ) -> PartitioningInfo:
+        if outer_scope_value_info is not None:
+            # extend value info if we're using it. we replace any value shadowed with a local one
+            value_info = outer_scope_value_info.copy()
+            _update_value_info(graph, value_info)
+        else:
+            value_info = {}
+
+        if outer_scope_initializers is None:
+            outer_scope_initializers = set()
+
+        info = _check_partitioning_for_graph(
+            graph,
+            node_to_producers,
+            node_to_consumers,
+            supported_ops_checker,
+            outer_scope_initializers,
+            require_fixed_input_sizes,
+            value_info,
+            max_rank,
+        )
+
+        if partitioning_info:
+            # merge in subgraph info
+            partitioning_info.merge(info)
+        else:
+            # main graph info
+            partitioning_info = info
+
+        # setup outer scope initializers. we copy the input set as a model may have multiple subgraphs
+        # on multiple levels, so we need to keep the set for each descent separate
+        subgraph_outer_scope_initializers = set(outer_scope_initializers)
+        for initializer in graph.initializer:
+            subgraph_outer_scope_initializers.add(initializer.name)
+
+        for node in graph.node:
+            # recurse into nodes with subgraphs
+            for attr in node.attribute:
+                if attr.HasField("g"):
+                    subgraph = attr.g
+                    partitioning_info = _check_graph(
+                        subgraph, value_info, subgraph_outer_scope_initializers, partitioning_info
+                    )
+
+        return partitioning_info
+
+    aggregated_partitioning_info = _check_graph(main_graph, {} if require_fixed_input_sizes else None)
+
+    return aggregated_partitioning_info
+
+
+def _check_ep_partitioning(
+    model: onnx.ModelProto, supported_ops_config: pathlib.Path, require_fixed_input_sizes: bool, max_rank: int = 999
+):
+    supported_ops = _SupportedOpsChecker(supported_ops_config)
+    partition_info = check_partitioning(model.graph, supported_ops, require_fixed_input_sizes, max_rank)
+    return partition_info
+
+
+def check_nnapi_partitions(model, require_fixed_input_sizes: bool):
+    # if we're running in the ORT python package the file should be local. otherwise assume we're running from the
+    # ORT repo
+    script_dir = pathlib.Path(__file__).parent
+    local_config = script_dir / "nnapi_supported_ops.md"
+    if local_config.exists():
+        config_path = local_config
+    else:
+        ort_root = script_dir.parents[3]
+        config_path = ort_root / "tools" / "ci_build" / "github" / "android" / "nnapi_supported_ops.md"
+
+    return _check_ep_partitioning(model, config_path, require_fixed_input_sizes)
+
+
+def check_coreml_partitions(model: onnx.ModelProto, require_fixed_input_sizes: bool, config_filename: str):
+    # if we're running in the ORT python package the file should be local. otherwise assume we're running from the
+    # ORT repo
+    script_dir = pathlib.Path(__file__).parent
+    local_config = script_dir / config_filename
+    if local_config.exists():
+        config_path = local_config
+    else:
+        ort_root = script_dir.parents[3]
+        config_path = ort_root / "tools" / "ci_build" / "github" / "apple" / config_filename
+
+    max_rank = 5
+    return _check_ep_partitioning(model, config_path, require_fixed_input_sizes, max_rank)
+
+
+def check_shapes(graph: onnx.GraphProto, logger: logging.Logger | None = None):
+    """
+    Check the shapes of graph inputs, values and graph outputs to determine if they have static or dynamic sizes.
+    NNAPI does not support dynamically sized values. CoreML does, but it will most likely cost performance.
+    :param graph: Graph to check. If shape inferencing has been run the checks on values will be meaningful.
+    :param logger: Optional logger for diagnostic information.
+    :return: Tuple of List of inputs with dynamic shapes, Number of dynamic values found
+    """
+
+    # it's OK if the input is dynamically sized and we do a Resize early to a fixed size.
+    # it's not good if lots of ops have dynamic inputs
+
+    num_fixed_values = 0
+    num_dynamic_values = 0
+
+    dynamic_inputs = []
+    for i in graph.input:
+        if not is_fixed_size_tensor(i):
+            dynamic_inputs.append(i)
+            # split/join to remove repeated whitespace and newlines from str(i)
+            if logger:
+                logger.info(f"Input is not a fixed size tensor: {' '.join(str(i).split())}")
+            num_dynamic_values += 1
+        else:
+            num_fixed_values += 1
+
+    dynamic_outputs = []
+    for o in graph.output:
+        if not is_fixed_size_tensor(o):
+            dynamic_outputs.append(o)
+            if logger:
+                logger.info(f"Output is not a fixed size tensor: {' '.join(str(o).split())}")
+            num_dynamic_values += 1
+        else:
+            num_fixed_values += 1
+
+    # check we have value info.
+    # special case some test graphs with a single node which only have graph input and output values, and
+    # a model where all inputs are dynamic (results in no value_info)
+    if not graph.value_info and not (len(graph.node) == 1 or len(dynamic_inputs) == len(graph.input)):
+        logger.warning(
+            "Unable to check shapes within model. ONNX shape inferencing should be run on the model prior to checking."
+        )
+
+    for vi in graph.value_info:
+        if is_fixed_size_tensor(vi):
+            num_fixed_values += 1
+        else:
+            num_dynamic_values += 1
+
+    if logger:
+        logger.info(
+            f"Num values with fixed shape={num_fixed_values}. Num values with dynamic shape={num_dynamic_values}"
+        )
+
+        if dynamic_inputs:
+            if dynamic_outputs:
+                logger.info(
+                    "Model has dynamic inputs and outputs. Consider re-exporting model with fixed sizes "
+                    "if NNAPI or CoreML can be used with this model."
+                )
+            else:
+                logger.info(
+                    """Model has dynamically sized inputs but fixed sized outputs.
+                       If the sizes become fixed early in the model (e.g. pre-processing of a dynamic input size
+                       results in a fixed input size for the majority of the model) performance with NNAPI and CoreML,
+                       if applicable, should not be significantly impacted."""
+                )
+
+    return dynamic_inputs, num_dynamic_values
+
+
+def checker(model_path: pathlib.Path, logger: logging.Logger):
+    model_with_shape_info_wrapper = ModelProtoWithShapeInfo(model_path)
+    model_with_shape_info = model_with_shape_info_wrapper.model_with_shape_info
+
+    dynamic_inputs, num_dynamic_values = check_shapes(model_with_shape_info.graph)
+
+    def check_ep(ep_name, checker_func):
+        logger.info(f"Checking {ep_name}")
+
+        # check with shape info first so supported nodes takes into account values with dynamic shapes
+        require_fixed_input_sizes = True
+        partition_info = checker_func(model_with_shape_info, require_fixed_input_sizes)
+        if logger.getEffectiveLevel() <= logging.INFO:
+            partition_info.print_analysis(logger, ep_name)
+
+        suitability = partition_info.suitability()
+        logger.info(f"Model should perform well with {ep_name} as is: {suitability.name}")
+
+        if suitability != PartitioningInfo.TryWithEP.YES and dynamic_inputs:
+            logger.info("--------")
+            logger.info("Checking if model will perform better if the dynamic shapes are fixed...")
+            require_fixed_input_sizes = False
+            partition_info_with_fixed_shapes = checker_func(model_with_shape_info, require_fixed_input_sizes)
+
+            if logger.getEffectiveLevel() <= logging.INFO:
+                # analyze and log detailed info
+                logger.info("Partition information if the model was updated to make the shapes fixed:")
+                partition_info_with_fixed_shapes.print_analysis(logger, ep_name)
+
+            fixed_shape_suitability = partition_info_with_fixed_shapes.suitability()
+            logger.info(
+                f"Model should perform well with {ep_name} if modified to have fixed input shapes: "
+                f"{fixed_shape_suitability.name}"
+            )
+
+            if fixed_shape_suitability != PartitioningInfo.TryWithEP.NO:
+                logger.info("Shapes can be altered using python -m onnxruntime.tools.make_dynamic_shape_fixed")
+
+            if fixed_shape_suitability.value > suitability.value:
+                suitability = fixed_shape_suitability
+
+        logger.info("================")
+        logger.info("")
+
+        return suitability
+
+    nnapi_suitability = check_ep("NNAPI", check_nnapi_partitions)
+
+    # Check for NeuralNetwork CoreML model
+    def check_nn_coreml(model: onnx.ModelProto, require_fixed_input_sizes):
+        return check_coreml_partitions(model, require_fixed_input_sizes, "coreml_supported_neuralnetwork_ops.md")
+
+    # Check for MLProgram CoreML model
+    def check_mlprogram_coreml(model: onnx.ModelProto, require_fixed_input_sizes):
+        return check_coreml_partitions(model, require_fixed_input_sizes, "coreml_supported_mlprogram_ops.md")
+
+    coreml_nn_suitability = check_ep("CoreML NeuralNetwork", check_nn_coreml)
+    coreml_mlprogram_suitability = check_ep("CoreML MLProgram", check_mlprogram_coreml)
+
+    if (
+        nnapi_suitability != PartitioningInfo.TryWithEP.YES
+        or coreml_nn_suitability != PartitioningInfo.TryWithEP.YES
+        or coreml_mlprogram_suitability != PartitioningInfo.TryWithEP.YES
+    ) and logger.getEffectiveLevel() > logging.INFO:
+        logger.info("Re-run with log level of INFO for more details on the NNAPI/CoreML issues.")
+
+    return (
+        nnapi_suitability != PartitioningInfo.TryWithEP.NO
+        or coreml_nn_suitability != PartitioningInfo.TryWithEP.NO
+        or coreml_mlprogram_suitability != PartitioningInfo.TryWithEP.NO
+    )
+
+
+def analyze_model(model_path: pathlib.Path, skip_optimize: bool = False, logger: logging.Logger | None = None):
+    """
+    Analyze the provided model to determine if it's likely to work well with the NNAPI or CoreML Execution Providers
+    :param model_path: Model to analyze.
+    :param skip_optimize: Skip optimizing to BASIC level before checking. When exporting to ORT format we will do this
+                          optimization..
+    :param logger: Logger for output
+    :return: True if either the NNAPI or CoreML Execution Providers may work well with this model.
+    """
+    if not logger:
+        logger = logging.getLogger("usability_checker")
+        logger.setLevel(logging.INFO)
+
+    logger.info(f"Checking {model_path} for usability with ORT Mobile.")
+
+    with tempfile.TemporaryDirectory() as tmp:
+        if not skip_optimize:
+            tmp_path = pathlib.Path(tmp) / model_path.name
+            optimize_model(model_path, tmp_path, use_external_initializers=True)
+            model_path = tmp_path
+
+        try_eps = checker(model_path.resolve(strict=True), logger)
+
+    return try_eps
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        os.path.basename(__file__), description="""Analyze an ONNX model for usage with the ORT mobile"""
+    )
+
+    parser.add_argument("--log_level", choices=["debug", "info"], default="info", help="Logging level")
+    parser.add_argument(
+        "--skip_optimize",
+        action="store_true",
+        help="Don't optimize the model to BASIC level prior to analyzing. "
+        "Optimization will occur when exporting the model to ORT format, so in general "
+        "should not be skipped unless you have a specific reason to do so.",
+    )
+    parser.add_argument("model_path", type=pathlib.Path, help="Provide path to ONNX model")
+
+    return parser.parse_args()
+
+
+def run_analyze_model():
+    args = parse_args()
+    logger = logging.getLogger("default")
+
+    if args.log_level == "debug":
+        logger.setLevel(logging.DEBUG)
+    elif args.log_level == "info":
+        logger.setLevel(logging.INFO)
+    elif args.log_level == "warning":
+        logger.setLevel(logging.WARNING)
+    else:
+        logger.setLevel(logging.ERROR)
+
+    model_path = args.model_path.resolve()
+    analyze_model(model_path, args.skip_optimize, logger)
+
+
+if __name__ == "__main__":
+    run_analyze_model()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..226ab64e051fc072011180c785df2d95518b7499
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/__init__.py
@@ -0,0 +1,27 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import os
+import sys
+
+# need to add the path to the ORT flatbuffers python module before we import anything else here.
+# we also auto-magically adjust to whether we're running from the ORT repo, or from within the ORT python package
+script_dir = os.path.dirname(os.path.realpath(__file__))
+fbs_py_schema_dirname = "ort_flatbuffers_py"
+if os.path.isdir(os.path.join(script_dir, fbs_py_schema_dirname)):
+    # fbs bindings are in this directory, so we're running in the ORT python package
+    ort_fbs_py_parent_dir = script_dir
+else:
+    # running directly from ORT repo, so fbs bindings are under onnxruntime/core/flatbuffers
+    ort_root = os.path.abspath(os.path.join(script_dir, "..", "..", "..", ".."))
+    ort_fbs_py_parent_dir = os.path.join(ort_root, "onnxruntime", "core", "flatbuffers")
+
+sys.path.append(ort_fbs_py_parent_dir)
+
+from .operator_type_usage_processors import (  # noqa: E402
+    GloballyAllowedTypesOpTypeImplFilter,  # noqa: F401
+    OperatorTypeUsageManager,  # noqa: F401
+    OpTypeImplFilterInterface,  # noqa: F401
+)
+from .ort_model_processor import OrtFormatModelProcessor  # noqa: E402, F401
+from .utils import create_config_from_models  # noqa: E402, F401
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/__pycache__/__init__.cpython-313.pyc
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/operator_type_usage_processors.py
@@ -0,0 +1,653 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+from __future__ import annotations
+
+import json
+from abc import ABC, abstractmethod
+
+import ort_flatbuffers_py.fbs as fbs
+
+from .types import FbsTypeInfo, value_name_to_typestr
+
+
+def _create_op_key(domain: str, optype: str):
+    return f"{domain}:{optype}"
+
+
+def _ort_constant_for_domain(domain: str):
+    """
+    Map a string domain value to the internal ONNX Runtime constant for that domain.
+    :param domain: Domain string to map.
+    :return: Internal ONNX Runtime constant
+    """
+
+    # constants are defined in <ORT root>/include/onnxruntime/core/graph/constants.h
+    # This list is limited to just the domains we have processors for
+    domain_to_constant_map = {"ai.onnx": "kOnnxDomain", "ai.onnx.ml": "kMLDomain", "com.microsoft": "kMSDomain"}
+
+    if domain not in domain_to_constant_map:
+        raise ValueError(f"Domain {domain} not found in map to ONNX Runtime constant. Please update map.")
+
+    return domain_to_constant_map[domain]
+
+
+def _reg_type_to_cpp_type(reg_type: str):
+    if reg_type == "string":
+        return "std::string"
+    return reg_type
+
+
+def _split_reg_types(reg_types_str: str):
+    """
+    Split on underscores but append "_t" to the previous element.
+    """
+    tokens = reg_types_str.split("_")
+    reg_types = []
+    for token in tokens:
+        if token == "t" and len(reg_types) > 0:
+            reg_types[-1] += "_t"
+        else:
+            reg_types += [token]
+    return reg_types
+
+
+class TypeUsageProcessor(ABC):
+    """
+    Abstract base class for processors which implement operator specific logic to determine the type or types required.
+    """
+
+    def __init__(self, domain: str, optype: str):
+        self.domain = domain
+        self.optype = optype
+        self.name = _create_op_key(domain, optype)
+
+    @abstractmethod
+    def process_node(self, node: fbs.Node, value_name_to_typeinfo: dict):
+        pass
+
+    def is_typed_registration_needed(self, type_in_registration: str, globally_allowed_types: set[str] | None):
+        """
+        Given the string from a kernel registration, determine if the registration is required or not.
+        :param type_in_registration: Type string from kernel registration
+        :param globally_allowed_types: Optional set of globally allowed types. If provided, these types take precedence
+                                       in determining the required types.
+        :return: True is required. False if not.
+        """
+        # Not all operators have typed registrations, so this is optionally implemented by derived classes
+        raise RuntimeError(f"Did not expect processor for {self.name} to have typed registrations.")
+
+    def get_cpp_entry(self):
+        """
+        Get the C++ code that specifies this operator's required types.
+        :return: List with any applicable C++ code for this operator's required types. One line per entry.
+        """
+        # Not applicable for some ops, so return no lines by default.
+        return []
+
+    @abstractmethod
+    def to_config_entry(self):
+        """
+        Generate a configuration file entry in JSON format with the required types for the operator.
+        :return: JSON string with required type information.
+        """
+
+    @abstractmethod
+    def from_config_entry(self, entry: str):
+        """
+        Re-create the types required from a configuration file entry created with to_config_entry.
+        NOTE: Any existing type information should be cleared prior to re-creating from a config file entry.
+        :param entry: Configuration file entry
+        """
+
+
+class DefaultTypeUsageProcessor(TypeUsageProcessor):
+    """
+    Operator processor which tracks the types used for selected input/s and/or output/s.
+    """
+
+    def __init__(
+        self,
+        domain: str,
+        optype: str,
+        inputs: [int] = [0],  # noqa: B006
+        outputs: [int] = [],  # noqa: B006
+        required_input_types: dict[int, set[str]] = {},  # noqa: B006
+        required_output_types: dict[int, set[str]] = {},  # noqa: B006
+    ):
+        """
+        Create DefaultTypeUsageProcessor. Types for one or more inputs and/or outputs can be tracked by the processor.
+        The default is to track the types required for input 0, as this is the most common use case in ONNX.
+
+        Required input and output types may be specified. These are only applicable to is_typed_registration_needed().
+        If a registration type matches a required type, the typed registration is needed.
+        There is a separate mechanism for specifying required types from C++ for kernels with untyped registration.
+
+        :param domain: Operator domain.
+        :param optype: Operator name.
+        :param inputs: Inputs to track. Zero based index. May be empty.
+        :param outputs: Outputs to track. Zero based index. May be empty.
+        :param required_input_types: Required input types. May be empty.
+        :param required_output_types: Required output types. May be empty.
+        """
+        super().__init__(domain, optype)
+        self._input_types = {}
+        self._output_types = {}
+
+        for i in inputs:
+            self._input_types[i] = set()
+
+        for o in outputs:
+            self._output_types[o] = set()
+
+        if not inputs and not outputs:
+            raise ValueError("At least one input or output must be tracked")
+
+        self._required_input_types = required_input_types
+        self._required_output_types = required_output_types
+
+    def _is_type_enabled(self, reg_type, index, required_types, allowed_type_set):
+        cpp_type = _reg_type_to_cpp_type(reg_type)
+        return cpp_type in required_types.get(index, set()) or cpp_type in allowed_type_set
+
+    def is_input_type_enabled(self, reg_type, index, allowed_type_set=None):
+        """Whether input type is enabled based on required and allowed types."""
+        if allowed_type_set is None:
+            allowed_type_set = self._input_types[index]
+        return self._is_type_enabled(reg_type, index, self._required_input_types, allowed_type_set)
+
+    def is_output_type_enabled(self, reg_type, index, allowed_type_set=None):
+        """Whether output type is enabled based on required and allowed types."""
+        if allowed_type_set is None:
+            allowed_type_set = self._output_types[index]
+        return self._is_type_enabled(reg_type, index, self._required_output_types, allowed_type_set)
+
+    def process_node(self, node: fbs.Node, value_name_to_typeinfo: dict):
+        for i in self._input_types:
+            if i >= node.InputsLength():
+                # Some operators have fewer inputs in earlier versions where data that was as an attribute
+                # become an input in later versions to allow it to be dynamically provided. Allow for that.
+                # e.g. Slice-1 had attributes for the indices, and Slice-10 moved those to be inputs
+                # raise RuntimeError('Node has {} outputs. Tracker for {} incorrectly configured as it requires {}.'
+                #                    .format(node.OutputsLength(), self.name, o))
+                pass
+            else:
+                type_str = value_name_to_typestr(node.Inputs(i), value_name_to_typeinfo)
+                self._input_types[i].add(type_str)
+
+        for o in self._output_types:
+            # Don't know of any ops where the number of outputs changed across versions, so require a valid length
+            if o >= node.OutputsLength():
+                raise RuntimeError(
+                    f"Node has {node.OutputsLength()} outputs. Tracker for {self.name} incorrectly configured as it requires {o}."
+                )
+
+            type_str = value_name_to_typestr(node.Outputs(o), value_name_to_typeinfo)
+            self._output_types[o].add(type_str)
+
+    def is_typed_registration_needed(self, type_in_registration: str, globally_allowed_types: set[str] | None):
+        if 0 not in self._input_types:
+            # currently all standard typed registrations are for input 0.
+            # custom registrations can be handled by operator specific processors (e.g. OneHotProcessor below).
+            raise RuntimeError(f"Expected typed registration to use type from input 0. Node:{self.name}")
+
+        return self.is_input_type_enabled(type_in_registration, 0, globally_allowed_types)
+
+    def get_cpp_entry(self):
+        entries = []
+        domain = _ort_constant_for_domain(self.domain)
+        for i in sorted(self._input_types.keys()):
+            if self._input_types[i]:
+                entries.append(
+                    "ORT_SPECIFY_OP_KERNEL_ARG_ALLOWED_TYPES({}, {}, Input, {}, {});".format(
+                        domain, self.optype, i, ", ".join(sorted(self._input_types[i]))
+                    )
+                )
+
+        for o in sorted(self._output_types.keys()):
+            if self._output_types[o]:
+                entries.append(
+                    "ORT_SPECIFY_OP_KERNEL_ARG_ALLOWED_TYPES({}, {}, Output, {}, {});".format(
+                        domain, self.optype, o, ", ".join(sorted(self._output_types[o]))
+                    )
+                )
+
+        return entries
+
+    def to_config_entry(self):
+        # convert the sets of types to lists so they can easily written out using the json model
+        aggregate_info = {"inputs": {}, "outputs": {}}
+
+        # filter out empty entries and sort the types
+        for i in sorted(self._input_types.keys()):
+            if self._input_types[i]:
+                aggregate_info["inputs"][i] = sorted(self._input_types[i])
+
+        for o in sorted(self._output_types.keys()):
+            if self._output_types[o]:
+                aggregate_info["outputs"][o] = sorted(self._output_types[o])
+
+        # remove any empty keys
+        if not aggregate_info["inputs"]:
+            aggregate_info.pop("inputs")
+        if not aggregate_info["outputs"]:
+            aggregate_info.pop("outputs")
+
+        entry = json.dumps(aggregate_info) if aggregate_info else None
+        return entry
+
+    def from_config_entry(self, entry: str):
+        self._input_types.clear()
+        self._output_types.clear()
+
+        aggregate_info = json.loads(entry)
+        if "inputs" in aggregate_info:
+            for i_str, values in aggregate_info["inputs"].items():
+                self._input_types[int(i_str)] = set(values)
+
+        if "outputs" in aggregate_info:
+            for o_str, values in aggregate_info["outputs"].items():
+                self._output_types[int(o_str)] = set(values)
+
+
+class Input1TypedRegistrationProcessor(DefaultTypeUsageProcessor):
+    """
+    Processor for operators where the second input type is used in a typed kernel registration.
+    """
+
+    def __init__(self, domain: str, optype: str):
+        # init with tracking of input 1 only.
+        super().__init__(domain, optype, inputs=[1], outputs=[])
+
+    def is_typed_registration_needed(self, type_in_registration: str, globally_allowed_types: set[str] | None):
+        return self.is_input_type_enabled(type_in_registration, 1, globally_allowed_types)
+
+
+class Output0TypedRegistrationProcessor(DefaultTypeUsageProcessor):
+    """
+    Processor for operators where the first output type is used in a typed kernel registration.
+    """
+
+    def __init__(self, domain: str, optype: str):
+        # init with tracking of output 0 only.
+        super().__init__(domain, optype, inputs=[], outputs=[0])
+
+    def is_typed_registration_needed(self, type_in_registration: str, globally_allowed_types: set[str] | None):
+        return self.is_output_type_enabled(type_in_registration, 0, globally_allowed_types)
+
+
+class OneHotProcessor(TypeUsageProcessor):
+    """
+    Processor for the OneHot operator, which requires custom logic as the type registration key is a concatenation of
+    the three types involved instead of a single type name.
+    """
+
+    def __init__(self):
+        super().__init__("ai.onnx", "OneHot")
+        self._triples = set()
+
+    def process_node(self, node: fbs.Node, value_name_to_typeinfo: dict):
+        type0 = value_name_to_typestr(node.Inputs(0), value_name_to_typeinfo)
+        type1 = value_name_to_typestr(node.Inputs(1), value_name_to_typeinfo)
+        type2 = value_name_to_typestr(node.Inputs(2), value_name_to_typeinfo)
+        # types in kernel registration are ordered this way: input (T1), output (T3), depth (T2)
+        key = (type0, type2, type1)
+        self._triples.add(key)
+
+    def is_typed_registration_needed(self, type_in_registration: str, globally_allowed_types: set[str] | None):
+        # the OneHot registration involves a concatenation of the 3 types involved
+        reg_types = tuple([_reg_type_to_cpp_type(reg_type) for reg_type in _split_reg_types(type_in_registration)])
+        if globally_allowed_types is not None:
+            return all(reg_type in globally_allowed_types for reg_type in reg_types)
+        else:
+            return reg_types in self._triples
+
+    def to_config_entry(self):
+        if not self._triples:
+            return None
+
+        aggregate_info = {"custom": sorted(self._triples)}
+        entry = json.dumps(aggregate_info)
+        return entry
+
+    def from_config_entry(self, entry: str):
+        self._triples.clear()
+        aggregate_info = json.loads(entry)
+        if "custom" in aggregate_info:
+            self._triples = {tuple(triple) for triple in aggregate_info["custom"]}
+
+
+def _create_operator_type_usage_processors():
+    """
+    Create a set of processors that determine the required types for all enabled operators.
+    :return: Dictionary of operator key to processor. Key is 'domain:operator (e.g. ai.onnx:Cast)'.
+    """
+    operator_processors = {}
+
+    def add(processor):
+        if processor.name in operator_processors:
+            raise RuntimeError("Duplicate processor for " + processor.name)
+
+        operator_processors[processor.name] = processor
+
+    # Starting with ops from:
+    #   - Priority 1P models
+    #   - Mobilenet + SSD Mobilenet + MobileBert
+    #   - some known large kernels
+    #
+    # Ops we are ignoring currently so as not to produce meaningless/unused output:
+    # - Implementation is type agnostic:
+    #    ai.onnx: If, Loop, Reshape, Scan, Shape, Squeeze, Tile, Unsqueeze
+    #    com.microsoft: DynamicQuantizeMatMul, MatMulIntegerToFloat
+    # - Only one type supported in the ORT implementation:
+    #    ai.onnx: NonMaxSuppression
+    #    com.microsoft: FusedConv, FusedGemm, FusedMatMul
+    # - Implementation does not have any significant type specific code:
+    #    ai.onnx: Concat, Flatten, Not, Reshape, Shape, Squeeze, Unsqueeze
+    #
+    default_processor_onnx_ops = [
+        "Abs",
+        "ArgMax",
+        "ArgMin",
+        "AveragePool",
+        "BatchNormalization",
+        "BitShift",
+        "Ceil",
+        "Clip",
+        "Conv",
+        "CumSum",
+        "Exp",
+        "Expand",
+        "Floor",
+        "Gemm",
+        "IsNaN",
+        "Log",
+        "LogSoftmax",
+        "LpNormalization",
+        "MatMul",
+        "Max",
+        "MaxPool",
+        "Mean",
+        "Min",
+        "NonZero",
+        "Pad",
+        "QLinearConv",
+        "QLinearMatMul",
+        "Range",
+        "Reciprocal",
+        "ReduceL1",
+        "ReduceL2",
+        "ReduceLogSum",
+        "ReduceLogSumExp",
+        "ReduceMax",
+        "ReduceMean",
+        "ReduceMin",
+        "ReduceProd",
+        "ReduceSum",
+        "ReduceSumSquare",
+        "Relu",
+        "Resize",
+        "ReverseSequence",
+        "RoiAlign",
+        "Round",
+        "Scatter",
+        "ScatterElements",
+        "ScatterND",
+        "Shrink",
+        "Sigmoid",
+        "Sign",
+        "Sin",
+        "Softmax",
+        "Split",
+        "SplitToSequence",
+        "Sqrt",
+        "Sum",
+        "Tanh",
+        "TopK",
+        "Transpose",
+        "Unique",
+    ]
+
+    # ops that are used to manipulate shapes or indices so require int32_t and int64_t to be available
+    default_processor_onnx_ops_requiring_ints_for_input_0 = [
+        "Add",
+        "Concat",
+        "Div",
+        "Equal",
+        "Greater",
+        "Less",
+        "Mul",
+        "Neg",  # used in tflite TransposeConv conversion
+        "Sub",
+    ]
+
+    # NOTE: QLinearConv has ONNX and internal implementations
+    internal_ops = ["QLinearAdd", "QLinearMul", "QLinearConv"]
+
+    # TODO - review and add ML ops as needed
+    # ML Op notes.
+    #  CastMap: Switch on value type of input map type, and output type
+    #  DictVectorizer: Templatized on key+value of input so need to handle like OneHot with custom processor
+    #  LabelEncoder: Implementation switches on input and output types (only supports string and int64 in T1 and T2)
+    #  LinearClassifier: Internal switch on input type and also switch on output type
+    #  SVMClassifier: ditto
+    #  TreeEnsembleClassifier: Templatized on input type and also switch on output type
+    #  ZipMap: Switch on output type (derived from attributes)
+    default_processor_onnxml_ops = []
+
+    [add(DefaultTypeUsageProcessor("ai.onnx", op)) for op in default_processor_onnx_ops]
+    [
+        add(DefaultTypeUsageProcessor("ai.onnx", op, required_input_types={0: {"int32_t", "int64_t"}}))
+        for op in default_processor_onnx_ops_requiring_ints_for_input_0
+    ]
+    [add(DefaultTypeUsageProcessor("ai.onnx.ml", op)) for op in default_processor_onnxml_ops]
+    [add(DefaultTypeUsageProcessor("com.microsoft", op)) for op in internal_ops]
+
+    #
+    # Operators that require custom handling
+    #
+
+    # Cast switches on types of input 0 and output 0
+    add(DefaultTypeUsageProcessor("ai.onnx", "Cast", inputs=[0], outputs=[0]))
+
+    # Operators that switch on the type of input 0 and 1
+    add(DefaultTypeUsageProcessor("ai.onnx", "Gather", inputs=[0, 1]))
+    add(DefaultTypeUsageProcessor("ai.onnx", "GatherElements", inputs=[0, 1]))
+    add(DefaultTypeUsageProcessor("ai.onnx", "Pow", inputs=[0, 1]))
+    add(DefaultTypeUsageProcessor("ai.onnx", "Slice", inputs=[0, 1]))
+
+    # Operators that switch on output type
+    add(DefaultTypeUsageProcessor("ai.onnx", "ConstantOfShape", inputs=[], outputs=[0]))
+
+    # Random generator ops produce new data so we track the output type
+    onnx_random_ops = ["RandomNormal", "RandomNormalLike", "RandomUniform", "RandomUniformLike", "Multinomial"]
+    [add(DefaultTypeUsageProcessor("ai.onnx", op, inputs=[], outputs=[0])) for op in onnx_random_ops]
+
+    # Where always has a boolean first input so track the second input type for typed registration
+    add(Input1TypedRegistrationProcessor("ai.onnx", "Where"))
+
+    # we only support 'float' as input for [Dynamic]QuantizeLinear so just track the output type
+    # as that's what is used in the typed registration
+    add(Output0TypedRegistrationProcessor("ai.onnx", "QuantizeLinear"))
+    add(Output0TypedRegistrationProcessor("ai.onnx", "DynamicQuantizeLinear"))
+
+    # make sure all the dequantize types are enabled. we use int32_t for parts of GEMM and Conv so just
+    # enabling int8 and uint8 is not enough.
+    # TODO: Only apply required types to the global type list and ignore if it's model based per-op type reduction
+    add(
+        DefaultTypeUsageProcessor(
+            "ai.onnx", "DequantizeLinear", inputs=[0], required_input_types={0: {"int8_t", "uint8_t", "int32_t"}}
+        )
+    )
+
+    # OneHot concatenates type strings into a triple in the typed registration
+    #   e.g. float_int64_t_int64_t
+    add(OneHotProcessor())
+
+    return operator_processors
+
+
+class OpTypeImplFilterInterface(ABC):
+    """
+    Class that filters operator implementations based on type.
+    """
+
+    @abstractmethod
+    def is_typed_registration_needed(self, domain: str, optype: str, type_registration_str: str):
+        """
+        Given the string from a kernel registration, determine if the registration is required or not.
+        :param domain: Operator domain.
+        :param optype: Operator type.
+        :param type_registration_str: Type string from kernel registration
+        :return: True is required. False if not.
+        """
+
+    @abstractmethod
+    def get_cpp_entries(self):
+        """
+        Get the C++ code that specifies the operator types to enable.
+        :return: List of strings. One line of C++ code per entry.
+        """
+
+
+class OperatorTypeUsageManager:
+    """
+    Class to manage the operator type usage processors.
+    TODO: Currently the type tracking is not specific to a version of the operator.
+    It's unclear how/where version specific logic could/should be added, and it would add significant complexity
+    to track types on a per-version basis. Not clear there's enough benefit from doing so either.
+    """
+
+    def __init__(self):
+        self._all_operator_processors = _create_operator_type_usage_processors()  # all possible processors
+        self._operator_processors = {}  # processors we have actually used so we can limit output to be meaningful
+
+    def _get_op_processor(self, key):
+        "Add the processor to _operator_processors as it is about to be used."
+        processor = None
+        if key in self._all_operator_processors:
+            if key not in self._operator_processors:
+                self._operator_processors[key] = self._all_operator_processors[key]
+
+            processor = self._operator_processors[key]
+
+        return processor
+
+    def process_node(self, node: fbs.Node, value_name_to_typeinfo: dict):
+        """
+        Process a Node and record info on the types used.
+        :param node: Node from ORT format model
+        :param value_name_to_typeinfo: Map of value names to TypeInfo instances
+        """
+        optype = node.OpType().decode()
+        domain = node.Domain().decode() or "ai.onnx"  # empty domain defaults to ai.onnx
+
+        key = _create_op_key(domain, optype)
+        op_processor = self._get_op_processor(key)
+        if op_processor:
+            op_processor.process_node(node, value_name_to_typeinfo)
+
+    def get_config_entry(self, domain: str, optype: str):
+        """
+        Get the config entry specifying the types for this operator.
+        :param domain: Operator domain.
+        :param optype: Operator type.
+        :return: JSON string with type info if available, else None
+        """
+        key = _create_op_key(domain, optype)
+        config_str = None
+        if key in self._operator_processors:
+            config_str = self._operator_processors[key].to_config_entry()
+
+        return config_str
+
+    def restore_from_config_entry(self, domain: str, optype: str, config_entry: str):
+        """
+        Restore the per-operator type information from a configuration file entry.
+        :param domain: Operator domain.
+        :param optype: Operator type.
+        :param config_entry: JSON string with type info as created by get_config_entry
+        """
+        key = _create_op_key(domain, optype)
+        op_processor = self._get_op_processor(key)
+        if op_processor:
+            op_processor.from_config_entry(config_entry)
+
+    def debug_dump(self):
+        print("C++ code that will be emitted:")
+        [print(cpp_line) for cpp_line in self.get_cpp_entries()]
+
+        print("Config file type information that will be returned by get_config_entry:")
+        for key in sorted(self._operator_processors.keys()):
+            entry = self._operator_processors[key].to_config_entry()
+            if entry:
+                print(f"{key} -> {entry}")
+
+                # roundtrip test to validate that we can initialize the processor from the entry and get the
+                # same values back
+                self._operator_processors[key].from_config_entry(entry)
+                assert entry == self._operator_processors[key].to_config_entry()
+
+    class _OpTypeImplFilter(OpTypeImplFilterInterface):
+        def __init__(self, manager):
+            self._manager = manager
+
+        def is_typed_registration_needed(self, domain: str, optype: str, type_registration_str: str):
+            needed = True  # we keep the registration unless the per-operator processor says not to
+            key = _create_op_key(domain, optype)
+            if key in self._manager._operator_processors:
+                needed = self._manager._operator_processors[key].is_typed_registration_needed(
+                    type_in_registration=type_registration_str, globally_allowed_types=None
+                )
+
+            return needed
+
+        def get_cpp_entries(self):
+            entries = []
+            for key in sorted(self._manager._operator_processors.keys()):
+                entries.extend(self._manager._operator_processors[key].get_cpp_entry())
+
+            return entries
+
+    def make_op_type_impl_filter(self):
+        """
+        Creates an OpTypeImplFilterInterface instance from this manager.
+        Filtering uses the manager's operator type usage processor state.
+        """
+        return OperatorTypeUsageManager._OpTypeImplFilter(self)
+
+
+class GloballyAllowedTypesOpTypeImplFilter(OpTypeImplFilterInterface):
+    """
+    Operator implementation filter which uses globally allowed types.
+    """
+
+    _valid_allowed_types = set(FbsTypeInfo.tensordatatype_to_string.values())  # noqa: RUF012
+
+    def __init__(self, globally_allowed_types: set[str]):
+        self._operator_processors = _create_operator_type_usage_processors()
+
+        if not globally_allowed_types.issubset(self._valid_allowed_types):
+            raise ValueError(
+                f"Globally allowed types must all be valid. Invalid types: {sorted(globally_allowed_types - self._valid_allowed_types)}"
+            )
+
+        self._globally_allowed_types = globally_allowed_types
+
+    def is_typed_registration_needed(self, domain: str, optype: str, type_registration_str: str):
+        key = _create_op_key(domain, optype)
+        if key in self._operator_processors:
+            needed = self._operator_processors[key].is_typed_registration_needed(
+                type_in_registration=type_registration_str, globally_allowed_types=self._globally_allowed_types
+            )
+        else:
+            needed = _reg_type_to_cpp_type(type_registration_str) in self._globally_allowed_types
+
+        return needed
+
+    def get_cpp_entries(self):
+        return [
+            "ORT_SPECIFY_OP_KERNEL_GLOBAL_ALLOWED_TYPES({});".format(", ".join(sorted(self._globally_allowed_types)))
+        ]
+
+    def global_type_list(self):
+        return self._globally_allowed_types
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/__pycache__/__init__.cpython-313.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..1b8b5f9a6962f7c71150bc1b1b4928cfa0cf7edd
Binary files /dev/null and b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/__pycache__/__init__.cpython-313.pyc differ
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgType.py
new file mode 100644
index 0000000000000000000000000000000000000000..2bdb7f8150bba2509d818a5590a00e0ab565d610
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgType.py
@@ -0,0 +1,7 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class ArgType(object):
+    INPUT = 0
+    OUTPUT = 1
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgTypeAndIndex.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgTypeAndIndex.py
new file mode 100644
index 0000000000000000000000000000000000000000..b4fc858a8ff97640332c0de28fa2b33c9d2cdfb3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ArgTypeAndIndex.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class ArgTypeAndIndex(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = ArgTypeAndIndex()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsArgTypeAndIndex(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ArgTypeAndIndexBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # ArgTypeAndIndex
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # ArgTypeAndIndex
+    def ArgType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int8Flags, o + self._tab.Pos)
+        return 0
+
+    # ArgTypeAndIndex
+    def Index(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+def ArgTypeAndIndexStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    ArgTypeAndIndexStart(builder)
+
+def ArgTypeAndIndexAddArgType(builder, argType):
+    builder.PrependInt8Slot(0, argType, 0)
+
+def AddArgType(builder, argType):
+    ArgTypeAndIndexAddArgType(builder, argType)
+
+def ArgTypeAndIndexAddIndex(builder, index):
+    builder.PrependUint32Slot(1, index, 0)
+
+def AddIndex(builder, index):
+    ArgTypeAndIndexAddIndex(builder, index)
+
+def ArgTypeAndIndexEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ArgTypeAndIndexEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Attribute.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Attribute.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf6f54d72e42263fa707ca5093c4414d94abe612
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Attribute.py
@@ -0,0 +1,337 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Attribute(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Attribute()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsAttribute(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def AttributeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Attribute
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Attribute
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Attribute
+    def DocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Attribute
+    def Type(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # Attribute
+    def F(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos)
+        return 0.0
+
+    # Attribute
+    def I(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+    # Attribute
+    def S(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Attribute
+    def T(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Attribute
+    def G(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Graph import Graph
+            obj = Graph()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Attribute
+    def Floats(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Float32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return 0
+
+    # Attribute
+    def FloatsAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Float32Flags, o)
+        return 0
+
+    # Attribute
+    def FloatsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Attribute
+    def FloatsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        return o == 0
+
+    # Attribute
+    def Ints(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 8))
+        return 0
+
+    # Attribute
+    def IntsAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Int64Flags, o)
+        return 0
+
+    # Attribute
+    def IntsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Attribute
+    def IntsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        return o == 0
+
+    # Attribute
+    def Strings(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Attribute
+    def StringsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Attribute
+    def StringsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        return o == 0
+
+    # Attribute
+    def Tensors(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Attribute
+    def TensorsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Attribute
+    def TensorsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        return o == 0
+
+    # Attribute
+    def Graphs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Graph import Graph
+            obj = Graph()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Attribute
+    def GraphsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Attribute
+    def GraphsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        return o == 0
+
+def AttributeStart(builder):
+    builder.StartObject(13)
+
+def Start(builder):
+    AttributeStart(builder)
+
+def AttributeAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    AttributeAddName(builder, name)
+
+def AttributeAddDocString(builder, docString):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(docString), 0)
+
+def AddDocString(builder, docString):
+    AttributeAddDocString(builder, docString)
+
+def AttributeAddType(builder, type):
+    builder.PrependInt32Slot(2, type, 0)
+
+def AddType(builder, type):
+    AttributeAddType(builder, type)
+
+def AttributeAddF(builder, f):
+    builder.PrependFloat32Slot(3, f, 0.0)
+
+def AddF(builder, f):
+    AttributeAddF(builder, f)
+
+def AttributeAddI(builder, i):
+    builder.PrependInt64Slot(4, i, 0)
+
+def AddI(builder, i):
+    AttributeAddI(builder, i)
+
+def AttributeAddS(builder, s):
+    builder.PrependUOffsetTRelativeSlot(5, flatbuffers.number_types.UOffsetTFlags.py_type(s), 0)
+
+def AddS(builder, s):
+    AttributeAddS(builder, s)
+
+def AttributeAddT(builder, t):
+    builder.PrependUOffsetTRelativeSlot(6, flatbuffers.number_types.UOffsetTFlags.py_type(t), 0)
+
+def AddT(builder, t):
+    AttributeAddT(builder, t)
+
+def AttributeAddG(builder, g):
+    builder.PrependUOffsetTRelativeSlot(7, flatbuffers.number_types.UOffsetTFlags.py_type(g), 0)
+
+def AddG(builder, g):
+    AttributeAddG(builder, g)
+
+def AttributeAddFloats(builder, floats):
+    builder.PrependUOffsetTRelativeSlot(8, flatbuffers.number_types.UOffsetTFlags.py_type(floats), 0)
+
+def AddFloats(builder, floats):
+    AttributeAddFloats(builder, floats)
+
+def AttributeStartFloatsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartFloatsVector(builder, numElems: int) -> int:
+    return AttributeStartFloatsVector(builder, numElems)
+
+def AttributeAddInts(builder, ints):
+    builder.PrependUOffsetTRelativeSlot(9, flatbuffers.number_types.UOffsetTFlags.py_type(ints), 0)
+
+def AddInts(builder, ints):
+    AttributeAddInts(builder, ints)
+
+def AttributeStartIntsVector(builder, numElems):
+    return builder.StartVector(8, numElems, 8)
+
+def StartIntsVector(builder, numElems: int) -> int:
+    return AttributeStartIntsVector(builder, numElems)
+
+def AttributeAddStrings(builder, strings):
+    builder.PrependUOffsetTRelativeSlot(10, flatbuffers.number_types.UOffsetTFlags.py_type(strings), 0)
+
+def AddStrings(builder, strings):
+    AttributeAddStrings(builder, strings)
+
+def AttributeStartStringsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartStringsVector(builder, numElems: int) -> int:
+    return AttributeStartStringsVector(builder, numElems)
+
+def AttributeAddTensors(builder, tensors):
+    builder.PrependUOffsetTRelativeSlot(11, flatbuffers.number_types.UOffsetTFlags.py_type(tensors), 0)
+
+def AddTensors(builder, tensors):
+    AttributeAddTensors(builder, tensors)
+
+def AttributeStartTensorsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartTensorsVector(builder, numElems: int) -> int:
+    return AttributeStartTensorsVector(builder, numElems)
+
+def AttributeAddGraphs(builder, graphs):
+    builder.PrependUOffsetTRelativeSlot(12, flatbuffers.number_types.UOffsetTFlags.py_type(graphs), 0)
+
+def AddGraphs(builder, graphs):
+    AttributeAddGraphs(builder, graphs)
+
+def AttributeStartGraphsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartGraphsVector(builder, numElems: int) -> int:
+    return AttributeStartGraphsVector(builder, numElems)
+
+def AttributeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return AttributeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/AttributeType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/AttributeType.py
new file mode 100644
index 0000000000000000000000000000000000000000..a7ee8309fad0fcf6f886aadc8ae08f16c9d8ca58
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/AttributeType.py
@@ -0,0 +1,18 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class AttributeType(object):
+    UNDEFINED = 0
+    FLOAT = 1
+    INT = 2
+    STRING = 3
+    TENSOR = 4
+    GRAPH = 5
+    FLOATS = 6
+    INTS = 7
+    STRINGS = 8
+    TENSORS = 9
+    GRAPHS = 10
+    SPARSE_TENSOR = 11
+    SPARSE_TENSORS = 12
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Checkpoint.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Checkpoint.py
new file mode 100644
index 0000000000000000000000000000000000000000..b8ace29fdaf79ac4083e1b894e8e9ca007bffd71
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Checkpoint.py
@@ -0,0 +1,125 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Checkpoint(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Checkpoint()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsCheckpoint(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def CheckpointBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # Checkpoint
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Checkpoint
+    def Version(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # Checkpoint
+    def ModuleState(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.ModuleState import ModuleState
+            obj = ModuleState()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Checkpoint
+    def OptimizerGroups(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.OptimizerGroup import OptimizerGroup
+            obj = OptimizerGroup()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Checkpoint
+    def OptimizerGroupsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Checkpoint
+    def OptimizerGroupsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+    # Checkpoint
+    def PropertyBag(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.PropertyBag import PropertyBag
+            obj = PropertyBag()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def CheckpointStart(builder):
+    builder.StartObject(4)
+
+def Start(builder):
+    CheckpointStart(builder)
+
+def CheckpointAddVersion(builder, version):
+    builder.PrependInt32Slot(0, version, 0)
+
+def AddVersion(builder, version):
+    CheckpointAddVersion(builder, version)
+
+def CheckpointAddModuleState(builder, moduleState):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(moduleState), 0)
+
+def AddModuleState(builder, moduleState):
+    CheckpointAddModuleState(builder, moduleState)
+
+def CheckpointAddOptimizerGroups(builder, optimizerGroups):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(optimizerGroups), 0)
+
+def AddOptimizerGroups(builder, optimizerGroups):
+    CheckpointAddOptimizerGroups(builder, optimizerGroups)
+
+def CheckpointStartOptimizerGroupsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOptimizerGroupsVector(builder, numElems: int) -> int:
+    return CheckpointStartOptimizerGroupsVector(builder, numElems)
+
+def CheckpointAddPropertyBag(builder, propertyBag):
+    builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(propertyBag), 0)
+
+def AddPropertyBag(builder, propertyBag):
+    CheckpointAddPropertyBag(builder, propertyBag)
+
+def CheckpointEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return CheckpointEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedKernelCreateInfos.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedKernelCreateInfos.py
new file mode 100644
index 0000000000000000000000000000000000000000..e7640b4829893b290988dbff53149267f065cd13
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedKernelCreateInfos.py
@@ -0,0 +1,120 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# deprecated: no longer using kernel def hashes
+class DeprecatedKernelCreateInfos(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = DeprecatedKernelCreateInfos()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDeprecatedKernelCreateInfos(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DeprecatedKernelCreateInfosBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # DeprecatedKernelCreateInfos
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # DeprecatedKernelCreateInfos
+    def NodeIndices(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def NodeIndicesAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint32Flags, o)
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def NodeIndicesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def NodeIndicesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+    # DeprecatedKernelCreateInfos
+    def KernelDefHashes(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Uint64Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 8))
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def KernelDefHashesAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint64Flags, o)
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def KernelDefHashesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # DeprecatedKernelCreateInfos
+    def KernelDefHashesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def DeprecatedKernelCreateInfosStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    DeprecatedKernelCreateInfosStart(builder)
+
+def DeprecatedKernelCreateInfosAddNodeIndices(builder, nodeIndices):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(nodeIndices), 0)
+
+def AddNodeIndices(builder, nodeIndices):
+    DeprecatedKernelCreateInfosAddNodeIndices(builder, nodeIndices)
+
+def DeprecatedKernelCreateInfosStartNodeIndicesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartNodeIndicesVector(builder, numElems: int) -> int:
+    return DeprecatedKernelCreateInfosStartNodeIndicesVector(builder, numElems)
+
+def DeprecatedKernelCreateInfosAddKernelDefHashes(builder, kernelDefHashes):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(kernelDefHashes), 0)
+
+def AddKernelDefHashes(builder, kernelDefHashes):
+    DeprecatedKernelCreateInfosAddKernelDefHashes(builder, kernelDefHashes)
+
+def DeprecatedKernelCreateInfosStartKernelDefHashesVector(builder, numElems):
+    return builder.StartVector(8, numElems, 8)
+
+def StartKernelDefHashesVector(builder, numElems: int) -> int:
+    return DeprecatedKernelCreateInfosStartKernelDefHashesVector(builder, numElems)
+
+def DeprecatedKernelCreateInfosEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DeprecatedKernelCreateInfosEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedNodeIndexAndKernelDefHash.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedNodeIndexAndKernelDefHash.py
new file mode 100644
index 0000000000000000000000000000000000000000..ca5620aa6ae20e6cbfeb6316670002a95eb73370
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedNodeIndexAndKernelDefHash.py
@@ -0,0 +1,68 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# deprecated: no longer using kernel def hashes
+class DeprecatedNodeIndexAndKernelDefHash(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = DeprecatedNodeIndexAndKernelDefHash()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDeprecatedNodeIndexAndKernelDefHash(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DeprecatedNodeIndexAndKernelDefHashBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # DeprecatedNodeIndexAndKernelDefHash
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # DeprecatedNodeIndexAndKernelDefHash
+    def NodeIndex(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # DeprecatedNodeIndexAndKernelDefHash
+    def KernelDefHash(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint64Flags, o + self._tab.Pos)
+        return 0
+
+def DeprecatedNodeIndexAndKernelDefHashStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    DeprecatedNodeIndexAndKernelDefHashStart(builder)
+
+def DeprecatedNodeIndexAndKernelDefHashAddNodeIndex(builder, nodeIndex):
+    builder.PrependUint32Slot(0, nodeIndex, 0)
+
+def AddNodeIndex(builder, nodeIndex):
+    DeprecatedNodeIndexAndKernelDefHashAddNodeIndex(builder, nodeIndex)
+
+def DeprecatedNodeIndexAndKernelDefHashAddKernelDefHash(builder, kernelDefHash):
+    builder.PrependUint64Slot(1, kernelDefHash, 0)
+
+def AddKernelDefHash(builder, kernelDefHash):
+    DeprecatedNodeIndexAndKernelDefHashAddKernelDefHash(builder, kernelDefHash)
+
+def DeprecatedNodeIndexAndKernelDefHashEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DeprecatedNodeIndexAndKernelDefHashEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSessionState.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSessionState.py
new file mode 100644
index 0000000000000000000000000000000000000000..3700cf196b755628a146e7aa69fbce33846d5000
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSessionState.py
@@ -0,0 +1,96 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# deprecated: no longer using kernel def hashes
+class DeprecatedSessionState(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = DeprecatedSessionState()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDeprecatedSessionState(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DeprecatedSessionStateBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # DeprecatedSessionState
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # DeprecatedSessionState
+    def Kernels(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.DeprecatedKernelCreateInfos import DeprecatedKernelCreateInfos
+            obj = DeprecatedKernelCreateInfos()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # DeprecatedSessionState
+    def SubGraphSessionStates(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.DeprecatedSubGraphSessionState import DeprecatedSubGraphSessionState
+            obj = DeprecatedSubGraphSessionState()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # DeprecatedSessionState
+    def SubGraphSessionStatesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # DeprecatedSessionState
+    def SubGraphSessionStatesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def DeprecatedSessionStateStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    DeprecatedSessionStateStart(builder)
+
+def DeprecatedSessionStateAddKernels(builder, kernels):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(kernels), 0)
+
+def AddKernels(builder, kernels):
+    DeprecatedSessionStateAddKernels(builder, kernels)
+
+def DeprecatedSessionStateAddSubGraphSessionStates(builder, subGraphSessionStates):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(subGraphSessionStates), 0)
+
+def AddSubGraphSessionStates(builder, subGraphSessionStates):
+    DeprecatedSessionStateAddSubGraphSessionStates(builder, subGraphSessionStates)
+
+def DeprecatedSessionStateStartSubGraphSessionStatesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartSubGraphSessionStatesVector(builder, numElems: int) -> int:
+    return DeprecatedSessionStateStartSubGraphSessionStatesVector(builder, numElems)
+
+def DeprecatedSessionStateEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DeprecatedSessionStateEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSubGraphSessionState.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSubGraphSessionState.py
new file mode 100644
index 0000000000000000000000000000000000000000..42f2e566b3e5d201f3f75edac52c982767776f76
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DeprecatedSubGraphSessionState.py
@@ -0,0 +1,72 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# deprecated: no longer using kernel def hashes
+class DeprecatedSubGraphSessionState(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = DeprecatedSubGraphSessionState()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDeprecatedSubGraphSessionState(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DeprecatedSubGraphSessionStateBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # DeprecatedSubGraphSessionState
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # DeprecatedSubGraphSessionState
+    def GraphId(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # DeprecatedSubGraphSessionState
+    def SessionState(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.DeprecatedSessionState import DeprecatedSessionState
+            obj = DeprecatedSessionState()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def DeprecatedSubGraphSessionStateStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    DeprecatedSubGraphSessionStateStart(builder)
+
+def DeprecatedSubGraphSessionStateAddGraphId(builder, graphId):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(graphId), 0)
+
+def AddGraphId(builder, graphId):
+    DeprecatedSubGraphSessionStateAddGraphId(builder, graphId)
+
+def DeprecatedSubGraphSessionStateAddSessionState(builder, sessionState):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(sessionState), 0)
+
+def AddSessionState(builder, sessionState):
+    DeprecatedSubGraphSessionStateAddSessionState(builder, sessionState)
+
+def DeprecatedSubGraphSessionStateEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DeprecatedSubGraphSessionStateEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Dimension.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Dimension.py
new file mode 100644
index 0000000000000000000000000000000000000000..275d333d748f2f484f910962f0fc0793c97f8e9f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Dimension.py
@@ -0,0 +1,71 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Dimension(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Dimension()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDimension(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DimensionBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Dimension
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Dimension
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.DimensionValue import DimensionValue
+            obj = DimensionValue()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Dimension
+    def Denotation(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+def DimensionStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    DimensionStart(builder)
+
+def DimensionAddValue(builder, value):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(value), 0)
+
+def AddValue(builder, value):
+    DimensionAddValue(builder, value)
+
+def DimensionAddDenotation(builder, denotation):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(denotation), 0)
+
+def AddDenotation(builder, denotation):
+    DimensionAddDenotation(builder, denotation)
+
+def DimensionEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DimensionEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValue.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValue.py
new file mode 100644
index 0000000000000000000000000000000000000000..c49473b58829c247ca12c293cf9fbdf8ad805fac
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValue.py
@@ -0,0 +1,80 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class DimensionValue(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = DimensionValue()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsDimensionValue(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def DimensionValueBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # DimensionValue
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # DimensionValue
+    def DimType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int8Flags, o + self._tab.Pos)
+        return 0
+
+    # DimensionValue
+    def DimValue(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+    # DimensionValue
+    def DimParam(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+def DimensionValueStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    DimensionValueStart(builder)
+
+def DimensionValueAddDimType(builder, dimType):
+    builder.PrependInt8Slot(0, dimType, 0)
+
+def AddDimType(builder, dimType):
+    DimensionValueAddDimType(builder, dimType)
+
+def DimensionValueAddDimValue(builder, dimValue):
+    builder.PrependInt64Slot(1, dimValue, 0)
+
+def AddDimValue(builder, dimValue):
+    DimensionValueAddDimValue(builder, dimValue)
+
+def DimensionValueAddDimParam(builder, dimParam):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(dimParam), 0)
+
+def AddDimParam(builder, dimParam):
+    DimensionValueAddDimParam(builder, dimParam)
+
+def DimensionValueEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return DimensionValueEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValueType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValueType.py
new file mode 100644
index 0000000000000000000000000000000000000000..36d33bd9dd6526cc81afd283908b7a38ef96c3a8
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/DimensionValueType.py
@@ -0,0 +1,8 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class DimensionValueType(object):
+    UNKNOWN = 0
+    VALUE = 1
+    PARAM = 2
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/EdgeEnd.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/EdgeEnd.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac3afdf150d5268a3455569a8233b4daf04e0b6b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/EdgeEnd.py
@@ -0,0 +1,32 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class EdgeEnd(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def SizeOf(cls):
+        return 12
+
+    # EdgeEnd
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # EdgeEnd
+    def NodeIndex(self): return self._tab.Get(flatbuffers.number_types.Uint32Flags, self._tab.Pos + flatbuffers.number_types.UOffsetTFlags.py_type(0))
+    # EdgeEnd
+    def SrcArgIndex(self): return self._tab.Get(flatbuffers.number_types.Int32Flags, self._tab.Pos + flatbuffers.number_types.UOffsetTFlags.py_type(4))
+    # EdgeEnd
+    def DstArgIndex(self): return self._tab.Get(flatbuffers.number_types.Int32Flags, self._tab.Pos + flatbuffers.number_types.UOffsetTFlags.py_type(8))
+
+def CreateEdgeEnd(builder, nodeIndex, srcArgIndex, dstArgIndex):
+    builder.Prep(4, 12)
+    builder.PrependInt32(dstArgIndex)
+    builder.PrependInt32(srcArgIndex)
+    builder.PrependUint32(nodeIndex)
+    return builder.Offset()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/FloatProperty.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/FloatProperty.py
new file mode 100644
index 0000000000000000000000000000000000000000..36976711fcf65e34908f13e7f0bf7849e0589b20
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/FloatProperty.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class FloatProperty(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = FloatProperty()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsFloatProperty(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def FloatPropertyBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # FloatProperty
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # FloatProperty
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # FloatProperty
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos)
+        return 0.0
+
+def FloatPropertyStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    FloatPropertyStart(builder)
+
+def FloatPropertyAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    FloatPropertyAddName(builder, name)
+
+def FloatPropertyAddValue(builder, value):
+    builder.PrependFloat32Slot(1, value, 0.0)
+
+def AddValue(builder, value):
+    FloatPropertyAddValue(builder, value)
+
+def FloatPropertyEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return FloatPropertyEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Graph.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Graph.py
new file mode 100644
index 0000000000000000000000000000000000000000..800d3184d0a3e40c35c315400cb1595ce1c61508
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Graph.py
@@ -0,0 +1,320 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Graph(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Graph()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsGraph(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def GraphBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Graph
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Graph
+    def Initializers(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Graph
+    def InitializersLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def InitializersIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+    # Graph
+    def NodeArgs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.ValueInfo import ValueInfo
+            obj = ValueInfo()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Graph
+    def NodeArgsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def NodeArgsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+    # Graph
+    def Nodes(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Node import Node
+            obj = Node()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Graph
+    def NodesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def NodesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+    # Graph
+    def MaxNodeIndex(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # Graph
+    def NodeEdges(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.NodeEdge import NodeEdge
+            obj = NodeEdge()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Graph
+    def NodeEdgesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def NodeEdgesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        return o == 0
+
+    # Graph
+    def Inputs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Graph
+    def InputsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def InputsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        return o == 0
+
+    # Graph
+    def Outputs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Graph
+    def OutputsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def OutputsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        return o == 0
+
+    # Graph
+    def SparseInitializers(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.SparseTensor import SparseTensor
+            obj = SparseTensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Graph
+    def SparseInitializersLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Graph
+    def SparseInitializersIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        return o == 0
+
+    # Graph
+    def RuntimeOptimizations(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.RuntimeOptimizations import RuntimeOptimizations
+            obj = RuntimeOptimizations()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def GraphStart(builder):
+    builder.StartObject(9)
+
+def Start(builder):
+    GraphStart(builder)
+
+def GraphAddInitializers(builder, initializers):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(initializers), 0)
+
+def AddInitializers(builder, initializers):
+    GraphAddInitializers(builder, initializers)
+
+def GraphStartInitializersVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartInitializersVector(builder, numElems: int) -> int:
+    return GraphStartInitializersVector(builder, numElems)
+
+def GraphAddNodeArgs(builder, nodeArgs):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(nodeArgs), 0)
+
+def AddNodeArgs(builder, nodeArgs):
+    GraphAddNodeArgs(builder, nodeArgs)
+
+def GraphStartNodeArgsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartNodeArgsVector(builder, numElems: int) -> int:
+    return GraphStartNodeArgsVector(builder, numElems)
+
+def GraphAddNodes(builder, nodes):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(nodes), 0)
+
+def AddNodes(builder, nodes):
+    GraphAddNodes(builder, nodes)
+
+def GraphStartNodesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartNodesVector(builder, numElems: int) -> int:
+    return GraphStartNodesVector(builder, numElems)
+
+def GraphAddMaxNodeIndex(builder, maxNodeIndex):
+    builder.PrependUint32Slot(3, maxNodeIndex, 0)
+
+def AddMaxNodeIndex(builder, maxNodeIndex):
+    GraphAddMaxNodeIndex(builder, maxNodeIndex)
+
+def GraphAddNodeEdges(builder, nodeEdges):
+    builder.PrependUOffsetTRelativeSlot(4, flatbuffers.number_types.UOffsetTFlags.py_type(nodeEdges), 0)
+
+def AddNodeEdges(builder, nodeEdges):
+    GraphAddNodeEdges(builder, nodeEdges)
+
+def GraphStartNodeEdgesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartNodeEdgesVector(builder, numElems: int) -> int:
+    return GraphStartNodeEdgesVector(builder, numElems)
+
+def GraphAddInputs(builder, inputs):
+    builder.PrependUOffsetTRelativeSlot(5, flatbuffers.number_types.UOffsetTFlags.py_type(inputs), 0)
+
+def AddInputs(builder, inputs):
+    GraphAddInputs(builder, inputs)
+
+def GraphStartInputsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartInputsVector(builder, numElems: int) -> int:
+    return GraphStartInputsVector(builder, numElems)
+
+def GraphAddOutputs(builder, outputs):
+    builder.PrependUOffsetTRelativeSlot(6, flatbuffers.number_types.UOffsetTFlags.py_type(outputs), 0)
+
+def AddOutputs(builder, outputs):
+    GraphAddOutputs(builder, outputs)
+
+def GraphStartOutputsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOutputsVector(builder, numElems: int) -> int:
+    return GraphStartOutputsVector(builder, numElems)
+
+def GraphAddSparseInitializers(builder, sparseInitializers):
+    builder.PrependUOffsetTRelativeSlot(7, flatbuffers.number_types.UOffsetTFlags.py_type(sparseInitializers), 0)
+
+def AddSparseInitializers(builder, sparseInitializers):
+    GraphAddSparseInitializers(builder, sparseInitializers)
+
+def GraphStartSparseInitializersVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartSparseInitializersVector(builder, numElems: int) -> int:
+    return GraphStartSparseInitializersVector(builder, numElems)
+
+def GraphAddRuntimeOptimizations(builder, runtimeOptimizations):
+    builder.PrependUOffsetTRelativeSlot(8, flatbuffers.number_types.UOffsetTFlags.py_type(runtimeOptimizations), 0)
+
+def AddRuntimeOptimizations(builder, runtimeOptimizations):
+    GraphAddRuntimeOptimizations(builder, runtimeOptimizations)
+
+def GraphEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return GraphEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/InferenceSession.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/InferenceSession.py
new file mode 100644
index 0000000000000000000000000000000000000000..3ad173a21330aad11fee6b9f69bff743e8e81bd3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/InferenceSession.py
@@ -0,0 +1,88 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class InferenceSession(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = InferenceSession()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsInferenceSession(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def InferenceSessionBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # InferenceSession
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # InferenceSession
+    def OrtVersion(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # InferenceSession
+    def Model(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Model import Model
+            obj = Model()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # InferenceSession
+    def KernelTypeStrResolver(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.KernelTypeStrResolver import KernelTypeStrResolver
+            obj = KernelTypeStrResolver()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def InferenceSessionStart(builder):
+    builder.StartObject(4)
+
+def Start(builder):
+    InferenceSessionStart(builder)
+
+def InferenceSessionAddOrtVersion(builder, ortVersion):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(ortVersion), 0)
+
+def AddOrtVersion(builder, ortVersion):
+    InferenceSessionAddOrtVersion(builder, ortVersion)
+
+def InferenceSessionAddModel(builder, model):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(model), 0)
+
+def AddModel(builder, model):
+    InferenceSessionAddModel(builder, model)
+
+def InferenceSessionAddKernelTypeStrResolver(builder, kernelTypeStrResolver):
+    builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(kernelTypeStrResolver), 0)
+
+def AddKernelTypeStrResolver(builder, kernelTypeStrResolver):
+    InferenceSessionAddKernelTypeStrResolver(builder, kernelTypeStrResolver)
+
+def InferenceSessionEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return InferenceSessionEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/IntProperty.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/IntProperty.py
new file mode 100644
index 0000000000000000000000000000000000000000..9fb55c642fb9061f9965ebddae46db4b852a32e3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/IntProperty.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class IntProperty(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = IntProperty()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsIntProperty(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def IntPropertyBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # IntProperty
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # IntProperty
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # IntProperty
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+def IntPropertyStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    IntPropertyStart(builder)
+
+def IntPropertyAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    IntPropertyAddName(builder, name)
+
+def IntPropertyAddValue(builder, value):
+    builder.PrependInt64Slot(1, value, 0)
+
+def AddValue(builder, value):
+    IntPropertyAddValue(builder, value)
+
+def IntPropertyEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return IntPropertyEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrArgsEntry.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrArgsEntry.py
new file mode 100644
index 0000000000000000000000000000000000000000..2279fe444729e98b2eef99ed9c9aef22a1f16b84
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrArgsEntry.py
@@ -0,0 +1,91 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class KernelTypeStrArgsEntry(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = KernelTypeStrArgsEntry()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsKernelTypeStrArgsEntry(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def KernelTypeStrArgsEntryBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # KernelTypeStrArgsEntry
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # KernelTypeStrArgsEntry
+    def KernelTypeStr(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # KernelTypeStrArgsEntry
+    def Args(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.ArgTypeAndIndex import ArgTypeAndIndex
+            obj = ArgTypeAndIndex()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # KernelTypeStrArgsEntry
+    def ArgsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # KernelTypeStrArgsEntry
+    def ArgsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def KernelTypeStrArgsEntryStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    KernelTypeStrArgsEntryStart(builder)
+
+def KernelTypeStrArgsEntryAddKernelTypeStr(builder, kernelTypeStr):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(kernelTypeStr), 0)
+
+def AddKernelTypeStr(builder, kernelTypeStr):
+    KernelTypeStrArgsEntryAddKernelTypeStr(builder, kernelTypeStr)
+
+def KernelTypeStrArgsEntryAddArgs(builder, args):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(args), 0)
+
+def AddArgs(builder, args):
+    KernelTypeStrArgsEntryAddArgs(builder, args)
+
+def KernelTypeStrArgsEntryStartArgsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartArgsVector(builder, numElems: int) -> int:
+    return KernelTypeStrArgsEntryStartArgsVector(builder, numElems)
+
+def KernelTypeStrArgsEntryEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return KernelTypeStrArgsEntryEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrResolver.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrResolver.py
new file mode 100644
index 0000000000000000000000000000000000000000..cee565f1ae8b3d5eacfabb47032aa30db188983a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/KernelTypeStrResolver.py
@@ -0,0 +1,78 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class KernelTypeStrResolver(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = KernelTypeStrResolver()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsKernelTypeStrResolver(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def KernelTypeStrResolverBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # KernelTypeStrResolver
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # KernelTypeStrResolver
+    def OpKernelTypeStrArgs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.OpIdKernelTypeStrArgsEntry import OpIdKernelTypeStrArgsEntry
+            obj = OpIdKernelTypeStrArgsEntry()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # KernelTypeStrResolver
+    def OpKernelTypeStrArgsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # KernelTypeStrResolver
+    def OpKernelTypeStrArgsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+def KernelTypeStrResolverStart(builder):
+    builder.StartObject(1)
+
+def Start(builder):
+    KernelTypeStrResolverStart(builder)
+
+def KernelTypeStrResolverAddOpKernelTypeStrArgs(builder, opKernelTypeStrArgs):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(opKernelTypeStrArgs), 0)
+
+def AddOpKernelTypeStrArgs(builder, opKernelTypeStrArgs):
+    KernelTypeStrResolverAddOpKernelTypeStrArgs(builder, opKernelTypeStrArgs)
+
+def KernelTypeStrResolverStartOpKernelTypeStrArgsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOpKernelTypeStrArgsVector(builder, numElems: int) -> int:
+    return KernelTypeStrResolverStartOpKernelTypeStrArgsVector(builder, numElems)
+
+def KernelTypeStrResolverEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return KernelTypeStrResolverEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/MapType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/MapType.py
new file mode 100644
index 0000000000000000000000000000000000000000..d7ff8fef4d2bd4224d459af504e9e44fe2aa0497
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/MapType.py
@@ -0,0 +1,71 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class MapType(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = MapType()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsMapType(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def MapTypeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # MapType
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # MapType
+    def KeyType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # MapType
+    def ValueType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.TypeInfo import TypeInfo
+            obj = TypeInfo()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def MapTypeStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    MapTypeStart(builder)
+
+def MapTypeAddKeyType(builder, keyType):
+    builder.PrependInt32Slot(0, keyType, 0)
+
+def AddKeyType(builder, keyType):
+    MapTypeAddKeyType(builder, keyType)
+
+def MapTypeAddValueType(builder, valueType):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(valueType), 0)
+
+def AddValueType(builder, valueType):
+    MapTypeAddValueType(builder, valueType)
+
+def MapTypeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return MapTypeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Model.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Model.py
new file mode 100644
index 0000000000000000000000000000000000000000..b1ab985851323f2ebabb28e81cfd97fb5c2179c7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Model.py
@@ -0,0 +1,223 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Model(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Model()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsModel(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ModelBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Model
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Model
+    def IrVersion(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+    # Model
+    def OpsetImport(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.OperatorSetId import OperatorSetId
+            obj = OperatorSetId()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Model
+    def OpsetImportLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Model
+    def OpsetImportIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+    # Model
+    def ProducerName(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Model
+    def ProducerVersion(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Model
+    def Domain(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Model
+    def ModelVersion(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+    # Model
+    def DocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Model
+    def Graph(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Graph import Graph
+            obj = Graph()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Model
+    def GraphDocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Model
+    def MetadataProps(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.StringStringEntry import StringStringEntry
+            obj = StringStringEntry()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Model
+    def MetadataPropsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Model
+    def MetadataPropsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        return o == 0
+
+def ModelStart(builder):
+    builder.StartObject(10)
+
+def Start(builder):
+    ModelStart(builder)
+
+def ModelAddIrVersion(builder, irVersion):
+    builder.PrependInt64Slot(0, irVersion, 0)
+
+def AddIrVersion(builder, irVersion):
+    ModelAddIrVersion(builder, irVersion)
+
+def ModelAddOpsetImport(builder, opsetImport):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(opsetImport), 0)
+
+def AddOpsetImport(builder, opsetImport):
+    ModelAddOpsetImport(builder, opsetImport)
+
+def ModelStartOpsetImportVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOpsetImportVector(builder, numElems: int) -> int:
+    return ModelStartOpsetImportVector(builder, numElems)
+
+def ModelAddProducerName(builder, producerName):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(producerName), 0)
+
+def AddProducerName(builder, producerName):
+    ModelAddProducerName(builder, producerName)
+
+def ModelAddProducerVersion(builder, producerVersion):
+    builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(producerVersion), 0)
+
+def AddProducerVersion(builder, producerVersion):
+    ModelAddProducerVersion(builder, producerVersion)
+
+def ModelAddDomain(builder, domain):
+    builder.PrependUOffsetTRelativeSlot(4, flatbuffers.number_types.UOffsetTFlags.py_type(domain), 0)
+
+def AddDomain(builder, domain):
+    ModelAddDomain(builder, domain)
+
+def ModelAddModelVersion(builder, modelVersion):
+    builder.PrependInt64Slot(5, modelVersion, 0)
+
+def AddModelVersion(builder, modelVersion):
+    ModelAddModelVersion(builder, modelVersion)
+
+def ModelAddDocString(builder, docString):
+    builder.PrependUOffsetTRelativeSlot(6, flatbuffers.number_types.UOffsetTFlags.py_type(docString), 0)
+
+def AddDocString(builder, docString):
+    ModelAddDocString(builder, docString)
+
+def ModelAddGraph(builder, graph):
+    builder.PrependUOffsetTRelativeSlot(7, flatbuffers.number_types.UOffsetTFlags.py_type(graph), 0)
+
+def AddGraph(builder, graph):
+    ModelAddGraph(builder, graph)
+
+def ModelAddGraphDocString(builder, graphDocString):
+    builder.PrependUOffsetTRelativeSlot(8, flatbuffers.number_types.UOffsetTFlags.py_type(graphDocString), 0)
+
+def AddGraphDocString(builder, graphDocString):
+    ModelAddGraphDocString(builder, graphDocString)
+
+def ModelAddMetadataProps(builder, metadataProps):
+    builder.PrependUOffsetTRelativeSlot(9, flatbuffers.number_types.UOffsetTFlags.py_type(metadataProps), 0)
+
+def AddMetadataProps(builder, metadataProps):
+    ModelAddMetadataProps(builder, metadataProps)
+
+def ModelStartMetadataPropsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartMetadataPropsVector(builder, numElems: int) -> int:
+    return ModelStartMetadataPropsVector(builder, numElems)
+
+def ModelEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ModelEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ModuleState.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ModuleState.py
new file mode 100644
index 0000000000000000000000000000000000000000..b3948e94638d1e6aff7203140f3f4acedbd4e3dd
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ModuleState.py
@@ -0,0 +1,141 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class ModuleState(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = ModuleState()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsModuleState(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ModuleStateBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # ModuleState
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # ModuleState
+    def RequiresGradParams(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # ModuleState
+    def RequiresGradParamsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # ModuleState
+    def RequiresGradParamsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+    # ModuleState
+    def FrozenParams(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # ModuleState
+    def FrozenParamsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # ModuleState
+    def FrozenParamsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+    # ModuleState
+    def IsNominalState(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
+        return False
+
+    # ModuleState
+    def HasExternalData(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
+        return False
+
+def ModuleStateStart(builder):
+    builder.StartObject(4)
+
+def Start(builder):
+    ModuleStateStart(builder)
+
+def ModuleStateAddRequiresGradParams(builder, requiresGradParams):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(requiresGradParams), 0)
+
+def AddRequiresGradParams(builder, requiresGradParams):
+    ModuleStateAddRequiresGradParams(builder, requiresGradParams)
+
+def ModuleStateStartRequiresGradParamsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartRequiresGradParamsVector(builder, numElems: int) -> int:
+    return ModuleStateStartRequiresGradParamsVector(builder, numElems)
+
+def ModuleStateAddFrozenParams(builder, frozenParams):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(frozenParams), 0)
+
+def AddFrozenParams(builder, frozenParams):
+    ModuleStateAddFrozenParams(builder, frozenParams)
+
+def ModuleStateStartFrozenParamsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartFrozenParamsVector(builder, numElems: int) -> int:
+    return ModuleStateStartFrozenParamsVector(builder, numElems)
+
+def ModuleStateAddIsNominalState(builder, isNominalState):
+    builder.PrependBoolSlot(2, isNominalState, 0)
+
+def AddIsNominalState(builder, isNominalState):
+    ModuleStateAddIsNominalState(builder, isNominalState)
+
+def ModuleStateAddHasExternalData(builder, hasExternalData):
+    builder.PrependBoolSlot(3, hasExternalData, 0)
+
+def AddHasExternalData(builder, hasExternalData):
+    ModuleStateAddHasExternalData(builder, hasExternalData)
+
+def ModuleStateEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ModuleStateEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Node.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Node.py
new file mode 100644
index 0000000000000000000000000000000000000000..c78dd92a14a15efbd94cc6187a4918b1ade30aba
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Node.py
@@ -0,0 +1,317 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Node(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Node()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsNode(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def NodeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Node
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Node
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Node
+    def DocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Node
+    def Domain(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Node
+    def SinceVersion(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # Node
+    def Index(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # Node
+    def OpType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Node
+    def Type(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # Node
+    def ExecutionProviderType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(18))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Node
+    def Inputs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Node
+    def InputsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Node
+    def InputsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(20))
+        return o == 0
+
+    # Node
+    def Outputs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Node
+    def OutputsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Node
+    def OutputsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(22))
+        return o == 0
+
+    # Node
+    def Attributes(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Attribute import Attribute
+            obj = Attribute()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Node
+    def AttributesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Node
+    def AttributesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(24))
+        return o == 0
+
+    # Node
+    def InputArgCounts(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return 0
+
+    # Node
+    def InputArgCountsAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Int32Flags, o)
+        return 0
+
+    # Node
+    def InputArgCountsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Node
+    def InputArgCountsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(26))
+        return o == 0
+
+    # Node
+    def ImplicitInputs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Node
+    def ImplicitInputsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Node
+    def ImplicitInputsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(28))
+        return o == 0
+
+def NodeStart(builder):
+    builder.StartObject(13)
+
+def Start(builder):
+    NodeStart(builder)
+
+def NodeAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    NodeAddName(builder, name)
+
+def NodeAddDocString(builder, docString):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(docString), 0)
+
+def AddDocString(builder, docString):
+    NodeAddDocString(builder, docString)
+
+def NodeAddDomain(builder, domain):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(domain), 0)
+
+def AddDomain(builder, domain):
+    NodeAddDomain(builder, domain)
+
+def NodeAddSinceVersion(builder, sinceVersion):
+    builder.PrependInt32Slot(3, sinceVersion, 0)
+
+def AddSinceVersion(builder, sinceVersion):
+    NodeAddSinceVersion(builder, sinceVersion)
+
+def NodeAddIndex(builder, index):
+    builder.PrependUint32Slot(4, index, 0)
+
+def AddIndex(builder, index):
+    NodeAddIndex(builder, index)
+
+def NodeAddOpType(builder, opType):
+    builder.PrependUOffsetTRelativeSlot(5, flatbuffers.number_types.UOffsetTFlags.py_type(opType), 0)
+
+def AddOpType(builder, opType):
+    NodeAddOpType(builder, opType)
+
+def NodeAddType(builder, type):
+    builder.PrependInt32Slot(6, type, 0)
+
+def AddType(builder, type):
+    NodeAddType(builder, type)
+
+def NodeAddExecutionProviderType(builder, executionProviderType):
+    builder.PrependUOffsetTRelativeSlot(7, flatbuffers.number_types.UOffsetTFlags.py_type(executionProviderType), 0)
+
+def AddExecutionProviderType(builder, executionProviderType):
+    NodeAddExecutionProviderType(builder, executionProviderType)
+
+def NodeAddInputs(builder, inputs):
+    builder.PrependUOffsetTRelativeSlot(8, flatbuffers.number_types.UOffsetTFlags.py_type(inputs), 0)
+
+def AddInputs(builder, inputs):
+    NodeAddInputs(builder, inputs)
+
+def NodeStartInputsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartInputsVector(builder, numElems: int) -> int:
+    return NodeStartInputsVector(builder, numElems)
+
+def NodeAddOutputs(builder, outputs):
+    builder.PrependUOffsetTRelativeSlot(9, flatbuffers.number_types.UOffsetTFlags.py_type(outputs), 0)
+
+def AddOutputs(builder, outputs):
+    NodeAddOutputs(builder, outputs)
+
+def NodeStartOutputsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOutputsVector(builder, numElems: int) -> int:
+    return NodeStartOutputsVector(builder, numElems)
+
+def NodeAddAttributes(builder, attributes):
+    builder.PrependUOffsetTRelativeSlot(10, flatbuffers.number_types.UOffsetTFlags.py_type(attributes), 0)
+
+def AddAttributes(builder, attributes):
+    NodeAddAttributes(builder, attributes)
+
+def NodeStartAttributesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartAttributesVector(builder, numElems: int) -> int:
+    return NodeStartAttributesVector(builder, numElems)
+
+def NodeAddInputArgCounts(builder, inputArgCounts):
+    builder.PrependUOffsetTRelativeSlot(11, flatbuffers.number_types.UOffsetTFlags.py_type(inputArgCounts), 0)
+
+def AddInputArgCounts(builder, inputArgCounts):
+    NodeAddInputArgCounts(builder, inputArgCounts)
+
+def NodeStartInputArgCountsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartInputArgCountsVector(builder, numElems: int) -> int:
+    return NodeStartInputArgCountsVector(builder, numElems)
+
+def NodeAddImplicitInputs(builder, implicitInputs):
+    builder.PrependUOffsetTRelativeSlot(12, flatbuffers.number_types.UOffsetTFlags.py_type(implicitInputs), 0)
+
+def AddImplicitInputs(builder, implicitInputs):
+    NodeAddImplicitInputs(builder, implicitInputs)
+
+def NodeStartImplicitInputsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartImplicitInputsVector(builder, numElems: int) -> int:
+    return NodeStartImplicitInputsVector(builder, numElems)
+
+def NodeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return NodeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeEdge.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeEdge.py
new file mode 100644
index 0000000000000000000000000000000000000000..de3fb21eab1fcf601a714da4bd77a1363227a537
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeEdge.py
@@ -0,0 +1,126 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class NodeEdge(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = NodeEdge()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsNodeEdge(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def NodeEdgeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # NodeEdge
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # NodeEdge
+    def NodeIndex(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # NodeEdge
+    def InputEdges(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 12
+            from ort_flatbuffers_py.fbs.EdgeEnd import EdgeEnd
+            obj = EdgeEnd()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # NodeEdge
+    def InputEdgesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # NodeEdge
+    def InputEdgesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+    # NodeEdge
+    def OutputEdges(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 12
+            from ort_flatbuffers_py.fbs.EdgeEnd import EdgeEnd
+            obj = EdgeEnd()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # NodeEdge
+    def OutputEdgesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # NodeEdge
+    def OutputEdgesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+def NodeEdgeStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    NodeEdgeStart(builder)
+
+def NodeEdgeAddNodeIndex(builder, nodeIndex):
+    builder.PrependUint32Slot(0, nodeIndex, 0)
+
+def AddNodeIndex(builder, nodeIndex):
+    NodeEdgeAddNodeIndex(builder, nodeIndex)
+
+def NodeEdgeAddInputEdges(builder, inputEdges):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(inputEdges), 0)
+
+def AddInputEdges(builder, inputEdges):
+    NodeEdgeAddInputEdges(builder, inputEdges)
+
+def NodeEdgeStartInputEdgesVector(builder, numElems):
+    return builder.StartVector(12, numElems, 4)
+
+def StartInputEdgesVector(builder, numElems: int) -> int:
+    return NodeEdgeStartInputEdgesVector(builder, numElems)
+
+def NodeEdgeAddOutputEdges(builder, outputEdges):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(outputEdges), 0)
+
+def AddOutputEdges(builder, outputEdges):
+    NodeEdgeAddOutputEdges(builder, outputEdges)
+
+def NodeEdgeStartOutputEdgesVector(builder, numElems):
+    return builder.StartVector(12, numElems, 4)
+
+def StartOutputEdgesVector(builder, numElems: int) -> int:
+    return NodeEdgeStartOutputEdgesVector(builder, numElems)
+
+def NodeEdgeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return NodeEdgeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeType.py
new file mode 100644
index 0000000000000000000000000000000000000000..031e13dbf0a5d4d957682cdc441e2d82b9306b7c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodeType.py
@@ -0,0 +1,7 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class NodeType(object):
+    Primitive = 0
+    Fused = 1
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodesToOptimizeIndices.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodesToOptimizeIndices.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6aebd1cd30ecd1fb6500c1d76142bf80b818af6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/NodesToOptimizeIndices.py
@@ -0,0 +1,160 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# nodes to consider for a runtime optimization
+# see corresponding type in onnxruntime/core/graph/runtime_optimization_record.h
+class NodesToOptimizeIndices(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = NodesToOptimizeIndices()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsNodesToOptimizeIndices(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def NodesToOptimizeIndicesBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # NodesToOptimizeIndices
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # NodesToOptimizeIndices
+    def NodeIndices(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return 0
+
+    # NodesToOptimizeIndices
+    def NodeIndicesAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint32Flags, o)
+        return 0
+
+    # NodesToOptimizeIndices
+    def NodeIndicesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # NodesToOptimizeIndices
+    def NodeIndicesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+    # NodesToOptimizeIndices
+    def NumInputs(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # NodesToOptimizeIndices
+    def NumOutputs(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # NodesToOptimizeIndices
+    def HasVariadicInput(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
+        return False
+
+    # NodesToOptimizeIndices
+    def HasVariadicOutput(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return bool(self._tab.Get(flatbuffers.number_types.BoolFlags, o + self._tab.Pos))
+        return False
+
+    # NodesToOptimizeIndices
+    def NumVariadicInputs(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+    # NodesToOptimizeIndices
+    def NumVariadicOutputs(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint32Flags, o + self._tab.Pos)
+        return 0
+
+def NodesToOptimizeIndicesStart(builder):
+    builder.StartObject(7)
+
+def Start(builder):
+    NodesToOptimizeIndicesStart(builder)
+
+def NodesToOptimizeIndicesAddNodeIndices(builder, nodeIndices):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(nodeIndices), 0)
+
+def AddNodeIndices(builder, nodeIndices):
+    NodesToOptimizeIndicesAddNodeIndices(builder, nodeIndices)
+
+def NodesToOptimizeIndicesStartNodeIndicesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartNodeIndicesVector(builder, numElems: int) -> int:
+    return NodesToOptimizeIndicesStartNodeIndicesVector(builder, numElems)
+
+def NodesToOptimizeIndicesAddNumInputs(builder, numInputs):
+    builder.PrependUint32Slot(1, numInputs, 0)
+
+def AddNumInputs(builder, numInputs):
+    NodesToOptimizeIndicesAddNumInputs(builder, numInputs)
+
+def NodesToOptimizeIndicesAddNumOutputs(builder, numOutputs):
+    builder.PrependUint32Slot(2, numOutputs, 0)
+
+def AddNumOutputs(builder, numOutputs):
+    NodesToOptimizeIndicesAddNumOutputs(builder, numOutputs)
+
+def NodesToOptimizeIndicesAddHasVariadicInput(builder, hasVariadicInput):
+    builder.PrependBoolSlot(3, hasVariadicInput, 0)
+
+def AddHasVariadicInput(builder, hasVariadicInput):
+    NodesToOptimizeIndicesAddHasVariadicInput(builder, hasVariadicInput)
+
+def NodesToOptimizeIndicesAddHasVariadicOutput(builder, hasVariadicOutput):
+    builder.PrependBoolSlot(4, hasVariadicOutput, 0)
+
+def AddHasVariadicOutput(builder, hasVariadicOutput):
+    NodesToOptimizeIndicesAddHasVariadicOutput(builder, hasVariadicOutput)
+
+def NodesToOptimizeIndicesAddNumVariadicInputs(builder, numVariadicInputs):
+    builder.PrependUint32Slot(5, numVariadicInputs, 0)
+
+def AddNumVariadicInputs(builder, numVariadicInputs):
+    NodesToOptimizeIndicesAddNumVariadicInputs(builder, numVariadicInputs)
+
+def NodesToOptimizeIndicesAddNumVariadicOutputs(builder, numVariadicOutputs):
+    builder.PrependUint32Slot(6, numVariadicOutputs, 0)
+
+def AddNumVariadicOutputs(builder, numVariadicOutputs):
+    NodesToOptimizeIndicesAddNumVariadicOutputs(builder, numVariadicOutputs)
+
+def NodesToOptimizeIndicesEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return NodesToOptimizeIndicesEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OpIdKernelTypeStrArgsEntry.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OpIdKernelTypeStrArgsEntry.py
new file mode 100644
index 0000000000000000000000000000000000000000..75f2732bc1b266da4d7e6b88fe43dfc42d22ee37
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OpIdKernelTypeStrArgsEntry.py
@@ -0,0 +1,91 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class OpIdKernelTypeStrArgsEntry(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = OpIdKernelTypeStrArgsEntry()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsOpIdKernelTypeStrArgsEntry(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def OpIdKernelTypeStrArgsEntryBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # OpIdKernelTypeStrArgsEntry
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # OpIdKernelTypeStrArgsEntry
+    def OpId(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # OpIdKernelTypeStrArgsEntry
+    def KernelTypeStrArgs(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.KernelTypeStrArgsEntry import KernelTypeStrArgsEntry
+            obj = KernelTypeStrArgsEntry()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # OpIdKernelTypeStrArgsEntry
+    def KernelTypeStrArgsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # OpIdKernelTypeStrArgsEntry
+    def KernelTypeStrArgsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def OpIdKernelTypeStrArgsEntryStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    OpIdKernelTypeStrArgsEntryStart(builder)
+
+def OpIdKernelTypeStrArgsEntryAddOpId(builder, opId):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(opId), 0)
+
+def AddOpId(builder, opId):
+    OpIdKernelTypeStrArgsEntryAddOpId(builder, opId)
+
+def OpIdKernelTypeStrArgsEntryAddKernelTypeStrArgs(builder, kernelTypeStrArgs):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(kernelTypeStrArgs), 0)
+
+def AddKernelTypeStrArgs(builder, kernelTypeStrArgs):
+    OpIdKernelTypeStrArgsEntryAddKernelTypeStrArgs(builder, kernelTypeStrArgs)
+
+def OpIdKernelTypeStrArgsEntryStartKernelTypeStrArgsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartKernelTypeStrArgsVector(builder, numElems: int) -> int:
+    return OpIdKernelTypeStrArgsEntryStartKernelTypeStrArgsVector(builder, numElems)
+
+def OpIdKernelTypeStrArgsEntryEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return OpIdKernelTypeStrArgsEntryEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OperatorSetId.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OperatorSetId.py
new file mode 100644
index 0000000000000000000000000000000000000000..1452cfcbf0f8497abd812dc602d138df93efc6fd
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OperatorSetId.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class OperatorSetId(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = OperatorSetId()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsOperatorSetId(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def OperatorSetIdBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # OperatorSetId
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # OperatorSetId
+    def Domain(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # OperatorSetId
+    def Version(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+def OperatorSetIdStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    OperatorSetIdStart(builder)
+
+def OperatorSetIdAddDomain(builder, domain):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(domain), 0)
+
+def AddDomain(builder, domain):
+    OperatorSetIdAddDomain(builder, domain)
+
+def OperatorSetIdAddVersion(builder, version):
+    builder.PrependInt64Slot(1, version, 0)
+
+def AddVersion(builder, version):
+    OperatorSetIdAddVersion(builder, version)
+
+def OperatorSetIdEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return OperatorSetIdEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OptimizerGroup.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OptimizerGroup.py
new file mode 100644
index 0000000000000000000000000000000000000000..e86c97984984b6865389da2e44901495be49e876
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/OptimizerGroup.py
@@ -0,0 +1,117 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class OptimizerGroup(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = OptimizerGroup()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsOptimizerGroup(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def OptimizerGroupBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # OptimizerGroup
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # OptimizerGroup
+    def GroupName(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # OptimizerGroup
+    def Step(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return 0
+
+    # OptimizerGroup
+    def InitialLearningRate(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos)
+        return 0.0
+
+    # OptimizerGroup
+    def OptimizerStates(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.ParameterOptimizerState import ParameterOptimizerState
+            obj = ParameterOptimizerState()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # OptimizerGroup
+    def OptimizerStatesLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # OptimizerGroup
+    def OptimizerStatesIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        return o == 0
+
+def OptimizerGroupStart(builder):
+    builder.StartObject(4)
+
+def Start(builder):
+    OptimizerGroupStart(builder)
+
+def OptimizerGroupAddGroupName(builder, groupName):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(groupName), 0)
+
+def AddGroupName(builder, groupName):
+    OptimizerGroupAddGroupName(builder, groupName)
+
+def OptimizerGroupAddStep(builder, step):
+    builder.PrependInt64Slot(1, step, 0)
+
+def AddStep(builder, step):
+    OptimizerGroupAddStep(builder, step)
+
+def OptimizerGroupAddInitialLearningRate(builder, initialLearningRate):
+    builder.PrependFloat32Slot(2, initialLearningRate, 0.0)
+
+def AddInitialLearningRate(builder, initialLearningRate):
+    OptimizerGroupAddInitialLearningRate(builder, initialLearningRate)
+
+def OptimizerGroupAddOptimizerStates(builder, optimizerStates):
+    builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(optimizerStates), 0)
+
+def AddOptimizerStates(builder, optimizerStates):
+    OptimizerGroupAddOptimizerStates(builder, optimizerStates)
+
+def OptimizerGroupStartOptimizerStatesVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartOptimizerStatesVector(builder, numElems: int) -> int:
+    return OptimizerGroupStartOptimizerStatesVector(builder, numElems)
+
+def OptimizerGroupEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return OptimizerGroupEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ParameterOptimizerState.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ParameterOptimizerState.py
new file mode 100644
index 0000000000000000000000000000000000000000..de6efe4e96ccb4c9008a431d7d41ca08b1138777
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ParameterOptimizerState.py
@@ -0,0 +1,91 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class ParameterOptimizerState(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = ParameterOptimizerState()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsParameterOptimizerState(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ParameterOptimizerStateBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # ParameterOptimizerState
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # ParameterOptimizerState
+    def ParamName(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # ParameterOptimizerState
+    def Momentums(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # ParameterOptimizerState
+    def MomentumsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # ParameterOptimizerState
+    def MomentumsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def ParameterOptimizerStateStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    ParameterOptimizerStateStart(builder)
+
+def ParameterOptimizerStateAddParamName(builder, paramName):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(paramName), 0)
+
+def AddParamName(builder, paramName):
+    ParameterOptimizerStateAddParamName(builder, paramName)
+
+def ParameterOptimizerStateAddMomentums(builder, momentums):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(momentums), 0)
+
+def AddMomentums(builder, momentums):
+    ParameterOptimizerStateAddMomentums(builder, momentums)
+
+def ParameterOptimizerStateStartMomentumsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartMomentumsVector(builder, numElems: int) -> int:
+    return ParameterOptimizerStateStartMomentumsVector(builder, numElems)
+
+def ParameterOptimizerStateEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ParameterOptimizerStateEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/PropertyBag.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/PropertyBag.py
new file mode 100644
index 0000000000000000000000000000000000000000..05c5829d693c0af2c910d3935ab99667b185a42a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/PropertyBag.py
@@ -0,0 +1,152 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class PropertyBag(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = PropertyBag()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsPropertyBag(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def PropertyBagBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # PropertyBag
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # PropertyBag
+    def Ints(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.IntProperty import IntProperty
+            obj = IntProperty()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # PropertyBag
+    def IntsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # PropertyBag
+    def IntsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+    # PropertyBag
+    def Floats(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.FloatProperty import FloatProperty
+            obj = FloatProperty()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # PropertyBag
+    def FloatsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # PropertyBag
+    def FloatsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+    # PropertyBag
+    def Strings(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.StringProperty import StringProperty
+            obj = StringProperty()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # PropertyBag
+    def StringsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # PropertyBag
+    def StringsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+def PropertyBagStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    PropertyBagStart(builder)
+
+def PropertyBagAddInts(builder, ints):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(ints), 0)
+
+def AddInts(builder, ints):
+    PropertyBagAddInts(builder, ints)
+
+def PropertyBagStartIntsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartIntsVector(builder, numElems: int) -> int:
+    return PropertyBagStartIntsVector(builder, numElems)
+
+def PropertyBagAddFloats(builder, floats):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(floats), 0)
+
+def AddFloats(builder, floats):
+    PropertyBagAddFloats(builder, floats)
+
+def PropertyBagStartFloatsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartFloatsVector(builder, numElems: int) -> int:
+    return PropertyBagStartFloatsVector(builder, numElems)
+
+def PropertyBagAddStrings(builder, strings):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(strings), 0)
+
+def AddStrings(builder, strings):
+    PropertyBagAddStrings(builder, strings)
+
+def PropertyBagStartStringsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartStringsVector(builder, numElems: int) -> int:
+    return PropertyBagStartStringsVector(builder, numElems)
+
+def PropertyBagEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return PropertyBagEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecord.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecord.py
new file mode 100644
index 0000000000000000000000000000000000000000..14defa261b8490116ae29290ee37e06df007d37c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecord.py
@@ -0,0 +1,105 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+# a single runtime optimization
+# see corresponding type in onnxruntime/core/graph/runtime_optimization_record.h
+class RuntimeOptimizationRecord(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = RuntimeOptimizationRecord()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsRuntimeOptimizationRecord(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def RuntimeOptimizationRecordBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # RuntimeOptimizationRecord
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # RuntimeOptimizationRecord
+    def ActionId(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # RuntimeOptimizationRecord
+    def NodesToOptimizeIndices(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.NodesToOptimizeIndices import NodesToOptimizeIndices
+            obj = NodesToOptimizeIndices()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # RuntimeOptimizationRecord
+    def ProducedOpIds(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # RuntimeOptimizationRecord
+    def ProducedOpIdsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # RuntimeOptimizationRecord
+    def ProducedOpIdsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        return o == 0
+
+def RuntimeOptimizationRecordStart(builder):
+    builder.StartObject(4)
+
+def Start(builder):
+    RuntimeOptimizationRecordStart(builder)
+
+def RuntimeOptimizationRecordAddActionId(builder, actionId):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(actionId), 0)
+
+def AddActionId(builder, actionId):
+    RuntimeOptimizationRecordAddActionId(builder, actionId)
+
+def RuntimeOptimizationRecordAddNodesToOptimizeIndices(builder, nodesToOptimizeIndices):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(nodesToOptimizeIndices), 0)
+
+def AddNodesToOptimizeIndices(builder, nodesToOptimizeIndices):
+    RuntimeOptimizationRecordAddNodesToOptimizeIndices(builder, nodesToOptimizeIndices)
+
+def RuntimeOptimizationRecordAddProducedOpIds(builder, producedOpIds):
+    builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(producedOpIds), 0)
+
+def AddProducedOpIds(builder, producedOpIds):
+    RuntimeOptimizationRecordAddProducedOpIds(builder, producedOpIds)
+
+def RuntimeOptimizationRecordStartProducedOpIdsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartProducedOpIdsVector(builder, numElems: int) -> int:
+    return RuntimeOptimizationRecordStartProducedOpIdsVector(builder, numElems)
+
+def RuntimeOptimizationRecordEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return RuntimeOptimizationRecordEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecordContainerEntry.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecordContainerEntry.py
new file mode 100644
index 0000000000000000000000000000000000000000..69cda44720a229d19230fd65032e7639c1605f76
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizationRecordContainerEntry.py
@@ -0,0 +1,91 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class RuntimeOptimizationRecordContainerEntry(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = RuntimeOptimizationRecordContainerEntry()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsRuntimeOptimizationRecordContainerEntry(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def RuntimeOptimizationRecordContainerEntryBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # RuntimeOptimizationRecordContainerEntry
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # RuntimeOptimizationRecordContainerEntry
+    def OptimizerName(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # RuntimeOptimizationRecordContainerEntry
+    def RuntimeOptimizationRecords(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.RuntimeOptimizationRecord import RuntimeOptimizationRecord
+            obj = RuntimeOptimizationRecord()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # RuntimeOptimizationRecordContainerEntry
+    def RuntimeOptimizationRecordsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # RuntimeOptimizationRecordContainerEntry
+    def RuntimeOptimizationRecordsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        return o == 0
+
+def RuntimeOptimizationRecordContainerEntryStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    RuntimeOptimizationRecordContainerEntryStart(builder)
+
+def RuntimeOptimizationRecordContainerEntryAddOptimizerName(builder, optimizerName):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(optimizerName), 0)
+
+def AddOptimizerName(builder, optimizerName):
+    RuntimeOptimizationRecordContainerEntryAddOptimizerName(builder, optimizerName)
+
+def RuntimeOptimizationRecordContainerEntryAddRuntimeOptimizationRecords(builder, runtimeOptimizationRecords):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(runtimeOptimizationRecords), 0)
+
+def AddRuntimeOptimizationRecords(builder, runtimeOptimizationRecords):
+    RuntimeOptimizationRecordContainerEntryAddRuntimeOptimizationRecords(builder, runtimeOptimizationRecords)
+
+def RuntimeOptimizationRecordContainerEntryStartRuntimeOptimizationRecordsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartRuntimeOptimizationRecordsVector(builder, numElems: int) -> int:
+    return RuntimeOptimizationRecordContainerEntryStartRuntimeOptimizationRecordsVector(builder, numElems)
+
+def RuntimeOptimizationRecordContainerEntryEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return RuntimeOptimizationRecordContainerEntryEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizations.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizations.py
new file mode 100644
index 0000000000000000000000000000000000000000..a82143d39a23ac4740d90e628f3ba92e6b15c7bb
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/RuntimeOptimizations.py
@@ -0,0 +1,79 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class RuntimeOptimizations(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = RuntimeOptimizations()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsRuntimeOptimizations(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def RuntimeOptimizationsBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # RuntimeOptimizations
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # mapping from optimizer name to [RuntimeOptimizationRecord]
+    # RuntimeOptimizations
+    def Records(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.RuntimeOptimizationRecordContainerEntry import RuntimeOptimizationRecordContainerEntry
+            obj = RuntimeOptimizationRecordContainerEntry()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # RuntimeOptimizations
+    def RecordsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # RuntimeOptimizations
+    def RecordsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+def RuntimeOptimizationsStart(builder):
+    builder.StartObject(1)
+
+def Start(builder):
+    RuntimeOptimizationsStart(builder)
+
+def RuntimeOptimizationsAddRecords(builder, records):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(records), 0)
+
+def AddRecords(builder, records):
+    RuntimeOptimizationsAddRecords(builder, records)
+
+def RuntimeOptimizationsStartRecordsVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartRecordsVector(builder, numElems: int) -> int:
+    return RuntimeOptimizationsStartRecordsVector(builder, numElems)
+
+def RuntimeOptimizationsEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return RuntimeOptimizationsEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SequenceType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SequenceType.py
new file mode 100644
index 0000000000000000000000000000000000000000..604dac0a27402f09ea461b7e55472dc882f06a59
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SequenceType.py
@@ -0,0 +1,58 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class SequenceType(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = SequenceType()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsSequenceType(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def SequenceTypeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # SequenceType
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # SequenceType
+    def ElemType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.TypeInfo import TypeInfo
+            obj = TypeInfo()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def SequenceTypeStart(builder):
+    builder.StartObject(1)
+
+def Start(builder):
+    SequenceTypeStart(builder)
+
+def SequenceTypeAddElemType(builder, elemType):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(elemType), 0)
+
+def AddElemType(builder, elemType):
+    SequenceTypeAddElemType(builder, elemType)
+
+def SequenceTypeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return SequenceTypeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Shape.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Shape.py
new file mode 100644
index 0000000000000000000000000000000000000000..39e588d94e9019bfdd7eef553d6935552379e7b9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Shape.py
@@ -0,0 +1,78 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Shape(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Shape()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsShape(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ShapeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Shape
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Shape
+    def Dim(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Vector(o)
+            x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4
+            x = self._tab.Indirect(x)
+            from ort_flatbuffers_py.fbs.Dimension import Dimension
+            obj = Dimension()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # Shape
+    def DimLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Shape
+    def DimIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        return o == 0
+
+def ShapeStart(builder):
+    builder.StartObject(1)
+
+def Start(builder):
+    ShapeStart(builder)
+
+def ShapeAddDim(builder, dim):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(dim), 0)
+
+def AddDim(builder, dim):
+    ShapeAddDim(builder, dim)
+
+def ShapeStartDimVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartDimVector(builder, numElems: int) -> int:
+    return ShapeStartDimVector(builder, numElems)
+
+def ShapeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ShapeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SparseTensor.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SparseTensor.py
new file mode 100644
index 0000000000000000000000000000000000000000..0f90d615d436fc77cca61c2a7e90f18fe41194d2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/SparseTensor.py
@@ -0,0 +1,114 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class SparseTensor(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = SparseTensor()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsSparseTensor(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def SparseTensorBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # SparseTensor
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # SparseTensor
+    def Values(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # SparseTensor
+    def Indices(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Tensor import Tensor
+            obj = Tensor()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+    # SparseTensor
+    def Dims(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 8))
+        return 0
+
+    # SparseTensor
+    def DimsAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Int64Flags, o)
+        return 0
+
+    # SparseTensor
+    def DimsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # SparseTensor
+    def DimsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+def SparseTensorStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    SparseTensorStart(builder)
+
+def SparseTensorAddValues(builder, values):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(values), 0)
+
+def AddValues(builder, values):
+    SparseTensorAddValues(builder, values)
+
+def SparseTensorAddIndices(builder, indices):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(indices), 0)
+
+def AddIndices(builder, indices):
+    SparseTensorAddIndices(builder, indices)
+
+def SparseTensorAddDims(builder, dims):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(dims), 0)
+
+def AddDims(builder, dims):
+    SparseTensorAddDims(builder, dims)
+
+def SparseTensorStartDimsVector(builder, numElems):
+    return builder.StartVector(8, numElems, 8)
+
+def StartDimsVector(builder, numElems: int) -> int:
+    return SparseTensorStartDimsVector(builder, numElems)
+
+def SparseTensorEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return SparseTensorEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringProperty.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringProperty.py
new file mode 100644
index 0000000000000000000000000000000000000000..f08e0e921c07c92134c75ae8e1d9b76a22511b27
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringProperty.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class StringProperty(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = StringProperty()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsStringProperty(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def StringPropertyBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x44\x54\x43", size_prefixed=size_prefixed)
+
+    # StringProperty
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # StringProperty
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # StringProperty
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+def StringPropertyStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    StringPropertyStart(builder)
+
+def StringPropertyAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    StringPropertyAddName(builder, name)
+
+def StringPropertyAddValue(builder, value):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(value), 0)
+
+def AddValue(builder, value):
+    StringPropertyAddValue(builder, value)
+
+def StringPropertyEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return StringPropertyEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringStringEntry.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringStringEntry.py
new file mode 100644
index 0000000000000000000000000000000000000000..7d0961f70a8eacce0c0b83838d9160a2bfe45a40
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/StringStringEntry.py
@@ -0,0 +1,67 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class StringStringEntry(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = StringStringEntry()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsStringStringEntry(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def StringStringEntryBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # StringStringEntry
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # StringStringEntry
+    def Key(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # StringStringEntry
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+def StringStringEntryStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    StringStringEntryStart(builder)
+
+def StringStringEntryAddKey(builder, key):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(key), 0)
+
+def AddKey(builder, key):
+    StringStringEntryAddKey(builder, key)
+
+def StringStringEntryAddValue(builder, value):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(value), 0)
+
+def AddValue(builder, value):
+    StringStringEntryAddValue(builder, value)
+
+def StringStringEntryEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return StringStringEntryEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Tensor.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Tensor.py
new file mode 100644
index 0000000000000000000000000000000000000000..1366b91b93a4c7a1552110dc85b7487c401e6de6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/Tensor.py
@@ -0,0 +1,203 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class Tensor(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = Tensor()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsTensor(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def TensorBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # Tensor
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # Tensor
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Tensor
+    def DocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # Tensor
+    def Dims(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 8))
+        return 0
+
+    # Tensor
+    def DimsAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Int64Flags, o)
+        return 0
+
+    # Tensor
+    def DimsLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Tensor
+    def DimsIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        return o == 0
+
+    # Tensor
+    def DataType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # Tensor
+    def RawData(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.Get(flatbuffers.number_types.Uint8Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 1))
+        return 0
+
+    # Tensor
+    def RawDataAsNumpy(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint8Flags, o)
+        return 0
+
+    # Tensor
+    def RawDataLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Tensor
+    def RawDataIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
+        return o == 0
+
+    # Tensor
+    def StringData(self, j):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            a = self._tab.Vector(o)
+            return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4))
+        return ""
+
+    # Tensor
+    def StringDataLength(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        if o != 0:
+            return self._tab.VectorLen(o)
+        return 0
+
+    # Tensor
+    def StringDataIsNone(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
+        return o == 0
+
+    # Tensor
+    def ExternalDataOffset(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(16))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int64Flags, o + self._tab.Pos)
+        return -1
+
+def TensorStart(builder):
+    builder.StartObject(7)
+
+def Start(builder):
+    TensorStart(builder)
+
+def TensorAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    TensorAddName(builder, name)
+
+def TensorAddDocString(builder, docString):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(docString), 0)
+
+def AddDocString(builder, docString):
+    TensorAddDocString(builder, docString)
+
+def TensorAddDims(builder, dims):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(dims), 0)
+
+def AddDims(builder, dims):
+    TensorAddDims(builder, dims)
+
+def TensorStartDimsVector(builder, numElems):
+    return builder.StartVector(8, numElems, 8)
+
+def StartDimsVector(builder, numElems: int) -> int:
+    return TensorStartDimsVector(builder, numElems)
+
+def TensorAddDataType(builder, dataType):
+    builder.PrependInt32Slot(3, dataType, 0)
+
+def AddDataType(builder, dataType):
+    TensorAddDataType(builder, dataType)
+
+def TensorAddRawData(builder, rawData):
+    builder.PrependUOffsetTRelativeSlot(4, flatbuffers.number_types.UOffsetTFlags.py_type(rawData), 0)
+
+def AddRawData(builder, rawData):
+    TensorAddRawData(builder, rawData)
+
+def TensorStartRawDataVector(builder, numElems):
+    return builder.StartVector(1, numElems, 1)
+
+def StartRawDataVector(builder, numElems: int) -> int:
+    return TensorStartRawDataVector(builder, numElems)
+
+def TensorAddStringData(builder, stringData):
+    builder.PrependUOffsetTRelativeSlot(5, flatbuffers.number_types.UOffsetTFlags.py_type(stringData), 0)
+
+def AddStringData(builder, stringData):
+    TensorAddStringData(builder, stringData)
+
+def TensorStartStringDataVector(builder, numElems):
+    return builder.StartVector(4, numElems, 4)
+
+def StartStringDataVector(builder, numElems: int) -> int:
+    return TensorStartStringDataVector(builder, numElems)
+
+def TensorAddExternalDataOffset(builder, externalDataOffset):
+    builder.PrependInt64Slot(6, externalDataOffset, -1)
+
+def AddExternalDataOffset(builder, externalDataOffset):
+    TensorAddExternalDataOffset(builder, externalDataOffset)
+
+def TensorEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return TensorEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorDataType.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorDataType.py
new file mode 100644
index 0000000000000000000000000000000000000000..903e48747f3b0d7179077757e0a945d0e4c2c464
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorDataType.py
@@ -0,0 +1,26 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class TensorDataType(object):
+    UNDEFINED = 0
+    FLOAT = 1
+    UINT8 = 2
+    INT8 = 3
+    UINT16 = 4
+    INT16 = 5
+    INT32 = 6
+    INT64 = 7
+    STRING = 8
+    BOOL = 9
+    FLOAT16 = 10
+    DOUBLE = 11
+    UINT32 = 12
+    UINT64 = 13
+    COMPLEX64 = 14
+    COMPLEX128 = 15
+    BFLOAT16 = 16
+    FLOAT8E4M3FN = 17
+    FLOAT8E4M3FNUZ = 18
+    FLOAT8E5M2 = 19
+    FLOAT8E5M2FNUZ = 20
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorTypeAndShape.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorTypeAndShape.py
new file mode 100644
index 0000000000000000000000000000000000000000..eedef28266c411c973127b2f9c7aa4d956d6712e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TensorTypeAndShape.py
@@ -0,0 +1,71 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class TensorTypeAndShape(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = TensorTypeAndShape()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsTensorTypeAndShape(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def TensorTypeAndShapeBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # TensorTypeAndShape
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # TensorTypeAndShape
+    def ElemType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Int32Flags, o + self._tab.Pos)
+        return 0
+
+    # TensorTypeAndShape
+    def Shape(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.Shape import Shape
+            obj = Shape()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def TensorTypeAndShapeStart(builder):
+    builder.StartObject(2)
+
+def Start(builder):
+    TensorTypeAndShapeStart(builder)
+
+def TensorTypeAndShapeAddElemType(builder, elemType):
+    builder.PrependInt32Slot(0, elemType, 0)
+
+def AddElemType(builder, elemType):
+    TensorTypeAndShapeAddElemType(builder, elemType)
+
+def TensorTypeAndShapeAddShape(builder, shape):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(shape), 0)
+
+def AddShape(builder, shape):
+    TensorTypeAndShapeAddShape(builder, shape)
+
+def TensorTypeAndShapeEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return TensorTypeAndShapeEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfo.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfo.py
new file mode 100644
index 0000000000000000000000000000000000000000..db669f78095f4e6a6d2e93ee4e2e7a6dfdbf6fe7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfo.py
@@ -0,0 +1,83 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class TypeInfo(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = TypeInfo()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsTypeInfo(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def TypeInfoBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # TypeInfo
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # TypeInfo
+    def Denotation(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # TypeInfo
+    def ValueType(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.Get(flatbuffers.number_types.Uint8Flags, o + self._tab.Pos)
+        return 0
+
+    # TypeInfo
+    def Value(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            from flatbuffers.table import Table
+            obj = Table(bytearray(), 0)
+            self._tab.Union(obj, o)
+            return obj
+        return None
+
+def TypeInfoStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    TypeInfoStart(builder)
+
+def TypeInfoAddDenotation(builder, denotation):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(denotation), 0)
+
+def AddDenotation(builder, denotation):
+    TypeInfoAddDenotation(builder, denotation)
+
+def TypeInfoAddValueType(builder, valueType):
+    builder.PrependUint8Slot(1, valueType, 0)
+
+def AddValueType(builder, valueType):
+    TypeInfoAddValueType(builder, valueType)
+
+def TypeInfoAddValue(builder, value):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(value), 0)
+
+def AddValue(builder, value):
+    TypeInfoAddValue(builder, value)
+
+def TypeInfoEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return TypeInfoEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfoValue.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfoValue.py
new file mode 100644
index 0000000000000000000000000000000000000000..ba76c5f794834ae63324690de3f0fc419a929ec6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/TypeInfoValue.py
@@ -0,0 +1,9 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+class TypeInfoValue(object):
+    NONE = 0
+    tensor_type = 1
+    sequence_type = 2
+    map_type = 3
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ValueInfo.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ValueInfo.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a4986a66cad2c05281814a740b0cd2de6635e52
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/ValueInfo.py
@@ -0,0 +1,84 @@
+# automatically generated by the FlatBuffers compiler, do not modify
+
+# namespace: fbs
+
+import flatbuffers
+from flatbuffers.compat import import_numpy
+np = import_numpy()
+
+class ValueInfo(object):
+    __slots__ = ['_tab']
+
+    @classmethod
+    def GetRootAs(cls, buf, offset=0):
+        n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
+        x = ValueInfo()
+        x.Init(buf, n + offset)
+        return x
+
+    @classmethod
+    def GetRootAsValueInfo(cls, buf, offset=0):
+        """This method is deprecated. Please switch to GetRootAs."""
+        return cls.GetRootAs(buf, offset)
+    @classmethod
+    def ValueInfoBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
+        return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x4F\x52\x54\x4D", size_prefixed=size_prefixed)
+
+    # ValueInfo
+    def Init(self, buf, pos):
+        self._tab = flatbuffers.table.Table(buf, pos)
+
+    # ValueInfo
+    def Name(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # ValueInfo
+    def DocString(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
+        if o != 0:
+            return self._tab.String(o + self._tab.Pos)
+        return None
+
+    # ValueInfo
+    def Type(self):
+        o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
+        if o != 0:
+            x = self._tab.Indirect(o + self._tab.Pos)
+            from ort_flatbuffers_py.fbs.TypeInfo import TypeInfo
+            obj = TypeInfo()
+            obj.Init(self._tab.Bytes, x)
+            return obj
+        return None
+
+def ValueInfoStart(builder):
+    builder.StartObject(3)
+
+def Start(builder):
+    ValueInfoStart(builder)
+
+def ValueInfoAddName(builder, name):
+    builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0)
+
+def AddName(builder, name):
+    ValueInfoAddName(builder, name)
+
+def ValueInfoAddDocString(builder, docString):
+    builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(docString), 0)
+
+def AddDocString(builder, docString):
+    ValueInfoAddDocString(builder, docString)
+
+def ValueInfoAddType(builder, type):
+    builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(type), 0)
+
+def AddType(builder, type):
+    ValueInfoAddType(builder, type)
+
+def ValueInfoEnd(builder):
+    return builder.EndObject()
+
+def End(builder):
+    return ValueInfoEnd(builder)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..6014761347704f0b8af6477ea0c122a1e91b36db
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_flatbuffers_py/fbs/__init__.py
@@ -0,0 +1,6 @@
+from os.path import dirname, basename, isfile, join, splitext
+import glob
+modules = glob.glob(join(dirname(__file__), "*.py"))
+__all__ = [splitext(basename(f))[0] for f in modules if isfile(f) and not f.endswith('__init__.py')]
+
+from . import *
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_model_processor.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_model_processor.py
new file mode 100644
index 0000000000000000000000000000000000000000..3343f44d919e239e2ad1281d616752aa832fd0e9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/ort_model_processor.py
@@ -0,0 +1,86 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import ort_flatbuffers_py.fbs as fbs
+
+from .operator_type_usage_processors import OperatorTypeUsageManager
+
+
+class OrtFormatModelProcessor:
+    "Class to process an ORT format model and determine required operators and types."
+
+    def __init__(self, model_path: str, required_ops: dict, processors: OperatorTypeUsageManager):
+        """
+        Initialize ORT format model processor
+        :param model_path: Path to model to load
+        :param required_ops: Dictionary required operator information will be added to.
+        :param processors: Operator type usage processors which will be called for each matching Node.
+        """
+        self._required_ops = required_ops  # dictionary of {domain: {opset:[operators]}}
+        self._file = open(model_path, "rb").read()  # noqa: SIM115
+        self._buffer = bytearray(self._file)
+        if not fbs.InferenceSession.InferenceSession.InferenceSessionBufferHasIdentifier(self._buffer, 0):
+            raise RuntimeError(f"File does not appear to be a valid ORT format model: '{model_path}'")
+        self._model = fbs.InferenceSession.InferenceSession.GetRootAsInferenceSession(self._buffer, 0).Model()
+        self._op_type_processors = processors
+
+    @staticmethod
+    def _setup_type_info(graph: fbs.Graph, outer_scope_value_typeinfo={}):  # noqa: B006
+        """
+        Setup the node args for this level of Graph.
+        We copy the current list which represents the outer scope values, and add the local node args to that
+        to create the valid list of values for the current Graph.
+        :param graph: Graph to create NodeArg list for
+        :param outer_scope_value_typeinfo: TypeInfo for outer scope values. Empty for the top-level graph in a model.
+        :return: Dictionary of NodeArg name to TypeInfo
+        """
+        value_name_to_typeinfo = outer_scope_value_typeinfo.copy()
+        for j in range(graph.NodeArgsLength()):
+            n = graph.NodeArgs(j)
+            value_name_to_typeinfo[n.Name()] = n.Type()  # TypeInfo for this NodeArg's name
+
+        return value_name_to_typeinfo
+
+    def _add_required_op(self, domain: str, opset: int, op_type: str):
+        if domain not in self._required_ops:
+            self._required_ops[domain] = {opset: {op_type}}
+        elif opset not in self._required_ops[domain]:
+            self._required_ops[domain][opset] = {op_type}
+        else:
+            self._required_ops[domain][opset].add(op_type)
+
+    def _process_graph(self, graph: fbs.Graph, outer_scope_value_typeinfo: dict):
+        """
+        Process one level of the Graph, descending into any subgraphs when they are found
+        :param outer_scope_value_typeinfo: Outer scope NodeArg dictionary from ancestor graphs
+        """
+        # Merge the TypeInfo for all values in this level of the graph with the outer scope value TypeInfo.
+        value_name_to_typeinfo = OrtFormatModelProcessor._setup_type_info(graph, outer_scope_value_typeinfo)
+
+        for i in range(graph.NodesLength()):
+            node = graph.Nodes(i)
+
+            optype = node.OpType().decode()
+            domain = node.Domain().decode() or "ai.onnx"  # empty domain defaults to ai.onnx
+
+            self._add_required_op(domain, node.SinceVersion(), optype)
+
+            if self._op_type_processors:
+                self._op_type_processors.process_node(node, value_name_to_typeinfo)
+
+            # Read all the attributes
+            for j in range(node.AttributesLength()):
+                attr = node.Attributes(j)
+                attr_type = attr.Type()
+                if attr_type == fbs.AttributeType.AttributeType.GRAPH:
+                    self._process_graph(attr.G(), value_name_to_typeinfo)
+                elif attr_type == fbs.AttributeType.AttributeType.GRAPHS:
+                    # the ONNX spec doesn't currently define any operators that have multiple graphs in an attribute
+                    # so entering this 'elif' isn't currently possible
+                    for k in range(attr.GraphsLength()):
+                        self._process_graph(attr.Graphs(k), value_name_to_typeinfo)
+
+    def process(self):
+        graph = self._model.Graph()
+        outer_scope_value_typeinfo = {}  # no outer scope values for the main graph
+        self._process_graph(graph, outer_scope_value_typeinfo)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/types.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/types.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff00cd22ea8bdba9119ec30b958530954a6b3650
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/types.py
@@ -0,0 +1,85 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import ort_flatbuffers_py.fbs as fbs
+
+
+class FbsTypeInfo:
+    "Class to provide conversion between ORT flatbuffers schema values and C++ types"
+
+    tensordatatype_to_string = {  # noqa: RUF012
+        fbs.TensorDataType.TensorDataType.FLOAT: "float",
+        fbs.TensorDataType.TensorDataType.UINT8: "uint8_t",
+        fbs.TensorDataType.TensorDataType.INT8: "int8_t",
+        fbs.TensorDataType.TensorDataType.UINT16: "uint16_t",
+        fbs.TensorDataType.TensorDataType.INT16: "int16_t",
+        fbs.TensorDataType.TensorDataType.INT32: "int32_t",
+        fbs.TensorDataType.TensorDataType.INT64: "int64_t",
+        fbs.TensorDataType.TensorDataType.STRING: "std::string",
+        fbs.TensorDataType.TensorDataType.BOOL: "bool",
+        fbs.TensorDataType.TensorDataType.FLOAT16: "MLFloat16",
+        fbs.TensorDataType.TensorDataType.DOUBLE: "double",
+        fbs.TensorDataType.TensorDataType.UINT32: "uint32_t",
+        fbs.TensorDataType.TensorDataType.UINT64: "uint64_t",
+        # fbs.TensorDataType.TensorDataType.COMPLEX64: 'complex64 is not supported',
+        # fbs.TensorDataType.TensorDataType.COMPLEX128: 'complex128 is not supported',
+        fbs.TensorDataType.TensorDataType.BFLOAT16: "BFloat16",
+        fbs.TensorDataType.TensorDataType.FLOAT8E4M3FN: "Float8E4M3FN",
+        fbs.TensorDataType.TensorDataType.FLOAT8E4M3FNUZ: "Float8E4M3FNUZ",
+        fbs.TensorDataType.TensorDataType.FLOAT8E5M2: "Float8E5M2",
+        fbs.TensorDataType.TensorDataType.FLOAT8E5M2FNUZ: "Float8E5M2FNUZ",
+    }
+
+    @staticmethod
+    def typeinfo_to_str(type: fbs.TypeInfo):
+        value_type = type.ValueType()
+        value = type.Value()
+        type_str = "unknown"
+
+        if value_type == fbs.TypeInfoValue.TypeInfoValue.tensor_type:
+            tensor_type_and_shape = fbs.TensorTypeAndShape.TensorTypeAndShape()
+            tensor_type_and_shape.Init(value.Bytes, value.Pos)
+            elem_type = tensor_type_and_shape.ElemType()
+            type_str = FbsTypeInfo.tensordatatype_to_string[elem_type]
+
+        elif value_type == fbs.TypeInfoValue.TypeInfoValue.map_type:
+            map_type = fbs.MapType.MapType()
+            map_type.init(value.Bytes, value.Pos)
+            key_type = map_type.KeyType()  # TensorDataType
+            key_type_str = FbsTypeInfo.tensordatatype_to_string[key_type]
+            value_type = map_type.ValueType()  # TypeInfo
+            value_type_str = FbsTypeInfo.typeinfo_to_str(value_type)
+            type_str = f"std::map<{key_type_str},{value_type_str}>"
+
+        elif value_type == fbs.TypeInfoValue.TypeInfoValue.sequence_type:
+            sequence_type = fbs.SequenceType.SequenceType()
+            sequence_type.Init(value.Bytes, value.Pos)
+            elem_type = sequence_type.ElemType()  # TypeInfo
+            elem_type_str = FbsTypeInfo.typeinfo_to_str(elem_type)
+            # TODO: Decide if we need to wrap the type in a std::vector. Issue is that the element type is internal
+            # to the onnxruntime::Tensor class so we're really returning the type inside the Tensor not vector<Tensor>.
+            # For now, return the element type (which will be the Tensor element type, or a map<A,B>) as
+            # an operator input or output will either be a sequence or a not, so we don't need to disambiguate
+            # between the two (i.e. we know if the returned value refers to the contents of a sequence, and can
+            # handle whether it's the element type of a Tensor in the sequence, or the map type in a sequence of maps
+            # due to this).
+            type_str = elem_type_str
+        else:
+            raise ValueError(f"Unknown or missing value type of {value_type}")
+
+        return type_str
+
+
+def get_typeinfo(name: str, value_name_to_typeinfo: dict) -> fbs.TypeInfo:
+    "Lookup a name in a dictionary mapping value name to TypeInfo."
+    if name not in value_name_to_typeinfo:
+        raise RuntimeError("Missing TypeInfo entry for " + name)
+
+    return value_name_to_typeinfo[name]  # TypeInfo object
+
+
+def value_name_to_typestr(name: str, value_name_to_typeinfo: dict):
+    "Lookup TypeInfo for value name and convert to a string representing the C++ type."
+    type = get_typeinfo(name, value_name_to_typeinfo)
+    type_str = FbsTypeInfo.typeinfo_to_str(type)
+    return type_str
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/utils.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f9242860811c5f701c947822d5483bf2e009b08
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/ort_format_model/utils.py
@@ -0,0 +1,61 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import pathlib
+import typing
+
+from ..logger import get_logger
+from .operator_type_usage_processors import OperatorTypeUsageManager
+from .ort_model_processor import OrtFormatModelProcessor
+
+log = get_logger("ort_format_model.utils")
+
+
+def _extract_ops_and_types_from_ort_models(model_files: typing.Iterable[pathlib.Path], enable_type_reduction: bool):
+    required_ops = {}
+    op_type_usage_manager = OperatorTypeUsageManager() if enable_type_reduction else None
+
+    for model_file in model_files:
+        if not model_file.is_file():
+            raise ValueError(f"Path is not a file: '{model_file}'")
+        model_processor = OrtFormatModelProcessor(str(model_file), required_ops, op_type_usage_manager)
+        model_processor.process()  # this updates required_ops and op_type_processors
+
+    return required_ops, op_type_usage_manager
+
+
+def create_config_from_models(
+    model_files: typing.Iterable[pathlib.Path], output_file: pathlib.Path, enable_type_reduction: bool
+):
+    """
+    Create a configuration file with required operators and optionally required types.
+    :param model_files: Model files to use to generate the configuration file.
+    :param output_file: File to write configuration to.
+    :param enable_type_reduction: Include required type information for individual operators in the configuration.
+    """
+
+    required_ops, op_type_processors = _extract_ops_and_types_from_ort_models(model_files, enable_type_reduction)
+
+    output_file.parent.mkdir(parents=True, exist_ok=True)
+
+    with open(output_file, "w") as out:
+        out.write("# Generated from model/s:\n")
+        out.writelines(f"# - {model_file}\n" for model_file in sorted(model_files))
+
+        for domain in sorted(required_ops.keys()):
+            for opset in sorted(required_ops[domain].keys()):
+                ops = required_ops[domain][opset]
+                if ops:
+                    out.write(f"{domain};{opset};")
+                    if enable_type_reduction:
+                        # type string is empty if op hasn't been seen
+                        entries = [
+                            "{}{}".format(op, op_type_processors.get_config_entry(domain, op) or "")
+                            for op in sorted(ops)
+                        ]
+                    else:
+                        entries = sorted(ops)
+
+                    out.write("{}\n".format(",".join(entries)))
+
+    log.info("Created config in %s", output_file)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/qdq_helpers/optimize_qdq_model.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/qdq_helpers/optimize_qdq_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..4f02d4e1dd0751cfe7a0aeaf6d11396f33064b12
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/qdq_helpers/optimize_qdq_model.py
@@ -0,0 +1,37 @@
+#!/usr/bin/env python3
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import argparse
+import os
+import pathlib
+
+import onnx
+
+
+def optimize_qdq_model():
+    parser = argparse.ArgumentParser(
+        os.path.basename(__file__),
+        description="Update a QDQ format ONNX model to ensure optimal performance when executed using ONNX Runtime.",
+    )
+
+    parser.add_argument("input_model", type=pathlib.Path, help="Provide path to ONNX model to update.")
+    parser.add_argument("output_model", type=pathlib.Path, help="Provide path to write updated ONNX model to.")
+
+    args = parser.parse_args()
+
+    model = onnx.load(str(args.input_model.resolve(strict=True)))
+
+    # run QDQ model optimizations here
+
+    # Originally, the fixing up of DQ nodes with multiple consumers was implemented as one such optimization.
+    # That was moved to an ORT graph transformer.
+    print("As of ORT 1.15, the fixing up of DQ nodes with multiple consumers is done by an ORT graph transformer.")
+
+    # There are no optimizations being run currently but we expect that there may be in the future.
+
+    onnx.save(model, str(args.output_model.resolve()))
+
+
+if __name__ == "__main__":
+    optimize_qdq_model()
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/__pycache__/preprocess.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/__pycache__/preprocess.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/add_trans_cast.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/add_trans_cast.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c47437b25c7a0eaa13346ae37cdb91a0635cfa4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/add_trans_cast.py
@@ -0,0 +1,292 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import json
+from argparse import ArgumentParser
+
+import onnx
+from onnx import TensorProto, helper
+
+
+def graph_topological_sort(graph):
+    deps_count = [0] * len(graph.node)  # dependency count of each node
+    deps_to_nodes = {}  # input to node indice
+    sorted_nodes = []  # initialize sorted_nodes
+    for node_idx, node in enumerate(graph.node):
+        # CANNOT use len(node.input) directly because input can be optional
+        deps_count[node_idx] = sum(1 for _ in node.input if _)
+        if deps_count[node_idx] == 0:  # Constant doesn't depend on any inputs
+            sorted_nodes.append(graph.node[node_idx])
+            continue
+
+        for input_name in node.input:
+            if input_name not in deps_to_nodes:
+                deps_to_nodes[input_name] = [node_idx]
+            else:
+                deps_to_nodes[input_name].append(node_idx)
+
+    # Note: this logic only applies to top level graph since a sub graph could use intializer from parent graph
+    initializer_names = [init.name for init in graph.initializer]
+    graph_input_names = [input.name for input in graph.input]
+    input_names = initializer_names + graph_input_names
+    input_names.sort()
+    prev_input_name = None
+    for input_name in input_names:
+        if prev_input_name == input_name:
+            continue
+
+        prev_input_name = input_name
+        if input_name in deps_to_nodes:
+            for node_idx in deps_to_nodes[input_name]:
+                deps_count[node_idx] = deps_count[node_idx] - 1
+                if deps_count[node_idx] == 0:
+                    sorted_nodes.append(graph.node[node_idx])
+
+    start = 0
+    end = len(sorted_nodes)
+
+    while start < end:
+        for output in sorted_nodes[start].output:
+            if output in deps_to_nodes:
+                for node_idx in deps_to_nodes[output]:
+                    deps_count[node_idx] = deps_count[node_idx] - 1
+                    if deps_count[node_idx] == 0:
+                        sorted_nodes.append(graph.node[node_idx])
+                        end = end + 1
+        start = start + 1
+
+    assert end == len(graph.node), "Graph is not a DAG"
+    graph.ClearField("node")
+    graph.node.extend(sorted_nodes)
+
+
+class QnnTensorStruct:
+    def __init__(self):
+        self.name = ""
+        self.onnx_data_type = TensorProto.FLOAT
+        self.dim = []
+
+
+def qnn_data_type_to_onnx_data_type(qnn_data_type):
+    # QNN_DATATYPE_UFIXED_POINT_8 QNN_DATATYPE_UINT_8
+    if qnn_data_type == 0x0408 or qnn_data_type == 0x0108:
+        return TensorProto.UINT8
+    # QNN_DATATYPE_UFIXED_POINT_16 QNN_DATATYPE_UINT_16
+    elif qnn_data_type == 0x0416 or qnn_data_type == 0x0116:
+        return TensorProto.UINT16
+    # QNN_DATATYPE_UFIXED_POINT_32 QNN_DATATYPE_UINT_32
+    elif qnn_data_type == 0x0432 or qnn_data_type == 0x0132:
+        return TensorProto.UINT32
+    # QNN_DATATYPE_UINT_64
+    elif qnn_data_type == 0x0164:
+        return TensorProto.UINT64
+    # QNN_DATATYPE_FIXED_POINT_8 QNN_DATATYPE_INT_8
+    elif qnn_data_type == 0x0308 or qnn_data_type == 0x0008:
+        return TensorProto.INT8
+    # QNN_DATATYPE_FIXED_POINT_16 QNN_DATATYPE_INT_16
+    elif qnn_data_type == 0x0316 or qnn_data_type == 0x0016:
+        return TensorProto.INT16
+    # QNN_DATATYPE_FIXED_POINT_32 QNN_DATATYPE_INT_32
+    elif qnn_data_type == 0x0332 or qnn_data_type == 0x0032:
+        return TensorProto.INT32
+    # QNN_DATATYPE_INT_64
+    elif qnn_data_type == 0x0064:
+        return TensorProto.INT64
+    # QNN_DATATYPE_FLOAT_16
+    elif qnn_data_type == 0x0216:
+        return TensorProto.FLOAT16
+    # QNN_DATATYPE_FLOAT_32
+    elif qnn_data_type == 0x0232:
+        return TensorProto.FLOAT
+    # QNN_DATATYPE_BOOL_8
+    elif qnn_data_type == 0x0508:
+        return TensorProto.BOOL
+    else:
+        return TensorProto.UNDEFINED
+
+
+def parse_qnn_json_file(qnn_json_file_path, qnn_input_output_tensor_dic):
+    with open(qnn_json_file_path) as qnn_json_file:
+        qnn_json = json.load(qnn_json_file)
+        assert "graph" in qnn_json, "QNN converted json file not valid. Can't find graph."
+        assert "tensors" in qnn_json["graph"], "QNN converted json file not valid. Can't find tensors."
+        for qnn_tensor_name, qnn_tensor_attribute in qnn_json["graph"]["tensors"].items():
+            # type:0 - QNN input tensor, type:1 - QNN output tensor
+            assert (
+                "type" in qnn_tensor_attribute
+                and "data_type" in qnn_tensor_attribute
+                and "dims" in qnn_tensor_attribute
+            ), "QNN converted json file not valid. Can't find some keys from tensors"
+            if qnn_tensor_attribute["type"] == 0 or qnn_tensor_attribute["type"] == 1:
+                qnn_tensor = QnnTensorStruct()
+                qnn_tensor.name = qnn_tensor_name
+                qnn_tensor.onnx_data_type = qnn_data_type_to_onnx_data_type(qnn_tensor_attribute["data_type"])
+                qnn_tensor.dim = qnn_tensor_attribute["dims"]
+                qnn_input_output_tensor_dic[qnn_tensor_name] = qnn_tensor
+
+    assert len(qnn_input_output_tensor_dic) > 1, (
+        "Converted QNN model not valid. It should have at least 1 input & 1 output."
+    )
+
+
+def compare_onnx_shape_with_qnn_shape(onnx_dims, qnn_dims):
+    assert len(onnx_dims) == len(qnn_dims), "Onnx shape and Qnn shape has different rank."
+    return all(onnx_dims[i].dim_value == qnn_dims[i] for i in range(len(onnx_dims)))
+
+
+def gen_to_channel_first_perm(rank):
+    assert rank > 2, "Shape rank should >2 for the Transpose node."
+    perm = []
+    perm.append(0)
+    perm.append(rank - 1)
+    for i in range(1, rank - 1):
+        perm.append(i)  # noqa: PERF402
+
+    return perm
+
+
+def gen_to_channel_last_perm(rank):
+    assert rank > 2, "Shape rank should >2 for the Transpose node."
+    perm = []
+    perm.append(0)
+    for i in range(2, rank):
+        perm.append(i)  # noqa: PERF402
+    perm.append(1)
+
+    return perm
+
+
+# Onnxruntime QNN EP can support context binary file generated by QNN tool chain. However QNN generated context binary file
+# uses channel last data layout and 8 bits or 16 bits for input and output.
+# This script gets the QNN model input & output information from QNN converted model_net.json file, compare them with Onnx model
+# and inserts Cast, Transpose nodes to Onnx model if required
+def main():
+    parser = ArgumentParser(
+        "Insert Cast, Transpose nodes into Onnx model to make it aligned with QNN generated context binary."
+    )
+    parser.add_argument("-m", "--onnx_model", help="Required. Path to Onnx model file.", required=True, type=str)
+    parser.add_argument(
+        "-q", "--qnn_json", help="Required. Path to Qnn converted model_net.json file.", required=True, type=str
+    )
+    args = parser.parse_args()
+
+    # Parse Qnn model_net.json file to get the graph input output information
+    qnn_input_output_tensor_dic = {}
+    parse_qnn_json_file(args.qnn_json, qnn_input_output_tensor_dic)
+
+    model = onnx.load(args.onnx_model)
+
+    nodes_to_add = []
+    # Tranch the tensor name change to update the consumer nodes
+    graph_input_output_name_dic = {}
+    for graph_input in model.graph.input:
+        if graph_input.name in qnn_input_output_tensor_dic:
+            input_name_fater_node_insert = graph_input.name
+            qnn_input_tensor = qnn_input_output_tensor_dic[graph_input.name]
+            # Insert Cast node if Onnx input and Qnn input has different data type
+            if graph_input.type.tensor_type.elem_type != qnn_input_tensor.onnx_data_type:
+                # Insert Cast node
+                cast_input_name = input_name_fater_node_insert
+                cast_output_name = cast_input_name + "_qnn_cast"
+                input_cast_node = helper.make_node(
+                    "Cast",
+                    name=cast_output_name,
+                    inputs=[cast_input_name],
+                    outputs=[cast_output_name],
+                    to=graph_input.type.tensor_type.elem_type,
+                )
+                # Change input data type to Qnn input data type
+                graph_input.type.tensor_type.elem_type = qnn_input_tensor.onnx_data_type
+                nodes_to_add.extend([input_cast_node])
+                input_name_fater_node_insert = cast_output_name
+                graph_input_output_name_dic[graph_input.name] = cast_output_name
+
+            if not compare_onnx_shape_with_qnn_shape(graph_input.type.tensor_type.shape.dim, qnn_input_tensor.dim):
+                # Add Transpose node (channel last to channel first)
+                transpose_perm = gen_to_channel_first_perm(len(graph_input.type.tensor_type.shape.dim))
+                transpose_input_name = input_name_fater_node_insert
+                transpose_output_name = transpose_input_name + "_qnn_trans"
+                input_transpose_node = helper.make_node(
+                    "Transpose",
+                    name=transpose_output_name,
+                    inputs=[transpose_input_name],
+                    outputs=[transpose_output_name],
+                    perm=transpose_perm,
+                )
+                nodes_to_add.extend([input_transpose_node])
+                graph_input_output_name_dic[graph_input.name] = transpose_output_name
+
+                # Change input shape to Qnn input shape
+                for i in range(len(graph_input.type.tensor_type.shape.dim)):
+                    graph_input.type.tensor_type.shape.dim[i].dim_value = qnn_input_tensor.dim[i]
+        else:
+            raise AssertionError("Error: Onnx model input: " + graph_input.name + " not exist from QNN model input.")
+
+    for graph_output in model.graph.output:
+        if graph_output.name in qnn_input_output_tensor_dic:
+            output_name_after_node_insert = graph_output.name
+            # Insert Cast node if Onnx input and Qnn input has idfferent data type
+            qnn_output_tensor = qnn_input_output_tensor_dic[graph_output.name]
+            if graph_output.type.tensor_type.elem_type != qnn_output_tensor.onnx_data_type:
+                # Insert Cast node
+                cast_output_name = output_name_after_node_insert
+                cast_input_name = cast_output_name + "_qnn_cast"
+                output_cast_node = helper.make_node(
+                    "Cast",
+                    name=cast_input_name,
+                    inputs=[cast_input_name],
+                    outputs=[cast_output_name],
+                    to=qnn_output_tensor.onnx_data_type,
+                )
+                # Change output data type to Onn output data type
+                graph_output.type.tensor_type.elem_type = qnn_output_tensor.onnx_data_type
+                nodes_to_add.extend([output_cast_node])
+                output_name_after_node_insert = cast_input_name
+                graph_input_output_name_dic[graph_output.name] = cast_input_name
+
+            if not compare_onnx_shape_with_qnn_shape(graph_output.type.tensor_type.shape.dim, qnn_output_tensor.dim):
+                # Add Transpose node (channel first to channel last)
+                transpose_perm = gen_to_channel_last_perm(len(graph_output.type.tensor_type.shape.dim))
+                transpose_output_name = output_name_after_node_insert
+                transpose_input_name = transpose_output_name + "_qnn_trans"
+                output_transpose_node = helper.make_node(
+                    "Transpose",
+                    name=transpose_input_name,
+                    inputs=[transpose_input_name],
+                    outputs=[transpose_output_name],
+                    perm=transpose_perm,
+                )
+                nodes_to_add.extend([output_transpose_node])
+                graph_input_output_name_dic[graph_output.name] = transpose_input_name
+
+                # Change output shape to Qnn output shape
+                for i in range(len(graph_output.type.tensor_type.shape.dim)):
+                    graph_output.type.tensor_type.shape.dim[i].dim_value = qnn_input_output_tensor_dic[
+                        graph_output.name
+                    ].dim[i]
+        else:
+            raise AssertionError("Error: Onnx model output: " + graph_output.name + " not exist from QNN model output.")
+
+    for node in model.graph.node:
+        for node_input_index, node_input in enumerate(node.input):
+            # update consumer node for graph inputs to connect to inserted node
+            if node_input in graph_input_output_name_dic:
+                node.input[node_input_index] = graph_input_output_name_dic[node_input]
+
+        for node_output_index, node_output in enumerate(node.output):
+            # update producer node for graph outputs to connect to inserted node
+            if node_output in graph_input_output_name_dic:
+                node.output[node_output_index] = graph_input_output_name_dic[node_output]
+
+    model.graph.node.extend(nodes_to_add)
+    graph_topological_sort(model.graph)
+
+    # Add extra parameter all_tensors_to_one_file=False, size_threshold=5000 if the model exceeds protobuf 2GB limit e.g below
+    # onnx.save(model, args.onnx_model.replace(".onnx", "_add_trans.onnx"), all_tensors_to_one_file=False, size_threshold=5000)
+    onnx.save(model, args.onnx_model.replace(".onnx", "_add_trans.onnx"))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/gen_qnn_ctx_onnx_model.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/gen_qnn_ctx_onnx_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..3d5aa6fa68fadaa23bbc021a58c1799f30119c47
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/gen_qnn_ctx_onnx_model.py
@@ -0,0 +1,364 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import json
+from argparse import ArgumentParser
+
+import onnx
+from onnx import TensorProto, helper
+
+
+class QnnTensorStruct:
+    def __init__(
+        self, name="", onnx_data_type=TensorProto.FLOAT, is_quantized=False, scale=0.0, offset=0, dim=None, id=None
+    ):
+        self.name = name
+        self.onnx_data_type = onnx_data_type
+        self.is_quantized = is_quantized
+        self.scale = scale
+        self.offset = offset
+        self.dim = [] if dim is None else dim
+        self.id = id
+
+
+def is_quantized_data_type(qnn_data_type, is_converter_json):
+    if is_converter_json:
+        # QNN_DATATYPE_UFIXED_POINT_8 QNN_DATATYPE_UFIXED_POINT_16 QNN_DATATYPE_FIXED_POINT_8 QNN_DATATYPE_FIXED_POINT_16
+        return qnn_data_type == 0x0408 or qnn_data_type == 0x0416 or qnn_data_type == 0x0308 or qnn_data_type == 0x0316
+    else:
+        return (
+            qnn_data_type == "QNN_DATATYPE_UFIXED_POINT_8"
+            or qnn_data_type == "QNN_DATATYPE_UFIXED_POINT_16"
+            or qnn_data_type == "QNN_DATATYPE_FIXED_POINT_8"
+            or qnn_data_type == "QNN_DATATYPE_FIXED_POINT_16"
+        )
+
+
+def qnn_data_type_to_onnx_data_type(qnn_data_type, is_converter_json):
+    if is_converter_json:
+        # QNN_DATATYPE_UFIXED_POINT_8 QNN_DATATYPE_UINT_8
+        if qnn_data_type == 0x0408 or qnn_data_type == 0x0108:
+            return TensorProto.UINT8
+        # QNN_DATATYPE_UFIXED_POINT_16 QNN_DATATYPE_UINT_16
+        elif qnn_data_type == 0x0416 or qnn_data_type == 0x0116:
+            return TensorProto.UINT16
+        # QNN_DATATYPE_UFIXED_POINT_32 QNN_DATATYPE_UINT_32
+        elif qnn_data_type == 0x0432 or qnn_data_type == 0x0132:
+            return TensorProto.UINT32
+        # QNN_DATATYPE_UINT_64
+        elif qnn_data_type == 0x0164:
+            return TensorProto.UINT64
+        # QNN_DATATYPE_FIXED_POINT_8 QNN_DATATYPE_INT_8
+        elif qnn_data_type == 0x0308 or qnn_data_type == 0x0008:
+            return TensorProto.INT8
+        # QNN_DATATYPE_FIXED_POINT_16 QNN_DATATYPE_INT_16
+        elif qnn_data_type == 0x0316 or qnn_data_type == 0x0016:
+            return TensorProto.INT16
+        # QNN_DATATYPE_FIXED_POINT_32 QNN_DATATYPE_INT_32
+        elif qnn_data_type == 0x0332 or qnn_data_type == 0x0032:
+            return TensorProto.INT32
+        # QNN_DATATYPE_INT_64
+        elif qnn_data_type == 0x0064:
+            return TensorProto.INT64
+        # QNN_DATATYPE_FLOAT_16
+        elif qnn_data_type == 0x0216:
+            return TensorProto.FLOAT16
+        # QNN_DATATYPE_FLOAT_32
+        elif qnn_data_type == 0x0232:
+            return TensorProto.FLOAT
+        # QNN_DATATYPE_BOOL_8
+        elif qnn_data_type == 0x0508:
+            return TensorProto.BOOL
+        else:
+            return TensorProto.UNDEFINED
+    else:
+        # QNN_DATATYPE_UFIXED_POINT_8 QNN_DATATYPE_UINT_8
+        if qnn_data_type == "QNN_DATATYPE_UFIXED_POINT_8" or qnn_data_type == "QNN_DATATYPE_UINT_8":
+            return TensorProto.UINT8
+        # QNN_DATATYPE_UFIXED_POINT_16 QNN_DATATYPE_UINT_16
+        elif qnn_data_type == "QNN_DATATYPE_UFIXED_POINT_16" or qnn_data_type == "QNN_DATATYPE_UINT_16":
+            return TensorProto.UINT16
+        # QNN_DATATYPE_UFIXED_POINT_32 QNN_DATATYPE_UINT_32
+        elif qnn_data_type == "QNN_DATATYPE_UFIXED_POINT_32" or qnn_data_type == "QNN_DATATYPE_UINT_32":
+            return TensorProto.UINT32
+        # QNN_DATATYPE_UINT_64
+        elif qnn_data_type == "QNN_DATATYPE_UINT_64":
+            return TensorProto.UINT64
+        # QNN_DATATYPE_FIXED_POINT_8 QNN_DATATYPE_INT_8
+        elif qnn_data_type == "QNN_DATATYPE_FIXED_POINT_8" or qnn_data_type == "QNN_DATATYPE_INT_8":
+            return TensorProto.INT8
+        # QNN_DATATYPE_FIXED_POINT_16 QNN_DATATYPE_INT_16
+        elif qnn_data_type == "QNN_DATATYPE_FIXED_POINT_16" or qnn_data_type == "QNN_DATATYPE_INT_16":
+            return TensorProto.INT16
+        # QNN_DATATYPE_FIXED_POINT_32 QNN_DATATYPE_INT_32
+        elif qnn_data_type == "QNN_DATATYPE_FIXED_POINT_32" or qnn_data_type == "QNN_DATATYPE_INT_32":
+            return TensorProto.INT32
+        # QNN_DATATYPE_INT_64
+        elif qnn_data_type == "QNN_DATATYPE_INT_64":
+            return TensorProto.INT64
+        # QNN_DATATYPE_FLOAT_16
+        elif qnn_data_type == "QNN_DATATYPE_FLOAT_16":
+            return TensorProto.FLOAT16
+        # QNN_DATATYPE_FLOAT_32
+        elif qnn_data_type == "QNN_DATATYPE_FLOAT_32":
+            return TensorProto.FLOAT
+        # QNN_DATATYPE_BOOL_8
+        elif qnn_data_type == "QNN_DATATYPE_BOOL_8":
+            return TensorProto.BOOL
+        else:
+            return TensorProto.UNDEFINED
+
+
+def parse_qnn_converter_json_file(qnn_convert_json, qnn_input_tensor_dic, qnn_output_tensor_dic):
+    is_qnn_converter_json = True
+    for qnn_tensor_name, qnn_tensor_attribute in qnn_convert_json["graph"]["tensors"].items():
+        # type:0 - QNN input tensor, type:1 - QNN output tensor
+        assert (
+            "type" in qnn_tensor_attribute
+            and "data_type" in qnn_tensor_attribute
+            and "dims" in qnn_tensor_attribute
+            and "id" in qnn_tensor_attribute
+            and "quant_params" in qnn_tensor_attribute
+        ), "QNN converted json file not valid. Can't find some keys from tensors"
+
+        # If tensor is not IO, ignore it
+        if qnn_tensor_attribute["type"] not in [0, 1]:
+            continue
+
+        # Get all graph inputs & output
+        qnn_tensor = QnnTensorStruct(
+            name=qnn_tensor_name,
+            onnx_data_type=qnn_data_type_to_onnx_data_type(qnn_tensor_attribute["data_type"], is_qnn_converter_json),
+            is_quantized=is_quantized_data_type(qnn_tensor_attribute["data_type"], is_qnn_converter_json),
+            dim=qnn_tensor_attribute["dims"],
+            id=qnn_tensor_attribute["id"],
+        )
+
+        if (
+            qnn_tensor_attribute["quant_params"]["definition"] == 1
+            and qnn_tensor_attribute["quant_params"]["encoding"] == 0
+        ):
+            qnn_tensor.scale = qnn_tensor_attribute["quant_params"]["scale_offset"]["scale"]
+            qnn_tensor.offset = -qnn_tensor_attribute["quant_params"]["scale_offset"]["offset"]
+
+        if qnn_tensor_attribute["type"] == 0:
+            qnn_input_tensor_dic[qnn_tensor_name] = qnn_tensor
+        else:
+            qnn_output_tensor_dic[qnn_tensor_name] = qnn_tensor
+
+    assert len(qnn_input_tensor_dic) >= 1 and len(qnn_output_tensor_dic) >= 1, (
+        "Converted QNN model not valid. It should have at least 1 input & 1 output."
+    )
+
+
+def generate_wrapper_onnx_file(
+    grap_name,
+    model_file_name,
+    qnn_input_tensor_dic,
+    qnn_output_tensor_dic,
+    disable_embed_mode,
+    qnn_ctx_file,
+    quantized_IO,
+    qnn_sdk_version="unknown",
+):
+    graph_nodes = []
+    ini_list = []
+    value_infos = []
+
+    model_inputs = []
+    for qnn_input in sorted(qnn_input_tensor_dic.values(), key=lambda inp: inp.id):
+        if qnn_input.is_quantized and not quantized_IO:
+            q_scale_input_name = qnn_input.name + "_scale"
+            q_offset_input_name = qnn_input.name + "_zp"
+            q_scale = helper.make_tensor(q_scale_input_name, TensorProto.FLOAT, [], [qnn_input.scale])
+            ini_list.append(q_scale)
+            q_offset = helper.make_tensor(q_offset_input_name, qnn_input.onnx_data_type, [], [qnn_input.offset])
+            ini_list.append(q_offset)
+            input_name = qnn_input.name + "_dq"
+
+            q_node = helper.make_node(
+                "QuantizeLinear",
+                name=qnn_input.name,
+                inputs=[input_name, q_scale_input_name, q_offset_input_name],
+                outputs=[qnn_input.name],
+            )
+
+            graph_nodes.append(q_node)
+            model_inputs.append(helper.make_tensor_value_info(input_name, TensorProto.FLOAT, qnn_input.dim))
+            value_infos.append(helper.make_tensor_value_info(qnn_input.name, qnn_input.onnx_data_type, qnn_input.dim))
+        else:
+            model_inputs.append(helper.make_tensor_value_info(qnn_input.name, qnn_input.onnx_data_type, qnn_input.dim))
+
+    if disable_embed_mode:
+        ep_cache_context_content = qnn_ctx_file
+        ctx_embed_mode = 0
+    else:
+        with open(qnn_ctx_file, "rb") as file:
+            ep_cache_context_content = file.read()
+        ctx_embed_mode = 1
+
+    qnn_ep_context_node = helper.make_node(
+        "EPContext",
+        name=grap_name,
+        inputs=qnn_input_tensor_dic.keys(),
+        outputs=qnn_output_tensor_dic.keys(),
+        ep_cache_context=ep_cache_context_content,
+        embed_mode=ctx_embed_mode,
+        ep_sdk_version=qnn_sdk_version,
+        source="Qnn",
+        domain="com.microsoft",
+    )
+    graph_nodes.append(qnn_ep_context_node)
+
+    model_outputs = []
+    for qnn_output in sorted(qnn_output_tensor_dic.values(), key=lambda out: out.id):
+        if qnn_output.is_quantized and not quantized_IO:
+            dq_scale_input_name = qnn_output.name + "_scale"
+            dq_offset_input_name = qnn_output.name + "_zp"
+            dq_scale = helper.make_tensor(dq_scale_input_name, TensorProto.FLOAT, [], [qnn_output.scale])
+            ini_list.append(dq_scale)
+            dq_offset = helper.make_tensor(dq_offset_input_name, qnn_output.onnx_data_type, [], [qnn_output.offset])
+            ini_list.append(dq_offset)
+            output_name = qnn_output.name + "_dq"
+
+            dq_node = helper.make_node(
+                "DequantizeLinear",
+                name=output_name,
+                inputs=[qnn_output.name, dq_scale_input_name, dq_offset_input_name],
+                outputs=[output_name],
+            )
+
+            graph_nodes.append(dq_node)
+            model_outputs.append(helper.make_tensor_value_info(output_name, TensorProto.FLOAT, qnn_output.dim))
+            value_infos.append(
+                helper.make_tensor_value_info(qnn_output.name, qnn_output.onnx_data_type, qnn_output.dim)
+            )
+        else:
+            model_outputs.append(
+                helper.make_tensor_value_info(qnn_output.name, qnn_output.onnx_data_type, qnn_output.dim)
+            )
+
+    graph_def = helper.make_graph(graph_nodes, "qnn-onnx-model", model_inputs, model_outputs, ini_list, "", value_infos)
+
+    model_def = helper.make_model(graph_def, producer_name="MS")
+
+    onnx.save(model_def, model_file_name)
+
+
+# parse Qnn graph from the json file that extracted from context binary file
+def parse_qnn_graph(qnn_graph, qnn_input_tensor_dic, qnn_output_tensor_dic):
+    is_qnn_converter_json = False
+    graph_name = qnn_graph["info"]["graphName"]
+    raw_inputs = qnn_graph["info"]["graphInputs"]
+    raw_outputs = qnn_graph["info"]["graphOutputs"]
+
+    for raw_input in raw_inputs:
+        tensor_info = raw_input["info"]
+        qnn_tensor = QnnTensorStruct()
+        qnn_tensor.name = tensor_info["name"]
+        qnn_tensor.onnx_data_type = qnn_data_type_to_onnx_data_type(tensor_info["dataType"], is_qnn_converter_json)
+        qnn_tensor.is_quantized = is_quantized_data_type(tensor_info["dataType"], is_qnn_converter_json)
+        qnn_tensor.dim = tensor_info["dimensions"]
+        if (
+            tensor_info["quantizeParams"]["definition"] == "QNN_DEFINITION_DEFINED"
+            and tensor_info["quantizeParams"]["quantizationEncoding"] == "QNN_QUANTIZATION_ENCODING_SCALE_OFFSET"
+        ):
+            qnn_tensor.scale = tensor_info["quantizeParams"]["scaleOffset"]["scale"]
+            qnn_tensor.offset = 0 - tensor_info["quantizeParams"]["scaleOffset"]["offset"]
+        qnn_input_tensor_dic[qnn_tensor.name] = qnn_tensor
+
+    for raw_output in raw_outputs:
+        tensor_info = raw_output["info"]
+        qnn_tensor = QnnTensorStruct()
+        qnn_tensor.name = tensor_info["name"]
+        qnn_tensor.onnx_data_type = qnn_data_type_to_onnx_data_type(tensor_info["dataType"], is_qnn_converter_json)
+        qnn_tensor.is_quantized = is_quantized_data_type(tensor_info["dataType"], is_qnn_converter_json)
+        qnn_tensor.dim = tensor_info["dimensions"]
+        if (
+            tensor_info["quantizeParams"]["definition"] == "QNN_DEFINITION_DEFINED"
+            and tensor_info["quantizeParams"]["quantizationEncoding"] == "QNN_QUANTIZATION_ENCODING_SCALE_OFFSET"
+        ):
+            qnn_tensor.scale = tensor_info["quantizeParams"]["scaleOffset"]["scale"]
+            qnn_tensor.offset = 0 - tensor_info["quantizeParams"]["scaleOffset"]["offset"]
+        qnn_output_tensor_dic[qnn_tensor.name] = qnn_tensor
+
+    assert len(qnn_input_tensor_dic) >= 1 and len(qnn_output_tensor_dic) >= 1, (
+        "Converted QNN model not valid. It should have at least 1 input & 1 output."
+    )
+
+    return graph_name
+
+
+# Onnxruntime QNN EP can support context binary file generated by QNN tool chain. However QNN generated context binary file
+# uses channel last data layout and 8 bits or 16 bits for input and output.
+# This script gets the QNN model input & output information from QNN converted model_net.json file, compare them with Onnx model
+# and inserts Cast, Transpose nodes to Onnx model if required
+def main():
+    parser = ArgumentParser("Generate Onnx model which includes the QNN context binary.")
+    parser.add_argument("-b", "--qnn_bin", help="Required. Path to Qnn context binary file.", required=True, type=str)
+    parser.add_argument(
+        "-q", "--qnn_json", help="Required. Path to Qnn converted model_net.json file.", required=True, type=str
+    )
+    parser.add_argument(
+        "--disable_embed_mode",
+        action="store_true",
+        default=False,
+        help="Set embed_mode=1 which mean embed Qnn context binary into the onnx model. Otherwise, set context binary file path in the onnx model",
+    )
+    parser.add_argument(
+        "--quantized_IO",
+        action="store_true",
+        default=False,
+        help="QNN converted context binary use quantized data as graph inputs and outputs. Will keep it if quantized_IO=True, otherwise, will insert Q and DQ nodes accordingly to make the graph inputs & outputs as float32 data type.",
+    )
+    args = parser.parse_args()
+
+    # Parse Qnn model_net.json file to get the graph input output information
+
+    with open(args.qnn_json) as qnn_json_file:
+        qnn_json_obj = json.load(qnn_json_file)
+        if "graph" in qnn_json_obj and "tensors" in qnn_json_obj["graph"]:
+            print("This json file is from Qnn converter")
+            qnn_input_tensor_dic = {}
+            qnn_output_tensor_dic = {}
+            parse_qnn_converter_json_file(qnn_json_obj, qnn_input_tensor_dic, qnn_output_tensor_dic)
+
+            generate_wrapper_onnx_file(
+                "QnnContext",
+                args.qnn_json.replace(".json", "_qnn_ctx.onnx"),
+                qnn_input_tensor_dic,
+                qnn_output_tensor_dic,
+                args.disable_embed_mode,
+                args.qnn_bin,
+                args.quantized_IO,
+            )
+        elif "info" in qnn_json_obj and "graphs" in qnn_json_obj["info"]:
+            print("This json file is extracted from QNN context binary file")
+            qnn_version = qnn_json_obj["info"]["buildId"]
+            for qnn_graph in qnn_json_obj["info"]["graphs"]:
+                qnn_input_tensor_dic = {}
+                qnn_output_tensor_dic = {}
+                graph_name = parse_qnn_graph(qnn_graph, qnn_input_tensor_dic, qnn_output_tensor_dic)
+
+                ctx_file_name = graph_name + "_qnn_ctx.onnx"
+                if not args.quantized_IO:
+                    ctx_file_name = ctx_file_name.replace(".onnx", "_fp32_io.onnx")
+
+                generate_wrapper_onnx_file(
+                    graph_name,
+                    ctx_file_name,
+                    qnn_input_tensor_dic,
+                    qnn_output_tensor_dic,
+                    args.disable_embed_mode,
+                    args.qnn_bin,
+                    args.quantized_IO,
+                    qnn_version,
+                )
+        else:
+            print("json file unrecoginized.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/preprocess.py b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/preprocess.py
new file mode 100644
index 0000000000000000000000000000000000000000..3396bf196b4f2c687b1b605c3916334b3171334e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/tools/qnn/preprocess.py
@@ -0,0 +1,165 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+"""Provide entry point to preprocess ONNX model especially for QNN."""
+
+import argparse
+import pathlib
+
+import onnx
+
+from onnxruntime.quantization.execution_providers import qnn
+
+
+def _parse_arguments():
+    """Parse cmdline arguments."""
+    parser = argparse.ArgumentParser(description="Arguments for QNN model preprocess.")
+
+    parser.add_argument("--input_model_path", "-i", required=True, help="Path to the input ONNX model.")
+    parser.add_argument("--output_model_path", "-o", required=True, help="Path to the output ONNX model.")
+
+    # Save preprocessed model with external data.
+    parser.add_argument(
+        "--save_as_external_data",
+        action="store_true",
+        help="Whether the output model would be saved with external data.",
+    )
+    parser.add_argument(
+        "--all_tensors_to_one_file",
+        action="store_true",
+        help="Whether to save all external data in one file or save each tensor to a file named with the tensor name.",
+    )
+    parser.add_argument(
+        "--external_data_location",
+        help="Filename of the external file where all tensors are saved. The path is relative to the model path.",
+    )
+    parser.add_argument(
+        "--external_data_size_threshold",
+        default=1024,
+        type=int,
+        help="Tensors with data size larger than this threshold are converted to external data.",
+    )
+    parser.add_argument(
+        "--external_data_convert_attribute",
+        action="store_true",
+        help="Whether to save all tensors, including attribute tensors, to external data.",
+    )
+
+    # Preprocess options.
+    parser.add_argument(
+        "--fuse_layernorm",
+        action="store_true",
+        help="Whether to fuse matched sequences into LayerNormalization nodes if possible.",
+    )
+
+    # I/O layouts.
+    parser.add_argument(
+        "--inputs_to_make_channel_last",
+        nargs="+",
+        default=None,
+        help="List of graph input names to be transposed into channel-last.",
+    )
+
+    parser.add_argument(
+        "--outputs_to_make_channel_last",
+        nargs="+",
+        default=None,
+        help="List of graph output names to be transposed into channel-last.",
+    )
+
+    # Fix dynamic input shapes.
+    parser.add_argument(
+        "--dynamic_input_shapes",
+        nargs=2,
+        action="append",
+        type=str,
+        default=None,
+        help="Model input name and desired static shape in comma seprated format, for example: 'input' 1,3,256,256",
+    )
+
+    # Exclude initializer from input
+    parser.add_argument(
+        "--exclude_initializer_from_input",
+        action="store_true",
+        help="Whether to exclude initializer from input if model.ir_version >= 4",
+    )
+
+    return parser.parse_args()
+
+
+def qnn_preprocess_model(
+    model_input: str | pathlib.Path | onnx.ModelProto,
+    model_output: str | pathlib.Path,
+    fuse_layernorm: bool = False,
+    save_as_external_data: bool = False,
+    all_tensors_to_one_file: bool = False,
+    external_data_location: str | None = None,
+    external_data_size_threshold: int = 1024,
+    external_data_convert_attribute: bool = False,
+    inputs_to_make_channel_last: list[str] | None = None,
+    outputs_to_make_channel_last: list[str] | None = None,
+    dynamic_input_shapes: list[tuple[str, str]] | None = None,
+    exclude_initializer_from_input: bool = False,
+) -> bool:
+    """Preprocess ONNX model for QNN.
+
+    Args:
+        model_input: A path or ONNX ModelProto specifiying the model to be preprocessed.
+        model_output: A path specifying where the preprocessed model to be saved.
+        fuse_layernorm: A bool specifying whether to fuse the matched sequence into a single LayerNormalization node.
+            Defaults to False.
+        save_as_external_data: A bool specifying whether to save model with external data. Defaults to False.
+        all_tensors_to_one_file: A bool specifying whether to save all external data in one file or save each tensor to
+            a file named with the tensor name. This argument is effective only when `save_as_external_data` is True.
+            Defaults to False.
+        external_data_location: A str specifying where to save the external data. The path is relative to the model
+            path. This argument is effective only when `save_as_external_data` is True. Defaults to the model name.
+        external_data_size_threshold: An int specifying the threshold of data size for tensors be saved as external
+            data. This argument is effective only when `save_as_external_data` is True. Defaults to 1024.
+        external_data_convert_attribute: A bool specifying whether to save all tensors including attributes as external
+            data. This argument is effective only when `save_as_external_data` is True. Defaults to False.
+        inputs_to_make_channel_last: A list of strs specifying graph input names to be transposed into channel-last.
+            Defaults to None.
+        outputs_to_make_channel_last: A list of strs specifying graph output names to be transposed into channel-last.
+            Defaults to None.
+        dynamic_input_shapes: A list of tuples specifying model input name to and its static shape in comma seprated
+            format, for example: [('input', '1,3,256,256')]. Defaults to None.
+        exclude_initializer_from_input: A bool specifying whether to exclude initializer from input. Defaults to False.
+
+    Returns:
+        A bool indicating whether the model is modified.
+    """
+    return qnn.qnn_preprocess_model(
+        model_input,
+        model_output,
+        fuse_layernorm=fuse_layernorm,
+        save_as_external_data=save_as_external_data,
+        all_tensors_to_one_file=all_tensors_to_one_file,
+        external_data_location=external_data_location,
+        external_data_size_threshold=external_data_size_threshold,
+        external_data_convert_attribute=external_data_convert_attribute,
+        inputs_to_make_channel_last=inputs_to_make_channel_last,
+        outputs_to_make_channel_last=outputs_to_make_channel_last,
+        dynamic_input_shapes=dynamic_input_shapes,
+        exclude_initializer_from_input=exclude_initializer_from_input,
+    )
+
+
+if __name__ == "__main__":
+    args = _parse_arguments()
+    qnn_preprocess_model(
+        args.input_model_path,
+        args.output_model_path,
+        fuse_layernorm=args.fuse_layernorm,
+        save_as_external_data=args.save_as_external_data,
+        all_tensors_to_one_file=args.all_tensors_to_one_file,
+        external_data_location=args.external_data_location,
+        external_data_size_threshold=args.external_data_size_threshold,
+        external_data_convert_attribute=args.external_data_convert_attribute,
+        inputs_to_make_channel_last=args.inputs_to_make_channel_last,
+        outputs_to_make_channel_last=args.outputs_to_make_channel_last,
+        dynamic_input_shapes=args.dynamic_input_shapes,
+        exclude_initializer_from_input=args.exclude_initializer_from_input,
+    )
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8d4e73b5766956e304bb53e860612ed232322bc3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/__init__.py
@@ -0,0 +1,8 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os
+import sys
+
+sys.path.append(os.path.dirname(__file__))
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/fusion_utils.py
@@ -0,0 +1,321 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+from logging import getLogger
+
+import numpy
+from numpy import array_equal, ndarray
+from onnx import NodeProto, TensorProto, helper, numpy_helper
+from onnx_model import OnnxModel
+
+logger = getLogger(__name__)
+
+
+class FusionUtils:
+    def __init__(self, model: OnnxModel):
+        self.model: OnnxModel = model
+
+    def cast_graph_input_to_int32(self, input_name: str) -> tuple[bool, str]:
+        graph_input = self.model.find_graph_input(input_name)
+        if graph_input is not None and graph_input.type.tensor_type.elem_type != TensorProto.INT32:
+            cast_output, cast_node = self.cast_input_to_int32(input_name)
+            logger.debug(f"Casted graph input {input_name} to int32")
+            return True, cast_output
+
+        logger.debug(f"Did not cast graph input {input_name} to int32: found {graph_input is not None}")
+        return False, input_name
+
+    def cast_input(self, input_name: str, target_type="int32"):
+        output_name = input_name + "_" + target_type
+
+        if target_type == "int32":
+            to_type = int(TensorProto.INT32)
+        elif target_type == "float32":
+            to_type = int(TensorProto.FLOAT)
+        elif target_type == "float16":
+            to_type = int(TensorProto.FLOAT16)
+        else:
+            raise ValueError("Invalid target_type: {target_type}")
+
+        cast_node = self.add_cast_node(input_name, to_type, output_name)
+
+        return output_name, cast_node
+
+    def add_cast_node(
+        self,
+        input_name: str,
+        to_type: int,
+        output_name: str | None = None,
+        output_name_to_node=None,
+        graph_name: str | None = None,
+    ):
+        if output_name is None:
+            output_name = input_name + f"_cast_to_{to_type}"
+
+        # Avoid consequent Cast nodes.
+        inputs = [input_name]
+        if output_name_to_node is None:
+            output_name_to_node = self.model.output_name_to_node()
+        if input_name in output_name_to_node:
+            parent_node = output_name_to_node[input_name]
+            if parent_node and parent_node.op_type == "Cast":
+                inputs = [parent_node.input[0]]
+
+        cast_node = helper.make_node("Cast", inputs=inputs, outputs=[output_name])
+
+        cast_node.attribute.extend([helper.make_attribute("to", to_type)])
+        self.model.add_node(cast_node, graph_name=graph_name)
+
+        return cast_node
+
+    def cast_input_to_int32(self, input_name: str):
+        return self.cast_input(input_name, "int32")
+
+    def remove_cast_int32(self, input_name: str):
+        input_name_to_nodes = self.model.input_name_to_nodes()
+        nodes = input_name_to_nodes[input_name]
+        for node in nodes:
+            if node.op_type == "Cast":
+                is_int32 = False
+                for att in node.attribute:
+                    if att.name == "to" and att.i == int(TensorProto.INT32):
+                        is_int32 = True
+                        break
+                if is_int32:
+                    output_name = node.output[0]
+                    self.model.remove_node(node)
+                    self.model.replace_input_of_all_nodes(output_name, input_name)
+
+    @staticmethod
+    def update_node_input(node, i, new_input_name, input_name_to_nodes):
+        old_input_reference = 0
+        if (node.input[i] in input_name_to_nodes) and node in input_name_to_nodes[node.input[i]]:
+            input_name_to_nodes[node.input[i]].remove(node)
+            old_input_reference = len(input_name_to_nodes[node.input[i]])
+
+        node.input[i] = new_input_name
+
+        if new_input_name in input_name_to_nodes:
+            input_name_to_nodes[new_input_name].append(node)
+        else:
+            input_name_to_nodes[new_input_name] = [node]
+
+        return old_input_reference
+
+    @staticmethod
+    def skip_parent(model: OnnxModel, node, parent_node, input_name_to_nodes, node_input_index=0, parent_input_index=0):
+        """
+        Before:
+              (input)-->parent-->node-->(output)
+        After:
+              (input)-->parent-->
+                |
+                +----->node-->(output)
+
+        This function returns a flag whether the parent node can be removed.
+        """
+
+        old_input_name = node.input[node_input_index]
+        new_input_name = parent_node.input[parent_input_index]
+        old_input_reference = FusionUtils.update_node_input(node, node_input_index, new_input_name, input_name_to_nodes)
+
+        # We can remove the first Transpose if its output is not used (linked to graph output or other nodes) anymore.
+        parent_can_be_removed = (old_input_reference == 0) and not model.find_graph_output(old_input_name)
+
+        return parent_can_be_removed
+
+    def get_squeeze_or_unsqueeze_axes(self, node: NodeProto) -> ndarray | None:
+        assert node.op_type in ["Squeeze", "Unsqueeze"]
+
+        # For opset >= 13, axes is an input instead of an attribute.
+        if len(node.input) > 1:
+            return self.model.get_constant_value(node.input[1])
+
+        axes = None
+        for attr in node.attribute:
+            if attr.name == "axes":
+                axes = helper.get_attribute_value(attr)
+        return axes
+
+    @staticmethod
+    def check_node_attribute(node, attribute_name: str, expected_value, default_value=None):
+        """Verify that a node has expected value for an attribute.
+
+        Args:
+            node (NodeProto): a node to check
+            attribute_name (str): name of attribute
+            expected_value (Any): expected value of the attribute
+            default_value (Any, optional): default value if the attribute does not exist. Defaults to None.
+
+        Returns:
+            bool: whether the check is passed or not
+        """
+        value = default_value
+        for attr in node.attribute:
+            if attr.name == attribute_name:
+                value = helper.get_attribute_value(attr)
+
+        if isinstance(expected_value, list):
+            return (isinstance(value, (ndarray, list))) and array_equal(expected_value, value, equal_nan=False)
+        else:
+            return value == expected_value
+
+    @staticmethod
+    def transpose_2d_int8_tensor(tensor: TensorProto):
+        """Transpose a 2-D INT8 TensorProto
+        Args:
+            tensor (TensorProto): tensor to be transposed
+        Returns:
+            tensor (TensorProto): transposed tensor
+        """
+        if not isinstance(tensor, TensorProto):
+            raise TypeError(f"Expected input type is an ONNX TensorProto but got {type(tensor)}")
+
+        if len(tensor.dims) != 2 or tensor.data_type != TensorProto.INT8:
+            raise ValueError("Only INT8 2-D tensors can be transposed")
+
+        if tensor.raw_data:
+            int32_data = numpy.reshape(numpy.frombuffer(tensor.raw_data, dtype="int8"), tensor.dims)
+            int32_transposed_data = numpy.transpose(int32_data, [1, 0])
+            tensor.raw_data = int32_transposed_data.tobytes()
+
+        else:
+            raise ValueError("only raw buffer supported")
+
+        return tensor
+
+    @staticmethod
+    def check_qdq_node_for_fusion(node: NodeProto, model: OnnxModel, allow_per_tensor_quantization_only=True):
+        """Verify if a provided QuantizeLinear (Q) / DequantizeLinear (DQ) node is a good candidate for fusion.
+           It is a good candidate for fusion if:
+           (1) The Q/DQ node is for per-tensor quantization if allow_per_tensor_quantization_only is `True`
+           (2) The Q/DQ node should have constant scale
+           (3) The Q/DQ node should have a zero point of 0
+        Args:
+            node (NodeProto): a Q/DQ node to check
+        Returns:
+            bool: whether the check is passed or not
+        """
+        if node.op_type not in {"QuantizeLinear", "DequantizeLinear"}:
+            logger.debug(f"Provided node is not a Q/DQ node. Op Type: {node.op_type}")
+
+        scale = model.get_constant_value(node.input[1])
+
+        # Scale is not constant
+        if scale is None:
+            return False
+
+        # Not per-tensor quantization
+        scale_has_single_element = scale.ndim == 0 or (scale.ndim == 1 and scale.shape[0] == 1)
+        if allow_per_tensor_quantization_only and not scale_has_single_element:
+            return False
+
+        # If the Q/DQ node has no zero point input, it is assumed to be 0 (per ONNX spec)
+        if len(node.input) == 2:
+            return True
+
+        # Zero point should be constant and should have a value of 0
+        zero_point = model.get_constant_value(node.input[2])
+
+        # Zero point and scale should have same number of dims
+        if scale.ndim != zero_point.ndim:
+            return False
+
+        # Zero point is not constant or zero point is not zero
+        if zero_point is None:
+            return False
+
+        return numpy.all(zero_point == 0)
+
+    def check_node_input_value(self, node, input_index: int, expected_value):
+        """Verify that a node has expected input value
+
+        Args:
+            node (NodeProto): a node to check
+            input_index (int): index of its input to be verified
+            expected_value (Any): expected value of the input
+
+        Returns:
+            bool: whether the check is passed or not
+        """
+        assert len(node.input) > input_index
+
+        value = self.model.get_constant_value(node.input[input_index])
+
+        if isinstance(expected_value, list):
+            return (isinstance(value, (ndarray, list))) and array_equal(expected_value, value, equal_nan=False)
+        else:
+            return value == expected_value
+
+    def remove_identity_nodes(self):
+        """Remove Identity nodes, except those right before graph output."""
+        nodes_to_remove = []
+        graph_output_names = self.model.get_graphs_output_names()
+        for node in self.model.nodes():
+            if node.op_type == "Identity":
+                if node.output[0] not in graph_output_names:
+                    self.model.replace_input_of_all_nodes(node.output[0], node.input[0])
+                    nodes_to_remove.append(node)
+
+        if nodes_to_remove:
+            self.model.remove_nodes(nodes_to_remove)
+            logger.info(f"Removed {len(nodes_to_remove)} Identity nodes")
+
+    def remove_cascaded_cast_nodes(self):
+        self.model.remove_cascaded_cast_nodes()
+
+    def remove_useless_cast_nodes(self):
+        self.model.remove_useless_cast_nodes()
+
+    def remove_useless_reshape_nodes(self):
+        """Remove reshape node that is not needed based on symbolic shape inference: input and output has same shape"""
+        shape_infer = self.model.infer_runtime_shape(update=True)
+        if shape_infer is None:
+            return
+
+        nodes_to_remove = []
+        for node in self.model.nodes():
+            if node.op_type == "Reshape":
+                input_shape = shape_infer.get_edge_shape(node.input[0])
+                output_shape = shape_infer.get_edge_shape(node.output[0])
+                if input_shape and output_shape and input_shape == output_shape:
+                    logger.info(
+                        f"Remove reshape node {node.name} since its input shape is same as output: {input_shape}"
+                    )
+                    nodes_to_remove.append(node)
+
+        if nodes_to_remove:
+            graph_input_names = set(self.model.get_graphs_input_names())
+            graph_output_names = set(self.model.get_graphs_output_names())
+            for node in nodes_to_remove:
+                if bool(set(node.output) & graph_output_names):
+                    if (
+                        not bool(set(node.input) & graph_input_names)
+                        and len(self.model.input_name_to_nodes()[node.input[0]]) == 1  # parent has only one child
+                    ):
+                        self.model.replace_output_of_all_nodes(node.input[0], node.output[0])
+                    else:
+                        continue
+                else:
+                    self.model.replace_input_of_all_nodes(node.output[0], node.input[0])
+                self.model.remove_node(node)
+
+
+class NumpyHelper:
+    @staticmethod
+    def to_array(tensor: TensorProto, fill_zeros: bool = False) -> ndarray:
+        # When weights are in external data format but not presented, we can still test the optimizer with two changes:
+        # (1) set fill_zeros = True  (2) change load_external_data=False in optimizer.py
+        if fill_zeros:
+            return ndarray(
+                shape=tensor.dims,
+                dtype=helper.tensor_dtype_to_np_dtype(tensor.data_type),
+            )
+
+        if tensor.data_type == TensorProto.BFLOAT16:
+            import onnx_ir as ir  # noqa: PLC0415
+
+            # Use onnx_ir to correctly handle bfloat16 tensors
+            return ir.from_proto(tensor).numpy()
+        return numpy_helper.to_array(tensor)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/huggingface_models.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/huggingface_models.py
new file mode 100644
index 0000000000000000000000000000000000000000..f38390dfb74f0377e74bc6648e4cb060cc696241
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/huggingface_models.py
@@ -0,0 +1,74 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+# Maps model class name to a tuple of model class
+MODEL_CLASSES = [
+    "AutoModel",
+    "AutoModelWithLMHead",
+    "AutoModelForSequenceClassification",
+    "AutoModelForQuestionAnswering",
+    "AutoModelForCausalLM",
+]
+
+# Pretrained model name to a tuple of input names, opset_version, use_external_data_format, optimization model type
+# Some models like GPT, T5, Bart etc has its own convert_to_onnx.py in models sub-directory, and they are excluded here.
+MODELS = {
+    # BERT
+    "bert-base-cased": (["input_ids", "attention_mask", "token_type_ids"], 16, False, "bert"),
+    "bert-large-cased": (["input_ids", "attention_mask", "token_type_ids"], 16, False, "bert"),
+    # Transformer-XL (Models uses Einsum, which need opset version 16 or later.)
+    "transfo-xl-wt103": (["input_ids", "mems"], 16, False, "bert"),
+    # XLNet
+    "xlnet-base-cased": (["input_ids"], 16, False, "bert"),
+    "xlnet-large-cased": (["input_ids"], 16, False, "bert"),
+    # XLM
+    "xlm-mlm-en-2048": (["input_ids"], 16, True, "bert"),
+    "xlm-mlm-ende-1024": (["input_ids"], 16, False, "bert"),
+    "xlm-mlm-enfr-1024": (["input_ids"], 16, False, "bert"),
+    # RoBERTa
+    "roberta-base": (["input_ids", "attention_mask"], 16, False, "bert"),
+    "roberta-large": (["input_ids", "attention_mask"], 16, False, "bert"),
+    "roberta-large-mnli": (["input_ids", "attention_mask"], 16, False, "bert"),
+    "deepset/roberta-base-squad2": (["input_ids", "attention_mask"], 16, False, "bert"),
+    "distilroberta-base": (["input_ids", "attention_mask"], 16, False, "bert"),
+    # DistilBERT
+    "distilbert-base-uncased": (["input_ids", "attention_mask"], 16, False, "bert"),
+    "distilbert-base-uncased-distilled-squad": (["input_ids", "attention_mask"], 16, False, "bert"),
+    # CTRL
+    "ctrl": (["input_ids"], 16, True, "bert"),
+    # CamemBERT
+    "camembert-base": (["input_ids"], 16, False, "bert"),
+    # ALBERT
+    "albert-base-v1": (["input_ids"], 16, False, "bert"),
+    "albert-large-v1": (["input_ids"], 16, False, "bert"),
+    "albert-xlarge-v1": (["input_ids"], 16, True, "bert"),
+    # "albert-xxlarge-v1": (["input_ids"], 16, True, "bert"),
+    "albert-base-v2": (["input_ids"], 16, False, "bert"),
+    "albert-large-v2": (["input_ids"], 16, False, "bert"),
+    "albert-xlarge-v2": (["input_ids"], 16, True, "bert"),
+    # "albert-xxlarge-v2": (["input_ids"], 16, True, "bert"),
+    # XLM-RoBERTa
+    "xlm-roberta-base": (["input_ids"], 16, False, "bert"),
+    "xlm-roberta-large": (["input_ids"], 16, True, "bert"),
+    # FlauBERT
+    "flaubert/flaubert_small_cased": (["input_ids"], 16, False, "bert"),
+    "flaubert/flaubert_base_cased": (["input_ids"], 16, False, "bert"),
+    # "flaubert/flaubert_large_cased": (["input_ids"], 16, False, "bert"),
+    # Layoutlm
+    "microsoft/layoutlm-base-uncased": (["input_ids"], 16, False, "bert"),
+    "microsoft/layoutlm-large-uncased": (["input_ids"], 16, False, "bert"),
+    # Squeezebert
+    "squeezebert/squeezebert-uncased": (["input_ids"], 16, False, "bert"),
+    "squeezebert/squeezebert-mnli": (["input_ids"], 16, False, "bert"),
+    "squeezebert/squeezebert-mnli-headless": (["input_ids"], 16, False, "bert"),
+    "unc-nlp/lxmert-base-uncased": (["input_ids", "visual_feats", "visual_pos"], 16, False, "bert"),
+    # ViT
+    "google/vit-base-patch16-224": (["pixel_values"], 16, False, "vit"),
+    # Swin
+    "microsoft/swin-base-patch4-window7-224": (["pixel_values"], 16, False, "swin"),
+    "microsoft/swin-small-patch4-window7-224": (["pixel_values"], 16, False, "swin"),
+    "microsoft/swin-tiny-patch4-window7-224": (["pixel_values"], 16, False, "swin"),
+}
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/import_utils.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/import_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..9015231850db6519b15e0d4887dc44f412640b00
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/import_utils.py
@@ -0,0 +1,20 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import importlib.metadata
+import importlib.util
+
+
+def is_installed(package):
+    try:
+        dist = importlib.metadata.distribution(package)
+    except importlib.metadata.PackageNotFoundError:
+        try:
+            spec = importlib.util.find_spec(package)
+        except ModuleNotFoundError:
+            return False
+
+        return spec is not None
+
+    return dist is not None
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/io_binding_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/io_binding_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..24c3917bf4341c899cffe0ccb149b65674d68475
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/io_binding_helper.py
@@ -0,0 +1,538 @@
+import copy
+import logging
+from collections import OrderedDict
+from collections.abc import Mapping
+from typing import Any
+
+import numpy
+import torch
+from onnx import TensorProto
+
+from onnxruntime import InferenceSession, RunOptions
+
+# Type alias
+ShapeDict = Mapping[str, tuple | list[int]]
+
+logger = logging.getLogger(__name__)
+
+
+class TypeHelper:
+    @staticmethod
+    def get_input_type(ort_session: InferenceSession, name: str) -> str:
+        for _i, input in enumerate(ort_session.get_inputs()):
+            if input.name == name:
+                return input.type
+        raise ValueError(f"input name {name} not found")
+
+    @staticmethod
+    def get_output_type(ort_session, name: str) -> str:
+        for _i, output in enumerate(ort_session.get_outputs()):
+            if output.name == name:
+                return output.type
+
+        raise ValueError(f"output name {name} not found")
+
+    @staticmethod
+    def ort_type_to_numpy_type(ort_type: str):
+        ort_type_to_numpy_type_map = {
+            "tensor(int64)": numpy.int64,
+            "tensor(int32)": numpy.int32,
+            "tensor(float)": numpy.float32,
+            "tensor(float16)": numpy.float16,
+            "tensor(bool)": bool,
+            "tensor(uint8)": numpy.uint8,
+            "tensor(int8)": numpy.int8,
+            "tensor(double)": numpy.float64,
+            "tensor(int16)": numpy.int16,
+            "tensor(uint16)": numpy.uint16,
+            "tensor(uint32)": numpy.uint32,
+            "tensor(uint64)": numpy.uint64,
+            "tensor(complex64)": numpy.complex64,
+            "tensor(complex128)": numpy.complex128,
+        }
+        if ort_type not in ort_type_to_numpy_type_map:
+            raise ValueError(f"{ort_type} not found in map")
+
+        return ort_type_to_numpy_type_map[ort_type]
+
+    @staticmethod
+    def ort_type_to_torch_type(ort_type: str):
+        ort_type_to_torch_type_map = {
+            "tensor(int64)": torch.int64,
+            "tensor(int32)": torch.int32,
+            "tensor(float)": torch.float32,
+            "tensor(float16)": torch.float16,
+            "tensor(bfloat16)": torch.bfloat16,
+            "tensor(bool)": torch.bool,
+            "tensor(uint8)": torch.uint8,
+            "tensor(int8)": torch.int8,
+            "tensor(double)": torch.float64,
+            "tensor(int16)": torch.int16,
+            "tensor(uint16)": torch.uint16,
+            "tensor(uint32)": torch.uint32,
+            "tensor(uint64)": torch.uint64,
+            "tensor(complex64)": torch.complex64,
+            "tensor(complex128)": torch.complex128,
+            "tensor(float8e4m3fn)": torch.float8_e4m3fn,
+            "tensor(float8e4m3fnuz)": torch.float8_e4m3fnuz,
+            "tensor(float8e5m2)": torch.float8_e5m2,
+            "tensor(float8e5m2fnuz)": torch.float8_e5m2fnuz,
+            "tensor(int4)": torch.int4,
+            "tensor(uint4)": torch.uint4,
+        }
+        if ort_type not in ort_type_to_torch_type_map:
+            raise ValueError(f"{ort_type} not found in map")
+
+        return ort_type_to_torch_type_map[ort_type]
+
+    @staticmethod
+    def get_io_onnx_type_map(ort_session: InferenceSession) -> dict[str, int]:
+        """Create a mapping from input/output name to onnx data type"""
+        name_to_onnx_type = {}
+        for input in ort_session.get_inputs():
+            name_to_onnx_type[input.name] = TypeHelper.ort_type_to_onnx_type(input.type)
+
+        for output in ort_session.get_outputs():
+            name_to_onnx_type[output.name] = TypeHelper.ort_type_to_onnx_type(output.type)
+        return name_to_onnx_type
+
+    @staticmethod
+    def ort_type_to_onnx_type(ort_type: str):
+        ort_type_to_onnx_type_map = {
+            "tensor(int64)": TensorProto.INT64,
+            "tensor(int32)": TensorProto.INT32,
+            "tensor(float)": TensorProto.FLOAT,
+            "tensor(float16)": TensorProto.FLOAT16,
+            "tensor(bfloat16)": TensorProto.BFLOAT16,
+            "tensor(bool)": TensorProto.BOOL,
+            "tensor(uint8)": TensorProto.UINT8,
+            "tensor(int8)": TensorProto.INT8,
+            "tensor(double)": TensorProto.DOUBLE,
+            "tensor(int16)": TensorProto.INT16,
+            "tensor(uint16)": TensorProto.UINT16,
+            "tensor(uint32)": TensorProto.UINT32,
+            "tensor(uint64)": TensorProto.UINT64,
+            "tensor(complex64)": TensorProto.COMPLEX64,
+            "tensor(complex128)": TensorProto.COMPLEX128,
+            "tensor(float8e4m3fn)": TensorProto.FLOAT8E4M3FN,
+            "tensor(float8e4m3fnuz)": TensorProto.FLOAT8E4M3FNUZ,
+            "tensor(float8e5m2)": TensorProto.FLOAT8E5M2,
+            "tensor(float8e5m2fnuz)": TensorProto.FLOAT8E5M2FNUZ,
+            "tensor(float4e2m1)": TensorProto.FLOAT4E2M1,
+            "tensor(int4)": TensorProto.INT4,
+            "tensor(uint4)": TensorProto.UINT4,
+            "tensor(string)": TensorProto.STRING,
+        }
+        if ort_type not in ort_type_to_onnx_type_map:
+            raise ValueError(f"{ort_type} not found in map")
+
+        return ort_type_to_onnx_type_map[ort_type]
+
+    @staticmethod
+    def numpy_type_to_torch_type(numpy_type: numpy.dtype):
+        numpy_type_to_torch_type_map = {
+            numpy.int64: torch.int64,
+            numpy.int32: torch.int32,
+            numpy.float32: torch.float32,
+            numpy.float16: torch.float16,
+            bool: torch.bool,
+            numpy.uint8: torch.uint8,
+            numpy.int8: torch.int8,
+            numpy.float64: torch.float64,
+            numpy.int16: torch.int16,
+            numpy.uint16: torch.uint16,
+            numpy.uint32: torch.uint32,
+            numpy.uint64: torch.uint64,
+            numpy.complex64: torch.complex64,
+            numpy.complex128: torch.complex128,
+        }
+
+        if numpy_type not in numpy_type_to_torch_type_map:
+            raise ValueError(f"{numpy_type} not found in map")
+
+        return numpy_type_to_torch_type_map[numpy_type]
+
+    @staticmethod
+    def torch_type_to_numpy_type(torch_type: torch.dtype):
+        torch_type_to_numpy_type_map = {
+            torch.int64: numpy.int64,
+            torch.int32: numpy.int32,
+            torch.float32: numpy.float32,
+            torch.float16: numpy.float16,
+            torch.bool: bool,
+            torch.uint8: numpy.uint8,
+            torch.int8: numpy.int8,
+            torch.float64: numpy.float64,
+            torch.int16: numpy.int16,
+            torch.uint16: numpy.uint16,
+            torch.uint32: numpy.uint32,
+            torch.uint64: numpy.uint64,
+            torch.complex64: numpy.complex64,
+            torch.complex128: numpy.complex128,
+        }
+
+        if torch_type not in torch_type_to_numpy_type_map:
+            raise ValueError(f"{torch_type} not found in map")
+
+        return torch_type_to_numpy_type_map[torch_type]
+
+    @staticmethod
+    def get_io_numpy_type_map(ort_session: InferenceSession) -> dict[str, numpy.dtype]:
+        """Create a mapping from input/output name to numpy data type"""
+        name_to_numpy_type = {}
+        for input in ort_session.get_inputs():
+            name_to_numpy_type[input.name] = TypeHelper.ort_type_to_numpy_type(input.type)
+
+        for output in ort_session.get_outputs():
+            name_to_numpy_type[output.name] = TypeHelper.ort_type_to_numpy_type(output.type)
+        return name_to_numpy_type
+
+    @staticmethod
+    def get_io_torch_type_map(ort_session: InferenceSession) -> dict[str, torch.dtype]:
+        """Create a mapping from input/output name to torch data type"""
+        name_to_torch_type = {}
+        for input in ort_session.get_inputs():
+            name_to_torch_type[input.name] = TypeHelper.ort_type_to_torch_type(input.type)
+
+        for output in ort_session.get_outputs():
+            name_to_torch_type[output.name] = TypeHelper.ort_type_to_torch_type(output.type)
+        return name_to_torch_type
+
+
+class IOBindingHelper:
+    @staticmethod
+    def get_output_buffers(ort_session: InferenceSession, output_shapes, device):
+        """Returns a dictionary of output name as key, and 1D tensor as value. The tensor has enough space for given shape."""
+        output_buffers = {}
+        for name, shape in output_shapes.items():
+            ort_type = TypeHelper.get_output_type(ort_session, name)
+            torch_type = TypeHelper.ort_type_to_torch_type(ort_type)
+            output_buffers[name] = torch.empty(numpy.prod(shape), dtype=torch_type, device=device)
+        return output_buffers
+
+    @staticmethod
+    def prepare_io_binding(
+        ort_session,
+        input_ids: torch.Tensor,
+        position_ids: torch.Tensor,
+        attention_mask: torch.Tensor,
+        past: list[torch.Tensor],
+        output_buffers,
+        output_shapes,
+    ):
+        """IO binding for a session: bind inputs (input_ids, position_ids, attention_mask, past_*) and outputs."""
+
+        name_to_onnx_type = TypeHelper.get_io_onnx_type_map(ort_session)
+
+        # Bind inputs and outputs to onnxruntime session
+        io_binding = ort_session.io_binding()
+
+        # Bind inputs
+        assert input_ids.is_contiguous()
+        io_binding.bind_input(
+            "input_ids",
+            input_ids.device.type,
+            0,
+            name_to_onnx_type["input_ids"],
+            list(input_ids.size()),
+            input_ids.data_ptr(),
+        )
+
+        if past is not None:
+            for i, past_i in enumerate(past):
+                assert past_i.is_contiguous()
+
+                data_ptr = past_i.data_ptr()
+                if data_ptr == 0:
+                    # When past_sequence_length is 0, its data_ptr will be zero. IO Binding asserts that data_ptr shall not be zero.
+                    # Here we workaround and pass data pointer of input_ids. Actual data is not used for past so it does not matter.
+                    data_ptr = input_ids.data_ptr()
+
+                io_binding.bind_input(
+                    f"past_{i}",
+                    past_i.device.type,
+                    0,
+                    name_to_onnx_type[f"past_{i}"],
+                    list(past_i.size()),
+                    data_ptr,
+                )
+
+        if attention_mask is not None:
+            assert attention_mask.is_contiguous()
+            io_binding.bind_input(
+                "attention_mask",
+                attention_mask.device.type,
+                0,
+                name_to_onnx_type["attention_mask"],
+                list(attention_mask.size()),
+                attention_mask.data_ptr(),
+            )
+
+        if position_ids is not None:
+            assert position_ids.is_contiguous()
+            io_binding.bind_input(
+                "position_ids",
+                position_ids.device.type,
+                0,
+                name_to_onnx_type["position_ids"],
+                list(position_ids.size()),
+                position_ids.data_ptr(),
+            )
+
+        # Bind outputs
+        for output in ort_session.get_outputs():
+            output_name = output.name
+            output_buffer = output_buffers[output_name]
+            logger.debug(f"{output_name} device type={output_buffer.device.type} shape={list(output_buffer.size())}")
+            io_binding.bind_output(
+                output_name,
+                output_buffer.device.type,
+                0,
+                name_to_onnx_type[output_name],
+                output_shapes[output_name],
+                output_buffer.data_ptr(),
+            )
+
+        return io_binding
+
+    @staticmethod
+    def get_outputs_from_io_binding_buffer(ort_session, output_buffers, output_shapes, return_numpy=True):
+        """Copy results to cpu. Returns a list of numpy array."""
+        ort_outputs = []
+        for output in ort_session.get_outputs():
+            output_name = output.name
+            buffer = output_buffers[output_name]
+            shape = output_shapes[output_name]
+            copy_tensor = buffer[0 : numpy.prod(shape)].reshape(shape).clone().detach()
+            if return_numpy:
+                ort_outputs.append(copy_tensor.cpu().numpy())
+            else:
+                ort_outputs.append(copy_tensor)
+        return ort_outputs
+
+
+class CudaSession:
+    """Inference Session with IO Binding for ONNX Runtime CUDA or TensorRT provider"""
+
+    def __init__(self, ort_session: InferenceSession, device: torch.device, enable_cuda_graph=False):
+        self.ort_session = ort_session
+        self.input_names = [input.name for input in self.ort_session.get_inputs()]
+        self.output_names = [output.name for output in self.ort_session.get_outputs()]
+        self.io_name_to_onnx_type = TypeHelper.get_io_onnx_type_map(self.ort_session)
+        self.io_name_to_torch_type = TypeHelper.get_io_torch_type_map(self.ort_session)
+        self.io_binding = self.ort_session.io_binding()
+        self.enable_cuda_graph = enable_cuda_graph
+
+        self.input_tensors = OrderedDict()
+        self.output_tensors = OrderedDict()
+        self.device = device
+
+        # Pairs of input and output names that share the same buffer.
+        self.buffer_sharing: dict[str, str] = {}
+
+    def set_buffer_sharing(self, input_name: str, output_name: str):
+        assert input_name in self.input_names
+        assert output_name in self.output_names
+        self.buffer_sharing[input_name] = output_name
+        self.buffer_sharing[output_name] = input_name
+
+    def __del__(self):
+        del self.input_tensors
+        del self.output_tensors
+        del self.io_binding
+
+    def bind_input_and_buffer_sharing(self, name: str, tensor: torch.Tensor):
+        device_id = tensor.device.index if tensor.device.index is not None else 0
+        tensor_shape = [1] if len(tensor.shape) == 0 else list(tensor.shape)
+
+        self.io_binding.bind_input(
+            name,
+            tensor.device.type,
+            device_id,
+            self.io_name_to_onnx_type[name],
+            tensor_shape,
+            tensor.data_ptr(),
+        )
+
+        if name in self.buffer_sharing:
+            self.io_binding.bind_output(
+                self.buffer_sharing[name],
+                tensor.device.type,
+                device_id,
+                self.io_name_to_onnx_type[name],
+                tensor_shape,
+                tensor.data_ptr(),
+            )
+            self.output_tensors[self.buffer_sharing[name]] = tensor
+
+    def allocate_buffers(self, shape_dict: ShapeDict):
+        """Allocate tensors for I/O Binding"""
+        if self.enable_cuda_graph:
+            for name, shape in shape_dict.items():
+                if name in self.input_names:
+                    # Reuse allocated buffer when the shape is same
+                    if name in self.input_tensors:
+                        if tuple(self.input_tensors[name].shape) == tuple(shape):
+                            continue
+                        raise RuntimeError("Expect static input shape for cuda graph")
+
+                    torch_dtype = self.io_name_to_torch_type[name]
+                    tensor = torch.empty(tuple(shape), dtype=torch_dtype).to(device=self.device)
+                    self.input_tensors[name] = tensor
+                    self.bind_input_and_buffer_sharing(name, tensor)
+
+        for name, shape in shape_dict.items():
+            if name in self.output_names:
+                # Reuse allocated buffer when the shape is same
+                if name in self.output_tensors and tuple(self.output_tensors[name].shape) == tuple(shape):
+                    continue
+
+                if name in self.buffer_sharing:
+                    continue
+
+                torch_dtype = self.io_name_to_torch_type[name]
+                tensor = torch.empty(tuple(shape), dtype=torch_dtype).to(device=self.device)
+                self.output_tensors[name] = tensor
+
+                self.io_binding.bind_output(
+                    name,
+                    tensor.device.type,
+                    tensor.device.index if tensor.device.index is not None else 0,
+                    self.io_name_to_onnx_type[name],
+                    list(tensor.size()),
+                    tensor.data_ptr(),
+                )
+
+    def infer(self, feed_dict: dict[str, torch.Tensor], run_options: RunOptions = None, synchronize: bool = True):
+        """Bind input tensors and run inference"""
+        for name, tensor in feed_dict.items():
+            assert isinstance(tensor, torch.Tensor) and tensor.is_contiguous()
+            if name in self.input_names:
+                if self.enable_cuda_graph:
+                    assert self.input_tensors[name].nelement() == tensor.nelement()
+                    assert self.input_tensors[name].dtype == tensor.dtype
+                    assert tensor.device.type == "cuda"
+                    self.input_tensors[name].copy_(tensor)
+                else:
+                    self.bind_input_and_buffer_sharing(name, tensor)
+
+        if synchronize:
+            self.io_binding.synchronize_inputs()
+            self.ort_session.run_with_iobinding(self.io_binding, run_options)
+            self.io_binding.synchronize_outputs()
+        else:
+            self.ort_session.run_with_iobinding(self.io_binding, run_options)
+
+        return self.output_tensors
+
+    @staticmethod
+    def get_cuda_provider_options(device_id: int, enable_cuda_graph: bool, stream: int = 0) -> dict[str, Any]:
+        options = {
+            "device_id": device_id,
+            "arena_extend_strategy": "kSameAsRequested",
+            "enable_cuda_graph": enable_cuda_graph,
+        }
+
+        # Stream is address of a CUDA stream. 0 means the default stream.
+        if stream != 0:
+            options["user_compute_stream"] = str(stream)
+
+        return options
+
+
+class GpuBinding(CudaSession):
+    def __init__(
+        self,
+        ort_session: InferenceSession,
+        device: torch.device,
+        shape_dict: ShapeDict,
+        enable_gpu_graph: bool = False,
+        gpu_graph_id: int = -1,
+        stream: int = 0,
+        buffer_sharing: dict[str, str] | None = None,
+    ):
+        super().__init__(ort_session, device, enable_gpu_graph)
+        if buffer_sharing:
+            for input_name, output_name in buffer_sharing.items():
+                self.set_buffer_sharing(input_name, output_name)
+
+        self.allocate_buffers(shape_dict)
+        self.gpu_graph_id = gpu_graph_id
+        # For cuda graph, we need to keep a copy of shape_dict to check if the shape is same in inference later.
+        self.shape_dict = copy.deepcopy(shape_dict) if enable_gpu_graph else None
+        self.stream = stream
+        # The gpu graph id of last run. It will be saved to image metadata.
+        self.last_run_gpu_graph_id = None
+
+    def get_run_options(self, disable_cuda_graph_in_run: bool = False) -> RunOptions:
+        options = RunOptions()
+
+        gpu_graph_id = -1 if disable_cuda_graph_in_run else self.gpu_graph_id
+
+        options.add_run_config_entry("gpu_graph_id", str(gpu_graph_id))
+
+        self.last_run_gpu_graph_id = gpu_graph_id
+
+        return options
+
+    def infer(self, feed_dict: dict[str, torch.Tensor], disable_cuda_graph_in_run: bool = False):
+        run_options = self.get_run_options(disable_cuda_graph_in_run)
+
+        if self.stream:
+            run_options.add_run_config_entry("disable_synchronize_execution_providers", "1")
+
+        return super().infer(feed_dict, run_options)
+
+
+class GpuBindingManager:
+    """A manager for I/O bindings that support multiple CUDA Graphs.
+    One cuda graph is reused for same input shape. Automatically add a new cuda graph for new input shape.
+    """
+
+    def __init__(self, ort_session: InferenceSession, device: torch.device, stream: int = 0, max_cuda_graphs: int = 1):
+        self.ort_session = ort_session
+        self.device = device
+
+        # Binding supports cuda graphs. For a binding, it is able to disable cuda graph for a specific run.
+        self.graph_bindings = []
+
+        # Binding for not using cuda graph.
+        self.no_graph_binding = None
+
+        self.stream = stream
+
+        self.max_cuda_graphs = max_cuda_graphs
+
+    def get_binding(
+        self,
+        shape_dict: ShapeDict,
+        use_cuda_graph: bool = False,
+        buffer_sharing: dict[str, str] | None = None,
+    ) -> GpuBinding:
+        for gpu_graph_binding in self.graph_bindings:
+            # Found a cuda graph that captured with the same shape
+            if gpu_graph_binding.shape_dict == shape_dict:
+                return gpu_graph_binding
+
+        # Reached the maximum number of cuda graphs. Return a binding without cuda graph.
+        if len(self.graph_bindings) >= self.max_cuda_graphs or (not use_cuda_graph):
+            if self.no_graph_binding is None:
+                self.no_graph_binding = GpuBinding(
+                    self.ort_session, self.device, shape_dict, stream=self.stream, buffer_sharing=buffer_sharing
+                )
+            else:
+                self.no_graph_binding.allocate_buffers(shape_dict)
+            return self.no_graph_binding
+
+        # This is a new input shape, create a new cuda graph
+        gpu_graph_binding = GpuBinding(
+            self.ort_session,
+            self.device,
+            shape_dict,
+            enable_gpu_graph=True,
+            gpu_graph_id=len(self.graph_bindings),
+            stream=self.stream,
+            buffer_sharing=buffer_sharing,
+        )
+        self.graph_bindings.append(gpu_graph_binding)
+        return gpu_graph_binding
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/large_model_exporter.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/large_model_exporter.py
new file mode 100644
index 0000000000000000000000000000000000000000..b9ae08cb439000c157b6937a9f72500178b2d6d9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/large_model_exporter.py
@@ -0,0 +1,396 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+"""
+Export LLM to onnx
+"""
+
+import argparse
+import inspect
+import math
+import os
+import tempfile
+from pathlib import Path
+
+import onnx
+import torch
+import transformers
+from torch import nn
+
+
+def disable_huggingface_init():
+    """do not init model twice as it slow initialization"""
+
+    torch.nn.init.kaiming_uniform_ = lambda x, *args, **kwargs: x
+    torch.nn.init.uniform_ = lambda x, *args, **kwargs: x
+    torch.nn.init.normal_ = lambda x, *args, **kwargs: x
+    torch.nn.init.constant_ = lambda x, *args, **kwargs: x
+    torch.nn.init.xavier_uniform_ = lambda x, *args, **kwargs: x
+    torch.nn.init.xavier_normal_ = lambda x, *args, **kwargs: x
+    torch.nn.init.kaiming_normal_ = lambda x, *args, **kwargs: x
+    torch.nn.init.orthogonal_ = lambda x, *args, **kwargs: x
+
+
+def get_model_parameter_size(model: nn.Module):
+    """to calculate how much memory this model needs"""
+    param_size = 0
+    param_sum = 0
+    for param in model.parameters():
+        param_size += param.nelement() * param.element_size()
+        param_sum += param.nelement()
+    buffer_size = 0
+    buffer_sum = 0
+    for buffer in model.buffers():
+        buffer_size += buffer.nelement() * buffer.element_size()
+        buffer_sum += buffer.nelement()
+    all_size = (param_size + buffer_size) / 1024 / 1024
+    return all_size
+
+
+def initialize_model_and_sample_inputs(hf_model: str, cache_dir: str | None, tokenizer=None):
+    """
+    get the pretrained torch model from hugginface,
+    and sample model-inputs
+    """
+
+    disable_huggingface_init()
+
+    model = transformers.AutoModelForCausalLM.from_pretrained(  # type: ignore
+        hf_model, torch_dtype=torch.float16, cache_dir=cache_dir, trust_remote_code=True
+    )
+    if tokenizer is None:
+        tokenizer = hf_model
+    tokenizer = transformers.AutoTokenizer.from_pretrained(tokenizer)  # type: ignore
+
+    sample_inputs = tuple(tokenizer("Hello, my dog is cute", return_tensors="pt").values())
+    return model, sample_inputs
+
+
+def auto_pipeline_parallel(model: nn.Module, gpulist: list, sample_inputs: tuple):
+    """Make the model executable across multiple GPUs."""
+
+    def input_gpu_device_hook(mod, inputs, kwargs):
+        modifyed_inputs = []
+        first_dev = None
+        for layer_input in inputs:
+            if type(layer_input) is not torch.Tensor:
+                modifyed_inputs.append(layer_input)
+            elif hasattr(mod, "weight"):
+                modifyed_inputs.append(layer_input.to(mod.weight.device))
+            elif hasattr(mod, "parameters"):
+                device = next(mod.parameters(), layer_input).device
+                modifyed_inputs.append(layer_input.to(device))
+            elif hasattr(next(mod.children(), None), "weight"):
+                modifyed_inputs.append(layer_input.to(next(mod.children()).weight.device))
+            elif first_dev is not None and layer_input.device != first_dev:
+                modifyed_inputs.append(layer_input.to(first_dev))
+            else:
+                modifyed_inputs.append(layer_input)
+            if first_dev is None:
+                first_dev = modifyed_inputs[0].device
+        for key, value in kwargs.items():
+            if type(value) is torch.Tensor:
+                kwargs[key] = value.to(first_dev)
+
+        return (tuple(modifyed_inputs), kwargs)
+
+    def move_layer_to_device_rurc(mod, dev):
+        mod.to(dev)
+        for layer in mod.named_children():
+            move_layer_to_device_rurc(layer[1], dev)
+
+    model = model.half()
+    all_hooks = []
+    all_hooks.append(model.register_forward_pre_hook(input_gpu_device_hook, with_kwargs=True))
+    pre_fix = next(iter(model.named_children()))[0]
+    for top_name, top_module in model.named_children():
+        for name, module in top_module.named_children():
+            all_hooks.append(module.register_forward_pre_hook(input_gpu_device_hook, with_kwargs=True))
+            if type(module) in [torch.nn.ModuleList]:
+                num_layers_on_each_gpu = math.floor(len(module) / len(gpulist))
+                for idx, attn_layer in enumerate(module):
+                    all_hooks.append(attn_layer.register_forward_pre_hook(input_gpu_device_hook, with_kwargs=True))
+
+                    to_dev = gpulist[min(idx // num_layers_on_each_gpu, len(gpulist))]
+                    attn_layer.to(to_dev)
+                    move_layer_to_device_rurc(attn_layer, to_dev)
+                    print(f"move {pre_fix}.{name}.{idx} to {to_dev}")
+            else:
+                module.to(gpulist[0])
+                print(f"move {pre_fix}.{name} to {gpulist[0]}")
+        if len(list(top_module.named_children())) == 0:
+            top_module.to(gpulist[0])
+            print(f"move {top_name} to {gpulist[0]}")
+
+    with torch.no_grad():
+        model(sample_inputs[0], attention_mask=sample_inputs[1])
+    return model
+
+
+def retrieve_onnx_inputs(model: nn.Module, sample_inputs: tuple, with_past: bool):
+    """
+    auto retrieve onnx inputs from torch model as we can't enumlate all possibilities
+    for all models
+    """
+    user_inputs = []
+
+    def hook_for_inputs(_, inputs, kwargs):
+        user_inputs.append((inputs, kwargs))
+        return user_inputs[0]
+
+    hook_handle = model.register_forward_pre_hook(hook_for_inputs, with_kwargs=True)
+
+    forward_params = inspect.signature(model.forward).parameters
+    input_keys = list(forward_params.keys())
+    default_values = [forward_params.get(key).default for key in input_keys]
+    out = model(sample_inputs[0], attention_mask=sample_inputs[1])
+    hook_handle.remove()
+    user_inputs = user_inputs[0]
+    onnx_inputs = default_values
+    for idx, _val in enumerate(user_inputs[0]):
+        onnx_inputs[idx] = user_inputs[0][idx]
+    for key, value in user_inputs[1].items():
+        idx = input_keys.index(key)
+        onnx_inputs[idx] = value
+    for idx, (key, value) in enumerate(zip(input_keys, onnx_inputs, strict=False)):
+        if type(value) is torch.Tensor:
+            value.to(model.device)
+        if "use_cache" in key:
+            onnx_inputs[idx] = with_past
+            out = model(sample_inputs[0], attention_mask=sample_inputs[1], use_cache=with_past) if with_past else out
+
+    return input_keys, onnx_inputs, out.past_key_values
+
+
+def move_to_appropriate_device(model: nn.Module, sample_inputs_tp: tuple) -> nn.Module:
+    """
+    According to the model size, we will upload it to
+    CPU if has no GPU or enough GPU memory,
+    Single GPU if has only one GPU in local or model size is enough to fit one GPU
+    Multiple GPU if there is more than one gpu in local and model is too large
+    """
+    total_mem_per_cpu = torch.cuda.get_device_properties(0).total_memory / 1024 / 1024
+
+    print(f"Model_Size = {get_model_parameter_size(model) / 1024} GB")
+    print(f"total_mem_per_cpu = {total_mem_per_cpu / 1024} GB")
+    if get_model_parameter_size(model) > total_mem_per_cpu * 0.45:
+        device_collection = [torch.device(i) for i in range(torch.cuda.device_count())]
+        if len(device_collection) > 1:
+            print(
+                f"{len(device_collection)} GPUs are used to export onnx, \
+                   Please set CUDA_VISIBLE_DEVICES to use specific GPU group"
+            )
+            model = auto_pipeline_parallel(model, device_collection, sample_inputs_tp)
+        else:
+            print("!!!! convert model to float and export onnx using CPU")
+            model = model.cpu().float()
+    else:
+        print("Export model on a single GPU")
+        model = model.cuda().half()
+    return model
+
+
+def adapt_inputs_to_device(sample_inputs: tuple, device: torch.device) -> tuple:
+    """move inputs to device"""
+    sample_inputs_ = []
+    for sample_int in sample_inputs:
+        if isinstance(sample_int, torch.Tensor):
+            sample_inputs_.append(sample_int.to(device))
+        else:
+            sample_inputs_.append(sample_int)
+    return tuple(sample_inputs_)
+
+
+def fetch_onnx_inputs_outputs_name(
+    model: nn.Module,
+    onnx_inputs: list,
+    torch_input_names: tuple,
+    past_key_values: tuple,
+    with_past: bool,
+    input_with_past: bool,
+):
+    """fetch onnx inputs and outputs name"""
+    num_of_past_key = 0
+    kv_cache_axis = {0: "batch_size"}
+    # try get num_of_past_key and shape of past_key_value
+    if past_key_values is not None:
+        num_of_past_key = len(past_key_values)
+        seq_index = (torch.tensor(past_key_values[0][0].shape) == onnx_inputs[0].shape[-1]).nonzero().view(-1)
+        assert seq_index.numel() == 1
+        kv_cache_axis = {0: "batch_size", seq_index.item(): "seq_len"}
+
+    if not num_of_past_key:
+        num_of_past_key = model.config.num_hidden_layers
+
+    # filter out constant inputs
+    onnx_inp_names = tuple(
+        [torch_input_names[i] for i in range(len(torch_input_names)) if isinstance(onnx_inputs[i], torch.Tensor)]
+    )
+    assert "input_ids" in onnx_inp_names and "attention_mask" in onnx_inp_names, (
+        "input_ids and attention_mask must be existed in inputs"
+    )
+    onnx_out_names = ("logits",)
+    onnx_dynamic_axes = {
+        "input_ids": {0: "batch_size", 1: "seq_len"},
+        "attention_mask": {0: "batch_size", 1: "seq_len"},
+    }
+    # add dyanmic dimensions for the unkonw inputs
+    for idx, name in enumerate(onnx_inp_names):
+        if name not in onnx_dynamic_axes:
+            unknown_dims = {i: f"{idx}__unknown_dims__{i}" for i in range(onnx_inputs[idx].dim())}
+            onnx_dynamic_axes[name] = unknown_dims
+    if input_with_past:
+        for i in range(num_of_past_key):
+            onnx_inp_names += (f"past_key_values.{i}.key",)
+            onnx_inp_names += (f"past_key_values.{i}.value",)
+
+            onnx_dynamic_axes[onnx_inp_names[-1]] = kv_cache_axis
+            onnx_dynamic_axes[onnx_inp_names[-2]] = kv_cache_axis
+
+    if with_past or input_with_past:
+        for i in range(num_of_past_key):
+            onnx_out_names += (f"present.{i}.key",)
+            onnx_out_names += (f"present.{i}.value",)
+
+    for idx, name in enumerate(torch_input_names):
+        if input_with_past:
+            if name == "past_key_values":
+                onnx_inputs[idx] = past_key_values
+            elif name == "attention_mask":
+                attn_mask = onnx_inputs[idx]
+                onnx_inputs[idx] = torch.cat(
+                    (attn_mask, torch.ones((attn_mask.shape[0], 1), device=attn_mask.device, dtype=attn_mask.dtype)),
+                    dim=1,
+                )
+            elif name == "input_ids":
+                input_ids = onnx_inputs[idx]
+                onnx_inputs[idx] = input_ids[:, -1:]
+
+    return onnx_inp_names, onnx_out_names, onnx_dynamic_axes
+
+
+def do_export_internal(model: nn.Module, onnx_io_tuple: tuple, onnx_inputs: tuple, onnx_path: Path, opset: int):
+    """do export with torch.onnx.export"""
+    onnx_model_name = onnx_path.name
+    onnx_inp_names, onnx_out_names, onnx_dynamic_axes = onnx_io_tuple
+    # two step to export onnx
+    # 1. export onnx with lots of pieces of weights
+    # 2. save all weights to external data
+    with tempfile.TemporaryDirectory() as tmpdirname:
+        tmp_onnx = os.path.join(tmpdirname, "tmp.onnx")
+
+        torch.onnx.export(
+            model=model,
+            args=tuple(onnx_inputs),
+            f=tmp_onnx,
+            verbose=False,
+            opset_version=opset,
+            input_names=onnx_inp_names,
+            output_names=onnx_out_names,
+            dynamic_axes=onnx_dynamic_axes,
+            dynamo=False,
+        )
+
+        onnx_path.unlink(missing_ok=True)
+        (onnx_path.parent / f"{onnx_model_name}_ext.data").unlink(missing_ok=True)
+
+        onnx_model = onnx.load(str(tmp_onnx))
+        onnx.save_model(
+            onnx_model,
+            str(onnx_path),
+            save_as_external_data=(len(os.listdir(tmpdirname)) > 1),
+            all_tensors_to_one_file=True,
+            location=f"{onnx_model_name}_ext.data",
+            size_threshold=1024,
+            convert_attribute=False,
+        )
+
+
+@torch.no_grad()
+def export_onnx(hf_model: str, cache_dir: str | None, onnx_path_str: str, with_past: bool, opset: int):
+    """
+    do export
+    model: torch model
+    onnx_path: where the onnx model saved to
+    sample_inputs_tp: inputs for torch model
+    """
+    model, sample_inputs_tp = initialize_model_and_sample_inputs(hf_model, cache_dir)
+
+    model = move_to_appropriate_device(model, sample_inputs_tp)
+
+    sample_inputs = adapt_inputs_to_device(sample_inputs_tp, next(model.parameters()).device)
+
+    # input_keys would be usesful if the model has some special inputs
+    input_keys, onnx_inputs, past_key_value = retrieve_onnx_inputs(model, sample_inputs, with_past)
+
+    onnx_io_tuple = fetch_onnx_inputs_outputs_name(model, onnx_inputs, input_keys, past_key_value, with_past, False)
+
+    onnx_model_name = "model.onnx"
+    onnx_path: Path = Path(onnx_path_str).absolute()
+    if onnx_path.suffix != ".onnx":
+        onnx_path = onnx_path / onnx_model_name
+
+    do_export_internal(model, onnx_io_tuple, onnx_inputs, onnx_path, opset)
+    if not with_past:
+        return
+
+    onnx_io_tuple = fetch_onnx_inputs_outputs_name(model, onnx_inputs, input_keys, past_key_value, with_past, True)
+
+    onnx_model_name = "model_with_past.onnx"
+    onnx_path = onnx_path.parent / onnx_model_name
+
+    do_export_internal(model, onnx_io_tuple, onnx_inputs, onnx_path, opset)
+
+
+def parse_arguments():
+    """arguments parsing."""
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model",
+        required=True,
+        type=str,
+        default=["meta-llama/Llama-2-70b-hf"],
+        help="Pre-trained models in huggingface model hub",
+    )
+    parser.add_argument(
+        "-s",
+        "--saved_path",
+        required=False,
+        type=str,
+        default="./onnx_models/",
+        help="where the onnx model will be saved",
+    )
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default=None,
+        help=("cache directly of huggingface, by setting this to avoid useless downloading if you have one"),
+    )
+    parser.add_argument(
+        "--with_past",
+        action="store_true",
+        default=False,
+        help=("The tool will export onnx without past-key-value by default"),
+    )
+    parser.add_argument(
+        "--opset",
+        required=False,
+        type=int,
+        default=17,
+        help=(
+            "the opset to save onnx model, \
+              try to increase it if this opset doens't have new features you want"
+        ),
+    )
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+
+    export_onnx(args.model, args.cache_dir, args.saved_path, args.with_past, args.opset)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/machine_info.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/machine_info.py
new file mode 100644
index 0000000000000000000000000000000000000000..7fc77108769d65cc3f21ea94c36db953de621875
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/machine_info.py
@@ -0,0 +1,230 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+# It is used to dump machine information for Notebooks
+
+import argparse
+import importlib.metadata
+import json
+import logging
+import platform
+from os import environ
+
+import cpuinfo
+import psutil
+from py3nvml.py3nvml import (
+    NVMLError,
+    nvmlDeviceGetCount,
+    nvmlDeviceGetHandleByIndex,
+    nvmlDeviceGetMemoryInfo,
+    nvmlDeviceGetName,
+    nvmlInit,
+    nvmlShutdown,
+    nvmlSystemGetDriverVersion,
+)
+
+
+class MachineInfo:
+    """Class encapsulating Machine Info logic."""
+
+    def __init__(self, silent=False, logger=None):
+        self.silent = silent
+
+        if logger is None:
+            logging.basicConfig(
+                format="%(asctime)s - %(name)s - %(levelname)s: %(message)s",
+                level=logging.INFO,
+            )
+            self.logger = logging.getLogger(__name__)
+        else:
+            self.logger = logger
+
+        self.machine_info = None
+        try:
+            self.machine_info = self.get_machine_info()
+        except Exception:
+            self.logger.exception("Exception in getting machine info.")
+            self.machine_info = None
+
+    def get_machine_info(self):
+        """Get machine info in metric format"""
+        gpu_info = self.get_gpu_info_by_nvml()
+        cpu_info = cpuinfo.get_cpu_info()
+
+        machine_info = {
+            "gpu": gpu_info,
+            "cpu": self.get_cpu_info(),
+            "memory": self.get_memory_info(),
+            "os": platform.platform(),
+            "python": self._try_get(cpu_info, ["python_version"]),
+            "packages": self.get_related_packages(),
+            "onnxruntime": self.get_onnxruntime_info(),
+            "pytorch": self.get_pytorch_info(),
+            "tensorflow": self.get_tensorflow_info(),
+        }
+        return machine_info
+
+    def get_memory_info(self) -> dict:
+        """Get memory info"""
+        mem = psutil.virtual_memory()
+        return {"total": mem.total, "available": mem.available}
+
+    def _try_get(self, cpu_info: dict, names: list) -> str:
+        for name in names:
+            if name in cpu_info:
+                value = cpu_info[name]
+                if isinstance(value, (list, tuple)):
+                    return ",".join([str(i) for i in value])
+                return value
+        return ""
+
+    def get_cpu_info(self) -> dict:
+        """Get CPU info"""
+        cpu_info = cpuinfo.get_cpu_info()
+
+        return {
+            "brand": self._try_get(cpu_info, ["brand", "brand_raw"]),
+            "cores": psutil.cpu_count(logical=False),
+            "logical_cores": psutil.cpu_count(logical=True),
+            "hz": self._try_get(cpu_info, ["hz_actual"]),
+            "l2_cache": self._try_get(cpu_info, ["l2_cache_size"]),
+            "flags": self._try_get(cpu_info, ["flags"]),
+            "processor": platform.uname().processor,
+        }
+
+    def get_gpu_info_by_nvml(self) -> dict:
+        """Get GPU info using nvml"""
+        gpu_info_list = []
+        driver_version = None
+        try:
+            nvmlInit()
+            driver_version = nvmlSystemGetDriverVersion()
+            deviceCount = nvmlDeviceGetCount()  # noqa: N806
+            for i in range(deviceCount):
+                handle = nvmlDeviceGetHandleByIndex(i)
+                info = nvmlDeviceGetMemoryInfo(handle)
+                gpu_info = {}
+                gpu_info["memory_total"] = info.total
+                gpu_info["memory_available"] = info.free
+                gpu_info["name"] = nvmlDeviceGetName(handle)
+                gpu_info_list.append(gpu_info)
+            nvmlShutdown()
+        except NVMLError as error:
+            if not self.silent:
+                self.logger.error("Error fetching GPU information using nvml: %s", error)
+            return None
+
+        result = {"driver_version": driver_version, "devices": gpu_info_list}
+
+        if "CUDA_VISIBLE_DEVICES" in environ:
+            result["cuda_visible"] = environ["CUDA_VISIBLE_DEVICES"]
+        return result
+
+    def get_related_packages(self) -> list[str]:
+        related_packages = {
+            "onnxruntime-gpu",
+            "onnxruntime",
+            "onnx",
+            "transformers",
+            "protobuf",
+            "sympy",
+            "torch",
+            "tensorflow",
+            "flatbuffers",
+            "numpy",
+            "onnxconverter-common",
+        }
+        related_packages_list = {}
+        for dist in importlib.metadata.distributions():
+            if dist.metadata["Name"].lower() in related_packages:
+                related_packages_list[dist.metadata["Name"].lower()] = dist.version
+
+        return related_packages_list
+
+    def get_onnxruntime_info(self) -> dict:
+        try:
+            import onnxruntime  # noqa: PLC0415
+
+            return {
+                "version": onnxruntime.__version__,
+                "support_gpu": "CUDAExecutionProvider" in onnxruntime.get_available_providers(),
+            }
+        except ImportError as error:
+            if not self.silent:
+                self.logger.exception(error)
+            return None
+        except Exception as exception:
+            if not self.silent:
+                self.logger.exception(exception, False)
+            return None
+
+    def get_pytorch_info(self) -> dict:
+        try:
+            import torch  # noqa: PLC0415
+
+            return {
+                "version": torch.__version__,
+                "support_gpu": torch.cuda.is_available(),
+                "cuda": torch.version.cuda,
+            }
+        except ImportError as error:
+            if not self.silent:
+                self.logger.exception(error)
+            return None
+        except Exception as exception:
+            if not self.silent:
+                self.logger.exception(exception, False)
+            return None
+
+    def get_tensorflow_info(self) -> dict:
+        try:
+            import tensorflow as tf  # noqa: PLC0415
+
+            return {
+                "version": tf.version.VERSION,
+                "git_version": tf.version.GIT_VERSION,
+                "support_gpu": tf.test.is_built_with_cuda(),
+            }
+        except ImportError as error:
+            if not self.silent:
+                self.logger.exception(error)
+            return None
+        except ModuleNotFoundError as error:
+            if not self.silent:
+                self.logger.exception(error)
+            return None
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--silent",
+        required=False,
+        action="store_true",
+        help="Do not print error message",
+    )
+    parser.set_defaults(silent=False)
+
+    args = parser.parse_args()
+    return args
+
+
+def get_machine_info(silent=True) -> str:
+    machine = MachineInfo(silent)
+    return json.dumps(machine.machine_info, indent=2)
+
+
+def get_device_info(silent=True) -> str:
+    machine = MachineInfo(silent)
+    info = machine.machine_info
+    if info:
+        info = {key: value for key, value in info.items() if key in ["gpu", "cpu", "memory"]}
+    return json.dumps(info, indent=2)
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    print(get_machine_info(args.silent))
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/metrics.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/metrics.py
new file mode 100644
index 0000000000000000000000000000000000000000..11f419059f73843455f9903addd9ddb2a77a2426
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/metrics.py
@@ -0,0 +1,163 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import datetime
+import json
+
+import pandas as pd
+
+
+class BaseObject:
+    def __init__(self):
+        self.customized = {}
+
+    def to_dict(self):
+        default_values = self.__dict__.copy()
+        default_values.pop("customized", None)
+        default_values.update(self.customized)
+
+        for k, v in default_values.items():
+            if isinstance(v, BaseObject):
+                default_values[k] = v.to_dict()
+
+        return {k: v for k, v in default_values.items() if v}
+
+
+class ModelInfo(BaseObject):
+    def __init__(
+        self,
+        full_name: str | None = None,
+        is_huggingface: bool | None = False,
+        is_text_generation: bool | None = False,
+        short_name: str | None = None,
+    ):
+        super().__init__()
+        self.full_name = full_name
+        self.is_huggingface = is_huggingface
+        self.is_text_generation = is_text_generation
+        self.short_name = short_name
+        self.input_shape = []
+
+
+class BackendOptions(BaseObject):
+    def __init__(
+        self,
+        enable_profiling: bool | None = False,
+        execution_provider: str | None = None,
+        use_io_binding: bool | None = False,
+    ):
+        super().__init__()
+        self.enable_profiling = enable_profiling
+        self.execution_provider = execution_provider
+        self.use_io_binding = use_io_binding
+
+
+class Config(BaseObject):
+    def __init__(
+        self,
+        backend: str | None = "onnxruntime",
+        batch_size: int | None = 1,
+        seq_length: int | None = 0,
+        precision: str | None = "fp32",
+        warmup_runs: int | None = 1,
+        measured_runs: int | None = 10,
+    ):
+        super().__init__()
+        self.backend = backend
+        self.batch_size = batch_size
+        self.seq_length = seq_length
+        self.precision = precision
+        self.warmup_runs = warmup_runs
+        self.measured_runs = measured_runs
+        self.model_info = ModelInfo()
+        self.backend_options = BackendOptions()
+
+
+class Metadata(BaseObject):
+    def __init__(
+        self,
+        device: str | None = None,
+        package_name: str | None = None,
+        package_version: str | None = None,
+        platform: str | None = None,
+        python_version: str | None = None,
+    ):
+        super().__init__()
+        self.device = device
+        self.package_name = package_name
+        self.package_version = package_version
+        self.platform = platform
+        self.python_version = python_version
+
+
+class Metrics(BaseObject):
+    def __init__(
+        self,
+        latency_ms_mean: float | None = 0.0,
+        throughput_qps: float | None = 0.0,
+        max_memory_usage_GB: float | None = 0.0,
+    ):
+        super().__init__()
+        self.latency_ms_mean = latency_ms_mean
+        self.throughput_qps = throughput_qps
+        self.max_memory_usage_GB = max_memory_usage_GB
+
+
+class BenchmarkRecord:
+    def __init__(
+        self,
+        model_name: str,
+        precision: str,
+        backend: str,
+        device: str,
+        package_name: str,
+        package_version: str,
+        batch_size: int | None = 1,
+        warmup_runs: int | None = 1,
+        measured_runs: int | None = 10,
+        trigger_date: str | None = None,
+    ):
+        self.config = Config()
+        self.metrics = Metrics()
+        self.metadata = Metadata()
+        self.trigger_date = trigger_date or datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+        self.config.model_info.full_name = model_name
+        self.config.precision = precision
+        self.config.backend = backend
+        self.config.batch_size = batch_size
+        self.config.warmup_runs = warmup_runs
+        self.config.measured_runs = measured_runs
+        self.metadata.device = device
+        self.metadata.package_name = package_name
+        self.metadata.package_version = package_version
+
+    def to_dict(self) -> dict:
+        return {
+            "config": self.config.to_dict(),
+            "metadata": self.metadata.to_dict(),
+            "metrics": self.metrics.to_dict(),
+            "trigger_date": self.trigger_date,
+        }
+
+    def to_json(self) -> str:
+        return json.dumps(self.to_dict(), default=str)
+
+    @classmethod
+    def save_as_csv(cls, file_name: str, records: list) -> None:
+        if records is None or len(records) == 0:
+            return
+        rds = [record.to_dict() for record in records]
+        df = pd.json_normalize(rds)
+        df.to_csv(file_name, index=False)
+
+    @classmethod
+    def save_as_json(cls, file_name: str, records: list) -> None:
+        if records is None or len(records) == 0:
+            return
+        rds = [record.to_dict() for record in records]
+        with open(file_name, "w") as f:
+            json.dump(rds, f, indent=4, default=str)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ef71ce9e355e17ea1c2ca9fb648951d917734b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__pycache__/export.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/__pycache__/export.cpython-313.pyc
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index 0000000000000000000000000000000000000000..174ff939a79d01726f6474f72746d1fbe38d01dd
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/export.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/export.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee05793cab0ed2984a3a3c742e80c3961dd0de14
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bart/export.py
@@ -0,0 +1,98 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import logging
+import os
+import sys
+
+from utils import (
+    chain_enc_dec_with_beamsearch,
+    export_summarization_edinit,
+    export_summarization_enc_dec_past,
+    onnx_inference,
+)
+
+# GLOBAL ENVS
+logging.basicConfig(
+    format="%(asctime)s | %(levelname)s | %(name)s |  [%(filename)s:%(lineno)d] %(message)s",
+    datefmt="%Y-%m-%d %H:%M:%S",
+    level=os.environ.get("LOGLEVEL", "INFO").upper(),
+    stream=sys.stdout,
+)
+logger = logging.getLogger("generate")
+
+
+def print_args(args):
+    for arg in vars(args):
+        logger.info(f"{arg}: {getattr(args, arg)}")
+
+
+def user_command():
+    parent_parser = argparse.ArgumentParser(add_help=False)
+    parent_parser.add_argument("--max_length", type=int, default=20, help="default to 20")
+    parent_parser.add_argument("--min_length", type=int, default=0, help="default to 0")
+    parent_parser.add_argument("-o", "--output", type=str, default="onnx_models", help="default name is onnx_models.")
+    parent_parser.add_argument("-i", "--input_text", type=str, default=None, help="input text")
+    parent_parser.add_argument("-s", "--spm_path", type=str, default=None, help="tokenizer model from sentencepice")
+    parent_parser.add_argument("-v", "--vocab_path", type=str, help="vocab dictionary")
+    parent_parser.add_argument("-b", "--num_beams", type=int, default=5, help="default to 5")
+    parent_parser.add_argument("--repetition_penalty", type=float, default=1.0, help="default to 1.0")
+    parent_parser.add_argument("--no_repeat_ngram_size", type=int, default=3, help="default to 3")
+    parent_parser.add_argument("--early_stopping", type=bool, default=False, help="default to False")
+    parent_parser.add_argument("--opset_version", type=int, default=14, help="minimum is 14")
+
+    parent_parser.add_argument("--no_encoder", action="store_true")
+    parent_parser.add_argument("--no_decoder", action="store_true")
+    parent_parser.add_argument("--no_chain", action="store_true")
+    parent_parser.add_argument("--no_inference", action="store_true")
+
+    required_args = parent_parser.add_argument_group("required input arguments")
+    required_args.add_argument(
+        "-m",
+        "--model_dir",
+        type=str,
+        required=True,
+        help="The directory contains input huggingface model. \
+                               An official model like facebook/bart-base is also acceptable.",
+    )
+
+    print_args(parent_parser.parse_args())
+    return parent_parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = user_command()
+    if args.opset_version < 14:
+        raise ValueError(f"The minimum supported opset version is 14! The given one was {args.opset_version}.")
+
+    isExist = os.path.exists(args.output)  # noqa: N816
+    if not isExist:
+        os.makedirs(args.output)
+
+    # beam search op only supports CPU for now
+    args.device = "cpu"
+    logger.info("ENV: CPU ...")
+
+    if not args.input_text:
+        args.input_text = (
+            "PG&E stated it scheduled the blackouts in response to forecasts for high winds "
+            "amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were "
+            "scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow."
+        )
+
+    if not args.no_encoder:
+        logger.info("========== EXPORTING ENCODER ==========")
+        export_summarization_edinit.export_encoder(args)
+    if not args.no_decoder:
+        logger.info("========== EXPORTING DECODER ==========")
+        export_summarization_enc_dec_past.export_decoder(args)
+    if not args.no_chain:
+        logger.info("========== CONVERTING MODELS ==========")
+        chain_enc_dec_with_beamsearch.convert_model(args)
+    if not args.no_inference:
+        logger.info("========== INFERENCING WITH ONNX MODEL ==========")
+        onnx_inference.run_inference(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ef71ce9e355e17ea1c2ca9fb648951d917734b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__pycache__/eval_squad.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/__pycache__/eval_squad.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/eval_squad.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/eval_squad.py
new file mode 100644
index 0000000000000000000000000000000000000000..1a3e1a311867788fbd3066107e02c90a77a46785
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/bert/eval_squad.py
@@ -0,0 +1,329 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+#
+# This script evaluates accuracy of ONNX models for question-answering task on SQuAD data set.
+# Example to evaluate raw and optimized model for CUDA in Linux:
+#   pip3 install datasets evaluate optimum transformers onnxruntime-gpu
+#
+#   python3 eval_squad.py -m bert-large-uncased-whole-word-masking-finetuned-squad -s 384 -b 1 --use_io_binding
+#
+#   python3 -m onnxruntime.transformers.optimizer \
+#           --input ./bert-large-uncased-whole-word-masking-finetuned-squad/model.onnx \
+#           --output ./bert-large-uncased-whole-word-masking-finetuned-squad/optimized_model.onnx
+#
+#   python3 eval_squad.py -m bert-large-uncased-whole-word-masking-finetuned-squad -s 384 -b 1 --use_io_binding \
+#           --onnx ./bert-large-uncased-whole-word-masking-finetuned-squad/optimized_model.onnx
+#
+#   Snippet of example output in A100:
+#   {'exact': 86.65089877010406, 'f1': 92.99433524952254, 'total': 10570, 'HasAns_exact': 86.65089877010406
+#    'total_time_in_seconds': 81.69239814393222, 'samples_per_second': 129.387804008115,
+#    'latency_in_seconds': 0.007728703703304846, 'provider': 'CUDAExecutionProvider',
+#    'pretrained_model_name': 'bert-large-uncased-whole-word-masking-finetuned-squad',
+#    'batch_size': 1, 'sequence_length': 384, 'use_io_binding': True}
+import argparse
+import csv
+import os
+import time
+
+try:
+    from importlib.metadata import PackageNotFoundError, version
+except ImportError:
+    from importlib_metadata import PackageNotFoundError, version
+
+from pathlib import Path
+from typing import Any
+
+from datasets import load_dataset
+from evaluate import evaluator
+from optimum.onnxruntime import ORTModelForQuestionAnswering
+from optimum.version import __version__ as optimum_version
+from packaging import version as version_check
+from transformers import AutoTokenizer, pipeline
+
+if version_check.parse(optimum_version) < version_check.parse("1.13.1"):
+    raise ImportError(f"Please install optimum>=1.13.1. Current version: {optimum_version}.")
+
+PRETRAINED_SQUAD_MODELS = [
+    "bert-large-uncased-whole-word-masking-finetuned-squad",
+    "deepset/roberta-base-squad2",
+    "distilbert-base-cased-distilled-squad",
+]
+
+
+def get_package_version(package_name: str):
+    try:
+        return version(package_name)
+    except PackageNotFoundError:
+        return None
+
+
+def load_onnx_model(
+    model_id: str, onnx_path: str | None = None, provider="CUDAExecutionProvider", use_io_binding: bool = False
+):
+    """Load onnx model given pretrained model name and optional ONNX model path. If onnx_path is None,
+    the default onnx model from optimum will be used.
+
+    Args:
+        model_id (str): pretrained model name or checkpoint path
+        onnx_path (Optional[str], optional): path of onnx model to evaluate. Defaults to None.
+
+    Returns:
+        model: ORTModel for the onnx model
+        onnx_path: the path of onnx model
+    """
+
+    if onnx_path is None:
+        # Export onnx to a sub-directory named by the model id
+        model = ORTModelForQuestionAnswering.from_pretrained(
+            model_id, export=True, provider=provider, use_io_binding=use_io_binding
+        )
+        save_onnx_dir = os.path.join(".", model_id)
+        model.save_pretrained(save_onnx_dir)
+        onnx_path = os.path.join(save_onnx_dir, "model.onnx")
+        print("Model is exported to onnx file:", onnx_path)
+    else:
+        model = ORTModelForQuestionAnswering.from_pretrained(
+            os.path.dirname(onnx_path),
+            file_name=Path(onnx_path).name,
+            provider=provider,
+            use_io_binding=use_io_binding,
+            # provider_options={"enable_skip_layer_norm_strict_mode": True},
+        )
+
+    return model, onnx_path
+
+
+def output_details(results: list[dict[str, Any]], csv_filename: str):
+    """Output a CSV file with detail of each test results.
+
+    Args:
+        results (List[Dict[str, Any]]): list of JSON results.
+        csv_filename (str): path of output CSV file
+    """
+    with open(csv_filename, mode="a", newline="", encoding="ascii") as csv_file:
+        column_names = [
+            "pretrained_model_name",
+            "onnx_path",
+            "provider",
+            "disable_fused_attention",
+            "batch_size",
+            "sequence_length",
+            "use_io_binding",
+            "exact",
+            "f1",
+            "total",
+            "HasAns_exact",
+            "HasAns_f1",
+            "HasAns_total",
+            "best_exact",
+            "best_exact_thresh",
+            "best_f1",
+            "best_f1_thresh",
+            "total_time_in_seconds",
+            "samples_per_second",
+            "latency_in_seconds",
+        ]
+
+        csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+        csv_writer.writeheader()
+        for result in results:
+            csv_writer.writerow(result)
+
+        csv_file.flush()
+
+    print(f"Detail results are saved to csv file: {csv_filename}")
+
+
+def output_summary(results: list[dict[str, Any]], csv_filename: str, metric_name: str):
+    """Output a CSV file with summary of a metric on combinations of batch_size and sequence_length.
+
+    Args:
+        results (List[Dict[str, Any]]): list of JSON results.
+        csv_filename (str): path of output CSV file
+        metric_name (str): the metric to summarize
+    """
+    with open(csv_filename, mode="a", newline="", encoding="ascii") as csv_file:
+        header_names = [
+            "pretrained_model_name",
+            "onnx_path",
+            "provider",
+            "disable_fused_attention",
+            "use_io_binding",
+        ]
+
+        model_list = list({result["onnx_path"] for result in results})
+        model_list.sort()
+
+        batch_sizes = list({result["batch_size"] for result in results})
+        batch_sizes.sort()
+
+        sequence_lengths = list({result["sequence_length"] for result in results})
+        sequence_lengths.sort()
+
+        key_names = []
+        for sequence_length in sequence_lengths:
+            for batch_size in batch_sizes:
+                key_names.append(f"b{batch_size}_s{sequence_length}")
+
+        csv_writer = csv.DictWriter(csv_file, fieldnames=header_names + key_names)
+        csv_writer.writeheader()
+
+        for model in model_list:
+            row = {}
+
+            # Metric value for given pair of batch_size and sequence_length.
+            # Assume that (onnx_path, batch_size and sequence_length) are unique so keep first occurrence only.
+            values = {}
+            values.update(dict.fromkeys(key_names, ""))
+
+            for result in results:
+                if result["onnx_path"] == model and result[metric_name]:
+                    headers = {k: v for k, v in result.items() if k in header_names}
+                    if not row:
+                        row.update(headers)
+
+                    batch_size = result["batch_size"]
+                    sequence_length = result["sequence_length"]
+                    key = f"b{batch_size}_s{sequence_length}"
+
+                    if key in key_names:
+                        values[key] = result[metric_name]
+
+            if row:
+                for key in key_names:
+                    row[key] = values.get(key, "")
+                csv_writer.writerow(row)
+
+        csv_file.flush()
+
+    print(f"Summary results for {metric_name} are saved to csv file: {csv_filename}")
+
+
+def main():
+    args = parse_arguments()
+    print(args)
+
+    for name in ["onnxruntime-gpu", "onnxruntime", "onnx", "torch", "transformers", "optimum", "datasets", "evaluate"]:
+        package_version = get_package_version(name)
+        if package_version:
+            print(f"{name} version", package_version)
+
+    pretrained_model_name = args.model_name
+    if args.onnx and not os.path.exists(args.onnx):
+        raise RuntimeError(f"Onnx model path does not exist: {args.onnx}")
+
+    disable_fused_attention = os.environ.get("ORT_DISABLE_FUSED_ATTENTION", "0") == "1"
+
+    all_results = []
+    tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name)
+    for sequence_length in args.sequence_lengths:
+        tokenizer.model_max_length = sequence_length
+        tokenizer.doc_stride = min(sequence_length // 2, 128)
+        if args.onnx is None:
+            print("Exporting onnx model. It might take a few minutes...")
+        start_time = time.time()
+        ort_model, onnx_path = load_onnx_model(pretrained_model_name, args.onnx, args.provider, args.use_io_binding)
+        latency = time.time() - start_time
+        print(f"Onnx model exported or loaded in {latency:.1f} seconds")
+
+        print(ort_model.config)
+        if sequence_length > ort_model.config.max_position_embeddings:
+            raise RuntimeError("sequence length should not be larger than {ort_model.config.max_position_embeddings}")
+
+        qa_pipeline = pipeline(
+            "question-answering", model=ort_model, tokenizer=tokenizer, question_first=True, batch_size=args.batch_size
+        )
+
+        task_evaluator = evaluator("question-answering")
+        print("Loading dataset...")
+        start_time = time.time()
+        squad_dataset = load_dataset("squad", split=f"validation[:{args.total}]" if args.total > 0 else "validation")
+        latency = time.time() - start_time
+        print(f"Dataset loaded in {latency:.1f} seconds")
+
+        print("Evaluating squad_v2 with ORT. It might take a few minutes...")
+        start_time = time.time()
+        result = task_evaluator.compute(
+            model_or_pipeline=qa_pipeline,
+            data=squad_dataset,
+            metric="squad_v2",
+            squad_v2_format=True,
+        )
+        latency = time.time() - start_time
+        print(f"Evaluation done in {latency:.1f} seconds")
+
+        result["provider"] = args.provider
+        result["disable_fused_attention"] = disable_fused_attention
+        result["pretrained_model_name"] = pretrained_model_name
+        result["onnx_path"] = onnx_path
+        result["batch_size"] = args.batch_size
+        result["sequence_length"] = sequence_length
+        result["use_io_binding"] = args.use_io_binding
+        print(result)
+
+        all_results.append(result)
+
+    output_details(all_results, "detail.csv")
+
+    for metric_name in ["f1", "exact", "samples_per_second"]:
+        output_summary(all_results, f"{metric_name}.csv", metric_name)
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name",
+        required=False,
+        type=str,
+        default=PRETRAINED_SQUAD_MODELS[0],
+        help=f"Checkpoint directory or pre-trained model names in the list: {PRETRAINED_SQUAD_MODELS}",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--sequence_lengths",
+        nargs="+",
+        type=int,
+        default=[384],
+        help="Sequence lengths for onnx model inputs. It could have multiple values.",
+    )
+
+    parser.add_argument(
+        "-b",
+        "--batch_size",
+        type=int,
+        default=1,
+        help="batch size for inference.",
+    )
+
+    parser.add_argument("-t", "--total", type=int, default=0, help="Total samples to test. 0 means all samples.")
+
+    parser.add_argument(
+        "--onnx",
+        required=False,
+        type=str,
+        default=None,
+        help="Optional onnx model path. If not specified, optimum will be used to export onnx model for testing.",
+    )
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        default="CUDAExecutionProvider",
+        help="Select which Execution Provider to use for runs. Default is CUDAExecutionProvider.",
+    )
+
+    parser.add_argument("--use_io_binding", required=False, action="store_true", help="Use IO Binding for GPU.")
+    parser.set_defaults(use_io_binding=False)
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/__init__.py
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/benchmark_gpt2.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/benchmark_gpt2.py
new file mode 100644
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/benchmark_gpt2.py
@@ -0,0 +1,413 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+# This script benchmarks gpt2 model with past state.
+# For gpt2 model without past state, use benchmark.py to measure performance.
+
+import argparse
+import csv
+import logging
+import os
+from datetime import datetime
+
+import psutil
+import torch
+from benchmark_helper import (
+    Precision,
+    create_onnxruntime_session,
+    get_ort_environment_variables,
+    prepare_environment,
+    setup_logger,
+)
+from gpt2_helper import DEFAULT_TOLERANCE, MODEL_CLASSES, PRETRAINED_GPT2_MODELS, Gpt2Helper
+from packaging import version
+from quantize_helper import QuantizeHelper
+from transformers import AutoConfig
+from transformers import __version__ as transformers_version
+
+logger = logging.getLogger("")
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name_or_path",
+        required=True,
+        type=str,
+        help="Model path, or pretrained model name selected in the list: " + ", ".join(PRETRAINED_GPT2_MODELS),
+    )
+
+    parser.add_argument(
+        "--model_class",
+        required=False,
+        type=str,
+        default="GPT2LMHeadModel",
+        choices=list(MODEL_CLASSES.keys()),
+        help="Model type selected in the list: " + ", ".join(MODEL_CLASSES.keys()),
+    )
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default=os.path.join(".", "cache_models"),
+        help="Directory to cache pre-trained models",
+    )
+
+    parser.add_argument(
+        "--onnx_dir",
+        required=False,
+        type=str,
+        default=os.path.join(".", "onnx_models"),
+        help="Directory to store onnx models",
+    )
+
+    parser.add_argument(
+        "--test_times",
+        required=False,
+        default=100,
+        type=int,
+        help="Number of repeat times to get average inference latency.",
+    )
+
+    parser.add_argument(
+        "-v",
+        "--validate_onnx",
+        required=False,
+        action="store_true",
+        help="Validate ONNX model",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--optimize_onnx",
+        required=False,
+        action="store_true",
+        help="Use optimizer.py to optimize onnx model",
+    )
+    parser.set_defaults(optimize_onnx=False)
+
+    parser.add_argument(
+        "--stage",
+        type=int,
+        default=0,
+        required=False,
+        choices=[0, 1, 2],
+        help="Stage in generation: 1 (initial decoder), 2 (decoder), 0 (both). "
+        "1 - decode the first token when past_sequence_length is zero; "
+        "2 - decode the remaining tokens when past_sequence_length is not zero; "
+        "0 - one onnx model for both stages 1 and 2. "
+        "Note that we will optimize 1 and 2 differently for best performance.",
+    )
+
+    parser.add_argument("--use_gpu", required=False, action="store_true", help="use GPU for inference")
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        type=Precision,
+        default=Precision.FLOAT32,
+        choices=list(Precision),
+        help="Precision of model to run. fp32 for full precision, fp16 for half precision, and int8 for quantization",
+    )
+
+    parser.add_argument("--torchscript", required=False, action="store_true", help="use Torchscript")
+    parser.set_defaults(torchscript=False)
+
+    parser.add_argument("-b", "--batch_sizes", nargs="+", type=int, default=[1], help="batch size")
+
+    parser.add_argument(
+        "--sequence_lengths",
+        nargs="+",
+        type=int,
+        default=[1],
+        help="sequence lengths (excluding past)",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--past_sequence_lengths",
+        nargs="+",
+        type=int,
+        default=[8, 16, 32, 64, 128, 256],
+        help="past sequence lengths",
+    )
+
+    parser.add_argument(
+        "-r",
+        "--result_csv",
+        required=False,
+        default=None,
+        help="CSV file for saving summary results.",
+    )
+
+    parser.add_argument("--thread_num", required=False, type=int, default=-1, help="Threads to use")
+
+    parser.add_argument("--include_copy_output_latency", required=False, action="store_true")
+    parser.set_defaults(include_copy_output_latency=False)
+
+    parser.add_argument("--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument("--output_torch_latency", required=False, action="store_true")
+    parser.set_defaults(output_torch_latency=False)
+
+    parser.add_argument("--disable_io_binding", required=False, action="store_true")
+    parser.set_defaults(disable_io_binding=False)
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+def main(args):
+    if version.parse(transformers_version) < version.parse(
+        "3.1.0"
+    ):  # past_key_values name does not exist in 3.0.2 or older
+        raise RuntimeError("This tool requires transformers 3.1.0 or later.")
+
+    logger.info(f"Arguments:{args}")
+    if args.precision == Precision.FLOAT16:
+        assert args.optimize_onnx and args.use_gpu, "fp16 requires --optimize_onnx --use_gpu"
+
+    if args.precision == Precision.INT8:
+        assert not args.use_gpu, "quantization only supports CPU"
+
+    if args.stage == 1:
+        assert args.past_sequence_lengths == [0], "past_sequence_lengths shall be 0 for stage==1 (init decoder)"
+
+    torch.set_num_threads(psutil.cpu_count(logical=True) if args.thread_num <= 0 else args.thread_num)
+    print(torch.__config__.parallel_info())
+
+    cache_dir = args.cache_dir
+    output_dir = args.onnx_dir
+    prepare_environment(cache_dir, output_dir, args.use_gpu)
+
+    model_class = MODEL_CLASSES[args.model_class][0]
+    gpt2helper = Gpt2Helper
+    config = AutoConfig.from_pretrained(args.model_name_or_path, torchscript=args.torchscript, cache_dir=cache_dir)
+    model = model_class.from_pretrained(args.model_name_or_path, config=config, cache_dir=cache_dir)
+
+    # This script does not support float16 for PyTorch.
+    # if args.float16:
+    #    model.half()
+
+    device = torch.device("cuda:0" if args.use_gpu else "cpu")
+    model.to(device)
+    use_external_data_format = config.n_layer > 24  # TODO: find a way to check model size > 2GB
+    onnx_model_paths = gpt2helper.get_onnx_paths(
+        output_dir,
+        args.model_name_or_path,
+        args.model_class,
+        has_past=True,
+        new_folder=use_external_data_format,
+    )
+
+    onnx_model_path = onnx_model_paths["raw"]
+    use_padding = MODEL_CLASSES[args.model_class][2]
+    gpt2helper.export_onnx(
+        model,
+        device,
+        onnx_model_path,
+        args.verbose,
+        use_external_data_format,
+        has_position_ids=use_padding,
+        has_attention_mask=use_padding,
+    )
+
+    if args.optimize_onnx or args.precision != Precision.FLOAT32:
+        onnx_model_path = onnx_model_paths[str(args.precision) if args.precision != Precision.INT8 else "fp32"]
+        gpt2helper.optimize_onnx(
+            onnx_model_paths["raw"],
+            onnx_model_path,
+            args.precision == Precision.FLOAT16,
+            model.config.num_attention_heads,
+            model.config.hidden_size,
+            use_external_data_format,
+            auto_mixed_precision=True,
+            stage=args.stage,
+        )
+
+        if args.precision == Precision.INT8:
+            logger.info("quantizing model...")
+            QuantizeHelper.quantize_onnx_model(onnx_model_path, onnx_model_paths["int8"], use_external_data_format)
+            model = QuantizeHelper.quantize_torch_model(model)
+            logger.info("finished quantizing model")
+            onnx_model_path = onnx_model_paths["int8"]
+
+    if args.torchscript:
+        model = gpt2helper.torchscript(
+            model,
+            config,
+            device,
+            has_position_ids=use_padding,
+            has_attention_mask=use_padding,
+        )
+
+    session = create_onnxruntime_session(
+        onnx_model_path,
+        args.use_gpu,
+        enable_all_optimization=False,
+        num_threads=args.thread_num,
+        verbose=args.verbose,
+    )
+    if session is None:
+        return
+
+    # Allocate output buffers for IO Binding
+    max_output_shapes = gpt2helper.get_output_shapes(
+        max(args.batch_sizes),
+        max(args.past_sequence_lengths),
+        max(args.sequence_lengths),
+        config,
+        args.model_class,
+    )
+    output_buffers = gpt2helper.get_output_buffers(max_output_shapes, device, args.precision == Precision.FLOAT16)
+
+    csv_filename = args.result_csv or "benchmark_result_{}.csv".format(datetime.now().strftime("%Y%m%d-%H%M%S"))
+    with open(csv_filename, mode="a", newline="") as csv_file:
+        column_names = [
+            "model_name",
+            "model_class",
+            "stage",
+            "environment_variables",
+            "gpu",
+            "precision",
+            "optimizer",
+            "torchscript",
+            "batch_size",
+            "sequence_length",
+            "past_sequence_length",
+            "disable_io_binding",
+            "torch_latency",
+            "onnxruntime_latency",
+        ]
+        csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+        csv_writer.writeheader()
+
+        for batch_size in args.batch_sizes:
+            for sequence_length in args.sequence_lengths:
+                for past_sequence_length in args.past_sequence_lengths:
+                    assert batch_size > 0 and sequence_length > 0 and past_sequence_length >= 0
+                    logger.debug(
+                        "Running test for batch_size=%d sequence_length=%d past_sequence_length=%d ...",
+                        batch_size,
+                        sequence_length,
+                        past_sequence_length,
+                    )
+
+                    dummy_inputs = gpt2helper.get_dummy_inputs(
+                        batch_size,
+                        past_sequence_length,
+                        sequence_length,
+                        config.num_attention_heads,
+                        config.hidden_size,
+                        config.n_layer,
+                        config.vocab_size,
+                        device,
+                        float16=(args.precision == Precision.FLOAT16),
+                        has_position_ids=use_padding,
+                        has_attention_mask=use_padding,
+                    )
+                    output_shapes = gpt2helper.get_output_shapes(
+                        batch_size,
+                        past_sequence_length,
+                        sequence_length,
+                        config,
+                        args.model_class,
+                    )
+
+                    try:
+                        if args.validate_onnx or args.output_torch_latency:
+                            outputs, torch_latency = gpt2helper.pytorch_inference(model, dummy_inputs, args.test_times)
+
+                            # Dump Torch output shape
+                            for i, value in enumerate(outputs):
+                                if isinstance(value, tuple):
+                                    logger.debug(
+                                        f"torch output {i} is tuple of size {len(value)}, shape {value[0].shape}"
+                                    )
+                                else:
+                                    logger.debug(f"torch output {i} shape {value.shape}")
+                        else:
+                            outputs = None
+                            torch_latency = None
+
+                        if args.disable_io_binding:
+                            ort_outputs, ort_latency = gpt2helper.onnxruntime_inference(
+                                session, dummy_inputs, args.test_times
+                            )
+                        else:
+                            ort_outputs, ort_latency = gpt2helper.onnxruntime_inference_with_binded_io(
+                                session,
+                                dummy_inputs,
+                                output_buffers,
+                                output_shapes,
+                                args.test_times,
+                                return_numpy=False,
+                                include_copy_output_latency=args.include_copy_output_latency,
+                            )
+
+                        if args.validate_onnx:
+                            copy_outputs = ort_outputs
+                            if not args.disable_io_binding:
+                                # Results of IO binding might be in GPU. Copy outputs to CPU for comparison.
+                                copy_outputs = []
+                                for output in ort_outputs:
+                                    copy_outputs.append(output.cpu().numpy())
+
+                            if gpt2helper.compare_outputs(
+                                outputs,
+                                copy_outputs,
+                                model_class=args.model_class,
+                                rtol=DEFAULT_TOLERANCE[args.precision],
+                                atol=DEFAULT_TOLERANCE[args.precision],
+                            ):
+                                logger.info(
+                                    f"Pytorch and ONNX Runtime outputs are all close (tolerance={DEFAULT_TOLERANCE[args.precision]})."
+                                )
+
+                        logger.info(
+                            "batch_size=%d, sequence_length=%d, past_sequence_length=%d, onnxruntime_latency=%.2f %s %s",
+                            batch_size,
+                            sequence_length,
+                            past_sequence_length,
+                            ort_latency,
+                            "(disable_io_binding)" if args.disable_io_binding else "",
+                            ", torch_latency={torch_latency}" if torch_latency else "",
+                        )
+
+                        row = {
+                            "model_name": args.model_name_or_path,
+                            "model_class": args.model_class,
+                            "stage": args.stage,
+                            "environment_variables": get_ort_environment_variables(),
+                            "gpu": args.use_gpu,
+                            "precision": args.precision,
+                            "optimizer": args.optimize_onnx,
+                            "torchscript": args.torchscript,
+                            "batch_size": batch_size,
+                            "sequence_length": sequence_length,
+                            "past_sequence_length": past_sequence_length,
+                            "disable_io_binding": args.disable_io_binding,
+                            "torch_latency": f"{torch_latency:.2f}" if torch_latency else "None",
+                            "onnxruntime_latency": f"{ort_latency:.2f}",
+                        }
+                        csv_writer.writerow(row)
+                    except Exception:
+                        logger.error("Exception", exc_info=True)  # noqa: G201
+                        return None
+
+    logger.info(f"Results are saved to file {csv_filename}")
+    return csv_filename
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    setup_logger(args.verbose)
+    main(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..7318c8c6d078bd9ad8626dbf089b0897248daf32
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/convert_to_onnx.py
@@ -0,0 +1,566 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+"""
+This converts GPT2 model to onnx. Examples:
+(1) Convert pretrained model 'gpt2' to ONNX
+   python convert_to_onnx.py -m gpt2 --output gpt2.onnx
+(2) Convert pretrained model 'distilgpt2' to ONNX, and use optimizer to get float16 model.
+   python convert_to_onnx.py -m distilgpt2 --output distilgpt2_fp16.onnx -o -p fp16
+(3) Convert a model check point to ONNX, and run optimization and int8 quantization
+   python convert_to_onnx.py -m ./my_model_checkpoint/ --output my_model_int8.onnx -o -p int8
+
+"""
+
+import argparse
+import csv
+import json
+import logging
+import os
+import shutil
+import sys
+import warnings
+from pathlib import Path
+
+import numpy
+import torch
+from benchmark_helper import (
+    Precision,
+    create_onnxruntime_session,
+    get_ort_environment_variables,
+    prepare_environment,
+    setup_logger,
+)
+from gpt2_helper import DEFAULT_TOLERANCE, MODEL_CLASSES, PRETRAINED_GPT2_MODELS, Gpt2Helper
+from gpt2_tester import Gpt2Tester
+from packaging import version
+from quantize_helper import QuantizeHelper
+from transformers import AutoConfig
+from transformers import __version__ as transformers_version
+
+from onnxruntime import __version__ as ort_version
+
+logger = logging.getLogger("")
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name_or_path",
+        required=True,
+        type=str,
+        help="Model path, or pretrained model name in the list: " + ", ".join(PRETRAINED_GPT2_MODELS),
+    )
+
+    parser.add_argument(
+        "--model_class",
+        required=False,
+        type=str,
+        default="GPT2LMHeadModel",
+        choices=list(MODEL_CLASSES.keys()),
+        help="Model type selected in the list: " + ", ".join(MODEL_CLASSES.keys()),
+    )
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default=os.path.join(".", "cache_models"),
+        help="Directory to cache pre-trained models",
+    )
+
+    parser.add_argument(
+        "--output",
+        required=False,
+        type=str,
+        default=os.path.join(".", "onnx_models"),
+        help="Output directory, or model path ends with .onnx",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--optimize_onnx",
+        required=False,
+        action="store_true",
+        help="Use optimizer.py to optimize onnx model",
+    )
+    parser.set_defaults(optimize_onnx=False)
+
+    parser.add_argument("--use_gpu", required=False, action="store_true", help="use GPU for inference")
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        default=None,
+        choices=["dml", "migraphx", "cuda", "tensorrt"],
+        help="use dml, cuda, tensorrt or migraphx for respective backend",
+    )
+
+    parser.add_argument(
+        "--tolerance",
+        required=False,
+        type=float,
+        default=0,
+        help="the absolute and relative tolerance for parity verification",
+    )
+
+    parser.add_argument(
+        "--input_test_file",
+        "-i",
+        required=False,
+        type=str,
+        default="",
+        help="Path to the file with inputs to test with",
+    )
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=False,
+        type=Precision,
+        default=Precision.FLOAT32,
+        choices=list(Precision),
+        help="Precision of model to run. fp32 for full precision, fp16 for half or mixed precision, and int8 for quantization",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--test_cases",
+        required=False,
+        type=int,
+        default=1000,
+        help="Number of test cases per run for parity",
+    )
+    parser.add_argument(
+        "-r",
+        "--test_runs",
+        required=False,
+        type=int,
+        default=10,
+        help="Number of runs for parity. It is used for significance test.",
+    )
+
+    parser.add_argument("--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument("-e", "--use_external_data_format", required=False, action="store_true")
+    parser.set_defaults(use_external_data_format=False)
+
+    parser.add_argument("--overwrite", required=False, action="store_true")
+    parser.set_defaults(overwrite=False)
+
+    parser.add_argument(
+        "--use_int64_inputs",
+        required=False,
+        action="store_true",
+        help="Use int32 instead of int64 for input_ids, position_ids and attention_mask.",
+    )
+    parser.set_defaults(use_int64_inputs=False)
+
+    parser.add_argument(
+        "-s",
+        "--stage",
+        type=int,
+        default=0,
+        required=False,
+        choices=[0, 1, 2],
+        help="Stage in generation: 1 (initial decoder), 2 (decoder), 0 (both). "
+        "1 - decode the first token when past_sequence_length is zero; "
+        "2 - decode the remaining tokens when past_sequence_length is not zero; "
+        "0 - one onnx model for both stages 1 and 2. "
+        "Note that we will optimize 1 and 2 differently for best performance.",
+    )
+
+    fp16_option_group = parser.add_argument_group(
+        'float to float16 conversion parameters that works when "--precision fp16" is specified'
+    )
+
+    fp16_option_group.add_argument(
+        "-a",
+        "--auto_mixed_precision",
+        required=False,
+        action="store_true",
+        help="Convert to mixed precision automatically. Other float16 conversion parameters will be ignored.",
+    )
+    fp16_option_group.set_defaults(auto_mixed_precision=False)
+
+    fp16_option_group.add_argument(
+        "--keep_io_types",
+        required=False,
+        action="store_true",
+        help="Use float32 for past inputs, present and logits outputs.",
+    )
+    fp16_option_group.set_defaults(keep_io_types=False)
+
+    fp16_option_group.add_argument(
+        "--io_block_list",
+        nargs="+",
+        default=[],
+        help="List of inputs or outputs in float32 instead of float16",
+    )
+
+    fp16_option_group.add_argument(
+        "--op_block_list",
+        nargs="+",
+        default=[],
+        help="List of operators (like Add LayerNormalization SkipLayerNormalization EmbedLayerNormalization FastGelu) "
+        "to compute in float32 instead of float16.",
+    )
+
+    fp16_option_group.add_argument(
+        "--node_block_list",
+        nargs="+",
+        default=[],
+        help="List of node names to compute in float32 instead of float16.",
+    )
+
+    fp16_option_group.add_argument(
+        "--force_fp16_initializers",
+        required=False,
+        action="store_true",
+        help="Convert all float initializers to float16.",
+    )
+    fp16_option_group.set_defaults(force_fp16_initializers=False)
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+def get_onnx_model_size(onnx_path: str, use_external_data_format: bool):
+    if not use_external_data_format:
+        return os.path.getsize(onnx_path)
+    else:
+        return sum([f.stat().st_size for f in Path(onnx_path).parent.rglob("*")])
+
+
+def get_latency_name(batch_size, sequence_length, past_sequence_length):
+    return f"average_latency(batch_size={batch_size},sequence_length={sequence_length},past_sequence_length={past_sequence_length})"
+
+
+def main(argv=None, experiment_name: str = "", run_id: str = "0", csv_filename: str = "gpt2_parity_results.csv"):
+    warnings.warn(
+        "This example is deprecated. Use the Olive recipe instead: "
+        "https://github.com/microsoft/olive-recipes/tree/main",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+    result = {}
+    if version.parse(transformers_version) < version.parse(
+        "3.1.0"
+    ):  # past_key_values name does not exist in 3.0.2 or older
+        raise RuntimeError("This tool requires transformers 3.1.0 or later.")
+
+    args = parse_arguments(argv)
+    setup_logger(args.verbose)
+
+    if not experiment_name:
+        experiment_name = " ".join(argv if argv else sys.argv[1:])
+
+    if args.tolerance == 0:
+        args.tolerance = DEFAULT_TOLERANCE[args.precision]
+
+    logger.info(f"Arguments:{args}")
+
+    cache_dir = args.cache_dir
+    output_dir = args.output if not args.output.endswith(".onnx") else os.path.dirname(args.output)
+    prepare_environment(cache_dir, output_dir, args.use_gpu)
+
+    if args.precision != Precision.FLOAT32:
+        assert args.optimize_onnx, "fp16/int8 requires --optimize_onnx"
+
+    if args.precision == Precision.FLOAT16:
+        assert args.use_gpu, "fp16 requires --use_gpu"
+
+    if args.precision == Precision.INT8:
+        assert not args.use_gpu, "quantization only supports CPU"
+
+    model_class = MODEL_CLASSES[args.model_class][0]
+    use_padding = MODEL_CLASSES[args.model_class][2]
+
+    gpt2helper = Gpt2Helper
+    config = AutoConfig.from_pretrained(args.model_name_or_path, cache_dir=cache_dir)
+    model = model_class.from_pretrained(args.model_name_or_path, config=config, cache_dir=cache_dir)
+
+    device = torch.device("cuda:0" if args.use_gpu else "cpu")
+    model.eval().to(device)
+
+    if (not args.use_external_data_format) and (config.n_layer > 24):
+        logger.info("Try --use_external_data_format when model size > 2GB")
+
+    onnx_model_paths = gpt2helper.get_onnx_paths(
+        output_dir,
+        args.model_name_or_path,
+        args.model_class,
+        new_folder=(args.precision == Precision.INT8),
+        remove_existing=["fp32", "fp16", "int8"],
+    )  # Do not remove raw model to save time in parity test
+
+    raw_onnx_model = onnx_model_paths["raw"]
+
+    int_data_type = torch.int64 if args.use_int64_inputs else torch.int32
+
+    if os.path.exists(raw_onnx_model) and not args.overwrite:
+        logger.warning(f"Skip exporting ONNX model since it existed: {raw_onnx_model}")
+    else:
+        logger.info(f"Exporting ONNX model to {raw_onnx_model}")
+        gpt2helper.export_onnx(
+            model,
+            device,
+            raw_onnx_model,
+            args.verbose,
+            args.use_external_data_format,
+            has_position_ids=use_padding,
+            has_attention_mask=use_padding,
+            input_ids_dtype=int_data_type,
+            position_ids_dtype=int_data_type,
+            attention_mask_dtype=int_data_type,
+        )
+
+    fp16_params = {"keep_io_types": args.keep_io_types}
+    if args.io_block_list:
+        fp16_params["keep_io_types"] = args.io_block_list
+    if args.node_block_list:
+        fp16_params["node_block_list"] = args.node_block_list
+    if args.op_block_list:
+        fp16_params["op_block_list"] = args.op_block_list
+    if args.force_fp16_initializers:
+        fp16_params["force_fp16_initializers"] = args.force_fp16_initializers
+
+    is_io_float16 = args.precision == Precision.FLOAT16 and not args.keep_io_types
+
+    optimized_ops = ""
+    all_ops = ""
+    if args.optimize_onnx or args.precision != Precision.FLOAT32:
+        output_path = onnx_model_paths[str(args.precision) if args.precision != Precision.INT8 else "fp32"]
+
+        logger.info(f"Optimizing model to {output_path}")
+        m = gpt2helper.optimize_onnx(
+            raw_onnx_model,
+            output_path,
+            args.precision == Precision.FLOAT16,
+            model.config.num_attention_heads,
+            model.config.hidden_size,
+            args.use_external_data_format,
+            auto_mixed_precision=args.auto_mixed_precision,
+            stage=args.stage,
+            **fp16_params,
+        )
+
+        nodes = m.nodes()
+        op_list = {node.op_type for node in nodes}
+        all_ops = ",".join(op_list)
+
+        # print optimized operators
+        optimized_op_counter = m.get_fused_operator_statistics()
+        if optimized_op_counter:
+            optimized_ops = ",".join([key for key in optimized_op_counter if optimized_op_counter[key] > 0])
+    else:
+        output_path = raw_onnx_model
+
+    if args.precision == Precision.INT8:
+        logger.info("quantizing model...")
+        QuantizeHelper.quantize_onnx_model(output_path, onnx_model_paths["int8"], args.use_external_data_format)
+        model = QuantizeHelper.quantize_torch_model(model)
+        logger.info("finished quantizing model")
+        output_path = onnx_model_paths["int8"]
+
+    if args.output.endswith(".onnx") and output_path != args.output and not args.use_external_data_format:
+        shutil.move(output_path, args.output)
+        output_path = args.output
+
+    logger.info(f"Output path: {output_path}")
+    model_size_in_MB = int(get_onnx_model_size(output_path, args.use_external_data_format) / 1024 / 1024)  # noqa: N806
+
+    provider = args.provider
+    session = create_onnxruntime_session(
+        output_path, args.use_gpu, provider, enable_all_optimization=True, verbose=args.verbose
+    )
+    if args.model_class == "GPT2LMHeadModel" and session is not None:
+        parity_result = gpt2helper.test_parity(
+            session,
+            model,
+            device,
+            is_io_float16,
+            rtol=args.tolerance,
+            atol=args.tolerance,
+            model_class=args.model_class,
+            has_position_ids=use_padding,
+            has_attention_mask=use_padding,
+            input_ids_dtype=int_data_type,
+            position_ids_dtype=int_data_type,
+            attention_mask_dtype=int_data_type,
+            test_cases_per_run=args.test_cases,
+            total_runs=args.test_runs,
+            stage=args.stage,
+            verbose=args.verbose,
+        )
+
+        # An example configuration for testing performance
+        batch_size = 8
+        sequence_length = 32 if args.stage == 1 else 1
+        past_sequence_length = 0 if args.stage == 1 else 32
+
+        latency = gpt2helper.test_performance(
+            session,
+            model,
+            device,
+            is_io_float16,
+            total_runs=100,
+            use_io_binding=True,
+            model_class=args.model_class,
+            has_position_ids=use_padding,
+            has_attention_mask=use_padding,
+            input_ids_dtype=int_data_type,
+            position_ids_dtype=int_data_type,
+            attention_mask_dtype=int_data_type,
+            batch_size=batch_size,
+            sequence_length=sequence_length,
+            past_sequence_length=past_sequence_length,
+        )
+
+        if args.precision == Precision.FLOAT16:
+            logger.info(f"fp16 conversion parameters:{fp16_params}")
+
+        # Write results to file
+        latency_name = get_latency_name(batch_size, sequence_length, past_sequence_length)
+        csv_file_existed = os.path.exists(csv_filename)
+        with open(csv_filename, mode="a", newline="") as csv_file:
+            column_names = [
+                "experiment",
+                "run_id",
+                "model_name",
+                "model_class",
+                "stage",
+                "gpu",
+                "precision",
+                "optimizer",
+                "test_cases",
+                "runs",
+                "keep_io_types",
+                "io_block_list",
+                "op_block_list",
+                "node_block_list",
+                "force_fp16_initializers",
+                "auto_mixed_precision",
+                "optimized_operators",
+                "operators",
+                "environment_variables",
+                "onnxruntime",
+                latency_name,
+                "top1_match_rate",
+                "onnx_size_in_MB",
+                "diff_50_percentile",
+                "diff_90_percentile",
+                "diff_95_percentile",
+                "diff_99_percentile",
+                "diff_pass_rate",
+                "nan_rate",
+                "top1_match_rate_per_run",
+            ]
+            csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+            if not csv_file_existed:
+                csv_writer.writeheader()
+            row = {
+                "experiment": experiment_name,
+                "run_id": run_id,
+                "model_name": args.model_name_or_path,
+                "model_class": args.model_class,
+                "stage": args.stage,
+                "gpu": args.use_gpu,
+                "precision": args.precision,
+                "optimizer": args.optimize_onnx,
+                "test_cases": args.test_cases,
+                "runs": args.test_runs,
+                "keep_io_types": args.keep_io_types,
+                "io_block_list": args.io_block_list,
+                "op_block_list": args.op_block_list,
+                "node_block_list": args.node_block_list,
+                "force_fp16_initializers": args.force_fp16_initializers,
+                "auto_mixed_precision": args.auto_mixed_precision,
+                "optimized_operators": optimized_ops,
+                "operators": all_ops,
+                "environment_variables": get_ort_environment_variables(),
+                "onnxruntime": ort_version,
+                latency_name: f"{latency:.2f}",
+                "diff_50_percentile": parity_result["max_diff_percentile_50"],
+                "diff_90_percentile": parity_result["max_diff_percentile_90"],
+                "diff_95_percentile": parity_result["max_diff_percentile_95"],
+                "diff_99_percentile": parity_result["max_diff_percentile_99"],
+                "diff_pass_rate": parity_result["diff_pass_rate"],
+                "nan_rate": parity_result["nan_rate"],
+                "top1_match_rate": parity_result["top1_match_rate"],
+                "top1_match_rate_per_run": parity_result["top1_match_rate_per_run"],
+                "onnx_size_in_MB": f"{model_size_in_MB}",
+            }
+            logger.info(f"result: {row}")
+            result.update(row)
+            csv_writer.writerow(row)
+
+    if args.input_test_file:
+        test_inputs = []
+        # Each line of test file is a JSON string like:
+        # {"input_ids": [[14698, 257, 1310, 13688, 319, 326]]}
+        with open(args.input_test_file) as read_f:
+            for _, line in enumerate(read_f):
+                line = line.rstrip()  # noqa: PLW2901
+                data = json.loads(line)
+                input_ids = torch.from_numpy(numpy.asarray(data["input_ids"], dtype=numpy.int64)).to(device)
+
+                if use_padding:
+                    if "attention_mask" in data:
+                        numpy_float = numpy.float16 if is_io_float16 else numpy.float32
+                        attention_mask = torch.from_numpy(numpy.asarray(data["attention_mask"], dtype=numpy_float)).to(
+                            device
+                        )
+                    else:
+                        padding = -1
+                        attention_mask = (input_ids != padding).type(torch.float16 if is_io_float16 else torch.float32)
+                        input_ids.masked_fill_(input_ids == padding, 0)
+
+                    if "position_ids" in data:
+                        position_ids = torch.from_numpy(numpy.asarray(data["position_ids"], dtype=numpy.int64)).to(
+                            device
+                        )
+                    else:
+                        position_ids = attention_mask.long().cumsum(-1) - 1
+                        position_ids.masked_fill_(position_ids < 0, 0)
+
+                    inputs = {
+                        "input_ids": input_ids.to(int_data_type),
+                        "position_ids": position_ids.to(int_data_type),
+                        "attention_mask": attention_mask.to(int_data_type),
+                    }
+                else:
+                    inputs = {"input_ids": input_ids.to(int_data_type)}
+
+                test_inputs.append(inputs)
+
+        Gpt2Tester.test_generation(
+            session,
+            model,
+            device,
+            test_inputs,
+            precision=args.precision,
+            model_class=args.model_class,
+            top_k=20,
+            top_k_no_order=True,
+            max_steps=24,
+            max_inputs=0,
+            verbose=args.verbose,
+            save_test_data=3,
+            save_test_data_dir=Path(output_path).parent,
+        )
+
+    logger.info(f"Done. Output model: {output_path}")
+    return result
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..536f1c2171f18254faebe3af02388907477c4415
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_helper.py
@@ -0,0 +1,1031 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+# This script helps onnx conversion and validation for GPT2 model with past state.
+import logging
+import os
+import pickle
+import random
+import shutil
+import tempfile
+import time
+from pathlib import Path
+
+import numpy
+import onnx
+import torch
+from benchmark_helper import Precision
+from float16 import float_to_float16_max_diff
+from fusion_options import FusionOptions
+from io_binding_helper import IOBindingHelper
+from onnx_model import OnnxModel
+from optimizer import optimize_model
+from torch_onnx_export_helper import torch_onnx_export
+from transformers import GPT2Config, GPT2LMHeadModel, GPT2Model, TFGPT2Model
+
+logger = logging.getLogger(__name__)
+
+PRETRAINED_GPT2_MODELS = ["distilgpt2", "gpt2", "gpt2-medium", "gpt2-large", "gpt2-xl"]
+
+DEFAULT_TOLERANCE = {
+    Precision.FLOAT32: 0.0005,
+    Precision.FLOAT16: 0.2,
+    Precision.INT8: 3.0,
+}
+
+
+class GPT2ModelNoPastState(GPT2Model):
+    """Here we wrap a class to disable past state output."""
+
+    def __init__(self, config):
+        super().__init__(config)
+
+    def forward(self, input_ids):
+        return super().forward(input_ids, use_cache=False, return_dict=False)
+
+
+class TFGPT2ModelNoPastState(TFGPT2Model):
+    """Here we wrap a class to disable past state output."""
+
+    def __init__(self, config):
+        config.use_cache = False
+        super().__init__(config)
+
+    def forward(self, input_ids):
+        return super().call(input_ids, use_cache=False)
+
+
+class MyGPT2Model(GPT2Model):
+    """Here we wrap a class for Onnx model conversion for GPT2Model with past state."""
+
+    def __init__(self, config):
+        super().__init__(config)
+
+    @staticmethod
+    def post_process(result, num_layer):
+        if isinstance(result[1][0], (tuple, list)):
+            assert len(result[1]) == num_layer and len(result[1][0]) == 2
+            # assert len(result[1][0][0].shape) == 4 and result[1][0][0].shape == result[1][0][1].shape
+            present = []
+            for i in range(num_layer):
+                # Since transformers v4.*, past key and values are separated outputs.
+                # Here we concate them into one tensor to be compatible with Attention operator.
+                present.append(
+                    torch.cat(
+                        (result[1][i][0].unsqueeze(0), result[1][i][1].unsqueeze(0)),
+                        dim=0,
+                    )
+                )
+            return (result[0], tuple(present))
+
+        return result
+
+    def forward(self, input_ids, position_ids, attention_mask, *past):
+        result = super().forward(
+            input_ids,
+            position_ids=position_ids,
+            attention_mask=attention_mask,
+            past_key_values=past,
+            return_dict=False,
+        )
+        return MyGPT2Model.post_process(result, self.config.n_layer)
+
+
+class MyGPT2LMHeadModel(GPT2LMHeadModel):
+    """Here we wrap a class for Onnx model conversion for GPT2LMHeadModel with past state."""
+
+    def __init__(self, config):
+        super().__init__(config)
+
+    def forward(self, input_ids, position_ids, attention_mask, *past):
+        result = super().forward(
+            input_ids,
+            position_ids=position_ids,
+            attention_mask=attention_mask,
+            past_key_values=past,
+            return_dict=False,
+        )
+
+        return MyGPT2Model.post_process(result, self.config.n_layer)
+
+
+class MyGPT2LMHeadModel_NoPadding(GPT2LMHeadModel):  # noqa: N801
+    """Here we wrap a class for Onnx model conversion for GPT2LMHeadModel with past state and no padding.
+    When you always use batch_size=1 in inference, there is no padding in inputs. In such case, position_ids
+    and attention_mask need no be in inputs.
+    """
+
+    def __init__(self, config):
+        super().__init__(config)
+
+    def forward(self, input_ids, *past):
+        result = super().forward(input_ids, past_key_values=past, return_dict=False)
+
+        return MyGPT2Model.post_process(result, self.config.n_layer)
+
+
+# Maps model class name to a tuple of model class, name of first output and use padding or not
+MODEL_CLASSES = {
+    "GPT2LMHeadModel": (MyGPT2LMHeadModel, "logits", True),
+    "GPT2LMHeadModel_NoPadding": (MyGPT2LMHeadModel_NoPadding, "logits", False),
+    "GPT2Model": (MyGPT2Model, "last_state", True),
+}
+
+
+class Gpt2Inputs:
+    def __init__(self, input_ids, position_ids, attention_mask, past):
+        self.input_ids: torch.LongTensor = input_ids
+        self.position_ids: torch.LongTensor = position_ids
+        self.attention_mask: torch.LongTensor | torch.FloatTensor | torch.HalfTensor = attention_mask
+        self.past: list[torch.FloatTensor] | list[torch.HalfTensor] = past
+
+    def to_list(self) -> list:
+        input_list = [v for v in [self.input_ids, self.position_ids, self.attention_mask] if v is not None]
+        if self.past:
+            input_list.extend(self.past)
+
+        return input_list
+
+    def to_tuple(self) -> tuple:
+        return tuple(v for v in [self.input_ids, self.position_ids, self.attention_mask, self.past] if v is not None)
+
+    def to_fp32(self):
+        # For attention mask, only convert fp16 to fp32, and keep the original type if it is integer.
+        attention_mask = None
+        if self.attention_mask is not None:
+            attention_mask = (
+                self.attention_mask.to(dtype=torch.float32)
+                if (self.attention_mask.dtype == torch.float16)
+                else self.attention_mask
+            )
+
+        past = [p.to(dtype=torch.float32) for p in self.past]
+        return Gpt2Inputs(self.input_ids, self.position_ids, attention_mask, past)
+
+
+class Gpt2Helper:
+    """A helper class for Gpt2 model conversion, inference and verification."""
+
+    @staticmethod
+    def get_dummy_inputs(
+        batch_size: int,
+        past_sequence_length: int,
+        sequence_length: int,
+        num_attention_heads: int,
+        hidden_size: int,
+        num_layer: int,
+        vocab_size: int,
+        device: torch.device,
+        float16: bool = False,
+        has_position_ids: bool = True,
+        has_attention_mask: bool = True,
+        input_ids_dtype: torch.dtype = torch.int32,
+        position_ids_dtype: torch.dtype = torch.int32,
+        attention_mask_dtype: torch.dtype = torch.int32,
+        left_side_padding: bool = True,
+    ) -> Gpt2Inputs:
+        """Create random inputs for GPT2 model.
+        Returns torch tensors of input_ids, position_ids, attention_mask and a list of past state tensors.
+        """
+        float_type = torch.float16 if float16 else torch.float32
+        past_shape = [
+            2,
+            batch_size,
+            num_attention_heads,
+            past_sequence_length,
+            int(hidden_size / num_attention_heads),
+        ]
+
+        past = [(torch.rand(past_shape, dtype=float_type, device=device) * 2.0 - 1.0) for _ in range(num_layer)]
+        input_ids = torch.randint(
+            low=0,
+            high=vocab_size - 1,
+            size=(batch_size, sequence_length),
+            dtype=input_ids_dtype,
+            device=device,
+        )
+
+        attention_mask = None
+        if has_attention_mask:
+            total_sequence_length = past_sequence_length + sequence_length
+            attention_mask = torch.ones(
+                [batch_size, total_sequence_length],
+                dtype=attention_mask_dtype,
+                device=device,
+            )
+
+            if total_sequence_length >= 2:
+                for i in range(batch_size):
+                    padding_length = random.randint(0, total_sequence_length - 1)
+                    if left_side_padding:
+                        attention_mask[i, :padding_length] = 0
+                    else:  # right side padding
+                        attention_mask[i, total_sequence_length - padding_length :] = 0
+
+        # Deduce position_ids from attention mask
+        position_ids = None
+        if has_position_ids:
+            position_ids = attention_mask.long().cumsum(-1) - 1
+            position_ids.masked_fill_(position_ids < 0, 0)
+            position_ids = position_ids[:, past_sequence_length:].to(position_ids_dtype)
+
+        return Gpt2Inputs(input_ids, position_ids, attention_mask, past)
+
+    @staticmethod
+    def get_output_shapes(
+        batch_size: int,
+        past_sequence_length: int,
+        sequence_length: int,
+        config: GPT2Config,
+        model_class: str = "GPT2LMHeadModel",
+    ) -> dict[str, list[int]]:
+        """Returns a dictionary with output name as key, and shape as value."""
+        num_attention_heads = config.num_attention_heads
+        hidden_size = config.hidden_size
+        num_layer = config.num_hidden_layers
+        vocab_size = config.vocab_size
+
+        output_name = MODEL_CLASSES[model_class][1]
+
+        last_state_shape = [
+            batch_size,
+            sequence_length,
+            vocab_size if output_name == "logits" else hidden_size,
+        ]
+        present_state_shape = [
+            2,
+            batch_size,
+            num_attention_heads,
+            past_sequence_length + sequence_length,
+            int(hidden_size / num_attention_heads),
+        ]
+
+        output_shapes = {output_name: last_state_shape}
+        for i in range(num_layer):
+            output_shapes["present_" + str(i)] = present_state_shape
+
+        return output_shapes
+
+    @staticmethod
+    def auto_increase_buffer_size(output_buffers, output_shapes):
+        for key in output_shapes:
+            assert key in output_buffers
+            buffer = output_buffers[key]
+            if numpy.prod(output_shapes[key]) > buffer.nelement():
+                output_buffers[key] = torch.empty(
+                    numpy.prod(output_shapes[key]),
+                    dtype=buffer.dtype,
+                    device=buffer.device,
+                )
+
+    @staticmethod
+    def get_output_buffers(output_shapes, device, is_float16=False):
+        """Returns a dictionary of output name as key, and 1D tensor as value. The tensor has enough space for given shape."""
+        data_type = torch.float16 if is_float16 else torch.float32
+
+        output_buffers = {}
+        for name, shape in output_shapes.items():
+            output_buffers[name] = torch.empty(numpy.prod(shape), dtype=data_type, device=device)
+        return output_buffers
+
+    @staticmethod
+    def diff_outputs(torch_outputs, ort_outputs, relative=False):
+        """Returns the maximum difference between PyTorch and OnnxRuntime outputs."""
+        expected_outputs = torch_outputs[0].cpu().numpy()
+        diff = numpy.abs(expected_outputs - ort_outputs[0])
+        if relative:
+            return numpy.amax(diff / (numpy.abs(expected_outputs) + 1e-6))
+        else:
+            return numpy.amax(diff)
+
+    @staticmethod
+    def compare_outputs(torch_outputs, ort_outputs, rtol=1e-03, atol=1e-03, **kwargs):
+        """Returns True if torch and ORT outputs are close for given thresholds, and False otherwise.
+        Note: need kwargs since Gpt2BeamSearchHelper.compare_outputs has an extra parameter model_class
+        """
+        is_close = numpy.allclose(ort_outputs[0], torch_outputs[0].cpu().numpy(), rtol=rtol, atol=atol)
+        logger.debug(f"PyTorch and OnnxRuntime output 0 (last_state) are close: {is_close}")
+
+        is_all_close = is_close
+        num_layers = len(ort_outputs) - 1
+
+        for layer in range(num_layers):
+            is_close = numpy.allclose(
+                ort_outputs[1 + layer],
+                torch_outputs[1][layer].cpu().numpy(),
+                rtol=rtol,
+                atol=atol,
+            )
+            logger.debug(f"PyTorch and OnnxRuntime layer {layer} state (present_{layer}) are close:{is_close}")
+            is_all_close = is_all_close and is_close
+
+        if not is_all_close:
+            max_abs_diff = Gpt2Helper.diff_outputs(torch_outputs, ort_outputs)
+            logger.info(f"PyTorch and OnnxRuntime results are not all close: max_abs_diff={max_abs_diff:.5f}")
+
+        return is_all_close
+
+    @staticmethod
+    def compare_outputs_v2(torch_outputs, ort_outputs, atol=1e-06):
+        """Compare outputs from PyTorch and OnnxRuntime
+
+        Args:
+            torch_outputs (Tuple[Torch.Tensor]): PyTorch model output
+            ort_outputs (List[numpy.ndarray]): OnnxRuntime output
+            atol (float, optional): Absolute tollerance. Defaults to 1e-06.
+
+        Returns:
+            is_all_close(bool): whether all elements are close.
+            max_abs_diff(float): maximum absolute difference.
+            messages(str): a list of debug message for each output
+        """
+        is_all_close = True
+        is_top1_matched = False
+        max_diffs = []
+        messages = []
+        for i in range(len(ort_outputs)):
+            ort_output = ort_outputs[i]
+            torch_output = (torch_outputs[0] if i == 0 else torch_outputs[1][i - 1]).cpu().numpy()
+            is_close = numpy.allclose(ort_output, torch_output, atol=atol, rtol=0)
+            max_diffs.append(numpy.amax(numpy.abs(torch_output - ort_output)))
+            is_all_close = is_all_close and is_close
+
+            if numpy.isnan(torch_output).any():
+                logger.debug(f"PyTorch output {i} has nan")
+            if numpy.isinf(torch_output).any():
+                logger.debug(f"PyTorch output {i} has inf")
+            if numpy.isnan(ort_output).any():
+                logger.debug(f"ORT output {i} has nan")
+            if numpy.isinf(ort_output).any():
+                logger.debug(f"ORT output {i} has inf")
+
+            diff = numpy.fabs(ort_output - torch_output)
+            idx = numpy.unravel_index(diff.argmax(), diff.shape)
+            messages.append(
+                f"diff={diff[idx]:.9f} index={idx} ort={ort_output[idx]:.9f} torch={float(torch_output[idx]):.9f}"
+            )
+
+            if i == 0:  # logits
+                ort_max_index = numpy.unravel_index(numpy.argmax(ort_output, axis=None), ort_output.shape)
+                torch_max_index = numpy.unravel_index(numpy.argmax(torch_output, axis=None), torch_output.shape)
+                is_top1_matched = numpy.array_equal(ort_max_index, torch_max_index)
+
+        max_diff_output_index = max_diffs.index(max(max_diffs))
+        return (
+            is_all_close,
+            max(max_diffs),
+            max_diff_output_index,
+            messages,
+            is_top1_matched,
+        )
+
+    @staticmethod
+    def export_onnx(
+        model,
+        device,
+        onnx_model_path: str,
+        verbose: bool = False,
+        use_external_data_format: bool = False,
+        has_position_ids: bool = True,
+        has_attention_mask: bool = True,
+        input_ids_dtype: torch.dtype = torch.int32,
+        position_ids_dtype: torch.dtype = torch.int32,
+        attention_mask_dtype: torch.dtype = torch.int32,
+    ):
+        """Export GPT-2 model with past state to ONNX model."""
+        config: GPT2Config = model.config
+        num_layer = config.n_layer
+        dummy_inputs = Gpt2Helper.get_dummy_inputs(
+            batch_size=1,
+            past_sequence_length=1,
+            sequence_length=1,
+            num_attention_heads=config.num_attention_heads,
+            hidden_size=config.hidden_size,
+            num_layer=num_layer,
+            vocab_size=config.vocab_size,
+            device=device,
+            float16=False,
+            has_position_ids=has_position_ids,
+            has_attention_mask=has_attention_mask,
+            input_ids_dtype=input_ids_dtype,
+            position_ids_dtype=position_ids_dtype,
+            attention_mask_dtype=attention_mask_dtype,
+        )
+        input_list = dummy_inputs.to_list()
+
+        with torch.no_grad():
+            outputs = model(*input_list)
+
+        past_names = [f"past_{i}" for i in range(num_layer)]
+        present_names = [f"present_{i}" for i in range(num_layer)]
+
+        # GPT2Model outputs last_state; GPT2LMHeadModel outputs logits (prediction_scores)
+        assert outputs[0].shape[2] == config.vocab_size or outputs[0].shape[2] == config.hidden_size
+        output_names = ["logits" if outputs[0].shape[2] == config.vocab_size else "last_state", *present_names]
+
+        # Shape of input tensors:
+        #    input_ids: (batch_size, seq_len)
+        #    past_{i}:  (2, batch_size, num_heads, past_seq_len, hidden_size/num_heads)
+        #    attention_mask: (batch_size, past_seq_len + seq_len)
+        # Shape of output tensors:
+        #    last_state: (batch_size, seq_len, hidden_size)
+        #      or logits: (batch_size, seq_len, vocab_size)
+        #    present_{i}:  (2, batch_size, num_heads, past_seq_len + seq_len, hidden_size/num_heads)
+        dynamic_axes = {
+            "input_ids": {0: "batch_size", 1: "seq_len"},
+            output_names[0]: {0: "batch_size", 1: "seq_len"},
+        }
+        for name in past_names:
+            dynamic_axes[name] = {1: "batch_size", 3: "past_seq_len"}
+        for name in present_names:
+            dynamic_axes[name] = {1: "batch_size", 3: "total_seq_len"}
+
+        input_names = ["input_ids"]
+        if has_position_ids:
+            dynamic_axes["position_ids"] = {0: "batch_size", 1: "seq_len"}
+            input_names.append("position_ids")
+        if has_attention_mask:
+            dynamic_axes["attention_mask"] = {0: "batch_size", 1: "total_seq_len"}
+            input_names.append("attention_mask")
+        input_names.extend(past_names)
+
+        assert len(outputs) == 2 and len(outputs[1]) == num_layer
+
+        logger.info(
+            f"Shapes: input_ids={dummy_inputs.input_ids.shape} past={dummy_inputs.past[0].shape} output={outputs[0].shape} present={outputs[1][0].shape}"
+        )
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+        if use_external_data_format:
+            # We let PyTorch export onnx to a temp directory first, then convert external data to one file.
+            with tempfile.TemporaryDirectory() as tmp_dir_name:
+                temp_onnx_model_path = os.path.join(tmp_dir_name, "gpt2.onnx")
+                Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+                torch_onnx_export(
+                    model,
+                    args=tuple(input_list),
+                    f=temp_onnx_model_path,
+                    export_params=True,
+                    input_names=input_names,
+                    output_names=output_names,
+                    dynamic_axes=dynamic_axes,
+                    opset_version=14,
+                    do_constant_folding=True,
+                    use_external_data_format=True,
+                    verbose=verbose,
+                )
+
+                model = onnx.load_model(temp_onnx_model_path, load_external_data=True)
+                OnnxModel.save(
+                    model,
+                    onnx_model_path,
+                    save_as_external_data=True,
+                    all_tensors_to_one_file=True,
+                )
+        else:
+            torch_onnx_export(
+                model,
+                args=tuple(input_list),
+                f=onnx_model_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=11,
+                do_constant_folding=True,
+                use_external_data_format=False,
+                verbose=verbose,
+            )
+
+    @staticmethod
+    def optimize_onnx(
+        onnx_model_path,
+        optimized_model_path,
+        is_float16,
+        num_attention_heads,
+        hidden_size,
+        use_external_data_format=False,
+        auto_mixed_precision=False,
+        stage=0,
+        **kwargs,
+    ):
+        """Optimize ONNX model with an option to convert it to use mixed precision."""
+        optimization_options = FusionOptions("gpt2")
+
+        m = optimize_model(
+            onnx_model_path,
+            model_type="gpt2",
+            num_heads=num_attention_heads,
+            hidden_size=hidden_size,
+            opt_level=0,
+            optimization_options=optimization_options,
+            use_gpu=False,
+        )
+
+        if is_float16:
+            if auto_mixed_precision:
+                Gpt2Helper.auto_mixed_precision(m)
+            else:
+                if "keep_io_types" not in kwargs:
+                    kwargs["keep_io_types"] = False
+                m.convert_float_to_float16(use_symbolic_shape_infer=True, **kwargs)
+
+        m.save_model_to_file(optimized_model_path, use_external_data_format)
+        return m
+
+    @staticmethod
+    def auto_mixed_precision(
+        onnx_model: OnnxModel,
+        op_block_list: list[str] = [  # noqa: B006
+            "Add",
+            "LayerNormalization",
+            "SkipLayerNormalization",
+            "FastGelu",
+            "EmbedLayerNormalization",
+        ],
+    ):
+        """Convert GPT-2 model to mixed precision.
+           It detects whether original model has fp16 weights, and set parameters for float16 conversion automatically.
+        Args:
+            onnx_model (OnnxModel): optimized ONNX model
+            op_block_list (List[str], optional): operators to compute in fp32. Defaults to ["Add", "LayerNormalization",
+                                                 "SkipLayerNormalization", "FastGelu", "EmbedLayerNormalization"]
+        Returns:
+            parameters(dict): a dictionary of parameters used in float16 conversion
+        """
+        op_full_set = {node.op_type for node in onnx_model.nodes()}
+        fp32_op_set = set(op_block_list)
+        fp16_op_set = op_full_set.difference(fp32_op_set)
+        logger.info(f"fp32 op: {fp32_op_set} fp16 op: {fp16_op_set}")
+
+        # logits is the first output
+        logits_output_name = onnx_model.graph().output[0].name
+
+        # We use the weight in last MatMul node to detect whether the model is stored with float16 weights from training.
+        is_weight_fp16_precision = False
+        output_name_to_node = onnx_model.output_name_to_node()
+        assert logits_output_name in output_name_to_node
+        node = output_name_to_node[logits_output_name]
+        last_matmul_node = None
+        if node.op_type == "MatMul":
+            last_matmul_node = node
+            logger.info(f"Found last MatMul node for logits: {node.name}")
+            initializer = None
+            for input in node.input:
+                initializer = onnx_model.get_initializer(input)
+                if initializer is not None:
+                    break
+
+            # when the max difference of value after converting float to float16 is lower than a threshold (1e-6),
+            # we can deduce that the weights are stored in float16 precision.
+            max_diff = float_to_float16_max_diff(initializer)
+            logger.debug(f"max diff of converting weights in last MatMul node {node.name}: {max_diff}")
+            is_weight_fp16_precision = max_diff < 1e-6
+        else:
+            logger.warning(f"Failed to find MatMul node for logits. Found {node.op_type} of node {node.name}")
+
+        keep_io_types = []
+        node_block_list = []
+        if (not is_weight_fp16_precision) and (last_matmul_node is not None):
+            # When original weight is float32 precision, keep logits and last MatMul in float32 could get better precision.
+            keep_io_types = [logits_output_name]
+            node_block_list = [last_matmul_node.name]
+
+        parameters = {
+            "keep_io_types": keep_io_types,
+            "op_block_list": op_block_list,
+            "node_block_list": node_block_list,
+            "force_fp16_initializers": is_weight_fp16_precision,
+        }
+
+        logger.info(f"auto_mixed_precision parameters: {parameters}")
+        onnx_model.convert_float_to_float16(use_symbolic_shape_infer=True, **parameters)
+
+        return parameters
+
+    @staticmethod
+    def pytorch_inference(model, inputs: Gpt2Inputs, total_runs: int = 0):
+        """Run inference of PyTorch model, and returns average latency in ms when total_runs > 0 besides outputs."""
+        logger.debug("start pytorch_inference")
+
+        # Convert it to fp32 as the PyTroch model cannot deal with half input.
+        input_list = inputs.to_fp32().to_list()
+
+        with torch.no_grad():
+            outputs = model(*input_list)
+
+        if total_runs == 0:
+            return outputs
+
+        latency = []
+        with torch.no_grad():
+            for _ in range(total_runs):
+                start = time.time()
+                outputs = model(*input_list)
+                latency.append(time.time() - start)
+
+        average_latency = sum(latency) * 1000 / len(latency)
+        logger.debug("PyTorch inference time = {} ms".format(format(average_latency, ".2f")))  # noqa: G001
+
+        return outputs, average_latency
+
+    @staticmethod
+    def onnxruntime_inference(ort_session, inputs: Gpt2Inputs, total_runs: int = 0):
+        """Run inference of ONNX model, and returns average latency in ms when total_runs > 0 besides outputs."""
+        logger.debug("start onnxruntime_inference")
+
+        ort_inputs = {"input_ids": numpy.ascontiguousarray(inputs.input_ids.cpu().numpy())}
+
+        if inputs.past is not None:
+            for i, past_i in enumerate(inputs.past):
+                ort_inputs[f"past_{i}"] = numpy.ascontiguousarray(past_i.cpu().numpy())
+
+        if inputs.attention_mask is not None:
+            ort_inputs["attention_mask"] = numpy.ascontiguousarray(inputs.attention_mask.cpu().numpy())
+
+        if inputs.position_ids is not None:
+            ort_inputs["position_ids"] = numpy.ascontiguousarray(inputs.position_ids.cpu().numpy())
+
+        ort_outputs = ort_session.run(None, ort_inputs)
+        if total_runs == 0:
+            return ort_outputs
+
+        latency = []
+        for _ in range(total_runs):
+            start = time.time()
+            ort_outputs = ort_session.run(None, ort_inputs)
+            latency.append(time.time() - start)
+
+        average_latency = sum(latency) * 1000 / len(latency)
+        logger.debug("OnnxRuntime Inference time = {} ms".format(format(average_latency, ".2f")))  # noqa: G001
+
+        return ort_outputs, average_latency
+
+    @staticmethod
+    def prepare_io_binding(
+        ort_session,
+        input_ids,
+        position_ids,
+        attention_mask,
+        past,
+        output_buffers,
+        output_shapes,
+    ):
+        """Returnas IO binding object for a session."""
+        return IOBindingHelper.prepare_io_binding(
+            ort_session,
+            input_ids,
+            position_ids,
+            attention_mask,
+            past,
+            output_buffers,
+            output_shapes,
+        )
+
+    @staticmethod
+    def get_outputs_from_io_binding_buffer(ort_session, output_buffers, output_shapes, return_numpy=True):
+        """Copy results to cpu. Returns a list of numpy array."""
+        return IOBindingHelper.get_outputs_from_io_binding_buffer(
+            ort_session, output_buffers, output_shapes, return_numpy
+        )
+
+    @staticmethod
+    def onnxruntime_inference_with_binded_io(
+        ort_session,
+        inputs: Gpt2Inputs,
+        output_buffers: dict[str, torch.Tensor],
+        output_shapes: dict[str, list[int]],
+        total_runs: int = 0,
+        return_numpy: bool = True,
+        include_copy_output_latency: bool = False,
+    ):
+        """Inference with IO binding. Returns outputs, and optional latency when total_runs > 0."""
+        logger.debug("start onnxruntime_inference_with_binded_io")
+
+        # Bind inputs and outputs to onnxruntime session
+        io_binding = Gpt2Helper.prepare_io_binding(
+            ort_session,
+            inputs.input_ids,
+            inputs.position_ids,
+            inputs.attention_mask,
+            inputs.past,
+            output_buffers,
+            output_shapes,
+        )
+
+        # Run onnxruntime with io binding
+        ort_session.run_with_iobinding(io_binding)
+
+        # Copy results to cpu for verification
+        ort_outputs = Gpt2Helper.get_outputs_from_io_binding_buffer(
+            ort_session, output_buffers, output_shapes, return_numpy
+        )
+
+        if total_runs == 0:
+            return ort_outputs
+
+        latency = []
+        for _ in range(total_runs):
+            start = time.time()
+            # Run onnxruntime with io binding
+            ort_session.run_with_iobinding(io_binding)
+            if include_copy_output_latency:
+                _ = Gpt2Helper.get_outputs_from_io_binding_buffer(
+                    ort_session, output_buffers, output_shapes, return_numpy
+                )
+            latency.append(time.time() - start)
+
+        average_latency = sum(latency) * 1000 / len(latency)
+        logger.debug("OnnxRuntime with IO binding inference time = %.2f ms", average_latency)
+
+        return ort_outputs, average_latency
+
+    @staticmethod
+    def save_outputs(i, ort_outputs, torch_outputs):
+        with open(f"ort_outputs_{i}.pickle", "wb") as f:
+            pickle.dump(ort_outputs, f)
+        logger.info(f"ORT output are saved to ort_outputs_{i}.pickle")
+
+        with open(f"torch_outputs_{i}.pickle", "wb") as f:
+            pickle.dump(torch_outputs, f)
+        logger.info(f"Torch output are saved to torch_outputs_{i}.pickle")
+
+    @staticmethod
+    def save_inputs(i, dummy_inputs, ort_outputs, torch_outputs):
+        with open(f"dummy_inputs_{i}.pickle", "wb") as f:
+            pickle.dump(dummy_inputs, f)
+        logger.info(f"inputs are saved to dummy_inputs_{i}.pickle")
+
+    @staticmethod
+    def test_parity(
+        ort_session,
+        model,
+        device,
+        is_float16=False,
+        rtol=5e-4,
+        atol=5e-4,
+        test_cases_per_run=10000,
+        total_runs=1,
+        use_io_binding=True,
+        model_class="GPT2LMHeadModel",
+        has_position_ids=True,
+        has_attention_mask=True,
+        input_ids_dtype=torch.int32,
+        position_ids_dtype=torch.int32,
+        attention_mask_dtype=torch.int32,
+        stage=0,
+        verbose=False,
+        enable_pickle_output=False,
+    ):
+        """Generate random inputs and compare the results of PyTorch and Onnx Runtime."""
+
+        config: GPT2Config = model.config
+
+        logger.info(
+            f"Running parity test (atol={atol}, test_cases={test_cases_per_run}, runs={total_runs}, use_io_binding={use_io_binding}, model_class={model_class}, is_float16={is_float16}) ..."
+        )
+
+        max_batch_size = 8
+        max_past_seq_len = 4  # Do not use large number here for higher chance of hitting empty past (past_seq_len=0)
+        max_seq_len = 2
+
+        output_buffers = None
+        if use_io_binding:
+            max_output_shapes = Gpt2Helper.get_output_shapes(
+                max_batch_size, max_past_seq_len, max_seq_len, config, model_class
+            )
+            output_buffers = Gpt2Helper.get_output_buffers(max_output_shapes, device, is_float16)
+
+        passed_test_cases = 0
+        top1_matched_cases = 0
+
+        max_abs_diff_list = []
+        top1_matched_cases_per_run = [0] * total_runs
+        total_test_cases = test_cases_per_run * total_runs
+        for i in range(total_test_cases):
+            run_id = int(i / test_cases_per_run)
+            sequence_length = random.randint(1, max_seq_len)
+            past_sequence_length = 0 if (stage == 1) else random.randint(0, max_past_seq_len)
+            batch_size = random.randint(1, max_batch_size)
+
+            logger.debug(
+                f"Running parity test for batch_size={batch_size} past_sequence_length={past_sequence_length}..."
+            )
+            dummy_inputs = Gpt2Helper.get_dummy_inputs(
+                batch_size,
+                past_sequence_length,
+                sequence_length,
+                config.num_attention_heads,
+                config.hidden_size,
+                config.n_layer,
+                config.vocab_size,
+                device,
+                is_float16,
+                has_position_ids,
+                has_attention_mask,
+                input_ids_dtype=input_ids_dtype,
+                position_ids_dtype=position_ids_dtype,
+                attention_mask_dtype=attention_mask_dtype,
+                left_side_padding=True,
+            )
+            outputs = Gpt2Helper.pytorch_inference(model, dummy_inputs)
+            if use_io_binding:
+                ort_outputs = Gpt2Helper.onnxruntime_inference(ort_session, dummy_inputs)
+            else:
+                output_shapes = Gpt2Helper.get_output_shapes(
+                    batch_size,
+                    past_sequence_length,
+                    sequence_length,
+                    config,
+                    model_class,
+                )
+                ort_outputs = Gpt2Helper.onnxruntime_inference_with_binded_io(
+                    ort_session, dummy_inputs, output_buffers, output_shapes
+                )
+
+            (
+                is_all_close,
+                max_abs_diff,
+                max_diff_output_index,
+                messages,
+                is_top1_matched,
+            ) = Gpt2Helper.compare_outputs_v2(outputs, ort_outputs, atol=atol)
+            if not numpy.isnan(max_abs_diff):
+                max_abs_diff_list.append(max_abs_diff)
+            if is_all_close:
+                passed_test_cases += 1
+
+            if is_top1_matched:
+                top1_matched_cases += 1
+                top1_matched_cases_per_run[run_id] += 1
+
+            if verbose and not is_all_close:
+                logger.info(
+                    f"test_case={i} batch_size={batch_size} past_sequence_length={past_sequence_length} sequence_length={sequence_length} MaxDiff={max_abs_diff}"
+                )
+                for i, message in enumerate(messages):  # noqa: PLW2901
+                    logger.info(f"\t{i}: Name={ort_session.get_outputs()[i].name}, {message}")
+
+            # Collect data for debugging
+            if enable_pickle_output and (numpy.isnan(max_abs_diff) or max_abs_diff > 100 * atol):
+                Gpt2Helper.save_inputs(i, dummy_inputs)
+                Gpt2Helper.save_outputs(i, ort_outputs, outputs)
+
+        if max_abs_diff_list:
+            result = {
+                f"max_diff_percentile_{p}": f"{numpy.percentile(max_abs_diff_list, p):.5f}" for p in [50, 90, 95, 99]
+            }
+        else:
+            result = {f"max_diff_percentile_{p}": "nan" for p in [50, 90, 95, 99]}
+
+        result["top1_match_rate"] = top1_matched_cases * 1.0 / total_test_cases
+        result["top1_match_rate_per_run"] = [x * 1.0 / test_cases_per_run for x in top1_matched_cases_per_run]
+        result["diff_pass_rate"] = passed_test_cases * 1.0 / total_test_cases
+        result["nan_rate"] = (total_test_cases - len(max_abs_diff_list)) * 1.0 / total_test_cases
+
+        logger.info(
+            f"Parity Test Cases={total_test_cases}; Passed={passed_test_cases}; Nan={total_test_cases - len(max_abs_diff_list)}; Top1_Matched={top1_matched_cases}"
+        )
+
+        if passed_test_cases > 0.95 * total_test_cases:
+            logger.info(f"Parity is good: passed rate={int(passed_test_cases * 100 / total_test_cases):.0f}%")
+
+        return result
+
+    @staticmethod
+    def test_performance(
+        ort_session,
+        model,
+        device,
+        is_float16=False,
+        total_runs=100,
+        use_io_binding=True,
+        model_class="GPT2LMHeadModel",
+        has_position_ids=True,
+        has_attention_mask=True,
+        input_ids_dtype=torch.int32,
+        position_ids_dtype=torch.int32,
+        attention_mask_dtype=torch.int32,
+        batch_size=8,
+        sequence_length=1,
+        past_sequence_length=32,
+    ):
+        """Generate random inputs and measure average latency of Onnx Runtime."""
+
+        config: GPT2Config = model.config
+
+        output_buffers = None
+        if use_io_binding:
+            output_shapes = Gpt2Helper.get_output_shapes(
+                batch_size, past_sequence_length, sequence_length, config, model_class
+            )
+            output_buffers = Gpt2Helper.get_output_buffers(output_shapes, device, is_float16)
+
+        dummy_inputs = Gpt2Helper.get_dummy_inputs(
+            batch_size,
+            past_sequence_length,
+            sequence_length,
+            config.num_attention_heads,
+            config.hidden_size,
+            config.n_layer,
+            config.vocab_size,
+            device,
+            is_float16,
+            has_position_ids,
+            has_attention_mask,
+            input_ids_dtype=input_ids_dtype,
+            position_ids_dtype=position_ids_dtype,
+            attention_mask_dtype=attention_mask_dtype,
+        )
+
+        if use_io_binding:
+            _, latency = Gpt2Helper.onnxruntime_inference(ort_session, dummy_inputs, total_runs)
+        else:
+            _, latency = Gpt2Helper.onnxruntime_inference_with_binded_io(
+                ort_session, dummy_inputs, output_buffers, output_shapes, total_runs
+            )
+
+        return latency
+
+    @staticmethod
+    def torchscript(model, config, device, has_position_ids=True, has_attention_mask=True):
+        """JIT trace for TorchScript."""
+        input_list = Gpt2Helper.get_dummy_inputs(
+            batch_size=1,
+            past_sequence_length=1,
+            sequence_length=1,
+            num_attention_heads=config.num_attention_heads,
+            hidden_size=config.hidden_size,
+            num_layer=config.n_layer,
+            vocab_size=config.vocab_size,
+            device=device,
+            float16=False,
+            has_position_ids=has_position_ids,
+            has_attention_mask=has_attention_mask,
+        ).to_list()
+        return torch.jit.trace(model, input_list)
+
+    @staticmethod
+    def get_onnx_paths(
+        output_dir,
+        model_name_or_path,
+        model_class: str = "GPT2LMHeadModel",
+        has_past=True,
+        new_folder=False,
+        remove_existing=["raw", "fp32", "fp16", "int8"],  # noqa: B006
+    ):
+        """Build a  path name for given model based on given attributes."""
+        model_name = model_name_or_path
+        if os.path.isdir(model_name_or_path):
+            model_name = Path(model_name_or_path).parts[-1]
+        else:
+            model_name.split("/")[-1]
+
+        if model_class != "GPT2LMHeadModel":
+            model_name += "_" + model_class
+
+        if has_past:
+            model_name += "_past"
+
+        if new_folder:
+            suffix = {"raw": "", "fp32": "_fp32", "fp16": "_fp16", "int8": "_int8"}
+            # Remove the directories if existed.
+            for model_type in ["raw", "fp32", "fp16", "int8"]:
+                new_dir = os.path.join(output_dir, model_name + suffix[model_type])
+                if os.path.exists(new_dir):
+                    if model_type in remove_existing:
+                        try:
+                            shutil.rmtree(new_dir)
+                            logger.info(f"Removed the existed directory: {new_dir}")
+                        except OSError as e:
+                            logger.info(f"Failed to remove the directory {new_dir}: {e.strerror}")
+                    else:
+                        logger.info(f"Directory for {model_type} existed: {new_dir}")
+
+            # store each model to its own directory (for external data format).
+            return {
+                "raw": os.path.join(os.path.join(output_dir, model_name), model_name + ".onnx"),
+                "fp32": os.path.join(
+                    os.path.join(output_dir, model_name + "_fp32"),
+                    model_name + "_fp32.onnx",
+                ),
+                "fp16": os.path.join(
+                    os.path.join(output_dir, model_name + "_fp16"),
+                    model_name + "_fp16.onnx",
+                ),
+                "int8": os.path.join(
+                    os.path.join(output_dir, model_name + "_int8"),
+                    model_name + "_int8.onnx",
+                ),
+            }
+
+        return {
+            "raw": os.path.join(output_dir, model_name + ".onnx"),
+            "fp32": os.path.join(output_dir, model_name + "_fp32.onnx"),
+            "fp16": os.path.join(output_dir, model_name + "_fp16.onnx"),
+            "int8": os.path.join(output_dir, model_name + "_int8.onnx"),
+        }
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_parity.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_parity.py
new file mode 100644
index 0000000000000000000000000000000000000000..3153fc502220f3c1aae21f22a46563a8dfcce053
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_parity.py
@@ -0,0 +1,513 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+# This script uses different configurations in mixed precision conversion for GPT-2 model, and
+# measures the inference latency, top 1 match rate (compared to PyTorch FP32 model) and ONNX model size.
+# It outputs a csv file with Mann-Whitney U test and T-Test on each pair of experiments, where
+# pvalue < 0.05 means two experiments have significant difference on top 1 match rate.
+# User could use this script to select the best mixed precision model according to these metrics.
+
+import argparse
+import csv
+import datetime
+import json
+import logging
+import os
+
+import onnx
+import scipy.stats
+from benchmark_helper import get_ort_environment_variables, setup_logger
+from convert_to_onnx import main
+from gpt2_helper import PRETRAINED_GPT2_MODELS, Gpt2Helper
+from onnx_model import OnnxModel
+
+logger = logging.getLogger("")
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name_or_path",
+        required=True,
+        type=str,
+        help="Model path, or pretrained model name in the list: " + ", ".join(PRETRAINED_GPT2_MODELS),
+    )
+
+    parser.add_argument(
+        "--csv",
+        required=False,
+        type=str,
+        default="gpt2_parity_results.csv",
+        help="path of csv file to save the result",
+    )
+
+    parser.add_argument(
+        "--test_cases",
+        required=False,
+        type=int,
+        default=500,
+        help="number of test cases per run",
+    )
+
+    parser.add_argument("--runs", required=False, type=int, default=40, help="number of repeated runs")
+
+    parser.add_argument("--use_gpu", required=False, action="store_true", help="use GPU for inference")
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "--all",
+        required=False,
+        action="store_true",
+        help="run all combinations of mixed precision",
+    )
+    parser.set_defaults(all=False)
+
+    parser.add_argument("-e", "--use_external_data_format", required=False, action="store_true")
+    parser.set_defaults(use_external_data_format=False)
+
+    parser.add_argument("--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument(
+        "--skip_test",
+        required=False,
+        action="store_true",
+        help="do not run test, and only rank experiments based on existing csv file",
+    )
+    parser.set_defaults(skip_test=False)
+
+    parser.add_argument(
+        "--overwrite",
+        required=False,
+        action="store_true",
+        help="Overwrite existing csv file",
+    )
+    parser.set_defaults(overwrite=False)
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+class ParityTask:
+    def __init__(self, test_cases, total_runs, csv_path):
+        self.total_runs = total_runs
+        self.test_cases = test_cases
+        self.csv_path = csv_path
+        self.results = []
+        self.run_id = 0
+
+    def run(self, argv, experiment_name):
+        start_time = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+        run_id = f"{start_time}_{self.run_id}"
+        self.run_id += 1
+
+        try:
+            result = main(
+                [*argv, "-t", f"{self.test_cases}", "-r", f"{self.total_runs}"],
+                experiment_name=experiment_name,
+                run_id=run_id,
+                csv_filename=self.csv_path,
+            )
+            if result:
+                self.results.append(result)
+        except Exception:
+            logger.exception(f"Failed to run experiment {experiment_name}")
+            result = None
+
+        return result
+
+
+def load_results_from_csv(csv_path):
+    rows = []
+    import csv  # noqa: PLC0415
+
+    with open(csv_path, newline="") as csvfile:
+        reader = csv.DictReader(csvfile)
+        for row in reader:
+            rows.append(row)  # noqa: PERF402
+    return rows
+
+
+def get_latency(row):
+    for name in row:
+        if name.startswith("average_latency(batch_size="):
+            return float(row[name])
+
+    raise RuntimeError("Failed to get average_latency from output")
+
+
+def score(row):
+    """Scoring function based on 3 metrics. The larger score is better."""
+    latency_in_ms = get_latency(row)
+    top1_match_rate = float(row["top1_match_rate"])
+    onnx_size_in_MB = float(row["onnx_size_in_MB"])  # noqa: N806
+    # A simple scoring function: cost of 0.1ms latency ~ 0.1% match rate ~ 100MB size
+    return top1_match_rate * 1000 - latency_in_ms * 10 - onnx_size_in_MB / 100
+
+
+def print_wins(wins, rows, test_name):
+    print()
+    print("*" * 10)
+
+    row_map = {}
+    for row in rows:
+        row_map[row["run_id"]] = row
+
+    sorted_wins = dict(
+        sorted(
+            wins.items(),
+            key=lambda item: (item[1], score(row_map[item[0]])),
+            reverse=True,
+        )
+    )
+    logger.debug(f"{test_name} Wins:{sorted_wins}")
+    logger.info(f"Based on {test_name} wins and a scoring function, the ranking:")
+
+    rank = 0
+    previous_value = -1
+    for count, (key, value) in enumerate(sorted_wins.items()):
+        if value != previous_value:
+            rank = count
+        previous_value = value
+
+        for row in rows:
+            if row["run_id"] == key:
+                logger.info(
+                    "{:02d}: WINs={:02d}, run_id={}, latency={:5.2f}, top1_match={:.4f}, size={}_MB, experiment={}, {}".format(  # noqa: G001
+                        rank,
+                        value,
+                        key,
+                        get_latency(row),
+                        float(row["top1_match_rate"]),
+                        row["onnx_size_in_MB"],
+                        row["experiment"],
+                        get_ort_environment_variables(),
+                    )
+                )
+                break
+
+
+def run_significance_test(rows, output_csv_path):
+    """Run U test and T test."""
+    utest_wins = {}
+    ttest_wins = {}
+    for row in rows:
+        run_id = row["run_id"]
+        utest_wins[run_id] = 0
+        ttest_wins[run_id] = 0
+
+    with open(output_csv_path, "w", newline="") as csvfile:
+        column_names = [
+            "model_name",
+            "run_id_1",
+            "experiment_1",
+            "top1_match_rate_1",
+            "run_id_2",
+            "experiment_2",
+            "top1_match_rate_2",
+            "U_statistic",
+            "U_pvalue",
+            "T_statistic",
+            "T_pvalue",
+        ]
+
+        writer = csv.DictWriter(csvfile, fieldnames=column_names)
+        writer.writeheader()
+
+        required_match_columns = ["model_name", "test_cases", "runs"]
+        num_results = len(rows)
+        for i in range(num_results - 1):
+            result1 = rows[i]
+
+            if isinstance(result1["top1_match_rate_per_run"], str):
+                a = json.loads(result1["top1_match_rate_per_run"])
+            else:
+                a = result1["top1_match_rate_per_run"]
+
+            for j in range(i + 1, num_results, 1):
+                result2 = rows[j]
+
+                all_matched = True
+                for column in required_match_columns:
+                    if result1[column] != result2[column]:
+                        all_matched = False
+                        break
+                if not all_matched:
+                    continue
+
+                if isinstance(result2["top1_match_rate_per_run"], str):
+                    b = json.loads(result2["top1_match_rate_per_run"])
+                else:
+                    b = result2["top1_match_rate_per_run"]
+
+                try:
+                    utest_statistic, utest_pvalue = scipy.stats.mannwhitneyu(
+                        a, b, use_continuity=True, alternative="two-sided"
+                    )  # TODO: shall we use one-sided: less or greater according to "top1_match_rate"
+                except ValueError:  # ValueError: All numbers are identical in mannwhitneyu
+                    utest_statistic = None
+                    utest_pvalue = None
+                ttest_statistic, ttest_pvalue = scipy.stats.ttest_ind(a, b, axis=None, equal_var=True)
+
+                if utest_pvalue is not None and utest_pvalue < 0.05:
+                    if float(result1["top1_match_rate"]) > float(result2["top1_match_rate"]):
+                        utest_wins[result1["run_id"]] += 1
+                    else:
+                        utest_wins[result2["run_id"]] += 1
+
+                if ttest_pvalue < 0.05:
+                    if float(result1["top1_match_rate"]) > float(result2["top1_match_rate"]):
+                        ttest_wins[result1["run_id"]] += 1
+                    else:
+                        ttest_wins[result2["run_id"]] += 1
+
+                row = {
+                    "model_name": result1["model_name"],
+                    "run_id_1": result1["run_id"],
+                    "experiment_1": result1["experiment"],
+                    "top1_match_rate_1": float(result1["top1_match_rate"]),
+                    "run_id_2": result2["run_id"],
+                    "experiment_2": result2["experiment"],
+                    "top1_match_rate_2": float(result2["top1_match_rate"]),
+                    "U_statistic": utest_statistic,
+                    "U_pvalue": utest_pvalue,
+                    "T_statistic": ttest_statistic,
+                    "T_pvalue": ttest_pvalue,
+                }
+
+                writer.writerow(row)
+    logger.info(f"U-Test and T-Test results are output to {output_csv_path}")
+    print_wins(utest_wins, rows, "U-Test")
+    print_wins(ttest_wins, rows, "T-Test")
+
+
+def get_last_matmul_node_name(raw_onnx_model: str):
+    model = onnx.load(raw_onnx_model)
+    onnx_model = OnnxModel(model)
+    output_name_to_node = onnx_model.output_name_to_node()
+
+    assert model.graph.output[0].name in output_name_to_node
+    node = output_name_to_node[model.graph.output[0].name]
+    if node.op_type == "MatMul":
+        logger.info(f"Found last MatMul node for logits: {node.name}")
+        return node.name
+
+    logger.warning(f"Failed to find MatMul node for logits. Found {node.op_type} of node {node.name}")
+    return None
+
+
+def get_mixed_precision_parameters(args, last_matmul_node_name, op_block_list):
+    model = args.model_name_or_path
+    parameters = f"-m {model} -o --use_gpu -p fp16".split()
+    if args.use_external_data_format:
+        parameters.append("--use_external_data_format")
+    parameters += [
+        "--io_block_list",
+        "logits",
+        "--node_block_list",
+        last_matmul_node_name,
+    ]
+
+    if op_block_list:
+        parameters.extend(["--op_block_list", *op_block_list])
+
+    return parameters
+
+
+def run_candidate(
+    task: ParityTask,
+    args,
+    last_matmul_node_name,
+    op_block_list=["FastGelu", "LayerNormalization"],  # noqa: B006
+):
+    parameters = get_mixed_precision_parameters(args, last_matmul_node_name, op_block_list)
+    op_block_list_str = ",".join(sorted(op_block_list))
+
+    if op_block_list:
+        name = f"Mixed precision baseline + {op_block_list_str} in FP32"
+    else:
+        name = f"Mixed precision baseline (logits output and last MatMul node {last_matmul_node_name} in FP32)"
+
+    env_vars = get_ort_environment_variables()
+    if env_vars:
+        name = name + f" ({env_vars})"
+
+    task.run(parameters, name)
+
+
+def get_baselines(args):
+    model = args.model_name_or_path
+    fp32_baseline = f"-m {model} -o -p fp32".split()
+    if args.use_gpu:
+        fp32_baseline.append("--use_gpu")
+    if args.use_external_data_format:
+        fp32_baseline.append("--use_external_data_format")
+
+    fp16_baseline = f"-m {model} -o --use_gpu -p fp16".split()
+    if args.use_external_data_format:
+        fp16_baseline.append("--use_external_data_format")
+
+    return fp32_baseline, fp16_baseline
+
+
+def run_tuning_step0(task, fp16_baseline, all_ops, optimized_ops):
+    """Step 0 is to check which operator in FP16 causes most loss"""
+    fp32_logits = ["--io_block_list", "logits"]
+    task.run(fp16_baseline + fp32_logits, "FP16 except logits")
+
+    fp32_io = ["--keep_io_types"]
+    task.run(fp16_baseline + fp32_io, "Graph I/O FP32, Other FP16")
+
+    # Only weights in FP16
+    task.run(
+        fp16_baseline + fp32_io + ["--op_block_list"] + list(all_ops) + ["--force_fp16_initializers"],
+        "FP32 except weights in FP16",
+    )
+
+    optimized_ops_results = []
+    op_list = optimized_ops
+    for op in op_list:
+        op_block_list = ["--op_block_list"] + [o for o in op_list if o != op]
+        result = task.run(fp16_baseline + fp32_io + op_block_list, f"FP32 except {op} in FP16")
+        if result:
+            optimized_ops_results.append(result)
+
+    # Check which optimized operator causes the most loss in precision
+    min_result = min(optimized_ops_results, key=lambda y: y["top1_match_rate"])
+    print("step 0: optimized operator causes the most loss in precision", min_result)
+
+
+def run_tuning_step1(task, mixed_precision_baseline, optimized_ops):
+    """Step 1 is to figure out which optimized operator in FP32 could benefit most"""
+    for op in optimized_ops:
+        op_block_list = ["--op_block_list", op]
+        task.run(
+            mixed_precision_baseline + op_block_list,
+            f"Mixed precision baseline + {op} in FP32",
+        )
+
+
+def run_tuning_step2(task, mixed_precision_baseline, optimized_ops):
+    """Assumed that you have run step 0 and 1 to figure out that Logits FP32 and some operators shall be in FP32,
+    This step will try add one more operator.
+    """
+    candidate_fp32_ops = ["FastGelu", "LayerNormalization", "SkipLayerNormalization"]
+    fp32_ops = [x for x in candidate_fp32_ops if x in optimized_ops]
+    for op in optimized_ops:
+        if op not in fp32_ops:
+            op_block_list = [*fp32_ops, op]
+            task.run(
+                [*mixed_precision_baseline, "--op_block_list", *op_block_list],
+                "Mixed precision baseline + {},{} in FP32".format(",".join(fp32_ops), op),
+            )
+
+
+def run_parity(task: ParityTask, args):
+    onnx_model_paths = Gpt2Helper.get_onnx_paths(
+        "onnx_models",
+        args.model_name_or_path,
+        new_folder=args.use_external_data_format,
+        remove_existing=[],
+    )
+
+    fp32_baseline, fp16_baseline = get_baselines(args)
+
+    result = task.run(fp32_baseline, "FP32 baseline")
+
+    optimized_ops = []
+    if result and ("optimized_operators" in result) and result["optimized_operators"]:
+        optimized_ops = result["optimized_operators"].split(",")
+    else:
+        raise RuntimeError("Failed to get optimized operators")
+
+    all_ops = []
+    if result and ("operators" in result) and result["operators"]:
+        all_ops = result["operators"].split(",")
+    else:
+        raise RuntimeError("Failed to get operators")
+
+    # The following tests for fp16 requires GPU
+    if not args.use_gpu:
+        logger.info("skip mixed precision since --use_gpu is not specified")
+        return
+
+    task.run(fp16_baseline, "FP16 baseline")
+
+    last_matmul_node_name = get_last_matmul_node_name(onnx_model_paths["raw"])
+
+    # Mixed precision baseline
+    run_candidate(task, args, last_matmul_node_name, op_block_list=[])
+
+    def get_fp32_ops(x):
+        return [op for op in x if op in all_ops]
+
+    if args.all:
+        run_tuning_step0(task, fp16_baseline, all_ops, optimized_ops)
+        mixed_precision_baseline = get_mixed_precision_parameters(args, last_matmul_node_name, op_block_list=[])
+        run_tuning_step1(task, mixed_precision_baseline, optimized_ops)
+        run_tuning_step2(task, mixed_precision_baseline, optimized_ops)
+    else:
+        run_candidate(
+            task,
+            args,
+            last_matmul_node_name,
+            op_block_list=get_fp32_ops(["SkipLayerNormalization", "LayerNormalization", "Add"]),
+        )
+        run_candidate(task, args, last_matmul_node_name, op_block_list=["FastGelu"])
+
+    # Run a few good candidates
+    run_candidate(
+        task,
+        args,
+        last_matmul_node_name,
+        op_block_list=get_fp32_ops(["FastGelu", "SkipLayerNormalization", "LayerNormalization", "Add"]),
+    )
+    run_candidate(
+        task,
+        args,
+        last_matmul_node_name,
+        op_block_list=get_fp32_ops(
+            ["FastGelu", "EmbedLayerNormalization", "SkipLayerNormalization", "LayerNormalization", "Add"]
+        ),
+    )
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    setup_logger(args.verbose)
+
+    if args.test_cases < 100 or args.runs < 20 or args.test_cases * args.runs < 10000:
+        logger.warning(
+            "Not enough test cases or runs to get stable results or test significance. "
+            "Recommend test_cases >= 100, runs >= 20, test_cases * runs >= 10000."
+        )
+
+    if os.path.exists(args.csv) and not args.skip_test:
+        if not args.overwrite:
+            raise RuntimeError(
+                f"Output file {args.csv} existed. Please remove the file, or use either --skip_test or --overwrite."
+            )
+        else:
+            logger.info("Remove existing file %s since --overwrite is specified", args.csv)
+            os.remove(args.csv)
+
+    task = ParityTask(args.test_cases, args.runs, args.csv)
+
+    if not args.skip_test:
+        run_parity(task, args)
+
+    try:
+        rows = load_results_from_csv(task.csv_path)
+    except Exception:
+        logger.exception(f"Failed to load csv {task.csv_path}")
+        rows = task.results
+
+    logger.info("Start running significance tests...")
+    summary_csv = task.csv_path.replace(".csv", ".stats.csv")
+    run_significance_test(rows, summary_csv)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_tester.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_tester.py
new file mode 100644
index 0000000000000000000000000000000000000000..1b832e3241dd63b335f252cc25f77d59b5ca1960
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/gpt2_tester.py
@@ -0,0 +1,501 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+# This script helps evaluation of GPT-2 model.
+import logging
+import math
+import os
+import statistics
+import timeit
+
+import numpy
+import torch
+from benchmark_helper import Precision
+from gpt2_helper import Gpt2Helper, Gpt2Inputs
+
+logger = logging.getLogger(__name__)
+
+
+class Gpt2Metric:
+    def __init__(self, treatment_name, baseline_name="Torch", top_k=20):
+        assert top_k > 1 and top_k <= 100
+        self.baseline = baseline_name
+        self.treatment = treatment_name
+        self.name: str = f"{treatment_name} vs {baseline_name}"
+        self.top_k = top_k
+        self.top_1_error: int = 0
+        self.top_k_error: int = 0
+        self.total_samples: int = 0
+        self.max_logits_diff: float = 0  # for non-empty past state
+        self.max_logits_diff_no_past: float = 0  # for empty past state
+        self.batch_top1_error: torch.FloatTensor = None  # top 1 error for current batch
+        self.batch_topk_error: torch.FloatTensor = None  # top k error for current batch
+        self.seq_len_latency = {}
+
+    def print(self):
+        if self.baseline != self.treatment:
+            print("---")
+            print(f"Metrics for {self.treatment} (baseline={self.baseline}):")
+            if self.total_samples > 0:
+                top_1_error_rate = 100.0 * self.top_1_error / self.total_samples
+                top_k_error_rate = 100.0 * self.top_k_error / self.total_samples
+                print(
+                    f"Total={self.total_samples} Top1Error={self.top_1_error} ({top_1_error_rate:.2f}%) Top{self.top_k}Error={self.top_k_error} ({top_k_error_rate:.2f}%)"
+                )
+            print("Max logits diffs:")
+            print(f"\twith past  = {self.max_logits_diff:.6f}")
+            print(f"\tempty past = {self.max_logits_diff_no_past:.6f}")
+        else:
+            print(f"Metrics for {self.treatment} (baseline):")
+
+        if self.seq_len_latency:
+            print("Past sequence length range and average latency:")
+            total = 0
+            count = 0
+            for key in sorted(self.seq_len_latency.keys()):
+                average = statistics.mean(self.seq_len_latency[key]) * 1000.0
+                if key == 0:
+                    print(f"\t{key}:         \t{average:.2f} ms")
+                else:
+                    print(f"\t[{2**key}, {2 ** (key + 1) - 1}]:\t{average:.2f} ms")
+                total += average * len(self.seq_len_latency[key])
+                count += len(self.seq_len_latency[key])
+            print(f"Average Latency: {total / count:.2f} ms")
+
+    def diff_logits(self, baseline_logits, treatment_logits, is_empty_past: bool):
+        diff = (baseline_logits - treatment_logits).abs().max()
+        if is_empty_past:
+            self.max_logits_diff_no_past = max(self.max_logits_diff_no_past, diff)
+        else:
+            self.max_logits_diff = max(self.max_logits_diff, diff)
+
+        return diff
+
+    def start_batch(self, batch_size: int):
+        self.total_samples += batch_size
+        self.batch_top1_error = torch.zeros((batch_size, 1), dtype=torch.bool)
+        self.batch_topk_error = torch.zeros((batch_size, 1), dtype=torch.bool)
+
+    def eval_batch(self, baseline, treatment, past_seq_len, verbose=True):
+        self._eval_topk(baseline.top_1_tokens, treatment.top_1_tokens, 1, verbose)
+        self._eval_topk(baseline.top_k_tokens, treatment.top_k_tokens, self.top_k, verbose)
+
+        max_diff = self.diff_logits(baseline.logits, treatment.logits, past_seq_len == 0)
+        if verbose:
+            print(f"Max logits diffs of {self.name}: {max_diff}")
+
+    def _eval_topk(self, baseline_topk, treatment_topk, top_k, verbose=True):
+        if not torch.all(torch.eq(baseline_topk, treatment_topk)):
+            if top_k == 1:
+                if verbose:
+                    print(f"Generated tokens not matched for {self.name}")
+                self.batch_top1_error |= torch.eq(baseline_topk, treatment_topk).logical_not()
+            else:
+                if verbose:
+                    print(
+                        f"Top {top_k} tokens not matched for {self.name}. This will lead to wrong beam search results"
+                    )
+                self.batch_topk_error |= (
+                    torch.eq(baseline_topk, treatment_topk).logical_not().sum(1).unsqueeze(dim=1) > 0
+                )
+
+    def end_batch(self):
+        self.top_1_error += self.batch_top1_error.sum()
+        self.top_k_error += self.batch_topk_error.sum()
+
+    def add_latency(self, past_seq_len, latency):
+        key = int(math.log2(past_seq_len)) + 1 if past_seq_len > 0 else 0
+        if key not in self.seq_len_latency:
+            self.seq_len_latency[key] = []
+        self.seq_len_latency[key].append(latency)
+
+
+class Gpt2Tester:
+    def __init__(
+        self,
+        input_ids,
+        position_ids,
+        attention_mask,
+        num_attention_heads,
+        hidden_size,
+        num_layer,
+        device,
+        is_fp16=False,
+        top_k=20,
+        top_k_required_order=False,
+    ):
+        self.batch_size = input_ids.shape[0]
+        self.input_length = input_ids.shape[1]
+        self.n_layer = num_layer
+
+        self.input_ids = input_ids
+        self.position_ids = position_ids
+        self.attention_mask = attention_mask
+
+        self.has_position_ids = position_ids is not None
+        self.has_attention_mask = attention_mask is not None
+
+        # Empty past state for first inference
+        self.past = []
+        past_shape = [
+            2,
+            self.batch_size,
+            num_attention_heads,
+            0,
+            hidden_size // num_attention_heads,
+        ]
+        for _i in range(num_layer):
+            empty_past = torch.empty(past_shape).type(torch.float16 if is_fp16 else torch.float32)
+            self.past.append(empty_past.to(device))
+
+        self.logits = None
+        self.top_1_tokens = None
+        self.top_k_tokens = None
+        self.top_k = top_k
+        self.top_k_required_order = top_k_required_order
+
+    def get_inputs(self) -> Gpt2Inputs:
+        return Gpt2Inputs(self.input_ids, self.position_ids, self.attention_mask, self.past)
+
+    def save_test_data(self, session, output, save_test_data_dir, test_case_id):
+        from onnx import numpy_helper  # noqa: PLC0415
+
+        path = os.path.join(save_test_data_dir, "test_data_set_" + str(test_case_id))
+        if os.path.exists(path):
+            print(f"Directory {path} existed. Skip saving test data")
+            return
+
+        os.makedirs(path, exist_ok=True)
+
+        def add_tensor(input_tensors, torch_tensor, name):
+            input_tensors.append(numpy_helper.from_array(torch_tensor.clone().cpu().numpy(), name))
+
+        input_tensors = []
+        add_tensor(input_tensors, self.input_ids, "input_ids")
+
+        if self.has_position_ids:
+            add_tensor(input_tensors, self.position_ids, "position_ids")
+
+        if self.has_attention_mask:
+            add_tensor(input_tensors, self.attention_mask, "attention_mask")
+
+        for i in range(self.n_layer):
+            add_tensor(input_tensors, self.past[i], "past_" + str(i))
+
+        for i, tensor in enumerate(input_tensors):
+            with open(os.path.join(path, f"input_{i}.pb"), "wb") as f:
+                f.write(tensor.SerializeToString())
+
+        output_names = [output.name for output in session.get_outputs()]
+        for i, _name in enumerate(output_names):
+            tensor = numpy_helper.from_array(
+                output[i] if isinstance(output[i], numpy.ndarray) else output[i].clone().cpu().numpy()
+            )
+            with open(os.path.join(path, f"output_{i}.pb"), "wb") as f:
+                f.write(tensor.SerializeToString())
+
+        print(f"Test data saved to directory {path}")
+
+    def update(self, output, step, device):
+        """
+        Update the inputs for next inference.
+        """
+        self.logits = (
+            torch.from_numpy(output[0]) if isinstance(output[0], numpy.ndarray) else output[0].clone().detach().cpu()
+        )
+
+        self.top_1_tokens = Gpt2Tester.predict_next_token(self.logits)
+        self.top_k_tokens = Gpt2Tester.predict_next_token(self.logits, self.top_k, self.top_k_required_order)
+
+        self.input_ids = self.top_1_tokens.clone().detach().reshape([self.batch_size, 1]).to(device)
+
+        if self.has_position_ids:
+            self.position_ids = (
+                torch.tensor([self.input_length + step - 1]).unsqueeze(0).repeat(self.batch_size, 1).to(device)
+            )
+
+        if self.has_attention_mask:
+            self.attention_mask = torch.cat(
+                [
+                    self.attention_mask,
+                    torch.ones([self.batch_size, 1]).type_as(self.attention_mask),
+                ],
+                1,
+            ).to(device)
+
+        self.past = []
+
+        if isinstance(output[1], tuple):  # past in torch output is tuple
+            self.past = list(output[1])
+        else:
+            for i in range(self.n_layer):
+                past_i = (
+                    torch.from_numpy(output[i + 1])
+                    if isinstance(output[i + 1], numpy.ndarray)
+                    else output[i + 1].clone().detach()
+                )
+                self.past.append(past_i.to(device))
+
+    def diff(self, baseline):
+        """
+        Compare inputs and logits output.
+        """
+
+        print("start diff...")
+        if self.logits is not None:
+            max_io_diff = (self.logits - baseline.logits).abs().max()
+            if max_io_diff > 1e-4:
+                print(f"Max logits difference is too large: {max_io_diff}")
+
+        if not torch.all(self.input_ids == baseline.input_ids):
+            print("Input_ids is different", self.input_ids, baseline.input_ids)
+
+        if self.has_position_ids:
+            if not torch.all(self.position_ids == baseline.position_ids):
+                print(
+                    "position_ids is different",
+                    self.position_ids,
+                    baseline.position_ids,
+                )
+
+        if self.has_attention_mask:
+            if not torch.all(self.attention_mask == baseline.attention_mask):
+                print(
+                    "attention_mask is different",
+                    self.attention_mask,
+                    baseline.attention_mask,
+                )
+
+        assert len(self.past) == len(baseline.past)
+
+        for i, past_i in enumerate(self.past):
+            assert past_i.shape == baseline.past[i].shape
+            if past_i.nelement() > 0:
+                max_past_diff = (past_i - baseline.past[i]).abs().max()
+                if max_past_diff > 1e-4:
+                    print(f"max_past_diff[{i}]={max_past_diff}")
+
+    @staticmethod
+    def predict_next_token(logits, top_k=1, required_order=False):
+        """
+        Get top k topkens based on logits.
+        """
+
+        # logits has shape (batch_size, seq_len, vocab_size)
+        # last token logits has shape (batch_size, vocab_size)
+        lastTokenLogits = logits[:, -1]  # noqa: N806
+        if top_k == 1:
+            generatedTokens = torch.argmax(lastTokenLogits, 1, True)  # noqa: N806
+            return generatedTokens
+        else:
+            topk = torch.argsort(lastTokenLogits, -1, descending=True)[:, :top_k]
+            if not required_order:
+                sorted_topk, _ = topk.sort()
+                return sorted_topk
+            return topk
+
+    @staticmethod
+    def diff_present(onnx_output, onnx_io_output, n_layer):
+        """
+        Compare the present outputs of two outputs from ONNX Runtime.
+        """
+        present_diff_max = []
+        for i in range(n_layer):
+            onnx_present_i = (
+                torch.from_numpy(onnx_output[i + 1])
+                if isinstance(onnx_output[i + 1], numpy.ndarray)
+                else onnx_output[i + 1]
+            )
+            onnx_io_present_i = (
+                torch.from_numpy(onnx_io_output[i + 1])
+                if isinstance(onnx_io_output[i + 1], numpy.ndarray)
+                else onnx_io_output[i + 1]
+            )
+            max_diff = (onnx_present_i - onnx_io_present_i).abs().max()
+            present_diff_max.append(max_diff)
+        print(f"present_diff_max={present_diff_max}")
+
+    @staticmethod
+    def is_quantized_onnx_model(onnx_model_path):
+        """
+        Returns True if the ONNX model is quantized.
+        """
+        from onnx import load  # noqa: PLC0415
+
+        model = load(onnx_model_path)
+        from onnxruntime.quantization.quantize import __producer__ as quantize_producer  # noqa: PLC0415
+
+        return model.producer_name == quantize_producer
+
+    @staticmethod
+    def test_generation(
+        session,
+        model,
+        device,
+        test_inputs,
+        precision=Precision.FLOAT32,
+        model_class="Gpt2LMHeadModel",
+        top_k=20,
+        top_k_no_order=True,
+        max_steps=24,
+        max_inputs=0,
+        verbose=False,
+        save_test_data=0,
+        save_test_data_dir=".",
+    ):
+        """
+        Test Generation using greedy beam search (without sampling) to compare PyTorch and ONNX model.
+        It will print top 1 and top k errors on the given test inputs.
+        """
+        print(
+            f"start test generation: (top_k={top_k} top_k_no_order={top_k_no_order} max_steps={max_steps} test_inputs={len(test_inputs)} max_inputs={max_inputs})"
+        )
+        n_layer = model.config.n_layer
+        n_head = model.config.n_head
+        n_embd = model.config.n_embd
+        eos_token_id = model.config.eos_token_id
+        test_data_saved = 0
+
+        is_float16 = precision == Precision.FLOAT16
+        if is_float16:
+            assert "float16" in session.get_outputs()[0].type
+
+        # We will still use fp32 torch model as baseline when onnx model if fp16
+        model.eval().to(device)
+
+        # Allocate initial buffers for IO Binding of ONNX Runtimne. The buffer size will automatically increase later.
+        init_output_shapes = Gpt2Helper.get_output_shapes(
+            batch_size=4,
+            past_sequence_length=128,
+            sequence_length=32,
+            config=model.config,
+            model_class=model_class,
+        )
+        output_buffers = Gpt2Helper.get_output_buffers(init_output_shapes, device, is_float16=is_float16)
+
+        baseline_name = "Torch"
+        treatment_name = "Quantized Onnx" if precision == Precision.INT8 else "Onnx"
+        torch_metric = Gpt2Metric(baseline_name, baseline_name, top_k)
+        onnx_metric = Gpt2Metric(treatment_name, baseline_name, top_k)
+        onnx_io_metric = Gpt2Metric(treatment_name + " with IO Binding", baseline_name, top_k)
+
+        for i, inputs in enumerate(test_inputs):
+            if max_inputs > 0 and i == max_inputs:
+                break
+            if i % 10 == 0:
+                print(f"{i}")
+            input_ids = inputs["input_ids"]
+            position_ids = inputs.get("position_ids", None)
+            attention_mask = inputs.get("attention_mask", None)
+
+            onnx_runner = Gpt2Tester(
+                input_ids,
+                position_ids,
+                attention_mask,
+                n_head,
+                n_embd,
+                n_layer,
+                device,
+                is_float16,
+                top_k,
+                not top_k_no_order,
+            )
+            onnx_io_runner = Gpt2Tester(
+                input_ids,
+                position_ids,
+                attention_mask,
+                n_head,
+                n_embd,
+                n_layer,
+                device,
+                is_float16,
+                top_k,
+                not top_k_no_order,
+            )
+            torch_runner = Gpt2Tester(
+                input_ids,
+                position_ids,
+                attention_mask,
+                n_head,
+                n_embd,
+                n_layer,
+                device,
+                False,
+                top_k,
+                not top_k_no_order,
+            )  # Torch model baseline is fp32
+
+            batch_size = torch_runner.batch_size
+            onnx_metric.start_batch(batch_size)
+            onnx_io_metric.start_batch(batch_size)
+
+            with torch.no_grad():
+                done = torch.zeros(batch_size, dtype=torch.bool)
+                for step in range(max_steps):
+                    seq_len = list(onnx_runner.input_ids.size())[1]
+                    past_seq_len = list(onnx_runner.past[0].size())[3]
+
+                    start_time = timeit.default_timer()
+                    pytorch_output = Gpt2Helper.pytorch_inference(model, torch_runner.get_inputs())
+                    torch_metric.add_latency(past_seq_len, timeit.default_timer() - start_time)
+                    torch_runner.update(pytorch_output, step, device)
+
+                    onnx_output, avg_latency_ms = Gpt2Helper.onnxruntime_inference(
+                        session, onnx_runner.get_inputs(), total_runs=1
+                    )
+                    onnx_metric.add_latency(past_seq_len, avg_latency_ms / 1000.0)
+                    onnx_runner.update(onnx_output, step, device)
+
+                    output_shapes = Gpt2Helper.get_output_shapes(
+                        batch_size,
+                        past_seq_len,
+                        seq_len,
+                        model.config,
+                        model_class=model_class,
+                    )
+                    Gpt2Helper.auto_increase_buffer_size(output_buffers, output_shapes)
+
+                    (
+                        onnx_io_output,
+                        avg_latency_ms,
+                    ) = Gpt2Helper.onnxruntime_inference_with_binded_io(
+                        session,
+                        onnx_io_runner.get_inputs(),
+                        output_buffers,
+                        output_shapes,
+                        total_runs=1,
+                        return_numpy=False,
+                        include_copy_output_latency=True,
+                    )
+                    onnx_io_metric.add_latency(past_seq_len, avg_latency_ms / 1000.0)
+
+                    if test_data_saved < save_test_data:
+                        onnx_io_runner.save_test_data(session, onnx_io_output, save_test_data_dir, test_data_saved)
+                        test_data_saved += 1
+
+                    onnx_io_runner.update(onnx_io_output, step, device)
+
+                    if verbose:
+                        onnx_runner.diff(onnx_io_runner)
+                        Gpt2Tester.diff_present(onnx_output, onnx_io_output, n_layer)
+
+                        print("Top 1 tokens:")
+                        print("\tTorch", torch_runner.top_1_tokens)
+                        print("\tONNX", onnx_runner.top_1_tokens)
+                        print("\tONNX with IO binding", onnx_io_runner.top_1_tokens)
+
+                    onnx_metric.eval_batch(torch_runner, onnx_runner, past_seq_len, verbose=verbose)
+                    onnx_io_metric.eval_batch(torch_runner, onnx_io_runner, past_seq_len, verbose=verbose)
+
+                    done = done | (torch_runner.top_1_tokens == eos_token_id).any()
+                    if torch.all(done):
+                        break
+
+            onnx_metric.end_batch()
+            onnx_io_metric.end_batch()
+
+        torch_metric.print()
+        onnx_metric.print()
+        onnx_io_metric.print()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/parity_check_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/parity_check_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..2d514ed2f8b3769579dc1c267a7a76f382447a68
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/gpt2/parity_check_helper.py
@@ -0,0 +1,146 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+# This script helps debugging parity issue for two same onnx models with fp16 and fp32 format
+# Please build ORT with --cmake_extra_defines onnxruntime_DEBUG_NODE_INPUTS_OUTPUTS=ON
+
+import math
+import multiprocessing
+import os
+from pathlib import Path
+
+import numpy
+import torch
+from benchmark_helper import create_onnxruntime_session
+from gpt2_helper import Gpt2Helper
+from onnx import TensorProto, numpy_helper
+
+NON_ZERO_VALUE = str(1)
+ZERO_VALUE = str(0)
+
+
+def environ_setting_nodes(node_name_filter=None, node_type_filter=None):
+    # Set I/O data as default
+    os.environ["ORT_DEBUG_NODE_IO_DUMP_SHAPE_DATA"] = ZERO_VALUE
+    os.environ["ORT_DEBUG_NODE_IO_DUMP_INPUT_DATA"] = NON_ZERO_VALUE
+    os.environ["ORT_DEBUG_NODE_IO_DUMP_OUTPUT_DATA"] = NON_ZERO_VALUE
+    if node_name_filter is not None:
+        os.environ["ORT_DEBUG_NODE_IO_NAME_FILTER"] = node_name_filter
+    elif node_type_filter is not None:
+        os.environ["ORT_DEBUG_NODE_IO_OP_TYPE_FILTER"] = node_type_filter
+    else:
+        os.environ["ORT_DEBUG_NODE_IO_DUMPING_DATA_TO_FILES_FOR_ALL_NODES_IS_OK"] = NON_ZERO_VALUE
+
+
+def environ_setting_paths(output_path):
+    # Set dumping values to files as default
+    os.environ["ORT_DEBUG_NODE_IO_DUMP_DATA_DESTINATION"] = "files"
+    os.environ["ORT_DEBUG_NODE_IO_OUTPUT_DIR"] = output_path
+
+
+def environ_reset():
+    for flag in [
+        "ORT_DEBUG_NODE_IO_DUMP_SHAPE_DATA",
+        "ORT_DEBUG_NODE_IO_DUMP_INPUT_DATA",
+        "ORT_DEBUG_NODE_IO_DUMP_OUTPUT_DATA",
+        "ORT_DEBUG_NODE_IO_NAME_FILTER",
+        "ORT_DEBUG_NODE_IO_OP_TYPE_FILTER",
+        "ORT_DEBUG_NODE_IO_DUMP_DATA_TO_FILES",
+        "ORT_DEBUG_NODE_IO_OUTPUT_DIR",
+        "ORT_DEBUG_NODE_IO_DUMPING_DATA_TO_FILES_FOR_ALL_NODES_IS_OK",
+    ]:
+        if flag in os.environ:
+            del os.environ[flag]
+
+
+def inference(model_path, dummy_inputs, outputs_path, use_gpu):
+    environ_reset()
+    environ_setting_nodes()
+    environ_setting_paths(outputs_path)
+    session = create_onnxruntime_session(model_path, use_gpu, enable_all_optimization=False)
+    Gpt2Helper.onnxruntime_inference(session, dummy_inputs)
+
+
+def generate_outputs_files(model_path, dummy_inputs, outputs_path, use_gpu):
+    dir_path = Path(outputs_path)
+    if dir_path.exists() and dir_path.is_dir():
+        import shutil  # noqa: PLC0415
+
+        shutil.rmtree(outputs_path)
+    dir_path.mkdir(parents=True, exist_ok=True)
+
+    process = multiprocessing.Process(target=inference, args=(model_path, dummy_inputs, outputs_path, use_gpu))
+    process.start()
+    process.join()
+
+
+def post_processing(outputs_path, outputs_path_other):
+    # Compare outputs with e.g. fp16 and fp32
+    record = {}
+    if_close = {}
+
+    import glob  # noqa: PLC0415
+
+    for filename in glob.glob(os.path.join(outputs_path, "*.tensorproto")):
+        filename_other = os.path.join(outputs_path_other, Path(filename).name)
+        if not os.path.exists(filename_other):
+            continue
+        with open(filename, "rb") as f:
+            tensor = TensorProto()
+            tensor.ParseFromString(f.read())
+            array = numpy_helper.to_array(tensor)
+            with open(filename_other, "rb") as f:  # noqa: PLW2901
+                tensor_other = TensorProto()
+                tensor_other.ParseFromString(f.read())
+                array_other = numpy_helper.to_array(tensor_other)
+                if array_other.size == 0:
+                    continue
+                diff = numpy.average(numpy.abs(array_other - array) / (numpy.abs(array_other) + 1e-6))
+                if math.isnan(diff):
+                    continue
+                record[Path(filename).name.split(".")[0]] = diff
+                if_close[Path(filename).name.split(".")[0]] = numpy.allclose(array, array_other, rtol=1e-04, atol=1e-04)
+
+    results = ["Node\tDiff\tClose"]
+    for k, v in sorted(record.items(), key=lambda x: x[1], reverse=True):
+        results.append(f"{k}\t{v}\t{if_close[k]}")
+    for line in results:
+        print(line)
+
+
+if __name__ == "__main__":
+    # Below example shows how to use this helper to investigate parity issue of gpt-2 fp32 and fp16 onnx model
+    # Please build ORT with --cmake_extra_defines onnxruntime_DEBUG_NODE_INPUTS_OUTPUTS=ON !!
+    multiprocessing.set_start_method("spawn")
+
+    # Generate Inputs
+    sequence_length = 8
+    past_sequence_length = 8
+    batch_size = 5
+    dummy_inputs_fp16 = Gpt2Helper.get_dummy_inputs(
+        batch_size,
+        past_sequence_length,
+        sequence_length,
+        12,
+        768,
+        12,
+        50257,
+        device=torch.device("cpu"),
+        float16=True,
+    )
+    dummy_inputs_fp32 = dummy_inputs_fp16.to_fp32()
+
+    # Get GPT-2 model from huggingface using convert_to_onnx.py
+    os.system("python convert_to_onnx.py -m gpt2 --output gpt2_fp32.onnx -o -p fp32 --use_gpu")
+    os.system("python convert_to_onnx.py -m gpt2 --output gpt2_fp16.onnx -o -p fp16 --use_gpu")
+
+    # Specify the directory to dump the node's I/O
+    outputs_path_fp32_gpu = "./fp32_gpu"
+    outputs_path_fp16_gpu = "./fp16_gpu"
+    generate_outputs_files("./gpt2_fp32.onnx", dummy_inputs_fp32, outputs_path_fp32_gpu, use_gpu=True)
+    generate_outputs_files("./gpt2_fp16.onnx", dummy_inputs_fp16, outputs_path_fp16_gpu, use_gpu=True)
+
+    # Compare each node's I/O value and sort based on average rtol
+    post_processing(outputs_path_fp16_gpu, outputs_path_fp32_gpu)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f9a57c902589567201d260a9248c59309a74576
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/__pycache__/__init__.cpython-313.pyc
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark.py
@@ -0,0 +1,700 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import argparse
+import datetime
+import gc
+import itertools
+import logging
+import os
+import sys
+import time
+
+import numpy as np
+import onnx
+import psutil
+import torch
+from benchmark_helper import measure_memory, setup_logger
+from dist_settings import get_rank, get_size
+from llama_inputs import (
+    add_io_bindings_as_ortvalues,
+    get_merged_sample_with_past_kv_inputs,
+    get_msft_sample_inputs,
+    get_sample_inputs,
+    get_sample_with_past_kv_inputs,
+    verify_ort_inputs,
+)
+from optimum.onnxruntime import ORTModelForCausalLM
+from torch.profiler import ProfilerActivity, profile, record_function
+from tqdm import trange
+from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
+
+import onnxruntime as ort
+
+logger = logging.getLogger(__name__)
+
+
+# For determining whether the ONNX model can do both prompt generation and token generation or only one of the two
+def get_ort_model_inputs_len(args, model):
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        return 0
+    if args.benchmark_type == "hf-ort":
+        try:
+            # New Optimum export (https://github.com/huggingface/optimum/blob/888332364c2e0091da1fc974737c7e277af168bf/optimum/onnxruntime/modeling_ort.py#L268)
+            return len(model.inputs_names)
+        except Exception:
+            # Old Optimum export (https://github.com/huggingface/optimum/blob/c5ad7f971cb0a494eac03dc0909f146725f999c5/optimum/onnxruntime/base.py#L54)
+            return len(model.decoder.input_names)
+    return len(model.get_inputs())
+
+
+def get_inputs(args: argparse.Namespace, ort_model_inputs_len: int):
+    init_inputs, iter_inputs = None, None
+
+    # For past_present_share_buffer:
+    # Set max_seq_len to 2048 for Microsoft LLaMA-2 model since that is the max value currently supported
+    # Set max_seq_len to config value for other models
+    max_seq_len = 2048 if args.benchmark_type == "ort-msft" else args.config.max_position_embeddings
+
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        init_inputs = get_sample_inputs(
+            args.config,
+            args.target_device,
+            args.batch_size,
+            args.sequence_length,
+            return_dict=True,
+        )
+        iter_inputs = get_sample_with_past_kv_inputs(
+            args.config,
+            args.target_device,
+            args.batch_size,
+            args.sequence_length,
+            use_fp16=args.use_fp16,
+            return_dict=True,
+        )
+
+    elif args.benchmark_type in {"hf-ort"}:
+        if ort_model_inputs_len == 3:  # [input_ids, attention_mask, position_ids]
+            # Using split models in Optimum (e.g. created by Optimum export)
+            init_inputs = get_sample_inputs(
+                args.config,
+                args.target_device,
+                args.batch_size,
+                args.sequence_length,
+                return_dict=True,
+            )
+            iter_inputs = get_sample_with_past_kv_inputs(
+                args.config,
+                args.target_device,
+                args.batch_size,
+                args.sequence_length,
+                use_fp16=args.use_fp16,
+                return_dict=True,
+            )
+        else:
+            # Using merged model in Optimum (e.g. created by convert_to_onnx export)
+            init_inputs = get_merged_sample_with_past_kv_inputs(
+                args.config,
+                args.target_device,
+                args.batch_size,
+                seq_len=args.sequence_length,
+                past_seq_len=0,
+                max_seq_len=max_seq_len,
+                use_fp16=args.use_fp16,
+                use_buffer_share=args.use_buffer_share,
+                engine="pt",
+                return_dict=True,
+            )
+            iter_inputs = get_merged_sample_with_past_kv_inputs(
+                args.config,
+                args.target_device,
+                args.batch_size,
+                seq_len=1,
+                past_seq_len=args.sequence_length,
+                max_seq_len=max_seq_len,
+                use_fp16=args.use_fp16,
+                use_buffer_share=args.use_buffer_share,
+                engine="pt",
+                return_dict=True,
+            )
+
+    elif args.benchmark_type == "ort-convert-to-onnx":
+        # Microsoft export from convert_to_onnx
+        init_inputs = get_merged_sample_with_past_kv_inputs(
+            args.config,
+            args.target_device,
+            args.batch_size,
+            seq_len=args.sequence_length,
+            past_seq_len=0,
+            max_seq_len=max_seq_len,
+            use_fp16=args.use_fp16,
+            use_buffer_share=args.use_buffer_share,
+            engine="ort",
+            return_dict=True,
+            world_size=args.world_size,
+        )
+        iter_inputs = get_merged_sample_with_past_kv_inputs(
+            args.config,
+            args.target_device,
+            args.batch_size,
+            seq_len=1,
+            past_seq_len=args.sequence_length,
+            max_seq_len=max_seq_len,
+            use_fp16=args.use_fp16,
+            use_buffer_share=args.use_buffer_share,
+            engine="ort",
+            return_dict=True,
+            world_size=args.world_size,
+        )
+
+    elif args.benchmark_type == "ort-msft":
+        # Microsoft export from https://github.com/microsoft/Llama-2-Onnx
+        split_kv = ort_model_inputs_len > 5  # original inputs: [x, attn_mask, k_cache, v_cache, pos]
+
+        init_inputs = get_msft_sample_inputs(
+            args.config,
+            args.batch_size,
+            past_seq_len=0,
+            seq_len=args.sequence_length,
+            max_seq_len=max_seq_len,
+            use_fp16=args.use_fp16,
+            use_buffer_share=args.use_buffer_share,
+            split_kv=split_kv,
+        )
+        iter_inputs = get_msft_sample_inputs(
+            args.config,
+            args.batch_size,
+            past_seq_len=args.sequence_length,
+            seq_len=1,
+            max_seq_len=max_seq_len,
+            use_fp16=args.use_fp16,
+            use_buffer_share=args.use_buffer_share,
+            split_kv=split_kv,
+        )
+
+    else:
+        raise Exception("Unable to auto-detect inputs for provided model")
+
+    return init_inputs, iter_inputs
+
+
+def get_model(args: argparse.Namespace):
+    model, sess_options = None, None
+    start_time, end_time = None, None
+
+    # There are multiple sources that the model could come from:
+    # 1) Benchmark LLaMA-2 from unofficial source on Hugging Face
+    # 2) Benchmark LLaMA-2 from official source on Hugging Face, which requires an authentication token
+    # 3) Benchmark LLaMA-2 from local download of model
+    # 4) Benchmark LLaMA-2 from Microsoft (already optimized, available at https://github.com/microsoft/Llama-2-Onnx)
+    # 5) Benchmark LLaMA-2 from convert_to_onnx
+
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        source = args.hf_pt_dir_path if args.hf_pt_dir_path else args.model_name
+        start_time = time.time()
+        model = AutoModelForCausalLM.from_pretrained(
+            source,
+            torch_dtype=torch.float16 if args.use_fp16 else torch.float32,
+            use_auth_token=args.auth,
+            trust_remote_code=args.auth,
+            use_cache=True,
+            cache_dir=args.cache_dir,
+        ).to(args.target_device)
+        end_time = time.time()
+
+        if args.benchmark_type == "hf-pt-compile":
+            model = torch.compile(model)
+
+    elif args.benchmark_type in {"hf-ort", "ort-msft", "ort-convert-to-onnx"}:
+        sess_options = ort.SessionOptions()
+        sess_options.enable_profiling = args.profile
+        if args.verbose:
+            sess_options.log_verbosity_level = 1
+            sess_options.log_severity_level = 1
+
+    else:
+        raise Exception(f"Cannot recognize {args.benchmark_type}")
+
+    if args.benchmark_type == "hf-ort":
+        # Optimum export or convert_to_onnx.py export
+        provider = args.execution_provider[0] if type(args.execution_provider) is tuple else args.execution_provider
+        provider_options = args.execution_provider[1] if type(args.execution_provider) is tuple else None
+
+        decoder_file_name = None
+        decoder_with_past_file_name = None
+        for filename in os.listdir(args.hf_ort_dir_path):
+            if ".onnx" not in filename or ".onnx_data" in filename or ".onnx.data" in filename:
+                continue
+            if "decoder_model" in filename or filename == "model.onnx":
+                decoder_file_name = filename
+            if "decoder_with_past_model" in filename:
+                decoder_with_past_file_name = filename
+            if "decoder_merged_model" in filename:
+                decoder_file_name = filename
+                decoder_with_past_file_name = filename
+
+        start_time = time.time()
+        model = ORTModelForCausalLM.from_pretrained(
+            args.hf_ort_dir_path,
+            decoder_file_name=decoder_file_name,
+            decoder_with_past_file_name=decoder_with_past_file_name,
+            use_auth_token=args.auth,
+            trust_remote_code=args.auth,
+            use_io_binding=True,  # Large perf gain even for cpu due to avoiding output copy.
+            use_merged=(True if decoder_file_name == "model.onnx" else None),
+            provider=provider,
+            provider_options=provider_options,
+            session_options=sess_options,
+        )
+        end_time = time.time()
+
+    if args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}:
+        # Ex: Microsoft export from https://github.com/microsoft/Llama-2-Onnx
+        logger.info(f"Loading model from {args.ort_model_path.format(args.rank)}")
+        start_time = time.time()
+        model = ort.InferenceSession(
+            args.ort_model_path.format(args.rank),
+            sess_options,
+            providers=[args.execution_provider],
+        )
+        end_time = time.time()
+
+    logger.info(f"Loaded model in {end_time - start_time} s")
+    return model
+
+
+def time_fn(args, fn, inputs):
+    # Warm up
+    warmup_range = (
+        range(args.warmup_runs)
+        if args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}
+        else trange(args.warmup_runs, file=sys.stdout, desc="Warm up")
+    )
+
+    if args.verbose:
+        outputs = fn(inputs)
+        logger.info(outputs)
+
+    input_sync = lambda *kwargs: (  # noqa: E731
+        args.io_binding.synchronize_inputs()
+        if args.device != "cpu" and args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}  # ORT synchronize
+        else lambda *kwargs: (
+            torch.cuda.synchronize()
+            if args.device != "cpu" and torch.cuda.is_available()  # PyTorch synchronize
+            else lambda *kwargs: None
+        )
+    )  # no-op function
+
+    output_sync = lambda *kwargs: (  # noqa: E731
+        args.io_binding.synchronize_outputs()
+        if args.device != "cpu" and args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}  # ORT synchronize
+        else lambda *kwargs: (
+            torch.cuda.synchronize()
+            if args.device != "cpu" and torch.cuda.is_available()  # PyTorch synchronize
+            else lambda *kwargs: None
+        )
+    )  # no-op function
+
+    for _ in warmup_range:
+        input_sync()
+        fn(inputs)
+        output_sync()
+
+    # Benchmark
+    total_time = 0
+    bench_range = (
+        range(args.num_runs)
+        if args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}
+        else trange(args.num_runs, file=sys.stdout, desc="Benchmark")
+    )
+    for _ in bench_range:
+        input_sync()
+        start_time = time.time()
+
+        fn(inputs)
+
+        output_sync()
+        end_time = time.time()
+
+        total_time += end_time - start_time
+
+    # Newline print after trange in order to print metrics on new lines without progress bar on same line
+    if args.benchmark_type not in {"ort-msft", "ort-convert-to-onnx"}:
+        logger.info("")
+
+    latency = total_time / args.num_runs
+    throughput = args.batch_size / latency
+
+    if args.rank == 0:
+        logger.info(f"Batch Size: {args.batch_size}")
+        logger.info(f"Sequence Length: {args.sequence_length}")
+        logger.info(f"Latency: {latency} s")
+        logger.info(f"Throughput: {throughput} tps")
+    return
+
+
+def profile_fn(args, fn, inputs, inputs_type):
+    # Filename prefix format:
+    # "b<batch-size>_s<sequence-length>_<benchmark-type>-<precision>-<device>_<inference-step>_<inputs-type>_<current-time>"
+    prefix = f"b{args.batch_size}_s{args.sequence_length}_{args.benchmark_type.lower()}-{args.precision}-{args.device}_{fn.__name__.replace('_', '-')}_{inputs_type}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}"
+    filename = None
+
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        # Profile PyTorch kernels
+        with profile(  # noqa: SIM117
+            activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA], record_shapes=True, profile_memory=True
+        ) as prof:
+            with record_function("model_inference"):
+                fn(inputs)
+        prof_data = prof.key_averages(group_by_stack_n=5).table(sort_by=args.pt_filter_by, row_limit=args.pt_num_rows)
+
+        filename = os.path.join(args.log_folder, f"{prefix}.log")
+        with open(filename, "w") as f:
+            f.write(prof_data)
+
+    else:
+        # Profile ORT kernels
+        fn(inputs)
+
+        # Set new log name for ORT profile log generated
+        filename = f"{prefix}.json"
+
+    return filename
+
+
+def measure_fn(args, fn, inputs):
+    # Measure CPU usage
+    pid = os.getpid()
+    process = psutil.Process(pid)
+    process.cpu_percent(interval=0.1)
+
+    fn(inputs)
+    if args.rank == 0:
+        logger.info(f"CPU usage: {process.cpu_percent(interval=None) / psutil.cpu_count(logical=False)}%")
+
+    # Measure memory usage
+    gc.collect()
+    torch.cuda.empty_cache()
+    measure_memory(is_gpu=(args.device != "cpu"), func=lambda: fn(inputs))
+
+    # Flush output so memory usage is printed
+    sys.stdout.flush()
+
+
+def run_hf_inference(args, init_inputs, iter_inputs, model):
+    # Inference steps to measure
+    def get_logits(inputs):
+        # Inference pass without decoding
+        outputs = model(**inputs)
+        return outputs
+
+    # Examples of other inference steps that can be measured:
+    # To use, uncomment the function and assign it to `generate_fn`
+
+    # def get_pred_ids(inputs):
+    #     # Inference pass with predicted token ids generation
+    #     predicted_ids = model.generate(**inputs)
+    #     return predicted_ids
+
+    # def gen_and_dec(inputs):
+    #     # Inference pass with generation and decoding
+    #     predicted_ids = get_pred_ids(inputs)
+    #     transcription = []
+    #     for bs in range(args.batch_size):
+    #         for rs in range(args.num_return_sequences):
+    #             transcription.append(
+    #                 args.tokenizer.batch_decode(
+    #                     predicted_ids[bs * args.num_return_sequences + rs], skip_special_tokens=True
+    #                 )[0]
+    #             )
+    #     return transcription
+
+    generate_fn = get_logits
+
+    if args.benchmark_type == "hf-pt-compile":
+        # Run forward pass once with each set of inputs to process through Dynamo
+        generate_fn(init_inputs)
+        generate_fn(iter_inputs)
+
+    if args.profile:
+        new_logname = profile_fn(args, generate_fn, init_inputs, "prompt")
+        if args.benchmark_type == "hf-ort":
+            # Turn profiling off to stop appending to log
+            old_logname = model.decoder.session.end_profiling()
+            logger.warning(f"Renaming {old_logname} to {new_logname}")
+            os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+        new_logname = profile_fn(args, generate_fn, iter_inputs, "token")
+        if args.benchmark_type == "hf-ort":
+            # Turn profiling off to stop appending to log
+            old_logname = model.decoder_with_past.session.end_profiling()
+            logger.warning(f"Renaming {old_logname} to {new_logname}")
+            os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+        return
+
+    # PyTorch evaluations
+    logger.info("\nEvaluating `model(inputs)` step to get past_key_values")
+    time_fn(args, generate_fn, init_inputs)
+    measure_fn(args, generate_fn, init_inputs)
+
+    logger.info("\nEvaluating `model(inputs)` step with past_key_values")
+    time_fn(args, generate_fn, iter_inputs)
+    measure_fn(args, generate_fn, iter_inputs)
+
+
+def run_ort_inference(args, init_inputs, iter_inputs, model):
+    def prepare_ort_inputs(inputs, kv_cache_ortvalues):
+        # Verify model inputs
+        inputs = verify_ort_inputs(model, inputs)
+
+        # Add IO bindings for non-CPU execution providers
+        if args.device != "cpu":
+            io_binding, kv_cache_ortvalues = add_io_bindings_as_ortvalues(
+                model, inputs, args.device, int(args.rank), args.use_buffer_share, kv_cache_ortvalues
+            )
+            setattr(args, "io_binding", io_binding)  # noqa: B010
+            return io_binding, kv_cache_ortvalues
+
+        return inputs, kv_cache_ortvalues
+
+    def with_io_binding(io_binding):
+        # Inference pass with IO binding
+        model.run_with_iobinding(io_binding)
+
+    def without_io_binding(inputs):
+        # Inference pass without IO binding
+        outputs = model.run(None, inputs)
+        return outputs
+
+    generate_fn = with_io_binding if args.device != "cpu" else without_io_binding
+    kv_cache_ortvalues = {}
+
+    if args.profile:
+        ort_init_inputs, kv_cache_ortvalues = prepare_ort_inputs(init_inputs, kv_cache_ortvalues)
+        new_logname = profile_fn(args, generate_fn, ort_init_inputs, "prompt")
+
+        # Turn profiling off to stop appending to log file
+        old_logname = model.end_profiling()
+        logger.warning(f"Renaming {old_logname} to {new_logname}")
+        os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+        # Re-initialize model for new log file instead of appending to old log file
+        model = get_model(args)
+        ort_iter_inputs, kv_cache_ortvalues = prepare_ort_inputs(iter_inputs, kv_cache_ortvalues)
+        new_logname = profile_fn(args, generate_fn, ort_iter_inputs, "token")
+
+        # Turn profiling off to stop appending to log
+        old_logname = model.end_profiling()
+        logger.warning(f"Renaming {old_logname} to {new_logname}")
+        os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+        return
+
+    # ORT evaluations
+    logger.info("\nEvaluating `model(inputs)` step to get past_key_values")
+    ort_init_inputs, kv_cache_ortvalues = prepare_ort_inputs(init_inputs, kv_cache_ortvalues)
+    time_fn(args, generate_fn, ort_init_inputs)
+    measure_fn(args, generate_fn, ort_init_inputs)
+
+    logger.info("\nEvaluating `model(inputs)` step with past_key_values")
+    ort_iter_inputs, kv_cache_ortvalues = prepare_ort_inputs(iter_inputs, kv_cache_ortvalues)
+    time_fn(args, generate_fn, ort_iter_inputs)
+    measure_fn(args, generate_fn, ort_iter_inputs)
+
+
+def run_inference(args, init_inputs, iter_inputs, model):
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile", "hf-ort"}:
+        run_hf_inference(args, init_inputs, iter_inputs, model)
+    elif args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}:
+        run_ort_inference(args, init_inputs, iter_inputs, model)
+    else:
+        raise Exception(f"Cannot recognize {args.benchmark_type}")
+
+
+def get_args(rank=0):
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "-bt",
+        "--benchmark-type",
+        type=str,
+        required=True,
+        choices=[
+            "hf-pt-eager",
+            "hf-pt-compile",
+            "hf-ort",
+            "ort-msft",
+            "ort-convert-to-onnx",
+        ],
+    )
+    parser.add_argument(
+        "-m",
+        "--model-name",
+        type=str,
+        required=True,
+        help="Hugging Face name of model (e.g. 'meta-llama/Llama-2-7b-hf')",
+    )
+    parser.add_argument(
+        "-a", "--auth", default=False, action="store_true", help="Use Hugging Face authentication token to access model"
+    )
+
+    # Args for choosing the model
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=True,
+        type=str,
+        default="fp32",
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision for model. For ONNX models, the model's precision should be set before running this script.",
+    )
+    parser.add_argument(
+        "--hf-pt-dir-path",
+        type=str,
+        default="",
+        help="Path to directory containing all PyTorch files (e.g. tokenizer, PyTorch model)",
+    )
+    parser.add_argument(
+        "--hf-ort-dir-path",
+        type=str,
+        default="",
+        help="Path to directory containing all ONNX files (e.g. tokenizer, decoder_merged, decoder, decoder_with_past)",
+    )
+    parser.add_argument(
+        "--ort-model-path",
+        type=str,
+        default="",
+        help="Path to ONNX model",
+    )
+
+    # Args for running and evaluating the model
+    parser.add_argument(
+        "-b",
+        "--batch-sizes",
+        default="1 2",
+    )
+    parser.add_argument(
+        "-s",
+        "--sequence-lengths",
+        default="32 64 128 256 512",
+    )
+    parser.add_argument(
+        "-d",
+        "--device",
+        type=str,
+        default="cuda" if torch.cuda.is_available() else "cpu",
+        choices=["cpu", "cuda"],
+    )
+    parser.add_argument("-id", "--device-id", type=int, default=0)
+    parser.add_argument("-w", "--warmup-runs", type=int, default=5)
+    parser.add_argument("-n", "--num-runs", type=int, default=10)
+    parser.add_argument("--seed", type=int, default=2)
+
+    # Args for decoding logic
+    parser.add_argument("--max-length", type=int, default=32)
+    parser.add_argument("--num-return-sequences", type=int, default=1)
+
+    # Args for accessing detailed info
+    parser.add_argument("--profile", default=False, action="store_true")
+    parser.add_argument(
+        "--pt-filter-by", type=str, default="self_cpu_time_total", help="What to filter PyTorch profiler by"
+    )
+    parser.add_argument("--pt-num-rows", type=int, default=1000, help="Number of rows for PyTorch profiler to display")
+    parser.add_argument("--verbose", default=False, action="store_true")
+    parser.add_argument("--log-folder", type=str, default=os.path.join("."), help="Folder to cache log files")
+    parser.add_argument(
+        "--cache-dir",
+        type=str,
+        required=True,
+        default="./model_cache",
+        help="Cache dir where Hugging Face files are stored",
+    )
+
+    args = parser.parse_args()
+
+    # Set seed properties
+    np.random.seed(args.seed)
+    torch.manual_seed(args.seed)
+
+    # Set runtime properties
+    if "ort" in args.benchmark_type:
+        setattr(args, "execution_provider", f"{args.device.upper()}ExecutionProvider")  # noqa: B010
+        if args.execution_provider == "CUDAExecutionProvider":
+            args.execution_provider = (args.execution_provider, {"device_id": rank})
+
+    # Check that paths have been specified for any benchmarking with ORT
+    if args.benchmark_type == "hf-ort":
+        assert args.hf_ort_dir_path, "Please specify a path to `--hf-ort-dir-path`"
+    if args.benchmark_type in {"ort-msft", "ort-convert-to-onnx"}:
+        assert args.ort_model_path, "Please specify a path to `--ort-model-path`"
+
+    args.batch_sizes = args.batch_sizes.split(" ")
+    args.sequence_lengths = args.sequence_lengths.split(" ")
+
+    # Use FP32 precision for FP32, INT8, INT4 CPU models, use FP16 precision for FP16 and INT4 GPU models
+    args.precision = (
+        "fp32" if args.precision in {"int8", "fp32"} or (args.precision == "int4" and args.device == "cpu") else "fp16"
+    )
+
+    # Check that only one (batch_size, sequence_length) combination is set for profiling
+    if args.profile:
+        assert len(args.batch_sizes) == 1 and len(args.sequence_lengths) == 1, (
+            "Please provide only one (batch_size, sequence_length) combination for profiling"
+        )
+
+    return args
+
+
+def main():
+    rank = get_rank()
+    world_size = get_size()
+
+    args = get_args(rank)
+    setup_logger(args.verbose)
+    logger.info(args.__dict__)
+    torch.backends.cudnn.benchmark = True
+
+    args.rank = rank
+    args.world_size = world_size
+    tokenizer = AutoTokenizer.from_pretrained(
+        args.model_name, cache_dir=args.cache_dir, use_auth_token=args.auth, trust_remote_code=args.auth
+    )
+    config = AutoConfig.from_pretrained(
+        args.model_name, cache_dir=args.cache_dir, use_auth_token=args.auth, trust_remote_code=args.auth
+    )
+    target_device = f"cuda:{args.rank}" if args.device != "cpu" else args.device
+    use_fp16 = args.precision == "fp16"
+
+    setattr(args, "tokenizer", tokenizer)  # noqa: B010
+    setattr(args, "config", config)  # noqa: B010
+    setattr(args, "target_device", target_device)  # noqa: B010
+    setattr(args, "use_fp16", use_fp16)  # noqa: B010
+
+    # Get model and model info
+    model = get_model(args)
+    ort_model_inputs_len = get_ort_model_inputs_len(args, model)
+
+    # Check if past_present_share_buffer can be enabled (only for FP16 models with GQA)
+    if args.benchmark_type in {"ort-convert-to-onnx", "ort-msft"}:
+        onnx_model = onnx.load_model(args.ort_model_path.format(args.rank), load_external_data=False)
+        gqa_nodes = list(filter(lambda node: node.op_type == "GroupQueryAttention", onnx_model.graph.node))
+
+        use_buffer_share = use_fp16 and len(gqa_nodes) > 0 and args.device != "cpu"
+        setattr(args, "use_buffer_share", use_buffer_share)  # noqa: B010
+    else:
+        setattr(args, "use_buffer_share", False)  # noqa: B010
+
+    # Measure prompt cost (init_inputs) and generated token cost (iter_inputs)
+    for batch_size, sequence_length in itertools.product(args.batch_sizes, args.sequence_lengths):
+        if args.rank == 0:
+            logger.info(f"\nBatch size = {batch_size} and sequence length = {sequence_length}...")
+        setattr(args, "batch_size", int(batch_size))  # noqa: B010
+        setattr(args, "sequence_length", int(sequence_length))  # noqa: B010
+
+        init_inputs, iter_inputs = get_inputs(args, ort_model_inputs_len)
+        run_inference(args, init_inputs, iter_inputs, model)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_all.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..287391e5ffd2186c90b5d1d8cd614556eb6022e0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_all.py
@@ -0,0 +1,488 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import argparse
+import datetime
+import json
+import logging
+import os
+import subprocess
+
+import torch
+from benchmark_helper import setup_logger
+from metrics import BenchmarkRecord
+
+logger = logging.getLogger(__name__)
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-b",
+        "--batch-sizes",
+        type=str,
+        default="1 2",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--sequence-lengths",
+        type=str,
+        default="8 16 32 64 128 256 512",
+    )
+
+    parser.add_argument(
+        "-w",
+        "--warmup-runs",
+        type=int,
+        default=5,
+    )
+
+    parser.add_argument(
+        "-n",
+        "--num-runs",
+        type=int,
+        default=1000,
+    )
+
+    parser.add_argument(
+        "--hf-pt-eager",
+        default=False,
+        action="store_true",
+        help="Benchmark in PyTorch without `torch.compile`",
+    )
+
+    parser.add_argument(
+        "--hf-pt-compile",
+        default=False,
+        action="store_true",
+        help="Benchmark in PyTorch with `torch.compile`",
+    )
+
+    parser.add_argument(
+        "--hf-ort-dir-path",
+        type=str,
+        default="",
+        help="Path to folder containing ONNX models for Optimum + ORT benchmarking",
+    )
+
+    parser.add_argument(
+        "--ort-msft-model-path",
+        type=str,
+        default="",
+        help="Path to ONNX model from https://github.com/microsoft/Llama-2-Onnx",
+    )
+
+    parser.add_argument(
+        "--ort-convert-to-onnx-model-path",
+        type=str,
+        default="",
+        help="Path to ONNX model from convert_to_onnx",
+    )
+
+    parser.add_argument(
+        "--cache-dir",
+        type=str,
+        default="./model_cache",
+        help="Cache dir where Hugging Face files are stored",
+    )
+
+    parser.add_argument(
+        "--model-name",
+        type=str,
+        required=True,
+        help="Model name in Hugging Face",
+    )
+
+    parser.add_argument(
+        "--precision",
+        type=str,
+        required=True,
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision to run model",
+    )
+
+    parser.add_argument(
+        "--device",
+        type=str,
+        required=True,
+        choices=["cpu", "cuda"],
+        help="Device to benchmark models",
+    )
+
+    parser.add_argument(
+        "--device-id",
+        type=int,
+        default=0,
+        help="GPU device ID",
+    )
+
+    parser.add_argument(
+        "--verbose",
+        default=False,
+        action="store_true",
+        help="Print detailed logs",
+    )
+
+    parser.add_argument(
+        "--timeout",
+        type=int,
+        default=10,
+        help="Number of mins to attempt the benchmark before moving on",
+    )
+
+    parser.add_argument(
+        "--log-folder",
+        type=str,
+        default=None,
+        help="Path to folder to save logs and results",
+    )
+
+    args = parser.parse_args()
+
+    setattr(args, "model_size", args.model_name.split("/")[-1].replace(".", "-"))  # noqa: B010
+    log_folder_name = f"./{args.model_size}_{args.precision}"
+    if not args.log_folder:
+        args.log_folder = log_folder_name
+    os.makedirs(args.log_folder, exist_ok=True)
+
+    # Convert timeout value to secs
+    args.timeout *= 60
+
+    return args
+
+
+def process_log_file(device_id, log_file, base_results):
+    entries = []
+    batch_size, sequence_length, step = None, None, None
+    latency_s, latency_ms, throughput, memory = None, None, None, None
+
+    batch_pattern = "Batch Size: "
+    sequence_pattern = "Sequence Length: "
+    prompt_step_pattern = "to get past_key_values"
+    per_token_step_pattern = "with past_key_values"
+    latency_pattern = "Latency: "
+    throughput_pattern = "Throughput: "
+    memory_pattern = "peak="
+
+    with open(log_file) as f:
+        for input_line in f:
+            line = input_line.replace("\n", "")
+
+            if batch_pattern in line:
+                batch_size = int(line[len(batch_pattern) :])
+            elif sequence_pattern in line:
+                sequence_length = int(line[len(sequence_pattern) :])
+            elif prompt_step_pattern in line:
+                step = "prompt"
+            elif per_token_step_pattern in line:
+                step = "per-token"
+            elif latency_pattern in line:
+                latency_s = float(line[len(latency_pattern) : line.rfind(" ")])
+                latency_ms = latency_s * 1000
+            elif throughput_pattern in line:
+                throughput = float(line[len(throughput_pattern) : line.rfind(" ")])
+            elif memory_pattern in line:
+                if "CPU" in line:
+                    # Example format for log entry:
+                    # CPU memory usage: before=1000.0 MB, peak=2000.0 MB
+                    memory = float(line[line.rfind("=") + 1 : line.rfind(" MB")]) / 1000
+                else:
+                    # Example format for log entry:
+                    # GPU memory usage: before=[{'device_id': 0, 'name': 'NVIDIA A100-SXM4-80GB', 'max_used_MB': 69637.25}, {'device_id': 1, 'name': 'NVIDIA A100-SXM4-80GB', 'max_used_MB': 890.625}]  peak=[{'device_id': 0, 'name': 'NVIDIA A100-SXM4-80GB', 'max_used_MB': 73861.25}, {'device_id': 1, 'name': 'NVIDIA A100-SXM4-80GB', 'max_used_MB': 890.625}]
+                    peak = line[line.find(memory_pattern) + len(memory_pattern) :].replace("'", '"')
+                    usage = json.loads(peak)[device_id]["max_used_MB"]
+                    memory = float(usage) / 1000
+
+                # Append log entry to list of entries
+                entry = base_results + [  # noqa: RUF005
+                    batch_size,
+                    sequence_length,
+                    step,
+                    latency_s,
+                    latency_ms,
+                    throughput,
+                    memory,
+                ]
+                entries.append(entry)
+
+    return entries
+
+
+def save_results(results, filename):
+    import pandas as pd  # noqa: PLC0415
+
+    df = pd.DataFrame(
+        results,
+        columns=[
+            "Warmup Runs",
+            "Measured Runs",
+            "Model Name",
+            "Engine",
+            "Precision",
+            "Device",
+            "Batch Size",
+            "Sequence Length",
+            "Step",
+            "Latency (s)",
+            "Latency (ms)",
+            "Throughput (tps)",
+            "Memory (GB)",
+        ],
+    )
+
+    # Set column types
+    df["Warmup Runs"] = df["Warmup Runs"].astype("int")
+    df["Measured Runs"] = df["Measured Runs"].astype("int")
+    df["Batch Size"] = df["Batch Size"].astype("int")
+    df["Sequence Length"] = df["Sequence Length"].astype("int")
+    df["Latency (s)"] = df["Latency (s)"].astype("float")
+    df["Latency (ms)"] = df["Latency (ms)"].astype("float")
+    df["Throughput (tps)"] = df["Throughput (tps)"].astype("float")
+    df["Memory (GB)"] = df["Memory (GB)"].astype("float")
+
+    # get package name and version
+    import pkg_resources  # noqa: PLC0415
+
+    installed_packages = pkg_resources.working_set
+    installed_packages_list = sorted(
+        [f"{i.key}=={i.version}" for i in installed_packages if i.key in ["onnxruntime", "onnxruntime-gpu"]]
+    )
+
+    ort_pkg_name = ""
+    ort_pkg_version = ""
+    if installed_packages_list:
+        ort_pkg_name = installed_packages_list[0].split("==")[0]
+        ort_pkg_version = installed_packages_list[0].split("==")[1]
+
+    # Save results to csv with standard format
+    records = []
+    for _, row in df.iterrows():
+        if row["Engine"] in ["optimum-ort", "onnxruntime"]:
+            record = BenchmarkRecord(
+                row["Model Name"], row["Precision"], "onnxruntime", row["Device"], ort_pkg_name, ort_pkg_version
+            )
+        elif row["Engine"] in ["pytorch-eager", "pytorch-compile"]:
+            record = BenchmarkRecord(
+                row["Model Name"], row["Precision"], "pytorch", row["Device"], torch.__name__, torch.__version__
+            )
+        else:
+            record = BenchmarkRecord(row["Model Name"], row["Precision"], row["Engine"], row["Device"], "", "")
+        record.config.warmup_runs = row["Warmup Runs"]
+        record.config.measured_runs = row["Measured Runs"]
+        record.config.batch_size = row["Batch Size"]
+        record.config.seq_length = row["Sequence Length"]
+        record.config.customized["measure_step"] = row["Step"]
+        record.config.customized["engine"] = row["Engine"]
+        record.metrics.customized["latency_s_mean"] = row["Latency (s)"]
+        record.metrics.latency_ms_mean = row["Latency (ms)"]
+        record.metrics.customized["throughput_tps"] = row["Throughput (tps)"]
+        record.metrics.max_memory_usage_GB = row["Memory (GB)"]
+
+        records.append(record)
+
+    BenchmarkRecord.save_as_csv(filename, records)
+    BenchmarkRecord.save_as_json(filename.replace(".csv", ".json"), records)
+    logger.info(f"Results saved in {filename}!")
+
+
+def benchmark(args, benchmark_cmd, engine):
+    log_filename = f"{engine}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}.log"
+    log_path = os.path.join(args.log_folder, log_filename)
+    with open(log_path, "w") as log_file:
+        process = subprocess.Popen(benchmark_cmd, stdout=log_file, stderr=log_file)
+        try:
+            process.wait(args.timeout)
+        except subprocess.TimeoutExpired:
+            process.kill()
+
+    # Create entries for csv
+    logger.info("Gathering data from log files...")
+    base_results = [args.warmup_runs, args.num_runs, args.model_name, engine, args.precision, args.device]
+    results = process_log_file(args.device_id, log_path, base_results)
+
+    return results
+
+
+def main():
+    args = get_args()
+    setup_logger(args.verbose)
+    logger.info(args.__dict__)
+    torch.backends.cudnn.benchmark = True
+
+    all_results = []
+    os.environ["CUDA_VISIBLE_DEVICES"] = str(args.device_id)
+
+    # Benchmark PyTorch without torch.compile
+    if args.hf_pt_eager:
+        benchmark_cmd = [
+            "python",
+            "-m",
+            "models.llama.benchmark",
+            "--benchmark-type",
+            "hf-pt-eager",
+            "--model-name",
+            args.model_name,
+            "--precision",
+            args.precision,
+            "--batch-sizes",
+            args.batch_sizes,
+            "--sequence-lengths",
+            args.sequence_lengths,
+            "--device",
+            args.device,
+            "--warmup-runs",
+            str(args.warmup_runs),
+            "--num-runs",
+            str(args.num_runs),
+            "--log-folder",
+            args.log_folder,
+            "--cache-dir",
+            args.cache_dir,
+            "--auth",
+        ]
+        logger.info("Benchmark PyTorch without torch.compile")
+        results = benchmark(args, benchmark_cmd, "pytorch-eager")
+        all_results.extend(results)
+
+    # Benchmark PyTorch with torch.compile
+    if args.hf_pt_compile:
+        benchmark_cmd = [
+            "python",
+            "-m",
+            "models.llama.benchmark",
+            "--benchmark-type",
+            "hf-pt-compile",
+            "--model-name",
+            args.model_name,
+            "--precision",
+            args.precision,
+            "--batch-sizes",
+            args.batch_sizes,
+            "--sequence-lengths",
+            args.sequence_lengths,
+            "--device",
+            args.device,
+            "--warmup-runs",
+            str(args.warmup_runs),
+            "--num-runs",
+            str(args.num_runs),
+            "--log-folder",
+            args.log_folder,
+            "--cache-dir",
+            args.cache_dir,
+            "--auth",
+        ]
+        logger.info("Benchmark PyTorch with torch.compile")
+        results = benchmark(args, benchmark_cmd, "pytorch-compile")
+        all_results.extend(results)
+
+    # Benchmark Optimum + ONNX Runtime
+    if args.hf_ort_dir_path:
+        benchmark_cmd = [
+            "python",
+            "-m",
+            "models.llama.benchmark",
+            "--benchmark-type",
+            "hf-ort",
+            "--hf-ort-dir-path",
+            args.hf_ort_dir_path,
+            "--model-name",
+            args.model_name,
+            "--precision",
+            args.precision,
+            "--batch-sizes",
+            args.batch_sizes,
+            "--sequence-lengths",
+            args.sequence_lengths,
+            "--device",
+            args.device,
+            "--warmup-runs",
+            str(args.warmup_runs),
+            "--num-runs",
+            str(args.num_runs),
+            "--log-folder",
+            args.log_folder,
+            "--cache-dir",
+            args.cache_dir,
+            "--auth",
+        ]
+        logger.info("Benchmark Optimum + ONNX Runtime")
+        results = benchmark(args, benchmark_cmd, "optimum-ort")
+        all_results.extend(results)
+
+    # Benchmark Microsoft model in ONNX Runtime
+    if args.ort_msft_model_path:
+        benchmark_cmd = [
+            "python",
+            "-m",
+            "models.llama.benchmark",
+            "--benchmark-type",
+            "ort-msft",
+            "--ort-model-path",
+            args.ort_msft_model_path,
+            "--model-name",
+            args.model_name,
+            "--precision",
+            args.precision,
+            "--batch-sizes",
+            args.batch_sizes,
+            "--sequence-lengths",
+            args.sequence_lengths,
+            "--device",
+            args.device,
+            "--warmup-runs",
+            str(args.warmup_runs),
+            "--num-runs",
+            str(args.num_runs),
+            "--log-folder",
+            args.log_folder,
+            "--cache-dir",
+            args.cache_dir,
+        ]
+        logger.info("Benchmark Microsoft model in ONNX Runtime")
+        results = benchmark(args, benchmark_cmd, "ort-msft")
+        all_results.extend(results)
+
+    # Benchmark convert_to_onnx model in ONNX Runtime
+    if args.ort_convert_to_onnx_model_path:
+        benchmark_cmd = [
+            "python",
+            "-m",
+            "models.llama.benchmark",
+            "--benchmark-type",
+            "ort-convert-to-onnx",
+            "--ort-model-path",
+            args.ort_convert_to_onnx_model_path,
+            "--model-name",
+            args.model_name,
+            "--precision",
+            args.precision,
+            "--batch-sizes",
+            args.batch_sizes,
+            "--sequence-lengths",
+            args.sequence_lengths,
+            "--device",
+            args.device,
+            "--warmup-runs",
+            str(args.warmup_runs),
+            "--num-runs",
+            str(args.num_runs),
+            "--log-folder",
+            args.log_folder,
+            "--cache-dir",
+            args.cache_dir,
+        ]
+        logger.info("Benchmark convert_to_onnx model in ONNX Runtime")
+        results = benchmark(args, benchmark_cmd, "onnxruntime")
+        all_results.extend(results)
+
+    csv_file = f"{args.model_size}_{args.precision}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}.csv"
+    save_results(all_results, os.path.join(args.log_folder, csv_file))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_e2e.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_e2e.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6a9dd4e2df20ba3c8b9bb3b589b33f707ff27fd
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/benchmark_e2e.py
@@ -0,0 +1,608 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+# This is an end-to-end benchmarking script for the Hugging Face LLaMA-2 model.
+#
+# Prerequisites:
+# 1) Install `huggingface-cli`:
+#
+# $ pip install huggingface_hub
+#
+# 2) Authenticate with Hugging Face's CLI:
+#
+# $ huggingface-cli login
+#
+# 3) Accept Meta's license in Hugging Face to access the models at https://huggingface.co/meta-llama/
+#
+# 4) Install the latest ONNX Runtime version
+#
+# $ pip install onnxruntime-gpu
+#
+# 5) Install flash attention v2
+#
+# $ pip install flash-attn --no-build-isolation
+#
+# 6) Install bitsandbytes
+#
+# $ pip install bitsandbytes
+
+from __future__ import annotations
+
+import argparse
+import datetime
+import gc
+import itertools
+import json
+import logging
+import os
+import textwrap
+import time
+
+import numpy as np
+import pandas as pd
+import torch
+from benchmark_helper import setup_logger
+from llama_inputs import add_io_bindings_as_tensors, get_initial_inputs_and_outputs
+from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+
+import onnxruntime as ort
+
+logger = logging.getLogger(__name__)
+
+
+def get_model(args: argparse.Namespace):
+    if args.benchmark_type in {"pt-eager", "pt-compile"}:
+        model = None
+        if args.onnx_precision == "int4" and args.device == "cuda":
+            bnb_config = BitsAndBytesConfig(
+                load_in_4bit=True,
+                bnb_4bit_use_double_quant=True,
+                bnb_4bit_quant_type="nf4",
+                bnb_4bit_compute_dtype=torch.float16,
+            )
+
+            model = AutoModelForCausalLM.from_pretrained(
+                args.hf_dir_path if args.hf_dir_path != "" else args.model_name,
+                cache_dir=args.cache_dir,
+                torch_dtype=args.torch_dtype,
+                use_auth_token=args.auth,
+                trust_remote_code=args.trust,
+                use_cache=True,
+                attn_implementation="flash_attention_2",
+                quantization_config=bnb_config,
+                max_memory={args.device_id: "80GB"},
+            )
+        else:
+            try:
+                model = AutoModelForCausalLM.from_pretrained(
+                    args.hf_dir_path if args.hf_dir_path != "" else args.model_name,
+                    cache_dir=args.cache_dir,
+                    torch_dtype=args.torch_dtype,
+                    use_auth_token=args.auth,
+                    trust_remote_code=args.trust,
+                    use_cache=True,
+                    attn_implementation=("flash_attention_2" if args.device == "cuda" else "sdpa"),
+                ).to(args.target_device)
+            except Exception as e:
+                # When flash_attention or sdpa doesn't support a model, it throws an exception.
+                # Rather than stopping a process, run as eager mode.
+                print("Try to load a model using eager mode: ", e)
+                model = AutoModelForCausalLM.from_pretrained(
+                    args.hf_dir_path if args.hf_dir_path != "" else args.model_name,
+                    cache_dir=args.cache_dir,
+                    torch_dtype=args.torch_dtype,
+                    use_auth_token=args.auth,
+                    trust_remote_code=args.trust,
+                    use_cache=True,
+                    attn_implementation="eager",
+                ).to(args.target_device)
+
+        model.eval()
+
+        if args.benchmark_type == "pt-compile":
+            model = torch.compile(model)
+
+    else:
+        sess_options = ort.SessionOptions()
+        ep = (
+            ("CUDAExecutionProvider", {"device_id": args.device_id})
+            if args.device == "cuda"
+            else "CPUExecutionProvider"
+        )
+        model = ort.InferenceSession(args.onnx_model_path, sess_options=sess_options, providers=[ep])
+
+    return model
+
+
+def run_inference(args, model, runs, inputs, outputs):
+    if args.benchmark_type == "pt-compile":
+        with torch.no_grad():
+            outputs = model(**inputs)
+
+    # Synchronize inputs
+    io_binding = None
+    if args.benchmark_type in {"pt-eager", "pt-compile"}:
+        if args.device != "cpu":
+            torch.cuda.synchronize(args.target_device)
+    else:
+        io_binding = add_io_bindings_as_tensors(model, inputs, outputs, args.use_fp16, args.use_buffer_share)
+        io_binding.synchronize_inputs()
+
+    # Run inference
+    start = time.perf_counter()
+    for _ in range(runs):
+        if args.benchmark_type in {"pt-eager", "pt-compile"}:
+            with torch.no_grad():
+                outputs = model(**inputs)
+                if args.device != "cpu":
+                    torch.cuda.synchronize(args.target_device)
+        else:
+            model.run_with_iobinding(io_binding)
+            io_binding.synchronize_outputs()
+
+    end = time.perf_counter()
+    avg = (end - start) / runs
+    return avg, outputs
+
+
+def prepare_model_for_inference(args, model, config, tokenizer, prompt_length, prompt):
+    clear_cache()
+    inputs, outputs = get_initial_inputs_and_outputs(
+        config, tokenizer, prompt_length, prompt, args.target_device, args.use_fp16, args.use_buffer_share, args.engine
+    )
+    _, outputs = run_inference(args, model, args.warmup_runs, inputs, outputs)
+    return inputs, outputs
+
+
+def clear_cache():
+    gc.collect()
+    torch.cuda.empty_cache()
+
+
+def save_results(results, filename, gen_length):
+    df = pd.DataFrame(
+        results,
+        columns=[
+            "Batch Size",
+            "Prompt Length",
+            "Prompt Processing Latency (ms)",
+            "Prompt Processing Throughput (tps)",
+            "Sampling Latency (ms)",
+            "Sampling Throughput (tps)",
+            "First Token Generated Latency (ms)",
+            "First Token Generated Throughput (tps)",
+            f"Average Latency of First {gen_length // 2} Tokens Generated (ms)",
+            f"Average Throughput of First {gen_length // 2} Tokens Generated (tps)",
+            f"Average Latency of First {gen_length} Tokens Generated (ms)",
+            f"Average Throughput of First {gen_length} Tokens Generated (tps)",
+            "Wall-Clock Latency (s)",
+            "Wall-Clock Throughput (tps)",
+        ],
+    )
+
+    df.to_csv(filename, index=False)
+    logger.info(f"Results saved in {filename}!")
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-bt",
+        "--benchmark-type",
+        type=str,
+        required=True,
+        choices=["pt-eager", "pt-compile", "ort"],
+    )
+
+    parser.add_argument(
+        "-m",
+        "--model-name",
+        type=str,
+        required=False,
+        help="Hugging Face name of model (e.g. 'meta-llama/Llama-2-7b-hf')",
+    )
+
+    parser.add_argument(
+        "-a",
+        "--auth",
+        default=False,
+        action="store_true",
+        help="Use Hugging Face authentication token to access model",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--trust",
+        default=False,
+        action="store_true",
+        help="Whether or not to allow for custom models defined on the Hugging Face Hub in their own modeling files",
+    )
+
+    parser.add_argument(
+        "-c",
+        "--cache-dir",
+        type=str,
+        default=os.path.join(".", "model_cache"),
+        help="Path to directory containing all Hugging Face files (e.g. config, tokenizer, PyTorch model). Use when loading model as `AutoModel.from_pretrained(model_name, cache_dir=cache_dir)`.",
+    )
+
+    parser.add_argument(
+        "--hf-dir-path",
+        type=str,
+        default="",
+        help="Path to directory containing all Hugging Face files (e.g. config, tokenizer, PyTorch model). Use when loading model as `AutoModel.from_pretrained(folder_path)`.",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--onnx-model-path",
+        required=False,
+        help="Path to ONNX model",
+    )
+
+    parser.add_argument(
+        "-f",
+        "--prompts-file",
+        required=True,
+        default=os.path.join(".", "models", "llama", "prompts.json"),
+        help="JSON file containing entries in the format 'prompt length: prompt' where prompt length = tokenized length of prompt",
+    )
+
+    parser.add_argument(
+        "--use_buffer_share",
+        default=False,
+        action="store_true",
+        help="Use when GroupQueryAttention (GQA) is in ONNX model",
+    )
+
+    (
+        parser.add_argument(
+            "--anomaly-filtering",
+            default=False,
+            action="store_true",
+            help="Use this flag to filter anomaly accelerator times for tokens generated. \
+              This may give more accurate latency and throughput metrics for tokens generated. \
+              Wall-clock metrics are still reported with anomaly times though.",
+        ),
+    )
+
+    parser.add_argument(
+        "-b",
+        "--batch-sizes",
+        default="1 2",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--prompt-lengths",
+        default="16 64 256 1024",
+    )
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=True,
+        type=str,
+        default="fp32",
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision for model. For ONNX models, the model's precision should be set before running this script.",
+    )
+
+    parser.add_argument(
+        "-g",
+        "--generation-length",
+        type=int,
+        default=256,
+        help="Number of new tokens to generate",
+    )
+
+    parser.add_argument(
+        "-d",
+        "--device",
+        type=str,
+        default="cuda" if torch.cuda.is_available() else "cpu",
+        choices=["cpu", "cuda"],
+    )
+
+    parser.add_argument("-id", "--device-id", type=int, default=0)
+    parser.add_argument("-w", "--warmup-runs", type=int, default=5)
+    parser.add_argument("-n", "--num-runs", type=int, default=100)
+    parser.add_argument("--seed", type=int, default=2)
+
+    args = parser.parse_args()
+
+    # Set seed properties
+    np.random.seed(args.seed)
+    torch.manual_seed(args.seed)
+
+    # Set runtime properties
+    if "ort" in args.benchmark_type:
+        setattr(args, "execution_provider", f"{args.device.upper()}ExecutionProvider")  # noqa: B010
+        if args.execution_provider == "CUDAExecutionProvider":
+            args.execution_provider = (args.execution_provider, {"device_id": args.device_id})
+
+    # Check that paths have been specified for any benchmarking with ORT
+    if args.benchmark_type == "ort":
+        assert args.onnx_model_path, "Please specify a path to `--onnx-model-path`"
+
+    args.batch_sizes = args.batch_sizes.split(" ")
+    args.prompt_lengths = args.prompt_lengths.split(" ")
+
+    # Use FP32 precision for FP32, INT8, INT4 CPU models, use FP16 precision for FP16 and INT4 GPU models
+    setattr(args, "onnx_precision", args.precision)  # noqa: B010
+    args.precision = (
+        "fp32" if args.precision in {"int8", "fp32"} or (args.precision == "int4" and args.device == "cpu") else "fp16"
+    )
+
+    target_device = f"cuda:{args.device_id}" if args.device != "cpu" else args.device
+    torch_dtype = torch.float16 if args.precision == "fp16" else torch.float32
+    engine = "ort" if args.benchmark_type == "ort" else "pt"
+    setattr(args, "target_device", target_device)  # noqa: B010
+    setattr(args, "torch_dtype", torch_dtype)  # noqa: B010
+    setattr(args, "engine", engine)  # noqa: B010
+    setattr(args, "use_fp16", args.precision == "fp16")  # noqa: B010
+
+    args.use_buffer_share = args.use_buffer_share and engine == "ort"
+
+    return args
+
+
+def main():
+    args = get_args()
+    setup_logger(False)
+    logger.info(args.__dict__)
+
+    # Get prompts and prompt sizes
+    size_to_prompt = None
+    with open(args.prompts_file) as f:
+        size_to_prompt = json.load(f, object_hook=lambda d: {int(k): v for k, v in d.items()})
+
+    # Get config, tokenizer, and model
+    config = AutoConfig.from_pretrained(
+        args.hf_dir_path if args.hf_dir_path != "" else args.model_name,
+        cache_dir=args.cache_dir,
+        use_auth_token=args.auth,
+        trust_remote_code=args.trust,
+    )
+    tokenizer = AutoTokenizer.from_pretrained(
+        args.hf_dir_path if args.hf_dir_path != "" else args.model_name,
+        cache_dir=args.cache_dir,
+        use_auth_token=args.auth,
+        trust_remote_code=args.trust,
+    )
+    model = get_model(args)
+
+    all_csv_metrics = []
+    for batch_size, prompt_length in itertools.product(args.batch_sizes, args.prompt_lengths):
+        batch_size, prompt_length = int(batch_size), int(prompt_length)  # noqa: PLW2901
+        logger.info(f"Running batch size = {batch_size}, prompt length = {prompt_length}")
+        clear_cache()
+        max_length = prompt_length + args.generation_length
+
+        if prompt_length not in size_to_prompt:
+            raise NotImplementedError(
+                textwrap.dedent(
+                    f"""
+                                A prompt of size {prompt_length} was not found in '{args.prompts_file}'. There are a couple of solutions to fix this.
+                                1) You can change one of the keys in '{args.prompts_file}' to be {prompt_length}.
+                                    If {prompt_length} < actual prompt's length, the benchmark E2E tool will repeat the first word in the prompt until {prompt_length} = actual prompt's length.
+                                    If {prompt_length} > actual prompt's length, the benchmark E2E tool will automatically trim the actual prompt's length so that {prompt_length} = actual prompt's length.
+                                2) You can add a new key-value entry in '{args.prompts_file}' of the form '{prompt_length}': 'your prompt goes here'.
+                """
+                )
+            )
+        prompt = [size_to_prompt[prompt_length]] * batch_size
+        csv_metrics = [batch_size, prompt_length]
+
+        try:
+            # Measure prompt processing
+            logger.info("Measuring prompt processing...")
+            inputs, outputs = prepare_model_for_inference(args, model, config, tokenizer, prompt_length, prompt)
+            accelerator_prompt_latency_s, outputs = run_inference(args, model, args.num_runs, inputs, outputs)
+
+            # Calculate prompt metrics
+            accelerator_prompt_latency_ms = accelerator_prompt_latency_s * 1000
+            accelerator_prompt_thrpt = batch_size * (prompt_length / accelerator_prompt_latency_s)
+            logger.info(f"Average Latency of Prompt Processing: {accelerator_prompt_latency_ms} ms")
+            logger.info(
+                f"Average Throughput of Prompt Processing: {batch_size * (prompt_length / accelerator_prompt_latency_s)} tps"
+            )
+            csv_metrics.extend([accelerator_prompt_latency_ms, accelerator_prompt_thrpt])
+
+            # Measure token generation
+            logger.info("Measuring token generation...")
+            clear_cache()
+            inputs, outputs = prepare_model_for_inference(args, model, config, tokenizer, prompt_length, prompt)
+
+            all_token_ids = inputs["input_ids"].clone()
+            current_length = all_token_ids.shape[-1]
+            num_heads = config.num_key_value_heads
+            head_size = (
+                config.head_dim if hasattr(config, "head_dim") else config.hidden_size // config.num_attention_heads
+            )
+
+            has_eos = torch.zeros(batch_size, device=args.target_device, dtype=torch.bool)
+
+            # 0th entry will have prompt accelerator time, 1st entry onwards will have token generation accelerator time
+            accelerator_times = []
+            sampling_times = []  # cost to sample after each model run
+
+            wall_clock_start_time = time.perf_counter()
+            while current_length <= max_length:
+                # Run inference
+                accelerator_time_latency_s, outputs = run_inference(args, model, 1, inputs, outputs)
+                accelerator_times.append(accelerator_time_latency_s)
+
+                # Sample with argmax (greedy search)
+                sampling_start_time = time.perf_counter()
+                if outputs["logits"].shape[1] > 1:
+                    prompt_end_indices = inputs["attention_mask"].sum(1) - 1
+                    idxs = (
+                        prompt_end_indices.unsqueeze(dim=1)
+                        .repeat(1, config.vocab_size)
+                        .view(batch_size, 1, config.vocab_size)
+                    )
+                    next_token_logits = torch.gather(outputs["logits"], 1, idxs).squeeze()
+                else:
+                    next_token_logits = outputs["logits"][:, -1, :]
+                next_tokens = torch.argmax(next_token_logits, dim=-1)
+
+                # Check if we previously reached EOS token id or if generated token id is EOS token id
+                has_eos = has_eos | next_tokens == tokenizer.eos_token_id
+
+                # Determine which new tokens to add to list of all token ids
+                # Add EOS token ids for batch entries that ended early (ragged batching scenario where some batch entries ended early and some haven't)
+                tokens_to_add = next_tokens.masked_fill(has_eos, tokenizer.eos_token_id).reshape([batch_size, 1])
+                sampling_end_time = time.perf_counter()
+                sampling_times.append(sampling_end_time - sampling_start_time)
+
+                all_token_ids = torch.cat([all_token_ids, tokens_to_add], dim=-1)
+                current_length += 1
+
+                # Update inputs for next inference run
+                inputs["input_ids"] = tokens_to_add
+                inputs["attention_mask"] = torch.cat(
+                    [inputs["attention_mask"], (~has_eos).to(torch.int64).reshape(batch_size, 1)], 1
+                )
+                if "position_ids" in inputs:
+                    inputs["position_ids"] = torch.max(inputs["position_ids"], dim=1)[0].reshape(batch_size, 1) + 1
+
+                # Set logits to zeros for next inference run and re-use memory buffer
+                if outputs["logits"].shape[1] != 1:
+                    outputs["logits"] = outputs["logits"][:, :1, :].contiguous()
+                outputs["logits"].zero_()
+
+                # Update KV caches for next inference run
+                if args.engine == "pt":
+                    # Update KV caches for PyTorch
+                    inputs["past_key_values"] = outputs["past_key_values"]
+                elif not args.use_buffer_share:
+                    # Update KV caches for ONNX Runtime if buffer sharing is not used
+                    for i in range(config.num_hidden_layers):
+                        inputs[f"past_key_values.{i}.key"] = outputs[f"present.{i}.key"]
+                        inputs[f"past_key_values.{i}.value"] = outputs[f"present.{i}.value"]
+
+                    new_sequence_length = inputs["attention_mask"].shape[1]
+                    for i in range(config.num_hidden_layers):
+                        present_key = torch.zeros(
+                            batch_size,
+                            num_heads,
+                            new_sequence_length,
+                            head_size,
+                            device=args.target_device,
+                            dtype=args.torch_dtype,
+                        )
+                        present_value = torch.zeros(
+                            batch_size,
+                            num_heads,
+                            new_sequence_length,
+                            head_size,
+                            device=args.target_device,
+                            dtype=args.torch_dtype,
+                        )
+                        outputs.update(
+                            {
+                                f"present.{i}.key": present_key.contiguous(),
+                                f"present.{i}.value": present_value.contiguous(),
+                            }
+                        )
+
+            wall_clock_end_time = time.perf_counter()
+
+            # Filter out any anomaly accelerator times (e.g. for `torch.compile`)
+            accelerator_times.pop(0)  # Remove prompt processing time
+            if args.anomaly_filtering:
+                anomaly_threshold_factor = 10
+                min_time_s = min(accelerator_times)
+                orig_size = len(accelerator_times)
+                accelerator_times = list(
+                    filter(lambda acc_time: acc_time < anomaly_threshold_factor * min_time_s, accelerator_times)
+                )
+                new_size = len(accelerator_times)
+                logger.info(
+                    f"Filtered out {orig_size - new_size} anomaly accelerator times that are {anomaly_threshold_factor}x greater than {min_time_s * 1000} ms..."
+                )
+
+            #######################################################
+            # Calculate sampling and first token generated metrics
+            #######################################################
+
+            # Calculate sampling metrics
+            avg_sampling_latency_s = sum(sampling_times) / len(sampling_times)
+            avg_sampling_latency_ms = avg_sampling_latency_s * 1000
+            avg_sampling_thrpt = batch_size * (1 / avg_sampling_latency_s)
+            logger.info(f"Average Latency of Sampling: {avg_sampling_latency_ms} ms")
+            logger.info(f"Average Throughput of Sampling: {avg_sampling_thrpt} tps")
+
+            # Calculate first token generated metrics
+            first_token_latency_s = accelerator_times[0]
+            first_token_latency_ms = first_token_latency_s * 1000
+            first_token_thrpt = batch_size * (1 / first_token_latency_s)
+            logger.info(f"Latency of First Token Generated: {first_token_latency_ms} ms")
+            logger.info(f"Throughput of First Token Generated: {first_token_thrpt} tps")
+
+            ####################################################
+            # Calculate first `halfway` token generated metrics
+            ####################################################
+
+            halfway = args.generation_length // 2
+            halfway_token_latency_s = sum(accelerator_times[:halfway]) / len(accelerator_times[:halfway])
+            halfway_token_latency_ms = halfway_token_latency_s * 1000
+            halfway_token_thrpt = batch_size * (1 / halfway_token_latency_s)
+            logger.info(f"Average Latency of First {halfway} Tokens Generated: {halfway_token_latency_ms} ms")
+            logger.info(f"Average Throughput of First {halfway} Tokens Generated: {halfway_token_thrpt} tps")
+
+            #########################################
+            # Calculate all tokens generated metrics
+            #########################################
+
+            all_token_latency_s = sum(accelerator_times) / len(accelerator_times)
+            all_token_latency_ms = all_token_latency_s * 1000
+            all_token_thrpt = batch_size * (1 / all_token_latency_s)
+            logger.info(
+                f"Average Latency of First {args.generation_length} Tokens Generated: {all_token_latency_ms} ms"
+            )
+            logger.info(f"Average Throughput of First {args.generation_length} Tokens Generated: {all_token_thrpt} tps")
+
+            ###############################
+            # Calculate wall clock metrics
+            ###############################
+
+            wall_clock_latency_s = wall_clock_end_time - wall_clock_start_time
+            wall_clock_thrpt = batch_size * ((prompt_length + args.generation_length) / wall_clock_latency_s)
+            logger.info(f"Wall-Clock Latency: {wall_clock_latency_s} s")
+            logger.info(
+                f"Wall-Clock Throughput: {batch_size * ((prompt_length + args.generation_length) / wall_clock_latency_s)} tps"
+            )
+
+            # Add metrics to CSV
+            logger.info("Adding results to CSV")
+            csv_metrics.extend(
+                [
+                    avg_sampling_latency_ms,
+                    avg_sampling_thrpt,
+                    first_token_latency_ms,
+                    first_token_thrpt,
+                    halfway_token_latency_ms,
+                    halfway_token_thrpt,
+                    all_token_latency_ms,
+                    all_token_thrpt,
+                    wall_clock_latency_s,
+                    wall_clock_thrpt,
+                ]
+            )
+            all_csv_metrics.append(csv_metrics)
+
+        except Exception as e:
+            logger.info(f"Could not benchmark at batch size = {batch_size}, prompt length = {prompt_length} - {e}")
+
+    filename = f"benchmark_{args.engine}_e2e_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}.csv"
+    save_results(all_csv_metrics, filename, args.generation_length)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..44ce403bb562cd87d2fa1baa7a5d3a18d08a33d3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/convert_to_onnx.py
@@ -0,0 +1,1066 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import argparse
+import logging
+import os
+import shutil
+import subprocess
+import sys
+import tempfile
+import warnings
+from itertools import chain
+
+import onnx
+import torch
+from benchmark_helper import Precision, prepare_environment, setup_logger
+from convert_generation import replace_mha_with_gqa
+from dist_settings import barrier, get_rank, get_size, init_dist
+from llama_inputs import get_merged_sample_with_past_kv_inputs, get_sample_inputs, get_sample_with_past_kv_inputs
+from llama_parity import main as parity_check
+from llama_torch import setup_torch_model
+
+# to patch transformers before exporting for transformers >= 4.45
+from models.torch_export_patches import bypass_export_some_errors
+from models.torch_export_patches.patch_inputs import convert_dynamic_axes_into_dynamic_shapes
+from onnx_model import OnnxModel
+from optimizer import optimize_model
+from packaging import version
+from transformers import AutoConfig, AutoModelForCausalLM
+
+from onnxruntime import __version__ as ort_version
+from onnxruntime import quantization as ort_quantization
+
+if version.parse(ort_version) < version.parse("1.22.0"):
+    from onnxruntime.quantization.matmul_4bits_quantizer import MatMul4BitsQuantizer as MatMulNBitsQuantizer
+else:
+    from onnxruntime.quantization.matmul_nbits_quantizer import MatMulNBitsQuantizer
+
+torch_export_onnx_opset_version = 14
+logger = logging.getLogger("")
+init_dist()
+
+
+def get_model_dynamic_axes(input_names: list[str], output_names: list[str]):
+    dynamic_axes = {}
+    for name in input_names + output_names:
+        if name in input_names:
+            # shape is (batch_size, sequence_length)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif name == "logits":
+            # shape is (batch_size, sequence_length, vocab_size)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif "present" in name:
+            # shape is (batch_size, num_heads, sequence_length, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "sequence_length"}
+        else:
+            raise Exception("Unknown input or output name found")
+    return dynamic_axes
+
+
+def get_model_with_past_kv_dynamic_axes(input_names: list[str], output_names: list[str]):
+    dynamic_axes = {}
+    for name in input_names + output_names:
+        if name in {"input_ids", "position_ids"}:
+            # shape is (batch_size, 1)
+            dynamic_axes[name] = {0: "batch_size"}
+        elif name == "attention_mask":
+            # shape is (batch_size, past_sequence_length + 1)
+            dynamic_axes[name] = {0: "batch_size", 1: "past_sequence_length + 1"}
+        elif "past" in name:
+            # shape is (batch_size, num_heads, past_sequence_length, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "past_sequence_length"}
+        elif name == "logits":
+            # shape is (batch_size, 1, vocab_size)
+            dynamic_axes[name] = {0: "batch_size"}
+        elif "present" in name:
+            # shape is (batch_size, num_heads, past_sequence_length + 1, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "past_sequence_length + 1"}
+        else:
+            raise Exception("Unknown input or output name found")
+    return dynamic_axes
+
+
+def get_merged_model_dynamic_axes(input_names: list[str], output_names: list[str]):
+    dynamic_axes = {}
+    for name in input_names + output_names:
+        if name in {"input_ids", "position_ids"}:
+            # shape is (batch_size, sequence_length)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif name == "attention_mask":
+            # shape is (batch_size, past_sequence_length + sequence_length) = (batch_size, total_sequence_length)
+            # for prompt generation, past_sequence_length = 0
+            # for token generation, sequence_length = 1
+            dynamic_axes[name] = {0: "batch_size", 1: "total_sequence_length"}
+        elif "past" in name:
+            # shape is (batch_size, num_heads, past_sequence_length, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "past_sequence_length"}
+        elif name == "logits":
+            # shape is (batch_size, sequence_length, vocab_size)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif "present" in name:
+            # shape is (batch_size, num_heads, past_sequence_length + sequence_length, head_size) = (batch_size, num_heads, total_sequence_length, head_size)
+            # for prompt generation, past_sequence_length = 0
+            # for token generation, sequence_length = 1
+            dynamic_axes[name] = {0: "batch_size", 2: "total_sequence_length"}
+        else:
+            raise Exception("Unknown input or output name found")
+    return dynamic_axes
+
+
+def save_onnx_model(onnx_model: onnx.ModelProto, output_path: str, data_path: str):
+    onnx.save(
+        onnx_model,
+        output_path,
+        save_as_external_data=True,
+        all_tensors_to_one_file=True,
+        location=data_path,
+        size_threshold=1024,
+        convert_attribute=False,
+    )
+
+
+def run_dynamo_export(
+    args: argparse.Namespace, l_config: AutoConfig, llama: AutoModelForCausalLM, rank: int = 0, world_size: int = 1
+):
+    from torch._dynamo import config  # noqa: PLC0415
+
+    config.capture_scalar_outputs = True
+
+    # Dummy values for export
+    batch_size, sequence_length, past_sequence_length = 2, 8, 3
+    device = llama.device if args.model_name == "Llama-2-70b-hf" else torch.device("cpu")
+
+    temp_name = args.model_name.lower().replace("-", "").replace("_", "")
+    max_sequence_length = 16384 if "codellama" in temp_name else 4096 if "llama2" in temp_name else 2048
+
+    # Export decoder_with_past_model.onnx
+    input_ids, attn_mask, pos_ids, past_kv = get_merged_sample_with_past_kv_inputs(
+        l_config,
+        device,
+        batch_size,
+        sequence_length,
+        past_sequence_length,
+        max_seq_len=max_sequence_length,
+        use_fp16=False,
+        world_size=world_size,
+    )
+    temp_dir = tempfile.TemporaryDirectory()
+    temp_path = os.path.join(temp_dir.name, "temp.onnx")
+
+    input_names = ["input_ids", "attention_mask", "position_ids"]
+    output_names = [
+        "logits",
+        *list(
+            chain.from_iterable((f"present.{i}.key", f"present.{i}.value") for i in range(l_config.num_hidden_layers))
+        ),
+    ]
+    dynamic_axes = get_model_dynamic_axes(input_names, output_names)
+
+    model_args = (input_ids, attn_mask, pos_ids, past_kv)
+    model_args, model_kwargs, dynamic_shapes = convert_dynamic_axes_into_dynamic_shapes(
+        llama, args=model_args, dynamic_axes=dynamic_axes, prefix_mapping={"present": "past_key_values"}
+    )
+
+    with bypass_export_some_errors(patch_transformers=True):
+        torch.onnx.export(
+            llama,
+            (),
+            temp_path,
+            kwargs=model_kwargs,
+            dynamic_shapes=dynamic_shapes,
+            dynamo=True,
+            verbose=args.verbose,
+            optimize=True,
+        )
+
+    # Check decoder_with_past_model.onnx and save all external data to one file
+    onnx.checker.check_model(temp_path)
+    onnx.shape_inference.infer_shapes_path(temp_path)
+
+    output_path = os.path.join(args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32.onnx")
+    onnx_model = onnx.load_model(temp_path, load_external_data=True)
+    save_onnx_model(onnx_model, output_path, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32.onnx.data")
+    del onnx_model
+    temp_dir.cleanup()
+
+    logger.info(f"The {args.model_name} ONNX model has been successfully created with the Dynamo exporter!")
+
+
+def _prepare_dir(dir_path):
+    if not os.path.exists(dir_path):
+        os.makedirs(dir_path)
+
+
+def run_torchscript_separate_export(
+    args: argparse.Namespace, l_config: AutoConfig, llama: AutoModelForCausalLM, rank: int = 0, world_size: int = 1
+):
+    # Dummy values for export
+    batch_size, sequence_length = 2, 8
+
+    # set device used to export model
+    # for llama-2-70b we will use current gpus to speed up export process
+    # for other models, we will use CPU to make sure we have enough memory to do export
+    device = llama.device if args.model_name == "Llama-2-70b-hf" else torch.device("cpu")
+
+    # Export decoder_model.onnx
+    decoder_inputs = get_sample_inputs(l_config, device, batch_size, sequence_length)
+
+    input_names = ["input_ids", "attention_mask", "position_ids"]
+    output_names = [
+        "logits",
+        *list(
+            chain.from_iterable((f"present.{i}.key", f"present.{i}.value") for i in range(l_config.num_hidden_layers))
+        ),
+    ]
+    dynamic_axes = get_model_dynamic_axes(input_names, output_names)
+
+    # Avoid using system temp dir to avoid overflood on hard disk as 70b model is very large.
+    # Use temp folder per rank to avoid race condition here.
+    temp_dir = f"./temp_{rank}"
+    _prepare_dir(temp_dir)
+    temp_path = os.path.join(temp_dir, "temp.onnx")
+    torch.onnx.export(
+        llama,
+        args=decoder_inputs,
+        f=temp_path,
+        export_params=True,
+        input_names=input_names,
+        output_names=output_names,
+        dynamic_axes=dynamic_axes,
+        opset_version=torch_export_onnx_opset_version,
+        do_constant_folding=True,
+        verbose=args.verbose,
+        dynamo=False,
+    )
+
+    # Check decoder_model.onnx and save all external data to one file
+    onnx.checker.check_model(temp_path)
+    onnx.shape_inference.infer_shapes_path(temp_path)
+
+    output_path = os.path.join(args.output, f"rank_{rank}_{args.model_name}_decoder_model_fp32.onnx")
+    onnx_model = onnx.load_model(temp_path, load_external_data=True)
+    save_onnx_model(
+        onnx_model,
+        output_path,
+        f"rank_{rank}_{args.model_name}_decoder_model_fp32.onnx.data",
+    )
+    del onnx_model
+    shutil.rmtree(temp_dir)
+
+    # Export decoder_with_past_model.onnx
+    decoder_with_past_inputs = get_sample_with_past_kv_inputs(
+        l_config,
+        device,
+        batch_size,
+        sequence_length,
+        use_fp16=False,
+        world_size=world_size,
+    )
+    input_names = [
+        "input_ids",
+        "attention_mask",
+        "position_ids",
+        *list(
+            chain.from_iterable(
+                (f"past_key_values.{i}.key", f"past_key_values.{i}.value") for i in range(l_config.num_hidden_layers)
+            )
+        ),
+    ]
+    output_names = [
+        "logits",
+        *list(
+            chain.from_iterable((f"present.{i}.key", f"present.{i}.value") for i in range(l_config.num_hidden_layers))
+        ),
+    ]
+    dynamic_axes = get_model_with_past_kv_dynamic_axes(input_names, output_names)
+
+    # Avoid using system temp dir to avoid overflood on hard disk as 70b model is very large.
+    # Use temp folder per rank to avoid race condition here.
+    temp_dir = f"./temp_past_{rank}"
+    _prepare_dir(temp_dir)
+    temp_path = os.path.join(temp_dir, "temp.onnx")
+    torch.onnx.export(
+        llama,
+        args=decoder_with_past_inputs,
+        f=temp_path,
+        export_params=True,
+        input_names=input_names,
+        output_names=output_names,
+        dynamic_axes=dynamic_axes,
+        opset_version=torch_export_onnx_opset_version,
+        do_constant_folding=True,
+        verbose=args.verbose,
+        dynamo=False,
+    )
+
+    # Check decoder_with_past_model.onnx and save all external data to one file
+    onnx.checker.check_model(temp_path)
+    onnx.shape_inference.infer_shapes_path(temp_path)
+
+    output_path = os.path.join(args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32.onnx")
+    onnx_model = onnx.load_model(temp_path, load_external_data=True)
+    save_onnx_model(
+        onnx_model,
+        output_path,
+        f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32.onnx.data",
+    )
+    del onnx_model
+    shutil.rmtree(temp_dir)
+
+    logger.info(
+        f"The {args.model_name} separate ONNX model has been successfully created with the TorchScript exporter!"
+    )
+
+
+def run_torchscript_merged_export(
+    args: argparse.Namespace, l_config: AutoConfig, llama: AutoModelForCausalLM, rank: int = 0, world_size: int = 1
+):
+    # Dummy values for export
+    batch_size, sequence_length, past_sequence_length = 2, 8, 0
+
+    # set device used to export model
+    # for llama-2-70b we will use current gpus to speed up export process
+    # for other models, we will use CPU to make sure we have enough memory to do export
+    device = llama.device if args.model_name == "Llama-2-70b-hf" else torch.device("cpu")
+
+    temp_name = args.model_name.lower().replace("-", "").replace("_", "")
+    max_sequence_length = 16384 if "codellama" in temp_name else 4096 if "llama2" in temp_name else 2048
+
+    # Export decoder_merged_model.onnx
+    decoder_merged_inputs = get_merged_sample_with_past_kv_inputs(
+        l_config,
+        device,
+        batch_size,
+        sequence_length,
+        past_sequence_length,
+        max_seq_len=max_sequence_length,
+        use_fp16=False,
+        world_size=world_size,
+    )
+    input_names = [
+        "input_ids",
+        "attention_mask",
+        "position_ids",
+        *list(
+            chain.from_iterable(
+                (f"past_key_values.{i}.key", f"past_key_values.{i}.value") for i in range(l_config.num_hidden_layers)
+            )
+        ),
+    ]
+    output_names = [
+        "logits",
+        *list(
+            chain.from_iterable((f"present.{i}.key", f"present.{i}.value") for i in range(l_config.num_hidden_layers))
+        ),
+    ]
+    dynamic_axes = get_merged_model_dynamic_axes(input_names, output_names)
+
+    # Avoid using system temp dir to avoid overflood on hard disk as 70b model is very large.
+    # Use temp folder per rank to avoid race condition here.
+    temp_dir = f"./temp_{rank}"
+    _prepare_dir(temp_dir)
+    temp_path = os.path.join(temp_dir, "temp.onnx")
+
+    torch.onnx.export(
+        llama,
+        args=decoder_merged_inputs,
+        f=temp_path,
+        export_params=True,
+        input_names=input_names,
+        output_names=output_names,
+        dynamic_axes=dynamic_axes,
+        opset_version=torch_export_onnx_opset_version,
+        do_constant_folding=True,
+        verbose=args.verbose,
+        dynamo=False,
+    )
+
+    # Check decoder_merged_model.onnx and save all external data to one file
+    onnx.checker.check_model(temp_path)
+    onnx.shape_inference.infer_shapes_path(temp_path)
+
+    output_path = os.path.join(args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_fp32.onnx")
+    onnx_model = onnx.load_model(temp_path, load_external_data=True)
+    save_onnx_model(
+        onnx_model,
+        output_path,
+        f"rank_{rank}_{args.model_name}_decoder_merged_model_fp32.onnx.data",
+    )
+    del onnx_model
+    shutil.rmtree(temp_dir)
+
+    logger.info(f"The {args.model_name} merged ONNX model has been successfully created with the TorchScript exporter!")
+
+
+# Optimize the model as FP32
+def optimize_export(
+    args: argparse.Namespace,
+    config: AutoConfig,
+    input_path: str,
+    output_path: str,
+    remove_model: bool = True,
+    world_size: int = 1,
+    window_size: int = -1,
+):
+    from fusion_options import FusionOptions  # noqa: PLC0415
+
+    optimization_options = FusionOptions("gpt2")
+
+    model_opt = optimize_model(
+        input_path,
+        model_type="gpt2",
+        num_heads=config.num_attention_heads,
+        hidden_size=config.hidden_size,
+        opt_level=0,
+        optimization_options=optimization_options,
+        only_onnxruntime=False,
+    )
+    if args.use_gqa:
+        model_opt = use_group_query_attention(config, model_opt, world_size, window_size)
+    model_opt.save_model_to_file(output_path, use_external_data_format=True)
+
+    # Run symbolic shape inference on optimized model to avoid shape errors during runtime
+    # Ex: Before attention fusion, RotaryEmbedding assumes a 4D input and produces a 4D output.
+    # After attention fusion, RotaryEmbedding expects a 3D input and produces a 3D output.
+    wheel_cmd = [sys.executable, "-m", "onnxruntime.tools.symbolic_shape_infer"]
+    source_cmd = [sys.executable, "../symbolic_shape_infer.py"]
+    symbolic_shape_infer_args = [
+        "--input",
+        output_path,
+        "--output",
+        output_path,
+        "--auto_merge",
+        "--save_as_external_data",
+        "--all_tensors_to_one_file",
+        "--external_data_location",
+        os.path.basename(output_path) + ".data",
+    ]
+
+    file_path = os.path.dirname(__file__)
+    if os.path.exists(os.path.join(file_path, "../../../tools/symbolic_shape_infer.py")):
+        main_cmd = wheel_cmd
+    else:
+        main_cmd = source_cmd
+    subprocess.run(main_cmd + symbolic_shape_infer_args)  # noqa: PLW1510
+
+    logger.info(f"The ONNX model at {input_path} has been successfully optimized and saved at {output_path}!")
+    if remove_model:
+        remove_existing_model(input_path)
+
+
+def convert_to_float16(args: argparse.Namespace, old_paths: list[str], rank: int = 0):
+    decoder_model_fp16_path = os.path.join(args.output, f"rank_{rank}_{args.model_name}_decoder_model_fp16.onnx")
+    decoder_with_past_model_fp16_path = os.path.join(
+        args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp16.onnx"
+    )
+    decoder_merged_model_fp16_path = os.path.join(
+        args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_fp16.onnx"
+    )
+    new_paths = [decoder_model_fp16_path, decoder_with_past_model_fp16_path, decoder_merged_model_fp16_path]
+
+    logger.info("Converting to float16...")
+    for fp32_path, fp16_path in zip(old_paths, new_paths, strict=False):
+        if os.path.exists(fp32_path):
+            model = OnnxModel(onnx.load_model(fp32_path, load_external_data=True))
+            model.convert_float_to_float16(keep_io_types=False)
+            model.save_model_to_file(fp16_path, use_external_data_format=True)
+            del model
+            logger.info(f"The ONNX model at {fp32_path} has been converted to float16 and saved at {fp16_path}!")
+            remove_existing_model(fp32_path)
+
+    logger.info(f"The {args.model_name} ONNX model has been successfully converted to float16!")
+    return new_paths
+
+
+def use_group_query_attention(config: AutoConfig, model_opt: OnnxModel, world_size: int = 1, window_size: int = -1):
+    # Replace MultiHeadAttention with GroupQueryAttention
+    model_opt = replace_mha_with_gqa(model_opt, "attention_mask", config.num_key_value_heads, world_size, window_size)
+    model_opt.prune_graph()
+    model_opt.update_graph(allow_remove_graph_inputs=True)
+    return model_opt
+
+
+def smooth_quant(
+    args: argparse.Namespace,
+    decoder_model_fp32_path: str,
+    decoder_with_past_model_fp32_path: str,
+    decoder_model_int8_path: str,
+    decoder_with_past_model_int8_path: str,
+):
+    from neural_compressor import PostTrainingQuantConfig, set_workspace  # noqa: PLC0415
+    from neural_compressor import quantization as intel_quantization  # noqa: PLC0415
+    from onnx.external_data_helper import load_external_data_for_model  # noqa: PLC0415
+    from quant_kv_dataloader import QuantKVDataLoader  # noqa: PLC0415
+
+    set_workspace(args.nc_workspace)
+    quantization_config = PostTrainingQuantConfig(
+        calibration_sampling_size=[args.calibration_sampling_size],
+        recipes={
+            "optypes_to_exclude_output_quant": ["MatMul"],
+            "smooth_quant": True,
+            "smooth_quant_args": {"alpha": args.smooth_quant_alpha},
+        },
+        op_type_dict={
+            "^((?!(MatMul|Gather|Conv)).)*$": {
+                "weight": {"dtype": ["fp32"]},
+                "activation": {"dtype": ["fp32"]},
+            }
+        },
+    )
+
+    # Convert decoder_model.onnx to INT8
+    decoder_model_int8 = intel_quantization.fit(
+        decoder_model_fp32_path,
+        quantization_config,
+        calib_dataloader=QuantKVDataLoader(args),
+    )
+    load_external_data_for_model(
+        decoder_model_int8._model,
+        os.path.split(decoder_model_int8._model_path)[0],
+    )
+    save_onnx_model(
+        decoder_model_int8._model,
+        decoder_model_int8_path,
+        f"{args.model_name}_decoder_model_int8.onnx.data",
+    )
+    del decoder_model_int8
+    logger.info(
+        f"The ONNX model at {decoder_model_fp32_path} has been quantized to int8 and saved at {decoder_model_int8_path}!"
+    )
+    remove_existing_model(decoder_model_fp32_path)
+
+    # Convert decoder_with_past_model.onnx to INT8
+    decoder_with_past_model_int8 = intel_quantization.fit(
+        decoder_with_past_model_fp32_path,
+        quantization_config,
+        calib_dataloader=QuantKVDataLoader(args, onnx_model_path=decoder_model_fp32_path),
+    )
+    load_external_data_for_model(
+        decoder_with_past_model_int8._model,
+        os.path.split(decoder_with_past_model_int8._model_path)[0],
+    )
+    save_onnx_model(
+        decoder_with_past_model_int8._model,
+        decoder_with_past_model_int8_path,
+        f"{args.model_name}_decoder_with_past_model_int8.onnx.data",
+    )
+    del decoder_with_past_model_int8
+    logger.info(
+        f"The ONNX model at {decoder_with_past_model_fp32_path} has been quantized to int8 and saved at {decoder_with_past_model_int8_path}!"
+    )
+    remove_existing_model(decoder_with_past_model_fp32_path)
+
+    logger.info(f"The {args.model_name} ONNX model has been successfully quantized to int8!")
+
+    logger.warning(f"Removing {args.nc_workspace}")
+    shutil.rmtree(args.nc_workspace)
+
+
+def remove_existing_model(model_path: str):
+    # Remove ONNX model and its external data
+    data_path = os.path.join(model_path + ".data")
+    os.remove(model_path)
+    os.remove(data_path)
+    logger.warning(f"Removed {model_path} and {data_path}")
+
+
+def remove_existing_files(output_path: str):
+    for filename in os.listdir(output_path):
+        filepath = os.path.join(output_path, filename)
+        if ".onnx" in filename or ".onnx.data" in filename:
+            os.remove(filepath)
+            logger.warning(f"Removed {filepath}")
+
+
+def optimize_optimum(config: AutoConfig, args: argparse.Namespace):
+    tmp_file = os.path.join(args.output, args.model_name + ".tmp.onnx")
+    output_file = os.path.join(args.output, args.model_name + ".onnx")
+    window_size = -1 if not hasattr(config, "sliding_window") else config.sliding_window
+    optimize_export(args, config, args.input, tmp_file, remove_model=False, window_size=window_size)
+    logger.info(f"Model successfully optimized to {tmp_file}")
+    opt_model = OnnxModel(onnx.load_model(tmp_file, load_external_data=True))
+    if args.precision == Precision.FLOAT16:
+        opt_model.convert_float_to_float16(keep_io_types=False)
+        logger.info("Model successfully fused and quantized to FP16!")
+    opt_model.save_model_to_file(output_file, use_external_data_format=True)
+    logger.info(f"Output model successfully saved to {output_file}")
+    logger.info(f"Removing {tmp_file}")
+    remove_existing_model(tmp_file)
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name",
+        required=True,
+        help="Model name in Hugging Face",
+    )
+
+    parser.add_argument(
+        "-i",
+        "--input",
+        required=False,
+        default=os.path.join("."),
+        help="Directory path to PyTorch model and associated files if saved on disk, or ONNX model file location if optimize_optimum is passed.",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--output",
+        required=False,
+        default=os.path.join(".", "llama_onnx_models"),
+        help="Directory path to save exported model files in",
+    )
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=False,
+        type=Precision,
+        default=Precision.FLOAT32,
+        choices=[Precision.FLOAT32, Precision.FLOAT16, Precision.INT8, Precision.INT4],
+        help="Precision to export model in",
+    )
+
+    parser.add_argument(
+        "-e",
+        "--execution_provider",
+        required=False,
+        default="cpu",
+        choices=["cpu", "cuda"],
+        help="Execution provider to verify parity with",
+    )
+
+    parser.add_argument(
+        "-r",
+        "--reexport",
+        required=False,
+        action="store_true",
+        help="Re-export models and overwrite existing models in output folder",
+    )
+    parser.set_defaults(reexport=False)
+
+    parser.add_argument(
+        "--use_gqa",
+        required=False,
+        action="store_true",
+        help="Use GroupQueryAttention instead of MultiHeadAttention",
+    )
+    parser.set_defaults(use_gqa=False)
+
+    parser.add_argument(
+        "--no_merged",
+        required=False,
+        action="store_true",
+        help="Export models into 2 ONNX files instead of 1. Deprecated in favor of exporting into 1 ONNX file.",
+    )
+    parser.set_defaults(no_merged=False)
+
+    parser.add_argument(
+        "-q",
+        "--quantization_method",
+        default="",
+        choices=["blockwise", "smooth_quant", "quantize_dynamic"],
+        help="Run a specific quantization algorithm (blockwise for int4, smooth_quant for int8, quantize_dynamic for int8). Blockwise is recommended. Need to install extra packages in `requirements-quant.txt` for SmoothQuant.",
+    )
+
+    blockwise_group = parser.add_argument_group("blockwise (4-bit quantization)")
+
+    parser.add_argument("--bits", default=4, type=int, help="the target bits to represent weight")
+
+    blockwise_group.add_argument(
+        "--block_size",
+        required=False,
+        default=32,
+        type=int,
+        help="Block size to quantize with. See https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/python/tools/quantization/matmul_nbits_quantizer.py for details.",
+    )
+
+    blockwise_group.add_argument(
+        "--int4_accuracy_level",
+        required=False,
+        type=int,
+        help="Accuracy level of the 4-bit quantized MatMul computation. "
+        "Refer to the MatMulNBits contrib op's 'accuracy_level' attribute for details "
+        "(https://github.com/microsoft/onnxruntime/blob/main/docs/ContribOperators.md#commicrosoftmatmulnbits).",
+    )
+
+    smooth_quant_group = parser.add_argument_group("smooth_quant (8-bit quantization)")
+
+    smooth_quant_group.add_argument(
+        "--smooth_quant_alpha",
+        required=False,
+        default=0.8,
+        type=float,
+        help="Strength to control migration difficulty from activation to weights. Default is 0.8 to match value \
+              used in original paper for LLaMA. Paper recommends using values in [0.4, 0.6] range. \
+              Link to paper: https://arxiv.org/pdf/2211.10438.pdf",
+    )
+
+    smooth_quant_group.add_argument(
+        "--smooth_quant_dataset",
+        required=False,
+        default="NeelNanda/pile-10k",
+        help="Path to dataset for calibration during quantization",
+    )
+
+    smooth_quant_group.add_argument(
+        "--pad_max",
+        required=False,
+        default=196,
+        type=int,
+        help="Max padding size",
+    )
+
+    smooth_quant_group.add_argument(
+        "--calibration_sampling_size",
+        required=False,
+        type=int,
+        default=8,
+        help="Calibration sampling size for quantization config",
+    )
+
+    smooth_quant_group.add_argument(
+        "--nc_workspace",
+        required=False,
+        type=str,
+        default=os.path.join(".", "nc_workspace"),
+        help="Workspace to save intermediate files generated by Intel's Neural Compressor package.",
+    )
+
+    quantize_dynamic_group = parser.add_argument_group("quantize_dynamic (8-bit quantization)")
+
+    quantize_dynamic_group.add_argument(
+        "--quantize_embedding_layer",
+        required=False,
+        action="store_true",
+        help="Quantize MatMul, GEMM, and Gather.",
+    )
+    quantize_dynamic_group.set_defaults(quantize_embedding_layer=False)
+
+    quantize_dynamic_group.add_argument(
+        "--quantize_per_channel",
+        required=False,
+        action="store_true",
+        help="Quantize weights per each channel.",
+    )
+    quantize_dynamic_group.set_defaults(quantize_per_channel=False)
+
+    quantize_dynamic_group.add_argument(
+        "--quantize_reduce_range",
+        required=False,
+        action="store_true",
+        help="Quantize weights with 7 bits.",
+    )
+    quantize_dynamic_group.set_defaults(quantize_reduce_range=False)
+
+    parser.add_argument(
+        "-v",
+        "--verbose",
+        action="store_true",
+        help="Print verbose logs",
+    )
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument(
+        "-d",
+        "--use_dynamo_export",
+        action="store_true",
+        help="Use the new Dynamo exporter instead of the old TorchScript exporter",
+    )
+    parser.set_defaults(use_dynamo_export=False)
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default="./model_cache",
+        help="model cache dir to override default HF cache dir to avoid overflood the /home dir",
+    )
+
+    parser.add_argument(
+        "--optimize_optimum",
+        action="store_true",
+        help="Avoid exporting model, only apply quantizations and optimizations to existing model exported from optimum.",
+    )
+
+    parser.add_argument(
+        "--small_gpu",
+        action="store_true",
+        help="Load the llama in GPU every time for parity_check if it's running in a machine which GPU memory < 36GB.",
+    )
+
+    parser.set_defaults(optimize_optimum=False)
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    warnings.warn(
+        "This example is deprecated. Use the Olive recipe instead: "
+        "https://github.com/microsoft/olive-recipes/tree/main",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+    if version.parse(torch.__version__) < version.parse("2.2.0"):
+        logger.error(f"Detected PyTorch version {torch.__version__}. Please upgrade and use v2.2.0 or newer.")
+        return
+
+    args = get_args()
+    setup_logger(args.verbose)
+    prepare_environment(args.input, args.output, args.execution_provider != "cpu")
+    if args.reexport:
+        remove_existing_files(args.output)
+    logger.info(f"Arguments: {args}")
+
+    world_size = get_size()
+    rank = get_rank()
+    args.world_size = world_size
+
+    # Load model and config
+    use_auth_token = args.input == os.path.join(".")
+    setattr(args, "use_auth_token", use_auth_token)  # noqa: B010
+
+    original_model_name = args.model_name
+    setattr(args, "original_model_name", original_model_name)  # noqa: B010
+    args.model_name = args.model_name.split("/")[-1]
+
+    setattr(args, "device_name", "cpu" if args.execution_provider == "cpu" else f"cuda:{rank}")  # noqa: B010
+    setattr(args, "device", torch.device(args.device_name))  # noqa: B010
+
+    location = args.original_model_name if use_auth_token else args.input
+
+    if args.optimize_optimum:
+        config = AutoConfig.from_pretrained(args.original_model_name, cache_dir=args.cache_dir)
+        optimize_optimum(config, args)
+        return
+
+    # Use CUDA for LLaMA-2-70B to speed up export and CPU for other models
+    l_config, llama = setup_torch_model(
+        args, location, use_auth_token, device=args.device if args.model_name == "Llama-2-70b-hf" else None
+    )
+
+    assert l_config.num_attention_heads % world_size == 0 and l_config.num_key_value_heads % world_size == 0
+
+    barrier()
+    for i in range(world_size):
+        if i == rank:
+            # Set model paths for FP32 model
+            decoder_model_fp32_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_model_fp32.onnx"
+            )
+            decoder_with_past_model_fp32_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32.onnx"
+            )
+            decoder_merged_model_fp32_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_fp32.onnx"
+            )
+            old_paths = [decoder_model_fp32_path, decoder_with_past_model_fp32_path, decoder_merged_model_fp32_path]
+
+            missing_separate_exports = (
+                args.no_merged
+                and not os.path.exists(decoder_model_fp32_path)
+                and not os.path.exists(decoder_with_past_model_fp32_path)
+            )
+            missing_merged_export = not args.no_merged and not os.path.exists(decoder_merged_model_fp32_path)
+
+            # Export to ONNX
+            if missing_separate_exports or missing_merged_export:
+                if args.use_dynamo_export:
+                    logger.warning("Please ensure you have installed PyTorch, ONNX, and ONNX Script as follows.")
+                    logger.warning("Step 1 - PyTorch nightly: https://pytorch.org/get-started/locally/")
+                    logger.warning("Step 2 - ONNX weekly: https://pypi.org/project/onnx-weekly/")
+                    logger.warning(
+                        "Step 3 - ONNX Script from source: https://github.com/microsoft/onnxscript#installing-onnx-script"
+                    )
+                    logger.warning(
+                        "Note: After you install ONNX weekly, omit `onnx` when running the first line for installing ONNX Script. This is because you already installed `onnx-weekly` in the previous step."
+                    )
+                    run_dynamo_export(args, l_config, llama)
+                elif args.no_merged:
+                    run_torchscript_separate_export(args, l_config, llama, rank, world_size)
+                else:
+                    run_torchscript_merged_export(args, l_config, llama, rank, world_size)
+            del llama  # Delete LLaMA model from memory since it will be loaded again during parity check
+
+            # Set model paths to store FP32 optimized model
+            decoder_model_fp32_opt_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_model_fp32_opt.onnx"
+            )
+            decoder_with_past_model_fp32_opt_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_fp32_opt.onnx"
+            )
+            decoder_merged_model_fp32_opt_path = os.path.join(
+                args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_fp32_opt.onnx"
+            )
+            new_paths = [
+                decoder_model_fp32_opt_path,
+                decoder_with_past_model_fp32_opt_path,
+                decoder_merged_model_fp32_opt_path,
+            ]
+
+            # Run the optimizer script.
+            logger.info("Optimizing models...")
+            for orig_path, opt_path in zip(old_paths, new_paths, strict=False):
+                if os.path.exists(orig_path):
+                    optimize_export(args, l_config, input_path=orig_path, output_path=opt_path, world_size=world_size)
+
+            # Re-assign default FP32 model paths as their optimized versions
+            decoder_model_fp32_path = decoder_model_fp32_opt_path
+            decoder_with_past_model_fp32_path = decoder_with_past_model_fp32_opt_path
+            decoder_merged_model_fp32_path = decoder_merged_model_fp32_opt_path
+            old_paths = [decoder_model_fp32_path, decoder_with_past_model_fp32_path, decoder_merged_model_fp32_path]
+
+            logger.info(
+                f"The {args.model_name} ONNX model has been successfully optimized with the ORT transformer optimizer script!"
+            )
+
+            # Change precision of exported models from FP32
+            if args.precision == Precision.FLOAT16:
+                new_paths = convert_to_float16(args, old_paths, rank)
+
+            elif args.precision == Precision.INT8:
+                decoder_model_int8_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_model_int8.onnx"
+                )
+                decoder_with_past_model_int8_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_int8.onnx"
+                )
+                decoder_merged_model_int8_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_int8.onnx"
+                )
+                new_paths = [decoder_model_int8_path, decoder_with_past_model_int8_path, decoder_merged_model_int8_path]
+
+                if args.quantization_method == "smooth_quant":
+                    if not args.no_merged:
+                        logger.error("SmoothQuant must be used on separately exported models")
+                    else:
+                        logger.info(
+                            f"Quantizing {decoder_model_fp32_path} and {decoder_with_past_model_fp32_path} to int8"
+                        )
+                        smooth_quant(args, old_paths[0], old_paths[1], new_paths[0], new_paths[1])
+
+                elif args.quantization_method == "quantize_dynamic":
+                    logger.warning(
+                        "The `quantize_dynamic` method is deprecated in favor of `smooth_quant` instead. Precision loss may be high with `quantize_dynamic`."
+                    )
+
+                    logger.info("Quantizing to int8...")
+                    for fp32_path, int8_path in zip(old_paths, new_paths, strict=False):
+                        if os.path.exists(fp32_path):
+                            ort_quantization.quantize_dynamic(
+                                fp32_path,
+                                int8_path,
+                                op_types_to_quantize=(
+                                    ["MatMul", "Gemm", "Gather"]
+                                    if args.quantize_embedding_layer
+                                    else ["MatMul", "Gemm"]
+                                ),
+                                per_channel=args.quantize_per_channel,
+                                reduce_range=args.quantize_reduce_range,
+                                use_external_data_format=True,
+                                extra_options={"MatMulConstBOnly": True},
+                            )
+                            logger.info(
+                                f"The ONNX model at {fp32_path} has been quantized to int8 and saved at {int8_path}!"
+                            )
+                            remove_existing_model(decoder_model_fp32_path)
+
+                    logger.info(f"The {args.model_name} ONNX model has been successfully quantized to int8!")
+
+                else:
+                    raise Exception(f"Could not recognize {args.quantization_method} as a quantization method")
+
+            elif args.precision == Precision.INT4:
+                if args.execution_provider != "cpu":
+                    old_paths = convert_to_float16(args, old_paths, rank)
+
+                decoder_model_int4_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_model_int4.onnx"
+                )
+                decoder_with_past_model_int4_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_with_past_model_int4.onnx"
+                )
+                decoder_merged_model_int4_path = os.path.join(
+                    args.output, f"rank_{rank}_{args.model_name}_decoder_merged_model_int4.onnx"
+                )
+                new_paths = [decoder_model_int4_path, decoder_with_past_model_int4_path, decoder_merged_model_int4_path]
+
+                for fp_path, int4_path in zip(old_paths, new_paths, strict=False):
+                    if os.path.exists(fp_path):
+                        model = onnx.load_model(fp_path, load_external_data=True)
+                        quant = MatMulNBitsQuantizer(
+                            model=model,
+                            bits=args.bits,
+                            block_size=args.block_size,
+                            is_symmetric=True,
+                            accuracy_level=args.int4_accuracy_level,
+                            nodes_to_exclude=[],
+                        )
+                        quant.process()
+                        quant.model.save_model_to_file(int4_path, use_external_data_format=True)
+                        del model
+                        del quant
+                        logger.info(f"The ONNX model at {fp_path} has been quantized to int4 and saved at {int4_path}!")
+                        remove_existing_model(fp_path)
+        barrier()
+
+    logger.info("Verifying parity on all ONNX models created")
+
+    # Use FP32 precision for FP32, INT8, INT4 CPU models, use FP16 precision for FP16 and INT4 GPU models
+    args.precision = (
+        "fp32"
+        if args.precision in {Precision.INT8, Precision.FLOAT32}
+        or (args.precision == Precision.INT4 and args.execution_provider == "cpu")
+        else "fp16"
+    )
+
+    # Verify parity on all saved ONNX models
+    for filename in os.listdir(args.output):
+        if (
+            ".data" in filename
+            or ".onnx" not in filename
+            or args.precision not in filename
+            or f"rank_{rank}" not in filename
+        ):
+            continue
+
+        parity_cmd = [
+            "-m",
+            original_model_name,
+            "-o",
+            os.path.join(args.output, filename),
+            "-ep",
+            args.execution_provider,
+            "--precision",
+            args.precision,
+            "--cache_dir",
+            args.cache_dir,
+            "--torch_model_directory",
+            args.input,
+        ]
+        if args.small_gpu:
+            parity_cmd.append("--small_gpu")
+        if "with_past" in filename:
+            parity_cmd.append("--use_past_kv")
+        if "merged" in filename:
+            parity_cmd.append("--merged")
+
+        try:
+            logger.info(f"check parity with cmd: {parity_cmd}")
+            parity_check(parity_cmd)
+        except Exception as e:
+            logger.exception(f"An error occurred while verifying parity: {e}")
+            sys.exit(-1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/dist_settings.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/dist_settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..db8f8eae7f841e8cbeac0416b44b4dc60ebcccb0
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/dist_settings.py
@@ -0,0 +1,57 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import os
+
+import torch.distributed as dist
+
+
+def init_dist():
+    if "LOCAL_RANK" in os.environ:
+        int(os.environ["LOCAL_RANK"])
+        rank = int(os.environ["RANK"])
+        world_size = int(os.environ["WORLD_SIZE"])
+
+        dist.init_process_group("nccl", init_method="tcp://127.0.0.1:7645", world_size=world_size, rank=rank)
+    elif "OMPI_COMM_WORLD_LOCAL_RANK" in os.environ:
+        int(os.environ.get("OMPI_COMM_WORLD_LOCAL_RANK", "0"))
+        rank = int(os.environ.get("OMPI_COMM_WORLD_RANK", "0"))
+        world_size = int(os.environ.get("OMPI_COMM_WORLD_SIZE", "1"))
+
+        dist.init_process_group("nccl", init_method="tcp://127.0.0.1:7647", world_size=world_size, rank=rank)
+    else:
+        # don't need to do init for single process
+        pass
+
+
+def _get_comm():
+    try:
+        from mpi4py import MPI  # noqa: PLC0415
+
+        comm = MPI.COMM_WORLD
+        return comm
+    except ImportError:
+        return None
+
+
+def get_rank():
+    comm = _get_comm()
+    return comm.Get_rank() if comm is not None else 0
+
+
+def get_size():
+    comm = _get_comm()
+    return comm.Get_size() if comm is not None else 1
+
+
+def barrier():
+    comm = _get_comm()
+    if comm is not None:
+        comm.Barrier()
+
+
+def print_out(*args):
+    if get_rank() == 0:
+        print(*args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_inputs.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_inputs.py
new file mode 100644
index 0000000000000000000000000000000000000000..71b312eb9360daf78370d9f7bd5f260445ab9ec2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_inputs.py
@@ -0,0 +1,504 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import numpy as np
+import torch
+from transformers import AutoConfig, AutoTokenizer
+from transformers.cache_utils import DynamicCache
+
+from onnxruntime import InferenceSession, OrtValue
+
+
+# Get position_ids from attention_mask
+def get_position_ids(attention_mask: torch.Tensor, use_past_kv: bool):
+    position_ids = attention_mask.long().cumsum(-1) - 1
+    position_ids.masked_fill_(attention_mask == 0, 1)
+    if use_past_kv:
+        # Shape: (batch_size, 1)
+        position_ids = position_ids[:, -1].unsqueeze(-1)
+
+    # Shape: (batch_size, sequence_length)
+    return position_ids
+
+
+# Inputs for first pass to get initial past_key_values
+#   input_ids: (batch_size, sequence_length)
+#   attention_mask: (batch_size, sequence_length)
+#   position_ids: (batch_size, sequence_length)
+def get_sample_inputs(
+    config: AutoConfig,
+    device: torch.device,
+    batch_size: int,
+    seq_len: int,
+    engine: str = "pt",
+    return_dict: bool = False,
+):
+    input_ids = torch.randint(low=0, high=config.vocab_size, size=(batch_size, seq_len), dtype=torch.int64)
+    attention_mask = torch.ones(batch_size, seq_len, dtype=torch.int64)
+    position_ids = get_position_ids(attention_mask, use_past_kv=False)
+
+    # Convert inputs to NumPy (for ORT) or send to device (for PyTorch)
+    input_ids = input_ids.numpy() if engine == "ort" else input_ids.to(device)
+    attention_mask = attention_mask.numpy() if engine == "ort" else attention_mask.to(device)
+    position_ids = position_ids.numpy() if engine == "ort" else position_ids.to(device)
+
+    if not return_dict:
+        # For export
+        return (input_ids, attention_mask, position_ids)
+
+    inputs = {
+        "input_ids": input_ids,
+        "attention_mask": attention_mask,
+        "position_ids": position_ids,
+    }
+    return inputs
+
+
+# Inputs for subsequent passes with past_key_values
+#   input_ids: (batch_size, 1)
+#   attention_mask: (batch_size, past_sequence_length + 1)
+#   position_ids: (batch_size, 1)
+#   past_key: (batch_size, num_heads, past_sequence_length, head_size)
+#   past_value: (batch_size, num_heads, past_sequence_length, head_size)
+def get_sample_with_past_kv_inputs(
+    config: AutoConfig,
+    device: torch.device,
+    batch_size: int,
+    past_seq_len: int,
+    use_fp16: bool = False,
+    engine: str = "pt",
+    return_dict: bool = False,
+    world_size: int = 1,
+):
+    input_ids = torch.randint(low=0, high=config.vocab_size, size=(batch_size, 1), dtype=torch.int64)
+    attention_mask = torch.ones(batch_size, past_seq_len + 1, dtype=torch.int64)
+    # position_ids is of shape (batch_size, 1)
+    position_ids = get_position_ids(attention_mask, use_past_kv=True)
+    past_kv = get_past_kv_inputs(config, batch_size, past_seq_len, use_fp16, world_size=world_size)
+
+    # Convert inputs to NumPy (for ORT) or send to device (for PyTorch)
+    input_ids = input_ids.numpy() if engine == "ort" else input_ids.to(device)
+    attention_mask = attention_mask.numpy() if engine == "ort" else attention_mask.to(device)
+    position_ids = position_ids.numpy() if engine == "ort" else position_ids.to(device)
+    past_kv = (
+        flatten_past_kv_inputs(past_kv) if engine == "ort" else [(kv[0].to(device), kv[1].to(device)) for kv in past_kv]
+    )
+
+    if not return_dict:
+        # For export
+        assert isinstance(past_kv, list)
+        return (input_ids, attention_mask, position_ids, past_kv)
+
+    inputs = {
+        "input_ids": input_ids,
+        "attention_mask": attention_mask,
+        "position_ids": position_ids,
+    }
+    if engine == "ort":
+        assert isinstance(past_kv, dict)
+        inputs.update(past_kv)
+    else:
+        assert isinstance(past_kv, list)
+        inputs["past_key_values"] = past_kv
+
+    return inputs
+
+
+# Inputs for all passes with past_key_values
+#   input_ids: (batch_size, sequence_length)
+#   attention_mask: (batch_size, past_sequence_length + sequence_length)
+#   position_ids: (batch_size, sequence_length)
+#   past_key: (batch_size, num_heads, kv_sequence_length, head_size)
+#      For models with GQA, kv_sequence_length = max_sequence_length
+#      For models without GQA, kv_sequence_length = past_sequence_length
+#   past_value: (batch_size, num_heads, kv_sequence_length, head_size)
+#      For models with GQA, kv_sequence_length = max_sequence_length
+#      For models without GQA, kv_sequence_length = past_sequence_length
+def get_merged_sample_with_past_kv_inputs(
+    config: AutoConfig,
+    device: torch.device,
+    batch_size: int,
+    seq_len: int,
+    past_seq_len: int,
+    max_seq_len: int,
+    use_fp16: bool = False,
+    use_buffer_share: bool = False,
+    engine: str = "pt",
+    return_dict: bool = False,
+    world_size: int = 1,
+):
+    input_ids = torch.randint(low=0, high=config.vocab_size, size=(batch_size, seq_len), dtype=torch.int64)
+    attention_mask = torch.ones(batch_size, past_seq_len + seq_len, dtype=torch.int64)
+    # position_ids is of shape (batch_size, seq_len) for prompt generation, (batch_size, 1) for token generation
+    position_ids = get_position_ids(attention_mask, use_past_kv=(past_seq_len != 0))
+    past_kv = get_past_kv_inputs(config, batch_size, past_seq_len, use_fp16, world_size=world_size)
+
+    # Convert inputs to NumPy (for ORT) or send to device (for PyTorch)
+    input_ids = input_ids.numpy() if engine == "ort" else input_ids.to(device)
+    attention_mask = attention_mask.numpy() if engine == "ort" else attention_mask.to(device)
+    position_ids = position_ids.numpy() if engine == "ort" else position_ids.to(device)
+    past_kv = (
+        flatten_past_kv_inputs(past_kv) if engine == "ort" else [(kv[0].to(device), kv[1].to(device)) for kv in past_kv]
+    )
+
+    if not return_dict:
+        # For export
+        assert isinstance(past_kv, list)
+        return (input_ids, attention_mask, position_ids, past_kv)
+
+    inputs = {
+        "input_ids": input_ids,
+        "attention_mask": attention_mask,
+        "position_ids": position_ids,
+    }
+    if engine == "ort":
+        assert isinstance(past_kv, dict)
+        inputs.update(past_kv)
+
+        if use_buffer_share:
+            inputs = enable_past_present_share_buffer(inputs, past_seq_len, max_seq_len)
+
+    else:
+        assert isinstance(past_kv, list)
+        inputs["past_key_values"] = past_kv
+
+    return inputs
+
+
+# Inputs for Microsoft export from https://github.com/microsoft/Llama-2-Onnx
+def get_msft_sample_inputs(
+    config: AutoConfig,
+    batch_size: int,
+    past_seq_len: int,
+    seq_len: int,
+    max_seq_len: int,
+    use_fp16: bool,
+    use_buffer_share: bool,
+    split_kv: bool,
+):
+    np_dtype = np.float16 if use_fp16 else np.float32
+    head_size = config.hidden_size // config.num_attention_heads
+
+    if not split_kv:
+        ort_inputs = {
+            "x": np.random.rand(batch_size, seq_len, config.hidden_size).astype(np_dtype),
+            "attn_mask": (-10000.0 * np.triu(np.ones((batch_size, max_seq_len, max_seq_len)), k=1)).astype(np_dtype),
+            "k_cache": np.random.rand(
+                batch_size, config.num_hidden_layers, past_seq_len, config.num_attention_heads, head_size
+            ).astype(np_dtype),
+            "v_cache": np.random.rand(
+                batch_size, config.num_hidden_layers, past_seq_len, config.num_attention_heads, head_size
+            ).astype(np_dtype),
+            "pos": np.array(past_seq_len, dtype=np.int64),
+        }
+    else:
+        ort_inputs = {
+            "x": np.random.rand(batch_size, seq_len, config.hidden_size).astype(np_dtype),
+            "attn_mask": (np.triu(np.ones((batch_size, max_seq_len, max_seq_len), dtype=np.int32), k=1) - 1).astype(
+                np.int32
+            ),
+            "pos": np.array(past_seq_len, dtype=np.int64),
+        }
+        for i in range(config.num_hidden_layers):
+            ort_inputs.update(
+                {
+                    f"k_{i}_cache": np.random.rand(
+                        batch_size, config.num_attention_heads, past_seq_len, head_size
+                    ).astype(np_dtype),
+                    f"v_{i}_cache": np.random.rand(
+                        batch_size, config.num_attention_heads, past_seq_len, head_size
+                    ).astype(np_dtype),
+                }
+            )
+
+        if use_buffer_share:
+            ort_inputs = enable_past_present_share_buffer(ort_inputs, past_seq_len, max_seq_len)
+
+    return ort_inputs
+
+
+# Create past_key_values
+# Each is of shape (batch_size, num_heads, past_sequence_length, head_size)
+def get_past_kv_inputs(config: AutoConfig, batch_size: int, past_seq_len: int, use_fp16: bool, world_size: int = 1):
+    num_heads = config.num_key_value_heads // world_size
+    head_size = config.head_dim if hasattr(config, "head_dim") else config.hidden_size // config.num_attention_heads
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+    past_kv = [
+        (
+            torch.rand(batch_size, num_heads, past_seq_len, head_size, dtype=torch_dtype),
+            torch.rand(batch_size, num_heads, past_seq_len, head_size, dtype=torch_dtype),
+        )
+        for _ in range(config.num_hidden_layers)
+    ]
+    return past_kv
+
+
+# Convert list of past_key_values to dict of past_key and past_value
+def flatten_past_kv_inputs(past_key_values: list[tuple[torch.Tensor, torch.Tensor]]):
+    past_kv = {}
+    for i, (past_k, past_v) in enumerate(past_key_values):
+        if isinstance(past_key_values, DynamicCache):
+            past_kv[f"past_key_values_key_cache_{i}"] = past_k.detach().cpu().numpy()
+            past_kv[f"past_key_values_value_cache_{i}"] = past_v.detach().cpu().numpy()
+        else:
+            past_kv[f"past_key_values.{i}.key"] = past_k.detach().cpu().numpy()
+            past_kv[f"past_key_values.{i}.value"] = past_v.detach().cpu().numpy()
+    return past_kv
+
+
+# Format PyTorch inputs to ONNX Runtime inputs
+def convert_inputs_for_ort(
+    pt_inputs: dict,
+    use_buffer_share: bool = False,
+    past_seq_len: int = 0,
+    max_seq_len: int = 2048,
+):
+    ort_inputs = {}
+    for k, v in pt_inputs.items():
+        if isinstance(v, np.ndarray):
+            ort_inputs[k] = v
+        elif k == "past_key_values":
+            ort_inputs.update(flatten_past_kv_inputs(v))
+        else:
+            ort_inputs[k] = v.detach().cpu().numpy()
+
+    # Reshape KV caches if using past-present-share-buffer
+    if use_buffer_share:
+        ort_inputs = enable_past_present_share_buffer(ort_inputs, past_seq_len, max_seq_len)
+
+    return ort_inputs
+
+
+# Re-allocate KV caches from (batch_size, num_heads, past_sequence_length, head_size) to
+# (batch_size, num_heads, max_sequence_length, head_size) for past-present buffer sharing
+def enable_past_present_share_buffer(ort_inputs: dict, past_seq_len: int, max_seq_len: int):
+    for k, v in ort_inputs.items():
+        # Allocate new buffers with max_sequence_length for GQA
+        if "cache" in k or "past_key_values" in k:
+            # Copy v (BxSxPxH) into new_v (BxSxMxH)
+            batch_size, num_heads, _, head_size = v.shape
+            new_v = np.zeros((batch_size, num_heads, max_seq_len, head_size), dtype=v.dtype)
+            new_v[:batch_size, :num_heads, :past_seq_len, :head_size] = v
+            ort_inputs[k] = new_v
+    return ort_inputs
+
+
+# Verify ONNX Runtime inputs with model
+def verify_ort_inputs(model: InferenceSession, ort_inputs: dict):
+    # Check that all model inputs will be provided
+    model_inputs = {model_input.name for model_input in model.get_inputs()}
+    user_inputs = set(ort_inputs.keys())
+    missing_inputs = model_inputs - user_inputs
+    if len(missing_inputs):
+        print(f"The following model inputs are missing: {missing_inputs}")
+        raise Exception("There are missing inputs to the model. Please add them and try again.")
+
+    # Remove unnecessary inputs from model inputs
+    unnecessary_inputs = user_inputs - model_inputs
+    if len(unnecessary_inputs):
+        for unnecessary_input in unnecessary_inputs:
+            del ort_inputs[unnecessary_input]
+
+    return ort_inputs
+
+
+# Add IO bindings for execution providers using OrtValue
+# Use when you need to run inference once or twice to save memory
+def add_io_bindings_as_ortvalues(
+    model: InferenceSession,
+    ort_inputs: dict,
+    device: str,
+    device_id: int,
+    use_buffer_share: bool,
+    kv_cache_ortvalues: dict,
+):
+    io_binding = model.io_binding()
+
+    model_inputs = {i.name for i in model.get_inputs()}
+    for k, v in ort_inputs.items():
+        # Use this check to handle scenarios such as INT4 CUDA and FP16 CUDA models with
+        # GQA + RotaryEmbedding fusion where `position_ids` is removed as an ONNX model input
+        # but `position_ids` is used as a PyTorch model input
+        if k not in model_inputs:
+            continue
+
+        # Bind OrtValue inputs to device
+        if use_buffer_share and ("cache" in k or "past_key_values" in k):
+            if k not in kv_cache_ortvalues:
+                v_device = OrtValue.ortvalue_from_numpy(v, device_type=device, device_id=device_id)
+                io_binding.bind_ortvalue_input(k, v_device)
+                kv_cache_ortvalues[k] = v_device
+            else:
+                kv_cache_ortvalues[k].update_inplace(v)
+                io_binding.bind_ortvalue_input(k, kv_cache_ortvalues[k])
+        else:
+            v_device = OrtValue.ortvalue_from_numpy(v, device_type=device, device_id=device_id)
+            io_binding.bind_ortvalue_input(k, v_device)
+
+    for output in model.get_outputs():
+        name = output.name
+        if use_buffer_share and ("out" in name or "present" in name):
+            # Bind present KV cache outputs to past KV cache inputs in order to buffer share
+            input_name = name.replace("out", "cache").replace("present", "past_key_values")
+            io_binding.bind_ortvalue_output(name, kv_cache_ortvalues[input_name])
+        else:
+            io_binding.bind_output(name, device_type=device, device_id=device_id)
+
+    return io_binding, kv_cache_ortvalues
+
+
+# Add IO bindings for execution providers using PyTorch tensors
+# Use when you need to run inference many times
+def add_io_bindings_as_tensors(
+    model: InferenceSession, inputs: dict, outputs: dict, use_fp16: bool, use_buffer_share: bool
+):
+    # Verify model inputs
+    inputs = verify_ort_inputs(model, inputs)
+
+    device = None
+    pt_to_np = {
+        "torch.int32": np.int32,
+        "torch.int64": np.int64,
+        "torch.float16": np.float16,
+        "torch.float32": np.float32,
+    }
+
+    # Bind inputs/outputs to IO binding
+    io_binding = model.io_binding()
+    for k, v in inputs.items():
+        io_binding.bind_input(
+            name=k,
+            device_type=v.device.type,
+            device_id=0 if v.device.type == "cpu" else v.device.index,
+            element_type=pt_to_np[repr(v.dtype)],
+            shape=tuple(v.shape),
+            buffer_ptr=v.data_ptr(),
+        )
+        device = v.device
+
+    for output in model.get_outputs():
+        name = output.name
+        # Bind KV cache outputs to KV cache inputs
+        v = (
+            inputs[name.replace("present", "past_key_values")]
+            if use_buffer_share and "present" in name
+            else outputs[name]
+        )
+        io_binding.bind_output(
+            name=name,
+            device_type=device.type,
+            device_id=0 if device.type == "cpu" else device.index,
+            element_type=(np.float16 if use_fp16 else np.float32),
+            shape=tuple(v.shape),
+            buffer_ptr=v.data_ptr(),
+        )
+
+    return io_binding
+
+
+# Get actual inputs when using real data (instead of sample data) and initialize outputs
+def get_initial_inputs_and_outputs(
+    config: AutoConfig,
+    tokenizer: AutoTokenizer,
+    requested_length: int,
+    prompt: list[str],
+    device: torch.device,
+    use_fp16: bool,
+    use_buffer_share: bool,
+    engine: str,
+):
+    tokenizer.pad_token = tokenizer.eos_token
+    encodings_dict = tokenizer.batch_encode_plus(prompt, padding=True)
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+
+    # input_ids:      pad token id is 0
+    # attention_mask: pad token id is 0
+    # position_ids:   pad token id is 1
+    input_ids = torch.tensor(encodings_dict["input_ids"], device=device, dtype=torch.int64)
+    attention_mask = torch.tensor(encodings_dict["attention_mask"], device=device, dtype=torch.int64)
+    position_ids = get_position_ids(attention_mask, use_past_kv=False)
+
+    # Check if tokenized prompt length matches the requested prompt length
+    tokenized_length = input_ids.shape[-1]
+    if tokenized_length > requested_length:
+        # Shorten the inputs from (batch_size, tokenized_length) to (batch_size, requested_length)
+        input_ids = input_ids[:, :requested_length]
+        attention_mask = attention_mask[:, :requested_length]
+        position_ids = get_position_ids(attention_mask, use_past_kv=False)
+    elif tokenized_length < requested_length:
+        # Lengthen the inputs from (batch_size, tokenized_length) to (batch_size, requested_length)
+        input_ids_first_col = input_ids[:, 0].unsqueeze(0).T
+        attention_mask_first_col = attention_mask[:, 0].unsqueeze(0).T
+        for _ in range(requested_length - tokenized_length):
+            input_ids = torch.hstack((input_ids_first_col, input_ids))
+            attention_mask = torch.hstack((attention_mask_first_col, attention_mask))
+        position_ids = get_position_ids(attention_mask, use_past_kv=False)
+
+    tokenized_length = input_ids.shape[-1]
+    assert tokenized_length == requested_length
+
+    # Create inputs
+    inputs = {
+        "input_ids": input_ids.contiguous() if engine == "ort" else input_ids,
+        "attention_mask": attention_mask.contiguous() if engine == "ort" else attention_mask,
+        "position_ids": position_ids.contiguous() if engine == "ort" else position_ids,
+    }
+    if engine != "ort":
+        inputs["past_key_values"] = []
+
+    # Get shape of KV cache inputs
+    batch_size, sequence_length = input_ids.shape
+    max_sequence_length = config.max_position_embeddings
+    num_heads = config.num_key_value_heads
+    head_size = config.head_dim if hasattr(config, "head_dim") else config.hidden_size // config.num_attention_heads
+
+    # Create KV cache inputs
+    for i in range(config.num_hidden_layers):
+        past_key = torch.zeros(
+            batch_size,
+            num_heads,
+            max_sequence_length if use_buffer_share else 0,
+            head_size,
+            device=device,
+            dtype=torch_dtype,
+        )
+        past_value = torch.zeros(
+            batch_size,
+            num_heads,
+            max_sequence_length if use_buffer_share else 0,
+            head_size,
+            device=device,
+            dtype=torch_dtype,
+        )
+        if engine == "ort":
+            inputs.update(
+                {
+                    f"past_key_values.{i}.key": past_key.contiguous(),
+                    f"past_key_values.{i}.value": past_value.contiguous(),
+                }
+            )
+        else:
+            inputs["past_key_values"].append((past_key, past_value))
+
+    outputs = None
+    if engine == "ort":
+        # Create outputs
+        logits = torch.zeros(batch_size, sequence_length, config.vocab_size, device=device, dtype=torch_dtype)
+        outputs = {"logits": logits.contiguous()}
+        if not use_buffer_share:
+            for i in range(config.num_hidden_layers):
+                present_key = torch.zeros(
+                    batch_size, num_heads, sequence_length, head_size, device=device, dtype=torch_dtype
+                )
+                present_value = torch.zeros(
+                    batch_size, num_heads, sequence_length, head_size, device=device, dtype=torch_dtype
+                )
+                outputs.update(
+                    {f"present.{i}.key": present_key.contiguous(), f"present.{i}.value": present_value.contiguous()}
+                )
+
+    return inputs, outputs
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_parity.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_parity.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4037e2c5e1495fee5489fe49613884bd03e9e37
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_parity.py
@@ -0,0 +1,343 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import argparse
+import logging
+import os
+import time
+
+import numpy as np
+import packaging.version as pv
+import torch
+from benchmark_helper import setup_logger
+from dist_settings import get_rank, get_size
+from llama_inputs import (
+    add_io_bindings_as_ortvalues,
+    convert_inputs_for_ort,
+    get_merged_sample_with_past_kv_inputs,
+    get_sample_inputs,
+    get_sample_with_past_kv_inputs,
+    verify_ort_inputs,
+)
+from llama_torch import setup_torch_model
+from models.torch_export_patches.cache_helper import make_dynamic_cache
+from transformers import AutoConfig
+from transformers import __version__ as transformers_version
+from transformers.cache_utils import DynamicCache
+
+import onnxruntime as ort
+
+logger = logging.getLogger("")
+
+
+def get_sequence_lengths(args: argparse.Namespace, config: AutoConfig):
+    past_sequence_length, curr_sequence_length = (8, 1) if args.use_past_kv else (0, 8)
+    max_sequence_length = config.max_position_embeddings
+    return past_sequence_length, curr_sequence_length, max_sequence_length
+
+
+def get_inputs(args: argparse.Namespace, config: AutoConfig):
+    # Dummy values for parity
+    world_size = get_size()
+    batch_size = 2
+    past_sequence_length, sequence_length, max_sequence_length = get_sequence_lengths(args, config)
+
+    if args.merged:
+        inputs = get_merged_sample_with_past_kv_inputs(
+            config,
+            args.device,
+            batch_size,
+            seq_len=sequence_length,
+            past_seq_len=past_sequence_length,
+            max_seq_len=max_sequence_length,
+            use_fp16=args.use_fp16,
+            use_buffer_share=args.use_buffer_share,
+            return_dict=True,
+            world_size=world_size,
+        )
+    elif args.use_past_kv:
+        inputs = get_sample_with_past_kv_inputs(
+            config,
+            args.device,
+            batch_size,
+            sequence_length,
+            use_fp16=args.use_fp16,
+            return_dict=True,
+            world_size=world_size,
+        )
+    else:
+        inputs = get_sample_inputs(config, args.device, batch_size, sequence_length, return_dict=True)
+
+    return inputs
+
+
+def torch_deepcopy(value):
+    if isinstance(value, (int, float, str)):
+        return value
+    if isinstance(value, tuple):
+        return tuple(torch_deepcopy(v) for v in value)
+    if isinstance(value, list):
+        return [torch_deepcopy(v) for v in value]
+    if isinstance(value, set):
+        return {torch_deepcopy(v) for v in value}
+    if isinstance(value, dict):
+        return {k: torch_deepcopy(v) for k, v in value.items()}
+    if isinstance(value, np.ndarray):
+        return value.copy()
+    if hasattr(value, "clone"):
+        return value.clone()
+    if isinstance(value, DynamicCache):
+        return make_dynamic_cache(torch_deepcopy(list(zip(value.key_cache, value.value_cache, strict=False))))
+    # We should have a code using serialization, deserialization assuming a model
+    # cannot be exported without them.
+    raise NotImplementedError(f"torch_deepcopy not implemented for type {type(value)}")
+
+
+def verify_parity(
+    args: argparse.Namespace,
+    location: str,
+    use_auth_token: bool,
+    kv_cache_ortvalues: dict,
+    pytorch_model: None | torch.nn.Module = None,
+    config: None | AutoConfig = None,
+):
+    # If it's running in a machine where GPU memory < 36GB, it should unload the model in GPU in time and free the GPU memory for ORT.
+    py_model = pytorch_model
+    if py_model is None:
+        config, py_model = setup_torch_model(
+            args,
+            location,
+            use_auth_token,
+            torch_dtype=(torch.float16 if args.use_fp16 else torch.float32),
+            device=args.device,
+        )
+
+    inputs = get_inputs(args, config)
+
+    if "past_key_values" in inputs and pv.Version(transformers_version) >= pv.Version("4.45"):
+        # Using DynamicCache
+        inputs["past_key_values"] = make_dynamic_cache(inputs["past_key_values"])
+
+    # Run inference with PyTorch
+    inputs_after_deepcopy = torch_deepcopy(inputs)
+    if args.execution_provider != "cpu":
+        torch.cuda.synchronize()
+    start_time = time.time()
+    # If there is a cache in the inputs, we need to make a copy as the model modifies them inplace.
+    # DynamicCache inherits from torch.nn.Module in some version of transformers.
+    # We need to make the copy manually.
+    pt_outputs = py_model(**inputs_after_deepcopy).logits.detach().cpu().numpy()
+    if args.execution_provider != "cpu":
+        torch.cuda.synchronize()
+    end_time = time.time()
+    logger.info(f"PyTorch took {end_time - start_time} s")
+
+    if args.small_gpu and py_model is not None:
+        del py_model
+        torch.cuda.empty_cache()
+
+    # Run inference with ORT
+    past_sequence_length, _, max_sequence_length = get_sequence_lengths(args, config)
+    inputs = convert_inputs_for_ort(
+        inputs,
+        use_buffer_share=args.use_buffer_share,
+        past_seq_len=past_sequence_length,
+        max_seq_len=max_sequence_length,
+    )
+
+    ep = f"{args.execution_provider.upper()}ExecutionProvider"
+    if ep == "CUDAExecutionProvider":
+        ep = (ep, {"device_id": args.rank})
+    ort_model = ort.InferenceSession(
+        args.onnx_model_path,
+        sess_options=ort.SessionOptions(),
+        providers=[ep],
+    )
+    inputs = verify_ort_inputs(ort_model, inputs)
+
+    # Add IO bindings for non-CPU execution providers
+    if args.execution_provider != "cpu":
+        io_binding, kv_cache_ortvalues = add_io_bindings_as_ortvalues(
+            ort_model,
+            ort_inputs=inputs,
+            device=args.execution_provider,
+            device_id=int(args.rank),
+            use_buffer_share=args.use_buffer_share,
+            kv_cache_ortvalues=kv_cache_ortvalues,
+        )
+
+        io_binding.synchronize_inputs()
+        start_time = time.time()
+        ort_model.run_with_iobinding(io_binding)
+        io_binding.synchronize_outputs()
+        end_time = time.time()
+
+        ort_outputs = io_binding.copy_outputs_to_cpu()[0]  # Get logits
+        del ort_model
+
+    else:
+        start_time = time.time()
+        ort_outputs = ort_model.run(None, inputs)
+        end_time = time.time()
+
+        ort_outputs = ort_outputs[0]  # Get logits
+
+    logger.info(f"ONNX Runtime took {end_time - start_time} s")
+
+    # Compare PyTorch and ONNX Runtime accuracy
+    tol = 2e1 if "int4" in args.onnx_model_path or "int8" in args.onnx_model_path else 5e-1
+    parity = np.allclose(pt_outputs, ort_outputs, rtol=tol, atol=tol)
+    logger.warning(f"Are PyTorch and ONNX Runtime results close? {parity}")
+    if not parity:
+        logger.warning(f"Max diff: {np.max(pt_outputs - ort_outputs)}")
+    return kv_cache_ortvalues
+
+
+def get_args(argv: list[str]):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model_name",
+        required=False,
+        help="Model name in Hugging Face",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--torch_model_directory",
+        required=False,
+        default=os.path.join("."),
+        help="Path to folder containing PyTorch model and associated files if saved on disk",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--onnx_model_path",
+        required=True,
+        default=os.path.join("."),
+        help="Path to ONNX model (with external data files saved in the same folder as the model)",
+    )
+
+    parser.add_argument(
+        "-ep",
+        "--execution_provider",
+        required=False,
+        default="cpu",
+        choices=["cpu", "cuda"],
+        help="Execution provider to verify parity with",
+    )
+
+    parser.add_argument(
+        "-v",
+        "--verbose",
+        action="store_true",
+        help="Print verbose logs",
+    )
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument(
+        "-p",
+        "--use_past_kv",
+        action="store_true",
+        help="Use past key and past value as inputs to the model. Necessary for decoder_with_past_model.onnx models.",
+    )
+    parser.set_defaults(use_past_kv=False)
+
+    parser.add_argument(
+        "-g",
+        "--use_buffer_share",
+        action="store_true",
+        help="Use if model has GroupQueryAttention and you want to enable past-present buffer sharing",
+    )
+    parser.set_defaults(use_buffer_share=False)
+
+    parser.add_argument(
+        "--merged",
+        action="store_true",
+        help="Use merged model (i.e. decoder_merged_model.onnx).",
+    )
+    parser.set_defaults(merged=False)
+
+    parser.add_argument(
+        "-fp",
+        "--precision",
+        required=True,
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision of model",
+    )
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default="./model_cache",
+        help="model cache dir to override default HF cache dir to avoid overflood the /home dir",
+    )
+
+    # The argument is used for CI mainly, because the CI machine has 24G GPU memory at most.
+    parser.add_argument(
+        "--small_gpu",
+        action="store_true",
+        help="Load the llama in GPU every time for parity_check if it's running in a machine which GPU memory < 36GB. ",
+    )
+
+    args = parser.parse_args() if argv == [] else parser.parse_args(argv)
+
+    # Use FP32 precision for FP32, INT8, INT4 CPU models, use FP16 precision for FP16 and INT4 GPU models
+    args.precision = (
+        "fp32"
+        if args.precision in {"int8", "fp32"} or (args.precision == "int4" and args.execution_provider == "cpu")
+        else "fp16"
+    )
+    return args
+
+
+def main(argv: list[str] = []):  # noqa: B006
+    args = get_args(argv)
+    setup_logger(args.verbose)
+    logger.info(f"Arguments: {args}")
+    rank = get_rank()
+
+    # Load model and config
+    setattr(args, "use_fp16", args.precision == "fp16")  # noqa: B010
+    args.rank = rank
+    setattr(args, "device_name", "cpu" if args.execution_provider == "cpu" else f"cuda:{rank}")  # noqa: B010
+    setattr(args, "device", torch.device(args.device_name))  # noqa: B010
+    use_auth_token = args.torch_model_directory == os.path.join(".")
+    location = args.model_name if use_auth_token else args.torch_model_directory
+
+    kv_cache_ortvalues = {}
+    if not args.merged:
+        verify_parity(args, location, use_auth_token, kv_cache_ortvalues)
+    else:
+        config = llama = None
+        if not args.small_gpu:
+            config, llama = setup_torch_model(
+                args,
+                location,
+                use_auth_token,
+                torch_dtype=(torch.float16 if args.use_fp16 else torch.float32),
+                device=args.device,
+            )
+
+        # Verify prompt processing in merged model (decoder_model.onnx)
+        args.use_past_kv = False
+        kv_cache_ortvalues = verify_parity(
+            args, location, use_auth_token, kv_cache_ortvalues, pytorch_model=llama, config=config
+        )
+
+        # Verify token generation in merged model (decoder_with_past_model.onnx)
+        args.use_past_kv = True
+        verify_parity(args, location, use_auth_token, kv_cache_ortvalues, pytorch_model=llama, config=config)
+
+
+if __name__ == "__main__":
+    seed = 2
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_torch.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_torch.py
new file mode 100644
index 0000000000000000000000000000000000000000..41d6b8afedc078f30016b95aa5f53e5c6e2311e7
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/llama_torch.py
@@ -0,0 +1,47 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import logging
+import os
+
+import torch
+from dist_settings import barrier, get_rank, get_size
+from transformers import AutoConfig, AutoModelForCausalLM
+
+logger = logging.getLogger("")
+
+
+def setup_torch_model(args, location, auth, torch_dtype=torch.float32, device=None):
+    world_size = get_size()
+    logger.info(f"world_size: {world_size}")
+    rank = get_rank()
+    barrier()
+
+    if not os.path.exists(args.cache_dir):
+        os.makedirs(args.cache_dir, exist_ok=True)
+
+    for i in range(world_size):
+        if i == rank % (world_size):
+            l_config = AutoConfig.from_pretrained(
+                location, use_auth_token=auth, cache_dir=args.cache_dir, trust_remote_code=auth
+            )
+            l_config.use_cache = True
+            l_config._attn_implementation = "eager"  # "eager" uses LlamaAttention for attention layer
+            llama = AutoModelForCausalLM.from_pretrained(
+                location,
+                use_auth_token=auth,
+                trust_remote_code=auth,
+                config=l_config,
+                torch_dtype=torch_dtype,
+                cache_dir=args.cache_dir,
+            )
+            if world_size > 1:
+                llama.parallel_model()
+            if device:
+                llama.to(device)
+            llama.eval()
+            llama.requires_grad_(False)
+        barrier()
+    return l_config, llama
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/quant_kv_dataloader.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/quant_kv_dataloader.py
new file mode 100644
index 0000000000000000000000000000000000000000..c9e609fc3a0058d872ed35fd3df2cd4c439bd991
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/llama/quant_kv_dataloader.py
@@ -0,0 +1,108 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import argparse
+
+import numpy as np
+import torch
+from benchmark_helper import create_onnxruntime_session
+from datasets import load_dataset
+from llama_inputs import get_position_ids
+from torch.nn.functional import pad
+from torch.utils.data import DataLoader
+from transformers import LlamaTokenizer
+
+
+class QuantKVDataLoader:
+    def __init__(self, args: argparse.Namespace, onnx_model_path: str = ""):
+        self.batch_size = 1
+        self.pad_max = args.pad_max
+
+        tokenizer = LlamaTokenizer.from_pretrained(args.original_model_name, use_auth_token=args.use_auth_token)
+        dataset = load_dataset(args.smooth_quant_dataset, split="train")
+        dataset = dataset.map(lambda examples: tokenizer(examples["text"]), batched=True)
+        dataset.set_format(type="torch", columns=["input_ids", "attention_mask"])
+
+        self.dataloader = DataLoader(
+            dataset,
+            batch_size=self.batch_size,
+            shuffle=False,
+            collate_fn=self.collate_batch,
+        )
+        self.decoder_model = (
+            create_onnxruntime_session(
+                onnx_model_path,
+                args.execution_provider != "cpu",  # use_gpu
+                provider=args.execution_provider,
+                verbose=args.verbose,
+            )
+            if onnx_model_path
+            else None
+        )
+
+    def collate_batch(self, batch):
+        input_ids_batched = []
+        attention_mask_batched = []
+        position_ids_batched = []
+        labels = []
+
+        for text in batch:
+            # Set inputs for model
+            input_ids = text["input_ids"]
+            attention_mask = torch.ones(len(input_ids))
+            position_ids = get_position_ids(attention_mask, use_past_kv=False)
+            label = len(input_ids) - 1
+
+            # Pad input data because all model inputs must have same shape
+            pad_len = self.pad_max - input_ids.shape[0]
+            input_ids = pad(input_ids, (0, pad_len), value=1)
+            attention_mask = pad(attention_mask, (0, pad_len), value=0)
+            position_ids = pad(position_ids, (0, pad_len), value=0)
+
+            input_ids_batched.append(input_ids)
+            attention_mask_batched.append(attention_mask)
+            position_ids_batched.append(position_ids)
+            labels.append(label)
+
+        input_ids_batched = torch.vstack(input_ids_batched)
+        attention_mask_batched = torch.vstack(attention_mask_batched)
+        position_ids_batched = torch.vstack(position_ids_batched)
+        labels = torch.tensor(labels)
+
+        return (input_ids_batched, attention_mask_batched, position_ids_batched), labels
+
+    def __iter__(self):
+        try:
+            for (input_ids, attention_mask, position_ids), labels in self.dataloader:
+                # Inputs for decoder_model.onnx
+                inputs = {
+                    "input_ids": input_ids[:, :-1].detach().cpu().numpy().astype(np.int64),
+                    "attention_mask": attention_mask[:, :-1].detach().cpu().numpy().astype(np.int64),
+                    "position_ids": position_ids[:, :-1].detach().cpu().numpy().astype(np.int64),
+                }
+                label = labels.detach().cpu().numpy()
+
+                if self.decoder_model is not None:
+                    # Run decoder_model.onnx to get inputs for decoder_with_past_model.onnx
+                    outputs = self.decoder_model.run(None, inputs)
+
+                    for i in range(int((len(outputs) - 1) / 2)):
+                        inputs[f"past_key_values.{i}.key"] = outputs[i * 2 + 1]
+                        inputs[f"past_key_values.{i}.value"] = outputs[i * 2 + 2]
+                    past_sequence_length = inputs["past_key_values.0.key"].shape[2]
+
+                    inputs["input_ids"] = input_ids[:, -1].unsqueeze(0).detach().cpu().numpy().astype(np.int64)
+                    attn_mask_torch = torch.ones((self.batch_size, past_sequence_length + 1), dtype=torch.int64)
+                    inputs["attention_mask"] = attn_mask_torch.detach().cpu().numpy().astype(np.int64)
+                    inputs["position_ids"] = (
+                        get_position_ids(attn_mask_torch, use_past_kv=True).detach().cpu().numpy().astype(np.int64)
+                    )
+
+                # Yield (inputs, label) tuple for Intel's Neural Compressor:
+                # https://github.com/intel/neural-compressor/blob/d4baed9ea11614e1f0dc8a1f4f55b73ed3ed585c/neural_compressor/quantization.py#L55-L62
+                yield (inputs, label)
+
+        except StopIteration:
+            return
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ef71ce9e355e17ea1c2ca9fb648951d917734b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/benchmark_longformer.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/benchmark_longformer.py
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+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/benchmark_longformer.py
@@ -0,0 +1,821 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+#
+# This script run benchmark of latency or peak memory usage of Longformer model inference.
+# Please run convert_to_onnx.py to get onnx model before running benchmark.
+#
+# It is tested with python 3.8, onnxruntime-gpu 1.11.0, PyTorch 1.11.0, transformers 4.18.0, CUDA 11.3 like:
+#   conda create -n gpu_env python=3.8
+#   conda activate gpu_env
+#   pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
+#   pip3 install onnx transformers onnxruntime-gpu numpy sympy psutil py3nvml
+#   python benchmark_longformer.py
+#
+# When there is no parameter, pre-defined tests will run on the longformer-base-4096 model.
+
+# Benchmark the latency:
+#   python benchmark_longformer.py --model longformer-base-4096 --batch_sizes 1 --sequence_lengths 512 1024 2048 4096 \
+#          --global_lengths 8 --onnx ./longformer-base-4096_fp16.onnx -t 100
+#
+# Benchmark GPU peak memory:
+#   export ORT_LONGFORMER_COMPACT_MEMORY=0
+#   python benchmark_longformer.py --model longformer-base-4096 --batch_sizes 1 --sequence_lengths 4096 \
+#          --global_lengths 8 --onnx ./longformer-base-4096_fp32.onnx --memory -t 10 --engine onnxruntime
+#   export ORT_LONGFORMER_COMPACT_MEMORY=1
+#   python benchmark_longformer.py --model longformer-base-4096 --batch_sizes 1 --sequence_lengths 4096 \
+#          --global_lengths 8 --onnx ./longformer-base-4096_fp32.onnx --memory -t 10 --engine onnxruntime
+#
+# By default, compact memory kernel is enabled. To disable it, set environment variable ORT_LONGFORMER_COMPACT_MEMORY=0.
+
+import argparse
+import csv
+import logging
+import math
+import os
+import re
+import sys
+import timeit
+import traceback
+from concurrent.futures import ProcessPoolExecutor
+from datetime import datetime
+from typing import Any
+
+import benchmark_helper
+import numpy as np
+import torch
+from longformer_helper import PRETRAINED_LONGFORMER_MODELS, LongformerHelper, LongformerInputs
+from transformers import LongformerModel
+
+import onnxruntime
+
+logger = logging.getLogger("")
+
+
+def test_torch_latency(
+    device,
+    model,
+    model_name,
+    batch_sizes,
+    sequence_lengths,
+    global_lengths,
+    test_times,
+    num_threads,
+) -> list[dict[str, Any]]:
+    if num_threads > 0:
+        torch.set_num_threads(num_threads)
+
+    results = []
+    for batch_size in batch_sizes:
+        for sequence_length in sequence_lengths:
+            for global_length in global_lengths:
+                logger.info(f"batch_size={batch_size} sequence_length={sequence_length} global_length={global_length}")
+                inputs: LongformerInputs = LongformerHelper.get_dummy_inputs(
+                    batch_size, sequence_length, global_length, device
+                )
+                input_list = inputs.to_list()
+
+                _ = model(*input_list)
+                runtimes = timeit.repeat(lambda: model(*input_list), repeat=test_times, number=1)  # noqa: B023
+                result = {
+                    "engine": "torch",  # TODO: test torchscript
+                    "version": torch.__version__,
+                    "device": "cuda",
+                    "optimizer": "",
+                    "precision": "fp32",
+                    "io_binding": "",
+                    "model_name": model_name,
+                    "description": model_name + " [torch]",
+                    "inputs": 3,
+                    "threads": num_threads,
+                    "batch_size": batch_size,
+                    "sequence_length": sequence_length,
+                    "global_length": global_length,
+                    "datetime": str(datetime.now()),
+                    "memory": "NA",
+                    "diff_max": 0,
+                    "diff_90_percentile": 0,
+                    "diff_95_percentile": 0,
+                    "diff_99_percentile": 0,
+                    "use_compact_memory": "NA",
+                }
+                result.update(benchmark_helper.get_latency_result(runtimes, batch_size))
+                logger.info("%s", result)
+                results.append(result)
+    return results
+
+
+def test_parity(device, model, ort_session, batch_size, sequence_length, global_length, verbose=True):
+    parameters = f"batch_size={batch_size} sequence_length={sequence_length} global_length={global_length}"
+    logger.info(f"Comparing Torch and ORT outputs for {parameters}...")
+    dummy_inputs: LongformerInputs = LongformerHelper.get_dummy_inputs(
+        batch_size, sequence_length, global_length, device
+    )
+    ort_inputs = dummy_inputs.get_ort_inputs()
+    ort_outputs = ort_session.run(None, ort_inputs)
+    input_list = dummy_inputs.to_list()
+    torch_outputs = model(*input_list)
+    max_diff = np.amax(torch_outputs[0].cpu().numpy() - ort_outputs[0])
+    logger.info(f"last_state max diff = {max_diff}")
+    if verbose and (math.isnan(max_diff) or max_diff > 0.001):
+        print("torch last_state:", torch_outputs[0])
+        print("ort last_state:", ort_outputs[0])
+    return float(max_diff)
+
+
+def test_ort_latency(
+    device,
+    model,
+    model_name,
+    description,
+    ort_session,
+    batch_sizes,
+    sequence_lengths,
+    global_lengths,
+    test_times,
+    num_threads,
+    optimizer=False,
+    precision="fp32",
+    disable_io_binding=False,
+    verbose=True,
+    use_compact_memory=False,
+    use_half4=False,
+    disable_parity=False,
+) -> list[dict[str, Any]]:
+    results = []
+    for batch_size in batch_sizes:
+        for sequence_length in sequence_lengths:
+            for global_length in global_lengths:
+                assert global_length <= model.config.attention_window[0], (
+                    "Limitation of current implementation: number of global token <= attention_window"
+                )
+
+                logger.info(
+                    f"Testing batch_size={batch_size} sequence_length={sequence_length} global_length={global_length} "
+                    f"optimizer={optimizer}, precision={precision} io_binding={not disable_io_binding}..."
+                )
+                dummy_inputs: LongformerInputs = LongformerHelper.get_dummy_inputs(
+                    batch_size, sequence_length, global_length, device
+                )
+
+                # Run OnnxRuntime
+                ort_inputs = dummy_inputs.get_ort_inputs()
+
+                if verbose:
+                    print(ort_inputs)
+
+                # run one query for warm up
+                ort_outputs = ort_session.run(None, ort_inputs)
+
+                result_template = {
+                    "model_name": model_name,
+                    "description": description,
+                    "inputs": 3,
+                    "engine": "OnnxRuntime",
+                    "version": str(onnxruntime.__version__),
+                    "device": "cuda",
+                    "precision": str(precision),
+                    "optimizer": int(optimizer),
+                    "threads": int(num_threads),
+                    "batch_size": int(batch_size),
+                    "sequence_length": int(sequence_length),
+                    "global_length": int(global_length),
+                    "test_times": int(test_times),
+                    "datetime": str(datetime.now()),
+                    "memory": "",
+                    "diff_max": None,
+                    "diff_90_percentile": None,
+                    "diff_95_percentile": None,
+                    "diff_99_percentile": None,
+                    "use_compact_memory": use_compact_memory,
+                    "use_half4": use_half4,
+                }
+
+                if not disable_io_binding:
+                    max_last_state_size = max(batch_sizes) * max(sequence_lengths) * model.config.hidden_size
+                    max_pooler_size = max(batch_sizes) * max(sequence_lengths)
+                    result = benchmark_helper.inference_ort_with_io_binding(
+                        ort_session,
+                        ort_inputs,
+                        result_template=result_template,
+                        repeat_times=test_times,
+                        ort_output_names=["last_state", "pooler"],
+                        ort_outputs=ort_outputs,
+                        output_buffers=[],
+                        output_buffer_max_sizes=[max_last_state_size, max_pooler_size],
+                        batch_size=batch_size,
+                        device=device,
+                        data_type=np.longlong,  # input data type
+                    )
+                else:
+                    result = benchmark_helper.inference_ort(
+                        ort_session,
+                        ort_inputs,
+                        result_template=result_template,
+                        repeat_times=test_times,
+                        batch_size=batch_size,
+                    )
+
+                # measure result difference between PyTorch and OnnxRuntime
+                if not disable_parity:
+                    diff_results = [
+                        test_parity(
+                            device,
+                            model,
+                            ort_session,
+                            batch_size,
+                            sequence_length,
+                            global_length,
+                            verbose,
+                        )
+                        for _ in range(test_times)
+                    ]
+
+                    result["diff_max"] = max(diff_results)
+                    result["diff_90_percentile"] = np.percentile(diff_results, 90)
+                    result["diff_95_percentile"] = np.percentile(diff_results, 95)
+                    result["diff_99_percentile"] = np.percentile(diff_results, 99)
+
+                results.append(result)
+    return results
+
+
+def test_ort_memory(
+    device,
+    onnx_model_path,
+    batch_size,
+    sequence_length,
+    global_length,
+    test_times,
+    num_threads,
+) -> dict[str, Any]:
+    logger.info(
+        f"Testing memory for model={onnx_model_path}, batch_size={batch_size}, sequence_length={sequence_length}, "
+        f"global_length={global_length}, test_times={test_times}, num_threads={num_threads}"
+    )
+
+    def inference():
+        # Update Arena strategy so that we can measure the minimum memory required
+        cuda_provider_options = {"arena_extend_strategy": "kSameAsRequested"}
+        provider_options = {"CUDAExecutionProvider": cuda_provider_options}
+        session = benchmark_helper.create_onnxruntime_session(
+            onnx_model_path,
+            use_gpu=True,
+            enable_all_optimization=True,
+            num_threads=num_threads,
+            provider_options=provider_options,
+        )
+
+        dummy_inputs: LongformerInputs = LongformerHelper.get_dummy_inputs(
+            batch_size, sequence_length, global_length, device
+        )
+        ort_inputs = dummy_inputs.get_ort_inputs()
+        for _ in range(test_times):
+            _ = session.run(None, ort_inputs)
+
+    memory_used = benchmark_helper.measure_memory(is_gpu=True, func=inference)
+
+    return {
+        "onnx_model": onnx_model_path,
+        "batch_size": batch_size,
+        "sequence_length": sequence_length,
+        "global_length": global_length,
+        "test_times": test_times,
+        "num_threads": num_threads,
+        "memory": memory_used,
+    }
+
+
+def load_torch_model(model_name, device):
+    torch_model_name_or_dir = PRETRAINED_LONGFORMER_MODELS.get(model_name, model_name)
+    model = LongformerModel.from_pretrained(torch_model_name_or_dir)
+    model.to(device)
+    return model
+
+
+def find_onnx_model(model_name, onnx_dir="."):
+    # Search onnx model in the following order: optimized fp16 model, optimized fp32 model, raw model
+    onnx_model_path = os.path.join(onnx_dir, model_name + ".onnx")
+    optimized_fp32_model = os.path.join(onnx_dir, model_name + "_fp32.onnx")
+    optimized_fp16_model = os.path.join(onnx_dir, model_name + "_fp16.onnx")
+    if os.path.isfile(optimized_fp16_model):
+        onnx_model_path = optimized_fp16_model
+    elif os.path.isfile(optimized_fp32_model):
+        onnx_model_path = optimized_fp32_model
+    return onnx_model_path
+
+
+def test_memory(args, device) -> dict[str, Any]:
+    if len(args.batch_sizes) > 1:
+        raise RuntimeError("For memory test, only one batch_size (-b) is allowed.")
+    if len(args.sequence_lengths) > 1:
+        raise RuntimeError("For memory test, only one sequence_length (-s) is allowed.")
+    if len(args.global_lengths) > 1:
+        raise RuntimeError("For memory test, only one global_length (-g) is allowed.")
+
+    model_name = args.model
+    onnx_model_path = find_onnx_model(model_name) if not args.onnx else args.onnx
+
+    torch.cuda.empty_cache()
+    return test_ort_memory(
+        device,
+        onnx_model_path,
+        args.batch_sizes[0],
+        args.sequence_lengths[0],
+        args.global_lengths[0],
+        args.test_times,
+        args.num_threads,
+    )
+
+
+def test_ort(args, device) -> list[dict[str, Any]]:
+    model_name = args.model
+
+    onnx_model_path = find_onnx_model(model_name) if not args.onnx else args.onnx
+
+    optimized = onnx_model_path.endswith("_fp16.onnx") or onnx_model_path.endswith("_fp32.onnx")  # noqa: PIE810
+    precision = "fp32" if not onnx_model_path.endswith("_fp16.onnx") else "fp16"
+
+    model = load_torch_model(model_name, device)
+
+    num_threads = args.num_threads
+
+    cuda_provider_options = {"arena_extend_strategy": "kSameAsRequested"}
+    provider_options = {"CUDAExecutionProvider": cuda_provider_options}
+    session = benchmark_helper.create_onnxruntime_session(
+        onnx_model_path,
+        use_gpu=True,
+        enable_all_optimization=True,
+        num_threads=num_threads,
+        provider_options=provider_options,
+    )
+    if session is None:
+        raise RuntimeError(f"Failed to create ORT session from ONNX file {onnx_model_path}")
+
+    use_compact_memory = os.environ.get("ORT_LONGFORMER_COMPACT_MEMORY", "1") == "1"
+    description = onnx_model_path
+    if not use_compact_memory:
+        description += "[non_compact_memory]"
+
+    if args.use_half4:
+        description += "[half4]" if precision == "fp16" else "[float4]"
+    else:
+        description += "[half2]" if precision == "fp16" else "[float4]"
+
+    return test_ort_latency(
+        device,
+        model,
+        model_name,
+        description,
+        session,
+        args.batch_sizes,
+        args.sequence_lengths,
+        args.global_lengths,
+        args.test_times,
+        num_threads,
+        optimized,
+        precision,
+        args.disable_io_binding,
+        args.verbose,
+        use_compact_memory,
+        args.use_half4,
+        args.disable_parity,
+    )
+
+
+def test_torch(args, device) -> list[dict[str, Any]]:
+    model = load_torch_model(args.model, device)
+    return test_torch_latency(
+        device,
+        model,
+        args.model,
+        args.batch_sizes,
+        args.sequence_lengths,
+        args.global_lengths,
+        args.test_times,
+        args.num_threads,
+    )
+
+
+def test_latency(args, device) -> list[dict[str, Any]]:
+    if args.engine == "onnxruntime":
+        return test_ort(args, device)
+
+    return test_torch(args, device)
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model",
+        required=False,
+        type=str,
+        default="longformer-base-4096",
+        help="Checkpoint directory or pre-trained model names in the list: "
+        + ", ".join(PRETRAINED_LONGFORMER_MODELS.keys()),
+    )
+
+    parser.add_argument(
+        "-e",
+        "--engine",
+        required=False,
+        type=str,
+        default="onnxruntime",
+        choices=["onnxruntime", "torch"],
+        help="Engine to benchmark.",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--test_times",
+        required=False,
+        default=1000,
+        type=int,
+        help="Number of repeat times to get average inference latency.",
+    )
+
+    parser.add_argument("-b", "--batch_sizes", nargs="+", type=int, default=[1])
+
+    # If --export_padding is not used in exporting onnx model, there is no padding in ONNX model,
+    # and you will need padding inputs by yourself before running onnx model.
+    # Here, we only test sequence length that is multiple of attention window size.
+    parser.add_argument(
+        "-s",
+        "--sequence_lengths",
+        nargs="+",
+        type=int,
+        default=[512, 1024, 2048, 4096],
+        help="Sequence lengths. It could have multiple values in latency test."
+        "If --export_padding is not used, sequence length shall be multiple of window size.",
+    )
+
+    parser.add_argument("--onnx", required=False, type=str, default=None, help="Onnx model path")
+
+    parser.add_argument(
+        "-g",
+        "--global_lengths",
+        nargs="+",
+        type=int,
+        default=[0],
+        help="Number of global tokens. It could have multiple values in latency test.",
+    )
+
+    parser.add_argument(
+        "-n",
+        "--num_threads",
+        required=False,
+        type=int,
+        default=0,
+        help="Threads to use.",
+    )
+
+    parser.add_argument(
+        "--disable_io_binding",
+        required=False,
+        action="store_true",
+        help="Do not use IO Binding.",
+    )
+
+    parser.add_argument(
+        "--memory",
+        required=False,
+        action="store_true",
+        help="Test memory usage instead of latency.",
+    )
+
+    parser.add_argument("--verbose", required=False, action="store_true", help="Print more information.")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument("--use_half4", required=False, action="store_true", help="Use half4 kernel.")
+    parser.set_defaults(use_half4=False)
+
+    parser.add_argument("--disable_parity", required=False, action="store_true", help="Do not run parity test.")
+    parser.set_defaults(disable_parity=False)
+
+    args = parser.parse_args(argv)
+
+    return args
+
+
+def output_details(results, csv_filename):
+    latency_results = [result for result in results if "average_latency_ms" in result]
+    if len(latency_results) == 0:
+        print("No latency results for output.")
+        return
+
+    with open(csv_filename, mode="a", newline="", encoding="ascii") as csv_file:
+        column_names = [
+            "engine",
+            "version",
+            "device",
+            "precision",
+            "optimizer",
+            "io_binding",
+            "model_name",
+            "inputs",
+            "threads",
+            "datetime",
+            "test_times",
+            "description",
+            "batch_size",
+            "sequence_length",
+            "global_length",
+            "use_compact_memory",
+            "use_half4",
+            "diff_max",
+            "diff_90_percentile",
+            "diff_95_percentile",
+            "diff_99_percentile",
+            "memory",
+            "QPS",
+            "average_latency_ms",
+            "latency_variance",
+            "latency_90_percentile",
+            "latency_95_percentile",
+            "latency_99_percentile",
+        ]
+
+        csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+        csv_writer.writeheader()
+        for result in latency_results:
+            print(result)
+            csv_writer.writerow(result)
+
+        csv_file.flush()
+
+    print(f"Detail results are saved to csv file: {csv_filename}")
+
+
+def run(args) -> list[dict[str, Any]]:
+    torch.set_grad_enabled(False)
+
+    # set random seed manually to get deterministic results
+    benchmark_helper.set_random_seed(123)
+
+    # Currently, the longformer attention operator could only run in GPU (no CPU implementation yet).
+    device = torch.device("cuda:0")
+
+    if args.memory:
+        return [test_memory(args, device)]  # Convert to List so that return type is same as test_latency
+
+    return test_latency(args, device)
+
+
+def launch_test(arguments) -> list[dict[str, Any]]:
+    if not torch.cuda.is_available():
+        raise RuntimeError("Please install PyTorch with Cuda, and use a machine with GPU for testing gpu performance.")
+
+    with ProcessPoolExecutor() as executor:
+        results = list(executor.map(run, [arguments]))
+        assert len(results) == 1
+        return results[0]
+
+
+def run_tests(
+    use_compact_memory=True,
+    run_torch=False,
+    run_memory=True,
+    use_io_binding=True,
+    use_fp16=True,
+    use_merged_qkv_weights=True,
+    use_half4=True,
+    batch_size=1,
+):
+    compact_memory = "1" if use_compact_memory else "0"
+    os.environ["ORT_LONGFORMER_COMPACT_MEMORY"] = compact_memory
+    logger.info(f"ORT_LONGFORMER_COMPACT_MEMORY={compact_memory}")
+
+    os.environ["ORT_LONGFORMER_USE_HALF4"] = "1" if use_half4 else "0"
+    logger.info("ORT_LONGFORMER_USE_HALF4={}".format("1" if use_half4 else "0"))  # noqa: G001
+
+    results = []
+    test_times = 1000
+    sequence_lengths = [4096, 2048, 1024, 512]
+    batch_sizes = [batch_size]
+    for model_name in ["longformer-base-4096"]:
+        for batch_size in batch_sizes:
+            for sequence_length in sequence_lengths:
+                for global_length in [16]:
+                    if run_torch:
+                        engine_name = "torch"
+                        args = parse_arguments(
+                            f"-e {engine_name} -t {test_times} -b {batch_size} -s {sequence_length} -g {global_length} "
+                            f"-t {test_times} -m {model_name}".split(" ")
+                        )
+                        results += run(args)
+
+                    engine_name = "onnxruntime"
+                    file_format = 1 if use_merged_qkv_weights else 0
+                    onnx_path = (
+                        f"{model_name}_f{file_format}_fp16.onnx"
+                        if use_fp16
+                        else f"{model_name}_f{file_format}_fp32.onnx"
+                    )
+                    if not os.path.exists(onnx_path):
+                        raise RuntimeError(f"onnx file not exists:{onnx_path}")
+
+                    arguments = (
+                        f"-e {engine_name} --onnx {onnx_path} "
+                        f"-b {batch_size} -s {sequence_length} -g {global_length} -m {model_name}"
+                    )
+
+                    if not use_io_binding:
+                        arguments += " --disable_io_binding"
+
+                    if use_half4:
+                        arguments += " --use_half4"
+
+                    # Disable parity test to avoid out of memory for large batch size
+                    if batch_size >= 4:
+                        arguments += " --disable_parity"
+
+                    memory_results = None
+                    try:
+                        if run_memory:
+                            args = parse_arguments(f"{arguments} -t 10 --memory".split(" "))
+                            memory_results = launch_test(args)
+
+                        args = parse_arguments(f"{arguments} -t {test_times}".split(" "))
+                        latency_results = launch_test(args)
+                    except KeyboardInterrupt as exc:
+                        raise RuntimeError("Keyboard Interrupted") from exc
+                    except Exception:
+                        traceback.print_exc()
+                        continue
+
+                    if len(latency_results) == 1:
+                        latency_results[0]["memory"] = memory_results[0]["memory"] if memory_results else "N/A"
+                    else:
+                        raise RuntimeError("length of latency_results should be 1")
+
+                    logger.info("%s", latency_results)
+
+                    results += latency_results
+    return results
+
+
+def output_summary(results, csv_filename, data_field="average_latency_ms"):
+    with open(csv_filename, mode="a", newline="", encoding="ascii") as csv_file:
+        header_names = [
+            "model_name",
+            "precision",
+            "engine",
+            "version",
+            "global_length",
+            "use_compact_memory",
+            "use_half4",
+            "description",
+        ]
+
+        description_list = list({result["description"] for result in results})
+        description_list.sort()
+
+        batch_sizes = list({result["batch_size"] for result in results})
+        batch_sizes.sort()
+
+        sequence_lengths = list({result["sequence_length"] for result in results})
+        sequence_lengths.sort()
+
+        data_names = []
+        for sequence_length in sequence_lengths:
+            for batch_size in batch_sizes:
+                data_names.append(f"b{batch_size}_s{sequence_length}")
+
+        csv_writer = csv.DictWriter(csv_file, fieldnames=header_names + data_names)
+        csv_writer.writeheader()
+
+        for description in description_list:
+            row = {}
+
+            sum_latency = {}
+            sum_latency.update(dict.fromkeys(data_names, 0))
+
+            count_latency = {}
+            count_latency.update(dict.fromkeys(data_names, 0))
+
+            for result in results:
+                if result["description"] == description and result[data_field]:
+                    headers = {k: v for k, v in result.items() if k in header_names}
+                    if not row:
+                        row.update(headers)
+                    else:
+                        for k in header_names:
+                            if row[k] != headers[k]:
+                                raise RuntimeError("Description shall be unique")
+
+                    batch_size = result["batch_size"]
+                    sequence_length = result["sequence_length"]
+                    key = f"b{batch_size}_s{sequence_length}"
+
+                    try:
+                        latency = float(result[data_field])
+                    except ValueError:
+                        continue
+
+                    sum_latency[key] += latency
+                    count_latency[key] += 1
+
+            if row:
+                for key in data_names:
+                    if key in count_latency and count_latency[key] > 0:
+                        row[key] = sum_latency[key] / count_latency[key]
+                    else:
+                        row[key] = ""
+
+                csv_writer.writerow(row)
+
+        csv_file.flush()
+
+
+def run_experiments(use_fp16, batch_size, is_baseline=False):
+    """Run experiments to compare different algorithms on one batch size"""
+    test_results = run_tests(
+        use_fp16=use_fp16,
+        use_merged_qkv_weights=True,
+        use_half4=False,
+        batch_size=batch_size,
+    )
+
+    if is_baseline:
+        return test_results
+
+    if use_fp16:
+        test_results += run_tests(
+            use_fp16=use_fp16,
+            use_merged_qkv_weights=True,
+            use_half4=True,
+            batch_size=batch_size,
+        )
+
+        test_results += run_tests(
+            use_fp16=use_fp16,
+            use_merged_qkv_weights=False,
+            use_half4=True,
+            batch_size=batch_size,
+        )
+
+    test_results += run_tests(
+        use_fp16=use_fp16,
+        use_merged_qkv_weights=False,
+        use_half4=False,
+        batch_size=batch_size,
+    )
+
+    return test_results
+
+
+def main():
+    torch.multiprocessing.set_start_method("spawn")
+
+    args = parse_arguments()
+
+    benchmark_helper.setup_logger(args.verbose)
+
+    if len(sys.argv) > 1:
+        test_results = launch_test(args)
+        time_stamp = datetime.now().strftime("%Y%m%d-%H%M%S")
+        csv_filename = f"benchmark_detail_{time_stamp}.csv"
+        output_details(test_results, csv_filename)
+        return
+
+    gpu_list = benchmark_helper.get_gpu_info()
+    logger.info("GPU info: %s", gpu_list)
+    fp16_batch_sizes = [16, 8, 4, 2, 1]
+    fp32_batch_sizes = [4, 2, 1]
+    if gpu_list and gpu_list[0]["total"] >= 32 * 1024 * 1024 * 1024:  # 32 GB
+        fp16_batch_sizes = [64, 32, 16, 8, 4, 2, 1]
+        fp32_batch_sizes = [16, 8, 4, 2, 1]
+
+    gpu_name = re.sub(r"(?u)[^-\w.]", "_", gpu_list[0]["name"]) if gpu_list else "gpu"
+    is_baseline = os.environ.get("ORT_LONGFORMER_BASELINE", "0") == "1"
+    experiment_name = f"longformer_base_{gpu_name}" + ("_baseline" if is_baseline else "")
+    logger.info(
+        f"experiment_name={experiment_name}, fp16_batch_sizes={fp16_batch_sizes}, fp32_batch_sizes={fp32_batch_sizes}"
+    )
+
+    total_runs = 1
+    all_results = []
+    for _ in range(total_runs):
+        for batch_size in fp16_batch_sizes:
+            fp16_results = run_experiments(use_fp16=True, batch_size=batch_size, is_baseline=is_baseline)
+            output_details(fp16_results, "longformer_base_fp16.csv")
+            all_results += fp16_results
+    for metric_name in ["average_latency_ms", "QPS", "memory", "diff_90_percentile"]:
+        output_summary(all_results, f"{experiment_name}_{metric_name}.csv", metric_name)
+
+    all_results = []
+    for _ in range(total_runs):
+        for batch_size in fp32_batch_sizes:
+            fp32_results = run_experiments(use_fp16=False, batch_size=batch_size, is_baseline=is_baseline)
+            output_details(fp32_results, "longformer_base_fp32.csv")
+            all_results += fp32_results
+    for metric_name in ["average_latency_ms", "QPS", "memory", "diff_90_percentile"]:
+        output_summary(all_results, f"{experiment_name}_{metric_name}.csv", metric_name)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4c4f401123090b22143c051cc69380e255d331e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/convert_to_onnx.py
@@ -0,0 +1,413 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+# This script converts Longformer model from huggingface transformers 4.0 or later to ONNX.
+# It translates LongformerSelfAttention to the LongformerAttention operator in ONNX Runtime.
+#
+# Before running this script, prepare a python environment in Linux with PyTorch 1.9.0 and other packages installed.
+# Then run "python setup.py install" in ./torch_extensions directory. If your python version is not 3.8, you will need
+# update this script with correct name of longformer_attention.cpython-*.so (search TODO below).
+#
+# It is tested in Ubuntu 18.04 with python 3.8, onnxruntime-gpu 1.11.0, PyTorch 1.9.0, transformers 4.18.0.
+# Warning: Using  PyTorch 1.10 or newer version might encounter issue in exporting, but they are fine for benchmarking.
+#
+# Example commands to export longformer base model in Linux:
+#   conda create -n longformer python=3.8
+#   conda activate longformer
+#   python3 -m pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
+#   python3 -m pip install flatbuffers numpy packaging sympy protobuf==3.20.1 onnx==1.12.0 transformers==4.18.0
+#   python3 -m pip install -i https://test.pypi.org/simple/ ort-nightly-gpu
+#   cd ./torch_extensions
+#   rm -rf build
+#   python setup.py install
+#   cd ..
+#   python convert_to_onnx.py --model longformer-base-4096 --precision fp16 --optimize_onnx
+#   python convert_to_onnx.py --model longformer-base-4096 --precision fp16 --optimize_onnx --no_merge_qkv
+#
+# GPU is not needed for this script. You can run it in CPU. For --optimize_onnx, you can use either onnxruntime or onnxruntime-gpu package.
+#
+# For inference of the onnx model, you will need onnxruntime-gpu 1.7.0 or newer version.
+
+import argparse
+import inspect
+from pathlib import Path
+
+import torch
+import transformers
+from longformer_helper import PRETRAINED_LONGFORMER_MODELS
+from onnx import load_model
+from onnx_model_bert import BertOnnxModel
+from packaging import version
+from torch.onnx import register_custom_op_symbolic
+from torch.onnx.symbolic_helper import parse_args
+from torch_onnx_export_helper import torch_onnx_export
+from transformers import LongformerModel, LongformerSelfAttention
+
+# Supports format 0 or 1
+weight_bias_format = 0
+
+
+@parse_args("v", "v", "v", "v", "v", "v", "v", "i", "i")
+def my_longformer_attention(
+    g,
+    input,
+    weight,
+    bias,
+    mask,
+    global_weight,
+    global_bias,
+    global_mask,
+    num_heads,
+    window,
+):
+    return g.op(
+        "com.microsoft::LongformerAttention",
+        input,
+        weight,
+        bias,
+        mask,
+        global_weight,
+        global_bias,
+        global_mask,
+        num_heads_i=num_heads,
+        window_i=window,
+    )
+
+
+# namespace is onnxruntime which is registered in longformer_attention.cpp
+register_custom_op_symbolic("onnxruntime::LongformerAttention", my_longformer_attention, 9)
+
+# TODO: search the directory to find correct output filename of "python setup.py install" when python version is not 3.8
+torch.ops.load_library(
+    r"./torch_extensions/build/lib.linux-x86_64-3.8/longformer_attention.cpython-38-x86_64-linux-gnu.so"
+)
+
+
+def parse_arguments():
+    """Parse arguments
+
+    Returns:
+        args: Namespace
+    """
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-m",
+        "--model",
+        required=False,
+        type=str,
+        default="longformer-base-4096",
+        help="Checkpoint directory or pre-trained model names in the list: "
+        + ", ".join(PRETRAINED_LONGFORMER_MODELS.keys()),
+    )
+
+    parser.add_argument(
+        "--export_padding",
+        required=False,
+        action="store_true",
+        help="Export padding logic to ONNX graph. If not enabled, user need pad input so that sequence length is multiple of window size.",
+    )
+    parser.set_defaults(export_padding=False)
+
+    parser.add_argument(
+        "--no_merge_qkv",
+        required=False,
+        action="store_true",
+        help="Stack the weights of q, k and v on dimension 0 instead of dimension 1.",
+    )
+    parser.set_defaults(no_merge_qkv=False)
+
+    parser.add_argument(
+        "-o",
+        "--optimize_onnx",
+        required=False,
+        action="store_true",
+        help="Use optimizer.py to optimize onnx model.",
+    )
+    parser.set_defaults(optimize_onnx=False)
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=False,
+        type=str,
+        default="fp32",
+        choices=["fp32", "fp16"],
+        help="Precision of model to run: fp32 for full precision, fp16 for mixed precision",
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+# Create a dummy input for ONNX export.
+def get_dummy_inputs(config, export_padding, device):
+    # When sequence length is multiple of windows size, there is no padding logic in ONNX graph
+    sequence_length = config.attention_window[0] + 1 if export_padding else config.attention_window[0]
+
+    # Create dummy inputs
+    input_ids = torch.arange(sequence_length).unsqueeze(0).to(device)
+
+    attention_mask = torch.ones(input_ids.shape, dtype=torch.long, device=device)
+    attention_mask[:, sequence_length - 1] = 0  # last token is masked
+
+    global_attention_mask = torch.zeros(input_ids.shape, dtype=torch.long, device=device)
+    global_attention_mask[:, 0] = 1  # first token is global token
+
+    return input_ids, attention_mask, global_attention_mask
+
+
+# A new function to replace LongformerSelfAttention.forward
+# For transformers 4.0.0
+def my_longformer_self_attention_forward_4(
+    self,
+    hidden_states,
+    attention_mask=None,
+    is_index_masked=None,
+    is_index_global_attn=None,
+    is_global_attn=None,
+):
+    global_mask = is_index_global_attn.int()
+    # The following check is based on the dummy inputs (only the first token is global).
+    assert (
+        len(global_mask.shape) == 2
+        and global_mask.shape[0] == 1
+        and global_mask.count_nonzero().item() == 1
+        and global_mask.tolist()[0][0] == 1
+    )
+
+    input_mask = is_index_masked.float()
+    # TODO: The filtering value may be -10000.0 or -inf. Check the huggingface implementation.
+    input_mask = input_mask.masked_fill(is_index_masked, -10000.0)
+    # Yet another way to generate input_mask = torch.masked_fill(attention_mask, is_index_global_attn, 0.0)
+
+    # TODO: add postprocessing of ONNX model to calculate based on graph input: input_mask = (attention_mask - 1) * 10000.0
+    # TODO: add postprocessing of ONNX model to use graph input directly: global_mask = global_attention_mask
+
+    # The following check is based on the dummy inputs (only the last token is masked).
+    assert (
+        len(input_mask.shape) == 2
+        and input_mask.shape[0] == 1
+        and input_mask.count_nonzero().item() == 1
+        and input_mask.tolist()[0][-1] == -10000.0
+    )
+
+    weight = torch.stack(
+        (
+            self.query.weight.transpose(0, 1),
+            self.key.weight.transpose(0, 1),
+            self.value.weight.transpose(0, 1),
+        ),
+        dim=weight_bias_format,
+    )
+
+    if weight_bias_format == 1:
+        # shape is (hidden_size, 3*hidden_size) for format 1, otherwise (3, hidden_size, hidden_size) by default
+        weight = weight.reshape(self.embed_dim, 3 * self.embed_dim)
+
+    global_weight = torch.stack(
+        (
+            self.query_global.weight.transpose(0, 1),
+            self.key_global.weight.transpose(0, 1),
+            self.value_global.weight.transpose(0, 1),
+        ),
+        dim=weight_bias_format,
+    )
+
+    if weight_bias_format == 1:
+        global_weight = global_weight.reshape(self.embed_dim, 3 * self.embed_dim)
+
+    if weight_bias_format == 1:
+        bias = torch.stack((self.query.bias, self.key.bias, self.value.bias), dim=0)
+        bias = bias.reshape(3 * self.embed_dim)
+        global_bias = torch.stack((self.query_global.bias, self.key_global.bias, self.value_global.bias), dim=0)
+        global_bias = global_bias.reshape(3 * self.embed_dim)
+    else:
+        bias = torch.stack(
+            (self.query.bias, self.key.bias, self.value.bias, self.key_global.bias, self.value_global.bias), dim=0
+        )
+        bias = bias.reshape(5 * self.embed_dim)
+        global_bias = self.query_global.bias
+        global_bias = global_bias.reshape(1 * self.embed_dim)
+
+    attn_output = torch.ops.onnxruntime.LongformerAttention(
+        hidden_states,
+        weight,
+        bias,
+        input_mask,
+        global_weight,
+        global_bias,
+        global_mask,
+        self.num_heads,
+        self.one_sided_attn_window_size,
+    )
+
+    assert attn_output.size() == hidden_states.size(), "Unexpected size"
+
+    outputs = (attn_output,)
+    return outputs
+
+
+# For transformers 4.3.0
+def my_longformer_self_attention_forward_4_3(
+    self,
+    hidden_states,
+    attention_mask=None,
+    is_index_masked=None,
+    is_index_global_attn=None,
+    is_global_attn=None,
+    output_attentions=False,
+):
+    assert output_attentions is False
+    return my_longformer_self_attention_forward_4(
+        self,
+        hidden_states,
+        attention_mask,
+        is_index_masked,
+        is_index_global_attn,
+        is_global_attn,
+    )
+
+
+# For transformers 4.3.2 or later versions
+def my_longformer_self_attention_forward_4_3_2(
+    self,
+    hidden_states,
+    attention_mask=None,
+    layer_head_mask=None,
+    is_index_masked=None,
+    is_index_global_attn=None,
+    is_global_attn=None,
+    output_attentions=False,
+):
+    assert output_attentions is False
+    assert layer_head_mask is None
+    return my_longformer_self_attention_forward_4(
+        self,
+        hidden_states,
+        attention_mask,
+        is_index_masked,
+        is_index_global_attn,
+        is_global_attn,
+    )
+
+
+def export_longformer(model: LongformerModel, onnx_model_path: str, export_padding: bool):
+    """Export longformer model to ONNX
+
+    Args:
+        model (LongformerModel): longformer model
+        onnx_model_path (str): output onnx path
+        export_padding (bool): whether export padding logic to ONNX so that input string can be any length.
+
+    Raises:
+        RuntimeError: This tool requires transformers 4.0.0 or later.
+        RuntimeError: LongformerSelfAttention.forward arguments are different.
+    """
+    input_ids, attention_mask, global_attention_mask = get_dummy_inputs(
+        model.config, export_padding, device=torch.device("cpu")
+    )
+
+    _ = model(
+        input_ids,
+        attention_mask=attention_mask,
+        global_attention_mask=global_attention_mask,
+    )
+
+    if version.parse(transformers.__version__) < version.parse("4.0.0"):
+        raise RuntimeError("This tool requires transformers 4.0.0 or later.")
+
+    # Here we replace LongformerSelfAttention.forward using our implementation for exporting ONNX model
+    key = " ".join(inspect.getfullargspec(LongformerSelfAttention.forward).args)
+    args_to_func = {
+        "self hidden_states attention_mask layer_head_mask is_index_masked is_index_global_attn is_global_attn output_attentions": my_longformer_self_attention_forward_4_3_2,
+        "self hidden_states attention_mask is_index_masked is_index_global_attn is_global_attn output_attentions": my_longformer_self_attention_forward_4_3,
+        "self hidden_states attention_mask is_index_masked is_index_global_attn is_global_attn": my_longformer_self_attention_forward_4,
+    }
+
+    if key not in args_to_func:
+        print(
+            "Current arguments",
+            inspect.getfullargspec(LongformerSelfAttention.forward).args,
+        )
+        raise RuntimeError(
+            "LongformerSelfAttention.forward arguments are different. Please install supported version (like transformers 4.3.0)."
+        )
+
+    # Store for restoring later
+    original_forward = LongformerSelfAttention.forward
+
+    LongformerSelfAttention.forward = args_to_func[key]
+
+    example_inputs = (input_ids, attention_mask, global_attention_mask)
+
+    Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+    torch_onnx_export(
+        model,
+        example_inputs,
+        onnx_model_path,
+        opset_version=12,
+        input_names=["input_ids", "attention_mask", "global_attention_mask"],
+        output_names=["last_state", "pooler"],
+        dynamic_axes={
+            "input_ids": {0: "batch_size", 1: "sequence_length"},
+            "attention_mask": {0: "batch_size", 1: "sequence_length"},
+            "global_attention_mask": {0: "batch_size", 1: "sequence_length"},
+            "last_state": {0: "batch_size", 1: "sequence_length"},
+            "pooler": {0: "batch_size", 1: "sequence_length"},
+        },
+        custom_opsets={"com.microsoft": 1},
+    )
+    print(f"ONNX model exported to {onnx_model_path}")
+
+    # Restore original implementation:
+    LongformerSelfAttention.forward = original_forward
+
+
+def optimize_longformer(onnx_model_path: str, fp32_model_path: str, fp16_model_path=None):
+    """Optimize longformer onnx model
+
+    Args:
+        onnx_model_path (str): path of original ONNX model.
+        fp32_model_path (str): path of optimized fp32 model.
+        fp16_model_path (str, optional): path of optimized fp16 model. Defaults to None.
+    """
+    model = load_model(onnx_model_path, format=None, load_external_data=True)
+    optimizer = BertOnnxModel(model)
+    optimizer.optimize()
+
+    use_external_data_format = False
+    if fp32_model_path:
+        optimizer.save_model_to_file(fp32_model_path, use_external_data_format)
+        print(f"optimized fp32 model saved to {fp32_model_path}")
+
+    if fp16_model_path:
+        optimizer.convert_float_to_float16(keep_io_types=True)
+        optimizer.save_model_to_file(fp16_model_path, use_external_data_format)
+        print(f"optimized fp16 model saved to {fp16_model_path}")
+
+
+def main(args):
+    model_name = args.model
+    onnx_model_path = model_name + ".onnx"
+
+    global weight_bias_format  # noqa: PLW0603
+    weight_bias_format = 0 if args.no_merge_qkv else 1
+
+    model = LongformerModel.from_pretrained(PRETRAINED_LONGFORMER_MODELS[model_name])
+
+    export_longformer(model, onnx_model_path, args.export_padding)
+
+    if args.optimize_onnx or args.precision != "fp32":
+        fp32_model_path = model_name + f"_f{weight_bias_format}" + "_fp32.onnx"
+        fp16_model_path = model_name + f"_f{weight_bias_format}" + "_fp16.onnx" if args.precision == "fp16" else None
+        optimize_longformer(onnx_model_path, fp32_model_path, fp16_model_path)
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    main(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/generate_test_data.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/generate_test_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..0955973264d6412c3960e2954009ca742e5f3590
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/generate_test_data.py
@@ -0,0 +1,347 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+# Generate test data for a longformer model, so that we can use onnxruntime_perf_test.exe to evaluate the inference latency.
+
+import argparse
+import os
+import random
+from pathlib import Path
+
+import numpy as np
+from bert_test_data import fake_input_ids_data, fake_input_mask_data, output_test_data
+from onnx import ModelProto, TensorProto
+from onnx_model import OnnxModel
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--model", required=True, type=str, help="bert onnx model path.")
+
+    parser.add_argument(
+        "--output_dir",
+        required=False,
+        type=str,
+        default=None,
+        help="output test data path. If not specified, .",
+    )
+
+    parser.add_argument("--batch_size", required=False, type=int, default=1, help="batch size of input")
+
+    parser.add_argument(
+        "--sequence_length",
+        required=False,
+        type=int,
+        default=128,
+        help="maximum sequence length of input",
+    )
+
+    parser.add_argument(
+        "-a",
+        "--average_sequence_length",
+        default=-1,
+        type=int,
+        help="average sequence length excluding padding",
+    )
+
+    parser.add_argument(
+        "-r",
+        "--random_sequence_length",
+        required=False,
+        action="store_true",
+        help="use uniform random instead of fixed sequence length",
+    )
+    parser.set_defaults(random_sequence_length=False)
+
+    parser.add_argument(
+        "--global_tokens",
+        required=False,
+        type=int,
+        default=10,
+        help="number of global tokens",
+    )
+
+    parser.add_argument(
+        "--input_ids_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for input ids",
+    )
+
+    parser.add_argument(
+        "--input_mask_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for attention mask",
+    )
+
+    parser.add_argument(
+        "--global_mask_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for global attention mask",
+    )
+
+    parser.add_argument(
+        "--samples",
+        required=False,
+        type=int,
+        default=1,
+        help="number of test cases to be generated",
+    )
+
+    parser.add_argument("--seed", required=False, type=int, default=3, help="random seed")
+
+    parser.add_argument(
+        "--verbose",
+        required=False,
+        action="store_true",
+        help="print verbose information",
+    )
+    parser.set_defaults(verbose=False)
+
+    args = parser.parse_args()
+    return args
+
+
+def get_longformer_inputs(onnx_file, input_ids_name=None, input_mask_name=None, global_mask_name=None):
+    """
+    Get graph inputs for longformer model.
+    """
+    model = ModelProto()
+    with open(onnx_file, "rb") as f:
+        model.ParseFromString(f.read())
+
+    onnx_model = OnnxModel(model)
+    graph_inputs = onnx_model.get_graph_inputs_excluding_initializers()
+
+    if input_ids_name is not None:
+        input_ids = onnx_model.find_graph_input(input_ids_name)
+        if input_ids is None:
+            raise ValueError(f"Graph does not have input named {input_ids_name}")
+
+        input_mask = None
+        if input_mask_name:
+            input_mask = onnx_model.find_graph_input(input_mask_name)
+            if input_mask is None:
+                raise ValueError(f"Graph does not have input named {input_mask_name}")
+
+        global_mask = None
+        if global_mask_name:
+            global_mask = onnx_model.find_graph_input(global_mask_name)
+            if global_mask is None:
+                raise ValueError(f"Graph does not have input named {global_mask_name}")
+
+        expected_inputs = 1 + (1 if input_mask else 0) + (1 if global_mask else 0)
+        if len(graph_inputs) != expected_inputs:
+            raise ValueError(f"Expect the graph to have {expected_inputs} inputs. Got {len(graph_inputs)}")
+
+        return input_ids, input_mask, global_mask
+
+    if len(graph_inputs) != 3:
+        raise ValueError(f"Expect the graph to have 3 inputs. Got {len(graph_inputs)}")
+
+    # Try guess the inputs based on naming.
+    input_ids = None
+    input_mask = None
+    global_mask = None
+    for input in graph_inputs:
+        input_name_lower = input.name.lower()
+        if "global" in input_name_lower:
+            global_mask = input
+        elif "mask" in input_name_lower:
+            input_mask = input
+        else:
+            input_ids = input
+
+    if input_ids and input_mask and global_mask:
+        return input_ids, input_mask, global_mask
+
+    raise ValueError("Fail to assign 3 inputs. You might try rename the graph inputs.")
+
+
+def fake_global_mask_data(global_mask, batch_size, sequence_length, num_global_tokens):
+    """
+    Fake data based on the graph input of segment_ids.
+    Args:
+        segment_ids (TensorProto): graph input of input tensor.
+    Returns:
+        data (np.array): the data for input tensor
+    """
+    data_type = global_mask.type.tensor_type.elem_type
+    assert data_type in [TensorProto.FLOAT, TensorProto.INT32, TensorProto.INT64]
+
+    if num_global_tokens > 0:
+        assert num_global_tokens <= sequence_length
+        data = np.zeros((batch_size, sequence_length), dtype=np.int32)
+        temp = np.ones((batch_size, num_global_tokens), dtype=np.int32)
+        data[: temp.shape[0], : temp.shape[1]] = temp
+    else:
+        data = np.zeros((batch_size, sequence_length), dtype=np.int32)
+
+    if data_type == TensorProto.FLOAT:
+        data = np.float32(data)
+    elif data_type == TensorProto.INT64:
+        data = np.int64(data)
+
+    return data
+
+
+def fake_test_data(
+    batch_size,
+    sequence_length,
+    test_cases,
+    dictionary_size,
+    verbose,
+    random_seed,
+    input_ids,
+    input_mask,
+    global_mask,
+    num_global_tokens,
+    average_sequence_length,
+    random_sequence_length,
+):
+    """
+    Generate fake input data for test.
+    """
+    assert input_ids is not None
+
+    np.random.seed(random_seed)
+    random.seed(random_seed)
+
+    all_inputs = []
+    for _ in range(test_cases):
+        input_1 = fake_input_ids_data(input_ids, batch_size, sequence_length, dictionary_size)
+        inputs = {input_ids.name: input_1}
+
+        if input_mask:
+            inputs[input_mask.name] = fake_input_mask_data(
+                input_mask, batch_size, sequence_length, average_sequence_length, random_sequence_length
+            )
+
+        if global_mask:
+            inputs[global_mask.name] = fake_global_mask_data(
+                global_mask, batch_size, sequence_length, num_global_tokens
+            )
+
+        if verbose and len(all_inputs) == 0:
+            print("Example inputs", inputs)
+        all_inputs.append(inputs)
+
+    return all_inputs
+
+
+def generate_test_data(
+    batch_size,
+    sequence_length,
+    test_cases,
+    seed,
+    verbose,
+    input_ids,
+    input_mask,
+    global_mask,
+    num_global_tokens,
+    average_sequence_length,
+    random_sequence_length,
+):
+    dictionary_size = 10000
+    all_inputs = fake_test_data(
+        batch_size,
+        sequence_length,
+        test_cases,
+        dictionary_size,
+        verbose,
+        seed,
+        input_ids,
+        input_mask,
+        global_mask,
+        num_global_tokens,
+        average_sequence_length,
+        random_sequence_length,
+    )
+    if len(all_inputs) != test_cases:
+        print("Failed to create test data for test.")
+    return all_inputs
+
+
+def create_longformer_test_data(
+    model,
+    output_dir,
+    batch_size,
+    sequence_length,
+    test_cases,
+    seed,
+    verbose,
+    input_ids_name,
+    input_mask_name,
+    global_mask_name,
+    num_global_tokens,
+    average_sequence_length,
+    random_sequence_length,
+):
+    input_ids, input_mask, global_mask = get_longformer_inputs(model, input_ids_name, input_mask_name, global_mask_name)
+    all_inputs = generate_test_data(
+        batch_size,
+        sequence_length,
+        test_cases,
+        seed,
+        verbose,
+        input_ids,
+        input_mask,
+        global_mask,
+        num_global_tokens,
+        average_sequence_length,
+        random_sequence_length,
+    )
+
+    for i, inputs in enumerate(all_inputs):
+        output_test_data(output_dir, i, inputs)
+
+
+def main():
+    args = parse_arguments()
+
+    output_dir = args.output_dir
+    if output_dir is None:
+        # Default output directory is a sub-directory under the directory of model.
+        output_dir = os.path.join(
+            Path(args.model).parent,
+            f"b{args.batch_size}_s{args.sequence_length}_g{args.global_tokens}",
+        )
+
+    if output_dir is not None:
+        # create the output directory if not existed
+        path = Path(output_dir)
+        path.mkdir(parents=True, exist_ok=True)
+    else:
+        print("Directory existed. test data files will be overwritten.")
+
+    if args.average_sequence_length <= 0:
+        args.average_sequence_length = args.sequence_length
+
+    create_longformer_test_data(
+        args.model,
+        output_dir,
+        args.batch_size,
+        args.sequence_length,
+        args.samples,
+        args.seed,
+        args.verbose,
+        args.input_ids_name,
+        args.input_mask_name,
+        args.global_mask_name,
+        args.global_tokens,
+        args.average_sequence_length,
+    )
+
+    print("Test data is saved to directory:", output_dir)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/longformer_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/longformer_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..074fa098e6a096ea0c08ca518c3221efda849658
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/longformer/longformer_helper.py
@@ -0,0 +1,76 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+# This script helps creating dummy inputs for Longformer model.
+
+import logging
+
+import numpy
+import torch
+
+logger = logging.getLogger(__name__)
+
+PRETRAINED_LONGFORMER_MODELS = {
+    "longformer-base-4096": "allenai/longformer-base-4096",
+    "longformer-large-4096": "allenai/longformer-large-4096",
+    "longformer-random-tiny": "patrickvonplaten/longformer-random-tiny",  # A tiny model for debugging
+}
+
+
+class LongformerInputs:
+    def __init__(self, input_ids, attention_mask, global_attention_mask):
+        self.input_ids: torch.LongTensor = input_ids
+        self.attention_mask: torch.FloatTensor | torch.HalfTensor = attention_mask
+        self.global_attention_mask: torch.FloatTensor | torch.HalfTensor = global_attention_mask
+
+    def to_list(self) -> list:
+        return [v for v in [self.input_ids, self.attention_mask, self.global_attention_mask] if v is not None]
+
+    def to_tuple(self) -> tuple:
+        return tuple(v for v in self.to_list())
+
+    def get_ort_inputs(self) -> dict:
+        return {
+            "input_ids": numpy.ascontiguousarray(self.input_ids.cpu().numpy()),
+            "attention_mask": numpy.ascontiguousarray(self.attention_mask.cpu().numpy()),
+            "global_attention_mask": numpy.ascontiguousarray(self.global_attention_mask.cpu().numpy()),
+        }
+
+
+class LongformerHelper:
+    """A helper class for Longformer model conversion, inference and verification."""
+
+    @staticmethod
+    def get_dummy_inputs(
+        batch_size: int,
+        sequence_length: int,
+        num_global_tokens: int,
+        device: torch.device,
+        vocab_size: int = 100,
+    ) -> LongformerInputs:
+        """Create random inputs for Longformer model.
+        Returns torch tensors of input_ids, attention_mask and global_attention_mask tensors.
+        """
+
+        input_ids = torch.randint(
+            low=0,
+            high=vocab_size - 1,
+            size=(batch_size, sequence_length),
+            dtype=torch.long,
+            device=device,
+        )
+        attention_mask = torch.ones(input_ids.shape, dtype=torch.long, device=device)
+        global_attention_mask = torch.zeros(input_ids.shape, dtype=torch.long, device=device)
+        global_token_index = list(range(num_global_tokens))
+        global_attention_mask[:, global_token_index] = 1
+        return LongformerInputs(input_ids, attention_mask, global_attention_mask)
+
+    @staticmethod
+    def get_output_shapes(batch_size: int, sequence_length: int, hidden_size: int) -> dict[str, list[int]]:
+        """Returns a dictionary with output name as key, and shape as value."""
+        return {
+            "last_state": [batch_size, sequence_length, hidden_size],
+            "pooler": [batch_size, sequence_length],
+        }
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f9a57c902589567201d260a9248c59309a74576
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/__pycache__/__init__.cpython-313.pyc b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/__pycache__/__init__.cpython-313.pyc
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..b45b732b194bb9db041cc40d6d0393bbe95c6a0d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/convert_to_onnx.py
@@ -0,0 +1,590 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+from __future__ import annotations
+
+import argparse
+import logging
+import os
+import warnings
+from pathlib import Path
+
+import onnx
+import torch
+from benchmark_helper import Precision
+from fusion_options import AttentionOpType
+from onnx_model import OnnxModel
+from packaging import version
+from transformers import AutoConfig, AutoModelForCausalLM
+
+from onnxruntime import __version__ as ort_version
+
+if version.parse(ort_version) < version.parse("1.22.0"):
+    from onnxruntime.quantization.matmul_4bits_quantizer import MatMul4BitsQuantizer as MatMulNBitsQuantizer
+else:
+    from onnxruntime.quantization.matmul_nbits_quantizer import MatMulNBitsQuantizer
+
+
+class ConvertPhi2ToONNX:
+    def __init__(
+        self,
+        device: torch.device,
+        model_class: str = "microsoft/phi-2",
+        cache_dir: str = "./cache",
+    ):
+        self.model_class = model_class
+        self.device = device
+        self.cache_dir = cache_dir
+        self.phi_config = AutoConfig.from_pretrained(self.model_class, trust_remote_code=True, cache_dir=self.cache_dir)
+        self.phi_model = None
+        self.batch_size = 2
+        self.sequence_length = 8
+        self.attn_op_type = None
+        self.precision = None
+        self.block_size = 16
+        self.accuracy_level = None
+
+    def set_quantization_params(self, block_size: int, accuracy_level: int | None):
+        self.block_size = block_size
+        self.accuracy_level = accuracy_level
+
+    def init_attn_type_and_precision(self, attn_op_type: AttentionOpType, precision: Precision):
+        self.attn_op_type = attn_op_type
+        self.precision = precision
+
+    def erase_onnx_model(self, onnx_path: str) -> None:
+        assert onnx_path.endswith(".onnx")
+        if not os.path.exists(onnx_path):
+            return
+
+        model = onnx.load_model(onnx_path, load_external_data=False)
+        onnx_data_path = None
+        for initializer in model.graph.initializer:
+            if initializer.data_location == 1 and initializer.external_data[0].key == "location":
+                onnx_data_path = "./" + initializer.external_data[0].value
+                break
+        logging.info(f"Erasing {onnx_path}...")
+        os.remove(onnx_path)
+        if onnx_data_path is not None:
+            onnx_data_path = os.path.join(Path(onnx_path).parent, onnx_data_path)
+            logging.info(f"Erasing {onnx_data_path}...")
+            os.remove(onnx_data_path)
+
+    def get_phi2_torch_model(self):
+        logging.info("Loading phi2 torch model...")
+        if self.phi_model is not None:
+            return
+        self.phi_model = AutoModelForCausalLM.from_pretrained(
+            self.model_class, trust_remote_code=True, cache_dir=self.cache_dir
+        )
+        self.phi_model.eval()
+        self.phi_model.to(self.device)
+
+    def get_phi2_torch_inputs(self, batch_size: int, sequence_length: int):
+        input_ids = torch.randint(
+            low=0,
+            high=self.phi_config.vocab_size,
+            size=(batch_size, sequence_length),
+            dtype=torch.int64,
+            device=self.device,
+        )
+        self.get_phi2_torch_model()
+        torch_inputs = self.phi_model.prepare_inputs_for_generation(
+            input_ids, past_key_values=self.phi_model(input_ids, use_cache=True)["past_key_values"]
+        )
+        return torch_inputs["input_ids"], torch_inputs["attention_mask"], torch_inputs["past_key_values"]
+
+    def dynamo_export(self, onnx_path: str):
+        input_ids, attention_mask, past_key_values = self.get_phi2_torch_inputs(self.batch_size, self.sequence_length)
+        self.phi_model(input_ids, attention_mask=attention_mask, past_key_values=past_key_values)
+
+        from torch._dynamo import config  # noqa: PLC0415
+
+        config.capture_scalar_outputs = True
+
+        logging.info("Exporting Phi2 torch model to ONNX...")
+        torch.onnx.dynamo_export(
+            self.phi_model,
+            input_ids,
+            attention_mask=attention_mask,
+            past_key_values=past_key_values,
+            export_options=torch.onnx.ExportOptions(dynamic_shapes=True),
+        ).save(onnx_path)
+        onnx.checker.check_model(onnx_path)
+        onnx.shape_inference.infer_shapes_path(onnx_path)
+
+    def optimize_phi2_onnx(self, onnx_path: str, onnx_path_opt: str):
+        from fusion_options import FusionOptions  # noqa: PLC0415
+        from optimizer import optimize_model  # noqa: PLC0415
+
+        optimization_options = FusionOptions("phi")
+        optimization_options.set_attention_op_type(self.attn_op_type)
+        optimizer = optimize_model(
+            onnx_path,
+            model_type="phi",
+            num_heads=self.phi_config.num_attention_heads,
+            hidden_size=self.phi_config.hidden_size,
+            opt_level=0,
+            optimization_options=optimization_options,
+            only_onnxruntime=False,
+        )
+
+        fused_op_count = optimizer.get_fused_operator_statistics()
+        if optimizer.is_fully_optimized(fused_op_count):
+            logging.info("Model is fully optimized.")
+        else:
+            logging.info("Model is not fully optimized.")
+
+        if self.precision == Precision.FLOAT32:
+            optimizer.save_model_to_file(onnx_path_opt, use_external_data_format=True)
+            return
+
+        if (
+            self.precision == Precision.FLOAT16 or self.precision == Precision.INT4
+        ) and self.attn_op_type != AttentionOpType.MultiHeadAttention:
+            # We keep last three layers of Attention as float32 or bfloat16 to avoid overflow.
+            node_block_list = (
+                [
+                    "Attention_29",
+                    "Attention_30",
+                    "Attention_31",
+                ]
+                if self.attn_op_type != AttentionOpType.PagedAttention
+                else []
+            )  # TODO: temp setting for paged attention
+            logging.info("Converting onnx model to float16/bfloat16...")
+            optimizer.convert_float_to_float16(
+                keep_io_types=False,
+                node_block_list=node_block_list,
+                use_symbolic_shape_infer=True,
+                use_bfloat16_as_blocked_nodes_dtype=self.attn_op_type == AttentionOpType.GroupQueryAttention,
+            )
+            logging.info("Converting onnx model to float16/bfloat16 done.")
+
+        if self.precision == Precision.FLOAT16:
+            optimizer.save_model_to_file(onnx_path_opt, use_external_data_format=True)
+            return
+        else:
+            assert self.precision == Precision.INT4
+            quant = MatMulNBitsQuantizer(
+                model=optimizer.model,
+                bits=4,
+                block_size=self.block_size,
+                is_symmetric=True,
+                accuracy_level=self.accuracy_level,
+            )
+            quant.process()
+            quant.model.save_model_to_file(onnx_path_opt, use_external_data_format=True)
+
+    # This function currently only works for phi2 model
+    def convert_to_use_cuda_graph(self, in_onnx_path: str, out_onnx_path: str):
+        onnx_model = OnnxModel(onnx.load(in_onnx_path, load_external_data=True))
+
+        from onnx import TensorProto, helper  # noqa: PLC0415
+
+        graph = onnx_model.graph()
+        new_inputs = []
+        for vi in graph.input:
+            if "attention_mask" in vi.name:
+                vi_seqlen_k = helper.make_tensor_value_info(
+                    "seqlens_k",
+                    elem_type=TensorProto.INT32,
+                    shape=["batch_size"],
+                )
+                vi_total_seq_len = helper.make_tensor_value_info(
+                    "total_sequence_length",
+                    elem_type=TensorProto.INT32,
+                    shape=[1],
+                )
+                new_inputs.extend([vi_seqlen_k, vi_total_seq_len])
+            else:
+                new_inputs.append(vi)
+
+        graph.ClearField("input")
+        graph.input.extend(new_inputs)
+
+        gqas = onnx_model.get_nodes_by_op_type("GroupQueryAttention")
+        gqa = gqas[0]
+        seqlens_path = onnx_model.match_parent_path(
+            gqa,
+            ["Cast", "Sub", "ReduceSum", "Cast"],
+            [5, 0, 0, 0],
+        )
+        if seqlens_path is None:
+            raise RuntimeError("Failed to find seqlens path for GroupQueryAttention node.")
+        total_seq_len_path = onnx_model.match_parent_path(
+            gqa,
+            ["Cast", "Gather", "Shape"],
+            [6, 0, 0],
+        )
+        if total_seq_len_path is None:
+            raise RuntimeError("Failed to find total_seq_len path for GroupQueryAttention node.")
+        onnx_model.remove_nodes(seqlens_path)
+        onnx_model.remove_nodes(total_seq_len_path)
+
+        for gqa in gqas:
+            gqa.input[5] = "seqlens_k"
+            gqa.input[6] = "total_sequence_length"
+
+        onnx_model.save(onnx_model.model, out_onnx_path, save_as_external_data=True)
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--fp32_cpu",
+        required=False,
+        action="store_true",
+        help="Generate fp32 ONNX model for CPU",
+    )
+
+    parser.add_argument(
+        "--int4_cpu",
+        required=False,
+        action="store_true",
+        help="Generate int4 ONNX model for CPU",
+    )
+
+    parser.add_argument(
+        "--fp32_gpu",
+        required=False,
+        action="store_true",
+        help="Generate fp32 ONNX model for Nvidia GPUs",
+    )
+
+    parser.add_argument(
+        "--fp16_gpu",
+        required=False,
+        action="store_true",
+        help="Generate fp16 ONNX model for Nvidia GPUs",
+    )
+
+    parser.add_argument(
+        "--int4_gpu",
+        required=False,
+        action="store_true",
+        help="Generate int4 ONNX model for Nvidia GPUs",
+    )
+
+    parser.add_argument(
+        "--fp16_gpu_sm8x",
+        required=False,
+        action="store_true",
+        help="Generate fp16 ONNX model for Nvidia GPUs with CUDA architecture SM=80~89",
+    )
+
+    parser.add_argument(
+        "--int4_gpu_sm8x",
+        required=False,
+        action="store_true",
+        help="Generate int4 ONNX model for Nvidia GPUs with CUDA architecture SM=80~89",
+    )
+
+    parser.add_argument(
+        "--fp16_vllm",
+        required=False,
+        action="store_true",
+        help="Generate fp16 ONNX model for ORT VLLM",
+    )
+
+    parser.add_argument(
+        "--int4_vllm",
+        required=False,
+        action="store_true",
+        help="Generate int4 ONNX model for ORT VLLM",
+    )
+
+    parser.add_argument(
+        "--use_cuda_graph",
+        required=False,
+        action="store_true",
+        help="Use CUDA Graph in decoding process",
+    )
+
+    parser.add_argument(
+        "--overwrite",
+        required=False,
+        action="store_true",
+        help="Overwrite existing ONNX models",
+    )
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default="./cache",
+        help="The cache directory for the pytorch model",
+    )
+
+    parser.add_argument(
+        "--device_id",
+        required=False,
+        type=int,
+        default=0,
+        help="The device id for the pytorch model",
+    )
+
+    parser.add_argument(
+        "--run_example",
+        required=False,
+        action="store_true",
+        help="Run ORT inference example",
+    )
+
+    parser.add_argument(
+        "--run_benchmark",
+        required=False,
+        action="store_true",
+        help="Run ORT benchmark",
+    )
+
+    parser.add_argument(
+        "--skip_export",
+        required=False,
+        action="store_true",
+        help="Skip exporting ONNX model",
+    )
+
+    parser.add_argument(
+        "--output_dir",
+        type=str,
+        help="The output directory for the ONNX models",
+        default="phi2_onnx_models",
+    )
+
+    parser.add_argument(
+        "--block_size",
+        required=False,
+        default=16,
+        type=int,
+        help="Block size to quantize with. See https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/python/tools/quantization/matmul_nbits_quantizer.py for details.",
+    )
+
+    parser.add_argument(
+        "--int4_accuracy_level",
+        required=False,
+        type=int,
+        help="Accuracy level of the 4-bit quantized MatMul computation. "
+        "Refer to the MatMulNBits contrib op's 'accuracy_level' attribute for details "
+        "(https://github.com/microsoft/onnxruntime/blob/main/docs/ContribOperators.md#commicrosoftmatmulnbits).",
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    warnings.warn(
+        "This example is deprecated. Use the Olive recipe instead: "
+        "https://github.com/microsoft/olive-recipes/tree/main",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+    args = parse_arguments()
+
+    device = torch.device("cuda", args.device_id) if torch.cuda.is_available() else torch.device("cpu")
+
+    converter = ConvertPhi2ToONNX(device, cache_dir=args.cache_dir)
+    converter.set_quantization_params(args.block_size, args.int4_accuracy_level)
+
+    output_dir = args.output_dir
+
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    original_onnx_path = os.path.join(output_dir, "phi2_original.onnx")
+
+    if not args.skip_export:
+        if not os.path.exists(original_onnx_path) or args.overwrite:
+            converter.dynamo_export(original_onnx_path)
+
+    model_type_to_args = {
+        "fp32_cpu": (
+            AttentionOpType.MultiHeadAttention,
+            Precision.FLOAT32,
+            os.path.join(output_dir, "phi2_decoder_fp32_cpu.onnx"),
+        ),
+        "int4_cpu": (
+            AttentionOpType.MultiHeadAttention,
+            Precision.INT4,
+            os.path.join(output_dir, "phi2_decoder_int4_cpu.onnx"),
+        ),
+        "fp32_gpu": (
+            AttentionOpType.Attention,
+            Precision.FLOAT32,
+            os.path.join(output_dir, "phi2_decoder_fp32_gpu.onnx"),
+        ),
+        "fp16_gpu": (
+            AttentionOpType.Attention,
+            Precision.FLOAT16,
+            os.path.join(output_dir, "phi2_decoder_fp16_gpu.onnx"),
+        ),
+        "int4_gpu": (AttentionOpType.Attention, Precision.INT4, os.path.join(output_dir, "phi2_decoder_int4_gpu.onnx")),
+        "fp16_gpu_sm8x": (
+            AttentionOpType.GroupQueryAttention,
+            Precision.FLOAT16,
+            os.path.join(output_dir, "phi2_decoder_fp16_gpu_sm8x.onnx"),
+        ),
+        "int4_gpu_sm8x": (
+            AttentionOpType.GroupQueryAttention,
+            Precision.INT4,
+            os.path.join(output_dir, "phi2_decoder_int4_gpu_sm8x.onnx"),
+        ),
+        "fp16_vllm": (
+            AttentionOpType.PagedAttention,
+            Precision.FLOAT16,
+            os.path.join(output_dir, "phi2_decoder_fp16_vllm.onnx"),
+        ),
+        "int4_vllm": (
+            AttentionOpType.PagedAttention,
+            Precision.INT4,
+            os.path.join(output_dir, "phi2_decoder_int4_vllm.onnx"),
+        ),
+    }
+
+    if not args.skip_export:
+        from multiprocessing import Process  # noqa: PLC0415
+
+        def run_optimize_phi2_onnx(
+            converter: ConvertPhi2ToONNX,
+            original_onnx_path: str,
+            attention_type: AttentionOpType,
+            precision: Precision,
+            optimized_onnx_path: str,
+        ):
+            converter.init_attn_type_and_precision(attention_type, precision)
+            converter.optimize_phi2_onnx(original_onnx_path, optimized_onnx_path)
+            if args.use_cuda_graph:
+                assert args.fp16_gpu_sm8x or args.int4_gpu_sm8x
+                converter.convert_to_use_cuda_graph(optimized_onnx_path, optimized_onnx_path)
+
+        processes = []
+        if args.fp32_cpu:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx, args=(converter, original_onnx_path, *model_type_to_args["fp32_cpu"])
+                )
+            )
+
+        if args.int4_cpu:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx, args=(converter, original_onnx_path, *model_type_to_args["int4_cpu"])
+                )
+            )
+
+        if args.fp32_gpu:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx, args=(converter, original_onnx_path, *model_type_to_args["fp32_gpu"])
+                )
+            )
+
+        if args.fp16_gpu:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx, args=(converter, original_onnx_path, *model_type_to_args["fp16_gpu"])
+                )
+            )
+
+        if args.int4_gpu:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx, args=(converter, original_onnx_path, *model_type_to_args["int4_gpu"])
+                )
+            )
+
+        if args.fp16_gpu_sm8x:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx,
+                    args=(converter, original_onnx_path, *model_type_to_args["fp16_gpu_sm8x"]),
+                )
+            )
+
+        if args.int4_gpu_sm8x:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx,
+                    args=(converter, original_onnx_path, *model_type_to_args["int4_gpu_sm8x"]),
+                )
+            )
+
+        if args.fp16_vllm:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx,
+                    args=(converter, original_onnx_path, *model_type_to_args["fp16_vllm"]),
+                )
+            )
+
+        if args.int4_vllm:
+            processes.append(
+                Process(
+                    target=run_optimize_phi2_onnx,
+                    args=(converter, original_onnx_path, *model_type_to_args["int4_vllm"]),
+                )
+            )
+
+        [p.start() for p in processes]
+        [p.join() for p in processes]
+
+    if args.run_example or args.run_benchmark:
+        from inference_example import run_phi2  # noqa: PLC0415
+
+        if args.fp16_gpu_sm8x:
+            logging.info("Running fp16_gpu_sm8x example...")
+            run_phi2(
+                onnx_model_path=model_type_to_args["fp16_gpu_sm8x"][2],
+                use_buffer_share=True,
+                device_id=args.device_id,
+                use_step=True,
+                use_cuda_graph=args.use_cuda_graph,
+                run_benchmark=args.run_benchmark,
+            )
+        if args.int4_gpu_sm8x:
+            logging.info("Running int4_gpu_sm8x example...")
+            run_phi2(
+                onnx_model_path=model_type_to_args["int4_gpu_sm8x"][2],
+                use_buffer_share=True,
+                device_id=args.device_id,
+                use_step=True,
+                use_cuda_graph=args.use_cuda_graph,
+                run_benchmark=args.run_benchmark,
+            )
+        if args.fp32_gpu:
+            logging.info("Running fp32_gpu example...")
+            run_phi2(
+                onnx_model_path=model_type_to_args["fp32_gpu"][2],
+                use_buffer_share=False,
+                device_id=args.device_id,
+                packed_kv=True,
+                use_fp16=False,
+                run_benchmark=args.run_benchmark,
+            )
+        if args.fp16_gpu:
+            logging.info("Running fp16_gpu example...")
+            run_phi2(
+                onnx_model_path=model_type_to_args["fp16_gpu"][2],
+                use_buffer_share=False,
+                device_id=args.device_id,
+                packed_kv=True,
+                run_benchmark=args.run_benchmark,
+            )
+        if args.int4_gpu:
+            logging.info("Running int4_gpu example...")
+            run_phi2(
+                onnx_model_path=model_type_to_args["int4_gpu"][2],
+                use_buffer_share=False,
+                device_id=args.device_id,
+                packed_kv=True,
+                run_benchmark=args.run_benchmark,
+            )
+        if args.fp32_cpu or args.int4_cpu or args.fp16_vllm or args.int4_vllm:
+            raise NotImplementedError("CPU/vllm inference example is not implemented yet.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/inference_example.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/inference_example.py
new file mode 100644
index 0000000000000000000000000000000000000000..3dadd28d7ee4e74f34c24e5e61f531832e9b6811
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/phi2/inference_example.py
@@ -0,0 +1,414 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import time
+
+import numpy as np
+import torch
+from transformers import AutoTokenizer
+
+import onnxruntime as ort
+
+pt_to_np = {
+    "torch.int32": np.int32,
+    "torch.int64": np.int64,
+    "torch.float32": np.float32,
+    "torch.float16": np.float16,
+}
+
+
+def cuda_memcpy(dst, src):
+    from cuda import cudart  # noqa: PLC0415
+
+    cudart.cudaMemcpy(
+        dst.data_ptr(),
+        src.data_ptr(),
+        src.element_size() * src.nelement(),
+        cudart.cudaMemcpyKind.cudaMemcpyDeviceToDevice,
+    )
+
+
+class ORTGenerator:
+    def __init__(self, decoder_path):
+        self.onnx_decoder_path = decoder_path
+        self.num_heads = 32
+        self.head_size = 80
+        self.num_layers = 32
+        self.max_sequence_length = 2048
+        self.device_id = 0
+        self.use_cuda_graph = False
+        self.use_traced_inputs = False
+        self.static_inputs_map = {}
+
+    def append_static_inputs(self, batch_size):
+        # Only use this function with GQA and with use_cuda_graph=True
+        if batch_size in self.static_inputs_map:
+            return
+
+        cpu_device = torch.device("cpu")
+        cuda_device = torch.device("cuda", self.device_id)
+
+        static_io = {}
+        static_io["input_ids"] = torch.zeros((batch_size, 1), dtype=torch.int32, device=cuda_device)
+        static_io["step"] = torch.tensor([0], dtype=torch.int64, device=cuda_device)
+        static_io["seqlens_k"] = torch.tensor(batch_size * [0], dtype=torch.int32, device=cuda_device)
+        static_io["total_sequence_length"] = torch.tensor([0], dtype=torch.int32, device=cpu_device)
+
+        cache_shape = (batch_size, self.num_heads, self.max_sequence_length, self.head_size)
+        for i in range(self.num_layers):
+            cache = torch.zeros(cache_shape, device=cuda_device, dtype=torch.float16)
+            static_io.update({f"past_key_{i}": cache.contiguous(), f"past_value_{i}": cache.clone().contiguous()})
+
+        static_io["logits"] = torch.zeros((batch_size, 1, 51200), dtype=torch.float16, device=cuda_device)
+
+        self.static_inputs_map[batch_size] = static_io
+
+    def get_initial_inputs_and_outputs(self, encodings_dict):
+        self.torch_dtype = torch.float16 if self.use_fp16 else torch.float32
+
+        input_ids = torch.tensor(encodings_dict["input_ids"], device=self.device, dtype=torch.int32)
+        attention_mask = torch.tensor(encodings_dict["attention_mask"], device=self.device, dtype=torch.int32)
+
+        batch_size, sequence_length = input_ids.shape
+
+        self.use_traced_inputs = (
+            self.use_cuda_graph
+            and (batch_size in self.static_inputs_map)
+            and self.use_buffer_share
+            and not self.packed_kv
+        )
+
+        step = (
+            torch.tensor([0], device=self.device, dtype=torch.int64)
+            if not self.use_traced_inputs
+            else self.static_inputs_map[batch_size]["step"]
+        )
+
+        seqlens_k = (
+            torch.tensor(batch_size * [0], device=self.device, dtype=torch.int32)
+            if not self.use_traced_inputs
+            else self.static_inputs_map[batch_size]["seqlens_k"]
+        )
+        cuda_memcpy(seqlens_k, attention_mask.sum(1).sub(1).to(torch.int32))
+
+        total_seq_length = (
+            torch.tensor([0], device=torch.device("cpu"), dtype=torch.int32)
+            if not self.use_traced_inputs
+            else self.static_inputs_map[batch_size]["total_sequence_length"]
+        )
+        total_seq_length[0] = sequence_length
+
+        inputs = {
+            "input_ids": input_ids.contiguous(),
+            "attention_mask": attention_mask.contiguous(),
+        }
+
+        if self.use_step:
+            inputs["step"] = step.contiguous()
+
+        if self.use_cuda_graph:
+            inputs["seqlens_k"] = seqlens_k.contiguous()
+            inputs["total_sequence_length"] = total_seq_length.contiguous()
+            del inputs["attention_mask"]
+
+        past_seq_length = self.max_sequence_length if self.use_buffer_share else 0
+        past_shape = (
+            (2, batch_size, self.num_heads, past_seq_length, self.head_size)
+            if self.packed_kv
+            else (batch_size, self.num_heads, past_seq_length, self.head_size)
+        )
+
+        if not self.use_traced_inputs:
+            for i in range(self.num_layers):
+                past = torch.zeros(past_shape, device=self.device, dtype=self.torch_dtype)
+                (
+                    inputs.update({f"past_key_{i}": past.contiguous(), f"past_value_{i}": past.clone().contiguous()})
+                    if not self.packed_kv
+                    else inputs.update({f"past_{i}": past.contiguous()})
+                )
+        else:
+            for i in range(self.num_layers):
+                inputs.update(
+                    {
+                        f"past_key_{i}": self.static_inputs_map[batch_size][f"past_key_{i}"].contiguous(),
+                        f"past_value_{i}": self.static_inputs_map[batch_size][f"past_value_{i}"].contiguous(),
+                    }
+                )
+
+        logits = torch.zeros(batch_size, sequence_length, 51200, device=self.device, dtype=self.torch_dtype)
+        outputs = {"logits": logits.contiguous()}
+
+        if not self.use_buffer_share:
+            present_shape = (
+                (2, batch_size, self.num_heads, sequence_length, self.head_size)
+                if self.packed_kv
+                else (batch_size, self.num_heads, sequence_length, self.head_size)
+            )
+            for i in range(self.num_layers):
+                present = torch.zeros(present_shape, device=self.device, dtype=self.torch_dtype)
+                (
+                    outputs.update(
+                        {f"present_key_{i}": present.contiguous(), f"present_value_{i}": present.contiguous()}
+                    )
+                    if not self.packed_kv
+                    else outputs.update({f"present_{i}": present.contiguous()})
+                )
+
+        return inputs, outputs
+
+    def apply_io_binding(self, model: ort.InferenceSession, inputs: dict, outputs: dict):
+        io_binding = model.io_binding()
+        device = None
+
+        for k, v in inputs.items():
+            io_binding.bind_input(
+                name=k,
+                device_type=v.device.type,
+                device_id=0 if v.device.type == "cpu" else v.device.index,
+                element_type=pt_to_np[repr(v.dtype)],
+                shape=tuple(v.shape),
+                buffer_ptr=v.data_ptr(),
+            )
+            device = v.device
+
+        for output in model.get_outputs():
+            name = output.name
+            if self.use_buffer_share and "present" in name:
+                v = inputs[name.replace("present", "past")]
+                io_binding.bind_output(
+                    name=name,
+                    device_type=v.device.type,
+                    device_id=v.device.index,
+                    element_type=(np.float16 if self.use_fp16 else np.float32),
+                    shape=tuple(v.shape),
+                    buffer_ptr=v.data_ptr(),
+                )
+            else:
+                v = outputs[name]
+                io_binding.bind_output(
+                    name=name,
+                    device_type=device.type,
+                    device_id=0 if device.type == "cpu" else device.index,
+                    element_type=(np.float16 if self.use_fp16 else np.float32),
+                    shape=tuple(v.shape),
+                    buffer_ptr=v.data_ptr(),
+                )
+
+        return io_binding
+
+    def create_session(
+        self, device_id, use_fp16=True, use_buffer_share=True, packed_kv=False, use_step=False, use_cuda_graph=False
+    ):
+        self.device_id = device_id
+        sess_options = ort.SessionOptions()
+        sess_options.log_verbosity_level = 4
+        sess_options.log_severity_level = 4
+        self.use_cuda_graph = use_cuda_graph
+        ep = (
+            ("CUDAExecutionProvider", {"device_id": self.device_id, "enable_cuda_graph": self.use_cuda_graph})
+            if self.device_id >= 0
+            else "CPUExecutionProvider"
+        )
+        self.sess = ort.InferenceSession(self.onnx_decoder_path, sess_options=sess_options, providers=[ep])
+        self.ro = ort.RunOptions()
+
+        self.device = torch.device("cuda", self.device_id) if torch.cuda.is_available() else torch.device("cpu")
+        self.use_fp16 = use_fp16
+        self.use_buffer_share = use_buffer_share
+        self.packed_kv = packed_kv
+        self.use_step = use_step
+
+        self.tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True)
+        self.tokenizer.pad_token = "[PAD]"
+
+    def generate_impl(self, encodings_dict, max_length, cuda_graph_annotation, benchmark=False):
+        inputs, outputs = self.get_initial_inputs_and_outputs(encodings_dict)
+
+        all_token_ids = inputs["input_ids"].clone()
+        batch_size, sequence_length = all_token_ids.shape
+
+        current_length = sequence_length
+        has_eos = torch.zeros(batch_size, device=self.device, dtype=torch.bool)
+
+        if benchmark:
+            latency = []
+
+        prompt_run = True
+        while current_length < max_length:
+            io_binding = self.apply_io_binding(self.sess, inputs, outputs)
+
+            if benchmark:
+                start = time.time()
+
+            io_binding.synchronize_inputs()
+            if prompt_run:
+                if self.use_cuda_graph:
+                    # Disable CUDA graph for the prompt run
+                    self.ro.add_run_config_entry("gpu_graph_id", "-1")
+                self.sess.run_with_iobinding(io_binding, self.ro)
+                if self.use_cuda_graph:
+                    # Enable CUDA graph for the decoding run
+                    self.ro.add_run_config_entry(
+                        "gpu_graph_id", str(cuda_graph_annotation) if self.use_traced_inputs else "-1"
+                    )
+                prompt_run = False
+            else:
+                self.sess.run_with_iobinding(io_binding, self.ro)
+            io_binding.synchronize_outputs()
+
+            if benchmark:
+                end = time.time()
+                latency.append(end - start)
+
+            # Sample with argmax (greedy search)
+            next_token_logits = outputs["logits"][:, -1, :]
+            next_tokens = torch.argmax(next_token_logits, dim=-1)
+
+            # Check if we previously reached EOS token id or if generated token id is EOS token id
+            has_eos = has_eos | next_tokens == self.tokenizer.eos_token_id
+
+            # Determine which new tokens to add to list of all token ids
+            # Add EOS token ids for batch entries that ended early (ragged batching scenario where some batch entries ended early and some haven't)
+            tokens_to_add = next_tokens.masked_fill(has_eos, self.tokenizer.eos_token_id).reshape([batch_size, 1])
+            all_token_ids = torch.cat([all_token_ids, tokens_to_add], dim=-1)
+
+            # Return early if all batch entries have reached EOS token id
+            if torch.all(has_eos):
+                break
+
+            # Update inputs for next inference run
+            current_length += 1
+
+            inputs["input_ids"] = tokens_to_add.to(torch.int32)
+            if self.use_traced_inputs:
+                cuda_memcpy(self.static_inputs_map[batch_size]["input_ids"], inputs["input_ids"])
+                inputs["input_ids"] = self.static_inputs_map[batch_size]["input_ids"]
+
+            if self.use_step:
+                inputs["step"] = torch.tensor([current_length - 1], device=self.device, dtype=torch.int64)
+                if self.use_traced_inputs:
+                    cuda_memcpy(self.static_inputs_map[batch_size]["step"], inputs["step"])
+                    inputs["step"] = self.static_inputs_map[batch_size]["step"]
+
+            if self.use_cuda_graph:
+                previous_seqlens_k = inputs["seqlens_k"]
+                inputs["seqlens_k"] = (previous_seqlens_k + (~has_eos).reshape(batch_size, 1)).to(torch.int32)
+                inputs["total_sequence_length"][0] = current_length
+                if self.use_traced_inputs:
+                    cuda_memcpy(self.static_inputs_map[batch_size]["seqlens_k"], inputs["seqlens_k"])
+                    inputs["seqlens_k"] = self.static_inputs_map[batch_size]["seqlens_k"]
+                    self.static_inputs_map[batch_size]["total_sequence_length"][0] = inputs["total_sequence_length"][0]
+                    inputs["total_sequence_length"] = self.static_inputs_map[batch_size]["total_sequence_length"]
+            else:
+                inputs["attention_mask"] = torch.cat(
+                    [inputs["attention_mask"], (~has_eos).reshape(batch_size, 1)], 1
+                ).to(torch.int32)
+
+            # Set logits to zeros for next inference run and re-use memory buffer
+            if outputs["logits"].shape[1] != 1:
+                outputs["logits"] = outputs["logits"][:, :1, :].contiguous()
+                if self.use_traced_inputs:
+                    outputs["logits"] = self.static_inputs_map[batch_size]["logits"]
+            outputs["logits"].zero_()
+
+            if not self.use_buffer_share:
+                for i in range(self.num_layers):
+                    if not self.packed_kv:
+                        inputs[f"past_key_{i}"] = outputs[f"present_key_{i}"]
+                        inputs[f"past_value_{i}"] = outputs[f"present_value_{i}"]
+                    else:
+                        inputs[f"past_{i}"] = outputs[f"present_{i}"]
+
+                new_sequence_length = inputs["attention_mask"].shape[1]
+                present_shape = (
+                    (2, batch_size, self.num_heads, new_sequence_length, self.head_size)
+                    if self.packed_kv
+                    else (batch_size, self.num_heads, new_sequence_length, self.head_size)
+                )
+                for i in range(self.num_layers):
+                    present = torch.zeros(present_shape, device=self.device, dtype=self.torch_dtype)
+                    (
+                        outputs.update(
+                            {
+                                f"present_key_{i}": present.contiguous(),
+                                f"present_value_{i}": present.clone().contiguous(),
+                            }
+                        )
+                        if not self.packed_kv
+                        else outputs.update({f"present_{i}": present.contiguous()})
+                    )
+
+        if benchmark:
+            print(
+                f"Batch size: {batch_size}, Sequence length: {sequence_length}, Token num: {max_length - sequence_length}"
+            )
+            print(f"Prompt letency: {1000 * latency[0]}ms, Token latency: {1000 * np.mean(latency[1:])}ms")
+            return
+
+        texts = self.tokenizer.batch_decode(all_token_ids, skip_special_tokens=True)
+        return texts
+
+    def generate(self, prompt, max_length, cuda_graph_annotation):
+        encodings_dict = self.tokenizer.batch_encode_plus(prompt, padding=True)
+
+        return self.generate_impl(encodings_dict, max_length, cuda_graph_annotation)
+
+    def generate_benchmark(self, prompt_shape, token_num, cuda_graph_annotation):
+        batch_size, sequence_length = prompt_shape
+        max_length = sequence_length + token_num
+
+        encodings_dict = {}
+        encodings_dict["input_ids"] = torch.randint(0, 50264, (batch_size, sequence_length), dtype=torch.int32).tolist()
+        encodings_dict["attention_mask"] = torch.ones((batch_size, sequence_length), dtype=torch.int32).tolist()
+
+        # Warm up run
+        self.generate_impl(encodings_dict, max_length, cuda_graph_annotation, benchmark=False)
+
+        # Benchmark run
+        self.generate_impl(encodings_dict, max_length, cuda_graph_annotation, benchmark=True)
+
+
+def run_phi2(
+    onnx_model_path,
+    use_buffer_share,
+    device_id,
+    packed_kv=False,
+    use_fp16=True,
+    use_step=False,
+    use_cuda_graph=False,
+    run_benchmark=False,
+):
+    generator = ORTGenerator(onnx_model_path)
+    generator.create_session(device_id, use_fp16, use_buffer_share, packed_kv, use_step, use_cuda_graph)
+
+    def simple_run(prompt):
+        example_batch_size = len(prompt)
+        if use_cuda_graph:
+            generator.append_static_inputs(batch_size=example_batch_size)
+        texts = generator.generate(prompt, max_length=210, cuda_graph_annotation=example_batch_size)
+
+        for i in range(len(texts)):
+            print("Prompt: ", prompt[i])
+            print("Texts: ", texts[i])
+
+    prompt = [
+        '''```python
+    def print_prime(n):
+    """
+    Print all primes between 1 and n
+    """'''
+    ]
+
+    if not run_benchmark:
+        simple_run(prompt)
+
+    # Run simple benchmark. Time the decoder only.
+    if run_benchmark:
+        token_num = 32
+        for batch_size in [1, 2, 4, 8]:
+            generator.append_static_inputs(batch_size)
+            for sequence_length in [16, 512]:
+                prompt_shape = (batch_size, sequence_length)
+                generator.generate_benchmark(prompt_shape, token_num, cuda_graph_annotation=batch_size)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/__init__.py
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/benchmark_sam2.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/benchmark_sam2.py
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--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/benchmark_sam2.py
@@ -0,0 +1,638 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+"""
+Benchmark performance of SAM2 encoder with ORT or PyTorch. See benchmark_sam2.sh for usage.
+"""
+
+import argparse
+import csv
+import statistics
+import time
+from collections.abc import Mapping
+from datetime import datetime
+
+import torch
+from image_decoder import SAM2ImageDecoder
+from image_encoder import SAM2ImageEncoder
+from sam2_utils import decoder_shape_dict, encoder_shape_dict, load_sam2_model
+
+from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+from onnxruntime.transformers.io_binding_helper import CudaSession
+
+
+class TestConfig:
+    def __init__(
+        self,
+        model_type: str,
+        onnx_path: str,
+        sam2_dir: str,
+        device: torch.device,
+        component: str = "image_encoder",
+        provider="CPUExecutionProvider",
+        torch_compile_mode="max-autotune",
+        batch_size: int = 1,
+        height: int = 1024,
+        width: int = 1024,
+        num_labels: int = 1,
+        num_points: int = 1,
+        num_masks: int = 1,
+        multi_mask_output: bool = False,
+        use_tf32: bool = True,
+        enable_cuda_graph: bool = False,
+        dtype=torch.float32,
+        prefer_nhwc: bool = False,
+        warm_up: int = 5,
+        enable_nvtx_profile: bool = False,
+        enable_ort_profile: bool = False,
+        enable_torch_profile: bool = False,
+        repeats: int = 1000,
+        verbose: bool = False,
+    ):
+        assert model_type in ["sam2_hiera_tiny", "sam2_hiera_small", "sam2_hiera_large", "sam2_hiera_base_plus"]
+        assert height >= 160 and height <= 4096
+        assert width >= 160 and width <= 4096
+
+        self.model_type = model_type
+        self.onnx_path = onnx_path
+        self.sam2_dir = sam2_dir
+        self.component = component
+        self.provider = provider
+        self.torch_compile_mode = torch_compile_mode
+        self.batch_size = batch_size
+        self.height = height
+        self.width = width
+        self.num_labels = num_labels
+        self.num_points = num_points
+        self.num_masks = num_masks
+        self.multi_mask_output = multi_mask_output
+        self.device = device
+        self.use_tf32 = use_tf32
+        self.enable_cuda_graph = enable_cuda_graph
+        self.dtype = dtype
+        self.prefer_nhwc = prefer_nhwc
+        self.warm_up = warm_up
+        self.enable_nvtx_profile = enable_nvtx_profile
+        self.enable_ort_profile = enable_ort_profile
+        self.enable_torch_profile = enable_torch_profile
+        self.repeats = repeats
+        self.verbose = verbose
+
+        if self.component == "image_encoder":
+            assert self.height == 1024 and self.width == 1024, "Only image size 1024x1024 is allowed for image encoder."
+
+    def __repr__(self):
+        return f"{vars(self)}"
+
+    def shape_dict(self) -> Mapping[str, list[int]]:
+        if self.component == "image_encoder":
+            return encoder_shape_dict(self.batch_size, self.height, self.width)
+        else:
+            return decoder_shape_dict(self.height, self.width, self.num_labels, self.num_points, self.num_masks)
+
+    def random_inputs(self) -> Mapping[str, torch.Tensor]:
+        dtype = self.dtype
+        if self.component == "image_encoder":
+            return {"image": torch.randn(self.batch_size, 3, self.height, self.width, dtype=dtype, device=self.device)}
+        else:
+            return {
+                "image_features_0": torch.rand(1, 32, 256, 256, dtype=dtype, device=self.device),
+                "image_features_1": torch.rand(1, 64, 128, 128, dtype=dtype, device=self.device),
+                "image_embeddings": torch.rand(1, 256, 64, 64, dtype=dtype, device=self.device),
+                "point_coords": torch.randint(
+                    0, 1024, (self.num_labels, self.num_points, 2), dtype=dtype, device=self.device
+                ),
+                "point_labels": torch.randint(
+                    0, 1, (self.num_labels, self.num_points), dtype=torch.int32, device=self.device
+                ),
+                "input_masks": torch.zeros(self.num_labels, 1, 256, 256, dtype=dtype, device=self.device),
+                "has_input_masks": torch.ones(self.num_labels, dtype=dtype, device=self.device),
+                "original_image_size": torch.tensor([self.height, self.width], dtype=torch.int32, device=self.device),
+            }
+
+
+def create_ort_session(config: TestConfig, session_options=None) -> InferenceSession:
+    if config.verbose:
+        print(f"create session for {vars(config)}")
+
+    if config.provider == "CUDAExecutionProvider":
+        device_id = torch.cuda.current_device() if isinstance(config.device, str) else config.device.index
+        provider_options = CudaSession.get_cuda_provider_options(device_id, config.enable_cuda_graph)
+        provider_options["use_tf32"] = int(config.use_tf32)
+        if config.prefer_nhwc:
+            provider_options["prefer_nhwc"] = 1
+        providers = [(config.provider, provider_options), "CPUExecutionProvider"]
+    else:
+        providers = ["CPUExecutionProvider"]
+
+    ort_session = InferenceSession(config.onnx_path, session_options, providers=providers)
+    return ort_session
+
+
+def create_session(config: TestConfig, session_options=None) -> CudaSession:
+    ort_session = create_ort_session(config, session_options)
+    cuda_session = CudaSession(ort_session, config.device, config.enable_cuda_graph)
+    cuda_session.allocate_buffers(config.shape_dict())
+    return cuda_session
+
+
+class OrtTestSession:
+    """A wrapper of ORT session to test relevance and performance."""
+
+    def __init__(self, config: TestConfig, session_options=None):
+        self.ort_session = create_session(config, session_options)
+        self.feed_dict = config.random_inputs()
+
+    def infer(self):
+        return self.ort_session.infer(self.feed_dict)
+
+
+def measure_latency(cuda_session: CudaSession, input_dict):
+    start = time.time()
+    _ = cuda_session.infer(input_dict)
+    end = time.time()
+    return end - start
+
+
+def run_torch(config: TestConfig):
+    device_type = config.device.type
+    is_cuda = device_type == "cuda"
+
+    # Turn on TF32 for Ampere GPUs which could help when data type is float32.
+    if is_cuda and torch.cuda.get_device_properties(0).major >= 8 and config.use_tf32:
+        torch.backends.cuda.matmul.allow_tf32 = True
+        torch.backends.cudnn.allow_tf32 = True
+
+    enabled_auto_cast = is_cuda and config.dtype != torch.float32
+    ort_inputs = config.random_inputs()
+
+    with torch.inference_mode(), torch.autocast(device_type=device_type, dtype=config.dtype, enabled=enabled_auto_cast):
+        sam2_model = load_sam2_model(config.sam2_dir, config.model_type, device=config.device)
+        if config.component == "image_encoder":
+            if is_cuda and config.torch_compile_mode != "none":
+                sam2_model.image_encoder.forward = torch.compile(
+                    sam2_model.image_encoder.forward,
+                    mode=config.torch_compile_mode,  # "reduce-overhead" if you want to reduce latency of first run.
+                    fullgraph=True,
+                    dynamic=False,
+                )
+
+            image_shape = config.shape_dict()["image"]
+            img = torch.randn(image_shape).to(device=config.device, dtype=config.dtype)
+            sam2_encoder = SAM2ImageEncoder(sam2_model)
+
+            if is_cuda and config.torch_compile_mode != "none":
+                print(f"Running warm up. It will take a while since torch compile mode is {config.torch_compile_mode}.")
+
+            for _ in range(config.warm_up):
+                _image_features_0, _image_features_1, _image_embeddings = sam2_encoder(img)
+
+            if is_cuda and config.enable_nvtx_profile:
+                import nvtx  # noqa: PLC0415
+                from cuda import cudart  # noqa: PLC0415
+
+                cudart.cudaProfilerStart()
+                print("Start nvtx profiling on encoder ...")
+                with nvtx.annotate("one_run"):
+                    sam2_encoder(img, enable_nvtx_profile=True)
+                cudart.cudaProfilerStop()
+
+            if is_cuda and config.enable_torch_profile:
+                with torch.profiler.profile(
+                    activities=[torch.profiler.ProfilerActivity.CPU, torch.profiler.ProfilerActivity.CUDA],
+                    record_shapes=True,
+                ) as prof:
+                    print("Start torch profiling on encoder ...")
+                    with torch.profiler.record_function("encoder"):
+                        sam2_encoder(img)
+                print(prof.key_averages().table(sort_by="cuda_time_total", row_limit=10))
+                prof.export_chrome_trace("torch_image_encoder.json")
+
+            if config.repeats == 0:
+                return
+
+            print(f"Start {config.repeats} runs of performance tests...")
+            start = time.time()
+            for _ in range(config.repeats):
+                _image_features_0, _image_features_1, _image_embeddings = sam2_encoder(img)
+                if is_cuda:
+                    torch.cuda.synchronize()
+        else:
+            torch_inputs = (
+                ort_inputs["image_features_0"],
+                ort_inputs["image_features_1"],
+                ort_inputs["image_embeddings"],
+                ort_inputs["point_coords"],
+                ort_inputs["point_labels"],
+                ort_inputs["input_masks"],
+                ort_inputs["has_input_masks"],
+                ort_inputs["original_image_size"],
+            )
+
+            sam2_decoder = SAM2ImageDecoder(
+                sam2_model,
+                multimask_output=config.multi_mask_output,
+            )
+
+            if is_cuda and config.torch_compile_mode != "none":
+                sam2_decoder.forward = torch.compile(
+                    sam2_decoder.forward,
+                    mode=config.torch_compile_mode,
+                    fullgraph=True,
+                    dynamic=False,
+                )
+
+            # warm up
+            for _ in range(config.warm_up):
+                _masks, _iou_predictions, _low_res_masks = sam2_decoder(*torch_inputs)
+
+            if is_cuda and config.enable_nvtx_profile:
+                import nvtx  # noqa: PLC0415
+                from cuda import cudart  # noqa: PLC0415
+
+                cudart.cudaProfilerStart()
+                print("Start nvtx profiling on decoder...")
+                with nvtx.annotate("one_run"):
+                    sam2_decoder(*torch_inputs, enable_nvtx_profile=True)
+                cudart.cudaProfilerStop()
+
+            if is_cuda and config.enable_torch_profile:
+                with torch.profiler.profile(
+                    activities=[torch.profiler.ProfilerActivity.CPU, torch.profiler.ProfilerActivity.CUDA],
+                    record_shapes=True,
+                ) as prof:
+                    print("Start torch profiling on decoder ...")
+                    with torch.profiler.record_function("decoder"):
+                        sam2_decoder(*torch_inputs)
+                print(prof.key_averages().table(sort_by="cuda_time_total", row_limit=10))
+                prof.export_chrome_trace("torch_image_decoder.json")
+
+            if config.repeats == 0:
+                return
+
+            print(f"Start {config.repeats} runs of performance tests...")
+            start = time.time()
+            for _ in range(config.repeats):
+                _masks, _iou_predictions, _low_res_masks = sam2_decoder(*torch_inputs)
+                if is_cuda:
+                    torch.cuda.synchronize()
+
+        end = time.time()
+        return (end - start) / config.repeats
+
+
+def run_test(
+    args: argparse.Namespace,
+    csv_writer: csv.DictWriter | None = None,
+):
+    use_gpu: bool = args.use_gpu
+    enable_cuda_graph: bool = args.use_cuda_graph
+    repeats: int = args.repeats
+
+    if use_gpu:
+        device_id = torch.cuda.current_device()
+        device = torch.device("cuda", device_id)
+        provider = "CUDAExecutionProvider"
+    else:
+        device_id = 0
+        device = torch.device("cpu")
+        enable_cuda_graph = False
+        provider = "CPUExecutionProvider"
+
+    dtypes = {"fp32": torch.float32, "fp16": torch.float16, "bf16": torch.bfloat16}
+    config = TestConfig(
+        model_type=args.model_type,
+        onnx_path=args.onnx_path,
+        sam2_dir=args.sam2_dir,
+        component=args.component,
+        provider=provider,
+        batch_size=args.batch_size,
+        height=args.height,
+        width=args.width,
+        device=device,
+        use_tf32=True,
+        enable_cuda_graph=enable_cuda_graph,
+        dtype=dtypes[args.dtype],
+        prefer_nhwc=args.prefer_nhwc,
+        repeats=args.repeats,
+        warm_up=args.warm_up,
+        enable_nvtx_profile=args.enable_nvtx_profile,
+        enable_ort_profile=args.enable_ort_profile,
+        enable_torch_profile=args.enable_torch_profile,
+        torch_compile_mode=args.torch_compile_mode,
+        verbose=False,
+    )
+
+    if args.engine == "ort":
+        sess_options = SessionOptions()
+        sess_options.intra_op_num_threads = args.intra_op_num_threads
+        if config.enable_ort_profile:
+            sess_options.enable_profiling = True
+            sess_options.log_severity_level = 4
+            sess_options.log_verbosity_level = 0
+
+        session = create_session(config, sess_options)
+        input_dict = config.random_inputs()
+
+        # warm up session
+        try:
+            for _ in range(config.warm_up):
+                _ = measure_latency(session, input_dict)
+        except Exception as e:
+            print(f"Failed to run {config=}. Exception: {e}")
+            return
+
+        if config.enable_nvtx_profile:
+            import nvtx  # noqa: PLC0415
+            from cuda import cudart  # noqa: PLC0415
+
+            cudart.cudaProfilerStart()
+            with nvtx.annotate("one_run"):
+                _ = session.infer(input_dict)
+            cudart.cudaProfilerStop()
+
+        if config.enable_ort_profile:
+            session.ort_session.end_profiling()
+
+        if repeats == 0:
+            return
+
+        latency_list = []
+        for _ in range(repeats):
+            latency = measure_latency(session, input_dict)
+            latency_list.append(latency)
+        average_latency = statistics.mean(latency_list)
+
+        del session
+    else:  # torch
+        with torch.no_grad():
+            try:
+                average_latency = run_torch(config)
+            except Exception as e:
+                print(f"Failed to run {config=}. Exception: {e}")
+                return
+
+        if repeats == 0:
+            return
+
+    engine = args.engine + ":" + ("cuda" if use_gpu else "cpu")
+    row = {
+        "model_type": args.model_type,
+        "component": args.component,
+        "dtype": args.dtype,
+        "use_gpu": use_gpu,
+        "enable_cuda_graph": enable_cuda_graph,
+        "prefer_nhwc": config.prefer_nhwc,
+        "use_tf32": config.use_tf32,
+        "batch_size": args.batch_size,
+        "height": args.height,
+        "width": args.width,
+        "multi_mask_output": args.multimask_output,
+        "num_labels": config.num_labels,
+        "num_points": config.num_points,
+        "num_masks": config.num_masks,
+        "intra_op_num_threads": args.intra_op_num_threads,
+        "warm_up": config.warm_up,
+        "repeats": repeats,
+        "enable_nvtx_profile": args.enable_nvtx_profile,
+        "torch_compile_mode": args.torch_compile_mode,
+        "engine": engine,
+        "average_latency": average_latency,
+    }
+
+    if csv_writer is not None:
+        csv_writer.writerow(row)
+
+    print(f"{vars(config)}")
+    print(f"{row}")
+
+
+def run_perf_test(args):
+    features = "gpu" if args.use_gpu else "cpu"
+    csv_filename = "benchmark_sam_{}_{}_{}.csv".format(
+        features,
+        args.engine,
+        datetime.now().strftime("%Y%m%d-%H%M%S"),
+    )
+    with open(csv_filename, mode="a", newline="") as csv_file:
+        column_names = [
+            "model_type",
+            "component",
+            "dtype",
+            "use_gpu",
+            "enable_cuda_graph",
+            "prefer_nhwc",
+            "use_tf32",
+            "batch_size",
+            "height",
+            "width",
+            "multi_mask_output",
+            "num_labels",
+            "num_points",
+            "num_masks",
+            "intra_op_num_threads",
+            "warm_up",
+            "repeats",
+            "enable_nvtx_profile",
+            "torch_compile_mode",
+            "engine",
+            "average_latency",
+        ]
+        csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+        csv_writer.writeheader()
+
+        run_test(args, csv_writer)
+
+
+def _parse_arguments():
+    parser = argparse.ArgumentParser(description="Benchmark SMA2 for ONNX Runtime and PyTorch.")
+
+    parser.add_argument(
+        "--component",
+        required=False,
+        choices=["image_encoder", "image_decoder"],
+        default="image_encoder",
+        help="component to benchmark. Choices are image_encoder and image_decoder.",
+    )
+
+    parser.add_argument(
+        "--dtype", required=False, choices=["fp32", "fp16", "bf16"], default="fp32", help="Data type for inference."
+    )
+
+    parser.add_argument(
+        "--use_gpu",
+        required=False,
+        action="store_true",
+        help="Use GPU for inference.",
+    )
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "--use_cuda_graph",
+        required=False,
+        action="store_true",
+        help="Use cuda graph in onnxruntime.",
+    )
+    parser.set_defaults(use_cuda_graph=False)
+
+    parser.add_argument(
+        "--intra_op_num_threads",
+        required=False,
+        type=int,
+        choices=[0, 1, 2, 4, 8, 16],
+        default=0,
+        help="intra_op_num_threads for onnxruntime. ",
+    )
+
+    parser.add_argument(
+        "--batch_size",
+        required=False,
+        type=int,
+        default=1,
+        help="batch size",
+    )
+
+    parser.add_argument(
+        "--height",
+        required=False,
+        type=int,
+        default=1024,
+        help="image height",
+    )
+
+    parser.add_argument(
+        "--width",
+        required=False,
+        type=int,
+        default=1024,
+        help="image width",
+    )
+
+    parser.add_argument(
+        "--repeats",
+        required=False,
+        type=int,
+        default=1000,
+        help="number of repeats for performance test. Default is 1000.",
+    )
+
+    parser.add_argument(
+        "--warm_up",
+        required=False,
+        type=int,
+        default=5,
+        help="number of runs for warm up. Default is 5.",
+    )
+
+    parser.add_argument(
+        "--engine",
+        required=False,
+        type=str,
+        default="ort",
+        choices=["ort", "torch"],
+        help="engine for inference",
+    )
+
+    parser.add_argument(
+        "--multimask_output",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Export mask_decoder or image_decoder with multimask_output",
+    )
+
+    parser.add_argument(
+        "--prefer_nhwc",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Use prefer_nhwc=1 provider option for CUDAExecutionProvider",
+    )
+
+    parser.add_argument(
+        "--enable_nvtx_profile",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Enable nvtx profiling. It will add an extra run for profiling before performance test.",
+    )
+
+    parser.add_argument(
+        "--enable_ort_profile",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Enable ORT profiling.",
+    )
+
+    parser.add_argument(
+        "--enable_torch_profile",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Enable PyTorch profiling. It will add an extra run for profiling before performance test.",
+    )
+
+    parser.add_argument(
+        "--model_type",
+        required=False,
+        type=str,
+        default="sam2_hiera_large",
+        choices=["sam2_hiera_tiny", "sam2_hiera_small", "sam2_hiera_large", "sam2_hiera_base_plus"],
+        help="sam2 model name",
+    )
+
+    parser.add_argument(
+        "--sam2_dir",
+        required=False,
+        type=str,
+        default="./segment-anything-2",
+        help="The directory of segment-anything-2 git root directory",
+    )
+
+    parser.add_argument(
+        "--onnx_path",
+        required=False,
+        type=str,
+        default="./sam2_onnx_models/sam2_hiera_large_image_encoder.onnx",
+        help="path of onnx model",
+    )
+
+    parser.add_argument(
+        "--torch_compile_mode",
+        required=False,
+        type=str,
+        default=None,
+        choices=["reduce-overhead", "max-autotune", "max-autotune-no-cudagraphs", "none"],
+        help="torch compile mode. none will disable torch compile.",
+    )
+
+    args = parser.parse_args()
+
+    return args
+
+
+if __name__ == "__main__":
+    args = _parse_arguments()
+    print(f"arguments:{args}")
+
+    if args.torch_compile_mode is None:
+        # image decoder will fail with compile modes other than "none".
+        args.torch_compile_mode = "max-autotune" if args.component == "image_encoder" else "none"
+
+    if args.use_gpu:
+        assert torch.cuda.is_available()
+        if args.engine == "ort":
+            assert "CUDAExecutionProvider" in get_available_providers()
+            args.enable_torch_profile = False
+    else:
+        # Only support cuda profiling for now.
+        assert not args.enable_nvtx_profile
+        assert not args.enable_torch_profile
+
+    if args.enable_nvtx_profile or args.enable_torch_profile:
+        run_test(args)
+    else:
+        run_perf_test(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..bca091ae91a7599691f63498d6b517f1fc8d6376
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/convert_to_onnx.py
@@ -0,0 +1,270 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import argparse
+import os
+import pathlib
+import sys
+
+import torch
+from image_decoder import export_decoder_onnx, test_decoder_onnx
+from image_encoder import export_image_encoder_onnx, test_image_encoder_onnx
+from mask_decoder import export_mask_decoder_onnx, test_mask_decoder_onnx
+from prompt_encoder import export_prompt_encoder_onnx, test_prompt_encoder_onnx
+from sam2_demo import run_demo, show_all_images
+from sam2_utils import load_sam2_model, sam2_onnx_path, setup_logger
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser(description="Export SAM2 models to ONNX")
+
+    parser.add_argument(
+        "--model_type",
+        required=False,
+        type=str,
+        choices=["sam2_hiera_tiny", "sam2_hiera_small", "sam2_hiera_large", "sam2_hiera_base_plus"],
+        default="sam2_hiera_large",
+        help="The model type to export",
+    )
+
+    parser.add_argument(
+        "--components",
+        required=False,
+        nargs="+",
+        choices=["image_encoder", "mask_decoder", "prompt_encoder", "image_decoder"],
+        default=["image_encoder", "image_decoder"],
+        help="Type of ONNX models to export. "
+        "Note that image_decoder is a combination of prompt_encoder and mask_decoder",
+    )
+
+    parser.add_argument(
+        "--output_dir",
+        type=str,
+        help="The output directory for the ONNX models",
+        default="sam2_onnx_models",
+    )
+
+    parser.add_argument(
+        "--dynamic_batch_axes",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Export image_encoder with dynamic batch axes",
+    )
+
+    parser.add_argument(
+        "--multimask_output",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Export mask_decoder or image_decoder with multimask_output",
+    )
+
+    parser.add_argument(
+        "--disable_dynamic_multimask_via_stability",
+        required=False,
+        action="store_true",
+        help="Disable mask_decoder dynamic_multimask_via_stability, and output first mask only."
+        "This option will be ignored when multimask_output is True",
+    )
+
+    parser.add_argument(
+        "--sam2_dir",
+        required=False,
+        type=str,
+        default="./segment-anything-2",
+        help="The directory of segment-anything-2 git repository",
+    )
+
+    parser.add_argument(
+        "--overwrite",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Overwrite onnx model file if exists.",
+    )
+
+    parser.add_argument(
+        "--demo",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Run demo with the exported ONNX models.",
+    )
+
+    parser.add_argument(
+        "--optimize",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Optimize onnx models",
+    )
+
+    parser.add_argument(
+        "--dtype", required=False, choices=["fp32", "fp16"], default="fp32", help="Data type for inference."
+    )
+
+    parser.add_argument(
+        "--use_gpu",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Optimize onnx models for GPU",
+    )
+
+    parser.add_argument(
+        "--dynamo",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Use dynamo for exporting onnx model. Only image_encoder supports dynamo right now.",
+    )
+
+    parser.add_argument(
+        "--verbose",
+        required=False,
+        default=False,
+        action="store_true",
+        help="Print verbose information",
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def optimize_sam2_model(onnx_model_path, optimized_model_path, float16: bool, use_gpu: bool):
+    print(f"Optimizing {onnx_model_path} to {optimized_model_path} with float16={float16} and use_gpu={use_gpu}...")
+
+    # Import from source directory.
+    transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+    if transformers_dir not in sys.path:
+        sys.path.insert(0, transformers_dir)
+    from optimizer import optimize_model  # noqa: PLC0415
+
+    optimized_model = optimize_model(onnx_model_path, model_type="sam2", opt_level=1, use_gpu=use_gpu)
+    if float16:
+        optimized_model.convert_float_to_float16(keep_io_types=False)
+    optimized_model.save_model_to_file(optimized_model_path)
+
+
+def main():
+    args = parse_arguments()
+
+    sam2_model = load_sam2_model(args.sam2_dir, args.model_type, device="cpu")
+
+    pathlib.Path(args.output_dir).mkdir(parents=True, exist_ok=True)
+
+    for component in args.components:
+        onnx_model_path = sam2_onnx_path(args.output_dir, args.model_type, component, args.multimask_output)
+        if component == "image_encoder":
+            if args.overwrite or not os.path.exists(onnx_model_path):
+                export_image_encoder_onnx(
+                    sam2_model, onnx_model_path, args.dynamic_batch_axes, args.verbose, args.dynamo
+                )
+                test_image_encoder_onnx(sam2_model, onnx_model_path, dynamic_batch_axes=args.dynamic_batch_axes)
+
+        elif component == "mask_decoder":
+            if args.overwrite or not os.path.exists(onnx_model_path):
+                export_mask_decoder_onnx(
+                    sam2_model,
+                    onnx_model_path,
+                    args.multimask_output,
+                    not args.disable_dynamic_multimask_via_stability,
+                    args.verbose,
+                )
+                test_mask_decoder_onnx(
+                    sam2_model,
+                    onnx_model_path,
+                    args.multimask_output,
+                    not args.disable_dynamic_multimask_via_stability,
+                )
+        elif component == "prompt_encoder":
+            if args.overwrite or not os.path.exists(onnx_model_path):
+                export_prompt_encoder_onnx(sam2_model, onnx_model_path)
+                test_prompt_encoder_onnx(sam2_model, onnx_model_path)
+        else:
+            assert component == "image_decoder"
+            if args.overwrite or not os.path.exists(onnx_model_path):
+                export_decoder_onnx(sam2_model, onnx_model_path, args.multimask_output)
+                test_decoder_onnx(sam2_model, onnx_model_path, args.multimask_output)
+
+    suffix = ""
+    convert_to_fp16 = args.dtype == "fp16"
+    if args.optimize:
+        suffix = f"_{args.dtype}_" + ("gpu" if args.use_gpu else "cpu")
+        for component in args.components:
+            onnx_model_path = sam2_onnx_path(args.output_dir, args.model_type, component, args.multimask_output)
+            optimized_model_path = sam2_onnx_path(
+                args.output_dir, args.model_type, component, args.multimask_output, suffix
+            )
+            optimize_sam2_model(onnx_model_path, optimized_model_path, convert_to_fp16, args.use_gpu)
+
+    if args.demo:
+        # Export required ONNX models for demo if not already exported.
+        image_encoder_onnx_path = sam2_onnx_path(
+            args.output_dir, args.model_type, "image_encoder", args.multimask_output
+        )
+        if not os.path.exists(image_encoder_onnx_path):
+            export_image_encoder_onnx(sam2_model, image_encoder_onnx_path, args.dynamic_batch_axes, args.verbose)
+
+        image_decoder_onnx_path = sam2_onnx_path(args.output_dir, args.model_type, "image_decoder", False)
+        if not os.path.exists(image_decoder_onnx_path):
+            export_decoder_onnx(sam2_model, image_decoder_onnx_path, False)
+
+        image_decoder_multi_onnx_path = sam2_onnx_path(args.output_dir, args.model_type, "image_decoder", True)
+        if not os.path.exists(image_decoder_multi_onnx_path):
+            export_decoder_onnx(sam2_model, image_decoder_multi_onnx_path, True)
+
+        dtype = torch.float32 if args.dtype == "fp32" else torch.float16
+        if suffix:
+            optimized_image_encoder_onnx_path = image_encoder_onnx_path.replace(".onnx", f"{suffix}.onnx")
+            if not os.path.exists(optimized_image_encoder_onnx_path):
+                optimize_sam2_model(
+                    image_encoder_onnx_path, optimized_image_encoder_onnx_path, convert_to_fp16, args.use_gpu
+                )
+
+            optimized_image_decoder_onnx_path = image_decoder_onnx_path.replace(".onnx", f"{suffix}.onnx")
+            if not os.path.exists(optimized_image_decoder_onnx_path):
+                optimize_sam2_model(
+                    image_decoder_onnx_path, optimized_image_decoder_onnx_path, convert_to_fp16, args.use_gpu
+                )
+
+            optimized_image_decoder_multi_onnx_path = image_decoder_multi_onnx_path.replace(".onnx", f"{suffix}.onnx")
+            if not os.path.exists(optimized_image_decoder_multi_onnx_path):
+                optimize_sam2_model(
+                    image_decoder_multi_onnx_path,
+                    optimized_image_decoder_multi_onnx_path,
+                    convert_to_fp16,
+                    args.use_gpu,
+                )
+
+            # Use optimized models to run demo.
+            image_encoder_onnx_path = optimized_image_encoder_onnx_path
+            image_decoder_onnx_path = optimized_image_decoder_onnx_path
+            image_decoder_multi_onnx_path = optimized_image_decoder_multi_onnx_path
+
+        ort_image_files = run_demo(
+            args.sam2_dir,
+            args.model_type,
+            engine="ort",
+            dtype=dtype,
+            image_encoder_onnx_path=image_encoder_onnx_path,
+            image_decoder_onnx_path=image_decoder_onnx_path,
+            image_decoder_multi_onnx_path=image_decoder_multi_onnx_path,
+            use_gpu=args.use_gpu,
+        )
+        print("demo output files for ONNX Runtime:", ort_image_files)
+
+        # Get results from torch engine to compare.
+        torch_image_files = run_demo(args.sam2_dir, args.model_type, engine="torch", dtype=dtype, use_gpu=args.use_gpu)
+        print("demo output files for PyTorch:", torch_image_files)
+
+        show_all_images(ort_image_files, torch_image_files, suffix)
+        print(f"Combined demo output: sam2_demo{suffix}.png")
+
+
+if __name__ == "__main__":
+    setup_logger(verbose=False)
+    with torch.no_grad():
+        main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_decoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..b5e0ceea90e87b7fdd36d9b2f55b390f5d5347fc
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_decoder.py
@@ -0,0 +1,272 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+import warnings
+
+import torch
+import torch.nn.functional as F
+from image_encoder import SAM2ImageEncoder, random_sam2_input_image
+from mask_decoder import SAM2MaskDecoder
+from prompt_encoder import SAM2PromptEncoder
+from sam2.modeling.sam2_base import SAM2Base
+from sam2_utils import compare_tensors_with_tolerance
+from torch import nn
+
+logger = logging.getLogger(__name__)
+
+
+class SAM2ImageDecoder(nn.Module):
+    def __init__(
+        self,
+        sam_model: SAM2Base,
+        multimask_output: bool,
+        dynamic_multimask_via_stability: bool = True,
+        return_logits: bool = False,
+        mask_threshold: float = 0.0,
+    ) -> None:
+        super().__init__()
+        self.prompt_encoder = SAM2PromptEncoder(sam_model)
+        self.mask_decoder = SAM2MaskDecoder(sam_model, multimask_output, dynamic_multimask_via_stability)
+        self.return_logits = return_logits
+        self.mask_threshold = mask_threshold
+
+    @torch.no_grad()
+    def forward(
+        self,
+        image_features_0: torch.Tensor,
+        image_features_1: torch.Tensor,
+        image_embeddings: torch.Tensor,
+        point_coords: torch.Tensor,
+        point_labels: torch.Tensor,
+        input_masks: torch.Tensor,
+        has_input_masks: torch.Tensor,
+        original_image_size: torch.Tensor,
+        enable_nvtx_profile: bool = False,
+    ):
+        """
+        Decode masks from image features and prompts. Batched images are not supported. H=W=1024.
+
+        Args:
+            image_features_0 (torch.Tensor): [1, 32, H/4, W/4]. high resolution features of level 0 from image encoder.
+            image_features_1 (torch.Tensor): [1, 64, H/8, W/8]. high resolution features of level 1 from image encoder.
+            image_embeddings (torch.Tensor): [1, 256, H/16, W/16]. image embedding from image encoder.
+            point_coords (torch.Tensor): [L, P, 2] shape and float32 dtype and contains the absolute pixel
+                                         coordinate in (x, y) format of the P input points in image of size 1024x1024.
+            point_labels (torch.Tensor): shape [L, P] and int32 dtype, where 1 means
+                                         positive (foreground), 0 means negative (background), -1 means padding,
+                                         2 (box left upper corner), 3 (box right bottom corner).
+            input_masks (torch.Tensor): [L, 1, H/4, W/4]. Low resolution mask input to the model.
+                                        Typically coming from a previous iteration.
+            has_input_masks (torch.Tensor): [L]. 1.0 if input_masks is used, 0.0 otherwise.
+            original_image_size(torch.Tensor): [2]. original image size H_o, W_o.
+            enable_nvtx_profile (bool): enable NVTX profiling.
+
+        Returns:
+            masks (torch.Tensor): [1, M, H_o, W_o] where M=3 or 1. Masks of original image size.
+            iou_predictions (torch.Tensor): [1, M]. scores for M masks.
+            low_res_masks (torch.Tensor, optional): [1, M, H/4, W/4]. low resolution masks.
+        """
+        nvtx_helper = None
+        if enable_nvtx_profile:
+            from nvtx_helper import NvtxHelper  # noqa: PLC0415
+
+            nvtx_helper = NvtxHelper(["prompt_encoder", "mask_decoder", "post_process"])
+
+        if nvtx_helper is not None:
+            nvtx_helper.start_profile("prompt_encoder", color="blue")
+
+        sparse_embeddings, dense_embeddings, image_pe = self.prompt_encoder(
+            point_coords, point_labels, input_masks, has_input_masks
+        )
+
+        if nvtx_helper is not None:
+            nvtx_helper.stop_profile("prompt_encoder")
+            nvtx_helper.start_profile("mask_decoder", color="red")
+
+        low_res_masks, iou_predictions = self.mask_decoder(
+            image_features_0, image_features_1, image_embeddings, image_pe, sparse_embeddings, dense_embeddings
+        )
+
+        if nvtx_helper is not None:
+            nvtx_helper.stop_profile("mask_decoder")
+            nvtx_helper.start_profile("post_process", color="green")
+
+        # Interpolate the low resolution masks back to the original image size.
+        masks = F.interpolate(
+            low_res_masks,
+            (original_image_size[0], original_image_size[1]),
+            mode="bilinear",
+            align_corners=False,  # Note that align_corners=True has less mismatches during comparing ORT and PyTorch.
+        )
+
+        low_res_masks = torch.clamp(low_res_masks, -32.0, 32.0)
+        if not self.return_logits:
+            masks = masks > self.mask_threshold
+
+        if nvtx_helper is not None:
+            nvtx_helper.stop_profile("post_process")
+            nvtx_helper.print_latency()
+
+        return masks, iou_predictions, low_res_masks
+
+
+def export_decoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    multimask_output: bool = False,
+    verbose: bool = False,
+):
+    batch_size = 1
+    image = random_sam2_input_image(batch_size)
+    sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+    image_features_0, image_features_1, image_embeddings = sam2_encoder(image)
+
+    logger.info("image_features_0.shape: %s", image_features_0.shape)
+    logger.info("image_features_1.shape: %s", image_features_1.shape)
+    logger.info("image_embeddings.shape: %s", image_embeddings.shape)
+
+    sam2_decoder = SAM2ImageDecoder(
+        sam2_model,
+        multimask_output=multimask_output,
+        dynamic_multimask_via_stability=True,
+    ).cpu()
+
+    num_labels = 2
+    num_points = 3
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.int32)
+    input_masks = torch.zeros(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.ones(1, dtype=torch.float)
+    original_image_size = torch.tensor([1200, 1800], dtype=torch.int32)
+
+    example_inputs = (
+        image_features_0,
+        image_features_1,
+        image_embeddings,
+        point_coords,
+        point_labels,
+        input_masks,
+        has_input_masks,
+        original_image_size,
+    )
+
+    logger.info("point_coords.shape: %s", point_coords.shape)
+    logger.info("point_labels.shape: %s", point_labels.shape)
+    logger.info("input_masks.shape: %s", input_masks.shape)
+    logger.info("has_input_masks.shape: %s", has_input_masks.shape)
+    logger.info("original_image_size.shape: %s", original_image_size.shape)
+
+    if verbose:
+        masks, iou_predictions, low_res_masks = sam2_decoder(*example_inputs)
+        logger.info("masks.shape: %s", masks.shape)
+        logger.info("iou_predictions.shape: %s", iou_predictions.shape)
+        logger.info("low_res_masks.shape: %s", low_res_masks.shape)
+
+    input_names = [
+        "image_features_0",
+        "image_features_1",
+        "image_embeddings",
+        "point_coords",
+        "point_labels",
+        "input_masks",
+        "has_input_masks",
+        "original_image_size",
+    ]
+
+    output_names = ["masks", "iou_predictions", "low_res_masks"]
+
+    dynamic_axes = {
+        "point_coords": {0: "num_labels", 1: "num_points"},
+        "point_labels": {0: "num_labels", 1: "num_points"},
+        "input_masks": {0: "num_labels"},
+        "has_input_masks": {0: "num_labels"},
+        "masks": {0: "num_labels", 2: "original_image_height", 3: "original_image_width"},
+        "low_res_masks": {0: "num_labels"},
+        "iou_predictions": {0: "num_labels"},
+    }
+
+    with warnings.catch_warnings():
+        if not verbose:
+            warnings.filterwarnings("ignore", category=torch.jit.TracerWarning)
+            warnings.filterwarnings("ignore", category=UserWarning)
+
+        torch.onnx.export(
+            sam2_decoder,
+            example_inputs,
+            onnx_model_path,
+            export_params=True,
+            opset_version=16,
+            do_constant_folding=True,
+            input_names=input_names,
+            output_names=output_names,
+            dynamic_axes=dynamic_axes,
+        )
+
+    logger.info("decoder onnx model saved to %s", onnx_model_path)
+
+
+def test_decoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    multimask_output=False,
+):
+    batch_size = 1
+    image = random_sam2_input_image(batch_size)
+    sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+    image_features_0, image_features_1, image_embeddings = sam2_encoder(image)
+
+    sam2_image_decoder = SAM2ImageDecoder(
+        sam2_model,
+        multimask_output=multimask_output,
+        dynamic_multimask_via_stability=True,
+    ).cpu()
+
+    num_labels = 1
+    num_points = 5
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.int32)
+    input_masks = torch.zeros(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.zeros(1, dtype=torch.float)
+    original_image_size = torch.tensor([1500, 1500], dtype=torch.int32)
+
+    example_inputs = (
+        image_features_0,
+        image_features_1,
+        image_embeddings,
+        point_coords,
+        point_labels,
+        input_masks,
+        has_input_masks,
+        original_image_size,
+    )
+
+    masks, iou_predictions, low_res_masks = sam2_image_decoder(*example_inputs)
+
+    import onnxruntime  # noqa: PLC0415
+
+    ort_session = onnxruntime.InferenceSession(onnx_model_path, providers=["CPUExecutionProvider"])
+
+    model_inputs = ort_session.get_inputs()
+    input_names = [model_inputs[i].name for i in range(len(model_inputs))]
+    logger.info("input_names: %s", input_names)
+
+    model_outputs = ort_session.get_outputs()
+    output_names = [model_outputs[i].name for i in range(len(model_outputs))]
+    logger.info("output_names: %s", output_names)
+    inputs = {model_inputs[i].name: example_inputs[i].numpy() for i in range(len(model_inputs))}
+    outputs = ort_session.run(output_names, inputs)
+
+    for i, output_name in enumerate(output_names):
+        logger.info(f"{output_name}.shape: %s", outputs[i].shape)
+
+    ort_masks, ort_iou_predictions, ort_low_res_masks = outputs
+    if (
+        compare_tensors_with_tolerance("masks", masks.float(), torch.tensor(ort_masks).float())
+        and compare_tensors_with_tolerance("iou_predictions", iou_predictions, torch.tensor(ort_iou_predictions))
+        and compare_tensors_with_tolerance("low_res_masks", low_res_masks, torch.tensor(ort_low_res_masks))
+    ):
+        print("onnx model has been verified:", onnx_model_path)
+    else:
+        print("onnx model verification failed:", onnx_model_path)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_encoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..7dc9226fbcc4a9945d59e4bf60046e21c055587a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/image_encoder.py
@@ -0,0 +1,236 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+import warnings
+
+import torch
+from sam2.modeling.sam2_base import SAM2Base
+from sam2_utils import compare_tensors_with_tolerance, random_sam2_input_image
+from torch import nn
+
+import onnxruntime
+
+logger = logging.getLogger(__name__)
+
+
+class SAM2ImageEncoder(nn.Module):
+    def __init__(self, sam_model: SAM2Base) -> None:
+        super().__init__()
+        self.model = sam_model
+        self.image_encoder = sam_model.image_encoder
+        self.no_mem_embed = sam_model.no_mem_embed
+
+    def forward(
+        self,
+        image: torch.Tensor,
+        enable_nvtx_profile: bool = False,
+    ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+        """
+        Encodes images into features.
+
+        Only supports H=W=1024. If you want to use different image sizes like 512x512,
+        see https://github.com/facebookresearch/segment-anything-2/issues/138.
+
+        Args:
+            image (torch.Tensor): images of shape [B, 3, H, W], B is batch size, H and W are height and width.
+            enable_nvtx_profile (bool): enable NVTX profiling.
+
+        Returns:
+            image_features_0: image features of shape [B, 32, H/4, W/4] - high resolution features of level 0
+            image_features_1: image features of shape [B, 64, H/8, W/8] - high resolution features of level 1
+            image_embeddings: image features of shape [B, 256, H/16, W/16] - 16 is the backbone_stride
+        """
+        nvtx_helper = None
+        if enable_nvtx_profile:
+            from nvtx_helper import NvtxHelper  # noqa: PLC0415
+
+            nvtx_helper = NvtxHelper(["image_encoder", "post_process"])
+
+        if nvtx_helper is not None:
+            nvtx_helper.start_profile("image_encoder")
+
+        backbone_out = self.image_encoder(image)
+
+        if nvtx_helper is not None:
+            nvtx_helper.stop_profile("image_encoder")
+            nvtx_helper.start_profile("post_process")
+
+        # precompute projected level 0 and level 1 features in SAM decoder
+        # to avoid running it again on every SAM click
+        backbone_out["backbone_fpn"][0] = self.model.sam_mask_decoder.conv_s0(backbone_out["backbone_fpn"][0])
+        backbone_out["backbone_fpn"][1] = self.model.sam_mask_decoder.conv_s1(backbone_out["backbone_fpn"][1])
+
+        # Prepare and flatten visual features.
+        feature_maps = backbone_out["backbone_fpn"][-self.model.num_feature_levels :]
+        vision_pos_embeds = backbone_out["vision_pos_enc"][-self.model.num_feature_levels :]
+        feat_sizes = [(x.shape[-2], x.shape[-1]) for x in vision_pos_embeds]
+
+        # flatten NxCxHxW to HWxNxC
+        # TODO: we should avoid this transpose since it will be transposed back to NCHW later.
+        vision_feats = [x.flatten(2).permute(2, 0, 1) for x in feature_maps]
+
+        vision_feats[-1] = vision_feats[-1] + self.no_mem_embed
+
+        feats = [
+            feat.permute(1, 2, 0).reshape(1, -1, *feat_size)
+            for feat, feat_size in zip(vision_feats[::-1], feat_sizes[::-1], strict=False)
+        ][::-1]
+
+        if nvtx_helper is not None:
+            nvtx_helper.stop_profile("post_process")
+            nvtx_helper.print_latency()
+
+        return feats[0], feats[1], feats[2]
+
+
+def export_image_encoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    dynamic_batch_axes: bool = False,
+    verbose: bool = False,
+    dynamo: bool = False,
+    clear_dynamo_metadata: bool = False,
+):
+    image = random_sam2_input_image()
+
+    sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+    image_features_0, image_features_1, image_embeddings = sam2_encoder(image)
+    logger.info("image.shape: %s", image.shape)
+    logger.info("image_features_0.shape: %s", image_features_0.shape)
+    logger.info("image_features_1.shape: %s", image_features_1.shape)
+    logger.info("image_embeddings.shape: %s", image_embeddings.shape)
+
+    dynamic_axes = None
+    if dynamic_batch_axes:
+        dynamic_axes = {
+            "image": {0: "batch_size"},
+            "image_features_0": {0: "batch_size"},
+            "image_features_1": {0: "batch_size"},
+            "image_embeddings": {0: "batch_size"},
+        }
+
+    with warnings.catch_warnings():
+        if not verbose:
+            warnings.filterwarnings("ignore", category=torch.jit.TracerWarning)
+            warnings.filterwarnings("ignore", category=UserWarning)
+
+        if not dynamo:
+            torch.onnx.export(
+                sam2_encoder,
+                image,
+                onnx_model_path,
+                export_params=True,
+                opset_version=17,
+                do_constant_folding=True,
+                input_names=["image"],
+                output_names=["image_features_0", "image_features_1", "image_embeddings"],
+                dynamic_axes=dynamic_axes,
+            )
+        else:
+            torch._dynamo.config.capture_scalar_outputs = True
+            ep = torch.export.export(
+                sam2_encoder,
+                args=(image,),
+                strict=False,
+                dynamic_shapes=[
+                    {0: torch.export.Dim.AUTO},
+                ],
+            )
+
+            onnx_program = torch.onnx.export(
+                ep,
+                (),
+                opset_version=17,
+                input_names=["image"],
+                output_names=["image_features_0", "image_features_1", "image_embeddings"],
+                dynamo=True,
+            )
+            onnx_program.optimize()
+            onnx_program.save(onnx_model_path + ".dynamo.onnx", external_data=False)
+            import onnx  # noqa: PLC0415
+
+            from onnxruntime.transformers.dynamo_onnx_helper import DynamoOnnxHelper  # noqa: PLC0415
+
+            onnx_model = onnx.load_model(onnx_model_path + ".dynamo.onnx", load_external_data=True)
+            if dynamic_batch_axes:
+                # Fix labels of dynamic axes since they can't be specified during Dynamo export currently
+                onnx_model.graph.input[0].type.tensor_type.shape.dim[0].dim_param = "batch_size"
+                for i in range(3):
+                    onnx_model.graph.output[i].type.tensor_type.shape.dim[0].dim_param = "batch_size"
+
+            onnx_model_helper = DynamoOnnxHelper(onnx_model)
+            onnx_model_helper.convert_constants_to_initializers()
+            if clear_dynamo_metadata:
+                onnx_model_helper.clear_metadata()
+
+            import os  # noqa: PLC0415
+
+            if os.path.exists(onnx_model_path):
+                os.remove(onnx_model_path)
+            if os.path.exists(onnx_model_path + ".data"):
+                os.remove(onnx_model_path + ".data")
+            onnx_model_helper.model.save_model_to_file(
+                onnx_model_path, use_external_data_format=True, all_tensors_to_one_file=True, convert_attribute=True
+            )
+
+    print("encoder onnx model saved to", onnx_model_path)
+
+
+def test_image_encoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    dynamic_batch_axes=False,
+):
+    ort_session = onnxruntime.InferenceSession(onnx_model_path, providers=["CPUExecutionProvider"])
+
+    model_inputs = ort_session.get_inputs()
+    input_names = [model_inputs[i].name for i in range(len(model_inputs))]
+    logger.info("input_names: %s", input_names)
+
+    model_outputs = ort_session.get_outputs()
+    output_names = [model_outputs[i].name for i in range(len(model_outputs))]
+    logger.info("output_names: %s", output_names)
+
+    batch_sizes = [1, 2] if dynamic_batch_axes else [1]
+    for batch_size in batch_sizes:
+        image = random_sam2_input_image(batch_size)
+
+        sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+        image_features_0, image_features_1, image_embeddings = sam2_encoder(image.clone())
+
+        logger.info("image.shape: %s", image.shape)
+        logger.info("image_features_0.shape: %s", image_features_0.shape)
+        logger.info("image_features_1.shape: %s", image_features_1.shape)
+        logger.info("image_embeddings.shape: %s", image_embeddings.shape)
+
+        outputs = ort_session.run(output_names, {"image": image.numpy()})
+        for i, output_name in enumerate(output_names):
+            logger.info("output %s shape %s", output_name, outputs[i].shape)
+        ort_image_features_0, ort_image_features_1, ort_image_embeddings = outputs
+
+        # ONNXRuntime and PyTorch has about 0.75% mismatched elements, but seems not impacting segmentation results.
+        if (
+            compare_tensors_with_tolerance(
+                "image_features_0",
+                image_features_0,
+                torch.tensor(ort_image_features_0),
+                mismatch_percentage_tolerance=1,
+            )
+            and compare_tensors_with_tolerance(
+                "image_features_1",
+                image_features_1,
+                torch.tensor(ort_image_features_1),
+                mismatch_percentage_tolerance=1,
+            )
+            and compare_tensors_with_tolerance(
+                "image_embeddings",
+                image_embeddings,
+                torch.tensor(ort_image_embeddings),
+                mismatch_percentage_tolerance=1,
+            )
+        ):
+            print(f"onnx model has been verified for batch_size={batch_size}: {onnx_model_path}")
+        else:
+            print(f"onnx model verification failed for batch_size={batch_size}: {onnx_model_path}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/mask_decoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/mask_decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..5fab016b8ae79ae4bf6b0a41d12dee03e0443f0f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/mask_decoder.py
@@ -0,0 +1,208 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+import warnings
+
+import torch
+from image_encoder import SAM2ImageEncoder, random_sam2_input_image
+from prompt_encoder import SAM2PromptEncoder
+from sam2.modeling.sam2_base import SAM2Base
+from torch import nn
+
+logger = logging.getLogger(__name__)
+
+
+class SAM2MaskDecoder(nn.Module):
+    def __init__(
+        self,
+        sam_model: SAM2Base,
+        multimask_output: bool,
+        dynamic_multimask_via_stability: bool = True,
+    ) -> None:
+        super().__init__()
+        self.mask_decoder = sam_model.sam_mask_decoder
+        self.prompt_encoder = sam_model.sam_prompt_encoder
+        self.model = sam_model
+        self.multimask_output = multimask_output
+        self.dynamic_multimask_via_stability = dynamic_multimask_via_stability
+
+    @torch.no_grad()
+    def forward(
+        self,
+        image_features_0: torch.Tensor,
+        image_features_1: torch.Tensor,
+        image_embeddings: torch.Tensor,
+        image_pe: torch.Tensor,
+        sparse_embeddings: torch.Tensor,
+        dense_embeddings: torch.Tensor,
+    ):
+        """
+        Decode masks from image and prompt embeddings. Only support H=W=1024.
+
+        Args:
+            image_features_0 (torch.Tensor): [1, 32, H/4, W/4]. high resolution features of level 0 from image encoder.
+            image_features_1 (torch.Tensor): [1, 64, H/8, W/8]. high resolution features of level 1 from image encoder.
+            image_embeddings (torch.Tensor): [1, 256, H/16, W/16]. image embedding from image encoder.
+            image_pe (torch.Tensor): [1, 256, H/16, W/16]. image positional encoding.
+            sparse_embeddings (torch.Tensor): [L, P+1, 256], embedding for points and boxes.
+            dense_embeddings (torch.Tensor):  [L, 256, H/16, W/16]. embedding for input masks.
+
+        Returns:
+            low_res_masks (torch.Tensor, optional): [1, M, H/4, W/4]. low resolution masks.
+            iou_predictions (torch.Tensor): [1, M]. scores for M masks.
+        """
+        low_res_masks, iou_predictions, _, _ = self.mask_decoder.predict_masks(
+            image_embeddings=image_embeddings,
+            image_pe=image_pe,
+            sparse_prompt_embeddings=sparse_embeddings,
+            dense_prompt_embeddings=dense_embeddings,
+            repeat_image=sparse_embeddings.shape[0] > 1,  # batch mode
+            high_res_features=[image_features_0, image_features_1],
+        )
+
+        if self.multimask_output:
+            low_res_masks = low_res_masks[:, 1:, :, :]
+            iou_predictions = iou_predictions[:, 1:]
+        elif self.dynamic_multimask_via_stability:
+            # When outputting a single mask, if the stability score from the current single-mask
+            # output (based on output token 0) falls below a threshold, we instead select from
+            # multi-mask outputs (based on output token 1~3) the mask with the highest predicted IoU score.
+            low_res_masks, iou_predictions = self.mask_decoder._dynamic_multimask_via_stability(
+                low_res_masks, iou_predictions
+            )
+        else:
+            low_res_masks = low_res_masks[:, 0:1, :, :]
+            iou_predictions = iou_predictions[:, 0:1]
+
+        return low_res_masks, iou_predictions
+
+
+def export_mask_decoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    multimask_output: bool,
+    dynamic_multimask_via_stability: bool = True,
+    verbose=False,
+):
+    sam2_prompt_encoder = SAM2PromptEncoder(sam2_model).cpu()
+
+    image = random_sam2_input_image()
+    sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+    image_features_0, image_features_1, image_embeddings = sam2_encoder(image)
+    logger.info("image_features_0.shape: %s", image_features_0.shape)
+    logger.info("image_features_1.shape: %s", image_features_1.shape)
+    logger.info("image_embeddings.shape: %s", image_embeddings.shape)
+
+    # encode an random prompt
+    num_labels = 2
+    num_points = 3
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.float)
+    input_masks = torch.zeros(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.ones(1, dtype=torch.float)
+
+    sparse_embeddings, dense_embeddings, image_pe = sam2_prompt_encoder(
+        point_coords, point_labels, input_masks, has_input_masks
+    )
+
+    logger.info("sparse_embeddings.shape: %s", sparse_embeddings.shape)
+    logger.info("dense_embeddings.shape: %s", dense_embeddings.shape)
+    logger.info("image_pe.shape: %s", image_pe.shape)
+
+    sam2_mask_decoder = SAM2MaskDecoder(sam2_model, multimask_output, dynamic_multimask_via_stability)
+    inputs = (image_features_0, image_features_1, image_embeddings, image_pe, sparse_embeddings, dense_embeddings)
+    low_res_masks, iou_predictions = sam2_mask_decoder(*inputs)
+    logger.info("low_res_masks.shape: %s", low_res_masks.shape)
+    logger.info("iou_predictions.shape: %s", iou_predictions.shape)
+
+    with warnings.catch_warnings():
+        if not verbose:
+            warnings.filterwarnings("ignore", category=torch.jit.TracerWarning)
+            warnings.filterwarnings("ignore", category=UserWarning)
+        torch.onnx.export(
+            sam2_mask_decoder,
+            inputs,
+            onnx_model_path,
+            export_params=True,
+            opset_version=18,
+            do_constant_folding=True,
+            input_names=[
+                "image_features_0",
+                "image_features_1",
+                "image_embeddings",
+                "image_pe",
+                "sparse_embeddings",
+                "dense_embeddings",
+            ],
+            output_names=["low_res_masks", "iou_predictions"],
+            dynamic_axes={
+                "sparse_embeddings": {0: "num_labels", 1: "num_points+1"},
+                "dense_embeddings": {0: "num_labels"},
+                "low_res_masks": {0: "num_labels"},
+                "iou_predictions": {0: "num_labels"},
+            },
+        )
+
+    print("mask decoder onnx model saved to", onnx_model_path)
+
+
+def test_mask_decoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+    multimask_output: bool,
+    dynamic_multimask_via_stability: bool,
+):
+    sam2_prompt_encoder = SAM2PromptEncoder(sam2_model).cpu()
+
+    image = random_sam2_input_image()
+    sam2_encoder = SAM2ImageEncoder(sam2_model).cpu()
+    image_features_0, image_features_1, image_embeddings = sam2_encoder(image)
+
+    num_labels = 1
+    num_points = 5
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.float)
+    input_masks = torch.rand(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.ones(1, dtype=torch.float)
+
+    sparse_embeddings, dense_embeddings, image_pe = sam2_prompt_encoder(
+        point_coords, point_labels, input_masks, has_input_masks
+    )
+
+    sam2_mask_decoder = SAM2MaskDecoder(sam2_model, multimask_output, dynamic_multimask_via_stability)
+    inputs = (image_features_0, image_features_1, image_embeddings, image_pe, sparse_embeddings, dense_embeddings)
+    low_res_masks, iou_predictions = sam2_mask_decoder(*inputs)
+
+    import onnxruntime  # noqa: PLC0415
+
+    ort_session = onnxruntime.InferenceSession(onnx_model_path, providers=["CPUExecutionProvider"])
+
+    model_inputs = ort_session.get_inputs()
+    input_names = [model_inputs[i].name for i in range(len(model_inputs))]
+    logger.info("input_names: %s", input_names)
+
+    model_outputs = ort_session.get_outputs()
+    output_names = [model_outputs[i].name for i in range(len(model_outputs))]
+    logger.info("output_names: %s", output_names)
+
+    outputs = ort_session.run(
+        output_names,
+        {
+            "image_features_0": image_features_0.numpy(),
+            "image_features_1": image_features_1.numpy(),
+            "image_embeddings": image_embeddings.numpy(),
+            "image_pe": image_pe.numpy(),
+            "sparse_embeddings": sparse_embeddings.numpy(),
+            "dense_embeddings": dense_embeddings.numpy(),
+        },
+    )
+
+    for i, output_name in enumerate(output_names):
+        logger.info("output %s shape: %s", output_name, outputs[i].shape)
+
+    ort_low_res_masks, ort_iou_predictions = outputs
+    torch.testing.assert_close(low_res_masks, torch.tensor(ort_low_res_masks), atol=5e-3, rtol=1e-4)
+    torch.testing.assert_close(iou_predictions, torch.tensor(ort_iou_predictions), atol=5e-3, rtol=1e-4)
+    print(f"onnx model has been verified: {onnx_model_path}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/nvtx_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/nvtx_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f561564050edc4782615e2703ac4dc76c20d648
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/nvtx_helper.py
@@ -0,0 +1,33 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import nvtx
+from cuda import cudart
+
+
+class NvtxHelper:
+    def __init__(self, stages):
+        self.stages = stages
+        self.events = {}
+        for stage in stages:
+            for marker in ["start", "stop"]:
+                self.events[stage + "-" + marker] = cudart.cudaEventCreate()[1]
+        self.markers = {}
+
+    def start_profile(self, stage, color="blue"):
+        self.markers[stage] = nvtx.start_range(message=stage, color=color)
+        event_name = stage + "-start"
+        if event_name in self.events:
+            cudart.cudaEventRecord(self.events[event_name], 0)
+
+    def stop_profile(self, stage):
+        event_name = stage + "-stop"
+        if event_name in self.events:
+            cudart.cudaEventRecord(self.events[event_name], 0)
+        nvtx.end_range(self.markers[stage])
+
+    def print_latency(self):
+        for stage in self.stages:
+            latency = cudart.cudaEventElapsedTime(self.events[f"{stage}-start"], self.events[f"{stage}-stop"])[1]
+            print(f"{stage}: {latency:.2f} ms")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/prompt_encoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/prompt_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..8bec00b0d5a9f08d95fa169dc90031d34137ac96
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/prompt_encoder.py
@@ -0,0 +1,189 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+import torch
+from sam2.modeling.sam2_base import SAM2Base
+from sam2_utils import compare_tensors_with_tolerance
+from torch import nn
+
+logger = logging.getLogger(__name__)
+
+
+class SAM2PromptEncoder(nn.Module):
+    def __init__(self, sam_model: SAM2Base):
+        super().__init__()
+        self.prompt_encoder = sam_model.sam_prompt_encoder
+        self.model = sam_model
+
+    @torch.no_grad()
+    def forward(
+        self,
+        point_coords: torch.Tensor,
+        point_labels: torch.Tensor,
+        input_masks: torch.Tensor,
+        has_input_masks: torch.Tensor,
+    ):
+        """Encode prompts.
+
+           Args:
+            point_coords (torch.Tensor): [L, P, 2] shape and float32 dtype and contains the absolute pixel
+                                         coordinate in (x, y) format of the P input points in image of size 1024x1024.
+            point_labels (torch.Tensor): shape [L, P] and int32 dtype, where 1 means
+                                         positive (foreground), 0 means negative (background), -1 means padding,
+                                         2 (box left upper corner), 3 (box right bottom corner).
+            input_masks (torch.Tensor): [L, 1, H/4, W/4]. Low resolution mask input to the model.
+                                        Typically coming from a previous iteration.
+            has_input_masks (torch.Tensor): [L]. 1.0 if input_masks is used, 0.0 otherwise.
+        Returns:
+            sparse_embeddings (torch.Tensor): [L, P+1, 256], embedding for points and boxes.
+            dense_embeddings (torch.Tensor):  [L, 256, 64, 64]. embedding for input masks.
+            image_pe (torch.Tensor, optional): [1, 256, 64, 64]. image positional encoding.
+        """
+        sparse_embeddings = self._embed_points(point_coords, point_labels)
+        dense_embeddings = self._embed_masks(input_masks, has_input_masks)
+        image_pe = self.prompt_encoder.get_dense_pe()
+
+        return sparse_embeddings, dense_embeddings, image_pe
+
+    def _embed_points(self, point_coords: torch.Tensor, point_labels: torch.Tensor) -> torch.Tensor:
+        point_coords = point_coords + 0.5
+
+        padding_point = torch.zeros((point_coords.shape[0], 1, 2), device=point_coords.device)
+        padding_label = -torch.ones((point_labels.shape[0], 1), device=point_labels.device)
+        point_coords = torch.cat([point_coords, padding_point], dim=1)
+        point_labels = torch.cat([point_labels, padding_label], dim=1)
+
+        # Note that the input coordinates are based on image size 1024x1024. Here we normalize it to [0.0, 1.0).
+        point_coords[:, :, 0] = point_coords[:, :, 0] / self.model.image_size
+        point_coords[:, :, 1] = point_coords[:, :, 1] / self.model.image_size
+
+        point_embedding = self.prompt_encoder.pe_layer._pe_encoding(point_coords)
+        point_labels = point_labels.unsqueeze(-1).expand_as(point_embedding)
+
+        point_embedding = point_embedding * (point_labels != -1)
+        point_embedding = point_embedding + self.prompt_encoder.not_a_point_embed.weight * (point_labels == -1)
+
+        for i in range(self.prompt_encoder.num_point_embeddings):
+            point_embedding = point_embedding + self.prompt_encoder.point_embeddings[i].weight * (point_labels == i)
+
+        return point_embedding
+
+    def _embed_masks(self, input_masks: torch.Tensor, has_input_masks: torch.Tensor) -> torch.Tensor:
+        mask_embedding = self.prompt_encoder.mask_downscaling(input_masks)
+        no_mask_embedding = self.prompt_encoder.no_mask_embed.weight.reshape(1, -1, 1, 1)
+        logger.info("no_mask_embedding.shape: %s", no_mask_embedding.shape)
+        mask_embedding = has_input_masks * mask_embedding + (1.0 - has_input_masks) * no_mask_embedding
+        logger.info("mask_embedding.shape: %s", mask_embedding.shape)
+        return mask_embedding
+
+
+def export_prompt_encoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+):
+    sam2_prompt_encoder = SAM2PromptEncoder(sam2_model).cpu()
+
+    num_labels = 2
+    num_points = 3
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.int32)
+    input_masks = torch.zeros(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.ones(1, dtype=torch.float)
+
+    sparse_embeddings, dense_embeddings, image_pe = sam2_prompt_encoder(
+        point_coords, point_labels, input_masks, has_input_masks
+    )
+
+    logger.info("point_coords.shape: %s", point_coords.shape)
+    logger.info("point_labels.shape: %s", point_labels.shape)
+    logger.info("input_masks.shape: %s", input_masks.shape)
+    logger.info("has_input_masks.shape: %s", has_input_masks.shape)
+
+    logger.info("sparse_embeddings.shape: %s", sparse_embeddings.shape)
+    logger.info("dense_embeddings.shape: %s", dense_embeddings.shape)
+    logger.info("image_pe.shape: %s", image_pe.shape)
+
+    torch.onnx.export(
+        sam2_prompt_encoder,
+        (point_coords, point_labels, input_masks, has_input_masks),
+        onnx_model_path,
+        export_params=True,
+        opset_version=18,
+        do_constant_folding=True,
+        input_names=["point_coords", "point_labels", "input_masks", "has_input_masks"],
+        output_names=["sparse_embeddings", "dense_embeddings", "image_pe"],
+        dynamic_axes={
+            "point_coords": {0: "num_labels", 1: "num_points"},
+            "point_labels": {0: "num_labels", 1: "num_points"},
+            "input_masks": {0: "num_labels"},
+            "sparse_embeddings": {0: "num_labels", 1: "num_points+1"},
+            "dense_embeddings": {0: "num_labels"},
+        },
+    )
+
+    print("prompt encoder onnx model saved to ", onnx_model_path)
+
+
+def test_prompt_encoder_onnx(
+    sam2_model: SAM2Base,
+    onnx_model_path: str,
+):
+    sam2_prompt_encoder = SAM2PromptEncoder(sam2_model).cpu()
+
+    num_labels = 1
+    num_points = 5
+    point_coords = torch.randint(low=0, high=1024, size=(num_labels, num_points, 2), dtype=torch.float)
+    point_labels = torch.randint(low=0, high=1, size=(num_labels, num_points), dtype=torch.int32)
+    input_masks = torch.rand(num_labels, 1, 256, 256, dtype=torch.float)
+    has_input_masks = torch.ones(1, dtype=torch.float)
+
+    sparse_embeddings, dense_embeddings, image_pe = sam2_prompt_encoder(
+        point_coords, point_labels, input_masks, has_input_masks
+    )
+
+    import onnxruntime  # noqa: PLC0415
+
+    ort_session = onnxruntime.InferenceSession(onnx_model_path, providers=["CPUExecutionProvider"])
+
+    model_inputs = ort_session.get_inputs()
+    input_names = [model_inputs[i].name for i in range(len(model_inputs))]
+    logger.info("input_names: %s", input_names)
+
+    model_outputs = ort_session.get_outputs()
+    output_names = [model_outputs[i].name for i in range(len(model_outputs))]
+    logger.info("output_names: %s", output_names)
+
+    outputs = ort_session.run(
+        output_names,
+        {
+            "point_coords": point_coords.numpy(),
+            "point_labels": point_labels.numpy(),
+            "input_masks": input_masks.numpy(),
+            "has_input_masks": has_input_masks.numpy(),
+        },
+    )
+
+    for i, output_name in enumerate(output_names):
+        logger.info("output %s shape: %s", output_name, outputs[i].shape)
+
+    ort_sparse_embeddings, ort_dense_embeddings, ort_image_pe = outputs
+    if (
+        compare_tensors_with_tolerance(
+            "sparse_embeddings",
+            sparse_embeddings,
+            torch.tensor(ort_sparse_embeddings),
+            mismatch_percentage_tolerance=0.2,
+        )
+        and compare_tensors_with_tolerance(
+            "dense_embeddings", dense_embeddings, torch.tensor(ort_dense_embeddings), mismatch_percentage_tolerance=0.2
+        )
+        and compare_tensors_with_tolerance(
+            "image_pe", image_pe, torch.tensor(ort_image_pe), mismatch_percentage_tolerance=0.2
+        )
+    ):
+        print(f"onnx model has been verified: {onnx_model_path}")
+    else:
+        print(f"onnx model verification failed: {onnx_model_path}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_demo.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..20ee0274ade3632fb155a0037c7e34383149dba1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_demo.py
@@ -0,0 +1,321 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os
+
+import matplotlib.image as mpimg
+import matplotlib.pyplot as plt
+import numpy as np
+import torch
+from matplotlib.patches import Rectangle
+from PIL import Image
+from sam2.sam2_image_predictor import SAM2ImagePredictor
+from sam2_image_onnx_predictor import SAM2ImageOnnxPredictor
+from sam2_utils import load_sam2_model
+
+import onnxruntime
+
+
+def show_mask(mask, ax, random_color=False, borders=True):
+    if random_color:
+        color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)
+    else:
+        color = np.array([30 / 255, 144 / 255, 255 / 255, 0.6])
+    h, w = mask.shape[-2:]
+    mask = mask.astype(np.uint8)
+    mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)
+    if borders:
+        import cv2  # noqa: PLC0415
+
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+        # Try to smooth contours
+        contours = [cv2.approxPolyDP(contour, epsilon=0.01, closed=True) for contour in contours]
+        mask_image = cv2.drawContours(mask_image, contours, -1, (1, 1, 1, 0.5), thickness=2)
+    ax.imshow(mask_image)
+
+
+def show_points(coords, labels, ax, marker_size=375):
+    pos_points = coords[labels == 1]
+    neg_points = coords[labels == 0]
+    ax.scatter(
+        pos_points[:, 0], pos_points[:, 1], color="green", marker="*", s=marker_size, edgecolor="white", linewidth=1.25
+    )
+    ax.scatter(
+        neg_points[:, 0], neg_points[:, 1], color="red", marker="*", s=marker_size, edgecolor="white", linewidth=1.25
+    )
+
+
+def show_box(box, ax):
+    x0, y0 = box[0], box[1]
+    w, h = box[2] - box[0], box[3] - box[1]
+    ax.add_patch(Rectangle((x0, y0), w, h, edgecolor="green", facecolor=(0, 0, 0, 0), lw=2))
+
+
+def show_masks(
+    image,
+    masks,
+    scores,
+    point_coords=None,
+    box_coords=None,
+    input_labels=None,
+    borders=True,
+    output_image_file_prefix=None,
+    image_files=None,
+):
+    for i, (mask, score) in enumerate(zip(masks, scores, strict=False)):
+        plt.figure(figsize=(10, 10))
+        plt.imshow(image)
+        show_mask(mask, plt.gca(), borders=borders)
+        if point_coords is not None:
+            assert input_labels is not None
+            show_points(point_coords, input_labels, plt.gca())
+
+        if box_coords is not None:
+            show_box(box_coords, plt.gca())
+
+        if len(scores) > 1:
+            plt.title(f"Mask {i + 1}, Score: {score:.3f}", fontsize=18)
+
+        plt.axis("off")
+        if output_image_file_prefix:
+            filename = f"{output_image_file_prefix}_{i}.png"
+            if os.path.exists(filename):
+                os.remove(filename)
+            plt.savefig(filename, format="png", bbox_inches="tight", pad_inches=0)
+            if isinstance(image_files, list):
+                image_files.append(filename)
+        plt.show(block=False)
+        plt.close()
+
+
+def get_predictor(
+    sam2_dir: str,
+    device: str | torch.device,
+    dtype: torch.dtype,
+    model_type="sam2_hiera_large",
+    engine="torch",
+    image_encoder_onnx_path: str = "",
+    image_decoder_onnx_path: str = "",
+    image_decoder_multi_onnx_path: str = "",
+    provider: str = "CUDAExecutionProvider",
+):
+    sam2_model = load_sam2_model(sam2_dir, model_type, device=device)
+    if engine == "torch":
+        predictor = SAM2ImagePredictor(sam2_model)
+    else:
+        predictor = SAM2ImageOnnxPredictor(
+            sam2_model,
+            image_encoder_onnx_path=image_encoder_onnx_path,
+            image_decoder_onnx_path=image_decoder_onnx_path,
+            image_decoder_multi_onnx_path=image_decoder_multi_onnx_path,
+            provider=provider,
+            device=device,
+            onnx_dtype=dtype,
+        )
+    return predictor
+
+
+def run_demo(
+    sam2_dir: str,
+    model_type: str = "sam2_hiera_large",
+    engine: str = "torch",
+    dtype: torch.dtype = torch.float32,
+    image_encoder_onnx_path: str = "",
+    image_decoder_onnx_path: str = "",
+    image_decoder_multi_onnx_path: str = "",
+    use_gpu: bool = True,
+    enable_batch: bool = False,
+):
+    if use_gpu:
+        assert torch.cuda.is_available()
+        assert "CUDAExecutionProvider" in onnxruntime.get_available_providers()
+        provider = "CUDAExecutionProvider"
+    else:
+        provider = "CPUExecutionProvider"
+
+    device = torch.device("cuda" if use_gpu else "cpu")
+
+    if use_gpu and engine == "torch" and torch.cuda.get_device_properties(0).major >= 8:
+        # Turn on tfloat32 for Ampere GPUs.
+        torch.backends.cuda.matmul.allow_tf32 = True
+        torch.backends.cudnn.allow_tf32 = True
+
+    np.random.seed(3)
+    image = Image.open("truck.jpg")
+    image = np.array(image.convert("RGB"))
+
+    predictor = get_predictor(
+        sam2_dir,
+        device,
+        dtype,
+        model_type,
+        engine,
+        image_encoder_onnx_path,
+        image_decoder_onnx_path,
+        image_decoder_multi_onnx_path,
+        provider=provider,
+    )
+
+    predictor.set_image(image)
+    prefix = f"sam2_demo_{engine}_"
+
+    #  The model returns masks, quality predictions for those masks,
+    #     and low resolution mask logits that can be passed to the next iteration of prediction.
+    #  With multimask_output=True (the default setting), SAM 2 outputs 3 masks, where
+    #     scores gives the model's own estimation of the quality of these masks.
+    #  For ambiguous prompts such as a single point, it is recommended to use multimask_output=True
+    #     even if only a single mask is desired;
+    input_point = np.array([[500, 375]])
+    input_label = np.array([1])
+    masks, scores, logits = predictor.predict(
+        point_coords=input_point,
+        point_labels=input_label,
+        multimask_output=True,
+    )
+
+    sorted_ind = np.argsort(scores)[::-1]
+    masks = masks[sorted_ind]
+    scores = scores[sorted_ind]
+    logits = logits[sorted_ind]
+
+    image_files = []
+    show_masks(
+        image,
+        masks,
+        scores,
+        point_coords=input_point,
+        input_labels=input_label,
+        borders=True,
+        output_image_file_prefix=prefix + "multimask",
+        image_files=image_files,
+    )
+
+    # Multiple points.
+    input_point = np.array([[500, 375], [1125, 625]])
+    input_label = np.array([1, 1])
+    mask_input = logits[np.argmax(scores), :, :]  # Choose the model's best mask
+    masks, scores, _ = predictor.predict(
+        point_coords=input_point,
+        point_labels=input_label,
+        mask_input=mask_input[None, :, :],
+        multimask_output=False,
+    )
+    show_masks(
+        image,
+        masks,
+        scores,
+        point_coords=input_point,
+        input_labels=input_label,
+        output_image_file_prefix=prefix + "multi_points",
+        image_files=image_files,
+    )
+
+    # Specify a window and a background point.
+    input_point = np.array([[500, 375], [1125, 625]])
+    input_label = np.array([1, 0])
+    mask_input = logits[np.argmax(scores), :, :]  # Choose the model's best mask
+    masks, scores, _ = predictor.predict(
+        point_coords=input_point,
+        point_labels=input_label,
+        mask_input=mask_input[None, :, :],
+        multimask_output=False,
+    )
+    show_masks(
+        image,
+        masks,
+        scores,
+        point_coords=input_point,
+        input_labels=input_label,
+        output_image_file_prefix=prefix + "background_point",
+        image_files=image_files,
+    )
+
+    # Take a box as input
+    input_box = np.array([425, 600, 700, 875])
+    masks, scores, _ = predictor.predict(
+        point_coords=None,
+        point_labels=None,
+        box=input_box[None, :],
+        multimask_output=False,
+    )
+    show_masks(
+        image,
+        masks,
+        scores,
+        box_coords=input_box,
+        output_image_file_prefix=prefix + "box",
+        image_files=image_files,
+    )
+
+    # Combining points and boxes
+    input_box = np.array([425, 600, 700, 875])
+    input_point = np.array([[575, 750]])
+    input_label = np.array([0])
+
+    masks, scores, logits = predictor.predict(
+        point_coords=input_point,
+        point_labels=input_label,
+        box=input_box,
+        multimask_output=False,
+    )
+    show_masks(
+        image,
+        masks,
+        scores,
+        box_coords=input_box,
+        point_coords=input_point,
+        input_labels=input_label,
+        output_image_file_prefix=prefix + "box_and_point",
+        image_files=image_files,
+    )
+
+    # TODO: support batched prompt inputs
+    if enable_batch:
+        input_boxes = np.array(
+            [
+                [75, 275, 1725, 850],
+                [425, 600, 700, 875],
+                [1375, 550, 1650, 800],
+                [1240, 675, 1400, 750],
+            ]
+        )
+        masks, scores, _ = predictor.predict(
+            point_coords=None,
+            point_labels=None,
+            box=input_boxes,
+            multimask_output=False,
+        )
+        plt.figure(figsize=(10, 10))
+        plt.imshow(image)
+        for mask in masks:
+            show_mask(mask.squeeze(0), plt.gca(), random_color=True)
+        for box in input_boxes:
+            show_box(box, plt.gca())
+        plt.axis("off")
+        plt.show()
+        plt.savefig(prefix + "batch_prompt.png")
+        image_files.append(prefix + "batch_prompt.png")
+    return image_files
+
+
+def show_all_images(left_images, right_images, suffix=""):
+    # Show images in two rows since display screen is horizontal in most cases.
+    fig, axes = plt.subplots(nrows=2, ncols=len(left_images), figsize=(19.20, 10.80))
+    for i, (left_img_path, right_img_path) in enumerate(zip(left_images, right_images, strict=False)):
+        left_img = mpimg.imread(left_img_path)
+        right_img = mpimg.imread(right_img_path)
+
+        axes[0, i].imshow(left_img)
+        axes[0, i].set_title(left_img_path.replace("sam2_demo_", "").replace(".png", ""), fontsize=10)
+        axes[0, i].axis("off")
+        axes[0, i].set_aspect(left_img.shape[1] / left_img.shape[0])
+
+        axes[1, i].imshow(right_img)
+        axes[1, i].set_title(right_img_path.replace("sam2_demo_", "").replace(".png", ""), fontsize=10)
+        axes[1, i].axis("off")
+        axes[1, i].set_aspect(right_img.shape[1] / right_img.shape[0])
+
+    plt.tight_layout()
+    plt.savefig(f"sam2_demo{suffix}.png", format="png", bbox_inches="tight", dpi=1000)
+    plt.show()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_image_onnx_predictor.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_image_onnx_predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..c497e2b22e0fd621671dd108224c5dcc7f0248aa
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_image_onnx_predictor.py
@@ -0,0 +1,279 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+import numpy as np
+import torch
+from PIL.Image import Image
+from sam2.modeling.sam2_base import SAM2Base
+from sam2.sam2_image_predictor import SAM2ImagePredictor
+from sam2_utils import decoder_shape_dict, encoder_shape_dict
+
+from onnxruntime import InferenceSession
+from onnxruntime.transformers.io_binding_helper import CudaSession
+
+logger = logging.getLogger(__name__)
+
+
+def create_ort_session(
+    onnx_path: str,
+    session_options=None,
+    provider="CUDAExecutionProvider",
+    enable_cuda_graph=False,
+    use_tf32=True,
+) -> InferenceSession:
+    if provider == "CUDAExecutionProvider":
+        device_id = torch.cuda.current_device()
+        provider_options = CudaSession.get_cuda_provider_options(device_id, enable_cuda_graph)
+        provider_options["use_tf32"] = int(use_tf32)
+        providers = [(provider, provider_options), "CPUExecutionProvider"]
+    else:
+        providers = ["CPUExecutionProvider"]
+    logger.info("Using providers: %s", providers)
+    return InferenceSession(onnx_path, session_options, providers=providers)
+
+
+def create_session(
+    onnx_path: str,
+    session_options=None,
+    provider="CUDAExecutionProvider",
+    device: str | torch.device = "cuda",
+    enable_cuda_graph=False,
+) -> CudaSession:
+    ort_session = create_ort_session(
+        onnx_path, session_options, provider, enable_cuda_graph=enable_cuda_graph, use_tf32=True
+    )
+    cuda_session = CudaSession(ort_session, device=torch.device(device), enable_cuda_graph=enable_cuda_graph)
+    return cuda_session
+
+
+class SAM2ImageOnnxPredictor(SAM2ImagePredictor):
+    def __init__(
+        self,
+        sam_model: SAM2Base,
+        image_encoder_onnx_path: str = "",
+        image_decoder_onnx_path: str = "",
+        image_decoder_multi_onnx_path: str = "",
+        provider: str = "CUDAExecutionProvider",
+        device: str | torch.device = "cuda",
+        onnx_dtype: torch.dtype = torch.float32,
+        mask_threshold=0.0,
+        max_hole_area=0.0,
+        max_sprinkle_area=0.0,
+        **kwargs,
+    ) -> None:
+        """
+        Uses SAM-2 to compute the image embedding for an image, and then allow mask prediction given prompts.
+
+        Arguments:
+          sam_model (SAM2Base): The model to use for mask prediction.
+          onnx_directory (str): The path of the directory that contains encoder and decoder onnx models.
+          onnx_dtype (torch.dtype): The data type to use for ONNX inputs.
+          mask_threshold (float): The threshold to convert mask logits to binary masks. Default is 0.0.
+          max_hole_area (float): If max_hole_area > 0, we fill small holes in up to
+                                 the maximum area of max_hole_area in low_res_masks.
+          max_sprinkle_area (float): If max_sprinkle_area > 0, we remove small sprinkles up to
+                                     the maximum area of max_sprinkle_area in low_res_masks.
+        """
+        super().__init__(
+            sam_model, mask_threshold=mask_threshold, max_hole_area=max_hole_area, max_sprinkle_area=max_sprinkle_area
+        )
+
+        logger.debug("self.device=%s, device=%s", self.device, device)
+
+        # This model is exported by image_encoder.py.
+        self.encoder_session = create_session(
+            image_encoder_onnx_path,
+            session_options=None,
+            provider=provider,
+            device=device,
+            enable_cuda_graph=False,
+        )
+        self.onnx_dtype = onnx_dtype
+
+        # This model is exported by image_decoder.py. It outputs only one mask.
+        self.decoder_session = create_session(
+            image_decoder_onnx_path,
+            session_options=None,
+            provider=provider,
+            device=device,
+            enable_cuda_graph=False,
+        )
+
+        # This model is exported by image_decoder.py. It outputs multiple (3) masks.
+        self.decoder_session_multi_out = create_session(
+            image_decoder_multi_onnx_path,
+            session_options=None,
+            provider=provider,
+            device=device,
+            enable_cuda_graph=False,
+        )
+
+    @torch.no_grad()
+    def set_image(self, image: np.ndarray | Image):
+        """
+        Calculates the image embeddings for the provided image.
+
+        Arguments:
+          image (np.ndarray or PIL Image): The input image to embed in RGB format.
+              The image should be in HWC format if np.ndarray, or WHC format if PIL Image with pixel values in [0, 255].
+        """
+        self.reset_predictor()
+        # Transform the image to the form expected by the model
+        if isinstance(image, np.ndarray):
+            # For numpy array image, we assume (HxWxC) format.
+            self._orig_hw = [image.shape[:2]]
+        elif isinstance(image, Image):
+            w, h = image.size
+            self._orig_hw = [(h, w)]
+        else:
+            raise NotImplementedError("Image format not supported")
+
+        input_image = self._transforms(image)
+        input_image = input_image[None, ...].to(self.device)
+
+        assert len(input_image.shape) == 4 and input_image.shape[1] == 3, (
+            f"input_image must be of size 1x3xHxW, got {input_image.shape}"
+        )
+
+        # Computing image embeddings for the provided image
+        io_shapes = encoder_shape_dict(batch_size=1, height=input_image.shape[2], width=input_image.shape[3])
+        self.encoder_session.allocate_buffers(io_shapes)
+
+        feed_dict = {"image": input_image.to(self.onnx_dtype).to(self.device)}
+
+        for key, value in feed_dict.items():
+            logger.debug(f"{key}: {value.shape}, {value.dtype}")
+        logger.debug(f"encoder onnx: {self.encoder_session.ort_session._model_path}")
+
+        ort_outputs = self.encoder_session.infer(feed_dict)
+
+        self._features = {
+            "image_embed": ort_outputs["image_embeddings"],
+            "high_res_feats": [ort_outputs[f"image_features_{i}"] for i in range(2)],
+        }
+        self._is_image_set = True
+        logging.info("Image embeddings computed.")
+
+    @torch.no_grad()
+    def _predict(
+        self,
+        point_coords: torch.Tensor | None,
+        point_labels: torch.Tensor | None,
+        boxes: torch.Tensor | None = None,
+        mask_input: torch.Tensor | None = None,
+        multimask_output: bool = True,
+        return_logits: bool = False,
+        img_idx: int = -1,
+    ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+        """
+        Predict masks for the given input prompts, using the currently set image.
+        Input prompts are batched torch tensors and are expected to already be
+        transformed to the input frame using SAM2Transforms.
+
+        Arguments:
+          point_coords (torch.Tensor or None): A BxNx2 array of point prompts to the
+            model. Each point is in (X,Y) in pixels.
+          point_labels (torch.Tensor or None): A BxN array of labels for the
+            point prompts. 1 indicates a foreground point and 0 indicates a
+            background point.
+          boxes (np.ndarray or None): A Bx4 array given a box prompt to the
+            model, in XYXY format.
+          mask_input (np.ndarray): A low resolution mask input to the model, typically
+            coming from a previous prediction iteration. Has form Bx1xHxW, where
+            for SAM, H=W=256. Masks returned by a previous iteration of the
+            predict method do not need further transformation.
+          multimask_output (bool): If true, the model will return three masks.
+            For ambiguous input prompts (such as a single click), this will often
+            produce better masks than a single prediction. If only a single
+            mask is needed, the model's predicted quality score can be used
+            to select the best mask. For non-ambiguous prompts, such as multiple
+            input prompts, multimask_output=False can give better results.
+          return_logits (bool): If true, returns un-thresholded masks logits
+            instead of a binary mask.
+
+        Returns:
+          (torch.Tensor): The output masks in BxCxHxW format, where C is the
+            number of masks, and (H, W) is the original image size.
+          (torch.Tensor): An array of shape BxC containing the model's
+            predictions for the quality of each mask.
+          (torch.Tensor): An array of shape BxCxHxW, where C is the number
+            of masks and H=W=256. These low res logits can be passed to
+            a subsequent iteration as mask input.
+        """
+        assert not return_logits  # onnx model is exported for returning bool masks.
+
+        if not self._is_image_set:
+            raise RuntimeError("An image must be set with .set_image(...) before mask prediction.")
+
+        if point_coords is not None:
+            concat_points = (point_coords, point_labels)
+        else:
+            concat_points = None
+
+        # Embed prompts
+        if boxes is not None:
+            box_coords = boxes.reshape(-1, 2, 2)
+            box_labels = torch.tensor([[2, 3]], dtype=torch.int, device=boxes.device)
+            box_labels = box_labels.repeat(boxes.size(0), 1)
+            # we merge "boxes" and "points" into a single "concat_points" input (where
+            # boxes are added at the beginning) to sam_prompt_encoder
+            if concat_points is not None:
+                concat_coords = torch.cat([box_coords, concat_points[0]], dim=1)
+                concat_labels = torch.cat([box_labels, concat_points[1]], dim=1)
+                concat_points = (concat_coords, concat_labels)
+            else:
+                concat_points = (box_coords, box_labels)
+
+        assert concat_points is not None
+        num_labels = concat_points[0].shape[0]
+        shape_dict = decoder_shape_dict(
+            original_image_height=self._orig_hw[img_idx][0],
+            original_image_width=self._orig_hw[img_idx][1],
+            num_labels=num_labels,
+            max_points=concat_points[0].shape[1],
+            num_masks=3 if multimask_output else 1,
+        )
+        if multimask_output:
+            decoder_session = self.decoder_session_multi_out
+        else:
+            decoder_session = self.decoder_session
+
+        decoder_session.allocate_buffers(shape_dict)
+
+        image_features_0 = self._features["high_res_feats"][0][img_idx].unsqueeze(0)
+        image_features_1 = self._features["high_res_feats"][1][img_idx].unsqueeze(0)
+        image_embeddings = self._features["image_embed"][img_idx].unsqueeze(0)
+
+        if mask_input is None:
+            input_masks = torch.zeros(num_labels, 1, 256, 256, dtype=self.onnx_dtype, device=self.device)
+            has_input_masks = torch.zeros(num_labels, dtype=self.onnx_dtype, device=self.device)
+        else:
+            input_masks = mask_input[img_idx].unsqueeze(0).repeat(num_labels, 1, 1, 1)
+            has_input_masks = torch.ones(num_labels, dtype=self.onnx_dtype, device=self.device)
+
+        feed_dict = {
+            "image_embeddings": image_embeddings.contiguous().to(dtype=self.onnx_dtype).to(self.device),
+            "image_features_0": image_features_0.contiguous().to(dtype=self.onnx_dtype).to(self.device),
+            "image_features_1": image_features_1.contiguous().to(dtype=self.onnx_dtype).to(self.device),
+            "point_coords": concat_points[0].to(dtype=self.onnx_dtype).to(self.device),
+            "point_labels": concat_points[1].to(dtype=torch.int32).to(self.device),
+            "input_masks": input_masks.to(dtype=self.onnx_dtype).to(self.device),
+            "has_input_masks": has_input_masks.to(dtype=self.onnx_dtype).to(self.device),
+            "original_image_size": torch.tensor(self._orig_hw[img_idx], dtype=torch.int32, device=self.device),
+        }
+
+        for key, value in feed_dict.items():
+            logger.debug(f"{key}: {value.shape}, {value.dtype}")
+        logger.debug(f"decoder onnx: {self.decoder_session.ort_session._model_path}")
+
+        ort_outputs = decoder_session.infer(feed_dict)
+
+        masks = ort_outputs["masks"]
+        iou_predictions = ort_outputs["iou_predictions"]
+        low_res_masks = ort_outputs["low_res_masks"]
+
+        return torch.Tensor(masks), torch.Tensor(iou_predictions), torch.Tensor(low_res_masks)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_utils.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..3bf9df4dab03e0d9da5b604cf2c7c99f3a94121a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/sam2/sam2_utils.py
@@ -0,0 +1,147 @@
+# -------------------------------------------------------------------------
+# Copyright (R) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+import os
+import sys
+from collections.abc import Mapping
+
+import torch
+from sam2.build_sam import build_sam2
+from sam2.modeling.sam2_base import SAM2Base
+
+logger = logging.getLogger(__name__)
+
+
+def _get_model_cfg(model_type) -> str:
+    assert model_type in ["sam2_hiera_tiny", "sam2_hiera_small", "sam2_hiera_large", "sam2_hiera_base_plus"]
+    if model_type == "sam2_hiera_tiny":
+        model_cfg = "sam2_hiera_t.yaml"
+    elif model_type == "sam2_hiera_small":
+        model_cfg = "sam2_hiera_s.yaml"
+    elif model_type == "sam2_hiera_base_plus":
+        model_cfg = "sam2_hiera_b+.yaml"
+    else:
+        model_cfg = "sam2_hiera_l.yaml"
+    return model_cfg
+
+
+def load_sam2_model(sam2_dir, model_type, device: str | torch.device = "cpu") -> SAM2Base:
+    checkpoints_dir = os.path.join(sam2_dir, "checkpoints")
+    sam2_config_dir = os.path.join(sam2_dir, "sam2_configs")
+    if not os.path.exists(sam2_dir):
+        raise FileNotFoundError(f"{sam2_dir} does not exist. Please specify --sam2_dir correctly.")
+
+    if not os.path.exists(checkpoints_dir):
+        raise FileNotFoundError(f"{checkpoints_dir} does not exist. Please specify --sam2_dir correctly.")
+
+    if not os.path.exists(sam2_config_dir):
+        raise FileNotFoundError(f"{sam2_config_dir} does not exist. Please specify --sam2_dir correctly.")
+
+    checkpoint_path = os.path.join(checkpoints_dir, f"{model_type}.pt")
+    if not os.path.exists(checkpoint_path):
+        raise FileNotFoundError(f"{checkpoint_path} does not exist. Please download checkpoints under the directory.")
+
+    if sam2_dir not in sys.path:
+        sys.path.append(sam2_dir)
+
+    model_cfg = _get_model_cfg(model_type)
+    sam2_model = build_sam2(model_cfg, checkpoint_path, device=device)
+    return sam2_model
+
+
+def sam2_onnx_path(output_dir, model_type, component, multimask_output=False, suffix=""):
+    if component == "image_encoder":
+        return os.path.join(output_dir, f"{model_type}_image_encoder{suffix}.onnx")
+    elif component == "mask_decoder":
+        return os.path.join(output_dir, f"{model_type}_mask_decoder{suffix}.onnx")
+    elif component == "prompt_encoder":
+        return os.path.join(output_dir, f"{model_type}_prompt_encoder{suffix}.onnx")
+    else:
+        assert component == "image_decoder"
+        return os.path.join(
+            output_dir, f"{model_type}_image_decoder" + ("_multi" if multimask_output else "") + f"{suffix}.onnx"
+        )
+
+
+def encoder_shape_dict(batch_size: int, height: int, width: int) -> Mapping[str, list[int]]:
+    assert height == 1024 and width == 1024, "Only 1024x1024 images are supported."
+    return {
+        "image": [batch_size, 3, height, width],
+        "image_features_0": [batch_size, 32, height // 4, width // 4],
+        "image_features_1": [batch_size, 64, height // 8, width // 8],
+        "image_embeddings": [batch_size, 256, height // 16, width // 16],
+    }
+
+
+def decoder_shape_dict(
+    original_image_height: int,
+    original_image_width: int,
+    num_labels: int = 1,
+    max_points: int = 16,
+    num_masks: int = 1,
+) -> dict:
+    height: int = 1024
+    width: int = 1024
+    return {
+        "image_features_0": [1, 32, height // 4, width // 4],
+        "image_features_1": [1, 64, height // 8, width // 8],
+        "image_embeddings": [1, 256, height // 16, width // 16],
+        "point_coords": [num_labels, max_points, 2],
+        "point_labels": [num_labels, max_points],
+        "input_masks": [num_labels, 1, height // 4, width // 4],
+        "has_input_masks": [num_labels],
+        "original_image_size": [2],
+        "masks": [num_labels, num_masks, original_image_height, original_image_width],
+        "iou_predictions": [num_labels, num_masks],
+        "low_res_masks": [num_labels, num_masks, height // 4, width // 4],
+    }
+
+
+def compare_tensors_with_tolerance(
+    name: str,
+    tensor1: torch.Tensor,
+    tensor2: torch.Tensor,
+    atol=5e-3,
+    rtol=1e-4,
+    mismatch_percentage_tolerance=0.1,
+) -> bool:
+    assert tensor1.shape == tensor2.shape
+    a = tensor1.clone().float()
+    b = tensor2.clone().float()
+
+    differences = torch.abs(a - b)
+    mismatch_count = (differences > (rtol * torch.max(torch.abs(a), torch.abs(b)) + atol)).sum().item()
+
+    total_elements = a.numel()
+    mismatch_percentage = (mismatch_count / total_elements) * 100
+
+    passed = mismatch_percentage < mismatch_percentage_tolerance
+
+    log_func = logger.error if not passed else logger.info
+    log_func(
+        "%s: mismatched elements percentage %.2f (%d/%d). Verification %s (threshold=%.2f).",
+        name,
+        mismatch_percentage,
+        mismatch_count,
+        total_elements,
+        "passed" if passed else "failed",
+        mismatch_percentage_tolerance,
+    )
+
+    return passed
+
+
+def random_sam2_input_image(batch_size=1, image_height=1024, image_width=1024) -> torch.Tensor:
+    image = torch.randn(batch_size, 3, image_height, image_width, dtype=torch.float32).cpu()
+    return image
+
+
+def setup_logger(verbose=True):
+    if verbose:
+        logging.basicConfig(format="[%(filename)s:%(lineno)s - %(funcName)20s()] %(message)s")
+        logging.getLogger().setLevel(logging.INFO)
+    else:
+        logging.basicConfig(format="[%(message)s")
+        logging.getLogger().setLevel(logging.WARNING)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ef71ce9e355e17ea1c2ca9fb648951d917734b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..2db5e3c68534e2443539cded84a4a380fd9898ff
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark.py
@@ -0,0 +1,1519 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import argparse
+import csv
+import logging
+import os
+import statistics
+import sys
+import time
+from pathlib import Path
+
+# import torch before onnxruntime so that onnxruntime uses the cuDNN in the torch package.
+import torch
+from benchmark_helper import measure_memory
+
+SD_MODELS = {
+    "1.5": "runwayml/stable-diffusion-v1-5",
+    "2.0": "stabilityai/stable-diffusion-2",
+    "2.1": "stabilityai/stable-diffusion-2-1",
+    "xl-1.0": "stabilityai/stable-diffusion-xl-refiner-1.0",
+    "3.0M": "stabilityai/stable-diffusion-3-medium-diffusers",
+    "3.5M": "stabilityai/stable-diffusion-3.5-medium",
+    "3.5L": "stabilityai/stable-diffusion-3.5-large",
+    "Flux.1S": "black-forest-labs/FLUX.1-schnell",
+    "Flux.1D": "black-forest-labs/FLUX.1-dev",
+}
+
+PROVIDERS = {
+    "cuda": "CUDAExecutionProvider",
+    "migraphx": "MIGraphXExecutionProvider",
+    "tensorrt": "TensorrtExecutionProvider",
+}
+
+
+def example_prompts():
+    prompts = [
+        "a photo of an astronaut riding a horse on mars",
+        "cute grey cat with blue eyes, wearing a bowtie, acrylic painting",
+        "a cute magical flying dog, fantasy art drawn by disney concept artists, highly detailed, digital painting",
+        "an illustration of a house with large barn with many cute flower pots and beautiful blue sky scenery",
+        "one apple sitting on a table, still life, reflective, full color photograph, centered, close-up product",
+        "background texture of stones, masterpiece, artistic, stunning photo, award winner photo",
+        "new international organic style house, tropical surroundings, architecture, 8k, hdr",
+        "beautiful Renaissance Revival Estate, Hobbit-House, detailed painting, warm colors, 8k, trending on Artstation",
+        "blue owl, big green eyes, portrait, intricate metal design, unreal engine, octane render, realistic",
+        "delicate elvish moonstone necklace on a velvet background, symmetrical intricate motifs, leaves, flowers, 8k",
+    ]
+
+    negative_prompt = "bad composition, ugly, abnormal, malformed"
+
+    return prompts, negative_prompt
+
+
+def warmup_prompts():
+    return "warm up", "bad"
+
+
+def measure_gpu_memory(monitor_type, func, start_memory=None):
+    return measure_memory(is_gpu=True, func=func, monitor_type=monitor_type, start_memory=start_memory)
+
+
+def get_ort_pipeline(model_name: str, directory: str, provider, disable_safety_checker: bool):
+    from diffusers import DDIMScheduler, OnnxStableDiffusionPipeline  # noqa: PLC0415
+
+    import onnxruntime  # noqa: PLC0415
+
+    if directory is not None:
+        assert os.path.exists(directory)
+        session_options = onnxruntime.SessionOptions()
+        pipe = OnnxStableDiffusionPipeline.from_pretrained(
+            directory,
+            provider=provider,
+            sess_options=session_options,
+        )
+    else:
+        pipe = OnnxStableDiffusionPipeline.from_pretrained(
+            model_name,
+            revision="onnx",
+            provider=provider,
+            use_auth_token=True,
+        )
+    pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+    pipe.set_progress_bar_config(disable=True)
+
+    if disable_safety_checker:
+        pipe.safety_checker = None
+        pipe.feature_extractor = None
+
+    return pipe
+
+
+def get_torch_pipeline(model_name: str, disable_safety_checker: bool, enable_torch_compile: bool, use_xformers: bool):
+    if "FLUX" in model_name:
+        from diffusers import FluxPipeline  # noqa: PLC0415
+
+        pipe = FluxPipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16).to("cuda")
+        if enable_torch_compile:
+            pipe.transformer.to(memory_format=torch.channels_last)
+            pipe.transformer = torch.compile(pipe.transformer, mode="max-autotune", fullgraph=True)
+        return pipe
+
+    if "stable-diffusion-3" in model_name:
+        from diffusers import StableDiffusion3Pipeline  # noqa: PLC0415
+
+        pipe = StableDiffusion3Pipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16).to("cuda")
+        if enable_torch_compile:
+            pipe.transformer.to(memory_format=torch.channels_last)
+            pipe.transformer = torch.compile(pipe.transformer, mode="max-autotune", fullgraph=True)
+        return pipe
+
+    from diffusers import DDIMScheduler, StableDiffusionPipeline  # noqa: PLC0415
+    from torch import channels_last, float16  # noqa: PLC0415
+
+    pipe = StableDiffusionPipeline.from_pretrained(model_name, torch_dtype=float16).to("cuda")
+
+    pipe.unet.to(memory_format=channels_last)  # in-place operation
+
+    if use_xformers:
+        pipe.enable_xformers_memory_efficient_attention()
+
+    if enable_torch_compile:
+        pipe.unet = torch.compile(pipe.unet)
+        pipe.vae = torch.compile(pipe.vae)
+        pipe.text_encoder = torch.compile(pipe.text_encoder)
+        print("Torch compiled unet, vae and text_encoder")
+
+    pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+    pipe.set_progress_bar_config(disable=True)
+
+    if disable_safety_checker:
+        pipe.safety_checker = None
+        pipe.feature_extractor = None
+
+    return pipe
+
+
+def get_image_filename_prefix(engine: str, model_name: str, batch_size: int, steps: int, disable_safety_checker: bool):
+    short_model_name = model_name.split("/")[-1].replace("stable-diffusion-", "sd")
+    return f"{engine}_{short_model_name}_b{batch_size}_s{steps}" + ("" if disable_safety_checker else "_safe")
+
+
+def run_ort_pipeline(
+    pipe,
+    batch_size: int,
+    image_filename_prefix: str,
+    height,
+    width,
+    steps,
+    num_prompts,
+    batch_count,
+    start_memory,
+    memory_monitor_type,
+    skip_warmup: bool = False,
+):
+    from diffusers import OnnxStableDiffusionPipeline  # noqa: PLC0415
+
+    assert isinstance(pipe, OnnxStableDiffusionPipeline)
+
+    prompts, negative_prompt = example_prompts()
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        pipe(
+            prompt=[prompt] * batch_size,
+            height=height,
+            width=width,
+            num_inference_steps=steps,
+            negative_prompt=[negative] * batch_size,
+        )
+
+    # Run warm up, and measure GPU memory of two runs
+    # cuDNN/MIOpen The first run has  algo search so it might need more memory)
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    latency_list = []
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        images = pipe(
+            prompt=[prompt] * batch_size,
+            height=height,
+            width=width,
+            num_inference_steps=steps,
+            negative_prompt=[negative_prompt] * batch_size,
+        ).images
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"Inference took {latency:.3f} seconds")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.jpg")
+
+    from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+    return {
+        "engine": "onnxruntime",
+        "version": ort_version,
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+    }
+
+
+def get_negative_prompt_kwargs(negative_prompt, use_num_images_per_prompt, is_flux, batch_size) -> dict:
+    # Flux does not support negative prompt
+    kwargs = (
+        (
+            {"negative_prompt": negative_prompt}
+            if use_num_images_per_prompt
+            else {"negative_prompt": [negative_prompt] * batch_size}
+        )
+        if not is_flux
+        else {}
+    )
+
+    # Fix the random seed so that we can inspect the output quality easily.
+    if torch.cuda.is_available():
+        kwargs["generator"] = torch.Generator(device="cuda").manual_seed(123)
+
+    return kwargs
+
+
+def run_torch_pipeline(
+    pipe,
+    batch_size: int,
+    image_filename_prefix: str,
+    height,
+    width,
+    steps,
+    num_prompts,
+    batch_count,
+    start_memory,
+    memory_monitor_type,
+    skip_warmup=False,
+):
+    prompts, negative_prompt = example_prompts()
+
+    import diffusers  # noqa: PLC0415
+
+    is_flux = isinstance(pipe, diffusers.FluxPipeline)
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        extra_kwargs = get_negative_prompt_kwargs(negative, False, is_flux, batch_size)
+        pipe(prompt=[prompt] * batch_size, height=height, width=width, num_inference_steps=steps, **extra_kwargs)
+
+    # Run warm up, and measure GPU memory of two runs (The first run has cuDNN algo search so it might need more memory)
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    torch.set_grad_enabled(False)
+
+    latency_list = []
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        torch.cuda.synchronize()
+        inference_start = time.time()
+        extra_kwargs = get_negative_prompt_kwargs(negative_prompt, False, is_flux, batch_size)
+        images = pipe(
+            prompt=[prompt] * batch_size,
+            height=height,
+            width=width,
+            num_inference_steps=steps,
+            **extra_kwargs,
+        ).images
+
+        torch.cuda.synchronize()
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"Inference took {latency:.3f} seconds")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.jpg")
+
+    return {
+        "engine": "torch",
+        "version": torch.__version__,
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+    }
+
+
+def run_ort(
+    model_name: str,
+    directory: str,
+    provider: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    tuning: bool,
+    skip_warmup: bool = False,
+):
+    provider_and_options = provider
+    if tuning and provider in ["CUDAExecutionProvider"]:
+        provider_and_options = (provider, {"tunable_op_enable": 1, "tunable_op_tuning_enable": 1})
+
+    load_start = time.time()
+    pipe = get_ort_pipeline(model_name, directory, provider_and_options, disable_safety_checker)
+    load_end = time.time()
+    print(f"Model loading took {load_end - load_start} seconds")
+
+    image_filename_prefix = get_image_filename_prefix("ort", model_name, batch_size, steps, disable_safety_checker)
+    result = run_ort_pipeline(
+        pipe,
+        batch_size,
+        image_filename_prefix,
+        height,
+        width,
+        steps,
+        num_prompts,
+        batch_count,
+        start_memory,
+        memory_monitor_type,
+        skip_warmup=skip_warmup,
+    )
+
+    result.update(
+        {
+            "model_name": model_name,
+            "directory": directory,
+            "provider": provider.replace("ExecutionProvider", ""),
+            "disable_safety_checker": disable_safety_checker,
+            "enable_cuda_graph": False,
+        }
+    )
+    return result
+
+
+def get_optimum_ort_pipeline(
+    model_name: str,
+    directory: str,
+    provider="CUDAExecutionProvider",
+    disable_safety_checker: bool = True,
+    use_io_binding: bool = False,
+):
+    from optimum.onnxruntime import ORTPipelineForText2Image  # noqa: PLC0415
+
+    if directory is not None and os.path.exists(directory):
+        pipeline = ORTPipelineForText2Image.from_pretrained(directory, provider=provider, use_io_binding=use_io_binding)
+    else:
+        pipeline = ORTPipelineForText2Image.from_pretrained(
+            model_name,
+            export=True,
+            provider=provider,
+            use_io_binding=use_io_binding,
+        )
+        pipeline.save_pretrained(directory)
+
+    if disable_safety_checker:
+        pipeline.safety_checker = None
+        pipeline.feature_extractor = None
+
+    return pipeline
+
+
+def run_optimum_ort_pipeline(
+    pipe,
+    batch_size: int,
+    image_filename_prefix: str,
+    height,
+    width,
+    steps,
+    num_prompts,
+    batch_count,
+    start_memory,
+    memory_monitor_type,
+    use_num_images_per_prompt=False,
+    skip_warmup=False,
+):
+    print("Pipeline type", type(pipe))
+    from optimum.onnxruntime.modeling_diffusion import ORTFluxPipeline  # noqa: PLC0415
+
+    is_flux = isinstance(pipe, ORTFluxPipeline)
+
+    prompts, negative_prompt = example_prompts()
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        extra_kwargs = get_negative_prompt_kwargs(negative, use_num_images_per_prompt, is_flux, batch_size)
+        if use_num_images_per_prompt:
+            pipe(
+                prompt=prompt,
+                height=height,
+                width=width,
+                num_inference_steps=steps,
+                num_images_per_prompt=batch_count,
+                **extra_kwargs,
+            )
+        else:
+            pipe(prompt=[prompt] * batch_size, height=height, width=width, num_inference_steps=steps, **extra_kwargs)
+
+    # Run warm up, and measure GPU memory of two runs.
+    # The first run has algo search for cuDNN/MIOpen, so it might need more memory.
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    extra_kwargs = get_negative_prompt_kwargs(negative_prompt, use_num_images_per_prompt, is_flux, batch_size)
+
+    latency_list = []
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        if use_num_images_per_prompt:
+            images = pipe(
+                prompt=prompt,
+                height=height,
+                width=width,
+                num_inference_steps=steps,
+                num_images_per_prompt=batch_size,
+                **extra_kwargs,
+            ).images
+        else:
+            images = pipe(
+                prompt=[prompt] * batch_size, height=height, width=width, num_inference_steps=steps, **extra_kwargs
+            ).images
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"Inference took {latency:.3f} seconds")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.jpg")
+
+    from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+    return {
+        "engine": "optimum_ort",
+        "version": ort_version,
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+    }
+
+
+def run_optimum_ort(
+    model_name: str,
+    directory: str,
+    provider: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    use_io_binding: bool = False,
+    skip_warmup: bool = False,
+):
+    load_start = time.time()
+    pipe = get_optimum_ort_pipeline(
+        model_name, directory, provider, disable_safety_checker, use_io_binding=use_io_binding
+    )
+    load_end = time.time()
+    print(f"Model loading took {load_end - load_start} seconds")
+
+    full_model_name = model_name + "_" + Path(directory).name if directory else model_name
+    image_filename_prefix = get_image_filename_prefix(
+        "optimum", full_model_name, batch_size, steps, disable_safety_checker
+    )
+    result = run_optimum_ort_pipeline(
+        pipe,
+        batch_size,
+        image_filename_prefix,
+        height,
+        width,
+        steps,
+        num_prompts,
+        batch_count,
+        start_memory,
+        memory_monitor_type,
+        skip_warmup=skip_warmup,
+    )
+
+    result.update(
+        {
+            "model_name": model_name,
+            "directory": directory,
+            "provider": provider.replace("ExecutionProvider", ""),
+            "disable_safety_checker": disable_safety_checker,
+            "enable_cuda_graph": False,
+        }
+    )
+    return result
+
+
+def run_ort_trt_static(
+    work_dir: str,
+    version: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    max_batch_size: int,
+    nvtx_profile: bool = False,
+    use_cuda_graph: bool = True,
+):
+    print("[I] Initializing ORT TensorRT EP accelerated StableDiffusionXL txt2img pipeline (static input shape)")
+
+    # Register TensorRT plugins
+    from trt_utilities import init_trt_plugins  # noqa: PLC0415
+
+    init_trt_plugins()
+
+    assert batch_size <= max_batch_size
+
+    from diffusion_models import PipelineInfo  # noqa: PLC0415
+
+    pipeline_info = PipelineInfo(version)
+    short_name = pipeline_info.short_name()
+
+    from engine_builder import EngineType, get_engine_paths  # noqa: PLC0415
+    from pipeline_stable_diffusion import StableDiffusionPipeline  # noqa: PLC0415
+
+    engine_type = EngineType.ORT_TRT
+    onnx_dir, engine_dir, output_dir, framework_model_dir, _ = get_engine_paths(work_dir, pipeline_info, engine_type)
+
+    # Initialize pipeline
+    pipeline = StableDiffusionPipeline(
+        pipeline_info,
+        scheduler="DDIM",
+        output_dir=output_dir,
+        verbose=False,
+        nvtx_profile=nvtx_profile,
+        max_batch_size=max_batch_size,
+        use_cuda_graph=use_cuda_graph,
+        framework_model_dir=framework_model_dir,
+        engine_type=engine_type,
+    )
+
+    # Load TensorRT engines and pytorch modules
+    pipeline.backend.build_engines(
+        engine_dir,
+        framework_model_dir,
+        onnx_dir,
+        17,
+        opt_image_height=height,
+        opt_image_width=width,
+        opt_batch_size=batch_size,
+        static_batch=True,
+        static_image_shape=True,
+        max_workspace_size=0,
+        device_id=torch.cuda.current_device(),
+    )
+
+    # Here we use static batch and image size, so the resource allocation only need done once.
+    # For dynamic batch and image size, some cost (like memory allocation) shall be included in latency.
+    pipeline.load_resources(height, width, batch_size)
+
+    def warmup():
+        prompt, negative = warmup_prompts()
+        pipeline.run([prompt] * batch_size, [negative] * batch_size, height, width, denoising_steps=steps)
+
+    # Run warm up, and measure GPU memory of two runs
+    # The first run has algo search so it might need more memory
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    image_filename_prefix = get_image_filename_prefix("ort_trt", short_name, batch_size, steps, disable_safety_checker)
+
+    latency_list = []
+    prompts, negative_prompt = example_prompts()
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        # Use warmup mode here since non-warmup mode will save image to disk.
+        images, pipeline_time = pipeline.run(
+            [prompt] * batch_size,
+            [negative_prompt] * batch_size,
+            height,
+            width,
+            denoising_steps=steps,
+            guidance=7.5,
+            seed=123,
+        )
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"End2End took {latency:.3f} seconds. Inference latency: {pipeline_time}")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.jpg")
+
+    pipeline.teardown()
+
+    from tensorrt import __version__ as trt_version  # noqa: PLC0415
+
+    from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+    return {
+        "model_name": pipeline_info.name(),
+        "engine": "onnxruntime",
+        "version": ort_version,
+        "provider": f"tensorrt({trt_version})",
+        "directory": engine_dir,
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+        "disable_safety_checker": disable_safety_checker,
+        "enable_cuda_graph": use_cuda_graph,
+    }
+
+
+def run_tensorrt_static(
+    work_dir: str,
+    version: str,
+    model_name: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    max_batch_size: int,
+    nvtx_profile: bool = False,
+    use_cuda_graph: bool = True,
+    skip_warmup: bool = False,
+):
+    print("[I] Initializing TensorRT accelerated StableDiffusionXL txt2img pipeline (static input shape)")
+
+    from cuda import cudart  # noqa: PLC0415
+
+    # Register TensorRT plugins
+    from trt_utilities import init_trt_plugins  # noqa: PLC0415
+
+    init_trt_plugins()
+
+    assert batch_size <= max_batch_size
+
+    from diffusion_models import PipelineInfo  # noqa: PLC0415
+
+    pipeline_info = PipelineInfo(version)
+
+    from engine_builder import EngineType, get_engine_paths  # noqa: PLC0415
+    from pipeline_stable_diffusion import StableDiffusionPipeline  # noqa: PLC0415
+
+    engine_type = EngineType.TRT
+    onnx_dir, engine_dir, output_dir, framework_model_dir, timing_cache = get_engine_paths(
+        work_dir, pipeline_info, engine_type
+    )
+
+    # Initialize pipeline
+    pipeline = StableDiffusionPipeline(
+        pipeline_info,
+        scheduler="DDIM",
+        output_dir=output_dir,
+        verbose=False,
+        nvtx_profile=nvtx_profile,
+        max_batch_size=max_batch_size,
+        use_cuda_graph=True,
+        engine_type=engine_type,
+    )
+
+    # Load TensorRT engines and pytorch modules
+    pipeline.backend.load_engines(
+        engine_dir=engine_dir,
+        framework_model_dir=framework_model_dir,
+        onnx_dir=onnx_dir,
+        onnx_opset=17,
+        opt_batch_size=batch_size,
+        opt_image_height=height,
+        opt_image_width=width,
+        static_batch=True,
+        static_shape=True,
+        enable_all_tactics=False,
+        timing_cache=timing_cache,
+    )
+
+    # activate engines
+    max_device_memory = max(pipeline.backend.max_device_memory(), pipeline.backend.max_device_memory())
+    _, shared_device_memory = cudart.cudaMalloc(max_device_memory)
+    pipeline.backend.activate_engines(shared_device_memory)
+
+    # Here we use static batch and image size, so the resource allocation only need done once.
+    # For dynamic batch and image size, some cost (like memory allocation) shall be included in latency.
+    pipeline.load_resources(height, width, batch_size)
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        pipeline.run([prompt] * batch_size, [negative] * batch_size, height, width, denoising_steps=steps)
+
+    # Run warm up, and measure GPU memory of two runs
+    # The first run has algo search so it might need more memory
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    image_filename_prefix = get_image_filename_prefix("trt", model_name, batch_size, steps, disable_safety_checker)
+
+    latency_list = []
+    prompts, negative_prompt = example_prompts()
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        # Use warmup mode here since non-warmup mode will save image to disk.
+        images, pipeline_time = pipeline.run(
+            [prompt] * batch_size,
+            [negative_prompt] * batch_size,
+            height,
+            width,
+            denoising_steps=steps,
+            seed=123,
+        )
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"End2End took {latency:.3f} seconds. Inference latency: {pipeline_time}")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.jpg")
+
+    pipeline.teardown()
+
+    import tensorrt as trt  # noqa: PLC0415
+
+    return {
+        "engine": "tensorrt",
+        "version": trt.__version__,
+        "provider": "default",
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+        "enable_cuda_graph": use_cuda_graph,
+    }
+
+
+def run_tensorrt_static_xl(
+    work_dir: str,
+    version: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    max_batch_size: int,
+    nvtx_profile: bool = False,
+    use_cuda_graph=True,
+    skip_warmup: bool = False,
+):
+    print("[I] Initializing TensorRT accelerated StableDiffusionXL txt2img pipeline (static input shape)")
+
+    import tensorrt as trt  # noqa: PLC0415
+    from cuda import cudart  # noqa: PLC0415
+    from trt_utilities import init_trt_plugins  # noqa: PLC0415
+
+    # Validate image dimensions
+    image_height = height
+    image_width = width
+    if image_height % 8 != 0 or image_width % 8 != 0:
+        raise ValueError(
+            f"Image height and width have to be divisible by 8 but specified as: {image_height} and {image_width}."
+        )
+
+    # Register TensorRT plugins
+    init_trt_plugins()
+
+    assert batch_size <= max_batch_size
+
+    from diffusion_models import PipelineInfo  # noqa: PLC0415
+    from engine_builder import EngineType, get_engine_paths  # noqa: PLC0415
+
+    def init_pipeline(pipeline_class, pipeline_info):
+        engine_type = EngineType.TRT
+
+        onnx_dir, engine_dir, output_dir, framework_model_dir, timing_cache = get_engine_paths(
+            work_dir, pipeline_info, engine_type
+        )
+
+        # Initialize pipeline
+        pipeline = pipeline_class(
+            pipeline_info,
+            scheduler="DDIM",
+            output_dir=output_dir,
+            verbose=False,
+            nvtx_profile=nvtx_profile,
+            max_batch_size=max_batch_size,
+            use_cuda_graph=use_cuda_graph,
+            framework_model_dir=framework_model_dir,
+            engine_type=engine_type,
+        )
+
+        pipeline.backend.load_engines(
+            engine_dir=engine_dir,
+            framework_model_dir=framework_model_dir,
+            onnx_dir=onnx_dir,
+            onnx_opset=17,
+            opt_batch_size=batch_size,
+            opt_image_height=height,
+            opt_image_width=width,
+            static_batch=True,
+            static_shape=True,
+            enable_all_tactics=False,
+            timing_cache=timing_cache,
+        )
+        return pipeline
+
+    from pipeline_stable_diffusion import StableDiffusionPipeline  # noqa: PLC0415
+
+    pipeline_info = PipelineInfo(version)
+    pipeline = init_pipeline(StableDiffusionPipeline, pipeline_info)
+
+    max_device_memory = max(pipeline.backend.max_device_memory(), pipeline.backend.max_device_memory())
+    _, shared_device_memory = cudart.cudaMalloc(max_device_memory)
+    pipeline.backend.activate_engines(shared_device_memory)
+
+    # Here we use static batch and image size, so the resource allocation only need done once.
+    # For dynamic batch and image size, some cost (like memory allocation) shall be included in latency.
+    pipeline.load_resources(image_height, image_width, batch_size)
+
+    def run_sd_xl_inference(prompt, negative_prompt, seed=None):
+        return pipeline.run(
+            prompt,
+            negative_prompt,
+            image_height,
+            image_width,
+            denoising_steps=steps,
+            guidance=5.0,
+            seed=seed,
+        )
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        run_sd_xl_inference([prompt] * batch_size, [negative] * batch_size)
+
+    # Run warm up, and measure GPU memory of two runs
+    # The first run has algo search so it might need more memory
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    model_name = pipeline_info.name()
+    image_filename_prefix = get_image_filename_prefix("trt", model_name, batch_size, steps, disable_safety_checker)
+
+    latency_list = []
+    prompts, negative_prompt = example_prompts()
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        # Use warmup mode here since non-warmup mode will save image to disk.
+        images, pipeline_time = run_sd_xl_inference([prompt] * batch_size, [negative_prompt] * batch_size, seed=123)
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"End2End took {latency:.3f} seconds. Inference latency: {pipeline_time}")
+        for k, image in enumerate(images):
+            image.save(f"{image_filename_prefix}_{i}_{k}.png")
+
+    pipeline.teardown()
+
+    return {
+        "model_name": model_name,
+        "engine": "tensorrt",
+        "version": trt.__version__,
+        "provider": "default",
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+        "enable_cuda_graph": use_cuda_graph,
+    }
+
+
+def run_ort_trt_xl(
+    work_dir: str,
+    version: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    max_batch_size: int,
+    nvtx_profile: bool = False,
+    use_cuda_graph=True,
+    skip_warmup: bool = False,
+):
+    from demo_utils import initialize_pipeline  # noqa: PLC0415
+    from engine_builder import EngineType  # noqa: PLC0415
+
+    pipeline = initialize_pipeline(
+        version=version,
+        engine_type=EngineType.ORT_TRT,
+        work_dir=work_dir,
+        height=height,
+        width=width,
+        use_cuda_graph=use_cuda_graph,
+        max_batch_size=max_batch_size,
+        opt_batch_size=batch_size,
+    )
+
+    assert batch_size <= max_batch_size
+
+    pipeline.load_resources(height, width, batch_size)
+
+    def run_sd_xl_inference(prompt, negative_prompt, seed=None):
+        return pipeline.run(
+            prompt,
+            negative_prompt,
+            height,
+            width,
+            denoising_steps=steps,
+            guidance=5.0,
+            seed=seed,
+        )
+
+    def warmup():
+        if skip_warmup:
+            return
+        prompt, negative = warmup_prompts()
+        run_sd_xl_inference([prompt] * batch_size, [negative] * batch_size)
+
+    # Run warm up, and measure GPU memory of two runs
+    # The first run has algo search so it might need more memory
+    first_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+    second_run_memory = measure_gpu_memory(memory_monitor_type, warmup, start_memory)
+
+    warmup()
+
+    model_name = pipeline.pipeline_info.name()
+    image_filename_prefix = get_image_filename_prefix("ort_trt", model_name, batch_size, steps, disable_safety_checker)
+
+    latency_list = []
+    prompts, negative_prompt = example_prompts()
+    for i, prompt in enumerate(prompts):
+        if i >= num_prompts:
+            break
+        inference_start = time.time()
+        # Use warmup mode here since non-warmup mode will save image to disk.
+        images, pipeline_time = run_sd_xl_inference([prompt] * batch_size, [negative_prompt] * batch_size, seed=123)
+        inference_end = time.time()
+        latency = inference_end - inference_start
+        latency_list.append(latency)
+        print(f"End2End took {latency:.3f} seconds. Inference latency: {pipeline_time}")
+        for k, image in enumerate(images):
+            filename = f"{image_filename_prefix}_{i}_{k}.png"
+            image.save(filename)
+            print("Image saved to", filename)
+
+    pipeline.teardown()
+
+    from tensorrt import __version__ as trt_version  # noqa: PLC0415
+
+    from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+    return {
+        "model_name": model_name,
+        "engine": "onnxruntime",
+        "version": ort_version,
+        "provider": f"tensorrt{trt_version})",
+        "height": height,
+        "width": width,
+        "steps": steps,
+        "batch_size": batch_size,
+        "batch_count": batch_count,
+        "num_prompts": num_prompts,
+        "average_latency": sum(latency_list) / len(latency_list),
+        "median_latency": statistics.median(latency_list),
+        "first_run_memory_MB": first_run_memory,
+        "second_run_memory_MB": second_run_memory,
+        "enable_cuda_graph": use_cuda_graph,
+    }
+
+
+def run_torch(
+    model_name: str,
+    batch_size: int,
+    disable_safety_checker: bool,
+    enable_torch_compile: bool,
+    use_xformers: bool,
+    height: int,
+    width: int,
+    steps: int,
+    num_prompts: int,
+    batch_count: int,
+    start_memory,
+    memory_monitor_type,
+    skip_warmup: bool = True,
+):
+    torch.backends.cudnn.enabled = True
+    torch.backends.cudnn.benchmark = True
+
+    torch.set_grad_enabled(False)
+
+    load_start = time.time()
+    pipe = get_torch_pipeline(model_name, disable_safety_checker, enable_torch_compile, use_xformers)
+    load_end = time.time()
+    print(f"Model loading took {load_end - load_start} seconds")
+
+    image_filename_prefix = get_image_filename_prefix("torch", model_name, batch_size, steps, disable_safety_checker)
+
+    if not enable_torch_compile:
+        with torch.inference_mode():
+            result = run_torch_pipeline(
+                pipe,
+                batch_size,
+                image_filename_prefix,
+                height,
+                width,
+                steps,
+                num_prompts,
+                batch_count,
+                start_memory,
+                memory_monitor_type,
+                skip_warmup=skip_warmup,
+            )
+    else:
+        result = run_torch_pipeline(
+            pipe,
+            batch_size,
+            image_filename_prefix,
+            height,
+            width,
+            steps,
+            num_prompts,
+            batch_count,
+            start_memory,
+            memory_monitor_type,
+            skip_warmup=skip_warmup,
+        )
+
+    result.update(
+        {
+            "model_name": model_name,
+            "directory": None,
+            "provider": "compile" if enable_torch_compile else "xformers" if use_xformers else "default",
+            "disable_safety_checker": disable_safety_checker,
+            "enable_cuda_graph": False,
+        }
+    )
+    return result
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-e",
+        "--engine",
+        required=False,
+        type=str,
+        default="onnxruntime",
+        choices=["onnxruntime", "optimum", "torch", "tensorrt"],
+        help="Engines to benchmark. Default is onnxruntime.",
+    )
+
+    parser.add_argument(
+        "-r",
+        "--provider",
+        required=False,
+        type=str,
+        default="cuda",
+        choices=list(PROVIDERS.keys()),
+        help="Provider to benchmark. Default is CUDAExecutionProvider.",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--tuning",
+        action="store_true",
+        help="Enable TunableOp and tuning. This will incur longer warmup latency.",
+    )
+
+    parser.add_argument(
+        "-v",
+        "--version",
+        required=False,
+        type=str,
+        choices=list(SD_MODELS.keys()),
+        default="1.5",
+        help="Stable diffusion version like 1.5, 2.0 or 2.1. Default is 1.5.",
+    )
+
+    parser.add_argument(
+        "-p",
+        "--pipeline",
+        required=False,
+        type=str,
+        default=None,
+        help="Directory of saved onnx pipeline. It could be the output directory of optimize_pipeline.py.",
+    )
+
+    parser.add_argument(
+        "-w",
+        "--work_dir",
+        required=False,
+        type=str,
+        default=".",
+        help="Root directory to save exported onnx models, built engines etc.",
+    )
+
+    parser.add_argument(
+        "--enable_safety_checker",
+        required=False,
+        action="store_true",
+        help="Enable safety checker",
+    )
+    parser.set_defaults(enable_safety_checker=False)
+
+    parser.add_argument(
+        "--enable_torch_compile",
+        required=False,
+        action="store_true",
+        help="Enable compile unet for PyTorch 2.0",
+    )
+    parser.set_defaults(enable_torch_compile=False)
+
+    parser.add_argument(
+        "--use_xformers",
+        required=False,
+        action="store_true",
+        help="Use xformers for PyTorch",
+    )
+    parser.set_defaults(use_xformers=False)
+
+    parser.add_argument(
+        "--use_io_binding",
+        required=False,
+        action="store_true",
+        help="Use I/O Binding for Optimum.",
+    )
+    parser.set_defaults(use_io_binding=False)
+
+    parser.add_argument(
+        "--skip_warmup",
+        required=False,
+        action="store_true",
+        help="No warmup.",
+    )
+    parser.set_defaults(skip_warmup=False)
+
+    parser.add_argument(
+        "-b",
+        "--batch_size",
+        type=int,
+        default=1,
+        choices=[1, 2, 3, 4, 8, 10, 16, 32],
+        help="Number of images per batch. Default is 1.",
+    )
+
+    parser.add_argument(
+        "--height",
+        required=False,
+        type=int,
+        default=512,
+        help="Output image height. Default is 512.",
+    )
+
+    parser.add_argument(
+        "--width",
+        required=False,
+        type=int,
+        default=512,
+        help="Output image width. Default is 512.",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--steps",
+        required=False,
+        type=int,
+        default=50,
+        help="Number of steps. Default is 50.",
+    )
+
+    parser.add_argument(
+        "-n",
+        "--num_prompts",
+        required=False,
+        type=int,
+        default=10,
+        help="Number of prompts. Default is 10.",
+    )
+
+    parser.add_argument(
+        "-c",
+        "--batch_count",
+        required=False,
+        type=int,
+        choices=range(1, 11),
+        default=5,
+        help="Number of batches to test. Default is 5.",
+    )
+
+    parser.add_argument(
+        "-m",
+        "--max_trt_batch_size",
+        required=False,
+        type=int,
+        choices=range(1, 16),
+        default=4,
+        help="Maximum batch size for TensorRT. Change the value may trigger TensorRT engine rebuild. Default is 4.",
+    )
+
+    parser.add_argument(
+        "-g",
+        "--enable_cuda_graph",
+        required=False,
+        action="store_true",
+        help="Enable Cuda Graph. Requires onnxruntime >= 1.16",
+    )
+    parser.set_defaults(enable_cuda_graph=False)
+
+    args = parser.parse_args()
+
+    return args
+
+
+def print_loaded_libraries(cuda_related_only=True):
+    import psutil  # noqa: PLC0415
+
+    p = psutil.Process(os.getpid())
+    for lib in p.memory_maps():
+        if (not cuda_related_only) or any(x in lib.path for x in ("libcu", "libnv", "tensorrt")):
+            print(lib.path)
+
+
+def main():
+    args = parse_arguments()
+    print(args)
+
+    if args.engine == "onnxruntime":
+        if args.version in ["2.1"]:
+            # Set a flag to avoid overflow in attention, which causes black image output in SD 2.1 model.
+            # The environment variables shall be set before the first run of Attention or MultiHeadAttention operator.
+            os.environ["ORT_DISABLE_TRT_FLASH_ATTENTION"] = "1"
+
+        from packaging import version  # noqa: PLC0415
+
+        from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+        if version.parse(ort_version) == version.parse("1.16.0"):
+            # ORT 1.16 has a bug that might trigger Attention RuntimeError when latest fusion script is applied on clip model.
+            # The walkaround is to enable fused causal attention, or disable Attention fusion for clip model.
+            os.environ["ORT_ENABLE_FUSED_CAUSAL_ATTENTION"] = "1"
+
+        if args.enable_cuda_graph:
+            if not (args.engine == "onnxruntime" and args.provider in ["cuda", "tensorrt"] and args.pipeline is None):
+                raise ValueError("The stable diffusion pipeline does not support CUDA graph.")
+
+            if version.parse(ort_version) < version.parse("1.16"):
+                raise ValueError("CUDA graph requires ONNX Runtime 1.16 or later")
+
+    logging.basicConfig(format="%(funcName)20s: %(message)s", level=logging.INFO, force=True)
+
+    memory_monitor_type = "cuda"
+
+    start_memory = measure_gpu_memory(memory_monitor_type, None)
+    print("GPU memory used before loading models:", start_memory)
+
+    sd_model = SD_MODELS[args.version]
+    provider = PROVIDERS[args.provider]
+    if args.engine == "onnxruntime" and args.provider == "tensorrt":
+        if "xl" in args.version:
+            print("Testing Txt2ImgXLPipeline with static input shape. Backend is ORT TensorRT EP.")
+            result = run_ort_trt_xl(
+                work_dir=args.work_dir,
+                version=args.version,
+                batch_size=args.batch_size,
+                disable_safety_checker=True,
+                height=args.height,
+                width=args.width,
+                steps=args.steps,
+                num_prompts=args.num_prompts,
+                batch_count=args.batch_count,
+                start_memory=start_memory,
+                memory_monitor_type=memory_monitor_type,
+                max_batch_size=args.max_trt_batch_size,
+                nvtx_profile=False,
+                use_cuda_graph=args.enable_cuda_graph,
+                skip_warmup=args.skip_warmup,
+            )
+        else:
+            print("Testing Txt2ImgPipeline with static input shape. Backend is ORT TensorRT EP.")
+            result = run_ort_trt_static(
+                work_dir=args.work_dir,
+                version=args.version,
+                batch_size=args.batch_size,
+                disable_safety_checker=not args.enable_safety_checker,
+                height=args.height,
+                width=args.width,
+                steps=args.steps,
+                num_prompts=args.num_prompts,
+                batch_count=args.batch_count,
+                start_memory=start_memory,
+                memory_monitor_type=memory_monitor_type,
+                max_batch_size=args.max_trt_batch_size,
+                nvtx_profile=False,
+                use_cuda_graph=args.enable_cuda_graph,
+                skip_warmup=args.skip_warmup,
+            )
+    elif args.engine == "optimum" and provider == "CUDAExecutionProvider":
+        if "xl" in args.version:
+            os.environ["ORT_ENABLE_FUSED_CAUSAL_ATTENTION"] = "1"
+
+        result = run_optimum_ort(
+            model_name=sd_model,
+            directory=args.pipeline,
+            provider=provider,
+            batch_size=args.batch_size,
+            disable_safety_checker=not args.enable_safety_checker,
+            height=args.height,
+            width=args.width,
+            steps=args.steps,
+            num_prompts=args.num_prompts,
+            batch_count=args.batch_count,
+            start_memory=start_memory,
+            memory_monitor_type=memory_monitor_type,
+            use_io_binding=args.use_io_binding,
+            skip_warmup=args.skip_warmup,
+        )
+    elif args.engine == "onnxruntime":
+        assert args.pipeline and os.path.isdir(args.pipeline), (
+            "--pipeline should be specified for the directory of ONNX models"
+        )
+        print(f"Testing diffusers StableDiffusionPipeline with {provider} provider and tuning={args.tuning}")
+        result = run_ort(
+            model_name=sd_model,
+            directory=args.pipeline,
+            provider=provider,
+            batch_size=args.batch_size,
+            disable_safety_checker=not args.enable_safety_checker,
+            height=args.height,
+            width=args.width,
+            steps=args.steps,
+            num_prompts=args.num_prompts,
+            batch_count=args.batch_count,
+            start_memory=start_memory,
+            memory_monitor_type=memory_monitor_type,
+            tuning=args.tuning,
+            skip_warmup=args.skip_warmup,
+        )
+    elif args.engine == "tensorrt" and "xl" in args.version:
+        print("Testing Txt2ImgXLPipeline with static input shape. Backend is TensorRT.")
+        result = run_tensorrt_static_xl(
+            work_dir=args.work_dir,
+            version=args.version,
+            batch_size=args.batch_size,
+            disable_safety_checker=True,
+            height=args.height,
+            width=args.width,
+            steps=args.steps,
+            num_prompts=args.num_prompts,
+            batch_count=args.batch_count,
+            start_memory=start_memory,
+            memory_monitor_type=memory_monitor_type,
+            max_batch_size=args.max_trt_batch_size,
+            nvtx_profile=False,
+            use_cuda_graph=args.enable_cuda_graph,
+            skip_warmup=args.skip_warmup,
+        )
+    elif args.engine == "tensorrt":
+        print("Testing Txt2ImgPipeline with static input shape. Backend is TensorRT.")
+        result = run_tensorrt_static(
+            work_dir=args.work_dir,
+            version=args.version,
+            model_name=sd_model,
+            batch_size=args.batch_size,
+            disable_safety_checker=True,
+            height=args.height,
+            width=args.width,
+            steps=args.steps,
+            num_prompts=args.num_prompts,
+            batch_count=args.batch_count,
+            start_memory=start_memory,
+            memory_monitor_type=memory_monitor_type,
+            max_batch_size=args.max_trt_batch_size,
+            nvtx_profile=False,
+            use_cuda_graph=args.enable_cuda_graph,
+            skip_warmup=args.skip_warmup,
+        )
+    else:
+        print(
+            f"Testing Txt2ImgPipeline with dynamic input shape. Backend is PyTorch: compile={args.enable_torch_compile}, xformers={args.use_xformers}."
+        )
+        result = run_torch(
+            model_name=sd_model,
+            batch_size=args.batch_size,
+            disable_safety_checker=not args.enable_safety_checker,
+            enable_torch_compile=args.enable_torch_compile,
+            use_xformers=args.use_xformers,
+            height=args.height,
+            width=args.width,
+            steps=args.steps,
+            num_prompts=args.num_prompts,
+            batch_count=args.batch_count,
+            start_memory=start_memory,
+            memory_monitor_type=memory_monitor_type,
+            skip_warmup=args.skip_warmup,
+        )
+
+    print(result)
+
+    with open("benchmark_result.csv", mode="a", newline="") as csv_file:
+        column_names = [
+            "model_name",
+            "directory",
+            "engine",
+            "version",
+            "provider",
+            "disable_safety_checker",
+            "height",
+            "width",
+            "steps",
+            "batch_size",
+            "batch_count",
+            "num_prompts",
+            "average_latency",
+            "median_latency",
+            "first_run_memory_MB",
+            "second_run_memory_MB",
+            "enable_cuda_graph",
+        ]
+        csv_writer = csv.DictWriter(csv_file, fieldnames=column_names)
+        csv_writer.writeheader()
+        csv_writer.writerow(result)
+
+    # Show loaded DLLs when steps == 1 for debugging purpose.
+    if args.steps == 1:
+        print_loaded_libraries(args.provider in ["cuda", "tensorrt"])
+
+
+if __name__ == "__main__":
+    import traceback
+
+    try:
+        main()
+    except Exception:
+        traceback.print_exception(*sys.exc_info())
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark_controlnet.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark_controlnet.py
new file mode 100644
index 0000000000000000000000000000000000000000..5d6b1cc1aea9cb07a798c756bf393d72e2379a3f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/benchmark_controlnet.py
@@ -0,0 +1,426 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import gc
+import importlib.util
+import time
+from statistics import mean
+
+import torch
+from demo_utils import PipelineInfo
+from diffusers import (
+    AutoencoderKL,
+    ControlNetModel,
+    DiffusionPipeline,
+    EulerAncestralDiscreteScheduler,
+    StableDiffusionXLControlNetPipeline,
+)
+from engine_builder import EngineType, get_engine_paths
+from pipeline_stable_diffusion import StableDiffusionPipeline
+
+"""
+Benchmark script for SDXL-Turbo with control net for engines like PyTorch or Stable Fast.
+
+Setup for Stable Fast (see https://github.com/chengzeyi/stable-fast/blob/main/README.md for more info):
+    git clone https://github.com/chengzeyi/stable-fast.git
+    cd stable-fast
+    git submodule update --init
+    pip3 install torch torchvision torchaudio ninja
+    pip3 install -e '.[dev,xformers,triton,transformers,diffusers]' -v
+    sudo apt install libgoogle-perftools-dev
+    export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libtcmalloc.so
+"""
+
+
+def get_canny_image():
+    import cv2  # noqa: PLC0415
+    import numpy as np  # noqa: PLC0415
+    from PIL import Image  # noqa: PLC0415
+
+    # Test Image can be downloaded from https://hf.co/datasets/huggingface/documentation-images/resolve/main/diffusers/input_image_vermeer.png
+    image = Image.open("input_image_vermeer.png").convert("RGB")
+
+    image = np.array(image)
+    image = cv2.Canny(image, 100, 200)
+    image = image[:, :, None]
+    image = np.concatenate([image, image, image], axis=2)
+    return Image.fromarray(image)
+
+
+def compile_stable_fast(pipeline, enable_cuda_graph=True):
+    from sfast.compilers.stable_diffusion_pipeline_compiler import CompilationConfig, compile  # noqa: PLC0415
+
+    config = CompilationConfig.Default()
+
+    if importlib.util.find_spec("xformers") is not None:
+        config.enable_xformers = True
+
+    if importlib.util.find_spec("triton") is not None:
+        config.enable_triton = True
+
+    config.enable_cuda_graph = enable_cuda_graph
+
+    pipeline = compile(pipeline, config)
+    return pipeline
+
+
+def compile_torch(pipeline, use_nhwc=False):
+    if use_nhwc:
+        pipeline.unet.to(memory_format=torch.channels_last)
+
+    pipeline.unet = torch.compile(pipeline.unet, mode="reduce-overhead", fullgraph=True)
+
+    if hasattr(pipeline, "controlnet"):
+        if use_nhwc:
+            pipeline.controlnet.to(memory_format=torch.channels_last)
+        pipeline.controlnet = torch.compile(pipeline.controlnet, mode="reduce-overhead", fullgraph=True)
+    return pipeline
+
+
+def load_pipeline(name, engine, use_control_net=False, use_nhwc=False, enable_cuda_graph=True):
+    gc.collect()
+    torch.cuda.empty_cache()
+    before_memory = torch.cuda.memory_allocated()
+
+    scheduler = EulerAncestralDiscreteScheduler.from_pretrained(name, subfolder="scheduler")
+    vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16).to("cuda")
+
+    if use_control_net:
+        assert "xl" in name
+        controlnet = ControlNetModel.from_pretrained("diffusers/controlnet-canny-sdxl-1.0", torch_dtype=torch.float16)
+        pipeline = StableDiffusionXLControlNetPipeline.from_pretrained(
+            name,
+            controlnet=controlnet,
+            vae=vae,
+            scheduler=scheduler,
+            variant="fp16",
+            use_safetensors=True,
+            torch_dtype=torch.float16,
+        ).to("cuda")
+    else:
+        pipeline = DiffusionPipeline.from_pretrained(
+            name,
+            vae=vae,
+            scheduler=scheduler,
+            variant="fp16",
+            use_safetensors=True,
+            torch_dtype=torch.float16,
+        ).to("cuda")
+    pipeline.safety_checker = None
+
+    gc.collect()
+    after_memory = torch.cuda.memory_allocated()
+    print(f"Loaded model with {after_memory - before_memory} bytes allocated")
+
+    if engine == "stable_fast":
+        pipeline = compile_stable_fast(pipeline, enable_cuda_graph=enable_cuda_graph)
+    elif engine == "torch":
+        pipeline = compile_torch(pipeline, use_nhwc=use_nhwc)
+
+    pipeline.set_progress_bar_config(disable=True)
+    return pipeline
+
+
+def get_prompt():
+    return "little cute gremlin wearing a jacket, cinematic, vivid colors, intricate masterpiece, golden ratio, highly detailed"
+
+
+def load_ort_cuda_pipeline(name, engine, use_control_net=False, enable_cuda_graph=True, work_dir="."):
+    version = PipelineInfo.supported_models()[name]
+    guidance_scale = 0.0
+    pipeline_info = PipelineInfo(
+        version,
+        use_vae=True,
+        use_fp16_vae=True,
+        do_classifier_free_guidance=(guidance_scale > 1.0),
+        controlnet=["canny"] if use_control_net else [],
+    )
+
+    engine_type = EngineType.ORT_CUDA if engine == "ort_cuda" else EngineType.ORT_TRT
+    onnx_dir, engine_dir, output_dir, framework_model_dir, _ = get_engine_paths(
+        work_dir=work_dir, pipeline_info=pipeline_info, engine_type=engine_type
+    )
+
+    pipeline = StableDiffusionPipeline(
+        pipeline_info,
+        scheduler="EulerA",
+        max_batch_size=32,
+        use_cuda_graph=enable_cuda_graph,
+        framework_model_dir=framework_model_dir,
+        output_dir=output_dir,
+        engine_type=engine_type,
+    )
+
+    pipeline.backend.build_engines(
+        engine_dir=engine_dir,
+        framework_model_dir=framework_model_dir,
+        onnx_dir=onnx_dir,
+        device_id=torch.cuda.current_device(),
+    )
+
+    return pipeline
+
+
+def test_ort_cuda(
+    pipeline,
+    batch_size=1,
+    steps=4,
+    control_image=None,
+    warmup_runs=3,
+    test_runs=10,
+    seed=123,
+    verbose=False,
+    image_height=512,
+    image_width=512,
+):
+    if batch_size > 4 and pipeline.pipeline_info.version == "xl-1.0":
+        pipeline.backend.enable_vae_slicing()
+
+    pipeline.load_resources(image_height, image_width, batch_size)
+
+    warmup_prompt = "warm up"
+    for _ in range(warmup_runs):
+        images, _ = pipeline.run(
+            [warmup_prompt] * batch_size,
+            [""] * batch_size,
+            image_height=image_height,
+            image_width=image_width,
+            denoising_steps=steps,
+            guidance=0.0,
+            seed=seed,
+            controlnet_images=[control_image],
+            controlnet_scales=torch.FloatTensor([0.5]),
+            output_type="image",
+        )
+        assert len(images) == batch_size
+
+    generator = torch.Generator(device="cuda")
+    generator.manual_seed(seed)
+
+    prompt = get_prompt()
+
+    latency_list = []
+    images = None
+    for _ in range(test_runs):
+        torch.cuda.synchronize()
+        start_time = time.perf_counter()
+        images, _ = pipeline.run(
+            [prompt] * batch_size,
+            [""] * batch_size,
+            image_height=image_height,
+            image_width=image_width,
+            denoising_steps=steps,
+            guidance=0.0,
+            seed=seed,
+            controlnet_images=[control_image],
+            controlnet_scales=torch.FloatTensor([0.5]),
+            output_type="pil",
+        )
+        torch.cuda.synchronize()
+        seconds = time.perf_counter() - start_time
+        latency_list.append(seconds)
+
+    if verbose:
+        print(latency_list)
+
+    return images, latency_list
+
+
+def test(pipeline, batch_size=1, steps=4, control_image=None, warmup_runs=3, test_runs=10, seed=123, verbose=False):
+    control_net_args = {}
+    if hasattr(pipeline, "controlnet"):
+        control_net_args = {
+            "image": control_image,
+            "controlnet_conditioning_scale": 0.5,
+        }
+
+    warmup_prompt = "warm up"
+    for _ in range(warmup_runs):
+        images = pipeline(
+            prompt=warmup_prompt,
+            num_inference_steps=steps,
+            num_images_per_prompt=batch_size,
+            guidance_scale=0.0,
+            **control_net_args,
+        ).images
+        assert len(images) == batch_size
+
+    generator = torch.Generator(device="cuda")
+    generator.manual_seed(seed)
+
+    prompt = get_prompt()
+
+    latency_list = []
+    images = None
+    for _ in range(test_runs):
+        torch.cuda.synchronize()
+        start_time = time.perf_counter()
+        images = pipeline(
+            prompt=prompt,
+            num_inference_steps=steps,
+            num_images_per_prompt=batch_size,
+            guidance_scale=0.0,
+            generator=generator,
+            **control_net_args,
+        ).images
+        torch.cuda.synchronize()
+        seconds = time.perf_counter() - start_time
+        latency_list.append(seconds)
+
+    if verbose:
+        print(latency_list)
+
+    return images, latency_list
+
+
+def arguments():
+    import argparse  # noqa: PLC0415
+
+    parser = argparse.ArgumentParser(description="Benchmark Stable Diffusion pipeline (optional control net for SDXL)")
+    parser.add_argument(
+        "--engine",
+        type=str,
+        default="torch",
+        choices=["torch", "stable_fast", "ort_cuda", "ort_trt"],
+        help="Backend engine: torch, stable_fast or ort_cuda",
+    )
+
+    parser.add_argument(
+        "--name",
+        type=str,
+        choices=list(PipelineInfo.supported_models().keys()),
+        default="stabilityai/sdxl-turbo",
+        help="Stable diffusion model name. Default is stabilityai/sdxl-turbo",
+    )
+
+    parser.add_argument(
+        "--work-dir",
+        type=str,
+        default=".",
+        help="working directory for ort_cuda or ort_trt",
+    )
+
+    parser.add_argument(
+        "--use_control_net",
+        action="store_true",
+        help="Use control net diffusers/controlnet-canny-sdxl-1.0",
+    )
+
+    parser.add_argument(
+        "--batch_size",
+        type=int,
+        default=1,
+        help="Batch size",
+    )
+
+    parser.add_argument(
+        "--steps",
+        type=int,
+        default=1,
+        help="Denoising steps",
+    )
+
+    parser.add_argument(
+        "--warmup_runs",
+        type=int,
+        default=3,
+        help="Number of warmup runs before measurement",
+    )
+
+    parser.add_argument(
+        "--use_nhwc",
+        action="store_true",
+        help="use channel last format for torch compile",
+    )
+
+    parser.add_argument(
+        "--enable_cuda_graph",
+        action="store_true",
+        help="enable cuda graph for stable fast",
+    )
+
+    parser.add_argument(
+        "--verbose",
+        action="store_true",
+        help="print more information",
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = arguments()
+
+    with torch.no_grad():
+        if args.engine == "ort_cuda":
+            pipeline = load_ort_cuda_pipeline(
+                args.name,
+                args.engine,
+                use_control_net=args.use_control_net,
+                enable_cuda_graph=args.enable_cuda_graph,
+                work_dir=args.work_dir,
+            )
+        else:
+            pipeline = load_pipeline(
+                args.name,
+                args.engine,
+                use_control_net=args.use_control_net,
+                use_nhwc=args.use_nhwc,
+                enable_cuda_graph=args.enable_cuda_graph,
+            )
+
+        canny_image = get_canny_image()
+
+        if args.engine == "ort_cuda":
+            images, latency_list = test_ort_cuda(
+                pipeline,
+                args.batch_size,
+                args.steps,
+                control_image=canny_image,
+                warmup_runs=args.warmup_runs,
+                verbose=args.verbose,
+            )
+        elif args.engine == "stable_fast":
+            from sfast.utils.compute_precision import low_compute_precision  # noqa: PLC0415
+
+            with low_compute_precision():
+                images, latency_list = test(
+                    pipeline,
+                    args.batch_size,
+                    args.steps,
+                    control_image=canny_image,
+                    warmup_runs=args.warmup_runs,
+                    verbose=args.verbose,
+                )
+        else:
+            images, latency_list = test(
+                pipeline,
+                args.batch_size,
+                args.steps,
+                control_image=canny_image,
+                warmup_runs=args.warmup_runs,
+                verbose=args.verbose,
+            )
+
+        # Save the first output image to inspect the result.
+        if images:
+            images[0].save(
+                f"{args.engine}_{args.name.replace('/', '_')}_{args.batch_size}_{args.steps}_c{int(args.use_control_net)}.png"
+            )
+
+        result = {
+            "engine": args.engine,
+            "batch_size": args.batch_size,
+            "steps": args.steps,
+            "control_net": args.use_control_net,
+            "nhwc": args.use_nhwc,
+            "enable_cuda_graph": args.enable_cuda_graph,
+            "average_latency_in_ms": mean(latency_list) * 1000,
+        }
+        print(result)
+
+
+main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img.py
new file mode 100644
index 0000000000000000000000000000000000000000..9db4eb0016c5a937c9cf2ce035d9f7074d2600ae
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img.py
@@ -0,0 +1,103 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from TensorRT demo diffusion, which has the following license:
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+
+import logging
+
+from cuda import cudart
+from demo_utils import (
+    add_controlnet_arguments,
+    arg_parser,
+    get_metadata,
+    load_pipelines,
+    parse_arguments,
+    process_controlnet_arguments,
+    repeat_prompt,
+)
+
+
+def main(args):
+    controlnet_images, controlnet_scale = process_controlnet_arguments(args)
+
+    pipeline, refiner = load_pipelines(args)
+    assert refiner is None
+
+    prompt, negative_prompt = repeat_prompt(args)
+    batch_size = len(prompt)
+    pipeline.load_resources(args.height, args.width, batch_size)
+
+    def run_inference(warmup=False):
+        return pipeline.run(
+            prompt,
+            negative_prompt,
+            args.height,
+            args.width,
+            denoising_steps=args.denoising_steps,
+            guidance=args.guidance,
+            seed=args.seed,
+            controlnet_images=controlnet_images,
+            controlnet_scales=controlnet_scale,
+            show_latency=not warmup,
+            output_type="pil",
+            deterministic=args.deterministic,
+        )
+
+    if not args.disable_cuda_graph:
+        # inference once to get cuda graph
+        _, _ = run_inference(warmup=True)
+
+    print("[I] Warming up ..")
+    for _ in range(args.num_warmup_runs):
+        _, _ = run_inference(warmup=True)
+
+    print("[I] Running StableDiffusion pipeline")
+    if args.nvtx_profile:
+        cudart.cudaProfilerStart()
+    images, perf_data = run_inference(warmup=False)
+    if args.nvtx_profile:
+        cudart.cudaProfilerStop()
+
+    metadata = get_metadata(args, False)
+    metadata.update(pipeline.metadata())
+    if perf_data:
+        metadata.update(perf_data)
+    metadata["images"] = len(images)
+    print(metadata)
+    pipeline.save_images(images, prompt, negative_prompt, metadata)
+
+    pipeline.teardown()
+
+
+if __name__ == "__main__":
+    logging.basicConfig(format="%(funcName)20s: %(message)s", level=logging.INFO)
+
+    parser = arg_parser("Options for Stable Diffusion Demo")
+    add_controlnet_arguments(parser)
+    args = parse_arguments(is_xl=False, parser=parser)
+
+    if args.user_compute_stream:
+        import torch
+
+        s = torch.cuda.Stream()
+        with torch.cuda.stream(s):
+            main(args)
+    else:
+        main(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img_xl.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img_xl.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c550923766545204fcb6b0874279334e77bcfc5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_txt2img_xl.py
@@ -0,0 +1,269 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from TensorRT demo diffusion, which has the following license:
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+
+import logging
+
+from cuda import cudart
+from demo_utils import (
+    add_controlnet_arguments,
+    arg_parser,
+    get_metadata,
+    load_pipelines,
+    parse_arguments,
+    process_controlnet_arguments,
+    repeat_prompt,
+)
+
+
+def run_pipelines(
+    args, base, refiner, prompt, negative_prompt, controlnet_image=None, controlnet_scale=None, is_warm_up=False
+):
+    image_height = args.height
+    image_width = args.width
+    batch_size = len(prompt)
+    base.load_resources(image_height, image_width, batch_size)
+    if refiner:
+        refiner.load_resources(image_height, image_width, batch_size)
+
+    def run_base_and_refiner(warmup=False):
+        images, base_perf = base.run(
+            prompt,
+            negative_prompt,
+            image_height,
+            image_width,
+            denoising_steps=args.denoising_steps,
+            guidance=args.guidance,
+            seed=args.seed,
+            controlnet_images=controlnet_image,
+            controlnet_scales=controlnet_scale,
+            show_latency=not warmup,
+            output_type="latent" if refiner else "pil",
+        )
+        if refiner is None:
+            return images, base_perf
+
+        # Use same seed in base and refiner.
+        seed = base.get_current_seed()
+
+        images, refiner_perf = refiner.run(
+            prompt,
+            negative_prompt,
+            image_height,
+            image_width,
+            denoising_steps=args.refiner_denoising_steps,
+            image=images,
+            strength=args.strength,
+            guidance=args.refiner_guidance,
+            seed=seed,
+            show_latency=not warmup,
+        )
+
+        perf_data = None
+        if base_perf and refiner_perf:
+            perf_data = {"latency": base_perf["latency"] + refiner_perf["latency"]}
+            perf_data.update({"base." + key: val for key, val in base_perf.items()})
+            perf_data.update({"refiner." + key: val for key, val in refiner_perf.items()})
+
+        return images, perf_data
+
+    if not args.disable_cuda_graph:
+        # inference once to get cuda graph
+        _, _ = run_base_and_refiner(warmup=True)
+
+    if args.num_warmup_runs > 0:
+        print("[I] Warming up ..")
+    for _ in range(args.num_warmup_runs):
+        _, _ = run_base_and_refiner(warmup=True)
+
+    if is_warm_up:
+        return
+
+    print("[I] Running StableDiffusion XL pipeline")
+    if args.nvtx_profile:
+        cudart.cudaProfilerStart()
+    images, perf_data = run_base_and_refiner(warmup=False)
+    if args.nvtx_profile:
+        cudart.cudaProfilerStop()
+
+    if refiner:
+        print("|----------------|--------------|")
+        print("| {:^14} | {:>9.2f} ms |".format("e2e", perf_data["latency"]))
+        print("|----------------|--------------|")
+
+    metadata = get_metadata(args, True)
+    metadata.update({"base." + key: val for key, val in base.metadata().items()})
+    if refiner:
+        metadata.update({"refiner." + key: val for key, val in refiner.metadata().items()})
+    if perf_data:
+        metadata.update(perf_data)
+    metadata["images"] = len(images)
+    print(metadata)
+    (refiner or base).save_images(images, prompt, negative_prompt, metadata)
+
+
+def run_demo(args):
+    """Run Stable Diffusion XL Base + Refiner together (known as ensemble of expert denoisers) to generate an image."""
+    controlnet_image, controlnet_scale = process_controlnet_arguments(args)
+    prompt, negative_prompt = repeat_prompt(args)
+    batch_size = len(prompt)
+    base, refiner = load_pipelines(args, batch_size)
+    run_pipelines(args, base, refiner, prompt, negative_prompt, controlnet_image, controlnet_scale)
+    base.teardown()
+    if refiner:
+        refiner.teardown()
+
+
+def run_dynamic_shape_demo(args):
+    """
+    Run demo of generating images with different settings with ORT CUDA provider.
+    Try "python demo_txt2img_xl.py --max-cuda-graphs 3 --user-compute-stream" to see the effect of multiple CUDA graphs.
+    """
+    args.engine = "ORT_CUDA"
+    base, refiner = load_pipelines(args, 1)
+
+    prompts = [
+        "starry night over Golden Gate Bridge by van gogh",
+        "beautiful photograph of Mt. Fuji during cherry blossom",
+        "little cute gremlin sitting on a bed, cinematic",
+        "cute grey cat with blue eyes, wearing a bowtie, acrylic painting",
+        "beautiful Renaissance Revival Estate, Hobbit-House, detailed painting, warm colors, 8k, trending on Artstation",
+        "blue owl, big green eyes, portrait, intricate metal design, unreal engine, octane render, realistic",
+        "An astronaut riding a rainbow unicorn, cinematic, dramatic",
+        "close-up photography of old man standing in the rain at night, in a street lit by lamps, leica 35mm",
+    ]
+
+    # batch size, height, width, scheduler, steps, prompt, seed, guidance, refiner scheduler, refiner steps, refiner strength
+    configs = [
+        (1, 832, 1216, "UniPC", 8, prompts[0], None, 5.0, "UniPC", 10, 0.3),
+        (1, 1024, 1024, "DDIM", 24, prompts[1], None, 5.0, "DDIM", 30, 0.3),
+        (1, 1216, 832, "EulerA", 16, prompts[2], 1716921396712843, 5.0, "EulerA", 10, 0.3),
+        (1, 1344, 768, "EulerA", 24, prompts[3], 123698071912362, 5.0, "EulerA", 20, 0.3),
+        (2, 640, 1536, "UniPC", 16, prompts[4], 4312973633252712, 5.0, "UniPC", 10, 0.3),
+        (2, 1152, 896, "DDIM", 24, prompts[5], 1964684802882906, 5.0, "UniPC", 20, 0.3),
+    ]
+
+    # In testing LCM, refiner is disabled so the settings of refiner is not used.
+    if args.lcm:
+        configs = [
+            (1, 1024, 1024, "LCM", 8, prompts[6], None, 1.0, "UniPC", 20, 0.3),
+            (1, 1216, 832, "LCM", 6, prompts[7], 1337, 1.0, "UniPC", 20, 0.3),
+        ]
+
+    # Warm up each combination of (batch size, height, width) once before serving.
+    args.prompt = ["warm up"]
+    args.num_warmup_runs = 1
+    for batch_size, height, width, _, _, _, _, _, _, _, _ in configs:
+        args.batch_size = batch_size
+        args.height = height
+        args.width = width
+        print(f"\nWarm up batch_size={batch_size}, height={height}, width={width}")
+        prompt, negative_prompt = repeat_prompt(args)
+        run_pipelines(args, base, refiner, prompt, negative_prompt, is_warm_up=True)
+
+    # Run pipeline on a list of prompts.
+    args.num_warmup_runs = 0
+    for (
+        batch_size,
+        height,
+        width,
+        scheduler,
+        steps,
+        example_prompt,
+        seed,
+        guidance,
+        refiner_scheduler,
+        refiner_denoising_steps,
+        strength,
+    ) in configs:
+        args.prompt = [example_prompt]
+        args.batch_size = batch_size
+        args.height = height
+        args.width = width
+        args.scheduler = scheduler
+        args.denoising_steps = steps
+        args.seed = seed
+        args.guidance = guidance
+        args.refiner_scheduler = refiner_scheduler
+        args.refiner_denoising_steps = refiner_denoising_steps
+        args.strength = strength
+        base.set_scheduler(scheduler)
+        if refiner:
+            refiner.set_scheduler(refiner_scheduler)
+        prompt, negative_prompt = repeat_prompt(args)
+        run_pipelines(args, base, refiner, prompt, negative_prompt, is_warm_up=False)
+
+    base.teardown()
+    if refiner:
+        refiner.teardown()
+
+
+def run_turbo_demo(args):
+    """Run demo of generating images with test prompts with ORT CUDA provider."""
+    args.engine = "ORT_CUDA"
+    base, refiner = load_pipelines(args, 1)
+
+    from datasets import load_dataset  # noqa: PLC0415
+
+    dataset = load_dataset("Gustavosta/Stable-Diffusion-Prompts")
+    num_rows = dataset["test"].num_rows
+    batch_size = args.batch_size
+    num_batch = int(num_rows / batch_size)
+    args.batch_size = 1
+    for i in range(num_batch):
+        args.prompt = [dataset["test"][i]["Prompt"] for i in range(i * batch_size, (i + 1) * batch_size)]
+        base.set_scheduler(args.scheduler)
+        if refiner:
+            refiner.set_scheduler(args.refiner_scheduler)
+        prompt, negative_prompt = repeat_prompt(args)
+        run_pipelines(args, base, refiner, prompt, negative_prompt, is_warm_up=False)
+
+    base.teardown()
+    if refiner:
+        refiner.teardown()
+
+
+def main(args):
+    no_prompt = isinstance(args.prompt, list) and len(args.prompt) == 1 and not args.prompt[0]
+    if no_prompt:
+        if args.version == "xl-turbo":
+            run_turbo_demo(args)
+        else:
+            run_dynamic_shape_demo(args)
+    else:
+        run_demo(args)
+
+
+if __name__ == "__main__":
+    logging.basicConfig(format="%(funcName)20s: %(message)s", level=logging.INFO)
+
+    parser = arg_parser("Options for Stable Diffusion XL Demo")
+    add_controlnet_arguments(parser)
+    args = parse_arguments(is_xl=True, parser=parser)
+
+    if args.user_compute_stream:
+        import torch
+
+        s = torch.cuda.Stream()
+        with torch.cuda.stream(s):
+            main(args)
+    else:
+        main(args)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_utils.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..b7df106649fe04c8782e39bd2c943f952fff6cf6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/demo_utils.py
@@ -0,0 +1,778 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from TensorRT demo diffusion, which has the following license:
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+import argparse
+import os
+import sys
+from importlib.metadata import PackageNotFoundError, version
+from typing import Any
+
+import controlnet_aux
+import cv2
+import numpy as np
+import torch
+from cuda import cudart
+from diffusion_models import PipelineInfo
+from engine_builder import EngineType, get_engine_paths, get_engine_type
+from PIL import Image
+from pipeline_stable_diffusion import StableDiffusionPipeline
+
+
+class RawTextArgumentDefaultsHelpFormatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawTextHelpFormatter):
+    pass
+
+
+def arg_parser(description: str):
+    return argparse.ArgumentParser(
+        description=description,
+        formatter_class=RawTextArgumentDefaultsHelpFormatter,
+    )
+
+
+def set_default_arguments(args):
+    # set default value for some arguments if not provided
+    if args.height is None:
+        args.height = PipelineInfo.default_resolution(args.version)
+
+    if args.width is None:
+        args.width = PipelineInfo.default_resolution(args.version)
+
+    is_lcm = (args.version == "xl-1.0" and args.lcm) or "lcm" in args.lora_weights
+    is_turbo = args.version in ["sd-turbo", "xl-turbo"]
+    if args.denoising_steps is None:
+        args.denoising_steps = 4 if is_turbo else 8 if is_lcm else (30 if args.version == "xl-1.0" else 50)
+
+    if args.scheduler is None:
+        args.scheduler = "LCM" if (is_lcm or is_turbo) else ("EulerA" if args.version == "xl-1.0" else "DDIM")
+
+    if args.guidance is None:
+        args.guidance = 0.0 if (is_lcm or is_turbo) else (5.0 if args.version == "xl-1.0" else 7.5)
+
+
+def parse_arguments(is_xl: bool, parser):
+    engines = ["ORT_CUDA", "ORT_TRT", "TRT", "TORCH"]
+
+    parser.add_argument(
+        "-e",
+        "--engine",
+        type=str,
+        default=engines[0],
+        choices=engines,
+        help="Backend engine in {engines}. "
+        "ORT_CUDA is CUDA execution provider; ORT_TRT is Tensorrt execution provider; TRT is TensorRT",
+    )
+
+    supported_versions = PipelineInfo.supported_versions(is_xl)
+    parser.add_argument(
+        "-v",
+        "--version",
+        type=str,
+        default="xl-1.0" if is_xl else "1.5",
+        choices=supported_versions,
+        help="Version of Stable Diffusion" + (" XL." if is_xl else "."),
+    )
+
+    parser.add_argument(
+        "-y",
+        "--height",
+        type=int,
+        default=None,
+        help="Height of image to generate (must be multiple of 8).",
+    )
+    parser.add_argument(
+        "-x", "--width", type=int, default=None, help="Height of image to generate (must be multiple of 8)."
+    )
+
+    parser.add_argument(
+        "-s",
+        "--scheduler",
+        type=str,
+        default=None,
+        choices=["DDIM", "EulerA", "UniPC", "LCM"],
+        help="Scheduler for diffusion process" + " of base" if is_xl else "",
+    )
+
+    parser.add_argument(
+        "-wd",
+        "--work-dir",
+        default=".",
+        help="Root Directory to store torch or ONNX models, built engines and output images etc.",
+    )
+
+    parser.add_argument(
+        "-i",
+        "--engine-dir",
+        default=None,
+        help="Root Directory to store built engines or optimized ONNX models etc.",
+    )
+
+    parser.add_argument("prompt", nargs="*", default=[""], help="Text prompt(s) to guide image generation.")
+
+    parser.add_argument(
+        "-n",
+        "--negative-prompt",
+        nargs="*",
+        default=[""],
+        help="Optional negative prompt(s) to guide the image generation.",
+    )
+    parser.add_argument(
+        "-b",
+        "--batch-size",
+        type=int,
+        default=1,
+        choices=[1, 2, 4, 8, 16],
+        help="Number of times to repeat the prompt (batch size multiplier).",
+    )
+
+    parser.add_argument(
+        "-d",
+        "--denoising-steps",
+        type=int,
+        default=None,
+        help="Number of denoising steps" + (" in base." if is_xl else "."),
+    )
+
+    parser.add_argument(
+        "-g",
+        "--guidance",
+        type=float,
+        default=None,
+        help="Higher guidance scale encourages to generate images that are closely linked to the text prompt.",
+    )
+
+    parser.add_argument(
+        "-ls", "--lora-scale", type=float, default=1, help="Scale of LoRA weights, default 1 (must between 0 and 1)"
+    )
+    parser.add_argument("-lw", "--lora-weights", type=str, default="", help="LoRA weights to apply in the base model")
+
+    if is_xl:
+        parser.add_argument(
+            "--lcm",
+            action="store_true",
+            help="Use fine-tuned latent consistency model to replace the UNet in base.",
+        )
+
+        parser.add_argument(
+            "-rs",
+            "--refiner-scheduler",
+            type=str,
+            default="EulerA",
+            choices=["DDIM", "EulerA", "UniPC"],
+            help="Scheduler for diffusion process of refiner.",
+        )
+
+        parser.add_argument(
+            "-rg",
+            "--refiner-guidance",
+            type=float,
+            default=5.0,
+            help="Guidance scale used in refiner.",
+        )
+
+        parser.add_argument(
+            "-rd",
+            "--refiner-denoising-steps",
+            type=int,
+            default=30,
+            help="Number of denoising steps in refiner. Note that actual steps is refiner_denoising_steps * strength.",
+        )
+
+        parser.add_argument(
+            "--strength",
+            type=float,
+            default=0.3,
+            help="A value between 0 and 1. The higher the value less the final image similar to the seed image.",
+        )
+
+        parser.add_argument(
+            "-r",
+            "--enable-refiner",
+            action="store_true",
+            help="Enable SDXL refiner to refine image from base pipeline.",
+        )
+
+    # ONNX export
+    parser.add_argument(
+        "--onnx-opset",
+        type=int,
+        default=None,
+        choices=range(14, 18),
+        help="Select ONNX opset version to target for exported models.",
+    )
+
+    # Engine build options.
+    parser.add_argument(
+        "-db",
+        "--build-dynamic-batch",
+        action="store_true",
+        help="Build TensorRT engines to support dynamic batch size.",
+    )
+    parser.add_argument(
+        "-ds",
+        "--build-dynamic-shape",
+        action="store_true",
+        help="Build TensorRT engines to support dynamic image sizes.",
+    )
+    parser.add_argument("--max-batch-size", type=int, default=None, choices=[1, 2, 4, 8, 16, 32], help="Max batch size")
+
+    # Inference related options
+    parser.add_argument(
+        "-nw", "--num-warmup-runs", type=int, default=5, help="Number of warmup runs before benchmarking performance."
+    )
+    parser.add_argument("--nvtx-profile", action="store_true", help="Enable NVTX markers for performance profiling.")
+    parser.add_argument("--seed", type=int, default=None, help="Seed for random generator to get consistent results.")
+    parser.add_argument("--deterministic", action="store_true", help="use deterministic algorithms.")
+    parser.add_argument("-dc", "--disable-cuda-graph", action="store_true", help="Disable cuda graph.")
+
+    parser.add_argument("--framework-model-dir", default=None, help="framework model directory")
+
+    group = parser.add_argument_group("Options for ORT_CUDA engine only")
+    group.add_argument("--enable-vae-slicing", action="store_true", help="True will feed only one image to VAE once.")
+    group.add_argument("--max-cuda-graphs", type=int, default=1, help="Max number of cuda graphs to use. Default 1.")
+    group.add_argument("--user-compute-stream", action="store_true", help="Use user compute stream.")
+
+    # TensorRT only options
+    group = parser.add_argument_group("Options for TensorRT (--engine=TRT) only")
+    group.add_argument(
+        "--build-all-tactics", action="store_true", help="Build TensorRT engines using all tactic sources."
+    )
+
+    args = parser.parse_args()
+
+    set_default_arguments(args)
+
+    # Validate image dimensions
+    if args.height % 64 != 0 or args.width % 64 != 0:
+        raise ValueError(
+            f"Image height and width have to be divisible by 64 but specified as: {args.height} and {args.width}."
+        )
+
+    if (args.build_dynamic_batch or args.build_dynamic_shape) and not args.disable_cuda_graph:
+        print("[I] CUDA Graph is disabled since dynamic input shape is configured.")
+        args.disable_cuda_graph = True
+
+    if args.onnx_opset is None:
+        args.onnx_opset = 14 if args.engine == "ORT_CUDA" else 17
+
+    if is_xl:
+        if args.version == "xl-turbo":
+            if args.lcm:
+                print("[I] sdxl-turbo cannot use with LCM.")
+                args.lcm = False
+
+        assert args.strength > 0.0 and args.strength < 1.0
+
+        assert not (args.lcm and args.lora_weights), "it is not supported to use both lcm unet and Lora together"
+
+    if args.scheduler == "LCM":
+        if args.guidance > 2.0:
+            print("[I] Use --guidance=0.0 (no more than 2.0) when LCM scheduler is used.")
+            args.guidance = 0.0
+        if args.denoising_steps > 16:
+            print("[I] Use --denoising_steps=8 (no more than 16) when LCM scheduler is used.")
+            args.denoising_steps = 8
+
+    print(args)
+
+    return args
+
+
+def max_batch(args):
+    if args.max_batch_size:
+        max_batch_size = args.max_batch_size
+    else:
+        do_classifier_free_guidance = args.guidance > 1.0
+        batch_multiplier = 2 if do_classifier_free_guidance else 1
+        max_batch_size = 32 // batch_multiplier
+        if args.engine != "ORT_CUDA" and (args.build_dynamic_shape or args.height > 512 or args.width > 512):
+            max_batch_size = 8 // batch_multiplier
+    return max_batch_size
+
+
+def get_metadata(args, is_xl: bool = False) -> dict[str, Any]:
+    metadata = {
+        "command": " ".join(['"' + x + '"' if " " in x else x for x in sys.argv]),
+        "args.prompt": args.prompt,
+        "args.negative_prompt": args.negative_prompt,
+        "args.batch_size": args.batch_size,
+        "height": args.height,
+        "width": args.width,
+        "cuda_graph": not args.disable_cuda_graph,
+        "vae_slicing": args.enable_vae_slicing,
+        "engine": args.engine,
+    }
+
+    if args.lora_weights:
+        metadata["lora_weights"] = args.lora_weights
+        metadata["lora_scale"] = args.lora_scale
+
+    if args.controlnet_type:
+        metadata["controlnet_type"] = args.controlnet_type
+        metadata["controlnet_scale"] = args.controlnet_scale
+
+    if is_xl and args.enable_refiner:
+        metadata["base.scheduler"] = args.scheduler
+        metadata["base.denoising_steps"] = args.denoising_steps
+        metadata["base.guidance"] = args.guidance
+        metadata["refiner.strength"] = args.strength
+        metadata["refiner.scheduler"] = args.refiner_scheduler
+        metadata["refiner.denoising_steps"] = args.refiner_denoising_steps
+        metadata["refiner.guidance"] = args.refiner_guidance
+    else:
+        metadata["scheduler"] = args.scheduler
+        metadata["denoising_steps"] = args.denoising_steps
+        metadata["guidance"] = args.guidance
+
+    # Version of installed python packages
+    packages = ""
+    for name in [
+        "onnxruntime-gpu",
+        "torch",
+        "tensorrt",
+        "transformers",
+        "diffusers",
+        "onnx",
+        "onnx-graphsurgeon",
+        "polygraphy",
+        "controlnet_aux",
+    ]:
+        try:
+            packages += (" " if packages else "") + f"{name}=={version(name)}"
+        except PackageNotFoundError:
+            continue
+    metadata["packages"] = packages
+    metadata["device"] = torch.cuda.get_device_name()
+    metadata["torch.version.cuda"] = torch.version.cuda
+
+    return metadata
+
+
+def repeat_prompt(args):
+    if not isinstance(args.prompt, list):
+        raise ValueError(f"`prompt` must be of type `str` or `str` list, but is {type(args.prompt)}")
+    prompt = args.prompt * args.batch_size
+
+    if not isinstance(args.negative_prompt, list):
+        raise ValueError(
+            f"`--negative-prompt` must be of type `str` or `str` list, but is {type(args.negative_prompt)}"
+        )
+
+    if len(args.negative_prompt) == 1:
+        negative_prompt = args.negative_prompt * len(prompt)
+    else:
+        negative_prompt = args.negative_prompt
+
+    return prompt, negative_prompt
+
+
+def initialize_pipeline(
+    version="xl-turbo",
+    is_refiner: bool = False,
+    is_inpaint: bool = False,
+    engine_type=EngineType.ORT_CUDA,
+    work_dir: str = ".",
+    engine_dir=None,
+    onnx_opset: int = 17,
+    scheduler="EulerA",
+    height=512,
+    width=512,
+    nvtx_profile=False,
+    use_cuda_graph=True,
+    build_dynamic_batch=False,
+    build_dynamic_shape=False,
+    min_image_size: int = 512,
+    max_image_size: int = 1024,
+    max_batch_size: int = 16,
+    opt_batch_size: int = 1,
+    build_all_tactics: bool = False,
+    do_classifier_free_guidance: bool = False,
+    lcm: bool = False,
+    controlnet=None,
+    lora_weights=None,
+    lora_scale: float = 1.0,
+    use_fp16_vae: bool = True,
+    use_vae: bool = True,
+    framework_model_dir: str | None = None,
+    max_cuda_graphs: int = 1,
+):
+    pipeline_info = PipelineInfo(
+        version,
+        is_refiner=is_refiner,
+        is_inpaint=is_inpaint,
+        use_vae=use_vae,
+        min_image_size=min_image_size,
+        max_image_size=max_image_size,
+        use_fp16_vae=use_fp16_vae,
+        use_lcm=lcm,
+        do_classifier_free_guidance=do_classifier_free_guidance,
+        controlnet=controlnet,
+        lora_weights=lora_weights,
+        lora_scale=lora_scale,
+    )
+
+    input_engine_dir = engine_dir
+
+    onnx_dir, engine_dir, output_dir, framework_model_dir, timing_cache = get_engine_paths(
+        work_dir=work_dir, pipeline_info=pipeline_info, engine_type=engine_type, framework_model_dir=framework_model_dir
+    )
+
+    pipeline = StableDiffusionPipeline(
+        pipeline_info,
+        scheduler=scheduler,
+        output_dir=output_dir,
+        verbose=False,
+        nvtx_profile=nvtx_profile,
+        max_batch_size=max_batch_size,
+        use_cuda_graph=use_cuda_graph,
+        framework_model_dir=framework_model_dir,
+        engine_type=engine_type,
+    )
+
+    import_engine_dir = None
+    if input_engine_dir:
+        if not os.path.exists(input_engine_dir):
+            raise RuntimeError(f"--engine_dir directory does not exist: {input_engine_dir}")
+
+        # Support importing from optimized diffusers onnx pipeline
+        if engine_type == EngineType.ORT_CUDA and os.path.exists(os.path.join(input_engine_dir, "model_index.json")):
+            import_engine_dir = input_engine_dir
+        else:
+            engine_dir = input_engine_dir
+
+    opt_image_height = pipeline_info.default_image_size() if build_dynamic_shape else height
+    opt_image_width = pipeline_info.default_image_size() if build_dynamic_shape else width
+
+    if engine_type == EngineType.ORT_CUDA:
+        pipeline.backend.build_engines(
+            engine_dir=engine_dir,
+            framework_model_dir=framework_model_dir,
+            onnx_dir=onnx_dir,
+            tmp_dir=os.path.join(work_dir or ".", engine_type.name, pipeline_info.short_name(), "tmp"),
+            device_id=torch.cuda.current_device(),
+            import_engine_dir=import_engine_dir,
+            max_cuda_graphs=max_cuda_graphs,
+        )
+    elif engine_type == EngineType.ORT_TRT:
+        pipeline.backend.build_engines(
+            engine_dir,
+            framework_model_dir,
+            onnx_dir,
+            onnx_opset,
+            opt_image_height=opt_image_height,
+            opt_image_width=opt_image_width,
+            opt_batch_size=opt_batch_size,
+            static_batch=not build_dynamic_batch,
+            static_image_shape=not build_dynamic_shape,
+            max_workspace_size=0,
+            device_id=torch.cuda.current_device(),
+            timing_cache=timing_cache,
+        )
+    elif engine_type == EngineType.TRT:
+        pipeline.backend.load_engines(
+            engine_dir,
+            framework_model_dir,
+            onnx_dir,
+            onnx_opset,
+            opt_batch_size=opt_batch_size,
+            opt_image_height=opt_image_height,
+            opt_image_width=opt_image_width,
+            static_batch=not build_dynamic_batch,
+            static_shape=not build_dynamic_shape,
+            enable_all_tactics=build_all_tactics,
+            timing_cache=timing_cache,
+        )
+    elif engine_type == EngineType.TORCH:
+        pipeline.backend.build_engines(framework_model_dir)
+    else:
+        raise RuntimeError("invalid engine type")
+
+    return pipeline
+
+
+def load_pipelines(args, batch_size=None):
+    engine_type = get_engine_type(args.engine)
+
+    # Register TensorRT plugins
+    if engine_type == EngineType.TRT:
+        from trt_utilities import init_trt_plugins  # noqa: PLC0415
+
+        init_trt_plugins()
+
+    max_batch_size = max_batch(args)
+
+    if batch_size is None:
+        assert isinstance(args.prompt, list)
+        batch_size = len(args.prompt) * args.batch_size
+
+    if batch_size > max_batch_size:
+        raise ValueError(f"Batch size {batch_size} is larger than allowed {max_batch_size}.")
+
+    # For TensorRT,  performance of engine built with dynamic shape is very sensitive to the range of image size.
+    # Here, we reduce the range of image size for TensorRT to trade-off flexibility and performance.
+    # This range can cover most frequent shape of landscape (832x1216), portrait (1216x832) or square (1024x1024).
+    if args.version == "xl-turbo":
+        min_image_size = 512
+        max_image_size = 768 if args.engine != "ORT_CUDA" else 1024
+    elif args.version == "xl-1.0":
+        min_image_size = 832 if args.engine != "ORT_CUDA" else 512
+        max_image_size = 1216 if args.engine != "ORT_CUDA" else 2048
+    else:
+        # This range can cover common used shape of landscape 512x768, portrait 768x512, or square 512x512 and 768x768.
+        min_image_size = 512 if args.engine != "ORT_CUDA" else 256
+        max_image_size = 768 if args.engine != "ORT_CUDA" else 1024
+
+    params = {
+        "version": args.version,
+        "is_refiner": False,
+        "is_inpaint": False,
+        "engine_type": engine_type,
+        "work_dir": args.work_dir,
+        "engine_dir": args.engine_dir,
+        "onnx_opset": args.onnx_opset,
+        "scheduler": args.scheduler,
+        "height": args.height,
+        "width": args.width,
+        "nvtx_profile": args.nvtx_profile,
+        "use_cuda_graph": not args.disable_cuda_graph,
+        "build_dynamic_batch": args.build_dynamic_batch,
+        "build_dynamic_shape": args.build_dynamic_shape,
+        "min_image_size": min_image_size,
+        "max_image_size": max_image_size,
+        "max_batch_size": max_batch_size,
+        "opt_batch_size": 1 if args.build_dynamic_batch else batch_size,
+        "build_all_tactics": args.build_all_tactics,
+        "do_classifier_free_guidance": args.guidance > 1.0,
+        "controlnet": args.controlnet_type,
+        "lora_weights": args.lora_weights,
+        "lora_scale": args.lora_scale,
+        "use_fp16_vae": "xl" in args.version,
+        "use_vae": True,
+        "framework_model_dir": args.framework_model_dir,
+        "max_cuda_graphs": args.max_cuda_graphs,
+    }
+
+    if "xl" in args.version:
+        params["lcm"] = args.lcm
+        params["use_vae"] = not args.enable_refiner
+    base = initialize_pipeline(**params)
+
+    refiner = None
+    if "xl" in args.version and args.enable_refiner:
+        params["version"] = "xl-1.0"  # Allow SDXL Turbo to use refiner.
+        params["is_refiner"] = True
+        params["scheduler"] = args.refiner_scheduler
+        params["do_classifier_free_guidance"] = args.refiner_guidance > 1.0
+        params["lcm"] = False
+        params["controlnet"] = None
+        params["lora_weights"] = None
+        params["use_vae"] = True
+        params["use_fp16_vae"] = True
+        refiner = initialize_pipeline(**params)
+
+    if engine_type == EngineType.TRT:
+        max_device_memory = max(base.backend.max_device_memory(), (refiner or base).backend.max_device_memory())
+        _, shared_device_memory = cudart.cudaMalloc(max_device_memory)
+        base.backend.activate_engines(shared_device_memory)
+        if refiner:
+            refiner.backend.activate_engines(shared_device_memory)
+
+    if engine_type == EngineType.ORT_CUDA:
+        enable_vae_slicing = args.enable_vae_slicing
+        if batch_size > 4 and not enable_vae_slicing and (args.height >= 1024 and args.width >= 1024):
+            print(
+                "Updating enable_vae_slicing to be True to avoid cuDNN error for batch size > 4 and resolution >= 1024."
+            )
+            enable_vae_slicing = True
+        if enable_vae_slicing:
+            (refiner or base).backend.enable_vae_slicing()
+    return base, refiner
+
+
+def get_depth_image(image):
+    """
+    Create depth map for SDXL depth control net.
+    """
+    from transformers import DPTFeatureExtractor, DPTForDepthEstimation  # noqa: PLC0415
+
+    depth_estimator = DPTForDepthEstimation.from_pretrained("Intel/dpt-hybrid-midas").to("cuda")
+    feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-hybrid-midas")
+
+    image = feature_extractor(images=image, return_tensors="pt").pixel_values.to("cuda")
+    with torch.no_grad(), torch.autocast("cuda"):
+        depth_map = depth_estimator(image).predicted_depth
+
+    # The depth map is 384x384 by default, here we interpolate to the default output size.
+    # Note that it will be resized to output image size later. May change the size here to avoid interpolate twice.
+    depth_map = torch.nn.functional.interpolate(
+        depth_map.unsqueeze(1),
+        size=(1024, 1024),
+        mode="bicubic",
+        align_corners=False,
+    )
+    depth_min = torch.amin(depth_map, dim=[1, 2, 3], keepdim=True)
+    depth_max = torch.amax(depth_map, dim=[1, 2, 3], keepdim=True)
+    depth_map = (depth_map - depth_min) / (depth_max - depth_min)
+    image = torch.cat([depth_map] * 3, dim=1)
+
+    image = image.permute(0, 2, 3, 1).cpu().numpy()[0]
+    image = Image.fromarray((image * 255.0).clip(0, 255).astype(np.uint8))
+    return image
+
+
+def get_canny_image(image) -> Image.Image:
+    """
+    Create canny image for SDXL control net.
+    """
+    image = np.array(image)
+    image = cv2.Canny(image, 100, 200)
+    image = image[:, :, None]
+    image = np.concatenate([image, image, image], axis=2)
+    image = Image.fromarray(image)
+    return image
+
+
+def process_controlnet_images_xl(args) -> list[Image.Image]:
+    """
+    Process control image for SDXL control net.
+    """
+    assert len(args.controlnet_image) == 1
+    image = Image.open(args.controlnet_image[0]).convert("RGB")
+
+    controlnet_images = []
+    if args.controlnet_type[0] == "canny":
+        controlnet_images.append(get_canny_image(image))
+    elif args.controlnet_type[0] == "depth":
+        controlnet_images.append(get_depth_image(image))
+    else:
+        raise ValueError(f"This controlnet type is not supported for SDXL or Turbo: {args.controlnet_type}.")
+
+    return controlnet_images
+
+
+def add_controlnet_arguments(parser, is_xl: bool = False):
+    """
+    Add control net related arguments.
+    """
+    group = parser.add_argument_group("Options for ControlNet (supports 1.5, sd-turbo, xl-turbo, xl-1.0).")
+
+    group.add_argument(
+        "-ci",
+        "--controlnet-image",
+        nargs="*",
+        type=str,
+        default=[],
+        help="Path to the input regular RGB image/images for controlnet",
+    )
+    group.add_argument(
+        "-ct",
+        "--controlnet-type",
+        nargs="*",
+        type=str,
+        default=[],
+        choices=list(PipelineInfo.supported_controlnet("xl-1.0" if is_xl else "1.5").keys()),
+        help="A list of controlnet type",
+    )
+    group.add_argument(
+        "-cs",
+        "--controlnet-scale",
+        nargs="*",
+        type=float,
+        default=[],
+        help="The outputs of the controlnet are multiplied by `controlnet_scale` before they are added to the residual in the original unet. Default is 0.5 for SDXL, or 1.0 for SD 1.5",
+    )
+
+
+def process_controlnet_image(controlnet_type: str, image: Image.Image, height, width):
+    """
+    Process control images of control net v1.1 for Stable Diffusion 1.5.
+    """
+    control_image = None
+    shape = (height, width)
+    image = image.convert("RGB")
+    if controlnet_type == "canny":
+        canny_image = controlnet_aux.CannyDetector()(image)
+        control_image = canny_image.resize(shape)
+    elif controlnet_type == "normalbae":
+        normal_image = controlnet_aux.NormalBaeDetector.from_pretrained("lllyasviel/Annotators")(image)
+        control_image = normal_image.resize(shape)
+    elif controlnet_type == "depth":
+        depth_image = controlnet_aux.LeresDetector.from_pretrained("lllyasviel/Annotators")(image)
+        control_image = depth_image.resize(shape)
+    elif controlnet_type == "mlsd":
+        mlsd_image = controlnet_aux.MLSDdetector.from_pretrained("lllyasviel/Annotators")(image)
+        control_image = mlsd_image.resize(shape)
+    elif controlnet_type == "openpose":
+        openpose_image = controlnet_aux.OpenposeDetector.from_pretrained("lllyasviel/Annotators")(image)
+        control_image = openpose_image.resize(shape)
+    elif controlnet_type == "scribble":
+        scribble_image = controlnet_aux.HEDdetector.from_pretrained("lllyasviel/Annotators")(image, scribble=True)
+        control_image = scribble_image.resize(shape)
+    elif controlnet_type == "seg":
+        seg_image = controlnet_aux.SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")(
+            image
+        )
+        control_image = seg_image.resize(shape)
+    else:
+        raise ValueError(f"There is no demo image of this controlnet_type: {controlnet_type}")
+    return control_image
+
+
+def process_controlnet_arguments(args):
+    """
+    Process control net arguments, and returns a list of control images and a tensor of control net scales.
+    """
+    assert isinstance(args.controlnet_type, list)
+    assert isinstance(args.controlnet_scale, list)
+    assert isinstance(args.controlnet_image, list)
+
+    if len(args.controlnet_image) != len(args.controlnet_type):
+        raise ValueError(
+            f"Numbers of controlnet_image {len(args.controlnet_image)} should be equal to number of controlnet_type {len(args.controlnet_type)}."
+        )
+
+    if len(args.controlnet_type) == 0:
+        return None, None
+
+    if args.version not in ["1.5", "xl-1.0", "xl-turbo", "sd-turbo"]:
+        raise ValueError("This demo only supports ControlNet in Stable Diffusion 1.5, XL or Turbo.")
+
+    is_xl = "xl" in args.version
+    if is_xl and len(args.controlnet_type) > 1:
+        raise ValueError("This demo only support one ControlNet for Stable Diffusion XL or Turbo.")
+
+    if len(args.controlnet_scale) == 0:
+        args.controlnet_scale = [0.5 if is_xl else 1.0] * len(args.controlnet_type)
+    elif len(args.controlnet_type) != len(args.controlnet_scale):
+        raise ValueError(
+            f"Numbers of controlnet_type {len(args.controlnet_type)} should be equal to number of controlnet_scale {len(args.controlnet_scale)}."
+        )
+
+    # Convert controlnet scales to tensor
+    controlnet_scale = torch.FloatTensor(args.controlnet_scale)
+
+    if is_xl:
+        images = process_controlnet_images_xl(args)
+    else:
+        images = []
+        for i, image in enumerate(args.controlnet_image):
+            images.append(process_controlnet_image(args.controlnet_type[i], Image.open(image), args.height, args.width))
+
+    return images, controlnet_scale
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_models.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_models.py
new file mode 100644
index 0000000000000000000000000000000000000000..302c6fe980c3f6e8d98896015c138669769dc605
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_models.py
@@ -0,0 +1,1318 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from stable_diffusion_tensorrt_txt2img.py in diffusers and TensorRT demo diffusion,
+# which has the following license:
+#
+# Copyright 2023 The HuggingFace Inc. team.
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import os
+import tempfile
+
+import onnx
+import onnx_graphsurgeon as gs
+import torch
+from diffusers.models import AutoencoderKL, ControlNetModel, UNet2DConditionModel
+from onnx import GraphProto, ModelProto, shape_inference
+from ort_optimizer import OrtStableDiffusionOptimizer
+from polygraphy.backend.onnx.loader import fold_constants
+from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
+
+from onnxruntime.transformers.onnx_model import OnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class TrtOptimizer:
+    def __init__(self, onnx_graph):
+        self.graph = gs.import_onnx(onnx_graph)
+
+    def cleanup(self):
+        self.graph.cleanup().toposort()
+
+    def get_optimized_onnx_graph(self):
+        return gs.export_onnx(self.graph)
+
+    def select_outputs(self, keep, names=None):
+        self.graph.outputs = [self.graph.outputs[o] for o in keep]
+        if names:
+            for i, name in enumerate(names):
+                self.graph.outputs[i].name = name
+
+    def fold_constants(self):
+        onnx_graph = fold_constants(gs.export_onnx(self.graph), allow_onnxruntime_shape_inference=True)
+        self.graph = gs.import_onnx(onnx_graph)
+
+    def infer_shapes(self):
+        onnx_graph = gs.export_onnx(self.graph)
+        if onnx_graph.ByteSize() >= onnx.checker.MAXIMUM_PROTOBUF:
+            with tempfile.TemporaryDirectory() as temp_dir:
+                input_onnx_path = os.path.join(temp_dir, "model.onnx")
+                onnx.save_model(
+                    onnx_graph,
+                    input_onnx_path,
+                    save_as_external_data=True,
+                    all_tensors_to_one_file=True,
+                    convert_attribute=False,
+                )
+                output_onnx_path = os.path.join(temp_dir, "model_with_shape.onnx")
+                onnx.shape_inference.infer_shapes_path(input_onnx_path, output_onnx_path)
+                onnx_graph = onnx.load(output_onnx_path)
+        else:
+            onnx_graph = shape_inference.infer_shapes(onnx_graph)
+
+        self.graph = gs.import_onnx(onnx_graph)
+
+
+class PipelineInfo:
+    def __init__(
+        self,
+        version: str,
+        is_inpaint: bool = False,
+        is_refiner: bool = False,
+        use_vae=True,  # TODO: this has couple with output type of pipeline
+        min_image_size=256,
+        max_image_size=1024,
+        use_fp16_vae=True,
+        use_lcm=False,
+        do_classifier_free_guidance=True,
+        controlnet=None,
+        lora_weights=None,
+        lora_scale=1.0,
+    ):
+        self.version = version
+        self._is_inpaint = is_inpaint
+        self._is_refiner = is_refiner
+        self._use_vae = use_vae
+        self._min_image_size = min_image_size
+        self._max_image_size = max_image_size
+        self._use_fp16_vae = use_fp16_vae
+        self._use_lcm = use_lcm
+        self.do_classifier_free_guidance = do_classifier_free_guidance and not use_lcm
+        self.controlnet = controlnet  # A list of control net type
+        self.lora_weights = lora_weights
+        self.lora_scale = lora_scale
+
+        if is_refiner:
+            assert not use_lcm
+            assert self.is_xl()
+
+    def is_inpaint(self) -> bool:
+        return self._is_inpaint
+
+    def is_xl(self) -> bool:
+        return "xl" in self.version
+
+    def is_xl_turbo(self) -> bool:
+        return self.version == "xl-turbo"
+
+    def is_xl_base(self) -> bool:
+        return self.version == "xl-1.0" and not self._is_refiner
+
+    def is_xl_base_or_turbo(self) -> bool:
+        return self.is_xl_base() or self.is_xl_turbo()
+
+    def is_xl_refiner(self) -> bool:
+        return self.version == "xl-1.0" and self._is_refiner
+
+    def use_safetensors(self) -> bool:
+        return self.is_xl() or self.version in ["sd-turbo"]
+
+    def stages(self) -> list[str]:
+        if self.is_xl_base_or_turbo():
+            return ["clip", "clip2", "unetxl"] + (["vae"] if self._use_vae else [])
+
+        if self.is_xl_refiner():
+            return ["clip2", "unetxl", "vae"]
+
+        return ["clip", "unet", "vae"]
+
+    def vae_scaling_factor(self) -> float:
+        return 0.13025 if self.is_xl() else 0.18215
+
+    def vae_torch_fallback(self) -> bool:
+        return self.is_xl() and not self._use_fp16_vae
+
+    def custom_fp16_vae(self) -> str | None:
+        # For SD XL, use a VAE that fine-tuned to run in fp16 precision without generating NaNs
+        return "madebyollin/sdxl-vae-fp16-fix" if self._use_fp16_vae and self.is_xl() else None
+
+    def custom_unet(self) -> str | None:
+        return "latent-consistency/lcm-sdxl" if self._use_lcm and self.is_xl_base() else None
+
+    @staticmethod
+    def supported_versions(is_xl: bool):
+        return ["xl-1.0", "xl-turbo"] if is_xl else ["1.4", "1.5", "2.0-base", "2.0", "2.1", "2.1-base", "sd-turbo"]
+
+    @staticmethod
+    def supported_models():
+        return {
+            "CompVis/stable-diffusion-v1-4": "1.4",
+            "runwayml/stable-diffusion-v1-5": "1.5",
+            "stabilityai/stable-diffusion-2-base": "2.0-base",
+            "stabilityai/stable-diffusion-2": "2.0",
+            "stabilityai/stable-diffusion-2-1": "2.1",
+            "stabilityai/stable-diffusion-2-1-base": "2.1",
+            "stabilityai/stable-diffusion-xl-base-1.0": "xl-1.0",
+            "stabilityai/stable-diffusion-xl-refiner-1.0": "xl-1.0",
+            "stabilityai/sdxl-turbo": "xl-turbo",
+            "stabilityai/sd-turbo": "sd-turbo",
+            # "runwayml/stable-diffusion-inpainting": "1.5",
+            # "stabilityai/stable-diffusion-2-inpainting": "2.0",
+        }
+
+    def name(self) -> str:
+        if self.version == "1.4":
+            if self.is_inpaint():
+                return "runwayml/stable-diffusion-inpainting"
+            else:
+                return "CompVis/stable-diffusion-v1-4"
+        elif self.version == "1.5":
+            if self.is_inpaint():
+                return "runwayml/stable-diffusion-inpainting"
+            else:
+                return "runwayml/stable-diffusion-v1-5"
+        elif self.version == "2.0-base":
+            if self.is_inpaint():
+                return "stabilityai/stable-diffusion-2-inpainting"
+            else:
+                return "stabilityai/stable-diffusion-2-base"
+        elif self.version == "2.0":
+            if self.is_inpaint():
+                return "stabilityai/stable-diffusion-2-inpainting"
+            else:
+                return "stabilityai/stable-diffusion-2"
+        elif self.version == "2.1":
+            return "stabilityai/stable-diffusion-2-1"
+        elif self.version == "2.1-base":
+            return "stabilityai/stable-diffusion-2-1-base"
+        elif self.version == "xl-1.0":
+            if self.is_xl_refiner():
+                return "stabilityai/stable-diffusion-xl-refiner-1.0"
+            else:
+                return "stabilityai/stable-diffusion-xl-base-1.0"
+        elif self.version == "xl-turbo":
+            return "stabilityai/sdxl-turbo"
+        elif self.version == "sd-turbo":
+            return "stabilityai/sd-turbo"
+
+        raise ValueError(f"Incorrect version {self.version}")
+
+    def short_name(self) -> str:
+        return self.name().split("/")[-1].replace("stable-diffusion", "sd")
+
+    def clip_embedding_dim(self):
+        # TODO: can we read from config instead
+        if self.version in ("1.4", "1.5"):
+            return 768
+        elif self.version in ("2.0", "2.0-base", "2.1", "2.1-base", "sd-turbo"):
+            return 1024
+        elif self.is_xl_base_or_turbo():
+            return 768
+        else:
+            raise ValueError(f"Invalid version {self.version}")
+
+    def clipwithproj_embedding_dim(self):
+        if self.is_xl():
+            return 1280
+        else:
+            raise ValueError(f"Invalid version {self.version}")
+
+    def unet_embedding_dim(self):
+        if self.version in ("1.4", "1.5"):
+            return 768
+        elif self.version in ("2.0", "2.0-base", "2.1", "2.1-base", "sd-turbo"):
+            return 1024
+        elif self.is_xl_base_or_turbo():
+            return 2048
+        elif self.is_xl_refiner():
+            return 1280
+        else:
+            raise ValueError(f"Invalid version {self.version}")
+
+    def min_image_size(self):
+        return self._min_image_size
+
+    def max_image_size(self):
+        return self._max_image_size
+
+    @staticmethod
+    def default_resolution(version: str) -> int:
+        if version == "xl-1.0":
+            return 1024
+        if version in ("2.0", "2.1"):
+            return 768
+        return 512
+
+    def default_image_size(self) -> int:
+        return PipelineInfo.default_resolution(self.version)
+
+    @staticmethod
+    def supported_controlnet(version="1.5"):
+        if version in ("xl-1.0", "xl-turbo"):
+            return {
+                "canny": "diffusers/controlnet-canny-sdxl-1.0",
+                "depth": "diffusers/controlnet-depth-sdxl-1.0",
+            }
+        elif version == "1.5":
+            return {
+                "canny": "lllyasviel/control_v11p_sd15_canny",
+                "depth": "lllyasviel/control_v11f1p_sd15_depth",
+                "openpose": "lllyasviel/control_v11p_sd15_openpose",
+                # "tile": "lllyasviel/control_v11f1e_sd15_tile",
+                # "lineart": "lllyasviel/control_v11p_sd15_lineart",
+                # "inpaint": "lllyasviel/control_v11p_sd15_inpaint",
+                # "softedge": "lllyasviel/control_v11p_sd15_softedge",
+                "mlsd": "lllyasviel/control_v11p_sd15_mlsd",
+                "scribble": "lllyasviel/control_v11p_sd15_scribble",
+                # "ip2p": "lllyasviel/control_v11e_sd15_ip2p",
+                "normalbae": "lllyasviel/control_v11p_sd15_normalbae",
+                "seg": "lllyasviel/control_v11p_sd15_seg",
+                # "shuffle": "lllyasviel/control_v11e_sd15_shuffle",
+                # "lineart_anime": "lllyasviel/control_v11p_sd15s2_lineart_anime",
+            }
+        return None
+
+    def controlnet_name(self):
+        """Return a list of controlnet name"""
+        if not self.controlnet:
+            return None
+        controlnet_map = PipelineInfo.supported_controlnet(self.version)
+        if controlnet_map is None:
+            return None
+        return [controlnet_map[controlnet] for controlnet in self.controlnet]
+
+
+class BaseModel:
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        fp16: bool = False,
+        max_batch_size: int = 16,
+        embedding_dim: int = 768,
+        text_maxlen: int = 77,
+    ):
+        self.name = self.__class__.__name__
+
+        self.pipeline_info = pipeline_info
+
+        self.model = model
+        self.fp16 = fp16
+        self.device = device
+
+        self.min_batch = 1
+        self.max_batch = max_batch_size
+        self.min_image_shape = pipeline_info.min_image_size()
+        self.max_image_shape = pipeline_info.max_image_size()
+        self.min_latent_shape = self.min_image_shape // 8
+        self.max_latent_shape = self.max_image_shape // 8
+
+        self.embedding_dim = embedding_dim
+        self.text_maxlen = text_maxlen
+
+    def get_batch_multiplier(self):
+        return 2 if self.pipeline_info.do_classifier_free_guidance else 1
+
+    def get_ort_optimizer(self):
+        model_name_to_model_type = {
+            "CLIP": "clip",
+            "UNet": "unet",
+            "VAE": "vae",
+            "UNetXL": "unet",
+            "CLIPWithProj": "clip",
+        }
+        model_type = model_name_to_model_type[self.name]
+        return OrtStableDiffusionOptimizer(model_type)
+
+    def get_model(self):
+        return self.model
+
+    def from_pretrained(self, model_class, framework_model_dir, subfolder=None, model_name=None, **kwargs):
+        if model_name is None:
+            model_name = self.pipeline_info.name()
+
+        if subfolder:
+            model_dir = os.path.join(framework_model_dir, model_name, subfolder)
+        else:
+            model_dir = os.path.join(framework_model_dir, model_name)
+
+        if not os.path.exists(model_dir):
+            model = model_class.from_pretrained(
+                model_name,
+                subfolder=subfolder,
+                use_safetensors=self.pipeline_info.use_safetensors(),
+                **kwargs,
+            ).to(self.device)
+            model.save_pretrained(model_dir)
+        else:
+            print(f"Load {self.name} pytorch model from: {model_dir}")
+
+            model = model_class.from_pretrained(model_dir).to(self.device)
+        return model
+
+    def load_model(self, framework_model_dir: str, subfolder: str):
+        pass
+
+    def get_input_names(self) -> list[str]:
+        pass
+
+    def get_output_names(self) -> list[str]:
+        pass
+
+    def get_dynamic_axes(self) -> dict[str, dict[int, str]]:
+        pass
+
+    def get_sample_input(self, batch_size, image_height, image_width) -> tuple:
+        pass
+
+    def get_profile_id(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        """For TensorRT EP"""
+        (
+            min_batch,
+            max_batch,
+            min_image_height,
+            max_image_height,
+            min_image_width,
+            max_image_width,
+            _,
+            _,
+            _,
+            _,
+        ) = self.get_minmax_dims(batch_size, image_height, image_width, static_batch, static_image_shape)
+
+        if (self.name in ["UNet", "UNetXL"]) and (self.get_batch_multiplier() == 1):
+            profile_id = f"_b1_{batch_size}" if static_batch else f"_b1_{min_batch}_{max_batch}"
+        else:
+            profile_id = f"_b_{batch_size}" if static_batch else f"_b_{min_batch}_{max_batch}"
+
+        if self.name != "CLIP":
+            if static_image_shape:
+                profile_id += f"_h_{image_height}_w_{image_width}"
+            else:
+                profile_id += f"_h_{min_image_height}_{max_image_height}_w_{min_image_width}_{max_image_width}"
+
+        return profile_id
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        """For TensorRT"""
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        pass
+
+    def fp32_input_output_names(self) -> list[str]:
+        """For CUDA EP, we export ONNX model with FP32 first, then convert it to mixed precision model.
+        This is a list of input or output names that are kept as float32 in optimized model.
+        """
+        return []
+
+    def optimize_ort(
+        self,
+        input_onnx_path,
+        optimized_onnx_path,
+        to_fp16=True,
+        fp32_op_list=None,
+        optimize_by_ort=True,
+        optimize_by_fusion=True,
+        tmp_dir=None,
+    ):
+        optimizer = self.get_ort_optimizer()
+        optimizer.optimize(
+            input_onnx_path,
+            optimized_onnx_path,
+            float16=to_fp16,
+            keep_io_types=self.fp32_input_output_names(),
+            fp32_op_list=fp32_op_list,
+            optimize_by_ort=optimize_by_ort,
+            optimize_by_fusion=optimize_by_fusion,
+            tmp_dir=tmp_dir,
+        )
+
+    def optimize_trt(self, input_onnx_path, optimized_onnx_path):
+        onnx_graph = onnx.load(input_onnx_path)
+        opt = TrtOptimizer(onnx_graph)
+        opt.cleanup()
+        opt.fold_constants()
+        opt.infer_shapes()
+        opt.cleanup()
+        onnx_opt_graph = opt.get_optimized_onnx_graph()
+
+        if onnx_opt_graph.ByteSize() > onnx.checker.MAXIMUM_PROTOBUF:
+            onnx.save_model(
+                onnx_opt_graph,
+                optimized_onnx_path,
+                save_as_external_data=True,
+                all_tensors_to_one_file=True,
+                convert_attribute=False,
+            )
+        else:
+            onnx.save(onnx_opt_graph, optimized_onnx_path)
+
+    def check_dims(self, batch_size, image_height, image_width):
+        assert batch_size >= self.min_batch and batch_size <= self.max_batch
+        assert image_height % 8 == 0 or image_width % 8 == 0
+        latent_height = image_height // 8
+        latent_width = image_width // 8
+        assert latent_height >= self.min_latent_shape and latent_height <= self.max_latent_shape
+        assert latent_width >= self.min_latent_shape and latent_width <= self.max_latent_shape
+        return (latent_height, latent_width)
+
+    def get_minmax_dims(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        min_batch = batch_size if static_batch else self.min_batch
+        max_batch = batch_size if static_batch else self.max_batch
+        latent_height = image_height // 8
+        latent_width = image_width // 8
+        min_image_height = image_height if static_image_shape else self.min_image_shape
+        max_image_height = image_height if static_image_shape else self.max_image_shape
+        min_image_width = image_width if static_image_shape else self.min_image_shape
+        max_image_width = image_width if static_image_shape else self.max_image_shape
+        min_latent_height = latent_height if static_image_shape else self.min_latent_shape
+        max_latent_height = latent_height if static_image_shape else self.max_latent_shape
+        min_latent_width = latent_width if static_image_shape else self.min_latent_shape
+        max_latent_width = latent_width if static_image_shape else self.max_latent_shape
+        return (
+            min_batch,
+            max_batch,
+            min_image_height,
+            max_image_height,
+            min_image_width,
+            max_image_width,
+            min_latent_height,
+            max_latent_height,
+            min_latent_width,
+            max_latent_width,
+        )
+
+
+class CLIP(BaseModel):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        max_batch_size,
+        embedding_dim: int = 0,
+        clip_skip=0,
+    ):
+        super().__init__(
+            pipeline_info,
+            model=model,
+            device=device,
+            max_batch_size=max_batch_size,
+            embedding_dim=embedding_dim if embedding_dim > 0 else pipeline_info.clip_embedding_dim(),
+        )
+        self.output_hidden_state = pipeline_info.is_xl()
+
+        # see https://github.com/huggingface/diffusers/pull/5057 for more information of clip_skip.
+        # Clip_skip=1 means that the output of the pre-final layer will be used for computing the prompt embeddings.
+        self.clip_skip = clip_skip
+
+    def get_input_names(self):
+        return ["input_ids"]
+
+    def get_output_names(self):
+        # The exported onnx model has no hidden_state. For SD-XL, We will add hidden_state to optimized onnx model.
+        return ["text_embeddings"]
+
+    def get_dynamic_axes(self):
+        return {"input_ids": {0: "B", 1: "S"}, "text_embeddings": {0: "B", 1: "S"}}
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        self.check_dims(batch_size, image_height, image_width)
+        min_batch, max_batch, _, _, _, _, _, _, _, _ = self.get_minmax_dims(
+            batch_size, image_height, image_width, static_batch, static_image_shape
+        )
+        return {
+            "input_ids": [(min_batch, self.text_maxlen), (batch_size, self.text_maxlen), (max_batch, self.text_maxlen)]
+        }
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        self.check_dims(batch_size, image_height, image_width)
+        output = {
+            "input_ids": (batch_size, self.text_maxlen),
+            "text_embeddings": (batch_size, self.text_maxlen, self.embedding_dim),
+        }
+
+        if self.output_hidden_state:
+            output["hidden_states"] = (batch_size, self.text_maxlen, self.embedding_dim)
+
+        return output
+
+    def get_sample_input(self, batch_size, image_height, image_width):
+        self.check_dims(batch_size, image_height, image_width)
+        return (torch.zeros(batch_size, self.text_maxlen, dtype=torch.int32, device=self.device),)
+
+    def add_hidden_states_graph_output(self, model: ModelProto, optimized_onnx_path, use_external_data_format=False):
+        graph: GraphProto = model.graph
+        hidden_layers = -1
+        for i in range(len(graph.node)):
+            for j in range(len(graph.node[i].output)):
+                name = graph.node[i].output[j]
+                if "layers" in name:
+                    hidden_layers = max(int(name.split(".")[1].split("/")[0]), hidden_layers)
+
+        assert self.clip_skip >= 0 and self.clip_skip < hidden_layers
+
+        node_output_name = f"/text_model/encoder/layers.{hidden_layers - 1 - self.clip_skip}/Add_1_output_0"
+
+        # search the name in outputs of all node
+        found = False
+        for i in range(len(graph.node)):
+            for j in range(len(graph.node[i].output)):
+                if graph.node[i].output[j] == node_output_name:
+                    found = True
+                    break
+            if found:
+                break
+        if not found:
+            raise RuntimeError("Failed to find hidden_states graph output in clip")
+
+        # Insert a Cast  (fp32 -> fp16) node so that hidden_states has same data type as the first graph output.
+        graph_output_name = "hidden_states"
+        cast_node = onnx.helper.make_node("Cast", inputs=[node_output_name], outputs=[graph_output_name])
+        cast_node.attribute.extend([onnx.helper.make_attribute("to", graph.output[0].type.tensor_type.elem_type)])
+
+        hidden_state = graph.output.add()
+        hidden_state.CopyFrom(
+            onnx.helper.make_tensor_value_info(
+                graph_output_name,
+                graph.output[0].type.tensor_type.elem_type,
+                ["B", "S", self.embedding_dim],
+            )
+        )
+
+        onnx_model = OnnxModel(model)
+        onnx_model.add_node(cast_node)
+        onnx_model.save_model_to_file(optimized_onnx_path, use_external_data_format=use_external_data_format)
+
+    def optimize_ort(
+        self,
+        input_onnx_path,
+        optimized_onnx_path,
+        to_fp16=True,
+        fp32_op_list=None,
+        optimize_by_ort=True,
+        optimize_by_fusion=True,
+        tmp_dir=None,
+    ):
+        optimizer = self.get_ort_optimizer()
+
+        if not self.output_hidden_state:
+            optimizer.optimize(
+                input_onnx_path,
+                optimized_onnx_path,
+                float16=to_fp16,
+                keep_io_types=[],
+                fp32_op_list=fp32_op_list,
+                keep_outputs=["text_embeddings"],
+                optimize_by_ort=optimize_by_ort,
+                optimize_by_fusion=optimize_by_fusion,
+                tmp_dir=tmp_dir,
+            )
+        elif optimize_by_fusion:
+            with tempfile.TemporaryDirectory() as tmp_dir:
+                # Save to a temporary file so that we can load it with Onnx Runtime.
+                logger.info("Saving a temporary model to add hidden_states to graph output ...")
+                tmp_model_path = os.path.join(tmp_dir, "model.onnx")
+
+                model = onnx.load(input_onnx_path)
+                self.add_hidden_states_graph_output(model, tmp_model_path, use_external_data_format=True)
+                optimizer.optimize(
+                    tmp_model_path,
+                    optimized_onnx_path,
+                    float16=to_fp16,
+                    keep_io_types=[],
+                    fp32_op_list=fp32_op_list,
+                    keep_outputs=["text_embeddings", "hidden_states"],
+                    optimize_by_ort=optimize_by_ort,
+                    optimize_by_fusion=optimize_by_fusion,
+                    tmp_dir=tmp_dir,
+                )
+        else:  # input is optimized model, there is no need to add hidden states.
+            optimizer.optimize(
+                input_onnx_path,
+                optimized_onnx_path,
+                float16=to_fp16,
+                keep_io_types=[],
+                fp32_op_list=fp32_op_list,
+                keep_outputs=["text_embeddings", "hidden_states"],
+                optimize_by_ort=optimize_by_ort,
+                optimize_by_fusion=optimize_by_fusion,
+                tmp_dir=tmp_dir,
+            )
+
+    def optimize_trt(self, input_onnx_path, optimized_onnx_path):
+        onnx_graph = onnx.load(input_onnx_path)
+        opt = TrtOptimizer(onnx_graph)
+        opt.select_outputs([0])  # delete graph output#1
+        opt.cleanup()
+        opt.fold_constants()
+        opt.infer_shapes()
+        opt.select_outputs([0], names=["text_embeddings"])  # rename network output
+        opt.cleanup()
+        onnx_opt_graph = opt.get_optimized_onnx_graph()
+        if self.output_hidden_state:
+            self.add_hidden_states_graph_output(onnx_opt_graph, optimized_onnx_path)
+        else:
+            onnx.save(onnx_opt_graph, optimized_onnx_path)
+
+    def load_model(self, framework_model_dir, subfolder="text_encoder"):
+        return self.from_pretrained(CLIPTextModel, framework_model_dir, subfolder)
+
+
+class CLIPWithProj(CLIP):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        max_batch_size=16,
+        clip_skip=0,
+    ):
+        super().__init__(
+            pipeline_info,
+            model,
+            device=device,
+            max_batch_size=max_batch_size,
+            embedding_dim=pipeline_info.clipwithproj_embedding_dim(),
+            clip_skip=clip_skip,
+        )
+
+    def load_model(self, framework_model_dir, subfolder="text_encoder_2"):
+        return self.from_pretrained(CLIPTextModelWithProjection, framework_model_dir, subfolder)
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        self.check_dims(batch_size, image_height, image_width)
+        output = {
+            "input_ids": (batch_size, self.text_maxlen),
+            "text_embeddings": (batch_size, self.embedding_dim),
+        }
+
+        if self.output_hidden_state:
+            output["hidden_states"] = (batch_size, self.text_maxlen, self.embedding_dim)
+
+        return output
+
+
+class UNet2DConditionControlNetModel(torch.nn.Module):
+    def __init__(self, unet, controlnets: ControlNetModel):
+        super().__init__()
+        self.unet = unet
+        self.controlnets = controlnets
+
+    def forward(self, sample, timestep, encoder_hidden_states, controlnet_images, controlnet_scales):
+        for i, (controlnet_image, conditioning_scale, controlnet) in enumerate(
+            zip(controlnet_images, controlnet_scales, self.controlnets, strict=False)
+        ):
+            down_samples, mid_sample = controlnet(
+                sample,
+                timestep,
+                encoder_hidden_states=encoder_hidden_states,
+                controlnet_cond=controlnet_image,
+                return_dict=False,
+            )
+
+            down_samples = [down_sample * conditioning_scale for down_sample in down_samples]
+            mid_sample *= conditioning_scale
+
+            # merge samples
+            if i == 0:
+                down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
+            else:
+                down_block_res_samples = [
+                    samples_prev + samples_curr
+                    for samples_prev, samples_curr in zip(down_block_res_samples, down_samples, strict=False)
+                ]
+                mid_block_res_sample += mid_sample
+
+        noise_pred = self.unet(
+            sample,
+            timestep,
+            encoder_hidden_states=encoder_hidden_states,
+            down_block_additional_residuals=down_block_res_samples,
+            mid_block_additional_residual=mid_block_res_sample,
+        )
+        return noise_pred[0]
+
+
+# Modified from convert_stable_diffusion_controlnet_to_onnx.py in diffusers
+class UNet2DConditionXLControlNetModel(torch.nn.Module):
+    def __init__(self, unet, controlnets: ControlNetModel):
+        super().__init__()
+        self.unet = unet
+        self.controlnets = controlnets
+
+    def forward(
+        self,
+        sample,
+        timestep,
+        encoder_hidden_states,
+        text_embeds,
+        time_ids,
+        controlnet_images,
+        controlnet_scales,
+    ):
+        added_cond_kwargs = {"text_embeds": text_embeds, "time_ids": time_ids}
+        for i, (controlnet_image, conditioning_scale, controlnet) in enumerate(
+            zip(controlnet_images, controlnet_scales, self.controlnets, strict=False)
+        ):
+            down_samples, mid_sample = controlnet(
+                sample,
+                timestep,
+                encoder_hidden_states=encoder_hidden_states,
+                controlnet_cond=controlnet_image,
+                conditioning_scale=conditioning_scale,
+                added_cond_kwargs=added_cond_kwargs,
+                return_dict=False,
+            )
+
+            # merge samples
+            if i == 0:
+                down_block_res_samples, mid_block_res_sample = down_samples, mid_sample
+            else:
+                down_block_res_samples = [
+                    samples_prev + samples_curr
+                    for samples_prev, samples_curr in zip(down_block_res_samples, down_samples, strict=False)
+                ]
+                mid_block_res_sample += mid_sample
+
+        noise_pred = self.unet(
+            sample,
+            timestep,
+            encoder_hidden_states=encoder_hidden_states,
+            down_block_additional_residuals=down_block_res_samples,
+            mid_block_additional_residual=mid_block_res_sample,
+            added_cond_kwargs=added_cond_kwargs,
+            return_dict=False,
+        )
+        return noise_pred[0]
+
+
+class UNet(BaseModel):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        fp16=False,  # used by TRT
+        max_batch_size=16,
+        text_maxlen=77,
+        unet_dim=4,
+    ):
+        super().__init__(
+            pipeline_info,
+            model=model,
+            device=device,
+            fp16=fp16,
+            max_batch_size=max_batch_size,
+            embedding_dim=pipeline_info.unet_embedding_dim(),
+            text_maxlen=text_maxlen,
+        )
+
+        self.unet_dim = unet_dim
+        self.controlnet = pipeline_info.controlnet_name()
+
+    def load_model(self, framework_model_dir, subfolder="unet"):
+        options = {"variant": "fp16", "torch_dtype": torch.float16}
+
+        model = self.from_pretrained(UNet2DConditionModel, framework_model_dir, subfolder, **options)
+
+        if self.controlnet:
+            controlnet_list = []
+            for name in self.controlnet:
+                controlnet = self.from_pretrained(
+                    ControlNetModel,
+                    framework_model_dir,
+                    subfolder=None,
+                    model_name=name,
+                    torch_dtype=torch.float16,
+                )
+                controlnet_list.append(controlnet)
+
+            model = UNet2DConditionControlNetModel(model, torch.nn.ModuleList(controlnet_list))
+
+        if not self.fp16:
+            model = model.to(torch.float32)
+
+        return model
+
+    def get_input_names(self):
+        if not self.controlnet:
+            return ["sample", "timestep", "encoder_hidden_states"]
+        else:
+            return ["sample", "timestep", "encoder_hidden_states", "controlnet_images", "controlnet_scales"]
+
+    def get_output_names(self):
+        return ["latent"]
+
+    def get_dynamic_axes(self):
+        b = "2B" if self.get_batch_multiplier() == 2 else "B"
+        output = {
+            "sample": {0: b, 2: "H", 3: "W"},
+            "encoder_hidden_states": {0: b},
+            "latent": {0: b, 2: "H", 3: "W"},
+        }
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": {1: b, 3: "8H", 4: "8W"},
+                }
+            )
+        return output
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        (
+            min_batch,
+            max_batch,
+            min_image_height,
+            max_image_height,
+            min_image_width,
+            max_image_width,
+            min_latent_height,
+            max_latent_height,
+            min_latent_width,
+            max_latent_width,
+        ) = self.get_minmax_dims(batch_size, image_height, image_width, static_batch, static_image_shape)
+        m = self.get_batch_multiplier()
+        output = {
+            "sample": [
+                (m * min_batch, self.unet_dim, min_latent_height, min_latent_width),
+                (m * batch_size, self.unet_dim, latent_height, latent_width),
+                (m * max_batch, self.unet_dim, max_latent_height, max_latent_width),
+            ],
+            "encoder_hidden_states": [
+                (m * min_batch, self.text_maxlen, self.embedding_dim),
+                (m * batch_size, self.text_maxlen, self.embedding_dim),
+                (m * max_batch, self.text_maxlen, self.embedding_dim),
+            ],
+        }
+
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": [
+                        (len(self.controlnet), m * min_batch, 3, min_image_height, min_image_width),
+                        (len(self.controlnet), m * batch_size, 3, image_height, image_width),
+                        (len(self.controlnet), m * max_batch, 3, max_image_height, max_image_width),
+                    ]
+                }
+            )
+        return output
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        m = self.get_batch_multiplier()
+        output = {
+            "sample": (m * batch_size, self.unet_dim, latent_height, latent_width),
+            "timestep": [1],
+            "encoder_hidden_states": (m * batch_size, self.text_maxlen, self.embedding_dim),
+            "latent": (m * batch_size, 4, latent_height, latent_width),
+        }
+
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": (len(self.controlnet), m * batch_size, 3, image_height, image_width),
+                    "controlnet_scales": [len(self.controlnet)],
+                }
+            )
+        return output
+
+    def get_sample_input(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        dtype = torch.float16 if self.fp16 else torch.float32
+        m = self.get_batch_multiplier()
+        output = (
+            torch.randn(m * batch_size, self.unet_dim, latent_height, latent_width, dtype=dtype, device=self.device),
+            torch.tensor([1.0], dtype=dtype, device=self.device),
+            torch.randn(m * batch_size, self.text_maxlen, self.embedding_dim, dtype=dtype, device=self.device),
+        )
+
+        if self.controlnet:
+            output = (
+                *output,
+                torch.randn(
+                    len(self.controlnet), m * batch_size, 3, image_height, image_width, dtype=dtype, device=self.device
+                ),
+                torch.randn(len(self.controlnet), dtype=dtype, device=self.device),
+            )
+        return output
+
+
+class UNetXL(BaseModel):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        fp16=False,  # used by TRT
+        max_batch_size=16,
+        text_maxlen=77,
+        unet_dim=4,
+        time_dim=6,
+    ):
+        super().__init__(
+            pipeline_info,
+            model,
+            device=device,
+            fp16=fp16,
+            max_batch_size=max_batch_size,
+            embedding_dim=pipeline_info.unet_embedding_dim(),
+            text_maxlen=text_maxlen,
+        )
+        self.unet_dim = unet_dim
+        self.time_dim = time_dim
+
+        self.custom_unet = pipeline_info.custom_unet()
+        self.controlnet = pipeline_info.controlnet_name()
+
+    def load_model(self, framework_model_dir, subfolder="unet", always_download_fp16=True):
+        options = {"variant": "fp16", "torch_dtype": torch.float16} if self.fp16 or always_download_fp16 else {}
+
+        if self.custom_unet:
+            model_dir = os.path.join(framework_model_dir, self.custom_unet, subfolder)
+            if not os.path.exists(model_dir):
+                unet = UNet2DConditionModel.from_pretrained(self.custom_unet, **options)
+                unet.save_pretrained(model_dir)
+            else:
+                unet = UNet2DConditionModel.from_pretrained(model_dir, **options)
+            model = unet.to(self.device)
+        else:
+            model = self.from_pretrained(UNet2DConditionModel, framework_model_dir, subfolder, **options)
+
+        if always_download_fp16 and not self.fp16:
+            model = model.to(torch.float32)
+
+        if self.controlnet:
+            cnet_model_opts = {"torch_dtype": torch.float16} if self.fp16 or always_download_fp16 else {}
+            controlnets = torch.nn.ModuleList(
+                [ControlNetModel.from_pretrained(path, **cnet_model_opts).to(self.device) for path in self.controlnet]
+            )
+            model = UNet2DConditionXLControlNetModel(model, controlnets)
+
+        if always_download_fp16 and not self.fp16:
+            model = model.to(torch.float32)
+
+        return model
+
+    def get_input_names(self):
+        input_names = ["sample", "timestep", "encoder_hidden_states", "text_embeds", "time_ids"]
+        if self.controlnet:
+            return [*input_names, "controlnet_images", "controlnet_scales"]
+        return input_names
+
+    def get_output_names(self):
+        return ["latent"]
+
+    def get_dynamic_axes(self):
+        b = "2B" if self.get_batch_multiplier() == 2 else "B"
+        output = {
+            "sample": {0: b, 2: "H", 3: "W"},
+            "encoder_hidden_states": {0: b},
+            "text_embeds": {0: b},
+            "time_ids": {0: b},
+            "latent": {0: b, 2: "H", 3: "W"},
+        }
+
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": {1: b, 3: "8H", 4: "8W"},
+                }
+            )
+        return output
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        (
+            min_batch,
+            max_batch,
+            min_image_height,
+            max_image_height,
+            min_image_width,
+            max_image_width,
+            min_latent_height,
+            max_latent_height,
+            min_latent_width,
+            max_latent_width,
+        ) = self.get_minmax_dims(batch_size, image_height, image_width, static_batch, static_image_shape)
+        m = self.get_batch_multiplier()
+        output = {
+            "sample": [
+                (m * min_batch, self.unet_dim, min_latent_height, min_latent_width),
+                (m * batch_size, self.unet_dim, latent_height, latent_width),
+                (m * max_batch, self.unet_dim, max_latent_height, max_latent_width),
+            ],
+            "encoder_hidden_states": [
+                (m * min_batch, self.text_maxlen, self.embedding_dim),
+                (m * batch_size, self.text_maxlen, self.embedding_dim),
+                (m * max_batch, self.text_maxlen, self.embedding_dim),
+            ],
+            "text_embeds": [(m * min_batch, 1280), (m * batch_size, 1280), (m * max_batch, 1280)],
+            "time_ids": [
+                (m * min_batch, self.time_dim),
+                (m * batch_size, self.time_dim),
+                (m * max_batch, self.time_dim),
+            ],
+        }
+
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": [
+                        (len(self.controlnet), m * min_batch, 3, min_image_height, min_image_width),
+                        (len(self.controlnet), m * batch_size, 3, image_height, image_width),
+                        (len(self.controlnet), m * max_batch, 3, max_image_height, max_image_width),
+                    ],
+                }
+            )
+        return output
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        m = self.get_batch_multiplier()
+        output = {
+            "sample": (m * batch_size, self.unet_dim, latent_height, latent_width),
+            "timestep": (1,),
+            "encoder_hidden_states": (m * batch_size, self.text_maxlen, self.embedding_dim),
+            "text_embeds": (m * batch_size, 1280),
+            "time_ids": (m * batch_size, self.time_dim),
+            "latent": (m * batch_size, 4, latent_height, latent_width),
+        }
+
+        if self.controlnet:
+            output.update(
+                {
+                    "controlnet_images": (len(self.controlnet), m * batch_size, 3, image_height, image_width),
+                    "controlnet_scales": [len(self.controlnet)],
+                }
+            )
+        return output
+
+    def get_sample_input(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        dtype = torch.float16 if self.fp16 else torch.float32
+        m = self.get_batch_multiplier()
+        if not self.controlnet:
+            return (
+                torch.randn(
+                    m * batch_size, self.unet_dim, latent_height, latent_width, dtype=dtype, device=self.device
+                ),
+                torch.tensor([1.0], dtype=dtype, device=self.device),
+                torch.randn(m * batch_size, self.text_maxlen, self.embedding_dim, dtype=dtype, device=self.device),
+                {
+                    "added_cond_kwargs": {
+                        "text_embeds": torch.randn(m * batch_size, 1280, dtype=dtype, device=self.device),
+                        "time_ids": torch.randn(m * batch_size, self.time_dim, dtype=dtype, device=self.device),
+                    }
+                },
+            )
+        else:
+            # sample, timestep, encoder_hidden_states, text_embeds, time_ids, controlnet_images, controlnet_scales,
+            return (
+                torch.randn(
+                    m * batch_size, self.unet_dim, latent_height, latent_width, dtype=dtype, device=self.device
+                ),
+                torch.tensor([1.0], dtype=dtype, device=self.device),
+                torch.randn(m * batch_size, self.text_maxlen, self.embedding_dim, dtype=dtype, device=self.device),
+                torch.randn(m * batch_size, 1280, dtype=dtype, device=self.device),
+                torch.randn(m * batch_size, self.time_dim, dtype=dtype, device=self.device),
+                torch.randn(
+                    len(self.controlnet), m * batch_size, 3, image_height, image_width, dtype=dtype, device=self.device
+                ),
+                torch.randn(len(self.controlnet), dtype=dtype, device=self.device),
+            )
+
+
+# VAE Decoder
+class VAE(BaseModel):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        model,
+        device,
+        max_batch_size,
+        fp16: bool = False,
+        custom_fp16_vae: str | None = None,
+    ):
+        super().__init__(
+            pipeline_info,
+            model=model,
+            device=device,
+            fp16=fp16,
+            max_batch_size=max_batch_size,
+        )
+
+        # For SD XL, need custom trained fp16 model to speed up, and avoid overflow at the same time.
+        self.custom_fp16_vae = custom_fp16_vae
+
+    def load_model(self, framework_model_dir, subfolder: str = "vae_decoder"):
+        model_name = self.custom_fp16_vae or self.pipeline_info.name()
+
+        model_dir = os.path.join(framework_model_dir, model_name, subfolder)
+        if not os.path.exists(model_dir):
+            if self.custom_fp16_vae:
+                vae = AutoencoderKL.from_pretrained(self.custom_fp16_vae, torch_dtype=torch.float16).to(self.device)
+            else:
+                vae = AutoencoderKL.from_pretrained(
+                    self.pipeline_info.name(),
+                    subfolder="vae",
+                    use_safetensors=self.pipeline_info.use_safetensors(),
+                ).to(self.device)
+            vae.save_pretrained(model_dir)
+        else:
+            print(f"Load {self.name} pytorch model from: {model_dir}")
+            if self.custom_fp16_vae:
+                vae = AutoencoderKL.from_pretrained(model_dir, torch_dtype=torch.float16).to(self.device)
+            else:
+                vae = AutoencoderKL.from_pretrained(model_dir).to(self.device)
+
+        vae.forward = vae.decode
+        return vae
+
+    def get_input_names(self):
+        return ["latent"]
+
+    def get_output_names(self):
+        return ["images"]
+
+    def get_dynamic_axes(self):
+        return {"latent": {0: "B", 2: "H", 3: "W"}, "images": {0: "B", 2: "8H", 3: "8W"}}
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        (
+            min_batch,
+            max_batch,
+            _,
+            _,
+            _,
+            _,
+            min_latent_height,
+            max_latent_height,
+            min_latent_width,
+            max_latent_width,
+        ) = self.get_minmax_dims(batch_size, image_height, image_width, static_batch, static_image_shape)
+        return {
+            "latent": [
+                (min_batch, 4, min_latent_height, min_latent_width),
+                (batch_size, 4, latent_height, latent_width),
+                (max_batch, 4, max_latent_height, max_latent_width),
+            ]
+        }
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        return {
+            "latent": (batch_size, 4, latent_height, latent_width),
+            "images": (batch_size, 3, image_height, image_width),
+        }
+
+    def get_sample_input(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        dtype = torch.float16 if self.fp16 else torch.float32
+        return (torch.randn(batch_size, 4, latent_height, latent_width, dtype=dtype, device=self.device),)
+
+    def fp32_input_output_names(self) -> list[str]:
+        return []
+
+
+def get_tokenizer(pipeline_info: PipelineInfo, framework_model_dir, subfolder="tokenizer"):
+    tokenizer_dir = os.path.join(framework_model_dir, pipeline_info.name(), subfolder)
+
+    if not os.path.exists(tokenizer_dir):
+        model = CLIPTokenizer.from_pretrained(
+            pipeline_info.name(),
+            subfolder=subfolder,
+            use_safetensors=pipeline_info.is_xl(),
+        )
+        model.save_pretrained(tokenizer_dir)
+    else:
+        print(f"[I] Load tokenizer pytorch model from: {tokenizer_dir}")
+        model = CLIPTokenizer.from_pretrained(tokenizer_dir)
+    return model
+
+
+class TorchVAEEncoder(torch.nn.Module):
+    def __init__(self, vae_encoder):
+        super().__init__()
+        self.vae_encoder = vae_encoder
+
+    def forward(self, x):
+        return self.vae_encoder.encode(x).latent_dist.sample()
+
+
+class VAEEncoder(BaseModel):
+    def __init__(self, pipeline_info: PipelineInfo, model, device, max_batch_size):
+        super().__init__(
+            pipeline_info,
+            model=model,
+            device=device,
+            max_batch_size=max_batch_size,
+        )
+
+    def load_model(self, framework_model_dir, subfolder="vae_encoder"):
+        vae = self.from_pretrained(AutoencoderKL, framework_model_dir, subfolder)
+        return TorchVAEEncoder(vae)
+
+    def get_input_names(self):
+        return ["images"]
+
+    def get_output_names(self):
+        return ["latent"]
+
+    def get_dynamic_axes(self):
+        return {"images": {0: "B", 2: "8H", 3: "8W"}, "latent": {0: "B", 2: "H", 3: "W"}}
+
+    def get_input_profile(self, batch_size, image_height, image_width, static_batch, static_image_shape):
+        self.check_dims(batch_size, image_height, image_width)
+
+        (
+            min_batch,
+            max_batch,
+            min_image_height,
+            max_image_height,
+            min_image_width,
+            max_image_width,
+            _,
+            _,
+            _,
+            _,
+        ) = self.get_minmax_dims(batch_size, image_height, image_width, static_batch, static_image_shape)
+
+        return {
+            "images": [
+                (min_batch, 3, min_image_height, min_image_width),
+                (batch_size, 3, image_height, image_width),
+                (max_batch, 3, max_image_height, max_image_width),
+            ],
+        }
+
+    def get_shape_dict(self, batch_size, image_height, image_width):
+        latent_height, latent_width = self.check_dims(batch_size, image_height, image_width)
+        return {
+            "images": (batch_size, 3, image_height, image_width),
+            "latent": (batch_size, 4, latent_height, latent_width),
+        }
+
+    def get_sample_input(self, batch_size, image_height, image_width):
+        self.check_dims(batch_size, image_height, image_width)
+        return torch.randn(batch_size, 3, image_height, image_width, dtype=torch.float32, device=self.device)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_schedulers.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_schedulers.py
new file mode 100644
index 0000000000000000000000000000000000000000..9e05ce4a677eff77e92f50b1365904363e9cea36
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/diffusion_schedulers.py
@@ -0,0 +1,1179 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from utilities.py of TensorRT demo diffusion, which has the following license:
+#
+# Copyright 2022 The HuggingFace Inc. team.
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+
+
+import numpy as np
+import torch
+
+
+class DDIMScheduler:
+    def __init__(
+        self,
+        device="cuda",
+        num_train_timesteps: int = 1000,
+        beta_start: float = 0.0001,
+        beta_end: float = 0.02,
+        clip_sample: bool = False,
+        set_alpha_to_one: bool = False,
+        steps_offset: int = 1,
+        prediction_type: str = "epsilon",
+        timestep_spacing: str = "leading",
+    ):
+        # this schedule is very specific to the latent diffusion model.
+        betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
+
+        alphas = 1.0 - betas
+        self.alphas_cumprod = torch.cumprod(alphas, dim=0)
+        # standard deviation of the initial noise distribution
+        self.init_noise_sigma = 1.0
+
+        # At every step in ddim, we are looking into the previous alphas_cumprod
+        # For the final step, there is no previous alphas_cumprod because we are already at 0
+        # `set_alpha_to_one` decides whether we set this parameter simply to one or
+        # whether we use the final alpha of the "non-previous" one.
+        self.final_alpha_cumprod = torch.tensor(1.0) if set_alpha_to_one else self.alphas_cumprod[0]
+
+        # setable values
+        self.num_inference_steps = None
+        self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy().astype(np.int64))
+        self.steps_offset = steps_offset
+        self.num_train_timesteps = num_train_timesteps
+        self.clip_sample = clip_sample
+        self.prediction_type = prediction_type
+        self.device = device
+        self.timestep_spacing = timestep_spacing
+
+    def configure(self):
+        variance = np.zeros(self.num_inference_steps, dtype=np.float32)
+        for idx, timestep in enumerate(self.timesteps):
+            prev_timestep = timestep - self.num_train_timesteps // self.num_inference_steps
+            variance[idx] = self._get_variance(timestep, prev_timestep)
+        self.variance = torch.from_numpy(variance).to(self.device)
+
+        timesteps = self.timesteps.long().cpu()
+        self.filtered_alphas_cumprod = self.alphas_cumprod[timesteps].to(self.device)
+        self.final_alpha_cumprod = self.final_alpha_cumprod.to(self.device)
+
+    def scale_model_input(self, sample: torch.FloatTensor, idx, *args, **kwargs) -> torch.FloatTensor:
+        return sample
+
+    def _get_variance(self, timestep, prev_timestep):
+        alpha_prod_t = self.alphas_cumprod[timestep]
+        alpha_prod_t_prev = self.alphas_cumprod[prev_timestep] if prev_timestep >= 0 else self.final_alpha_cumprod
+        beta_prod_t = 1 - alpha_prod_t
+        beta_prod_t_prev = 1 - alpha_prod_t_prev
+
+        variance = (beta_prod_t_prev / beta_prod_t) * (1 - alpha_prod_t / alpha_prod_t_prev)
+
+        return variance
+
+    def set_timesteps(self, num_inference_steps: int):
+        self.num_inference_steps = num_inference_steps
+        if self.timestep_spacing == "leading":
+            step_ratio = self.num_train_timesteps // self.num_inference_steps
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy().astype(np.int64)
+            timesteps += self.steps_offset
+        elif self.timestep_spacing == "trailing":
+            step_ratio = self.num_train_timesteps / self.num_inference_steps
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = np.round(np.arange(self.num_train_timesteps, 0, -step_ratio)).astype(np.int64)
+            timesteps -= 1
+        else:
+            raise ValueError(
+                f"{self.timestep_spacing} is not supported. Please make sure to choose one of 'linspace', 'leading' or 'trailing'."
+            )
+
+        self.timesteps = torch.from_numpy(timesteps).to(self.device)
+
+    def step(
+        self,
+        model_output,
+        sample,
+        idx,
+        timestep,
+        eta: float = 0.0,
+        use_clipped_model_output: bool = False,
+        generator=None,
+        variance_noise: torch.FloatTensor = None,
+    ):
+        if self.num_inference_steps is None:
+            raise ValueError(
+                "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
+            )
+
+        # See formulas (12) and (16) of DDIM paper https://arxiv.org/pdf/2010.02502.pdf
+        # Ideally, read DDIM paper in-detail understanding
+
+        # Notation (<variable name> -> <name in paper>
+        # - pred_noise_t -> e_theta(x_t, t)
+        # - pred_original_sample -> f_theta(x_t, t) or x_0
+        # - std_dev_t -> sigma_t
+        # - eta -> η
+        # - pred_sample_direction -> "direction pointing to x_t"
+        # - pred_prev_sample -> "x_t-1"
+
+        prev_idx = idx + 1
+        alpha_prod_t = self.filtered_alphas_cumprod[idx]
+        alpha_prod_t_prev = (
+            self.filtered_alphas_cumprod[prev_idx] if prev_idx < self.num_inference_steps else self.final_alpha_cumprod
+        )
+
+        beta_prod_t = 1 - alpha_prod_t
+
+        # 3. compute predicted original sample from predicted noise also called
+        # "predicted x_0" of formula (12) from https://arxiv.org/pdf/2010.02502.pdf
+        if self.prediction_type == "epsilon":
+            pred_original_sample = (sample - beta_prod_t ** (0.5) * model_output) / alpha_prod_t ** (0.5)
+        elif self.prediction_type == "sample":
+            pred_original_sample = model_output
+        elif self.prediction_type == "v_prediction":
+            pred_original_sample = (alpha_prod_t**0.5) * sample - (beta_prod_t**0.5) * model_output
+            # predict V
+            model_output = (alpha_prod_t**0.5) * model_output + (beta_prod_t**0.5) * sample
+        else:
+            raise ValueError(
+                f"prediction_type given as {self.prediction_type} must be one of `epsilon`, `sample`, or `v_prediction`"
+            )
+
+        # 4. Clip "predicted x_0"
+        if self.clip_sample:
+            pred_original_sample = torch.clamp(pred_original_sample, -1, 1)
+
+        # 5. compute variance: "sigma_t(η)" -> see formula (16)
+        # o_t = sqrt((1 - a_t-1)/(1 - a_t)) * sqrt(1 - a_t/a_t-1)
+        variance = self.variance[idx]
+        std_dev_t = eta * variance ** (0.5)
+
+        if use_clipped_model_output:
+            # the model_output is always re-derived from the clipped x_0 in Glide
+            model_output = (sample - alpha_prod_t ** (0.5) * pred_original_sample) / beta_prod_t ** (0.5)
+
+        # 6. compute "direction pointing to x_t" of formula (12) from https://arxiv.org/pdf/2010.02502.pdf
+        pred_sample_direction = (1 - alpha_prod_t_prev - std_dev_t**2) ** (0.5) * model_output
+
+        # 7. compute x_t without "random noise" of formula (12) from https://arxiv.org/pdf/2010.02502.pdf
+        prev_sample = alpha_prod_t_prev ** (0.5) * pred_original_sample + pred_sample_direction
+
+        if eta > 0:
+            # randn_like does not support generator https://github.com/pytorch/pytorch/issues/27072
+            device = model_output.device
+            if variance_noise is not None and generator is not None:
+                raise ValueError(
+                    "Cannot pass both generator and variance_noise. Please make sure that either `generator` or"
+                    " `variance_noise` stays `None`."
+                )
+
+            if variance_noise is None:
+                variance_noise = torch.randn(
+                    model_output.shape, generator=generator, device=device, dtype=model_output.dtype
+                )
+            variance = std_dev_t * variance_noise
+
+            prev_sample = prev_sample + variance
+
+        return prev_sample
+
+    def add_noise(self, init_latents, noise, idx, latent_timestep):
+        sqrt_alpha_prod = self.filtered_alphas_cumprod[idx] ** 0.5
+        sqrt_one_minus_alpha_prod = (1 - self.filtered_alphas_cumprod[idx]) ** 0.5
+        noisy_latents = sqrt_alpha_prod * init_latents + sqrt_one_minus_alpha_prod * noise
+
+        return noisy_latents
+
+
+class EulerAncestralDiscreteScheduler:
+    def __init__(
+        self,
+        num_train_timesteps: int = 1000,
+        beta_start: float = 0.0001,
+        beta_end: float = 0.02,
+        device="cuda",
+        steps_offset: int = 1,
+        prediction_type: str = "epsilon",
+        timestep_spacing: str = "trailing",  # set default to trailing for SDXL Turbo
+    ):
+        betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
+        alphas = 1.0 - betas
+        self.alphas_cumprod = torch.cumprod(alphas, dim=0)
+
+        sigmas = np.array(((1 - self.alphas_cumprod) / self.alphas_cumprod) ** 0.5)
+        sigmas = np.concatenate([sigmas[::-1], [0.0]]).astype(np.float32)
+        self.sigmas = torch.from_numpy(sigmas)
+
+        # standard deviation of the initial noise distribution
+        self.init_noise_sigma = self.sigmas.max()
+
+        # setable values
+        self.num_inference_steps = None
+        timesteps = np.linspace(0, num_train_timesteps - 1, num_train_timesteps, dtype=float)[::-1].copy()
+        self.timesteps = torch.from_numpy(timesteps)
+        self.is_scale_input_called = False
+
+        self._step_index = None
+
+        self.device = device
+        self.num_train_timesteps = num_train_timesteps
+        self.steps_offset = steps_offset
+        self.prediction_type = prediction_type
+        self.timestep_spacing = timestep_spacing
+
+    # Copied from diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler._init_step_index
+    def _init_step_index(self, timestep):
+        if isinstance(timestep, torch.Tensor):
+            timestep = timestep.to(self.timesteps.device)
+
+        index_candidates = (self.timesteps == timestep).nonzero()
+
+        # The sigma index that is taken for the **very** first `step`
+        # is always the second index (or the last index if there is only 1)
+        # This way we can ensure we don't accidentally skip a sigma in
+        # case we start in the middle of the denoising schedule (e.g. for image-to-image)
+        if len(index_candidates) > 1:
+            step_index = index_candidates[1]
+        else:
+            step_index = index_candidates[0]
+
+        self._step_index = step_index.item()
+
+    def scale_model_input(self, sample: torch.FloatTensor, idx, timestep, *args, **kwargs) -> torch.FloatTensor:
+        if self._step_index is None:
+            self._init_step_index(timestep)
+
+        sigma = self.sigmas[self._step_index]
+        sample = sample / ((sigma**2 + 1) ** 0.5)
+        self.is_scale_input_called = True
+        return sample
+
+    def set_timesteps(self, num_inference_steps: int):
+        self.num_inference_steps = num_inference_steps
+
+        if self.timestep_spacing == "linspace":
+            timesteps = np.linspace(0, self.num_train_timesteps - 1, num_inference_steps, dtype=np.float32)[::-1].copy()
+        elif self.timestep_spacing == "leading":
+            step_ratio = self.num_train_timesteps // self.num_inference_steps
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy().astype(np.float32)
+            timesteps += self.steps_offset
+        elif self.timestep_spacing == "trailing":
+            step_ratio = self.num_train_timesteps / self.num_inference_steps
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = (np.arange(self.num_train_timesteps, 0, -step_ratio)).round().copy().astype(np.float32)
+            timesteps -= 1
+        else:
+            raise ValueError(
+                f"{self.timestep_spacing} is not supported. Please make sure to choose one of 'linspace', 'leading' or 'trailing'."
+            )
+
+        sigmas = np.array(((1 - self.alphas_cumprod) / self.alphas_cumprod) ** 0.5)
+        sigmas = np.interp(timesteps, np.arange(0, len(sigmas)), sigmas)
+        sigmas = np.concatenate([sigmas, [0.0]]).astype(np.float32)
+        self.sigmas = torch.from_numpy(sigmas).to(device=self.device)
+        self.timesteps = torch.from_numpy(timesteps).to(device=self.device)
+
+        self._step_index = None
+
+    def configure(self):
+        dts = np.zeros(self.num_inference_steps, dtype=np.float32)
+        sigmas_up = np.zeros(self.num_inference_steps, dtype=np.float32)
+        for idx, timestep in enumerate(self.timesteps):
+            step_index = (self.timesteps == timestep).nonzero().item()
+            sigma = self.sigmas[step_index]
+
+            sigma_from = self.sigmas[step_index]
+            sigma_to = self.sigmas[step_index + 1]
+            sigma_up = (sigma_to**2 * (sigma_from**2 - sigma_to**2) / sigma_from**2) ** 0.5
+            sigma_down = (sigma_to**2 - sigma_up**2) ** 0.5
+            dt = sigma_down - sigma
+            dts[idx] = dt
+            sigmas_up[idx] = sigma_up
+
+        self.dts = torch.from_numpy(dts).to(self.device)
+        self.sigmas_up = torch.from_numpy(sigmas_up).to(self.device)
+
+    def step(
+        self,
+        model_output,
+        sample,
+        idx,
+        timestep,
+        generator=None,
+    ):
+        if self._step_index is None:
+            self._init_step_index(timestep)
+        sigma = self.sigmas[self._step_index]
+
+        # 1. compute predicted original sample (x_0) from sigma-scaled predicted noise
+        if self.prediction_type == "epsilon":
+            pred_original_sample = sample - sigma * model_output
+        elif self.prediction_type == "v_prediction":
+            # * c_out + input * c_skip
+            pred_original_sample = model_output * (-sigma / (sigma**2 + 1) ** 0.5) + (sample / (sigma**2 + 1))
+        else:
+            raise ValueError(
+                f"prediction_type given as {self.prediction_type} must be one of `epsilon`, or `v_prediction`"
+            )
+
+        sigma_from = self.sigmas[self._step_index]
+        sigma_to = self.sigmas[self._step_index + 1]
+        sigma_up = (sigma_to**2 * (sigma_from**2 - sigma_to**2) / sigma_from**2) ** 0.5
+        sigma_down = (sigma_to**2 - sigma_up**2) ** 0.5
+
+        # 2. Convert to an ODE derivative
+        derivative = (sample - pred_original_sample) / sigma
+
+        dt = sigma_down - sigma
+
+        prev_sample = sample + derivative * dt
+
+        device = model_output.device
+        noise = torch.randn(model_output.shape, dtype=model_output.dtype, device=device, generator=generator).to(device)
+
+        prev_sample = prev_sample + noise * sigma_up
+
+        # upon completion increase step index by one
+        self._step_index += 1
+
+        return prev_sample
+
+    def add_noise(self, original_samples, noise, idx, timestep=None):
+        sigmas = self.sigmas.to(device=original_samples.device, dtype=original_samples.dtype)
+        schedule_timesteps = self.timesteps.to(original_samples.device)
+        timesteps = timestep.to(original_samples.device)
+
+        step_indices = [(schedule_timesteps == t).nonzero().item() for t in timesteps]
+
+        sigma = sigmas[step_indices].flatten()
+        while len(sigma.shape) < len(original_samples.shape):
+            sigma = sigma.unsqueeze(-1)
+
+        noisy_samples = original_samples + noise * sigma
+        return noisy_samples
+
+
+class UniPCMultistepScheduler:
+    def __init__(
+        self,
+        device="cuda",
+        num_train_timesteps: int = 1000,
+        beta_start: float = 0.00085,
+        beta_end: float = 0.012,
+        solver_order: int = 2,
+        prediction_type: str = "epsilon",
+        thresholding: bool = False,
+        dynamic_thresholding_ratio: float = 0.995,
+        sample_max_value: float = 1.0,
+        predict_x0: bool = True,
+        solver_type: str = "bh2",
+        lower_order_final: bool = True,
+        disable_corrector: list[int] | None = None,
+        use_karras_sigmas: bool | None = False,
+        timestep_spacing: str = "linspace",
+        steps_offset: int = 0,
+        sigma_min=None,
+        sigma_max=None,
+    ):
+        self.device = device
+        self.betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
+
+        self.alphas = 1.0 - self.betas
+        self.alphas_cumprod = torch.cumprod(self.alphas, dim=0)
+        # Currently we only support VP-type noise schedule
+        self.alpha_t = torch.sqrt(self.alphas_cumprod)
+        self.sigma_t = torch.sqrt(1 - self.alphas_cumprod)
+        self.lambda_t = torch.log(self.alpha_t) - torch.log(self.sigma_t)
+
+        # standard deviation of the initial noise distribution
+        self.init_noise_sigma = 1.0
+
+        self.predict_x0 = predict_x0
+        # setable values
+        self.num_inference_steps = None
+        timesteps = np.linspace(0, num_train_timesteps - 1, num_train_timesteps, dtype=np.float32)[::-1].copy()
+        self.timesteps = torch.from_numpy(timesteps)
+        self.model_outputs = [None] * solver_order
+        self.timestep_list = [None] * solver_order
+        self.lower_order_nums = 0
+        self.disable_corrector = disable_corrector if disable_corrector else []
+        self.last_sample = None
+
+        self._step_index = None
+
+        self.num_train_timesteps = num_train_timesteps
+        self.solver_order = solver_order
+        self.prediction_type = prediction_type
+        self.thresholding = thresholding
+        self.dynamic_thresholding_ratio = dynamic_thresholding_ratio
+        self.sample_max_value = sample_max_value
+        self.solver_type = solver_type
+        self.lower_order_final = lower_order_final
+        self.use_karras_sigmas = use_karras_sigmas
+        self.timestep_spacing = timestep_spacing
+        self.steps_offset = steps_offset
+        self.sigma_min = sigma_min
+        self.sigma_max = sigma_max
+
+    @property
+    def step_index(self):
+        """
+        The index counter for current timestep. It will increase 1 after each scheduler step.
+        """
+        return self._step_index
+
+    def set_timesteps(self, num_inference_steps: int):
+        if self.timestep_spacing == "linspace":
+            timesteps = (
+                np.linspace(0, self.num_train_timesteps - 1, num_inference_steps + 1)
+                .round()[::-1][:-1]
+                .copy()
+                .astype(np.int64)
+            )
+        elif self.timestep_spacing == "leading":
+            step_ratio = self.num_train_timesteps // (num_inference_steps + 1)
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = (np.arange(0, num_inference_steps + 1) * step_ratio).round()[::-1][:-1].copy().astype(np.int64)
+            timesteps += self.steps_offset
+        elif self.timestep_spacing == "trailing":
+            step_ratio = self.num_train_timesteps / num_inference_steps
+            # creates integer timesteps by multiplying by ratio
+            # casting to int to avoid issues when num_inference_step is power of 3
+            timesteps = np.arange(self.num_train_timesteps, 0, -step_ratio).round().copy().astype(np.int64)
+            timesteps -= 1
+        else:
+            raise ValueError(
+                f"{self.timestep_spacing} is not supported. Please make sure to choose one of 'linspace', 'leading' or 'trailing'."
+            )
+
+        sigmas = np.array(((1 - self.alphas_cumprod) / self.alphas_cumprod) ** 0.5)
+        if self.use_karras_sigmas:
+            log_sigmas = np.log(sigmas)
+            sigmas = np.flip(sigmas).copy()
+            sigmas = self._convert_to_karras(in_sigmas=sigmas, num_inference_steps=num_inference_steps)
+            timesteps = np.array([self._sigma_to_t(sigma, log_sigmas) for sigma in sigmas]).round()
+            sigmas = np.concatenate([sigmas, sigmas[-1:]]).astype(np.float32)
+        else:
+            sigmas = np.interp(timesteps, np.arange(0, len(sigmas)), sigmas)
+            sigma_last = ((1 - self.alphas_cumprod[0]) / self.alphas_cumprod[0]) ** 0.5
+            sigmas = np.concatenate([sigmas, [sigma_last]]).astype(np.float32)
+
+        self.sigmas = torch.from_numpy(sigmas)
+        self.timesteps = torch.from_numpy(timesteps).to(device=self.device, dtype=torch.int64)
+
+        self.num_inference_steps = len(timesteps)
+
+        self.model_outputs = [
+            None,
+        ] * self.solver_order
+        self.lower_order_nums = 0
+        self.last_sample = None
+
+        # add an index counter for schedulers that allow duplicated timesteps
+        self._step_index = None
+
+    # Copied from diffusers.schedulers.scheduling_ddpm.DDPMScheduler._threshold_sample
+    def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatTensor:
+        dtype = sample.dtype
+        batch_size, channels, *remaining_dims = sample.shape
+
+        if dtype not in (torch.float32, torch.float64):
+            sample = sample.float()  # upcast for quantile calculation, and clamp not implemented for cpu half
+
+        # Flatten sample for doing quantile calculation along each image
+        sample = sample.reshape(batch_size, channels * np.prod(remaining_dims))
+
+        abs_sample = sample.abs()  # "a certain percentile absolute pixel value"
+
+        s = torch.quantile(abs_sample, self.dynamic_thresholding_ratio, dim=1)
+        s = torch.clamp(
+            s, min=1, max=self.sample_max_value
+        )  # When clamped to min=1, equivalent to standard clipping to [-1, 1]
+        s = s.unsqueeze(1)  # (batch_size, 1) because clamp will broadcast along dim=0
+        sample = torch.clamp(sample, -s, s) / s  # "we threshold xt0 to the range [-s, s] and then divide by s"
+
+        sample = sample.reshape(batch_size, channels, *remaining_dims)
+        sample = sample.to(dtype)
+
+        return sample
+
+    # Copied from diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler._sigma_to_t
+    def _sigma_to_t(self, sigma, log_sigmas):
+        # get log sigma
+        log_sigma = np.log(np.maximum(sigma, 1e-10))
+
+        # get distribution
+        dists = log_sigma - log_sigmas[:, np.newaxis]
+
+        # get sigmas range
+        low_idx = np.cumsum((dists >= 0), axis=0).argmax(axis=0).clip(max=log_sigmas.shape[0] - 2)
+        high_idx = low_idx + 1
+
+        low = log_sigmas[low_idx]
+        high = log_sigmas[high_idx]
+
+        # interpolate sigmas
+        w = (low - log_sigma) / (low - high)
+        w = np.clip(w, 0, 1)
+
+        # transform interpolation to time range
+        t = (1 - w) * low_idx + w * high_idx
+        t = t.reshape(sigma.shape)
+        return t
+
+    # Copied from diffusers.schedulers.scheduling_dpmsolver_multistep.DPMSolverMultistepScheduler._sigma_to_alpha_sigma_t
+    def _sigma_to_alpha_sigma_t(self, sigma):
+        alpha_t = 1 / ((sigma**2 + 1) ** 0.5)
+        sigma_t = sigma * alpha_t
+
+        return alpha_t, sigma_t
+
+    # Copied from diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler._convert_to_karras
+    def _convert_to_karras(self, in_sigmas: torch.FloatTensor, num_inference_steps) -> torch.FloatTensor:
+        """Constructs the noise schedule of Karras et al. (2022)."""
+
+        sigma_min = self.sigma_min
+        sigma_max = self.sigma_max
+
+        sigma_min = sigma_min if sigma_min is not None else in_sigmas[-1].item()
+        sigma_max = sigma_max if sigma_max is not None else in_sigmas[0].item()
+
+        rho = 7.0  # 7.0 is the value used in the paper
+        ramp = np.linspace(0, 1, num_inference_steps)
+        min_inv_rho = sigma_min ** (1 / rho)
+        max_inv_rho = sigma_max ** (1 / rho)
+        sigmas = (max_inv_rho + ramp * (min_inv_rho - max_inv_rho)) ** rho
+        return sigmas
+
+    def convert_model_output(
+        self,
+        model_output: torch.FloatTensor,
+        *args,
+        sample: torch.FloatTensor = None,
+        **kwargs,
+    ) -> torch.FloatTensor:
+        timestep = args[0] if len(args) > 0 else kwargs.pop("timestep", None)
+        if sample is None:
+            if len(args) > 1:
+                sample = args[1]
+            else:
+                raise ValueError("missing `sample` as a required keyword argument")
+        if timestep is not None:
+            print(
+                "Passing `timesteps` is deprecated and has no effect as model output conversion is now handled via an internal counter `self.step_index`",
+            )
+
+        sigma = self.sigmas[self.step_index]
+        alpha_t, sigma_t = self._sigma_to_alpha_sigma_t(sigma)
+
+        if self.predict_x0:
+            if self.prediction_type == "epsilon":
+                x0_pred = (sample - sigma_t * model_output) / alpha_t
+            elif self.prediction_type == "sample":
+                x0_pred = model_output
+            elif self.prediction_type == "v_prediction":
+                x0_pred = alpha_t * sample - sigma_t * model_output
+            else:
+                raise ValueError(
+                    f"prediction_type given as {self.prediction_type} must be one of `epsilon`, `sample`, or"
+                    " `v_prediction` for the UniPCMultistepScheduler."
+                )
+
+            if self.thresholding:
+                x0_pred = self._threshold_sample(x0_pred)
+
+            return x0_pred
+        else:
+            if self.prediction_type == "epsilon":
+                return model_output
+            elif self.prediction_type == "sample":
+                epsilon = (sample - alpha_t * model_output) / sigma_t
+                return epsilon
+            elif self.prediction_type == "v_prediction":
+                epsilon = alpha_t * model_output + sigma_t * sample
+                return epsilon
+            else:
+                raise ValueError(
+                    f"prediction_type given as {self.prediction_type} must be one of `epsilon`, `sample`, or"
+                    " `v_prediction` for the UniPCMultistepScheduler."
+                )
+
+    def multistep_uni_p_bh_update(
+        self,
+        model_output: torch.FloatTensor,
+        *args,
+        sample: torch.FloatTensor = None,
+        order: int | None = None,
+        **kwargs,
+    ) -> torch.FloatTensor:
+        prev_timestep = args[0] if len(args) > 0 else kwargs.pop("prev_timestep", None)
+        if sample is None:
+            if len(args) > 1:
+                sample = args[1]
+            else:
+                raise ValueError(" missing `sample` as a required keyword argument")
+        if order is None:
+            if len(args) > 2:
+                order = args[2]
+            else:
+                raise ValueError(" missing `order` as a required keyword argument")
+        if prev_timestep is not None:
+            print(
+                "Passing `prev_timestep` is deprecated and has no effect as model output conversion is now handled via an internal counter `self.step_index`",
+            )
+        model_output_list = self.model_outputs
+
+        # s0 = self.timestep_list[-1]
+        m0 = model_output_list[-1]
+        x = sample
+
+        sigma_t, sigma_s0 = self.sigmas[self.step_index + 1], self.sigmas[self.step_index]
+        alpha_t, sigma_t = self._sigma_to_alpha_sigma_t(sigma_t)
+        alpha_s0, sigma_s0 = self._sigma_to_alpha_sigma_t(sigma_s0)
+
+        lambda_t = torch.log(alpha_t) - torch.log(sigma_t)
+        lambda_s0 = torch.log(alpha_s0) - torch.log(sigma_s0)
+
+        h = lambda_t - lambda_s0
+        device = sample.device
+
+        rks = []
+        d1s = []
+        for i in range(1, order):
+            si = self.step_index - i
+            mi = model_output_list[-(i + 1)]
+            alpha_si, sigma_si = self._sigma_to_alpha_sigma_t(self.sigmas[si])
+            lambda_si = torch.log(alpha_si) - torch.log(sigma_si)
+            rk = (lambda_si - lambda_s0) / h
+            rks.append(rk)
+            d1s.append((mi - m0) / rk)
+
+        rks.append(1.0)
+        rks = torch.tensor(rks, device=device)
+
+        r = []
+        b = []
+
+        hh = -h if self.predict_x0 else h
+        h_phi_1 = torch.expm1(hh)  # h\phi_1(h) = e^h - 1
+        h_phi_k = h_phi_1 / hh - 1
+
+        factorial_i = 1
+
+        if self.solver_type == "bh1":
+            b_h = hh
+        elif self.solver_type == "bh2":
+            b_h = torch.expm1(hh)
+        else:
+            raise NotImplementedError()
+
+        for i in range(1, order + 1):
+            r.append(torch.pow(rks, i - 1))
+            b.append(h_phi_k * factorial_i / b_h)
+            factorial_i *= i + 1
+            h_phi_k = h_phi_k / hh - 1 / factorial_i
+
+        r = torch.stack(r)
+        b = torch.tensor(b, device=device)
+
+        if len(d1s) > 0:
+            d1s = torch.stack(d1s, dim=1)  # (B, K)
+            # for order 2, we use a simplified version
+            if order == 2:
+                rhos_p = torch.tensor([0.5], dtype=x.dtype, device=device)
+            else:
+                rhos_p = torch.linalg.solve(r[:-1, :-1], b[:-1])
+        else:
+            d1s = None
+
+        if self.predict_x0:
+            x_t_ = sigma_t / sigma_s0 * x - alpha_t * h_phi_1 * m0
+            if d1s is not None:
+                pred_res = torch.einsum("k,bkc...->bc...", rhos_p, d1s)
+            else:
+                pred_res = 0
+            x_t = x_t_ - alpha_t * b_h * pred_res
+        else:
+            x_t_ = alpha_t / alpha_s0 * x - sigma_t * h_phi_1 * m0
+            if d1s is not None:
+                pred_res = torch.einsum("k,bkc...->bc...", rhos_p, d1s)
+            else:
+                pred_res = 0
+            x_t = x_t_ - sigma_t * b_h * pred_res
+
+        x_t = x_t.to(x.dtype)
+        return x_t
+
+    def multistep_uni_c_bh_update(
+        self,
+        this_model_output: torch.FloatTensor,
+        *args,
+        last_sample: torch.FloatTensor = None,
+        this_sample: torch.FloatTensor = None,
+        order: int | None = None,
+        **kwargs,
+    ) -> torch.FloatTensor:
+        this_timestep = args[0] if len(args) > 0 else kwargs.pop("this_timestep", None)
+        if last_sample is None:
+            if len(args) > 1:
+                last_sample = args[1]
+            else:
+                raise ValueError(" missing`last_sample` as a required keyword argument")
+        if this_sample is None:
+            if len(args) > 2:
+                this_sample = args[2]
+            else:
+                raise ValueError(" missing`this_sample` as a required keyword argument")
+        if order is None:
+            if len(args) > 3:
+                order = args[3]
+            else:
+                raise ValueError(" missing`order` as a required keyword argument")
+        if this_timestep is not None:
+            print(
+                "Passing `this_timestep` is deprecated and has no effect as model output conversion is now handled via an internal counter `self.step_index`",
+            )
+
+        model_output_list = self.model_outputs
+
+        m0 = model_output_list[-1]
+        x = last_sample
+        # x_t = this_sample
+        model_t = this_model_output
+
+        sigma_t, sigma_s0 = self.sigmas[self.step_index], self.sigmas[self.step_index - 1]
+        alpha_t, sigma_t = self._sigma_to_alpha_sigma_t(sigma_t)
+        alpha_s0, sigma_s0 = self._sigma_to_alpha_sigma_t(sigma_s0)
+
+        lambda_t = torch.log(alpha_t) - torch.log(sigma_t)
+        lambda_s0 = torch.log(alpha_s0) - torch.log(sigma_s0)
+
+        h = lambda_t - lambda_s0
+        device = this_sample.device
+
+        rks = []
+        d1s = []
+        for i in range(1, order):
+            si = self.step_index - (i + 1)
+            mi = model_output_list[-(i + 1)]
+            alpha_si, sigma_si = self._sigma_to_alpha_sigma_t(self.sigmas[si])
+            lambda_si = torch.log(alpha_si) - torch.log(sigma_si)
+            rk = (lambda_si - lambda_s0) / h
+            rks.append(rk)
+            d1s.append((mi - m0) / rk)
+
+        rks.append(1.0)
+        rks = torch.tensor(rks, device=device)
+
+        r = []
+        b = []
+
+        hh = -h if self.predict_x0 else h
+        h_phi_1 = torch.expm1(hh)  # h\phi_1(h) = e^h - 1
+        h_phi_k = h_phi_1 / hh - 1
+
+        factorial_i = 1
+
+        if self.solver_type == "bh1":
+            b_h = hh
+        elif self.solver_type == "bh2":
+            b_h = torch.expm1(hh)
+        else:
+            raise NotImplementedError()
+
+        for i in range(1, order + 1):
+            r.append(torch.pow(rks, i - 1))
+            b.append(h_phi_k * factorial_i / b_h)
+            factorial_i *= i + 1
+            h_phi_k = h_phi_k / hh - 1 / factorial_i
+
+        r = torch.stack(r)
+        b = torch.tensor(b, device=device)
+
+        if len(d1s) > 0:
+            d1s = torch.stack(d1s, dim=1)
+        else:
+            d1s = None
+
+        # for order 1, we use a simplified version
+        if order == 1:
+            rhos_c = torch.tensor([0.5], dtype=x.dtype, device=device)
+        else:
+            rhos_c = torch.linalg.solve(r, b)
+
+        if self.predict_x0:
+            x_t_ = sigma_t / sigma_s0 * x - alpha_t * h_phi_1 * m0
+            if d1s is not None:
+                corr_res = torch.einsum("k,bkc...->bc...", rhos_c[:-1], d1s)
+            else:
+                corr_res = 0
+            d1_t = model_t - m0
+            x_t = x_t_ - alpha_t * b_h * (corr_res + rhos_c[-1] * d1_t)
+        else:
+            x_t_ = alpha_t / alpha_s0 * x - sigma_t * h_phi_1 * m0
+            if d1s is not None:
+                corr_res = torch.einsum("k,bkc...->bc...", rhos_c[:-1], d1s)
+            else:
+                corr_res = 0
+            d1_t = model_t - m0
+            x_t = x_t_ - sigma_t * b_h * (corr_res + rhos_c[-1] * d1_t)
+        x_t = x_t.to(x.dtype)
+        return x_t
+
+    def _init_step_index(self, timestep):
+        if isinstance(timestep, torch.Tensor):
+            timestep = timestep.to(self.timesteps.device)
+
+        index_candidates = (self.timesteps == timestep).nonzero()
+
+        if len(index_candidates) == 0:
+            step_index = len(self.timesteps) - 1
+        # The sigma index that is taken for the **very** first `step`
+        # is always the second index (or the last index if there is only 1)
+        # This way we can ensure we don't accidentally skip a sigma in
+        # case we start in the middle of the denoising schedule (e.g. for image-to-image)
+        elif len(index_candidates) > 1:
+            step_index = index_candidates[1].item()
+        else:
+            step_index = index_candidates[0].item()
+
+        self._step_index = step_index
+
+    def step(
+        self,
+        model_output: torch.FloatTensor,
+        timestep: int,
+        sample: torch.FloatTensor,
+        return_dict: bool = True,
+    ):
+        if self.num_inference_steps is None:
+            raise ValueError(
+                "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
+            )
+
+        if self.step_index is None:
+            self._init_step_index(timestep)
+
+        use_corrector = (
+            self.step_index > 0 and self.step_index - 1 not in self.disable_corrector and self.last_sample is not None
+        )
+
+        model_output_convert = self.convert_model_output(model_output, sample=sample)
+        if use_corrector:
+            sample = self.multistep_uni_c_bh_update(
+                this_model_output=model_output_convert,
+                last_sample=self.last_sample,
+                this_sample=sample,
+                order=self.this_order,
+            )
+
+        for i in range(self.solver_order - 1):
+            self.model_outputs[i] = self.model_outputs[i + 1]
+            self.timestep_list[i] = self.timestep_list[i + 1]
+
+        self.model_outputs[-1] = model_output_convert
+        self.timestep_list[-1] = timestep
+
+        if self.lower_order_final:
+            this_order = min(self.solver_order, len(self.timesteps) - self.step_index)
+        else:
+            this_order = self.solver_order
+
+        self.this_order = min(this_order, self.lower_order_nums + 1)  # warmup for multistep
+        assert self.this_order > 0
+
+        self.last_sample = sample
+        prev_sample = self.multistep_uni_p_bh_update(
+            model_output=model_output,  # pass the original non-converted model output, in case solver-p is used
+            sample=sample,
+            order=self.this_order,
+        )
+
+        if self.lower_order_nums < self.solver_order:
+            self.lower_order_nums += 1
+
+        # upon completion increase step index by one
+        self._step_index += 1
+
+        if not return_dict:
+            return (prev_sample,)
+
+        return prev_sample
+
+    def scale_model_input(self, sample: torch.FloatTensor, *args, **kwargs) -> torch.FloatTensor:
+        return sample
+
+    def add_noise(
+        self,
+        original_samples: torch.FloatTensor,
+        noise: torch.FloatTensor,
+        idx,
+        timesteps: torch.IntTensor,
+    ) -> torch.FloatTensor:
+        # Make sure sigmas and timesteps have the same device and dtype as original_samples
+        sigmas = self.sigmas.to(device=original_samples.device, dtype=original_samples.dtype)
+        schedule_timesteps = self.timesteps.to(original_samples.device)
+        timesteps = timesteps.to(original_samples.device)
+
+        step_indices = [(schedule_timesteps == t).nonzero().item() for t in timesteps]
+        sigma = sigmas[step_indices].flatten()
+        while len(sigma.shape) < len(original_samples.shape):
+            sigma = sigma.unsqueeze(-1)
+
+        alpha_t, sigma_t = self._sigma_to_alpha_sigma_t(sigma)
+        noisy_samples = alpha_t * original_samples + sigma_t * noise
+        return noisy_samples
+
+    def configure(self):
+        pass
+
+    def __len__(self):
+        return self.num_train_timesteps
+
+
+# Modified from diffusers.schedulers.LCMScheduler
+class LCMScheduler:
+    def __init__(
+        self,
+        device="cuda",
+        num_train_timesteps: int = 1000,
+        beta_start: float = 0.00085,
+        beta_end: float = 0.012,
+        original_inference_steps: int = 50,
+        clip_sample: bool = False,
+        clip_sample_range: float = 1.0,
+        steps_offset: int = 0,
+        prediction_type: str = "epsilon",
+        thresholding: bool = False,
+        dynamic_thresholding_ratio: float = 0.995,
+        sample_max_value: float = 1.0,
+        timestep_spacing: str = "leading",
+        timestep_scaling: float = 10.0,
+    ):
+        self.device = device
+        self.betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
+        self.alphas = 1.0 - self.betas
+        self.alphas_cumprod = torch.cumprod(self.alphas, dim=0)
+        self.final_alpha_cumprod = self.alphas_cumprod[0]
+        # standard deviation of the initial noise distribution
+        self.init_noise_sigma = 1.0
+        # setable values
+        self.num_inference_steps = None
+        self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy().astype(np.int64))
+
+        self.num_train_timesteps = num_train_timesteps
+        self.clip_sample = clip_sample
+        self.clip_sample_range = clip_sample_range
+        self.steps_offset = steps_offset
+        self.prediction_type = prediction_type
+        self.thresholding = thresholding
+        self.timestep_spacing = timestep_spacing
+        self.timestep_scaling = timestep_scaling
+        self.original_inference_steps = original_inference_steps
+        self.dynamic_thresholding_ratio = dynamic_thresholding_ratio
+        self.sample_max_value = sample_max_value
+
+        self._step_index = None
+
+    # Copied from diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler._init_step_index
+    def _init_step_index(self, timestep):
+        if isinstance(timestep, torch.Tensor):
+            timestep = timestep.to(self.timesteps.device)
+
+        index_candidates = (self.timesteps == timestep).nonzero()
+
+        if len(index_candidates) > 1:
+            step_index = index_candidates[1]
+        else:
+            step_index = index_candidates[0]
+
+        self._step_index = step_index.item()
+
+    @property
+    def step_index(self):
+        return self._step_index
+
+    def scale_model_input(self, sample: torch.FloatTensor, *args, **kwargs) -> torch.FloatTensor:
+        return sample
+
+    # Copied from diffusers.schedulers.scheduling_ddpm.DDPMScheduler._threshold_sample
+    def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatTensor:
+        dtype = sample.dtype
+        batch_size, channels, *remaining_dims = sample.shape
+
+        if dtype not in (torch.float32, torch.float64):
+            sample = sample.float()  # upcast for quantile calculation, and clamp not implemented for cpu half
+
+        # Flatten sample for doing quantile calculation along each image
+        sample = sample.reshape(batch_size, channels * np.prod(remaining_dims))
+
+        abs_sample = sample.abs()  # "a certain percentile absolute pixel value"
+
+        s = torch.quantile(abs_sample, self.dynamic_thresholding_ratio, dim=1)
+        s = torch.clamp(
+            s, min=1, max=self.sample_max_value
+        )  # When clamped to min=1, equivalent to standard clipping to [-1, 1]
+        s = s.unsqueeze(1)  # (batch_size, 1) because clamp will broadcast along dim=0
+        sample = torch.clamp(sample, -s, s) / s  # "we threshold xt0 to the range [-s, s] and then divide by s"
+
+        sample = sample.reshape(batch_size, channels, *remaining_dims)
+        sample = sample.to(dtype)
+
+        return sample
+
+    def set_timesteps(
+        self,
+        num_inference_steps: int,
+        strength: int = 1.0,
+    ):
+        assert num_inference_steps <= self.num_train_timesteps
+
+        self.num_inference_steps = num_inference_steps
+        original_steps = self.original_inference_steps
+
+        assert original_steps <= self.num_train_timesteps
+        assert num_inference_steps <= original_steps
+
+        # LCM Timesteps Setting
+        # Currently, only linear spacing is supported.
+        c = self.num_train_timesteps // original_steps
+        # LCM Training Steps Schedule
+        lcm_origin_timesteps = np.asarray(list(range(1, int(original_steps * strength) + 1))) * c - 1
+        skipping_step = len(lcm_origin_timesteps) // num_inference_steps
+        # LCM Inference Steps Schedule
+        timesteps = lcm_origin_timesteps[::-skipping_step][:num_inference_steps]
+
+        self.timesteps = torch.from_numpy(timesteps.copy()).to(device=self.device, dtype=torch.long)
+
+        self._step_index = None
+
+    def get_scalings_for_boundary_condition_discrete(self, timestep):
+        self.sigma_data = 0.5  # Default: 0.5
+        scaled_timestep = timestep * self.timestep_scaling
+
+        c_skip = self.sigma_data**2 / (scaled_timestep**2 + self.sigma_data**2)
+        c_out = scaled_timestep / (scaled_timestep**2 + self.sigma_data**2) ** 0.5
+        return c_skip, c_out
+
+    def step(
+        self,
+        model_output: torch.FloatTensor,
+        timestep: int,
+        sample: torch.FloatTensor,
+        generator: torch.Generator | None = None,
+    ):
+        if self.num_inference_steps is None:
+            raise ValueError(
+                "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
+            )
+
+        if self.step_index is None:
+            self._init_step_index(timestep)
+
+        # 1. get previous step value
+        prev_step_index = self.step_index + 1
+        if prev_step_index < len(self.timesteps):
+            prev_timestep = self.timesteps[prev_step_index]
+        else:
+            prev_timestep = timestep
+
+        # 2. compute alphas, betas
+        alpha_prod_t = self.alphas_cumprod[timestep]
+        alpha_prod_t_prev = self.alphas_cumprod[prev_timestep] if prev_timestep >= 0 else self.final_alpha_cumprod
+
+        beta_prod_t = 1 - alpha_prod_t
+        beta_prod_t_prev = 1 - alpha_prod_t_prev
+
+        # 3. Get scalings for boundary conditions
+        c_skip, c_out = self.get_scalings_for_boundary_condition_discrete(timestep)
+
+        # 4. Compute the predicted original sample x_0 based on the model parameterization
+        if self.prediction_type == "epsilon":  # noise-prediction
+            predicted_original_sample = (sample - beta_prod_t.sqrt() * model_output) / alpha_prod_t.sqrt()
+        elif self.prediction_type == "sample":  # x-prediction
+            predicted_original_sample = model_output
+        elif self.prediction_type == "v_prediction":  # v-prediction
+            predicted_original_sample = alpha_prod_t.sqrt() * sample - beta_prod_t.sqrt() * model_output
+        else:
+            raise ValueError(
+                f"prediction_type given as {self.prediction_type} must be one of `epsilon`, `sample` or"
+                " `v_prediction` for `LCMScheduler`."
+            )
+
+        # 5. Clip or threshold "predicted x_0"
+        if self.thresholding:
+            predicted_original_sample = self._threshold_sample(predicted_original_sample)
+        elif self.clip_sample:
+            predicted_original_sample = predicted_original_sample.clamp(-self.clip_sample_range, self.clip_sample_range)
+
+        # 6. Denoise model output using boundary conditions
+        denoised = c_out * predicted_original_sample + c_skip * sample
+
+        # 7. Sample and inject noise z ~ N(0, I) for MultiStep Inference
+        # Noise is not used on the final timestep of the timestep schedule.
+        # This also means that noise is not used for one-step sampling.
+        if self.step_index != self.num_inference_steps - 1:
+            noise = torch.randn(
+                model_output.shape, device=model_output.device, dtype=denoised.dtype, generator=generator
+            )
+            prev_sample = alpha_prod_t_prev.sqrt() * denoised + beta_prod_t_prev.sqrt() * noise
+        else:
+            prev_sample = denoised
+
+        # upon completion increase step index by one
+        self._step_index += 1
+
+        return (prev_sample,)
+
+    # Copied from diffusers.schedulers.scheduling_ddpm.DDPMScheduler.add_noise
+    def add_noise(
+        self,
+        original_samples: torch.FloatTensor,
+        noise: torch.FloatTensor,
+        timesteps: torch.IntTensor,
+    ) -> torch.FloatTensor:
+        # Make sure alphas_cumprod and timestep have same device and dtype as original_samples
+        alphas_cumprod = self.alphas_cumprod.to(device=original_samples.device, dtype=original_samples.dtype)
+        timesteps = timesteps.to(original_samples.device)
+
+        sqrt_alpha_prod = alphas_cumprod[timesteps] ** 0.5
+        sqrt_alpha_prod = sqrt_alpha_prod.flatten()
+        while len(sqrt_alpha_prod.shape) < len(original_samples.shape):
+            sqrt_alpha_prod = sqrt_alpha_prod.unsqueeze(-1)
+
+        sqrt_one_minus_alpha_prod = (1 - alphas_cumprod[timesteps]) ** 0.5
+        sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.flatten()
+        while len(sqrt_one_minus_alpha_prod.shape) < len(original_samples.shape):
+            sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.unsqueeze(-1)
+
+        noisy_samples = sqrt_alpha_prod * original_samples + sqrt_one_minus_alpha_prod * noise
+        return noisy_samples
+
+    def configure(self):
+        pass
+
+    def __len__(self):
+        return self.num_train_timesteps
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder.py
new file mode 100644
index 0000000000000000000000000000000000000000..248a00c49fed69d4b01f499a8b5570990437dd03
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder.py
@@ -0,0 +1,295 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import hashlib
+import os
+from enum import Enum
+
+import torch
+from diffusion_models import CLIP, VAE, CLIPWithProj, PipelineInfo, UNet, UNetXL
+
+
+class EngineType(Enum):
+    ORT_CUDA = 0  # ONNX Runtime CUDA Execution Provider
+    ORT_TRT = 1  # ONNX Runtime TensorRT Execution Provider
+    TRT = 2  # TensorRT
+    TORCH = 3  # PyTorch
+
+
+def get_engine_type(name: str) -> EngineType:
+    name_to_type = {
+        "ORT_CUDA": EngineType.ORT_CUDA,
+        "ORT_TRT": EngineType.ORT_TRT,
+        "TRT": EngineType.TRT,
+        "TORCH": EngineType.TORCH,
+    }
+    return name_to_type[name]
+
+
+class EngineBuilder:
+    def __init__(
+        self,
+        engine_type: EngineType,
+        pipeline_info: PipelineInfo,
+        device="cuda",
+        max_batch_size=16,
+        use_cuda_graph=False,
+    ):
+        """
+        Initializes the Engine Builder.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            device (str | torch.device):
+                device to run engine
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+        """
+        self.engine_type = engine_type
+        self.pipeline_info = pipeline_info
+        self.max_batch_size = max_batch_size
+        self.use_cuda_graph = use_cuda_graph
+        self.device = torch.device(device)
+        self.torch_device = torch.device(device, torch.cuda.current_device())
+        self.stages = pipeline_info.stages()
+
+        self.vae_torch_fallback = self.pipeline_info.vae_torch_fallback() and self.engine_type != EngineType.TORCH
+        self.custom_fp16_vae = self.pipeline_info.custom_fp16_vae()
+
+        self.models = {}
+        self.engines = {}
+        self.torch_models = {}
+        self.use_vae_slicing = False
+
+        self.torch_sdpa = getattr(torch.nn.functional, "scaled_dot_product_attention", None)
+
+    def enable_vae_slicing(self):
+        self.use_vae_slicing = True
+
+    def disable_torch_spda(self):
+        if hasattr(torch.nn.functional, "scaled_dot_product_attention"):
+            delattr(torch.nn.functional, "scaled_dot_product_attention")
+
+    def enable_torch_spda(self):
+        if (not hasattr(torch.nn.functional, "scaled_dot_product_attention")) and self.torch_sdpa:
+            torch.nn.functional.scaled_dot_product_attention = self.torch_sdpa
+
+    def teardown(self):
+        for engine in self.engines.values():
+            del engine
+        self.engines = {}
+
+    def get_diffusers_module_name(self, model_name):
+        name_mapping = {
+            "clip": "text_encoder",
+            "clip2": "text_encoder_2",
+            "unet": "unet",
+            "unetxl": "unet",
+            "vae": "vae_decoder",
+        }
+        return name_mapping.get(model_name, model_name)
+
+    def get_cached_model_name(self, model_name):
+        model_name = self.get_diffusers_module_name(model_name)
+        is_unet = model_name == "unet"
+        hash_source = []
+        if model_name in ["text_encoder", "text_encoder_2", "unet"] and self.pipeline_info.lora_weights:
+            if self.pipeline_info.lora_weights in [
+                "latent-consistency/lcm-lora-sdxl",
+                "latent-consistency/lcm-lora-sdv1-5",
+            ]:
+                if is_unet:
+                    model_name = "unet_lcm-lora"
+            else:
+                model_name = model_name + "_lora"
+                hash_source.append(self.pipeline_info.lora_weights)
+
+        # TODO(tianleiwu): save custom model to a directory named by its original model.
+        if is_unet and self.pipeline_info.custom_unet():
+            model_name = model_name + "_lcm"
+
+        if model_name in ["unet"] and self.pipeline_info.controlnet:
+            model_name = model_name + "_" + "_".join(self.pipeline_info.controlnet)
+
+        if hash_source:
+            model_name += "_" + hashlib.sha256("\t".join(hash_source).encode("utf-8")).hexdigest()[:8]
+
+        # TODO: When we support original VAE, we shall save custom VAE to another directory.
+
+        if self.pipeline_info.is_inpaint():
+            model_name += "_inpaint"
+        return model_name
+
+    def get_model_dir(self, model_name, root_dir, opt=True, suffix="", create=True):
+        engine_name = self.engine_type.name.lower()
+        if engine_name != "ort_cuda" and not suffix:
+            suffix = f".{engine_name}" if opt else ""
+        directory_name = self.get_cached_model_name(model_name) + suffix
+        onnx_model_dir = os.path.join(root_dir, directory_name)
+        if create:
+            os.makedirs(onnx_model_dir, exist_ok=True)
+        return onnx_model_dir
+
+    def get_onnx_path(self, model_name, onnx_dir, opt=True, suffix=""):
+        onnx_model_dir = self.get_model_dir(model_name, onnx_dir, opt=opt, suffix=suffix)
+        return os.path.join(onnx_model_dir, "model.onnx")
+
+    def get_engine_path(self, engine_dir, model_name, profile_id):
+        return os.path.join(engine_dir, self.get_cached_model_name(model_name) + profile_id)
+
+    def load_pipeline_with_lora(self):
+        """Load text encoders and UNet with diffusers pipeline"""
+        from diffusers import DiffusionPipeline  # noqa: PLC0415
+
+        pipeline = DiffusionPipeline.from_pretrained(
+            self.pipeline_info.name(),
+            variant="fp16",
+            torch_dtype=torch.float16,
+        )
+        pipeline.load_lora_weights(self.pipeline_info.lora_weights)
+        pipeline.fuse_lora(lora_scale=self.pipeline_info.lora_scale)
+
+        del pipeline.vae
+        pipeline.vae = None
+        return pipeline
+
+    def get_or_load_model(self, pipeline, model_name, model_obj, framework_model_dir):
+        if model_name in ["clip", "clip2", "unet", "unetxl"] and pipeline:
+            if model_name == "clip":
+                model = pipeline.text_encoder
+                pipeline.text_encoder = None
+            elif model_name == "clip2":
+                model = pipeline.text_encoder_2
+                pipeline.text_encoder_2 = None
+            else:
+                model = pipeline.unet
+                pipeline.unet = None
+        else:
+            model = model_obj.load_model(framework_model_dir)
+
+        return model.to(self.torch_device)
+
+    def load_models(self, framework_model_dir: str):
+        # For TRT or ORT_TRT, we will export fp16 torch model for UNet and VAE
+        # For ORT_CUDA, we export fp32 model first, then optimize to fp16.
+        export_fp16 = self.engine_type in [EngineType.ORT_TRT, EngineType.TRT]
+
+        if "clip" in self.stages:
+            self.models["clip"] = CLIP(
+                self.pipeline_info,
+                None,  # not loaded yet
+                device=self.torch_device,
+                max_batch_size=self.max_batch_size,
+                clip_skip=0,
+            )
+
+        if "clip2" in self.stages:
+            self.models["clip2"] = CLIPWithProj(
+                self.pipeline_info,
+                None,  # not loaded yet
+                device=self.torch_device,
+                max_batch_size=self.max_batch_size,
+                clip_skip=0,
+            )
+
+        if "unet" in self.stages:
+            self.models["unet"] = UNet(
+                self.pipeline_info,
+                None,  # not loaded yet
+                device=self.torch_device,
+                fp16=export_fp16,
+                max_batch_size=self.max_batch_size,
+                unet_dim=(9 if self.pipeline_info.is_inpaint() else 4),
+            )
+
+        if "unetxl" in self.stages:
+            self.models["unetxl"] = UNetXL(
+                self.pipeline_info,
+                None,  # not loaded yet
+                device=self.torch_device,
+                fp16=export_fp16,
+                max_batch_size=self.max_batch_size,
+                unet_dim=4,
+                time_dim=(5 if self.pipeline_info.is_xl_refiner() else 6),
+            )
+
+        # VAE Decoder
+        if "vae" in self.stages:
+            self.models["vae"] = VAE(
+                self.pipeline_info,
+                None,  # not loaded yet
+                device=self.torch_device,
+                max_batch_size=self.max_batch_size,
+                fp16=export_fp16,
+                custom_fp16_vae=self.custom_fp16_vae,
+            )
+
+            if self.vae_torch_fallback:
+                self.torch_models["vae"] = self.models["vae"].load_model(framework_model_dir)
+
+    def load_resources(self, image_height, image_width, batch_size):
+        if self.engine_type == EngineType.TORCH:
+            return
+
+        # Allocate buffers for I/O bindings
+        for model_name, obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+            slice_size = 1 if (model_name == "vae" and self.use_vae_slicing) else batch_size
+            self.engines[model_name].allocate_buffers(
+                shape_dict=obj.get_shape_dict(slice_size, image_height, image_width), device=self.torch_device
+            )
+
+    def _vae_decode(self, latents):
+        if self.engine_type == EngineType.TORCH:
+            if self.pipeline_info.is_xl() and not self.custom_fp16_vae:  # need upcast
+                latents = latents.to(dtype=torch.float32)
+                images = self.engines["vae"](latents)["sample"]
+            else:
+                images = self.engines["vae"](latents)["sample"]
+        elif self.vae_torch_fallback:
+            if not self.custom_fp16_vae:
+                latents = latents.to(dtype=torch.float32)
+                self.torch_models["vae"] = self.torch_models["vae"].to(dtype=torch.float32)
+            images = self.torch_models["vae"](latents)["sample"]
+        else:
+            if self.pipeline_info.is_xl() and not self.custom_fp16_vae:  # need upcast
+                images = self.run_engine("vae", {"latent": latents.to(dtype=torch.float32)})["images"]
+            else:
+                images = self.run_engine("vae", {"latent": latents})["images"]
+
+        return images
+
+    def vae_decode(self, latents):
+        if self.use_vae_slicing:
+            # The output tensor points to same buffer. Need clone it to avoid overwritten.
+            decoded_slices = [self._vae_decode(z_slice).clone() for z_slice in latents.split(1)]
+            return torch.cat(decoded_slices)
+
+        return self._vae_decode(latents)
+
+
+def get_engine_paths(
+    work_dir: str, pipeline_info: PipelineInfo, engine_type: EngineType, framework_model_dir: str | None = None
+):
+    root_dir = work_dir or "."
+    short_name = pipeline_info.short_name()
+
+    # When both ORT_CUDA and ORT_TRT/TRT is used, we shall make sub directory for each engine since
+    # ORT_CUDA need fp32 torch model, while ORT_TRT/TRT use fp16 torch model.
+    onnx_dir = os.path.join(root_dir, engine_type.name, short_name, "onnx")
+    engine_dir = os.path.join(root_dir, engine_type.name, short_name, "engine")
+    output_dir = os.path.join(root_dir, engine_type.name, short_name, "output")
+
+    timing_cache = os.path.join(root_dir, engine_type.name, "timing_cache")
+
+    # Shared among ORT_CUDA, ORT_TRT and TRT engines, and need use load_model(..., always_download_fp16=True)
+    # So that the shared model is always fp16.
+    if framework_model_dir is None:
+        framework_model_dir = os.path.join(root_dir, "torch_model")
+
+    return onnx_dir, engine_dir, output_dir, framework_model_dir, timing_cache
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_cuda.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_cuda.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ee5622c671a1901ce016179b7e8350bc64c56ab
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_cuda.py
@@ -0,0 +1,387 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import gc
+import logging
+import os
+
+import onnx
+import torch
+from diffusion_models import PipelineInfo
+from engine_builder import EngineBuilder, EngineType
+from packaging import version
+
+import onnxruntime as ort
+from onnxruntime.transformers.io_binding_helper import CudaSession, GpuBindingManager
+from onnxruntime.transformers.onnx_model import OnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class OrtCudaEngine:
+    def __init__(
+        self,
+        onnx_path,
+        device_id: int = 0,
+        enable_cuda_graph: bool = False,
+        disable_optimization: bool = False,
+        max_cuda_graphs: int = 1,
+    ):
+        self.onnx_path = onnx_path
+        self.provider = "CUDAExecutionProvider"
+        self.stream = torch.cuda.current_stream().cuda_stream
+        self.provider_options = CudaSession.get_cuda_provider_options(device_id, enable_cuda_graph, self.stream)
+        session_options = ort.SessionOptions()
+
+        # When the model has been optimized by onnxruntime, we can disable optimization to save session creation time.
+        if disable_optimization:
+            session_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
+
+        logger.info("creating CUDA EP session for %s", onnx_path)
+        ort_session = ort.InferenceSession(
+            onnx_path,
+            session_options,
+            providers=[
+                (self.provider, self.provider_options),
+                "CPUExecutionProvider",
+            ],
+        )
+        logger.info("created CUDA EP session for %s", onnx_path)
+
+        device = torch.device("cuda", device_id)
+        self.enable_cuda_graph = enable_cuda_graph
+
+        # Support multiple CUDA graphs for different input shapes.
+        # For clip2 model that disabled cuda graph, max_cuda_graphs is updated to 0 here.
+        self.gpu_binding_manager = GpuBindingManager(
+            ort_session=ort_session,
+            device=device,
+            stream=self.stream,
+            max_cuda_graphs=max_cuda_graphs if enable_cuda_graph else 0,
+        )
+
+        self.current_gpu_binding = None
+
+    def metadata(self, name: str):
+        data = {}
+        if self.current_gpu_binding is not None:
+            if self.current_gpu_binding.last_run_gpu_graph_id >= 0:
+                data[f"{name}.gpu_graph_id"] = self.current_gpu_binding.last_run_gpu_graph_id
+        return data
+
+    def infer(self, feed_dict: dict[str, torch.Tensor]):
+        return self.current_gpu_binding.infer(feed_dict=feed_dict, disable_cuda_graph_in_run=not self.enable_cuda_graph)
+
+    def allocate_buffers(self, shape_dict, device):
+        self.current_gpu_binding = self.gpu_binding_manager.get_binding(
+            shape_dict=shape_dict, use_cuda_graph=self.enable_cuda_graph
+        )
+
+
+class _ModelConfig:
+    """
+    Configuration of one model (like Clip, UNet etc) on ONNX export and optimization for CUDA provider.
+    For example, if you want to use fp32 in layer normalization, set the following:
+        force_fp32_ops=["SkipLayerNormalization", "LayerNormalization"]
+    """
+
+    def __init__(
+        self,
+        onnx_opset_version: int,
+        use_cuda_graph: bool,
+        fp16: bool = True,
+        force_fp32_ops: list[str] | None = None,
+        optimize_by_ort: bool = True,
+    ):
+        self.onnx_opset_version = onnx_opset_version
+        self.use_cuda_graph = use_cuda_graph
+        self.fp16 = fp16
+        self.force_fp32_ops = force_fp32_ops
+        self.optimize_by_ort = optimize_by_ort
+
+
+class OrtCudaEngineBuilder(EngineBuilder):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        max_batch_size=16,
+        device="cuda",
+        use_cuda_graph=False,
+    ):
+        """
+        Initializes the ONNX Runtime TensorRT ExecutionProvider Engine Builder.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            device (str):
+                device to run.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+        """
+        super().__init__(
+            EngineType.ORT_CUDA,
+            pipeline_info,
+            max_batch_size=max_batch_size,
+            device=device,
+            use_cuda_graph=use_cuda_graph,
+        )
+
+        self.model_config = {}
+
+    def _configure(
+        self,
+        model_name: str,
+        onnx_opset_version: int,
+        use_cuda_graph: bool,
+        fp16: bool = True,
+        force_fp32_ops: list[str] | None = None,
+        optimize_by_ort: bool = True,
+    ):
+        self.model_config[model_name] = _ModelConfig(
+            onnx_opset_version,
+            use_cuda_graph,
+            fp16=fp16,
+            force_fp32_ops=force_fp32_ops,
+            optimize_by_ort=optimize_by_ort,
+        )
+
+    def configure_xl(self, onnx_opset_version: int):
+        self._configure(
+            "clip",
+            onnx_opset_version=onnx_opset_version,
+            use_cuda_graph=self.use_cuda_graph,
+        )
+        self._configure(
+            "clip2",
+            onnx_opset_version=onnx_opset_version,  # TODO: ArgMax-12 is not implemented in CUDA
+            use_cuda_graph=False,  # TODO: fix Runtime Error with cuda graph
+        )
+        self._configure(
+            "unetxl",
+            onnx_opset_version=onnx_opset_version,
+            use_cuda_graph=self.use_cuda_graph,
+        )
+
+        self._configure(
+            "vae",
+            onnx_opset_version=onnx_opset_version,
+            use_cuda_graph=self.use_cuda_graph,
+        )
+
+    def optimized_onnx_path(self, engine_dir, model_name):
+        suffix = "" if self.model_config[model_name].fp16 else ".fp32"
+        return self.get_onnx_path(model_name, engine_dir, opt=True, suffix=suffix)
+
+    def import_diffusers_engine(self, diffusers_onnx_dir: str, engine_dir: str):
+        """Import optimized onnx models for diffusers from Olive or optimize_pipeline tools.
+
+        Args:
+            diffusers_onnx_dir (str): optimized onnx directory of Olive
+            engine_dir (str): the directory to store imported onnx
+        """
+        if version.parse(ort.__version__) < version.parse("1.17.0"):
+            print("Skip importing since onnxruntime-gpu version < 1.17.0.")
+            return
+
+        for model_name, model_obj in self.models.items():
+            onnx_import_path = self.optimized_onnx_path(diffusers_onnx_dir, model_name)
+            if not os.path.exists(onnx_import_path):
+                print(f"{onnx_import_path} not existed. Skip importing.")
+                continue
+
+            onnx_opt_path = self.optimized_onnx_path(engine_dir, model_name)
+            if os.path.exists(onnx_opt_path):
+                print(f"{onnx_opt_path} existed. Skip importing.")
+                continue
+
+            if model_name == "vae" and self.pipeline_info.is_xl():
+                print(f"Skip importing VAE since it is not fully compatible with float16: {onnx_import_path}.")
+                continue
+
+            model = OnnxModel(onnx.load(onnx_import_path, load_external_data=True))
+
+            if model_name in ["clip", "clip2"]:
+                hidden_states_per_layer = []
+                for output in model.graph().output:
+                    if output.name.startswith("hidden_states."):
+                        hidden_states_per_layer.append(output.name)
+                if hidden_states_per_layer:
+                    kept_hidden_states = hidden_states_per_layer[-2 - model_obj.clip_skip]
+                    model.rename_graph_output(kept_hidden_states, "hidden_states")
+
+                model.rename_graph_output(
+                    "last_hidden_state" if model_name == "clip" else "text_embeds", "text_embeddings"
+                )
+                model.prune_graph(
+                    ["text_embeddings", "hidden_states"] if hidden_states_per_layer else ["text_embeddings"]
+                )
+
+                if model_name == "clip2":
+                    model.change_graph_input_type(model.find_graph_input("input_ids"), onnx.TensorProto.INT32)
+
+                model.save_model_to_file(onnx_opt_path, use_external_data_format=(model_name == "clip2"))
+            elif model_name in ["unet", "unetxl"]:
+                model.rename_graph_output("out_sample", "latent")
+                model.save_model_to_file(onnx_opt_path, use_external_data_format=True)
+
+            del model
+            continue
+
+    def build_engines(
+        self,
+        engine_dir: str,
+        framework_model_dir: str,
+        onnx_dir: str,
+        tmp_dir: str | None = None,
+        onnx_opset_version: int = 17,
+        device_id: int = 0,
+        save_fp32_intermediate_model: bool = False,
+        import_engine_dir: str | None = None,
+        max_cuda_graphs: int = 1,
+    ):
+        self.torch_device = torch.device("cuda", device_id)
+        self.load_models(framework_model_dir)
+
+        if not os.path.isdir(engine_dir):
+            os.makedirs(engine_dir)
+
+        if not os.path.isdir(onnx_dir):
+            os.makedirs(onnx_dir)
+
+        # Add default configuration if missing
+        if self.pipeline_info.is_xl():
+            self.configure_xl(onnx_opset_version)
+        for model_name in self.models:
+            if model_name not in self.model_config:
+                self.model_config[model_name] = _ModelConfig(onnx_opset_version, self.use_cuda_graph)
+
+        # Import Engine
+        if import_engine_dir:
+            if self.pipeline_info.is_xl():
+                self.import_diffusers_engine(import_engine_dir, engine_dir)
+            else:
+                print(f"Only support importing SDXL onnx. Ignore --engine-dir {import_engine_dir}")
+
+        # Load lora only when we need export text encoder or UNet to ONNX.
+        load_lora = False
+        if self.pipeline_info.lora_weights:
+            for model_name in self.models:
+                if model_name not in ["clip", "clip2", "unet", "unetxl"]:
+                    continue
+                onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+                onnx_opt_path = self.optimized_onnx_path(engine_dir, model_name)
+                if not os.path.exists(onnx_opt_path):
+                    if not os.path.exists(onnx_path):
+                        load_lora = True
+                        break
+
+        # Export models to ONNX
+        self.disable_torch_spda()
+        pipe = self.load_pipeline_with_lora() if load_lora else None
+
+        for model_name, model_obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+
+            onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+            onnx_opt_path = self.optimized_onnx_path(engine_dir, model_name)
+            if not os.path.exists(onnx_opt_path):
+                if not os.path.exists(onnx_path):
+                    print("----")
+                    logger.info("Exporting model: %s", onnx_path)
+
+                    model = self.get_or_load_model(pipe, model_name, model_obj, framework_model_dir)
+                    model = model.to(torch.float32)
+
+                    with torch.inference_mode():
+                        # For CUDA EP, export FP32 onnx since some graph fusion only supports fp32 graph pattern.
+                        # Export model with sample of batch size 1, image size 512 x 512
+                        inputs = model_obj.get_sample_input(1, 512, 512)
+
+                        torch.onnx.export(
+                            model,
+                            inputs,
+                            onnx_path,
+                            export_params=True,
+                            opset_version=self.model_config[model_name].onnx_opset_version,
+                            do_constant_folding=True,
+                            input_names=model_obj.get_input_names(),
+                            output_names=model_obj.get_output_names(),
+                            dynamic_axes=model_obj.get_dynamic_axes(),
+                        )
+                    del model
+                    torch.cuda.empty_cache()
+                    gc.collect()
+                else:
+                    logger.info("Found cached model: %s", onnx_path)
+
+                # Generate fp32 optimized model.
+                # If final target is fp16 model, we save fp32 optimized model so that it is easy to tune
+                # fp16 conversion. That could save a lot of time in developing.
+                use_fp32_intermediate = save_fp32_intermediate_model and self.model_config[model_name].fp16
+                onnx_fp32_path = onnx_path
+                if use_fp32_intermediate:
+                    onnx_fp32_path = self.get_onnx_path(model_name, engine_dir, opt=True, suffix=".fp32")
+                    if not os.path.exists(onnx_fp32_path):
+                        print("------")
+                        logger.info("Generating optimized model: %s", onnx_fp32_path)
+                        model_obj.optimize_ort(
+                            onnx_path,
+                            onnx_fp32_path,
+                            to_fp16=False,
+                            fp32_op_list=self.model_config[model_name].force_fp32_ops,
+                            optimize_by_ort=self.model_config[model_name].optimize_by_ort,
+                            tmp_dir=self.get_model_dir(model_name, tmp_dir, opt=False, suffix=".fp32", create=False),
+                        )
+                    else:
+                        logger.info("Found cached optimized model: %s", onnx_fp32_path)
+
+                # Generate the final optimized model.
+                if not os.path.exists(onnx_opt_path):
+                    print("------")
+                    logger.info("Generating optimized model: %s", onnx_opt_path)
+
+                    # When there is fp32 intermediate optimized model, this will just convert model from fp32 to fp16.
+                    optimize_by_ort = False if use_fp32_intermediate else self.model_config[model_name].optimize_by_ort
+
+                    model_obj.optimize_ort(
+                        onnx_fp32_path,
+                        onnx_opt_path,
+                        to_fp16=self.model_config[model_name].fp16,
+                        fp32_op_list=self.model_config[model_name].force_fp32_ops,
+                        optimize_by_ort=optimize_by_ort,
+                        optimize_by_fusion=not use_fp32_intermediate,
+                        tmp_dir=self.get_model_dir(model_name, tmp_dir, opt=False, suffix=".ort", create=False),
+                    )
+                else:
+                    logger.info("Found cached optimized model: %s", onnx_opt_path)
+        self.enable_torch_spda()
+
+        built_engines = {}
+        for model_name in self.models:
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+
+            onnx_opt_path = self.optimized_onnx_path(engine_dir, model_name)
+            use_cuda_graph = self.model_config[model_name].use_cuda_graph
+
+            engine = OrtCudaEngine(
+                onnx_opt_path,
+                device_id=device_id,
+                enable_cuda_graph=use_cuda_graph,
+                disable_optimization=False,
+                max_cuda_graphs=max_cuda_graphs,
+            )
+
+            logger.info("%s options for %s: %s", engine.provider, model_name, engine.provider_options)
+            built_engines[model_name] = engine
+
+        self.engines = built_engines
+
+    def run_engine(self, model_name, feed_dict):
+        return self.engines[model_name].infer(feed_dict)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_trt.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_trt.py
new file mode 100644
index 0000000000000000000000000000000000000000..0af46f70d99dbb0e0346d9b703f84d4d905f821c
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_ort_trt.py
@@ -0,0 +1,288 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import gc
+import logging
+import os
+
+import torch
+from cuda import cudart
+from diffusion_models import PipelineInfo
+from engine_builder import EngineBuilder, EngineType
+from packaging import version
+
+import onnxruntime as ort
+from onnxruntime.transformers.io_binding_helper import CudaSession
+
+logger = logging.getLogger(__name__)
+
+
+class OrtTensorrtEngine(CudaSession):
+    def __init__(
+        self,
+        engine_path,
+        device_id,
+        onnx_path,
+        fp16,
+        input_profile,
+        workspace_size,
+        enable_cuda_graph,
+        timing_cache_path=None,
+    ):
+        self.engine_path = engine_path
+        self.ort_trt_provider_options = self.get_tensorrt_provider_options(
+            input_profile,
+            workspace_size,
+            fp16,
+            device_id,
+            enable_cuda_graph,
+            timing_cache_path=timing_cache_path,
+        )
+
+        session_options = ort.SessionOptions()
+        session_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
+        logger.info("creating TRT EP session for %s", onnx_path)
+        ort_session = ort.InferenceSession(
+            onnx_path,
+            session_options,
+            providers=[
+                ("TensorrtExecutionProvider", self.ort_trt_provider_options),
+            ],
+        )
+        logger.info("created TRT EP session for %s", onnx_path)
+
+        device = torch.device("cuda", device_id)
+        super().__init__(ort_session, device, enable_cuda_graph)
+
+    def get_tensorrt_provider_options(
+        self, input_profile, workspace_size, fp16, device_id, enable_cuda_graph, timing_cache_path=None
+    ):
+        trt_ep_options = {
+            "device_id": device_id,
+            "trt_fp16_enable": fp16,
+            "trt_engine_cache_enable": True,
+            "trt_timing_cache_enable": True,
+            "trt_detailed_build_log": True,
+            "trt_engine_cache_path": self.engine_path,
+        }
+
+        if version.parse(ort.__version__) > version.parse("1.16.2") and timing_cache_path is not None:
+            trt_ep_options["trt_timing_cache_path"] = timing_cache_path
+
+        if enable_cuda_graph:
+            trt_ep_options["trt_cuda_graph_enable"] = True
+
+        if workspace_size > 0:
+            trt_ep_options["trt_max_workspace_size"] = workspace_size
+
+        if input_profile:
+            min_shapes = []
+            max_shapes = []
+            opt_shapes = []
+            for name, profile in input_profile.items():
+                assert isinstance(profile, list) and len(profile) == 3
+                min_shape = profile[0]
+                opt_shape = profile[1]
+                max_shape = profile[2]
+                assert len(min_shape) == len(opt_shape) and len(opt_shape) == len(max_shape)
+
+                min_shapes.append(f"{name}:" + "x".join([str(x) for x in min_shape]))
+                opt_shapes.append(f"{name}:" + "x".join([str(x) for x in opt_shape]))
+                max_shapes.append(f"{name}:" + "x".join([str(x) for x in max_shape]))
+
+            trt_ep_options["trt_profile_min_shapes"] = ",".join(min_shapes)
+            trt_ep_options["trt_profile_max_shapes"] = ",".join(max_shapes)
+            trt_ep_options["trt_profile_opt_shapes"] = ",".join(opt_shapes)
+
+        logger.info("trt_ep_options=%s", trt_ep_options)
+
+        return trt_ep_options
+
+    def allocate_buffers(self, shape_dict, device):
+        super().allocate_buffers(shape_dict)
+
+
+class OrtTensorrtEngineBuilder(EngineBuilder):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        max_batch_size=16,
+        device="cuda",
+        use_cuda_graph=False,
+    ):
+        """
+        Initializes the ONNX Runtime TensorRT ExecutionProvider Engine Builder.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            device (str):
+                device to run.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+        """
+        super().__init__(
+            EngineType.ORT_TRT,
+            pipeline_info,
+            max_batch_size=max_batch_size,
+            device=device,
+            use_cuda_graph=use_cuda_graph,
+        )
+
+    def has_engine_file(self, engine_path):
+        if os.path.isdir(engine_path):
+            children = os.scandir(engine_path)
+            for entry in children:
+                if entry.is_file() and entry.name.endswith(".engine"):
+                    return True
+        return False
+
+    def get_work_space_size(self, model_name, max_workspace_size):
+        gibibyte = 2**30
+        workspace_size = 4 * gibibyte if model_name == "clip" else max_workspace_size
+        if workspace_size == 0:
+            _, free_mem, _ = cudart.cudaMemGetInfo()
+            # The following logic are adopted from TensorRT demo diffusion.
+            if free_mem > 6 * gibibyte:
+                workspace_size = free_mem - 4 * gibibyte
+        return workspace_size
+
+    def build_engines(
+        self,
+        engine_dir,
+        framework_model_dir,
+        onnx_dir,
+        onnx_opset,
+        opt_image_height,
+        opt_image_width,
+        opt_batch_size=1,
+        static_batch=False,
+        static_image_shape=True,
+        max_workspace_size=0,
+        device_id=0,
+        timing_cache=None,
+    ):
+        self.torch_device = torch.device("cuda", device_id)
+        self.load_models(framework_model_dir)
+
+        if not os.path.isdir(engine_dir):
+            os.makedirs(engine_dir)
+
+        if not os.path.isdir(onnx_dir):
+            os.makedirs(onnx_dir)
+
+        # Load lora only when we need export text encoder or UNet to ONNX.
+        load_lora = False
+        if self.pipeline_info.lora_weights:
+            for model_name, model_obj in self.models.items():
+                if model_name not in ["clip", "clip2", "unet", "unetxl"]:
+                    continue
+                profile_id = model_obj.get_profile_id(
+                    opt_batch_size, opt_image_height, opt_image_width, static_batch, static_image_shape
+                )
+                engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+                if not self.has_engine_file(engine_path):
+                    onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+                    onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+                    if not os.path.exists(onnx_opt_path):
+                        if not os.path.exists(onnx_path):
+                            load_lora = True
+                            break
+
+        # Export models to ONNX
+        self.disable_torch_spda()
+        pipe = self.load_pipeline_with_lora() if load_lora else None
+
+        for model_name, model_obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+
+            profile_id = model_obj.get_profile_id(
+                opt_batch_size, opt_image_height, opt_image_width, static_batch, static_image_shape
+            )
+            engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+            if not self.has_engine_file(engine_path):
+                onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+                onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+                if not os.path.exists(onnx_opt_path):
+                    if not os.path.exists(onnx_path):
+                        logger.info(f"Exporting model: {onnx_path}")
+                        model = self.get_or_load_model(pipe, model_name, model_obj, framework_model_dir)
+
+                        with torch.inference_mode(), torch.autocast("cuda"):
+                            inputs = model_obj.get_sample_input(opt_batch_size, opt_image_height, opt_image_width)
+                            torch.onnx.export(
+                                model,
+                                inputs,
+                                onnx_path,
+                                export_params=True,
+                                opset_version=onnx_opset,
+                                do_constant_folding=True,
+                                input_names=model_obj.get_input_names(),
+                                output_names=model_obj.get_output_names(),
+                                dynamic_axes=model_obj.get_dynamic_axes(),
+                            )
+                        del model
+                        torch.cuda.empty_cache()
+                        gc.collect()
+                    else:
+                        logger.info("Found cached model: %s", onnx_path)
+
+                    # Optimize onnx
+                    if not os.path.exists(onnx_opt_path):
+                        logger.info("Generating optimizing model: %s", onnx_opt_path)
+                        model_obj.optimize_trt(onnx_path, onnx_opt_path)
+                    else:
+                        logger.info("Found cached optimized model: %s", onnx_opt_path)
+        self.enable_torch_spda()
+
+        built_engines = {}
+        for model_name, model_obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+
+            profile_id = model_obj.get_profile_id(
+                opt_batch_size, opt_image_height, opt_image_width, static_batch, static_image_shape
+            )
+
+            engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+            onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+            if not self.has_engine_file(engine_path):
+                logger.info(
+                    "Building TensorRT engine for %s from %s to %s. It can take a while to complete...",
+                    model_name,
+                    onnx_opt_path,
+                    engine_path,
+                )
+            else:
+                logger.info("Reuse cached TensorRT engine in directory %s", engine_path)
+
+            input_profile = model_obj.get_input_profile(
+                opt_batch_size,
+                opt_image_height,
+                opt_image_width,
+                static_batch=static_batch,
+                static_image_shape=static_image_shape,
+            )
+
+            engine = OrtTensorrtEngine(
+                engine_path,
+                device_id,
+                onnx_opt_path,
+                fp16=True,
+                input_profile=input_profile,
+                workspace_size=self.get_work_space_size(model_name, max_workspace_size),
+                enable_cuda_graph=self.use_cuda_graph,
+                timing_cache_path=timing_cache,
+            )
+
+            built_engines[model_name] = engine
+
+        self.engines = built_engines
+
+    def run_engine(self, model_name, feed_dict):
+        return self.engines[model_name].infer(feed_dict)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_tensorrt.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_tensorrt.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ba92f4569b9df1847f3859c93eca19357a74a49
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_tensorrt.py
@@ -0,0 +1,395 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from TensorRT demo diffusion, which has the following license:
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+
+import gc
+import os
+import pathlib
+from collections import OrderedDict
+
+import numpy as np
+import tensorrt as trt
+import torch
+from cuda import cudart
+from diffusion_models import PipelineInfo
+from engine_builder import EngineBuilder, EngineType
+from polygraphy.backend.common import bytes_from_path
+from polygraphy.backend.trt import (
+    CreateConfig,
+    ModifyNetworkOutputs,
+    Profile,
+    engine_from_bytes,
+    engine_from_network,
+    network_from_onnx_path,
+    save_engine,
+)
+
+# Map of numpy dtype -> torch dtype
+numpy_to_torch_dtype_dict = {
+    np.int32: torch.int32,
+    np.int64: torch.int64,
+    np.float16: torch.float16,
+    np.float32: torch.float32,
+}
+
+
+def _cuda_assert(cuda_ret):
+    err = cuda_ret[0]
+    if err != cudart.cudaError_t.cudaSuccess:
+        raise RuntimeError(
+            f"CUDA ERROR: {err}, error code reference: https://nvidia.github.io/cuda-python/module/cudart.html#cuda.cudart.cudaError_t"
+        )
+    if len(cuda_ret) > 1:
+        return cuda_ret[1]
+    return None
+
+
+class TensorrtEngine:
+    def __init__(
+        self,
+        engine_path,
+    ):
+        self.engine_path = engine_path
+        self.engine = None
+        self.context = None
+        self.buffers = OrderedDict()
+        self.tensors = OrderedDict()
+        self.cuda_graph_instance = None
+
+    def __del__(self):
+        del self.engine
+        del self.context
+        del self.buffers
+        del self.tensors
+
+    def build(
+        self,
+        onnx_path,
+        fp16,
+        input_profile=None,
+        enable_all_tactics=False,
+        timing_cache=None,
+        update_output_names=None,
+    ):
+        print(f"Building TensorRT engine for {onnx_path}: {self.engine_path}")
+        p = Profile()
+        if input_profile:
+            for name, dims in input_profile.items():
+                assert len(dims) == 3
+                p.add(name, min=dims[0], opt=dims[1], max=dims[2])
+
+        config_kwargs = {}
+        if not enable_all_tactics:
+            config_kwargs["tactic_sources"] = []
+
+        network = network_from_onnx_path(onnx_path, flags=[trt.OnnxParserFlag.NATIVE_INSTANCENORM])
+        if update_output_names:
+            print(f"Updating network outputs to {update_output_names}")
+            network = ModifyNetworkOutputs(network, update_output_names)
+        engine = engine_from_network(
+            network,
+            config=CreateConfig(
+                fp16=fp16, refittable=False, profiles=[p], load_timing_cache=timing_cache, **config_kwargs
+            ),
+            save_timing_cache=timing_cache,
+        )
+        save_engine(engine, path=self.engine_path)
+
+    def load(self):
+        print(f"Loading TensorRT engine: {self.engine_path}")
+        self.engine = engine_from_bytes(bytes_from_path(self.engine_path))
+
+    def activate(self, reuse_device_memory=None):
+        if reuse_device_memory:
+            self.context = self.engine.create_execution_context_without_device_memory()
+            self.context.device_memory = reuse_device_memory
+        else:
+            self.context = self.engine.create_execution_context()
+
+    def allocate_buffers(self, shape_dict=None, device="cuda"):
+        for idx in range(self.engine.num_io_tensors):
+            binding = self.engine[idx]
+            if shape_dict and binding in shape_dict:
+                shape = shape_dict[binding]
+            else:
+                shape = self.engine.get_binding_shape(binding)
+            dtype = trt.nptype(self.engine.get_binding_dtype(binding))
+            if self.engine.binding_is_input(binding):
+                self.context.set_binding_shape(idx, shape)
+            tensor = torch.empty(tuple(shape), dtype=numpy_to_torch_dtype_dict[dtype]).to(device=device)
+            self.tensors[binding] = tensor
+
+    def infer(self, feed_dict, stream, use_cuda_graph=False):
+        for name, buf in feed_dict.items():
+            self.tensors[name].copy_(buf)
+
+        for name, tensor in self.tensors.items():
+            self.context.set_tensor_address(name, tensor.data_ptr())
+
+        if use_cuda_graph:
+            if self.cuda_graph_instance is not None:
+                _cuda_assert(cudart.cudaGraphLaunch(self.cuda_graph_instance, stream))
+                _cuda_assert(cudart.cudaStreamSynchronize(stream))
+            else:
+                # do inference before CUDA graph capture
+                noerror = self.context.execute_async_v3(stream)
+                if not noerror:
+                    raise ValueError("ERROR: inference failed.")
+                # capture cuda graph
+                _cuda_assert(
+                    cudart.cudaStreamBeginCapture(stream, cudart.cudaStreamCaptureMode.cudaStreamCaptureModeGlobal)
+                )
+                self.context.execute_async_v3(stream)
+                self.graph = _cuda_assert(cudart.cudaStreamEndCapture(stream))
+
+                from cuda import nvrtc  # noqa: PLC0415
+
+                result, major, minor = nvrtc.nvrtcVersion()
+                assert result == nvrtc.nvrtcResult(0)
+                if major < 12:
+                    self.cuda_graph_instance = _cuda_assert(
+                        cudart.cudaGraphInstantiate(self.graph, b"", 0)
+                    )  # cuda < 12
+                else:
+                    self.cuda_graph_instance = _cuda_assert(cudart.cudaGraphInstantiate(self.graph, 0))  # cuda >= 12
+        else:
+            noerror = self.context.execute_async_v3(stream)
+            if not noerror:
+                raise ValueError("ERROR: inference failed.")
+
+        return self.tensors
+
+
+class TensorrtEngineBuilder(EngineBuilder):
+    """
+    Helper class to hide the detail of TensorRT Engine from pipeline.
+    """
+
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        max_batch_size=16,
+        device="cuda",
+        use_cuda_graph=False,
+    ):
+        """
+        Initializes the ONNX Runtime TensorRT ExecutionProvider Engine Builder.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            device (str):
+                device to run.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+        """
+        super().__init__(
+            EngineType.TRT,
+            pipeline_info,
+            max_batch_size=max_batch_size,
+            device=device,
+            use_cuda_graph=use_cuda_graph,
+        )
+
+        self.stream = None
+        self.shared_device_memory = None
+
+    def load_resources(self, image_height, image_width, batch_size):
+        super().load_resources(image_height, image_width, batch_size)
+
+        self.stream = _cuda_assert(cudart.cudaStreamCreate())
+
+    def teardown(self):
+        super().teardown()
+
+        if self.shared_device_memory:
+            cudart.cudaFree(self.shared_device_memory)
+
+        cudart.cudaStreamDestroy(self.stream)
+        del self.stream
+
+    def load_engines(
+        self,
+        engine_dir,
+        framework_model_dir,
+        onnx_dir,
+        onnx_opset,
+        opt_batch_size,
+        opt_image_height,
+        opt_image_width,
+        static_batch=False,
+        static_shape=True,
+        enable_all_tactics=False,
+        timing_cache=None,
+    ):
+        """
+        Build and load engines for TensorRT accelerated inference.
+        Export ONNX models first, if applicable.
+
+        Args:
+            engine_dir (str):
+                Directory to write the TensorRT engines.
+            framework_model_dir (str):
+                Directory to write the framework model ckpt.
+            onnx_dir (str):
+                Directory to write the ONNX models.
+            onnx_opset (int):
+                ONNX opset version to export the models.
+            opt_batch_size (int):
+                Batch size to optimize for during engine building.
+            opt_image_height (int):
+                Image height to optimize for during engine building. Must be a multiple of 8.
+            opt_image_width (int):
+                Image width to optimize for during engine building. Must be a multiple of 8.
+            static_batch (bool):
+                Build engine only for specified opt_batch_size.
+            static_shape (bool):
+                Build engine only for specified opt_image_height & opt_image_width. Default = True.
+            enable_all_tactics (bool):
+                Enable all tactic sources during TensorRT engine builds.
+            timing_cache (str):
+                Path to the timing cache to accelerate build or None
+        """
+        # Create directory
+        for directory in [engine_dir, onnx_dir]:
+            if not os.path.exists(directory):
+                print(f"[I] Create directory: {directory}")
+                pathlib.Path(directory).mkdir(parents=True)
+
+        self.load_models(framework_model_dir)
+
+        # Load lora only when we need export text encoder or UNet to ONNX.
+        load_lora = False
+        if self.pipeline_info.lora_weights:
+            for model_name, model_obj in self.models.items():
+                if model_name not in ["clip", "clip2", "unet", "unetxl"]:
+                    continue
+                profile_id = model_obj.get_profile_id(
+                    opt_batch_size, opt_image_height, opt_image_width, static_batch, static_shape
+                )
+                engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+                if not os.path.exists(engine_path):
+                    onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+                    onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+                    if not os.path.exists(onnx_opt_path):
+                        if not os.path.exists(onnx_path):
+                            load_lora = True
+                            break
+
+        # Export models to ONNX
+        self.disable_torch_spda()
+        pipe = self.load_pipeline_with_lora() if load_lora else None
+
+        for model_name, model_obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+            profile_id = model_obj.get_profile_id(
+                opt_batch_size, opt_image_height, opt_image_width, static_batch, static_shape
+            )
+            engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+            if not os.path.exists(engine_path):
+                onnx_path = self.get_onnx_path(model_name, onnx_dir, opt=False)
+                onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+                if not os.path.exists(onnx_opt_path):
+                    if not os.path.exists(onnx_path):
+                        print(f"Exporting model: {onnx_path}")
+                        model = self.get_or_load_model(pipe, model_name, model_obj, framework_model_dir)
+
+                        with torch.inference_mode(), torch.autocast("cuda"):
+                            inputs = model_obj.get_sample_input(1, opt_image_height, opt_image_width)
+                            torch.onnx.export(
+                                model,
+                                inputs,
+                                onnx_path,
+                                export_params=True,
+                                opset_version=onnx_opset,
+                                do_constant_folding=True,
+                                input_names=model_obj.get_input_names(),
+                                output_names=model_obj.get_output_names(),
+                                dynamic_axes=model_obj.get_dynamic_axes(),
+                            )
+                        del model
+                        torch.cuda.empty_cache()
+                        gc.collect()
+                    else:
+                        print(f"Found cached model: {onnx_path}")
+
+                    # Optimize onnx
+                    if not os.path.exists(onnx_opt_path):
+                        print(f"Generating optimizing model: {onnx_opt_path}")
+                        model_obj.optimize_trt(onnx_path, onnx_opt_path)
+                    else:
+                        print(f"Found cached optimized model: {onnx_opt_path} ")
+        self.enable_torch_spda()
+
+        # Build TensorRT engines
+        for model_name, model_obj in self.models.items():
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+            profile_id = model_obj.get_profile_id(
+                opt_batch_size, opt_image_height, opt_image_width, static_batch, static_shape
+            )
+            engine_path = self.get_engine_path(engine_dir, model_name, profile_id)
+            engine = TensorrtEngine(engine_path)
+            onnx_opt_path = self.get_onnx_path(model_name, onnx_dir, opt=True)
+
+            if not os.path.exists(engine.engine_path):
+                engine.build(
+                    onnx_opt_path,
+                    fp16=True,
+                    input_profile=model_obj.get_input_profile(
+                        opt_batch_size,
+                        opt_image_height,
+                        opt_image_width,
+                        static_batch,
+                        static_shape,
+                    ),
+                    enable_all_tactics=enable_all_tactics,
+                    timing_cache=timing_cache,
+                    update_output_names=None,
+                )
+            self.engines[model_name] = engine
+
+        # Load TensorRT engines
+        for model_name in self.models:
+            if model_name == "vae" and self.vae_torch_fallback:
+                continue
+            self.engines[model_name].load()
+
+    def max_device_memory(self):
+        max_device_memory = 0
+        for engine in self.engines.values():
+            max_device_memory = max(max_device_memory, engine.engine.device_memory_size)
+        return max_device_memory
+
+    def activate_engines(self, shared_device_memory=None):
+        if shared_device_memory is None:
+            max_device_memory = self.max_device_memory()
+            _, shared_device_memory = cudart.cudaMalloc(max_device_memory)
+        self.shared_device_memory = shared_device_memory
+        # Load and activate TensorRT engines
+        for engine in self.engines.values():
+            engine.activate(reuse_device_memory=self.shared_device_memory)
+
+    def run_engine(self, model_name, feed_dict):
+        return self.engines[model_name].infer(feed_dict, self.stream, use_cuda_graph=self.use_cuda_graph)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_torch.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_torch.py
new file mode 100644
index 0000000000000000000000000000000000000000..9cddc783cc006757effe938dffef971466db630d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/engine_builder_torch.py
@@ -0,0 +1,108 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+from diffusion_models import PipelineInfo
+from engine_builder import EngineBuilder, EngineType
+
+logger = logging.getLogger(__name__)
+
+
+class TorchEngineBuilder(EngineBuilder):
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        max_batch_size=16,
+        device="cuda",
+        use_cuda_graph=False,
+    ):
+        """
+        Initializes the ONNX Runtime TensorRT ExecutionProvider Engine Builder.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            device (str):
+                device to run.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+        """
+        super().__init__(
+            EngineType.TORCH,
+            pipeline_info,
+            max_batch_size=max_batch_size,
+            device=device,
+            use_cuda_graph=use_cuda_graph,
+        )
+
+        self.compile_config = {}
+        if use_cuda_graph:
+            self.compile_config = {
+                "clip": {"mode": "reduce-overhead", "dynamic": False},
+                "clip2": {"mode": "reduce-overhead", "dynamic": False},
+                "unet": {"mode": "reduce-overhead", "fullgraph": True, "dynamic": False},
+                "unetxl": {"mode": "reduce-overhead", "fullgraph": True, "dynamic": False},
+                "vae": {"mode": "reduce-overhead", "fullgraph": False, "dynamic": False},
+            }
+
+    def build_engines(
+        self,
+        framework_model_dir: str,
+    ):
+        import torch  # noqa: PLC0415
+
+        self.torch_device = torch.device("cuda", torch.cuda.current_device())
+        self.load_models(framework_model_dir)
+
+        pipe = self.load_pipeline_with_lora() if self.pipeline_info.lora_weights else None
+
+        built_engines = {}
+        for model_name, model_obj in self.models.items():
+            model = self.get_or_load_model(pipe, model_name, model_obj, framework_model_dir)
+            if self.pipeline_info.is_xl() and not self.custom_fp16_vae:
+                model = model.to(device=self.torch_device, dtype=torch.float32)
+            else:
+                model = model.to(device=self.torch_device, dtype=torch.float16)
+
+            if model_name in self.compile_config:
+                compile_config = self.compile_config[model_name]
+                if model_name in ["unet", "unetxl"]:
+                    model.to(memory_format=torch.channels_last)
+                engine = torch.compile(model, **compile_config)
+                built_engines[model_name] = engine
+            else:  # eager mode
+                built_engines[model_name] = model
+
+        self.engines = built_engines
+
+    def run_engine(self, model_name, feed_dict):
+        if model_name in ["unet", "unetxl"]:
+            if "controlnet_images" in feed_dict:
+                return {"latent": self.engines[model_name](**feed_dict)}
+
+            if model_name == "unetxl":
+                added_cond_kwargs = {k: feed_dict[k] for k in feed_dict if k in ["text_embeds", "time_ids"]}
+                return {
+                    "latent": self.engines[model_name](
+                        feed_dict["sample"],
+                        feed_dict["timestep"],
+                        feed_dict["encoder_hidden_states"],
+                        added_cond_kwargs=added_cond_kwargs,
+                        return_dict=False,
+                    )[0]
+                }
+
+            return {
+                "latent": self.engines[model_name](
+                    feed_dict["sample"], feed_dict["timestep"], feed_dict["encoder_hidden_states"], return_dict=False
+                )[0]
+            }
+
+        if model_name in ["vae_encoder"]:
+            return {"latent": self.engines[model_name](feed_dict["images"])}
+
+        raise RuntimeError(f"Shall not reach here: {model_name}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/optimize_pipeline.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/optimize_pipeline.py
new file mode 100644
index 0000000000000000000000000000000000000000..83e4dac2d09aa9553eaedefdae3085f56d43024d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/optimize_pipeline.py
@@ -0,0 +1,590 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+#
+# This script converts stable diffusion onnx models from float to half (mixed) precision for GPU inference.
+#
+# Before running this script, follow README.md to setup python environment and convert stable diffusion checkpoint
+# to float32 onnx models.
+#
+# For example, the float32 ONNX pipeline is saved to ./sd-v1-5 directory, you can optimize and convert it to float16
+# like the following:
+#    python optimize_pipeline.py -i ./sd-v1-5 -o ./sd-v1-5-fp16 --float16
+#
+# Note that the optimizations are carried out for CUDA Execution Provider at first, other EPs may not have the support
+# for the fused operators. The users could disable the operator fusion manually to workaround.
+
+import argparse
+import logging
+import os
+import shutil
+import tempfile
+import warnings
+from pathlib import Path
+
+import onnx
+from fusion_options import FusionOptions
+from onnx_model_clip import ClipOnnxModel
+from onnx_model_mmdit import MmditOnnxModel
+from onnx_model_t5 import T5OnnxModel
+from onnx_model_unet import UnetOnnxModel
+from onnx_model_vae import VaeOnnxModel
+from optimizer import optimize_by_onnxruntime, optimize_model
+from packaging import version
+
+import onnxruntime
+
+logger = logging.getLogger(__name__)
+
+
+def has_external_data(onnx_model_path):
+    original_model = onnx.load_model(str(onnx_model_path), load_external_data=False)
+    for initializer in original_model.graph.initializer:
+        if initializer.HasField("data_location") and initializer.data_location == onnx.TensorProto.EXTERNAL:
+            return True
+    return False
+
+
+def is_sd_3(source_dir: Path):
+    return (source_dir / "text_encoder_3").exists()
+
+
+def is_sdxl(source_dir: Path):
+    return (
+        (source_dir / "text_encoder_2").exists()
+        and not (source_dir / "text_encoder_3").exists()
+        and not (source_dir / "transformer").exists()
+    )
+
+
+def is_flux(source_dir: Path):
+    return (
+        (source_dir / "text_encoder_2").exists()
+        and not (source_dir / "text_encoder_3").exists()
+        and (source_dir / "transformer").exists()
+    )
+
+
+def _classify_pipeline_type(source_dir: Path):
+    # May also check _class_name in model_index.json like `StableDiffusion3Pipeline` or `FluxPipeline` etc to classify.
+    if is_sd_3(source_dir):
+        return "sd3"
+
+    if is_flux(source_dir):
+        return "flux"
+
+    if is_sdxl(source_dir):
+        return "sdxl"
+
+    # sd 1.x and 2.x
+    return "sd"
+
+
+def _get_model_list(pipeline_type: str):
+    if pipeline_type == "sd3":
+        return ["text_encoder", "text_encoder_2", "text_encoder_3", "transformer", "vae_encoder", "vae_decoder"]
+
+    if pipeline_type == "flux":
+        return ["text_encoder", "text_encoder_2", "transformer", "vae_encoder", "vae_decoder"]
+
+    if pipeline_type == "sdxl":
+        return ["text_encoder", "text_encoder_2", "unet", "vae_encoder", "vae_decoder"]
+
+    assert pipeline_type == "sd"
+    return ["text_encoder", "unet", "vae_encoder", "vae_decoder"]
+
+
+def _optimize_sd_pipeline(
+    source_dir: Path,
+    target_dir: Path,
+    pipeline_type: str,
+    model_list: list[str],
+    use_external_data_format: bool | None,
+    float16: bool,
+    bfloat16: bool,
+    force_fp32_ops: list[str],
+    enable_runtime_optimization: bool,
+    args,
+):
+    """Optimize onnx models used in stable diffusion onnx pipeline and optionally convert to float16.
+
+    Args:
+        source_dir (Path): Root of input directory of stable diffusion onnx pipeline with float32 models.
+        target_dir (Path): Root of output directory of stable diffusion onnx pipeline with optimized models.
+        model_list (List[str]): list of directory names with onnx model.
+        use_external_data_format (Optional[bool]): use external data format.
+        float16 (bool): use half precision
+        bfloat16 (bool): use bfloat16 as fallback if float16 is also provided.
+        force_fp32_ops(List[str]): operators that are forced to run in float32.
+        enable_runtime_optimization(bool): run graph optimization using Onnx Runtime.
+
+    Raises:
+        RuntimeError: input onnx model does not exist
+        RuntimeError: output onnx model path existed
+    """
+    is_flux_pipeline = pipeline_type == "flux"
+    model_type_mapping = {
+        "transformer": "mmdit",
+        "unet": "unet",
+        "vae_encoder": "vae",
+        "vae_decoder": "vae",
+        "text_encoder": "clip",
+        "text_encoder_2": "t5" if is_flux_pipeline else "clip",
+        "text_encoder_3": "t5",  # t5-v1_1-xxl is used in SD 3.x text_encoder_3 and Flux text_encoder_2.
+        "safety_checker": "unet",
+    }
+
+    model_type_class_mapping = {
+        "unet": UnetOnnxModel,
+        "vae": VaeOnnxModel,
+        "clip": ClipOnnxModel,
+        "t5": T5OnnxModel,
+        "mmdit": MmditOnnxModel,
+    }
+
+    force_fp32_operators = {
+        "unet": [],
+        "vae_encoder": [],
+        "vae_decoder": [],
+        "text_encoder": [],
+        "text_encoder_2": [],
+        "safety_checker": [],
+        "text_encoder_3": [],
+        "transformer": [],
+    }
+
+    # The node block list is generated by running the fp32 model and get statistics of node inputs and outputs.
+    # Nodes with any input or output of float or double data type, but value ouf of range of float16 are candidates.
+    #   python optimize_pipeline.py -i ./flux1_schnell_onnx/fp32 -o ./flux1_schnell_onnx/fp32_opt
+    #   export ORT_DEBUG_NODE_IO_DUMP_STATISTICS_DATA=1
+    #   export ORT_DEBUG_NODE_IO_DUMP_INPUT_DATA=1
+    #   export ORT_DEBUG_NODE_IO_DUMP_OUTPUT_DATA=1
+    #   python benchmark.py --height 1024 --width 1024 --steps 4 -b 1 -v Flux.1S -p flux1_schnell_onnx/fp32_opt -e optimum >stdout.txt 2>stderr.txt
+    # Warning: The node name might change in different export settings. See benchmark_flux.sh for the settings.
+    flux_node_block_list = {
+        "text_encoder_2": [
+            "/encoder/block.10/layer.1/DenseReluDense/wo/MatMul",
+            "SkipLayerNorm_20",
+            "SkipLayerNorm_21",
+            "SkipLayerNorm_22",
+            "SkipLayerNorm_23",
+            "SkipLayerNorm_24",
+            "SkipLayerNorm_25",
+            "SkipLayerNorm_26",
+            "SkipLayerNorm_27",
+            "SkipLayerNorm_28",
+            "SkipLayerNorm_29",
+            "SkipLayerNorm_30",
+            "SkipLayerNorm_31",
+            "SkipLayerNorm_32",
+            "SkipLayerNorm_33",
+            "SkipLayerNorm_34",
+            "SkipLayerNorm_35",
+            "SkipLayerNorm_36",
+            "SkipLayerNorm_37",
+            "SkipLayerNorm_38",
+            "SkipLayerNorm_39",
+            "SkipLayerNorm_40",
+            "SkipLayerNorm_41",
+            "SkipLayerNorm_42",
+            "SkipLayerNorm_43",
+            "SkipLayerNorm_44",
+            "SkipLayerNorm_45",
+            "/encoder/block.23/layer.1/DenseReluDense/wo/MatMul",
+            "SkipLayerNorm_46",
+        ],
+        "vae_decoder": [
+            "/decoder/mid_block/attentions.0/MatMul",
+            "/decoder/mid_block/attentions.0/Softmax",
+        ],
+        "transformer": [
+            "/transformer_blocks.18/Mul_5",
+            "/transformer_blocks.18/Add_7",
+            "/Concat_1",
+            "LayerNorm_76",
+            "/single_transformer_blocks.0/Add",
+            "LayerNorm_77",
+            "/single_transformer_blocks.1/Add",
+            "LayerNorm_78",
+            "/single_transformer_blocks.2/Add",
+            "LayerNorm_79",
+            "/single_transformer_blocks.3/Add",
+            "LayerNorm_80",
+            "/single_transformer_blocks.4/Add",
+            "LayerNorm_81",
+            "/single_transformer_blocks.5/Add",
+            "LayerNorm_82",
+            "/single_transformer_blocks.6/Add",
+            "LayerNorm_83",
+            "/single_transformer_blocks.7/Add",
+            "LayerNorm_84",
+            "/single_transformer_blocks.8/Add",
+            "LayerNorm_85",
+            "/single_transformer_blocks.9/Add",
+            "LayerNorm_86",
+            "/single_transformer_blocks.10/Add",
+            "LayerNorm_87",
+            "/single_transformer_blocks.11/Add",
+            "LayerNorm_88",
+            "/single_transformer_blocks.12/Add",
+            "LayerNorm_89",
+            "/single_transformer_blocks.13/Add",
+            "LayerNorm_90",
+            "/single_transformer_blocks.14/Add",
+            "LayerNorm_91",
+            "/single_transformer_blocks.15/Add",
+            "LayerNorm_92",
+            "/single_transformer_blocks.16/Add",
+            "LayerNorm_93",
+            "/single_transformer_blocks.17/Add",
+            "LayerNorm_94",
+            "/single_transformer_blocks.18/Add",
+            "LayerNorm_95",
+            "/single_transformer_blocks.19/Add",
+            "LayerNorm_96",
+            "/single_transformer_blocks.20/Add",
+            "LayerNorm_97",
+            "/single_transformer_blocks.21/Add",
+            "LayerNorm_98",
+            "/single_transformer_blocks.22/Add",
+            "LayerNorm_99",
+            "/single_transformer_blocks.23/Add",
+            "LayerNorm_100",
+            "/single_transformer_blocks.24/Add",
+            "LayerNorm_101",
+            "/single_transformer_blocks.25/Add",
+            "LayerNorm_102",
+            "/single_transformer_blocks.26/Add",
+            "LayerNorm_103",
+            "/single_transformer_blocks.27/Add",
+            "LayerNorm_104",
+            "/single_transformer_blocks.28/Add",
+            "LayerNorm_105",
+            "/single_transformer_blocks.29/Add",
+            "LayerNorm_106",
+            "/single_transformer_blocks.30/Add",
+            "LayerNorm_107",
+            "/single_transformer_blocks.31/Add",
+            "LayerNorm_108",
+            "/single_transformer_blocks.32/Add",
+            "LayerNorm_109",
+            "/single_transformer_blocks.33/Add",
+            "LayerNorm_110",
+            "/single_transformer_blocks.34/Add",
+            "LayerNorm_111",
+            "/single_transformer_blocks.35/Add",
+            "LayerNorm_112",
+            "/single_transformer_blocks.36/Add",
+            "LayerNorm_113",
+            "/single_transformer_blocks.37/Add",
+            "/Shape",
+            "/Slice",
+        ],
+    }
+
+    sd3_node_block_list = {"text_encoder_3": flux_node_block_list["text_encoder_2"]}
+
+    if force_fp32_ops:
+        for fp32_operator in force_fp32_ops:
+            parts = fp32_operator.split(":")
+            if len(parts) == 2 and parts[0] in force_fp32_operators and (parts[1] and parts[1][0].isupper()):
+                force_fp32_operators[parts[0]].append(parts[1])
+            else:
+                raise ValueError(
+                    f"--force_fp32_ops shall be in the format of module:operator like unet:Attention, got {fp32_operator}"
+                )
+
+    op_counters = {}
+    for name, model_type in model_type_mapping.items():
+        onnx_model_path = source_dir / name / "model.onnx"
+        if not os.path.exists(onnx_model_path):
+            if name != "safety_checker" and name in model_list:
+                logger.warning("input onnx model does not exist: %s", onnx_model_path)
+            # some model are optional so we do not raise error here.
+            continue
+
+        # Prepare output directory
+        optimized_model_path = target_dir / name / "model.onnx"
+        if os.path.exists(optimized_model_path):
+            if not args.overwrite:
+                logger.warning("Skipped optimization since the target file existed: %s", optimized_model_path)
+            continue
+        output_dir = optimized_model_path.parent
+        output_dir.mkdir(parents=True, exist_ok=True)
+
+        if use_external_data_format is None:
+            use_external_data_format = has_external_data(onnx_model_path)
+
+        # Graph fusion before fp16 conversion, otherwise they cannot be fused later.
+        logger.info("Optimize %s ...", onnx_model_path)
+
+        args.model_type = model_type
+        fusion_options = FusionOptions.parse(args)
+
+        if model_type in ["unet"]:
+            # Some optimizations are not available in v1.14 or older version: packed QKV and BiasAdd
+            has_all_optimizations = version.parse(onnxruntime.__version__) >= version.parse("1.15.0")
+            fusion_options.enable_packed_kv = float16 and fusion_options.enable_packed_kv
+            fusion_options.enable_packed_qkv = float16 and has_all_optimizations and fusion_options.enable_packed_qkv
+            fusion_options.enable_bias_add = has_all_optimizations and fusion_options.enable_bias_add
+
+        m = optimize_model(
+            str(onnx_model_path),
+            model_type=model_type,
+            num_heads=0,  # will be deduced from graph
+            hidden_size=0,  # will be deduced from graph
+            opt_level=0,
+            optimization_options=fusion_options,
+            use_gpu=True,
+            provider=args.provider,
+        )
+
+        if float16:
+            model_node_block_list = (
+                flux_node_block_list if is_flux_pipeline else sd3_node_block_list if pipeline_type == "sd3" else {}
+            )
+            if name in model_node_block_list:
+                # Opset 12 does not support bfloat16.
+                # By default, optimum exports T5 model with opset 12. So we need to check the opset version.
+                use_bfloat16 = bfloat16
+                if use_bfloat16:
+                    for opset in m.model.opset_import:
+                        if opset.domain in ["", "ai.onnx"] and opset.version < 13:
+                            logger.warning(
+                                "onnx model requires opset 13 or higher to use bfloat16. Fall back to float32."
+                            )
+                            use_bfloat16 = False
+
+                m.convert_float_to_float16(
+                    keep_io_types=False,
+                    node_block_list=model_node_block_list[name],
+                    use_bfloat16_as_blocked_nodes_dtype=use_bfloat16,
+                )
+            # For SD-XL, use FP16 in VAE decoder will cause NaN and black image so we keep it in FP32.
+            elif pipeline_type in ["sdxl"] and name in ["vae_decoder"]:
+                logger.info("Skip converting %s to float16 to avoid NaN", name)
+            else:
+                logger.info("Convert %s to float16 ...", name)
+                m.convert_float_to_float16(
+                    keep_io_types=False,
+                    op_block_list=force_fp32_operators[name],
+                )
+
+        if enable_runtime_optimization:
+            # Use this step to see the final graph that executed by Onnx Runtime.
+            with tempfile.TemporaryDirectory() as tmp_dir:
+                # Save to a temporary file so that we can load it with Onnx Runtime.
+                logger.info("Saving a temporary model to run OnnxRuntime graph optimizations...")
+                tmp_model_path = Path(tmp_dir) / "model.onnx"
+                m.save_model_to_file(str(tmp_model_path), use_external_data_format=use_external_data_format)
+                ort_optimized_model_path = Path(tmp_dir) / "optimized.onnx"
+                optimize_by_onnxruntime(
+                    str(tmp_model_path),
+                    use_gpu=True,
+                    provider=args.provider,
+                    optimized_model_path=str(ort_optimized_model_path),
+                    save_as_external_data=use_external_data_format,
+                )
+                model = onnx.load(str(ort_optimized_model_path), load_external_data=True)
+                m = model_type_class_mapping[model_type](model)
+
+        m.get_operator_statistics()
+        op_counters[name] = m.get_fused_operator_statistics()
+        m.save_model_to_file(str(optimized_model_path), use_external_data_format=use_external_data_format)
+        logger.info("%s is optimized", name)
+        logger.info("*" * 20)
+
+    return op_counters
+
+
+def _copy_extra_directory(source_dir: Path, target_dir: Path, model_list: list[str]):
+    """Copy extra directory that does not have onnx model
+
+    Args:
+        source_dir (Path): source directory
+        target_dir (Path): target directory
+        model_list (List[str]): list of directory names with onnx model.
+
+    Raises:
+        RuntimeError: source path does not exist
+    """
+    extra_dirs = ["scheduler", "tokenizer", "tokenizer_2", "tokenizer_3", "feature_extractor"]
+
+    for name in extra_dirs:
+        source_path = source_dir / name
+        if not os.path.exists(source_path):
+            continue
+
+        target_path = target_dir / name
+        if target_path.exists():
+            shutil.rmtree(target_path)
+        shutil.copytree(source_path, target_path)
+        logger.info("%s => %s", source_path, target_path)
+
+    extra_files = ["model_index.json"]
+    for name in extra_files:
+        source_path = source_dir / name
+        if not os.path.exists(source_path):
+            raise RuntimeError(f"source path does not exist: {source_path}")
+
+        target_path = target_dir / name
+        shutil.copyfile(source_path, target_path)
+        logger.info("%s => %s", source_path, target_path)
+
+    # Some directory are optional
+    for onnx_model_dir in model_list:
+        source_path = source_dir / onnx_model_dir / "config.json"
+        target_path = target_dir / onnx_model_dir / "config.json"
+        if source_path.exists():
+            target_path.parent.mkdir(parents=True, exist_ok=True)
+            shutil.copyfile(source_path, target_path)
+            logger.info("%s => %s", source_path, target_path)
+
+
+def optimize_stable_diffusion_pipeline(
+    input_dir: str,
+    output_dir: str,
+    overwrite: bool,
+    use_external_data_format: bool | None,
+    float16: bool,
+    enable_runtime_optimization: bool,
+    args,
+):
+    if os.path.exists(output_dir):
+        if overwrite:
+            shutil.rmtree(output_dir, ignore_errors=True)
+
+    source_dir = Path(input_dir)
+    target_dir = Path(output_dir)
+    target_dir.mkdir(parents=True, exist_ok=True)
+
+    pipeline_type = _classify_pipeline_type(source_dir)
+    model_list = _get_model_list(pipeline_type)
+
+    _copy_extra_directory(source_dir, target_dir, model_list)
+
+    return _optimize_sd_pipeline(
+        source_dir,
+        target_dir,
+        pipeline_type,
+        model_list,
+        use_external_data_format,
+        float16,
+        args.bfloat16,
+        args.force_fp32_ops,
+        enable_runtime_optimization,
+        args,
+    )
+
+
+def parse_arguments(argv: list[str] | None = None):
+    """Parse arguments
+
+    Returns:
+        Namespace: arguments
+    """
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-i",
+        "--input",
+        required=True,
+        type=str,
+        help="Root of input directory of stable diffusion onnx pipeline with float32 models.",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--output",
+        required=True,
+        type=str,
+        help="Root of output directory of stable diffusion onnx pipeline with optimized models.",
+    )
+
+    parser.add_argument(
+        "--float16",
+        required=False,
+        action="store_true",
+        help="Output models of float16, except some nodes falls back to float32 or bfloat16 to avoid overflow.",
+    )
+    parser.set_defaults(float16=False)
+
+    parser.add_argument(
+        "--bfloat16",
+        required=False,
+        action="store_true",
+        help="Allow bfloat16 as fallback if --float16 is also provided.",
+    )
+    parser.set_defaults(bfloat16=False)
+
+    parser.add_argument(
+        "--force_fp32_ops",
+        required=False,
+        nargs="+",
+        type=str,
+        help="Force given operators (like unet:Attention) to run in float32. It is case sensitive!",
+    )
+
+    parser.add_argument(
+        "--inspect",
+        required=False,
+        action="store_true",
+        help="Save the optimized graph from Onnx Runtime. "
+        "This option has no impact on inference performance except it might reduce session creation time.",
+    )
+    parser.set_defaults(inspect=False)
+
+    parser.add_argument(
+        "--overwrite",
+        required=False,
+        action="store_true",
+        help="Overwrite exists files.",
+    )
+    parser.set_defaults(overwrite=False)
+
+    parser.add_argument(
+        "-e",
+        "--use_external_data_format",
+        required=False,
+        action="store_true",
+        help="Onnx model larger than 2GB need to use external data format. "
+        "If specified, save each onnx model to two files: one for onnx graph, another for weights. "
+        "If not specified, use same format as original model by default. ",
+    )
+    parser.set_defaults(use_external_data_format=None)
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        type=str,
+        default=None,
+        help="Execution provider to use.",
+    )
+
+    FusionOptions.add_arguments(parser)
+
+    args = parser.parse_args(argv)
+    return args
+
+
+def main(argv: list[str] | None = None):
+    warnings.warn(
+        "This example is deprecated. Use the Olive recipe instead: "
+        "https://github.com/microsoft/olive-recipes/tree/main",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+    args = parse_arguments(argv)
+
+    logger.info("Arguments: %s", str(args))
+
+    # Return op counters for testing purpose.
+    return optimize_stable_diffusion_pipeline(
+        args.input, args.output, args.overwrite, args.use_external_data_format, args.float16, args.inspect, args
+    )
+
+
+if __name__ == "__main__":
+    logging.basicConfig(format="%(funcName)20s: %(message)s", level=logging.INFO)
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/ort_optimizer.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/ort_optimizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ea1a0969fd9d274b678e413327866be9800025f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/ort_optimizer.py
@@ -0,0 +1,136 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+"""
+ONNX Model Optimizer for Stable Diffusion
+"""
+
+import gc
+import logging
+import os
+import shutil
+import tempfile
+from pathlib import Path
+
+import onnx
+from packaging import version
+
+from onnxruntime.transformers.fusion_options import FusionOptions
+from onnxruntime.transformers.onnx_model_clip import ClipOnnxModel
+from onnxruntime.transformers.onnx_model_unet import UnetOnnxModel
+from onnxruntime.transformers.onnx_model_vae import VaeOnnxModel
+from onnxruntime.transformers.optimizer import optimize_by_onnxruntime, optimize_model
+
+logger = logging.getLogger(__name__)
+
+
+class OrtStableDiffusionOptimizer:
+    def __init__(self, model_type: str):
+        assert model_type in ["vae", "unet", "clip"]
+        self.model_type = model_type
+        self.model_type_class_mapping = {
+            "unet": UnetOnnxModel,
+            "vae": VaeOnnxModel,
+            "clip": ClipOnnxModel,
+        }
+
+    def _optimize_by_ort(self, onnx_model, use_external_data_format, tmp_dir):
+        # Save to a temporary file so that we can load it with Onnx Runtime.
+        logger.info("Saving a temporary model to run OnnxRuntime graph optimizations...")
+        tmp_model_path = Path(tmp_dir) / "model.onnx"
+        onnx_model.save_model_to_file(str(tmp_model_path), use_external_data_format=use_external_data_format)
+
+        del onnx_model
+        gc.collect()
+
+        ort_optimized_model_path = Path(tmp_dir) / "optimized.onnx"
+        optimize_by_onnxruntime(
+            str(tmp_model_path),
+            use_gpu=True,
+            optimized_model_path=str(ort_optimized_model_path),
+            save_as_external_data=use_external_data_format,
+            external_data_filename="optimized.onnx_data",
+        )
+        model = onnx.load(str(ort_optimized_model_path), load_external_data=True)
+        return self.model_type_class_mapping[self.model_type](model)
+
+    def optimize_by_ort(self, onnx_model, use_external_data_format=False, tmp_dir=None):
+        # Use this step to see the final graph that executed by Onnx Runtime.
+        if tmp_dir is None:
+            with tempfile.TemporaryDirectory() as temp_dir:
+                return self._optimize_by_ort(onnx_model, use_external_data_format, temp_dir)
+        else:
+            os.makedirs(tmp_dir, exist_ok=True)
+            model = self._optimize_by_ort(onnx_model, use_external_data_format, tmp_dir)
+            shutil.rmtree(tmp_dir)
+            return model
+
+    def optimize(
+        self,
+        input_fp32_onnx_path,
+        optimized_onnx_path,
+        float16=True,
+        keep_io_types=False,
+        fp32_op_list=None,
+        keep_outputs=None,
+        optimize_by_ort=True,
+        optimize_by_fusion=True,
+        final_target_float16=True,
+        tmp_dir=None,
+    ):
+        """Optimize onnx model using ONNX Runtime transformers optimizer"""
+        logger.info(f"Optimize {input_fp32_onnx_path}...")
+
+        if optimize_by_fusion:
+            fusion_options = FusionOptions(self.model_type)
+
+            # It is allowed float16=False and final_target_float16=True, for using fp32 as intermediate optimization step.
+            # For rare fp32 use case, we can disable packed kv/qkv since there is no fp32 TRT fused attention kernel.
+            if self.model_type in ["unet"] and not final_target_float16:
+                fusion_options.enable_packed_kv = False
+                fusion_options.enable_packed_qkv = False
+
+            m = optimize_model(
+                input_fp32_onnx_path,
+                model_type=self.model_type,
+                num_heads=0,  # will be deduced from graph
+                hidden_size=0,  # will be deduced from graph
+                opt_level=0,
+                optimization_options=fusion_options,
+                use_gpu=True,
+            )
+        else:
+            model = onnx.load_model(input_fp32_onnx_path, load_external_data=True)
+            m = self.model_type_class_mapping[self.model_type](model)
+
+        if keep_outputs:
+            m.prune_graph(outputs=keep_outputs)
+
+        model_size = m.model.ByteSize()
+
+        # model size might be negative (overflow?) in Windows.
+        use_external_data_format = model_size <= 0 or model_size >= onnx.checker.MAXIMUM_PROTOBUF
+
+        # Note that ORT < 1.16 could not save model larger than 2GB.
+        # This step is is optional since it has no impact on inference latency.
+        # The optimized model is not portable. It could only run in the same execution provider (CUDA EP in this case).
+        # When the model has been optimized by onnxruntime, we can disable optimization in SessionOption
+        # to save session creation time. Another benefit is to inspect the final graph for developing purpose.
+        from onnxruntime import __version__ as ort_version  # noqa: PLC0415
+
+        if optimize_by_ort and (version.parse(ort_version) >= version.parse("1.16.0") or not use_external_data_format):
+            m = self.optimize_by_ort(m, use_external_data_format=use_external_data_format, tmp_dir=tmp_dir)
+
+        if float16:
+            logger.info("Convert to float16 ...")
+            m.convert_float_to_float16(
+                keep_io_types=keep_io_types,
+                op_block_list=fp32_op_list,
+            )
+
+        m.get_operator_statistics()
+        m.get_fused_operator_statistics()
+        m.save_model_to_file(optimized_onnx_path, use_external_data_format=use_external_data_format)
+        logger.info("%s is optimized: %s", self.model_type, optimized_onnx_path)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/pipeline_stable_diffusion.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/pipeline_stable_diffusion.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ad7ac91a9df978a537ccad546b891e63aa83e6a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/pipeline_stable_diffusion.py
@@ -0,0 +1,831 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+# Modified from TensorRT demo diffusion, which has the following license:
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+
+import os
+import pathlib
+import random
+import time
+from typing import Any
+
+import numpy as np
+import nvtx
+import torch
+from cuda import cudart
+from diffusion_models import PipelineInfo, get_tokenizer
+from diffusion_schedulers import DDIMScheduler, EulerAncestralDiscreteScheduler, LCMScheduler, UniPCMultistepScheduler
+from engine_builder import EngineType
+from engine_builder_ort_cuda import OrtCudaEngineBuilder
+from engine_builder_ort_trt import OrtTensorrtEngineBuilder
+from engine_builder_tensorrt import TensorrtEngineBuilder
+from engine_builder_torch import TorchEngineBuilder
+from PIL import Image
+
+
+class StableDiffusionPipeline:
+    """
+    Stable Diffusion pipeline using TensorRT.
+    """
+
+    def __init__(
+        self,
+        pipeline_info: PipelineInfo,
+        max_batch_size=16,
+        scheduler="DDIM",
+        device="cuda",
+        output_dir=".",
+        verbose=False,
+        nvtx_profile=False,
+        use_cuda_graph=False,
+        framework_model_dir="pytorch_model",
+        engine_type: EngineType = EngineType.ORT_CUDA,
+    ):
+        """
+        Initializes the Diffusion pipeline.
+
+        Args:
+            pipeline_info (PipelineInfo):
+                Version and Type of pipeline.
+            max_batch_size (int):
+                Maximum batch size for dynamic batch engine.
+            scheduler (str):
+                The scheduler to guide the denoising process. Must be one of [DDIM, EulerA, UniPC, LCM].
+            device (str):
+                PyTorch device to run inference. Default: 'cuda'
+            output_dir (str):
+                Output directory for log files and image artifacts
+            verbose (bool):
+                Enable verbose logging.
+            nvtx_profile (bool):
+                Insert NVTX profiling markers.
+            use_cuda_graph (bool):
+                Use CUDA graph to capture engine execution and then launch inference
+            framework_model_dir (str):
+                cache directory for framework checkpoints
+            engine_type (EngineType)
+                backend engine type like ORT_TRT or TRT
+        """
+
+        self.pipeline_info = pipeline_info
+        self.version = pipeline_info.version
+
+        self.vae_scaling_factor = pipeline_info.vae_scaling_factor()
+
+        self.max_batch_size = max_batch_size
+
+        self.framework_model_dir = framework_model_dir
+        self.output_dir = output_dir
+        for directory in [self.framework_model_dir, self.output_dir]:
+            if not os.path.exists(directory):
+                print(f"[I] Create directory: {directory}")
+                pathlib.Path(directory).mkdir(parents=True)
+
+        self.device = device
+        self.torch_device = torch.device(device, torch.cuda.current_device())
+        self.verbose = verbose
+        self.nvtx_profile = nvtx_profile
+
+        self.use_cuda_graph = use_cuda_graph
+
+        self.tokenizer = None
+        self.tokenizer2 = None
+
+        self.generator = torch.Generator(device="cuda")
+        self.actual_steps = None
+
+        self.current_scheduler = None
+        self.set_scheduler(scheduler)
+
+        # backend engine
+        self.engine_type = engine_type
+        if engine_type == EngineType.TRT:
+            self.backend = TensorrtEngineBuilder(pipeline_info, max_batch_size, device, use_cuda_graph)
+        elif engine_type == EngineType.ORT_TRT:
+            self.backend = OrtTensorrtEngineBuilder(pipeline_info, max_batch_size, device, use_cuda_graph)
+        elif engine_type == EngineType.ORT_CUDA:
+            self.backend = OrtCudaEngineBuilder(pipeline_info, max_batch_size, device, use_cuda_graph)
+        elif engine_type == EngineType.TORCH:
+            self.backend = TorchEngineBuilder(pipeline_info, max_batch_size, device, use_cuda_graph)
+        else:
+            raise RuntimeError(f"Backend engine type {engine_type.name} is not supported")
+
+        # Load text tokenizer
+        if not self.pipeline_info.is_xl_refiner():
+            self.tokenizer = get_tokenizer(self.pipeline_info, self.framework_model_dir, subfolder="tokenizer")
+
+        if self.pipeline_info.is_xl():
+            self.tokenizer2 = get_tokenizer(self.pipeline_info, self.framework_model_dir, subfolder="tokenizer_2")
+
+        self.control_image_processor = None
+        if self.pipeline_info.is_xl() and self.pipeline_info.controlnet:
+            from diffusers.image_processor import VaeImageProcessor  # noqa: PLC0415
+
+            self.control_image_processor = VaeImageProcessor(
+                vae_scale_factor=8, do_convert_rgb=True, do_normalize=False
+            )
+
+        # Create CUDA events
+        self.events = {}
+        for stage in ["clip", "denoise", "vae", "vae_encoder", "pil"]:
+            for marker in ["start", "stop"]:
+                self.events[stage + "-" + marker] = cudart.cudaEventCreate()[1]
+        self.markers = {}
+
+    def is_backend_tensorrt(self):
+        return self.engine_type == EngineType.TRT
+
+    def set_scheduler(self, scheduler: str):
+        if scheduler == self.current_scheduler:
+            return
+
+        # Scheduler options
+        sched_opts = {"num_train_timesteps": 1000, "beta_start": 0.00085, "beta_end": 0.012}
+        if self.version in ("2.0", "2.1"):
+            sched_opts["prediction_type"] = "v_prediction"
+        else:
+            sched_opts["prediction_type"] = "epsilon"
+
+        if scheduler == "DDIM":
+            self.scheduler = DDIMScheduler(device=self.device, **sched_opts)
+        elif scheduler == "EulerA":
+            self.scheduler = EulerAncestralDiscreteScheduler(device=self.device, **sched_opts)
+        elif scheduler == "UniPC":
+            self.scheduler = UniPCMultistepScheduler(device=self.device, **sched_opts)
+        elif scheduler == "LCM":
+            self.scheduler = LCMScheduler(device=self.device, **sched_opts)
+        else:
+            raise ValueError("Scheduler should be either DDIM, EulerA, UniPC or LCM")
+
+        self.current_scheduler = scheduler
+        self.denoising_steps = None
+
+    def set_denoising_steps(self, denoising_steps: int):
+        if not (self.denoising_steps == denoising_steps and isinstance(self.scheduler, DDIMScheduler)):
+            self.scheduler.set_timesteps(denoising_steps)
+            self.scheduler.configure()
+            self.denoising_steps = denoising_steps
+
+    def load_resources(self, image_height, image_width, batch_size):
+        # If engine is built with static input shape, call this only once after engine build.
+        # Otherwise, it need be called before every inference run.
+        self.backend.load_resources(image_height, image_width, batch_size)
+
+    def set_random_seed(self, seed):
+        if isinstance(seed, int):
+            self.generator.manual_seed(seed)
+        else:
+            self.generator.seed()
+
+    def get_current_seed(self):
+        return self.generator.initial_seed()
+
+    def teardown(self):
+        for e in self.events.values():
+            cudart.cudaEventDestroy(e)
+
+        if self.backend:
+            self.backend.teardown()
+
+    def run_engine(self, model_name, feed_dict):
+        return self.backend.run_engine(model_name, feed_dict)
+
+    def initialize_latents(self, batch_size, unet_channels, latent_height, latent_width):
+        latents_dtype = torch.float16
+        latents_shape = (batch_size, unet_channels, latent_height, latent_width)
+        latents = torch.randn(latents_shape, device=self.device, dtype=latents_dtype, generator=self.generator)
+        # Scale the initial noise by the standard deviation required by the scheduler
+        latents = latents * self.scheduler.init_noise_sigma
+        return latents
+
+    def initialize_timesteps(self, timesteps, strength):
+        """Initialize timesteps for refiner."""
+        self.scheduler.set_timesteps(timesteps)
+        offset = self.scheduler.steps_offset if hasattr(self.scheduler, "steps_offset") else 0
+        init_timestep = int(timesteps * strength) + offset
+        init_timestep = min(init_timestep, timesteps)
+        t_start = max(timesteps - init_timestep + offset, 0)
+        timesteps = self.scheduler.timesteps[t_start:].to(self.device)
+        return timesteps, t_start
+
+    def initialize_refiner(self, batch_size, image, strength):
+        """Add noise to a reference image."""
+        # Initialize timesteps
+        timesteps, t_start = self.initialize_timesteps(self.denoising_steps, strength)
+
+        latent_timestep = timesteps[:1].repeat(batch_size)
+
+        # Pre-process input image
+        image = self.preprocess_images(batch_size, (image,))[0]
+
+        # VAE encode init image
+        if image.shape[1] == 4:
+            init_latents = image
+        else:
+            init_latents = self.encode_image(image)
+
+        # Add noise to latents using timesteps
+        noise = torch.randn(init_latents.shape, device=self.device, dtype=torch.float16, generator=self.generator)
+
+        latents = self.scheduler.add_noise(init_latents, noise, t_start, latent_timestep)
+
+        return timesteps, t_start, latents
+
+    def _get_add_time_ids(
+        self,
+        original_size,
+        crops_coords_top_left,
+        target_size,
+        aesthetic_score,
+        negative_aesthetic_score,
+        dtype,
+        requires_aesthetics_score,
+    ):
+        if requires_aesthetics_score:
+            add_time_ids = list(original_size + crops_coords_top_left + (aesthetic_score,))
+            add_neg_time_ids = list(original_size + crops_coords_top_left + (negative_aesthetic_score,))
+        else:
+            add_time_ids = list(original_size + crops_coords_top_left + target_size)
+            add_neg_time_ids = list(original_size + crops_coords_top_left + target_size)
+
+        add_time_ids = torch.tensor([add_time_ids], dtype=dtype)
+        add_neg_time_ids = torch.tensor([add_neg_time_ids], dtype=dtype)
+
+        return add_time_ids, add_neg_time_ids
+
+    def start_profile(self, name, color="blue"):
+        if self.nvtx_profile:
+            self.markers[name] = nvtx.start_range(message=name, color=color)
+        event_name = name + "-start"
+        if event_name in self.events:
+            cudart.cudaEventRecord(self.events[event_name], 0)
+
+    def stop_profile(self, name):
+        event_name = name + "-stop"
+        if event_name in self.events:
+            cudart.cudaEventRecord(self.events[event_name], 0)
+        if self.nvtx_profile:
+            nvtx.end_range(self.markers[name])
+
+    def preprocess_images(self, batch_size, images=()):
+        self.start_profile("preprocess", color="pink")
+        init_images = []
+        for i in images:
+            image = i.to(self.device)
+            if image.shape[0] != batch_size:
+                image = image.repeat(batch_size, 1, 1, 1)
+            init_images.append(image)
+        self.stop_profile("preprocess")
+        return tuple(init_images)
+
+    def preprocess_controlnet_images(
+        self, batch_size, images=None, do_classifier_free_guidance=True, height=1024, width=1024
+    ):
+        """
+        Process a list of PIL.Image.Image as control images, and return a torch tensor.
+        """
+        if images is None:
+            return None
+        self.start_profile("preprocess", color="pink")
+
+        if not self.pipeline_info.is_xl():
+            images = [
+                torch.from_numpy(
+                    (np.array(image.convert("RGB")).astype(np.float32) / 255.0)[..., None].transpose(3, 2, 0, 1)
+                )
+                .to(device=self.device, dtype=torch.float16)
+                .repeat_interleave(batch_size, dim=0)
+                for image in images
+            ]
+        else:
+            images = [
+                self.control_image_processor.preprocess(image, height=height, width=width)
+                .to(device=self.device, dtype=torch.float16)
+                .repeat_interleave(batch_size, dim=0)
+                for image in images
+            ]
+
+        if do_classifier_free_guidance:
+            images = [torch.cat([i] * 2) for i in images]
+        images = torch.cat([image[None, ...] for image in images], dim=0)
+
+        self.stop_profile("preprocess")
+        return images
+
+    def encode_prompt(
+        self,
+        prompt,
+        negative_prompt,
+        encoder="clip",
+        tokenizer=None,
+        pooled_outputs=False,
+        output_hidden_states=False,
+        force_zeros_for_empty_prompt=False,
+        do_classifier_free_guidance=True,
+        dtype=torch.float16,
+    ):
+        if tokenizer is None:
+            tokenizer = self.tokenizer
+
+        self.start_profile("clip", color="green")
+
+        def tokenize(prompt, output_hidden_states):
+            text_input_ids = (
+                tokenizer(
+                    prompt,
+                    padding="max_length",
+                    max_length=tokenizer.model_max_length,
+                    truncation=True,
+                    return_tensors="pt",
+                )
+                .input_ids.type(torch.int32)
+                .to(self.device)
+            )
+
+            hidden_states = None
+            if self.engine_type == EngineType.TORCH:
+                outputs = self.backend.engines[encoder](text_input_ids)
+                text_embeddings = outputs[0]
+                if output_hidden_states:
+                    hidden_states = outputs["last_hidden_state"]
+            else:
+                outputs = self.run_engine(encoder, {"input_ids": text_input_ids})
+                text_embeddings = outputs["text_embeddings"]
+                if output_hidden_states:
+                    hidden_states = outputs["hidden_states"]
+            return text_embeddings, hidden_states
+
+        # Tokenize prompt
+        text_embeddings, hidden_states = tokenize(prompt, output_hidden_states)
+
+        # NOTE: output tensor for CLIP must be cloned because it will be overwritten when called again for negative prompt
+        text_embeddings = text_embeddings.clone()
+        if hidden_states is not None:
+            hidden_states = hidden_states.clone()
+
+        # Note: negative prompt embedding is not needed for SD XL when guidance <= 1
+        if do_classifier_free_guidance:
+            # For SD XL base, handle force_zeros_for_empty_prompt
+            is_empty_negative_prompt = all(not i for i in negative_prompt)
+            if force_zeros_for_empty_prompt and is_empty_negative_prompt:
+                uncond_embeddings = torch.zeros_like(text_embeddings)
+                if output_hidden_states:
+                    uncond_hidden_states = torch.zeros_like(hidden_states)
+            else:
+                # Tokenize negative prompt
+                uncond_embeddings, uncond_hidden_states = tokenize(negative_prompt, output_hidden_states)
+
+            # Concatenate the unconditional and text embeddings into a single batch to avoid doing two forward passes for classifier free guidance
+            text_embeddings = torch.cat([uncond_embeddings, text_embeddings])
+
+            if output_hidden_states:
+                hidden_states = torch.cat([uncond_hidden_states, hidden_states])
+
+        self.stop_profile("clip")
+
+        if pooled_outputs:
+            # For text encoder in sdxl base
+            return hidden_states.to(dtype=dtype), text_embeddings.to(dtype=dtype)
+
+        if output_hidden_states:
+            # For text encoder 2 in sdxl base or refiner
+            return hidden_states.to(dtype=dtype)
+
+        # For text encoder in sd 1.5
+        return text_embeddings.to(dtype=dtype)
+
+    def denoise_latent(
+        self,
+        latents,
+        text_embeddings,
+        denoiser="unet",
+        timesteps=None,
+        step_offset=0,
+        guidance=7.5,
+        add_kwargs=None,
+    ):
+        do_classifier_free_guidance = guidance > 1.0
+
+        self.start_profile("denoise", color="blue")
+
+        if not isinstance(timesteps, torch.Tensor):
+            timesteps = self.scheduler.timesteps
+
+        for step_index, timestep in enumerate(timesteps):
+            # Expand the latents if we are doing classifier free guidance
+            latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents
+
+            latent_model_input = self.scheduler.scale_model_input(
+                latent_model_input, step_offset + step_index, timestep
+            )
+
+            # Predict the noise residual
+            if self.nvtx_profile:
+                nvtx_unet = nvtx.start_range(message="unet", color="blue")
+
+            params = {
+                "sample": latent_model_input,
+                "timestep": timestep.to(latents.dtype),
+                "encoder_hidden_states": text_embeddings,
+            }
+
+            if add_kwargs:
+                params.update(add_kwargs)
+
+            noise_pred = self.run_engine(denoiser, params)["latent"]
+
+            if self.nvtx_profile:
+                nvtx.end_range(nvtx_unet)
+
+            # perform guidance
+            if do_classifier_free_guidance:
+                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
+                noise_pred = noise_pred_uncond + guidance * (noise_pred_text - noise_pred_uncond)
+
+            if type(self.scheduler) is UniPCMultistepScheduler:
+                latents = self.scheduler.step(noise_pred, timestep, latents, return_dict=False)[0]
+            elif type(self.scheduler) is LCMScheduler:
+                latents = self.scheduler.step(noise_pred, timestep, latents, generator=self.generator)[0]
+            else:
+                latents = self.scheduler.step(noise_pred, latents, step_offset + step_index, timestep)
+
+        # The actual number of steps. It might be different from denoising_steps.
+        self.actual_steps = len(timesteps)
+
+        self.stop_profile("denoise")
+        return latents
+
+    def encode_image(self, image):
+        self.start_profile("vae_encoder", color="red")
+        init_latents = self.run_engine("vae_encoder", {"images": image})["latent"]
+        init_latents = self.vae_scaling_factor * init_latents
+        self.stop_profile("vae_encoder")
+        return init_latents
+
+    def decode_latent(self, latents):
+        self.start_profile("vae", color="red")
+        images = self.backend.vae_decode(latents)
+        self.stop_profile("vae")
+        return images
+
+    def print_summary(self, tic, toc, batch_size, vae_enc=False, pil=False) -> dict[str, Any]:
+        throughput = batch_size / (toc - tic)
+        latency_clip = cudart.cudaEventElapsedTime(self.events["clip-start"], self.events["clip-stop"])[1]
+        latency_unet = cudart.cudaEventElapsedTime(self.events["denoise-start"], self.events["denoise-stop"])[1]
+        latency_vae = cudart.cudaEventElapsedTime(self.events["vae-start"], self.events["vae-stop"])[1]
+        latency_vae_encoder = (
+            cudart.cudaEventElapsedTime(self.events["vae_encoder-start"], self.events["vae_encoder-stop"])[1]
+            if vae_enc
+            else None
+        )
+        latency_pil = cudart.cudaEventElapsedTime(self.events["pil-start"], self.events["pil-stop"])[1] if pil else None
+
+        latency = (toc - tic) * 1000.0
+
+        print("|----------------|--------------|")
+        print("| {:^14} | {:^12} |".format("Module", "Latency"))
+        print("|----------------|--------------|")
+        if vae_enc:
+            print("| {:^14} | {:>9.2f} ms |".format("VAE-Enc", latency_vae_encoder))
+        print("| {:^14} | {:>9.2f} ms |".format("CLIP", latency_clip))
+        print(
+            "| {:^14} | {:>9.2f} ms |".format(
+                "UNet" + ("+CNet" if self.pipeline_info.controlnet else "") + " x " + str(self.actual_steps),
+                latency_unet,
+            )
+        )
+        print("| {:^14} | {:>9.2f} ms |".format("VAE-Dec", latency_vae))
+        pipeline = "Refiner" if self.pipeline_info.is_xl_refiner() else "Pipeline"
+        if pil:
+            print("| {:^14} | {:>9.2f} ms |".format("PIL", latency_pil))
+        print("|----------------|--------------|")
+        print(f"| {pipeline:^14} | {latency:>9.2f} ms |")
+        print("|----------------|--------------|")
+        print(f"Throughput: {throughput:.2f} image/s")
+
+        perf_data = {
+            "latency_clip": latency_clip,
+            "latency_unet": latency_unet,
+            "latency_vae": latency_vae,
+            "latency_pil": latency_pil,
+            "latency": latency,
+            "throughput": throughput,
+        }
+        if vae_enc:
+            perf_data["latency_vae_encoder"] = latency_vae_encoder
+        return perf_data
+
+    @staticmethod
+    def pt_to_pil(images):
+        images = (
+            ((images + 1) * 255 / 2).clamp(0, 255).detach().permute(0, 2, 3, 1).round().type(torch.uint8).cpu().numpy()
+        )
+        return [Image.fromarray(images[i]) for i in range(images.shape[0])]
+
+    @staticmethod
+    def pt_to_numpy(images: torch.FloatTensor):
+        """
+        Convert a PyTorch tensor to a NumPy image.
+        """
+        return ((images + 1) / 2).clamp(0, 1).detach().permute(0, 2, 3, 1).float().cpu().numpy()
+
+    def metadata(self) -> dict[str, Any]:
+        data = {
+            "actual_steps": self.actual_steps,
+            "seed": self.get_current_seed(),
+            "name": self.pipeline_info.name(),
+            "custom_vae": self.pipeline_info.custom_fp16_vae(),
+            "custom_unet": self.pipeline_info.custom_unet(),
+        }
+
+        if self.engine_type == EngineType.ORT_CUDA:
+            for engine_name, engine in self.backend.engines.items():
+                data.update(engine.metadata(engine_name))
+
+        return data
+
+    def save_images(self, images: list, prompt: list[str], negative_prompt: list[str], metadata: dict[str, Any]):
+        session_id = str(random.randint(1000, 9999))
+        for i, image in enumerate(images):
+            seed = str(self.get_current_seed())
+            prefix = "".join(x for x in prompt[i] if x.isalnum() or x in ", -").replace(" ", "_")[:20]
+            parts = [prefix, session_id, str(i + 1), str(seed), self.current_scheduler, str(self.actual_steps)]
+            image_path = os.path.join(self.output_dir, "-".join(parts) + ".png")
+            print(f"Saving image {i + 1} / {len(images)} to: {image_path}")
+
+            from PIL import PngImagePlugin  # noqa: PLC0415
+
+            info = PngImagePlugin.PngInfo()
+            for k, v in metadata.items():
+                info.add_text(k, str(v))
+            info.add_text("prompt", prompt[i])
+            info.add_text("negative_prompt", negative_prompt[i])
+
+            image.save(image_path, "PNG", pnginfo=info)
+
+    def _infer(
+        self,
+        prompt,
+        negative_prompt,
+        image_height,
+        image_width,
+        denoising_steps=30,
+        guidance=5.0,
+        seed=None,
+        image=None,
+        strength=0.3,
+        controlnet_images=None,
+        controlnet_scales=None,
+        show_latency=False,
+        output_type="pil",
+    ):
+        if show_latency:
+            torch.cuda.synchronize()
+            start_time = time.perf_counter()
+
+        assert len(prompt) == len(negative_prompt)
+        batch_size = len(prompt)
+
+        self.set_denoising_steps(denoising_steps)
+        self.set_random_seed(seed)
+
+        timesteps = None
+        step_offset = 0
+        with torch.inference_mode(), torch.autocast("cuda"):
+            if image is not None:
+                timesteps, step_offset, latents = self.initialize_refiner(
+                    batch_size=batch_size,
+                    image=image,
+                    strength=strength,
+                )
+            else:
+                # Pre-initialize latents
+                latents = self.initialize_latents(
+                    batch_size=batch_size,
+                    unet_channels=4,
+                    latent_height=(image_height // 8),
+                    latent_width=(image_width // 8),
+                )
+
+            do_classifier_free_guidance = guidance > 1.0
+            if not self.pipeline_info.is_xl():
+                denoiser = "unet"
+                text_embeddings = self.encode_prompt(
+                    prompt,
+                    negative_prompt,
+                    do_classifier_free_guidance=do_classifier_free_guidance,
+                    dtype=latents.dtype,
+                )
+                add_kwargs = {}
+            else:
+                denoiser = "unetxl"
+
+                # Time embeddings
+                original_size = (image_height, image_width)
+                crops_coords_top_left = (0, 0)
+                target_size = (image_height, image_width)
+                aesthetic_score = 6.0
+                negative_aesthetic_score = 2.5
+                add_time_ids, add_negative_time_ids = self._get_add_time_ids(
+                    original_size,
+                    crops_coords_top_left,
+                    target_size,
+                    aesthetic_score,
+                    negative_aesthetic_score,
+                    dtype=latents.dtype,
+                    requires_aesthetics_score=self.pipeline_info.is_xl_refiner(),
+                )
+                if do_classifier_free_guidance:
+                    add_time_ids = torch.cat([add_negative_time_ids, add_time_ids], dim=0)
+                add_time_ids = add_time_ids.to(device=self.device).repeat(batch_size, 1)
+
+                if self.pipeline_info.is_xl_refiner():
+                    # CLIP text encoder 2
+                    text_embeddings, pooled_embeddings2 = self.encode_prompt(
+                        prompt,
+                        negative_prompt,
+                        encoder="clip2",
+                        tokenizer=self.tokenizer2,
+                        pooled_outputs=True,
+                        output_hidden_states=True,
+                        dtype=latents.dtype,
+                    )
+                    add_kwargs = {"text_embeds": pooled_embeddings2, "time_ids": add_time_ids}
+                else:  # XL Base
+                    # CLIP text encoder
+                    text_embeddings = self.encode_prompt(
+                        prompt,
+                        negative_prompt,
+                        encoder="clip",
+                        tokenizer=self.tokenizer,
+                        output_hidden_states=True,
+                        force_zeros_for_empty_prompt=True,
+                        do_classifier_free_guidance=do_classifier_free_guidance,
+                        dtype=latents.dtype,
+                    )
+                    # CLIP text encoder 2
+                    text_embeddings2, pooled_embeddings2 = self.encode_prompt(
+                        prompt,
+                        negative_prompt,
+                        encoder="clip2",
+                        tokenizer=self.tokenizer2,
+                        pooled_outputs=True,
+                        output_hidden_states=True,
+                        force_zeros_for_empty_prompt=True,
+                        do_classifier_free_guidance=do_classifier_free_guidance,
+                        dtype=latents.dtype,
+                    )
+
+                    # Merged text embeddings
+                    text_embeddings = torch.cat([text_embeddings, text_embeddings2], dim=-1)
+
+                    add_kwargs = {"text_embeds": pooled_embeddings2, "time_ids": add_time_ids}
+
+            if self.pipeline_info.controlnet:
+                controlnet_images = self.preprocess_controlnet_images(
+                    latents.shape[0],
+                    controlnet_images,
+                    do_classifier_free_guidance=do_classifier_free_guidance,
+                    height=image_height,
+                    width=image_width,
+                )
+                add_kwargs.update(
+                    {
+                        "controlnet_images": controlnet_images,
+                        "controlnet_scales": controlnet_scales.to(controlnet_images.dtype).to(controlnet_images.device),
+                    }
+                )
+
+            # UNet denoiser
+            latents = self.denoise_latent(
+                latents,
+                text_embeddings,
+                timesteps=timesteps,
+                step_offset=step_offset,
+                denoiser=denoiser,
+                guidance=guidance,
+                add_kwargs=add_kwargs,
+            )
+
+        with torch.inference_mode():
+            # VAE decode latent
+            if output_type == "latent":
+                images = latents
+            else:
+                images = self.decode_latent(latents / self.vae_scaling_factor)
+                if output_type == "pil":
+                    self.start_profile("pil", color="green")
+                    images = self.pt_to_pil(images)
+                    self.stop_profile("pil")
+
+        perf_data = None
+        if show_latency:
+            torch.cuda.synchronize()
+            end_time = time.perf_counter()
+            perf_data = self.print_summary(
+                start_time, end_time, batch_size, vae_enc=self.pipeline_info.is_xl_refiner(), pil=(output_type == "pil")
+            )
+
+        return images, perf_data
+
+    def run(
+        self,
+        prompt: list[str],
+        negative_prompt: list[str],
+        image_height: int,
+        image_width: int,
+        denoising_steps: int = 30,
+        guidance: float = 5.0,
+        seed: int | None = None,
+        image: torch.Tensor | None = None,
+        strength: float = 0.3,
+        controlnet_images: torch.Tensor | None = None,
+        controlnet_scales: torch.Tensor | None = None,
+        show_latency: bool = False,
+        output_type: str = "pil",
+        deterministic: bool = False,
+    ):
+        """
+        Run the diffusion pipeline.
+
+        Args:
+            prompt (List[str]):
+                The text prompt to guide image generation.
+            negative_prompt (List[str]):
+                The prompt not to guide the image generation.
+            image_height (int):
+                Height (in pixels) of the image to be generated. Must be a multiple of 8.
+            image_width (int):
+                Width (in pixels) of the image to be generated. Must be a multiple of 8.
+            denoising_steps (int):
+                Number of denoising steps. More steps usually lead to higher quality image at the expense of slower inference.
+            guidance (float):
+                Higher guidance scale encourages to generate images that are closely linked to the text prompt.
+            seed (int):
+                Seed for the random generator
+            image (tuple[torch.Tensor]):
+                Reference image.
+            strength (float):
+                Indicates extent to transform the reference image, which is used as a starting point,
+                and more noise is added the higher the strength.
+            show_latency (bool):
+                Whether return latency data.
+            output_type (str):
+                It can be "latent", "pt" or "pil".
+        """
+        if deterministic:
+            torch.use_deterministic_algorithms(True)
+
+        if self.is_backend_tensorrt():
+            import tensorrt as trt  # noqa: PLC0415
+            from trt_utilities import TRT_LOGGER  # noqa: PLC0415
+
+            with trt.Runtime(TRT_LOGGER):
+                return self._infer(
+                    prompt,
+                    negative_prompt,
+                    image_height,
+                    image_width,
+                    denoising_steps=denoising_steps,
+                    guidance=guidance,
+                    seed=seed,
+                    image=image,
+                    strength=strength,
+                    controlnet_images=controlnet_images,
+                    controlnet_scales=controlnet_scales,
+                    show_latency=show_latency,
+                    output_type=output_type,
+                )
+        else:
+            return self._infer(
+                prompt,
+                negative_prompt,
+                image_height,
+                image_width,
+                denoising_steps=denoising_steps,
+                guidance=guidance,
+                seed=seed,
+                image=image,
+                strength=strength,
+                controlnet_images=controlnet_images,
+                controlnet_scales=controlnet_scales,
+                show_latency=show_latency,
+                output_type=output_type,
+            )
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/trt_utilities.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/trt_utilities.py
new file mode 100644
index 0000000000000000000000000000000000000000..c75d53bb61f6ff8fd615ab303307effad4a8d059
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/stable_diffusion/trt_utilities.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import tensorrt as trt
+
+TRT_LOGGER = trt.Logger(trt.Logger.ERROR)
+
+
+def init_trt_plugins():
+    # Register TensorRT plugins
+    trt.init_libnvinfer_plugins(TRT_LOGGER, "")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5ef71ce9e355e17ea1c2ca9fb648951d917734b5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os.path
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..4d891628211248f79a58de18f3aab8bc08606e6b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/convert_to_onnx.py
@@ -0,0 +1,318 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import copy
+import logging
+import os
+
+import torch
+from benchmark_helper import (
+    Precision,
+    create_onnxruntime_session,
+    prepare_environment,
+    setup_logger,
+)
+from onnx.shape_inference import infer_shapes_path
+from t5_helper import PRETRAINED_MT5_MODELS, PRETRAINED_T5_MODELS, T5Helper
+from transformers import MT5Config, T5Config
+
+logger = logging.getLogger("")
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+
+    pretrained_models = PRETRAINED_T5_MODELS + PRETRAINED_MT5_MODELS
+    parser.add_argument(
+        "-m",
+        "--model_name_or_path",
+        required=False,
+        default=PRETRAINED_T5_MODELS[0],
+        type=str,
+        help="Model path, or pretrained model name in the list: " + ", ".join(pretrained_models),
+    )
+
+    parser.add_argument(
+        "--model_type",
+        required=False,
+        type=str,
+        default="t5",
+        choices=["t5", "mt5"],
+        help="Model type: either t5 (default) or mt5",
+    )
+
+    parser.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default=os.path.join(".", "cache_models"),
+        help="Directory to cache pre-trained models",
+    )
+
+    parser.add_argument(
+        "--output",
+        required=False,
+        type=str,
+        default=os.path.join(".", "onnx_models"),
+        help="Output directory",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--optimize_onnx",
+        required=False,
+        action="store_true",
+        help="Use optimizer.py to optimize onnx model",
+    )
+    parser.set_defaults(optimize_onnx=False)
+
+    parser.add_argument("--use_gpu", required=False, action="store_true", help="use GPU for inference")
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "-p",
+        "--precision",
+        required=False,
+        type=str,
+        default=Precision.FLOAT32.value,
+        choices=[Precision.FLOAT32.value, Precision.FLOAT16.value],
+        help="Precision of model to run. fp32 for full precision, fp16 for half precision",
+    )
+
+    parser.add_argument("--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument("-e", "--use_external_data_format", required=False, action="store_true")
+    parser.set_defaults(use_external_data_format=False)
+
+    parser.add_argument(
+        "-s",
+        "--use_decoder_start_token",
+        required=False,
+        action="store_true",
+        help="Use config.decoder_start_token_id. Otherwise, add an extra graph input for decoder_input_ids.",
+    )
+    parser.set_defaults(use_decoder_start_token=False)
+
+    parser.add_argument(
+        "-w",
+        "--overwrite",
+        required=False,
+        action="store_true",
+        help="overwrite existing ONNX model",
+    )
+    parser.set_defaults(overwrite=False)
+
+    parser.add_argument(
+        "--disable_auto_mixed_precision",
+        required=False,
+        action="store_true",
+        help="do not use auto mixed precision conversion",
+    )
+    parser.set_defaults(disable_auto_mixed_precision=False)
+
+    parser.add_argument(
+        "--force_fp16_io",
+        required=False,
+        action="store_true",
+        help="Force to convert all float inputs and outputs to fp16 when precision is fp16.",
+    )
+    parser.set_defaults(force_fp16_io=False)
+
+    parser.add_argument(
+        "--use_int64_inputs",
+        required=False,
+        action="store_true",
+        help="Use int64 instead of int32 for input_ids, position_ids and attention_mask.",
+    )
+    parser.set_defaults(use_int64_inputs=False)
+
+    parser.add_argument(
+        "--state_dict_path",
+        type=str,
+        default="",
+        help="filepath to load pre-trained model with custom state dictionary (e.g. pytorch_model.bin)",
+    )
+
+    parser.add_argument(
+        "--encoder_decoder_init",
+        required=False,
+        action="store_true",
+        help="Combine encoder and decoder kv cache initialization into one model. It is legacy format that will be deprecated.",
+    )
+    parser.set_defaults(encoder_decoder_init=False)
+
+    args = parser.parse_args()
+
+    return args
+
+
+def export_onnx_models(
+    model_name_or_path: str,
+    cache_dir: str,
+    output_dir: str,
+    use_gpu: bool = False,
+    use_external_data_format: bool = False,
+    optimize_onnx: bool = False,
+    precision: str = Precision.FLOAT32.value,
+    verbose: bool = False,
+    use_decoder_start_token: bool = False,
+    overwrite: bool = False,
+    disable_auto_mixed_precision: bool = False,
+    use_int32_inputs: bool = True,
+    model_type: str = "t5",
+    state_dict_path: str = "",
+    encoder_decoder_init: bool = False,
+    force_fp16_io: bool = False,
+    shape_infer_before_optimization: bool = False,
+):
+    assert precision in [Precision.FLOAT32.value, Precision.FLOAT16.value], (
+        f"Invalid precision: {precision}. Use 'fp32' or 'fp16'."
+    )
+    device = torch.device("cuda:0" if use_gpu else "cpu")
+
+    models = T5Helper.load_model(
+        model_name_or_path,
+        cache_dir,
+        device,
+        model_type,
+        state_dict_path,
+        encoder_decoder_init=encoder_decoder_init,
+    )
+    config: T5Config | MT5Config = models["decoder"].config
+
+    if (not use_external_data_format) and (config.num_layers > 24):
+        logger.info("Try use_external_data_format when model size > 2GB")
+
+    output_paths = []
+    for name, model in models.items():
+        model.to(device)
+        filename_suffix = "_" + name
+
+        onnx_path = T5Helper.get_onnx_path(
+            output_dir,
+            model_name_or_path,
+            suffix=filename_suffix,
+            new_folder=False,
+        )
+
+        if overwrite or not os.path.exists(onnx_path):
+            logger.info(f"Exporting ONNX model to {onnx_path}")
+            # We have to clone model before exporting onnx, otherwise verify_onnx will report large difference.
+            cloned_model = copy.deepcopy(model).to(device)
+            T5Helper.export_onnx(
+                cloned_model,
+                device,
+                onnx_path,
+                verbose,
+                use_external_data_format,
+                use_decoder_input_ids=not use_decoder_start_token,
+                use_int32_inputs=use_int32_inputs,
+            )
+        else:
+            logger.info(f"Skip exporting: existed ONNX model {onnx_path}")
+
+        # Optimize ONNX graph.
+        # The precision shall be compared with string value. It is because the Precision enum loaded from local file
+        # (like by transformers test in CI pipeline) are not same as Precision enum from package.
+        if optimize_onnx or precision != Precision.FLOAT32.value:
+            onnx_shape_path = None
+            if shape_infer_before_optimization:
+                onnx_shape_path = T5Helper.get_onnx_path(
+                    output_dir,
+                    model_name_or_path,
+                    suffix=filename_suffix + "_shape",
+                    new_folder=False,
+                )
+                infer_shapes_path(onnx_path, onnx_shape_path)
+
+            output_path = T5Helper.get_onnx_path(
+                output_dir,
+                model_name_or_path,
+                suffix=filename_suffix + "_" + str(precision),
+                new_folder=False,
+            )
+
+            if overwrite or not os.path.exists(output_path):
+                logger.info(f"Optimizing model to {output_path}")
+                T5Helper.optimize_onnx(
+                    onnx_shape_path or onnx_path,
+                    output_path,
+                    precision == Precision.FLOAT16.value,
+                    config.num_heads,
+                    config.hidden_size,
+                    use_external_data_format,
+                    auto_mixed_precision=not disable_auto_mixed_precision,
+                    use_gpu=use_gpu,
+                    force_fp16_io=force_fp16_io,
+                )
+            else:
+                logger.info(f"Skip optimizing: existed ONNX model {output_path}")
+        else:
+            output_path = onnx_path
+
+        ort_session = create_onnxruntime_session(
+            output_path,
+            use_gpu=use_gpu,
+            verbose=verbose,
+        )
+        if ort_session is None:
+            break
+
+        with torch.no_grad():
+            max_diff = T5Helper.verify_onnx(model, ort_session, device, use_int32_inputs)
+        logger.info(f"PyTorch and OnnxRuntime results max difference = {max_diff}")
+
+        # The threshold cannot apply to fp16 model, which need a larger threshold.
+        if precision == Precision.FLOAT32.value and max_diff > 1e-4:
+            logger.warning("PyTorch and OnnxRuntime results are NOT close")
+
+        output_paths.append(output_path)
+
+    return output_paths
+
+
+def main():
+    args = parse_arguments()
+
+    setup_logger(args.verbose)
+
+    logger.info(f"Arguments:{args}")
+
+    cache_dir = args.cache_dir
+    output_dir = args.output if not args.output.endswith(".onnx") else os.path.dirname(args.output)
+    prepare_environment(cache_dir, output_dir, args.use_gpu)
+
+    if args.precision != Precision.FLOAT32.value:
+        assert args.optimize_onnx, "fp16/int8 requires --optimize_onnx"
+
+    if args.precision == Precision.FLOAT16.value:
+        assert args.use_gpu, "fp16 requires --use_gpu"
+
+    output_paths = export_onnx_models(
+        args.model_name_or_path,
+        cache_dir,
+        output_dir,
+        args.use_gpu,
+        args.use_external_data_format,
+        args.optimize_onnx,
+        args.precision,
+        args.verbose,
+        args.use_decoder_start_token,
+        args.overwrite,
+        args.disable_auto_mixed_precision,
+        not args.use_int64_inputs,
+        args.model_type,
+        encoder_decoder_init=args.encoder_decoder_init,
+        force_fp16_io=args.force_fp16_io,
+    )
+
+    logger.info(f"Done! Outputs: {output_paths}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_decoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..1300bee0dd91f3e1d4a9ecba37c994800b9c6b0d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_decoder.py
@@ -0,0 +1,437 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import tempfile
+from pathlib import Path
+
+import numpy
+import onnx
+import torch
+from io_binding_helper import TypeHelper
+from onnx_model import OnnxModel
+from past_helper import PastKeyValuesHelper
+from t5_encoder import T5EncoderInputs
+from torch_onnx_export_helper import torch_onnx_export
+from transformers import MT5Config, T5Config
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+class T5DecoderInit(torch.nn.Module):
+    """A T5 decoder with LM head to create initial past key values.
+    This model is only called once during starting decoding.
+    """
+
+    def __init__(
+        self,
+        decoder: torch.nn.Module,
+        lm_head: torch.nn.Module,
+        config: T5Config | MT5Config,
+        decoder_start_token_id: int | None = None,
+    ):
+        super().__init__()
+        self.decoder = decoder
+        self.lm_head = lm_head
+        self.config = config
+        self.decoder_start_token_id = (
+            decoder_start_token_id if decoder_start_token_id is not None else self.config.decoder_start_token_id
+        )
+        self.tie_word_embeddings = (
+            self.config.tie_word_embeddings if hasattr(self.config, "tie_word_embeddings") else True
+        )
+
+    def forward(
+        self,
+        decoder_input_ids: torch.Tensor,
+        encoder_attention_mask: torch.Tensor,
+        encoder_hidden_states: torch.FloatTensor,
+    ):
+        if decoder_input_ids is None:
+            batch_size = encoder_attention_mask.shape[0]
+            decoder_input_ids = (
+                torch.ones(
+                    (batch_size, 1),
+                    dtype=torch.long,
+                    device=encoder_attention_mask.device,
+                )
+                * self.decoder_start_token_id
+            )
+
+        decoder_outputs = self.decoder(
+            input_ids=decoder_input_ids,
+            encoder_hidden_states=encoder_hidden_states,
+            encoder_attention_mask=encoder_attention_mask,
+            use_cache=True,
+            return_dict=True,
+        )
+
+        sequence_output = decoder_outputs.last_hidden_state
+        present_key_values = decoder_outputs.past_key_values
+
+        if self.tie_word_embeddings:
+            sequence_output = sequence_output * (self.config.d_model**-0.5)
+
+        lm_logits = self.lm_head(sequence_output)
+        past_self, past_cross = PastKeyValuesHelper.group_by_self_or_cross(present_key_values)
+        return lm_logits, past_self, past_cross
+
+
+class T5Decoder(torch.nn.Module):
+    """A T5 decoder with LM head and past key values"""
+
+    def __init__(self, decoder, lm_head, config):
+        super().__init__()
+        self.decoder = decoder
+        self.lm_head = lm_head
+        self.config = config
+        self.tie_word_embeddings = (
+            self.config.tie_word_embeddings if hasattr(self.config, "tie_word_embeddings") else True
+        )
+
+    def forward(self, decoder_input_ids, encoder_attention_mask, *past):
+        num_decoder_layers = self.config.num_decoder_layers
+        past_key_values = PastKeyValuesHelper.group_by_layer(past, num_decoder_layers)
+
+        # This is a hack since only the third dimension of encoder_hidden_states is used here
+        dummy_encoder_hidden_states = encoder_attention_mask.unsqueeze(2)
+        decoder_outputs = self.decoder(
+            input_ids=decoder_input_ids,
+            past_key_values=past_key_values,
+            encoder_hidden_states=dummy_encoder_hidden_states,
+            encoder_attention_mask=encoder_attention_mask,
+            use_cache=True,
+            return_dict=True,
+        )
+
+        sequence_output = decoder_outputs.last_hidden_state
+        present_key_values = decoder_outputs.past_key_values
+
+        if self.tie_word_embeddings:
+            sequence_output = sequence_output * (self.config.d_model**-0.5)
+
+        lm_logits = self.lm_head(sequence_output)
+        present_self, _ = PastKeyValuesHelper.group_by_self_or_cross(present_key_values)
+
+        # Do not return present_cross since they are identical to corresponding past_cross input
+        return lm_logits, present_self
+
+
+class T5DecoderInputs:
+    def __init__(
+        self,
+        decoder_input_ids,
+        encoder_attention_mask,
+        past_key_values=None,
+    ):
+        self.decoder_input_ids: torch.LongTensor = decoder_input_ids
+        self.encoder_attention_mask: torch.LongTensor = encoder_attention_mask
+        self.past_key_values: list[torch.FloatTensor] | list[torch.HalfTensor] | None = past_key_values
+
+    @staticmethod
+    def create_dummy(
+        config: T5Config | MT5Config,
+        batch_size: int,
+        encode_sequence_length: int,
+        past_decode_sequence_length: int,
+        device: torch.device,
+        float16: bool = False,
+        use_int32_inputs: bool = False,
+    ):  # -> T5DecoderInputs:
+        """Create dummy inputs for T5Decoder.
+
+        Args:
+            decoder: decoder
+            batch_size (int): batch size
+            encode_sequence_length (int): sequence length of input_ids for encoder
+            past_decode_sequence_length (int): past sequence length of input_ids for decoder
+            device (torch.device): device of output tensors
+            float16 (bool): whether the model uses float32 or float16 in input
+            use_int32_inputs(bool): whether use int32 instead of int64 for some inputs
+
+        Returns:
+            T5DecoderInputs: dummy inputs for decoder
+        """
+        num_attention_heads: int = config.num_heads
+        num_layers: int = config.num_decoder_layers
+        vocab_size: int = config.vocab_size
+
+        # Do not use head_size = hidden_size / num_attention_heads here.
+        # For example, mt5-small, d_model=512 and num_heads=6
+        head_size: int = config.d_kv
+
+        sequence_length: int = 1  # fixed for decoding
+        decoder_input_ids = torch.randint(
+            low=0,
+            high=vocab_size - 1,
+            size=(batch_size, sequence_length),
+            dtype=(torch.int32 if use_int32_inputs else torch.int64),
+            device=device,
+        )
+
+        encoder_inputs = T5EncoderInputs.create_dummy(
+            batch_size,
+            encode_sequence_length,
+            vocab_size,
+            device,
+            use_int32_inputs=use_int32_inputs,
+        )
+
+        float_type = torch.float16 if float16 else torch.float32
+
+        if past_decode_sequence_length > 0:
+            self_attention_past_shape = [
+                batch_size,
+                num_attention_heads,
+                past_decode_sequence_length,
+                head_size,
+            ]
+            cross_attention_past_shape = [
+                batch_size,
+                num_attention_heads,
+                encode_sequence_length,
+                head_size,
+            ]
+
+            past = []
+            for _ in range(2 * num_layers):
+                past.append(torch.rand(self_attention_past_shape, dtype=float_type, device=device))
+
+            for _ in range(2 * num_layers):
+                past.append(torch.rand(cross_attention_past_shape, dtype=float_type, device=device))
+        else:
+            past = None
+
+        return T5DecoderInputs(decoder_input_ids, encoder_inputs.attention_mask, past)
+
+    def to_list(self) -> list:
+        input_list = [
+            self.decoder_input_ids,
+            self.encoder_attention_mask,
+        ]
+        if self.past_key_values:
+            input_list.extend(self.past_key_values)
+        return input_list
+
+    def to_fp32(self):
+        past = [p.to(dtype=torch.float32) for p in self.past_key_values] if self.past_key_values else None
+        return T5DecoderInputs(
+            self.decoder_input_ids.clone(),
+            self.encoder_attention_mask.clone(),
+            past,
+        )
+
+
+class T5DecoderHelper:
+    @staticmethod
+    def export_onnx(
+        decoder: T5Decoder | T5DecoderInit,
+        device: torch.device,
+        onnx_model_path: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_int32_inputs: bool = False,
+    ):
+        """Export decoder to ONNX
+
+        Args:
+            decoder (Union[T5Decoder, T5DecoderNoPastState]): decoder object
+            device (torch.device): device of decoder object
+            onnx_model_path (str): onnx path
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_int32_inputs (bool, optional): use int32 inputs
+        """
+        assert isinstance(decoder, (T5Decoder, T5DecoderInit))
+
+        inputs = T5DecoderInputs.create_dummy(
+            decoder.config,
+            batch_size=2,
+            encode_sequence_length=3,
+            past_decode_sequence_length=5 if isinstance(decoder, T5Decoder) else 0,
+            device=device,
+            use_int32_inputs=use_int32_inputs,
+        )
+        input_list = inputs.to_list()
+
+        num_decoder_layers = decoder.config.num_decoder_layers
+
+        past_names = PastKeyValuesHelper.get_past_names(num_decoder_layers, present=False)
+        present_names = PastKeyValuesHelper.get_past_names(num_decoder_layers, present=True)
+        present_self_names = present_names[: 2 * num_decoder_layers]
+
+        input_past_names = past_names if isinstance(decoder, T5Decoder) else []
+        output_present_names = present_self_names if isinstance(decoder, T5Decoder) else present_names
+        output_names = ["logits", *output_present_names]
+
+        # Shape of input tensors (sequence_length==1):
+        #    input_ids: (batch_size, sequence_length)
+        #    encoder_attention_mask: (batch_size, encode_sequence_length)
+        #    past_self_*: (batch_size, num_heads, past_decode_sequence_length, head_size)
+        #    past_cross_*: (batch_size, num_heads, encode_sequence_length, head_size)
+
+        # Shape of output tensors:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    past_self_*: (batch_size, num_heads, past_decode_sequence_length + sequence_length, head_size)
+        #    past_cross_*: (batch_size, num_heads, encode_sequence_length, head_size)
+
+        input_names = ["input_ids"]
+        input_names.append("encoder_attention_mask")
+        input_names.extend(input_past_names)
+
+        dynamic_axes = {
+            "input_ids": {
+                0: "batch_size",
+                # 1: 'sequence_length'
+            },
+            "encoder_attention_mask": {0: "batch_size", 1: "encode_sequence_length"},
+            "encoder_hidden_states": {0: "batch_size", 1: "encode_sequence_length"},
+            "logits": {
+                0: "batch_size",
+                # 1: 'sequence_length'
+            },
+        }
+
+        for name in input_past_names:
+            dynamic_axes[name] = {
+                0: "batch_size",
+                2: "past_decode_sequence_length" if "self" in name else "encode_sequence_length",
+            }
+
+        for name in output_present_names:
+            if "cross" in name:
+                dynamic_axes[name] = {0: "batch_size", 2: "encode_sequence_length"}
+            else:  # self attention past state
+                if isinstance(decoder, T5Decoder):
+                    dynamic_axes[name] = {
+                        0: "batch_size",
+                        2: "past_decode_sequence_length + 1",
+                    }
+                else:
+                    dynamic_axes[name] = {
+                        0: "batch_size",
+                        # 2: 'sequence_length'
+                    }
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "decoder.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            torch_onnx_export(
+                decoder,
+                args=tuple(input_list),
+                f=temp_onnx_model_path if use_external_data_format else onnx_model_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=12,
+                do_constant_folding=True,
+                use_external_data_format=use_external_data_format,
+                verbose=verbose,
+            )
+
+            if use_external_data_format:
+                model = onnx.load_model(temp_onnx_model_path, load_external_data=True)
+                OnnxModel.save(
+                    model,
+                    onnx_model_path,
+                    save_as_external_data=True,
+                    all_tensors_to_one_file=True,
+                )
+
+    @staticmethod
+    def onnxruntime_inference(ort_session, inputs: T5DecoderInputs):
+        """Run inference of ONNX model."""
+        logger.debug("start onnxruntime_inference")
+
+        ort_inputs = {
+            "input_ids": numpy.ascontiguousarray(inputs.decoder_input_ids.cpu().numpy()),
+            "encoder_attention_mask": numpy.ascontiguousarray(inputs.encoder_attention_mask.cpu().numpy()),
+        }
+
+        if inputs.past_key_values:
+            assert len(inputs.past_key_values) % 4 == 0
+            num_layers = int(len(inputs.past_key_values) / 4)
+            past_names = PastKeyValuesHelper.get_past_names(num_layers)
+            for i, past_tensor in enumerate(inputs.past_key_values):
+                ort_inputs[past_names[i]] = numpy.ascontiguousarray(past_tensor.cpu().numpy())
+
+        ort_outputs = ort_session.run(None, ort_inputs)
+        return ort_outputs
+
+    @staticmethod
+    def verify_onnx(
+        model: T5Decoder | T5DecoderInit,
+        ort_session: InferenceSession,
+        device: torch.device,
+        use_int32_inputs: bool,
+        max_cases: int = 4,
+    ):
+        """Compare the result from PyTorch and OnnxRuntime to verify the ONNX model is good."""
+        float16: bool = TypeHelper.get_input_type(ort_session, "past_key_self_0") == "tensor(float16)"
+
+        test_cases = [(4, 11, 3), (1, 2, 5), (3, 1, 1), (8, 5, 2)]
+        test_cases_max_diff = []
+        for (
+            batch_size,
+            encode_sequence_length,
+            past_decode_sequence_length,
+        ) in test_cases[:max_cases]:
+            if isinstance(model, T5DecoderInit):
+                past_decode_sequence_length = 0  # noqa: PLW2901
+
+            inputs = T5DecoderInputs.create_dummy(
+                model.config,
+                batch_size,
+                encode_sequence_length,
+                past_decode_sequence_length,
+                device=device,
+                float16=float16,
+                use_int32_inputs=use_int32_inputs,
+            )
+
+            # We use fp32 PyTroch model as baseline even when ONNX model is fp16
+            input_list = inputs.to_fp32().to_list()
+
+            # Run inference of PyTorch model
+            with torch.no_grad():
+                torch_outputs = model(*input_list)
+
+            ort_outputs = T5DecoderHelper.onnxruntime_inference(ort_session, inputs)
+            num_decoder_layers = model.config.num_decoder_layers
+
+            max_diff = numpy.amax(numpy.abs(torch_outputs[0].cpu().numpy() - ort_outputs[0]))
+            max_diff_all = max_diff
+            logger.debug(f"logits max_diff={max_diff}")
+
+            for i in range(2 * num_decoder_layers):
+                max_diff = numpy.amax(numpy.abs(torch_outputs[1][i].cpu().numpy() - ort_outputs[1 + i]))
+                logger.debug(f"self attention past state {i} max_diff={max_diff}")
+                max_diff_all = max(max_diff_all, max_diff)
+
+            if isinstance(model, T5DecoderInit):
+                for i in range(2 * num_decoder_layers):
+                    max_diff = numpy.amax(
+                        numpy.abs(torch_outputs[2][i].cpu().numpy() - ort_outputs[1 + 2 * num_decoder_layers + i])
+                    )
+                    logger.debug(f"cross attention past state {i} max_diff={max_diff}")
+                    max_diff_all = max(max_diff_all, max_diff)
+
+            test_cases_max_diff.append(max_diff_all)
+            logger.info(
+                "batch_size=%s, encode_sequence_length=%s, past_decode_sequence_length=%s, max_diff=%s",
+                batch_size,
+                encode_sequence_length,
+                past_decode_sequence_length,
+                max_diff_all,
+            )
+
+        return max_diff_all
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee287941ddf1a95a42093eb94b9eda7436f00e2e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder.py
@@ -0,0 +1,70 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# -------------------------------------------------------------------------
+
+import logging
+import random
+
+import torch
+from transformers import MT5Config, T5Config
+
+logger = logging.getLogger(__name__)
+
+
+class T5Encoder(torch.nn.Module):
+    """T5 encoder outputs only the last hidden state"""
+
+    def __init__(self, encoder, config: T5Config | MT5Config):
+        super().__init__()
+        self.encoder = encoder
+        self.config = config
+
+    def forward(self, input_ids, attention_mask):
+        return self.encoder(input_ids, attention_mask)[0]
+
+
+class T5EncoderInputs:
+    def __init__(self, input_ids, attention_mask):
+        self.input_ids: torch.LongTensor = input_ids
+        self.attention_mask: torch.LongTensor = attention_mask
+
+    @staticmethod
+    def create_dummy(
+        batch_size: int,
+        sequence_length: int,
+        vocab_size: int,
+        device: torch.device,
+        use_int32_inputs: bool = False,
+    ):  # -> T5EncoderInputs
+        """Create dummy inputs for T5 encoder.
+
+        Args:
+            batch_size (int): batch size
+            sequence_length (int): sequence length
+            vocab_size (int): vocabulary size
+            device (torch.device): device of output tensors
+
+        Returns:
+            T5EncoderInputs: dummy inputs for encoder
+        """
+        dtype = torch.int32 if use_int32_inputs else torch.int64
+
+        input_ids = torch.randint(
+            low=0,
+            high=vocab_size - 1,
+            size=(batch_size, sequence_length),
+            dtype=dtype,
+            device=device,
+        )
+
+        attention_mask = torch.ones([batch_size, sequence_length], dtype=dtype, device=device)
+        if sequence_length >= 2:
+            for i in range(batch_size):
+                padding_position = random.randint(0, sequence_length - 1)
+                attention_mask[i, :padding_position] = 0
+        return T5EncoderInputs(input_ids, attention_mask)
+
+    def to_list(self) -> list:
+        input_list = [v for v in [self.input_ids, self.attention_mask] if v is not None]
+        return input_list
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder_decoder_init.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder_decoder_init.py
new file mode 100644
index 0000000000000000000000000000000000000000..ba725862b6cb353e2dfc3d2683bfa95ca2fd530b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_encoder_decoder_init.py
@@ -0,0 +1,361 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# -------------------------------------------------------------------------
+
+import logging
+import os
+import tempfile
+from pathlib import Path
+
+import numpy
+import onnx
+import torch
+from onnx_model import OnnxModel
+from past_helper import PastKeyValuesHelper
+from t5_decoder import T5DecoderInit
+from t5_encoder import T5Encoder, T5EncoderInputs
+from torch_onnx_export_helper import torch_onnx_export
+from transformers import MT5Config, T5Config
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+class T5EncoderDecoderInit(torch.nn.Module):
+    """A combination of T5Encoder and T5DecoderInit."""
+
+    def __init__(
+        self,
+        encoder: torch.nn.Module,
+        decoder: torch.nn.Module,
+        lm_head: torch.nn.Linear,
+        config: T5Config | MT5Config,
+        decoder_start_token_id: int | None = None,
+        output_cross_only: bool = False,
+    ):
+        super().__init__()
+        self.config: T5Config | MT5Config = config
+        self.t5_encoder = T5Encoder(encoder, config)
+        self.t5_decoder_init = T5DecoderInit(decoder, lm_head, config, decoder_start_token_id)
+        self.output_cross_only = output_cross_only
+
+    def forward(
+        self,
+        encoder_input_ids: torch.Tensor,
+        encoder_attention_mask: torch.Tensor,
+        decoder_input_ids: torch.Tensor | None = None,
+    ):
+        encoder_hidden_states: torch.FloatTensor = self.t5_encoder(encoder_input_ids, encoder_attention_mask)
+
+        lm_logits, past_self, past_cross = self.t5_decoder_init(
+            decoder_input_ids, encoder_attention_mask, encoder_hidden_states
+        )
+
+        if self.output_cross_only:
+            return past_cross
+        else:
+            return lm_logits, encoder_hidden_states, past_self, past_cross
+
+
+class T5EncoderDecoderInitInputs:
+    def __init__(self, encoder_input_ids, encoder_attention_mask, decoder_input_ids=None):
+        self.encoder_input_ids: torch.LongTensor = encoder_input_ids
+        self.encoder_attention_mask: torch.LongTensor = encoder_attention_mask
+        self.decoder_input_ids: torch.LongTensor | None = decoder_input_ids
+
+    @staticmethod
+    def create_dummy(
+        config: T5Config | MT5Config,
+        batch_size: int,
+        encode_sequence_length: int,
+        use_decoder_input_ids: int,
+        device: torch.device,
+        use_int32_inputs: bool = False,
+    ):  # -> T5EncoderDecoderInitInputs:
+        encoder_inputs: T5EncoderInputs = T5EncoderInputs.create_dummy(
+            batch_size,
+            encode_sequence_length,
+            config.vocab_size,
+            device,
+            use_int32_inputs=use_int32_inputs,
+        )
+        decoder_input_ids = None
+        if use_decoder_input_ids:
+            dtype = torch.int32 if use_int32_inputs else torch.int64
+            decoder_input_ids = torch.ones((batch_size, 1), dtype=dtype, device=device) * config.decoder_start_token_id
+
+        return T5EncoderDecoderInitInputs(encoder_inputs.input_ids, encoder_inputs.attention_mask, decoder_input_ids)
+
+    def to_list(self) -> list:
+        input_list = [self.encoder_input_ids, self.encoder_attention_mask]
+        if self.decoder_input_ids is not None:
+            input_list.append(self.decoder_input_ids)
+        return input_list
+
+
+class T5EncoderDecoderInitHelper:
+    @staticmethod
+    def export_onnx(
+        model: T5EncoderDecoderInit,
+        device: torch.device,
+        onnx_model_path: str,
+        use_decoder_input_ids: bool = True,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_int32_inputs: bool = False,
+    ):
+        """Export decoder to ONNX
+
+        Args:
+            model (T5EncoderDecoderInit): the model to export
+            device (torch.device): device of decoder object
+            onnx_model_path (str): onnx path
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_int32_inputs (bool, optional): use int32 instead of int64 for integer inputs. Defaults to False.
+        """
+        assert isinstance(model, T5EncoderDecoderInit)
+
+        # Do not exclude decoder in torch onnx export so that cross can show up.
+        output_cross_only = model.output_cross_only
+        model.output_cross_only = False
+
+        inputs = T5EncoderDecoderInitInputs.create_dummy(
+            model.config,
+            batch_size=2,
+            encode_sequence_length=3,
+            use_decoder_input_ids=use_decoder_input_ids,
+            device=device,
+            use_int32_inputs=use_int32_inputs,
+        )
+        input_list = inputs.to_list()
+
+        present_names = PastKeyValuesHelper.get_past_names(model.config.num_decoder_layers, present=True)
+
+        output_names = ["logits", "encoder_hidden_states", *present_names]
+
+        # Shape of input tensors (sequence_length==1):
+        #    input_ids: (batch_size, sequence_length)
+        #    encoder_attention_mask: (batch_size, encode_sequence_length)
+        #    encoder_hidden_states: (batch_size, encode_sequence_length, hidden_size)
+        #    past_self_*: (batch_size, num_heads, past_decode_sequence_length, head_size)
+        #    past_cross_*: (batch_size, num_heads, encode_sequence_length, head_size)
+
+        # Shape of output tensors:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    past_self_*: (batch_size, num_heads, past_decode_sequence_length + sequence_length, head_size)
+        #    past_cross_*: (batch_size, num_heads, encode_sequence_length, head_size)
+
+        input_names = ["encoder_input_ids", "encoder_attention_mask"]
+
+        # ONNX exporter might mark dimension like 'present_value_self_1_dim_2' in shape inference.
+        # We use a workaround here: first use dim_param "1" for sequence_length, and later change to dim_value.
+        sequence_length = "1"
+        num_heads = str(model.config.num_heads)
+        hidden_size = str(model.config.d_model)
+        head_size = str(model.config.d_kv)
+
+        dynamic_axes = {
+            "encoder_input_ids": {0: "batch_size", 1: "encode_sequence_length"},
+            "encoder_attention_mask": {0: "batch_size", 1: "encode_sequence_length"},
+            "encoder_hidden_states": {
+                0: "batch_size",
+                1: "encode_sequence_length",
+                2: hidden_size,
+            },
+            "logits": {
+                0: "batch_size",
+                1: sequence_length,
+            },
+        }
+
+        if use_decoder_input_ids:
+            input_names.append("decoder_input_ids")
+            dynamic_axes["decoder_input_ids"] = {
+                0: "batch_size",
+                1: sequence_length,
+            }
+
+        for name in present_names:
+            if "cross" in name:
+                dynamic_axes[name] = {
+                    0: "batch_size",
+                    1: num_heads,
+                    2: "encode_sequence_length",
+                    3: head_size,
+                }
+
+            else:  # self attention past state
+                dynamic_axes[name] = {
+                    0: "batch_size",
+                    1: num_heads,
+                    2: sequence_length,
+                    3: head_size,
+                }
+
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "encoder_decoder_init.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            torch_onnx_export(
+                model,
+                args=tuple(input_list),
+                f=temp_onnx_model_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=12,
+                do_constant_folding=True,
+                use_external_data_format=use_external_data_format,
+                verbose=verbose,
+            )
+
+            # Restore output_cross_only setting.
+            model.output_cross_only = output_cross_only
+
+            # Workaround as mentioned earlier: change numeric dim_param to dim_value
+            exported_model: onnx.ModelProto = onnx.load(temp_onnx_model_path)
+            for tensor in exported_model.graph.output:
+                for dim_proto in tensor.type.tensor_type.shape.dim:
+                    if dim_proto.HasField("dim_param") and dim_proto.dim_param in [
+                        sequence_length,
+                        num_heads,
+                        hidden_size,
+                        head_size,
+                    ]:
+                        dim_value = int(dim_proto.dim_param)
+                        dim_proto.Clear()
+                        dim_proto.dim_value = dim_value
+
+            if output_cross_only:
+                # Rewrite onnx graph to only keep present_[key|value]_cross_* outputs.
+                onnx_model = OnnxModel(exported_model)
+                output_name_to_node = onnx_model.output_name_to_node()
+
+                for output in exported_model.graph.output:
+                    if "cross" in output.name:
+                        assert output.name in output_name_to_node
+
+                        transpose_node = output_name_to_node[output.name]
+                        assert transpose_node and transpose_node.op_type == "Transpose"
+
+                        permutation = OnnxModel.get_node_attribute(transpose_node, "perm")
+                        assert isinstance(permutation, list)
+                        assert permutation == [0, 2, 1, 3]
+
+                        matched_nodes = onnx_model.match_parent_path(
+                            transpose_node,
+                            ["Reshape", "MatMul"],
+                            [0, 0],
+                            output_name_to_node,
+                        )
+                        assert matched_nodes is not None
+
+                        reshape_node, matmul_node = matched_nodes
+                        assert "encoder_hidden_states" in matmul_node.input
+
+                        if not onnx_model.get_initializer("cross_reshape_shape"):
+                            shape_tensor = onnx.helper.make_tensor(
+                                name="cross_reshape_shape",
+                                data_type=onnx.TensorProto.INT64,
+                                dims=[4],
+                                vals=[0, 0, int(num_heads), int(head_size)],
+                                raw=False,
+                            )
+                            onnx_model.add_initializer(shape_tensor)
+
+                        reshape_node.input[1] = "cross_reshape_shape"
+
+                cross_outputs = [output.name for output in exported_model.graph.output if "cross" in output.name]
+                onnx_model.prune_graph(cross_outputs, allow_remove_graph_inputs=True)
+
+            OnnxModel.save(
+                exported_model,
+                onnx_model_path,
+                save_as_external_data=use_external_data_format,
+                all_tensors_to_one_file=True,
+            )
+
+    @staticmethod
+    def onnxruntime_inference(ort_session, inputs: T5EncoderDecoderInitInputs):
+        """Run inference of ONNX model."""
+        logger.debug("start onnxruntime_inference")
+
+        ort_inputs = {
+            "encoder_input_ids": numpy.ascontiguousarray(inputs.encoder_input_ids.cpu().numpy()),
+            "encoder_attention_mask": numpy.ascontiguousarray(inputs.encoder_attention_mask.cpu().numpy()),
+        }
+        if inputs.decoder_input_ids is not None:
+            ort_inputs["decoder_input_ids"] = numpy.ascontiguousarray(inputs.decoder_input_ids.cpu().numpy())
+
+        ort_outputs = ort_session.run(None, ort_inputs)
+        return ort_outputs
+
+    @staticmethod
+    def verify_onnx(
+        model: T5EncoderDecoderInit,
+        ort_session: InferenceSession,
+        device: torch.device,
+        use_int32_inputs: bool,
+        max_cases: int = 4,
+    ):
+        """Compare the result from PyTorch and OnnxRuntime to verify the ONNX model is good."""
+        ort_inputs = ort_session.get_inputs()
+        use_decoder_input_ids = len(ort_inputs) == 3
+
+        test_cases = [(4, 11), (1, 2), (3, 1), (8, 5)]
+        test_cases_max_diff = []
+        for batch_size, encode_sequence_length in test_cases[:max_cases]:
+            inputs = T5EncoderDecoderInitInputs.create_dummy(
+                model.config,
+                batch_size,
+                encode_sequence_length,
+                use_decoder_input_ids=use_decoder_input_ids,
+                device=device,
+                use_int32_inputs=use_int32_inputs,
+            )
+
+            ort_outputs = T5EncoderDecoderInitHelper.onnxruntime_inference(ort_session, inputs)
+
+            # Run inference of PyTorch model
+            input_list = inputs.to_list()
+            torch_outputs = model(*input_list)
+
+            num_decoder_layers = model.config.num_decoder_layers
+
+            if not model.output_cross_only:
+                assert torch_outputs[0].cpu().numpy().shape == ort_outputs[0].shape
+                max_diff = numpy.amax(numpy.abs(torch_outputs[0].cpu().numpy() - ort_outputs[0]))
+                logger.debug(f"logits max_diff={max_diff}")
+                max_diff_all = max_diff
+
+                assert torch_outputs[1].cpu().numpy().shape == ort_outputs[1].shape
+                max_diff = numpy.amax(numpy.abs(torch_outputs[1].cpu().numpy() - ort_outputs[1]))
+                logger.debug(f"encoder_hidden_states max_diff={max_diff}")
+                max_diff_all = max(max_diff_all, max_diff)
+
+                for i in range(2 * num_decoder_layers):
+                    max_diff = numpy.amax(numpy.abs(torch_outputs[2][i].cpu().numpy() - ort_outputs[2 + i]))
+                    logger.debug(f"self attention past state {i} max_diff={max_diff}")
+
+                for i in range(2 * num_decoder_layers):
+                    max_diff = numpy.amax(
+                        numpy.abs(torch_outputs[3][i].cpu().numpy() - ort_outputs[2 + 2 * num_decoder_layers + i])
+                    )
+                    logger.debug(f"cross attention past state {i} max_diff={max_diff}")
+                    max_diff_all = max(max_diff_all, max_diff)
+            else:
+                max_diff_all = -float("inf")
+                for i in range(2 * num_decoder_layers):
+                    max_diff = numpy.amax(numpy.abs(torch_outputs[i].cpu().numpy() - ort_outputs[i]))
+                    logger.debug(f"cross attention past state {i} max_diff={max_diff}")
+                    max_diff_all = max(max_diff_all, max_diff)
+
+            test_cases_max_diff.append(max_diff_all)
+            logger.info(
+                f"batch_size={batch_size} encode_sequence_length={encode_sequence_length}, max_diff={max_diff_all}"
+            )
+
+        return max(test_cases_max_diff)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..0617ec19c2480d4877e3d5cfcc6e6acc33164a22
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/t5/t5_helper.py
@@ -0,0 +1,315 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# -------------------------------------------------------------------------
+
+import logging
+import os
+from pathlib import Path
+
+import torch
+from float16 import float_to_float16_max_diff
+from onnx_model import OnnxModel
+from optimizer import optimize_model
+from t5_decoder import T5Decoder, T5DecoderHelper
+from t5_encoder_decoder_init import T5EncoderDecoderInit, T5EncoderDecoderInitHelper
+from transformers import MT5ForConditionalGeneration, T5ForConditionalGeneration
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+def _torch_load_weights_only(path: str, **kwargs):
+    try:
+        return torch.load(path, weights_only=True, **kwargs)
+    except TypeError:
+        logger.warning(
+            "Current PyTorch version does not support torch.load(..., weights_only=True); "
+            "falling back to default torch.load behavior for %s.",
+            path,
+        )
+        return torch.load(path, **kwargs)
+
+
+PRETRAINED_T5_MODELS = ["t5-small", "t5-base", "t5-large", "t5-3b", "t5-11b"]
+PRETRAINED_MT5_MODELS = [
+    "google/mt5-small",
+    "google/mt5-base",
+    "google/mt5-large",
+    "google/mt5-xl",
+    "google/mt5-xxl",
+]
+
+
+class T5Helper:
+    @staticmethod
+    def get_onnx_path(
+        output_dir: str,
+        model_name_or_path: str,
+        suffix: str = "",
+        new_folder: bool = False,
+    ) -> str:
+        """Build onnx path
+
+        Args:
+            output_dir (str): output directory
+            model_name_or_path (str): pretrained model name, or path to the model checkpoint
+            suffix (str, optional): suffix like "_encoder" or "_decoder_fp16" will be appended to file name. Defaults to None.
+            new_folder (bool, optional): create a new directory for the model. Defaults to False.
+
+        Returns:
+            str: path of onnx model
+        """
+        model_name = model_name_or_path
+        if os.path.isdir(model_name_or_path):
+            model_name = Path(model_name_or_path).parts[-1]
+        else:
+            model_name.split("/")[-1]
+
+        model_name += suffix
+
+        directory = os.path.join(output_dir, model_name) if new_folder else output_dir
+        return os.path.join(directory, model_name + ".onnx")
+
+    @staticmethod
+    def load_model(
+        model_name_or_path: str,
+        cache_dir: str,
+        device: torch.device,
+        model_type: str = "t5",
+        state_dict_path: str = "",
+        encoder_decoder_init: bool = False,
+    ) -> dict[str, T5EncoderDecoderInit | T5Decoder]:
+        """Load model given a pretrained name or path, then build models for ONNX conversion.
+
+        Args:
+            model_name_or_path (str): pretrained model name or path
+            cache_dir (str): cache directory
+            device (torch.device): device to run the model
+            model_type (str, optional): model type "t5" or "mt5"
+            state_dict_path(str, optional): state dictionary path
+            encoder_decoder_init (bool, optional): combine encoder and decoder kv cache initialization into one model.
+        Returns:
+            Dict[str, torch.nn.Module]: mapping from name to modules for ONNX conversion.
+        """
+        if model_type == "t5":
+            model = T5ForConditionalGeneration.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        elif model_type == "mt5":
+            model = MT5ForConditionalGeneration.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        else:
+            raise ValueError("only support mode_type=t5 or mt5")
+
+        if state_dict_path:
+            model.load_state_dict(_torch_load_weights_only(state_dict_path))
+
+        decoder = T5Decoder(model.decoder, model.lm_head, model.config)
+        decoder.eval().to(device)
+
+        encoder = T5EncoderDecoderInit(
+            model.encoder,
+            model.decoder,
+            model.lm_head,
+            model.config,
+            decoder_start_token_id=None,
+            output_cross_only=not encoder_decoder_init,
+        )
+
+        encoder_name = "encoder_decoder_init" if encoder_decoder_init else "encoder"
+        return {encoder_name: encoder, "decoder": decoder}
+
+    @staticmethod
+    def export_onnx(
+        model: T5Decoder | T5EncoderDecoderInit,
+        device: torch.device,
+        onnx_model_path: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_decoder_input_ids: bool = True,
+        use_int32_inputs: bool = False,
+    ):
+        if isinstance(model, T5EncoderDecoderInit):
+            T5EncoderDecoderInitHelper.export_onnx(
+                model,
+                device,
+                onnx_model_path,
+                use_decoder_input_ids,
+                verbose,
+                use_external_data_format,
+                use_int32_inputs,
+            )
+        else:
+            T5DecoderHelper.export_onnx(
+                model,
+                device,
+                onnx_model_path,
+                verbose,
+                use_external_data_format,
+                use_int32_inputs,
+            )
+
+    @staticmethod
+    def auto_mixed_precision(
+        onnx_model: OnnxModel,
+        op_block_list: list[str] | None = None,
+        force_fp16_logits: bool = False,
+        use_symbolic_shape_infer: bool = True,
+    ):
+        """Convert model to mixed precision.
+           It detects whether original model has fp16 precision weights, and set parameters for float16 conversion automatically.
+        Args:
+            onnx_model (OnnxModel): optimized ONNX model
+            op_block_list (List[str], optional): operators need to run in fp32.
+            force_fp16_logits (bool, optional): force logits and last MatMul node to be in float16. Defaults to False.
+            use_symbolic_shape_infer (bool, optional): use symbolic shape inference to convert float to float16. Defaults to True.
+        Returns:
+            parameters(dict): a dictionary of parameters used in float16 conversion
+        """
+        if op_block_list is None:
+            op_block_list = [
+                "SimplifiedLayerNormalization",
+                "SkipSimplifiedLayerNormalization",
+                "Relu",
+                "Add",
+            ]
+
+        op_full_set = {node.op_type for node in onnx_model.nodes()}
+        fp32_op_set = set(op_block_list)
+        fp16_op_set = op_full_set.difference(fp32_op_set)
+        logger.info(f"fp32 op: {fp32_op_set} fp16 op: {fp16_op_set}")
+
+        # logits is the first output
+        logits_output_name = onnx_model.graph().output[0].name
+
+        # We use the weight in last MatMul node to detect whether the model is stored with float16 weights from training.
+        is_weight_fp16_precision = False
+        output_name_to_node = onnx_model.output_name_to_node()
+        assert logits_output_name in output_name_to_node
+        node = output_name_to_node[logits_output_name]
+        last_matmul_node = None
+        if node.op_type == "MatMul":
+            last_matmul_node = node
+            logger.info(f"Found last MatMul node for logits: {node.name}")
+            initializer = None
+            for input in node.input:
+                initializer = onnx_model.get_initializer(input)
+                if initializer is not None:
+                    break
+
+            # when the max difference of value after converting float to float16 is lower than a threshold (1e-6),
+            # we can deduce that the weights are stored in float16 precision.
+            max_diff = float_to_float16_max_diff(initializer)
+            logger.debug(f"max diff of converting weights in last MatMul node {node.name}: {max_diff}")
+            is_weight_fp16_precision = max_diff < 1e-6
+        else:
+            logger.warning(f"Failed to find MatMul node for logits. Found {node.op_type} of node {node.name}")
+
+        keep_io_types = []
+        node_block_list = []
+        if (not is_weight_fp16_precision) and (last_matmul_node is not None) and not force_fp16_logits:
+            # When original weight is float32 precision, keep logits and last MatMul in float32 could get better precision.
+            keep_io_types = [logits_output_name]
+            node_block_list = [last_matmul_node.name]
+
+        if "Add" not in op_block_list:
+            input_name_to_nodes = onnx_model.input_name_to_nodes()
+            fp32_add = 0
+            changed = True
+            add_nodes = onnx_model.get_nodes_by_op_type("Add")
+            while changed:
+                changed = False
+                for node in add_nodes:
+                    if node.name not in node_block_list:
+                        parents = onnx_model.get_parents(node, output_name_to_node)
+                        children = onnx_model.get_children(node, input_name_to_nodes)
+                        blocked_children = [
+                            child for child in children if child.op_type in op_block_list or child in node_block_list
+                        ]
+                        blocked_parents = [
+                            parent for parent in parents if parent.op_type in op_block_list or parent in node_block_list
+                        ]
+                        # If any child or parent is in fp32, we place the Add node to fp32.
+                        if (len(blocked_children) + len(blocked_parents)) > 0:
+                            node_block_list.append(node.name)
+                            fp32_add += 1
+                            changed = True
+            fp16_add = len(add_nodes) - fp32_add
+            logger.info(f"node counter of Add operator: fp32={fp32_add} fp16={fp16_add}")
+
+        logger.info(f"node_block_list: {node_block_list}")
+
+        parameters = {
+            "keep_io_types": keep_io_types,
+            "op_block_list": op_block_list,
+            "node_block_list": node_block_list,
+            "force_fp16_initializers": is_weight_fp16_precision,
+        }
+
+        logger.info(f"auto_mixed_precision parameters: {parameters}")
+        if use_symbolic_shape_infer:
+            onnx_model.convert_float_to_float16(use_symbolic_shape_infer=True, **parameters)
+        else:
+            # Workaround when symbolic shape inference fails.
+            # Need enable shape_infer_before_optimization in convert_to_onnx.py as well.
+            from float16 import convert_float_to_float16  # noqa: PLC0415
+
+            convert_float_to_float16(
+                onnx_model.model,
+                disable_shape_infer=True,
+                **parameters,
+            )
+
+        return parameters
+
+    @staticmethod
+    def optimize_onnx(
+        onnx_model_path: str,
+        optimized_model_path: str,
+        is_float16: bool,
+        num_attention_heads: int,
+        hidden_size: int,
+        use_external_data_format: bool = False,
+        auto_mixed_precision: bool = True,
+        use_gpu: bool = False,
+        force_fp16_io: bool = False,
+    ):
+        """Optimize ONNX model with an option to convert it to use mixed precision."""
+
+        from fusion_options import FusionOptions  # noqa: PLC0415
+
+        optimization_options = None
+        if is_float16:
+            optimization_options = FusionOptions("t5")
+            # SkipLayerNormalization is faster but might bring accuracy drop since it uses fp16 accumulation.
+            optimization_options.enable_skip_layer_norm = not auto_mixed_precision
+
+        m = optimize_model(
+            onnx_model_path,
+            model_type="t5",
+            num_heads=num_attention_heads,
+            hidden_size=hidden_size,
+            opt_level=0,
+            optimization_options=optimization_options,
+            use_gpu=use_gpu,
+        )
+
+        if is_float16:
+            if auto_mixed_precision:
+                T5Helper.auto_mixed_precision(m, force_fp16_logits=force_fp16_io)
+            else:
+                m.convert_model_float32_to_float16(cast_input_output=force_fp16_io)
+
+        m.save_model_to_file(optimized_model_path, use_external_data_format, all_tensors_to_one_file=True)
+
+    @staticmethod
+    def verify_onnx(
+        model: T5Decoder | T5EncoderDecoderInit,
+        ort_session: InferenceSession,
+        device: torch.device,
+        use_int32_inputs: bool,
+    ):
+        """Compare the result from PyTorch and OnnxRuntime to verify the ONNX model is good."""
+        if isinstance(model, T5EncoderDecoderInit):
+            return T5EncoderDecoderInitHelper.verify_onnx(model, ort_session, device, use_int32_inputs)
+
+        return T5DecoderHelper.verify_onnx(model, ort_session, device, use_int32_inputs)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/__init__.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f9a57c902589567201d260a9248c59309a74576
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/__init__.py
@@ -0,0 +1,12 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import os
+import sys
+
+sys.path.append(os.path.dirname(__file__))
+
+transformers_dir = os.path.normpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+if transformers_dir not in sys.path:
+    sys.path.append(transformers_dir)
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diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6b5b3f3bcc90165d3eb1a8ce268504e0731bbec
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark.py
@@ -0,0 +1,585 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import ast
+import datetime
+import gc
+import logging
+import os
+import sys
+import time
+
+import numpy as np
+import psutil
+import torch
+import whisper
+from benchmark_helper import measure_memory, setup_logger
+from onnxruntime_extensions import get_library_path
+from optimum.onnxruntime import ORTModelForSpeechSeq2Seq
+from torch.profiler import ProfilerActivity, profile, record_function
+from tqdm import trange
+from transformers import AutoModelForSpeechSeq2Seq, WhisperConfig, WhisperProcessor
+
+import onnxruntime as ort
+
+logger = logging.getLogger(__name__)
+
+
+def get_inputs(args: argparse.Namespace):
+    if args.benchmark_type not in {"hf-pt-eager", "hf-pt-compile", "hf-ort", "ort"}:
+        raise Exception("Unable to auto-detect inputs for provided model")
+
+    def load_via_ffmpeg():
+        audio = whisper.load_audio(args.audio_path)
+        audio = whisper.pad_or_trim(audio)
+        return audio
+
+    def load_via_numpy():
+        with open(args.audio_path, "rb") as f:
+            audio = np.asarray(list(f.read()), dtype=np.uint8)
+            audio = np.array([audio])
+        return audio
+
+    inputs = {
+        "max_length": args.max_length,
+        "min_length": args.min_length,
+        "num_beams": args.num_beams,
+        "num_return_sequences": args.num_return_sequences,
+        "length_penalty": args.length_penalty,
+        "repetition_penalty": args.repetition_penalty,
+    }
+    if args.benchmark_type == "ort":
+        # convert_to_onnx export or ONNX E2E solution created by Olive
+        for k, v in inputs.items():
+            inputs[k] = np.array([v], dtype=np.float32 if "penalty" in k else np.int32)
+        if args.has_decoder_input_ids:
+            inputs["decoder_input_ids"] = np.array([args.decoder_input_ids], dtype=np.int32)
+        if args.has_logits_processor:
+            inputs["logits_processor"] = np.array([args.logits_processor], dtype=np.int32)
+        if args.has_temperature:
+            inputs["temperature"] = np.array([args.temperature], dtype=np.float32)
+
+    # Measure time taken to load audio file
+    logger.info(f"Load audio: {args.audio_path}")
+    load_audio_fn = lambda onnx_e2e: load_via_numpy() if onnx_e2e else load_via_ffmpeg()  # noqa: E731
+    time_fn(args, load_audio_fn, args.has_audio_stream)
+    audio_data = load_audio_fn(args.has_audio_stream)
+
+    if args.has_audio_stream:
+        # ONNX E2E solution created by Olive
+        inputs["audio_stream"] = audio_data
+        return inputs
+
+    # Measure time taken to get input features
+    logger.info("Feature extraction: ")
+    return_type = "np" if args.benchmark_type == "ort" else "pt"
+    processor_fn = lambda audio: args.processor.feature_extractor(  # noqa: E731
+        [audio], return_tensors=return_type, sampling_rate=args.sampling_rate
+    ).input_features
+    time_fn(args, processor_fn, audio_data)
+    input_features = processor_fn(audio_data)
+
+    if args.benchmark_type == "ort":
+        # convert_to_onnx export
+        inputs["input_features"] = input_features
+        return inputs
+
+    inputs["inputs"] = input_features.to(
+        dtype=torch.float16 if args.use_fp16 else torch.float32, device=args.target_device
+    )
+    inputs["no_repeat_ngram_size"] = args.no_repeat_ngram_size
+    inputs["early_stopping"] = True
+    inputs["use_cache"] = True
+
+    if args.decoder_input_ids:
+        inputs["forced_decoder_ids"] = args.decoder_input_ids
+
+    return inputs
+
+
+def get_model(args: argparse.Namespace):
+    model, sess_options = None, None
+    start_time, end_time = None, None
+
+    # There are multiple sources that the model could come from:
+    # 1) Benchmark Whisper from Hugging Face
+    # 2) Benchmark Whisper ONNX model from Optimum export (without pre/post processing)
+    # 3) Benchmark Whisper ONNX E2E model from Olive (with pre/post processing)
+
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        source = args.hf_pt_model_path if args.hf_pt_model_path else args.model_name
+        start_time = time.time()
+        model = AutoModelForSpeechSeq2Seq.from_pretrained(
+            source,
+            torch_dtype=torch.float16 if args.use_fp16 else torch.float32,
+            use_cache=True,
+        ).to(args.target_device)
+        end_time = time.time()
+
+        if args.benchmark_type == "hf-pt-compile":
+            model = torch.compile(model)
+
+    elif args.benchmark_type in {"hf-ort", "ort"}:
+        sess_options = ort.SessionOptions()
+        sess_options.enable_profiling = args.profile
+        sess_options.register_custom_ops_library(get_library_path())
+        if args.verbose:
+            sess_options.log_verbosity_level = 1
+            sess_options.log_severity_level = 1
+
+    else:
+        raise Exception(f"Cannot recognize {args.benchmark_type}")
+
+    if args.benchmark_type == "hf-ort":
+        # Optimum export
+        provider = args.execution_provider[0] if type(args.execution_provider) is tuple else args.execution_provider
+        provider_options = args.execution_provider[1] if type(args.execution_provider) is tuple else None
+
+        start_time = time.time()
+        model = ORTModelForSpeechSeq2Seq.from_pretrained(
+            args.hf_ort_dir_path,
+            provider=provider,
+            provider_options=provider_options,
+            session_options=sess_options,
+            use_io_binding=True,  # Avoid memory copy overhead
+        )
+        end_time = time.time()
+
+    if args.benchmark_type == "ort":
+        # convert_to_onnx.py export
+        logger.info(f"Loading model from {args.ort_model_path}")
+        start_time = time.time()
+        model = ort.InferenceSession(
+            args.ort_model_path,
+            sess_options,
+            providers=[args.execution_provider],
+        )
+        end_time = time.time()
+
+    logger.info(f"Loaded model in {end_time - start_time} s")
+
+    return model
+
+
+def time_fn(args, fn, inputs):
+    warmup_inputs = inputs[0] if type(inputs) is tuple else inputs
+    benchmark_inputs = inputs[1] if type(inputs) is tuple else inputs
+    torch_device = torch.device(args.target_device)
+
+    # Warm up
+    warmup_range = (
+        range(args.warmup_runs)
+        if args.benchmark_type == "ort"
+        else trange(args.warmup_runs, file=sys.stdout, desc="Warm up")
+    )
+
+    if args.verbose:
+        outputs = fn(warmup_inputs)
+        logger.info(outputs)
+
+    for _ in warmup_range:
+        fn(warmup_inputs)
+
+    # Benchmark
+    if args.device != "cpu":
+        torch.cuda.synchronize(torch_device)
+    start_time = time.time()
+
+    bench_range = (
+        range(args.num_runs)
+        if args.benchmark_type == "ort"
+        else trange(args.num_runs, file=sys.stdout, desc="Benchmark")
+    )
+    for _ in bench_range:
+        fn(benchmark_inputs)
+
+    if args.device != "cpu":
+        torch.cuda.synchronize(torch_device)
+    end_time = time.time()
+
+    # Newline print after trange in order to print metrics on new lines without progress bar on same line
+    if args.benchmark_type != "ort":
+        logger.info("")
+
+    batch_size = 1
+    latency = (end_time - start_time) / args.num_runs
+    throughput = batch_size / latency
+
+    logger.info(f"Latency: {latency} s")
+    logger.info(f"Throughput: {throughput} qps")
+    return
+
+
+def profile_fn(args, fn, inputs, inputs_type):
+    # Filename prefix format:
+    # "<benchmark-type>-<precision>-<device>_<inference-step>_<inputs-type>_<current-time>"
+    prefix = f"{args.benchmark_type.lower()}-{args.precision}-{args.device}_{fn.__name__.replace('_', '-')}_{inputs_type}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}"
+    filename = None
+
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile"}:
+        # Profile PyTorch kernels
+        with profile(  # noqa: SIM117
+            activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA], record_shapes=True, profile_memory=True
+        ) as prof:
+            with record_function("model_inference"):
+                fn(inputs)
+        prof_data = prof.key_averages(group_by_stack_n=5).table(sort_by=args.pt_filter_by, row_limit=args.pt_num_rows)
+
+        filename = os.path.join(args.log_folder, f"{prefix}.log")
+        with open(filename, "w") as f:
+            f.write(prof_data)
+
+    else:
+        # Profile ORT kernels
+        fn(inputs)
+
+        # Set new log name for ORT profile log generated
+        filename = f"{prefix}.json"
+
+    return filename
+
+
+def measure_fn(args, fn, inputs):
+    # Measure CPU usage
+    pid = os.getpid()
+    process = psutil.Process(pid)
+    process.cpu_percent(interval=0.1)
+
+    fn(inputs)
+    logger.info(f"CPU usage: {process.cpu_percent(interval=None)}%")
+
+    # Measure memory usage
+    gc.collect()
+    torch.cuda.empty_cache()
+    measure_memory(is_gpu=(args.device != "cpu"), func=lambda: fn(inputs), monitor_type=args.monitor_type)
+
+    # Flush output so memory usage is printed
+    sys.stdout.flush()
+
+
+def run_hf_inference(args, inputs, model):
+    # Inference steps to measure
+    def get_pred_ids(inputs):
+        # Inference pass with predicted token ids generation
+        predicted_ids = model.generate(**inputs)
+        return predicted_ids
+
+    def gen_and_dec(inputs):
+        # Inference pass with generation and decoding
+        predicted_ids = get_pred_ids(inputs)
+        transcription = []
+        for _ in range(args.num_return_sequences):
+            transcription.append(args.processor.batch_decode(predicted_ids, skip_special_tokens=True)[0])
+        return predicted_ids, transcription
+
+    # Examples of other inference steps that can be measured:
+    # To use, uncomment the function and assign it to `generate_fn`
+
+    # def get_logits(inputs):
+    #     # Inference pass without decoding
+    #     outputs = model(**inputs)
+    #     return outputs
+
+    generate_fn = gen_and_dec
+
+    if args.benchmark_type == "hf-pt-compile":
+        # Run forward pass once with each set of inputs to process through Dynamo
+        generate_fn(inputs)
+
+    if args.profile:
+        new_logname = profile_fn(args, generate_fn, inputs, "gen-and-dec")
+        if args.benchmark_type == "hf-ort":
+            # Rename log files per model component and turn profiling off to stop appending to log
+            new_prefix = new_logname[: -len(".json")]
+
+            old_logname = model.encoder.session.end_profiling()
+            new_logname = new_prefix + "-encoder.json"
+            if os.path.isfile(old_logname):
+                logger.warning(f"Renaming {old_logname} to {new_logname}")
+                os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+            old_logname = model.decoder.session.end_profiling()
+            new_logname = new_prefix + "-decoder.json"
+            if os.path.isfile(old_logname):
+                logger.warning(f"Renaming {old_logname} to {new_logname}")
+                os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+            old_logname = model.decoder_with_past.session.end_profiling()
+            new_logname = new_prefix + "-decoder-with-past.json"
+            if os.path.isfile(old_logname):
+                logger.warning(f"Renaming {old_logname} to {new_logname}")
+                os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+        return
+
+    # PyTorch evaluations
+    logger.info("\nEvaluating PyTorch...")
+    time_fn(args, generate_fn, inputs)
+    predicted_ids, transcription = generate_fn(inputs)
+    logger.info(f"Generated token length: {len(predicted_ids[0])} tokens")
+    logger.info(f"Transcription: {transcription[0]}")
+    measure_fn(args, generate_fn, inputs)
+
+
+def run_ort_inference(args, inputs, model):
+    def prepare_ort_inputs(inputs, warmup=False):
+        # Check that all model inputs will be provided
+        model_inputs = {model_input.name for model_input in model.get_inputs()}
+        user_inputs = set(inputs.keys())
+        missing_inputs = model_inputs - user_inputs
+        if len(missing_inputs):
+            logger.error(f"The following model inputs are missing: {missing_inputs}")
+            raise Exception("There are missing inputs to the model. Please add them and try again.")
+
+        # Remove unnecessary inputs from model inputs
+        unnecessary_inputs = user_inputs - model_inputs
+        if len(unnecessary_inputs):
+            for unnecessary_input in unnecessary_inputs:
+                logger.info(f"Removing unnecessary input '{unnecessary_input}' from user provided inputs")
+                del inputs[unnecessary_input]
+
+        # Add IO bindings for non-CPU execution providers
+        if args.device != "cpu":
+            io_binding = model.io_binding()
+            for k, v in inputs.items():
+                io_binding.bind_cpu_input(k, v)
+            for output in model.get_outputs():
+                io_binding.bind_output(output.name, device_type=args.device, device_id=args.device_id)
+            return io_binding
+
+        return inputs
+
+    def with_io_binding(io_binding):
+        # Inference pass with IO binding
+        model.run_with_iobinding(io_binding)
+        return io_binding
+
+    def without_io_binding(inputs):
+        # Inference pass without IO binding
+        outputs = model.run(None, inputs)
+        return outputs
+
+    def handle_output(output):
+        if args.eos_token_id in output:
+            first_end = np.where(output == args.eos_token_id)[0][0]
+            return output[: first_end + 1]
+
+        return output
+
+    generate_fn = with_io_binding if args.device != "cpu" else without_io_binding
+    ort_inputs = prepare_ort_inputs(inputs)
+
+    if args.profile:
+        new_logname = profile_fn(args, generate_fn, ort_inputs, "e2e")
+
+        # Turn profiling off to stop appending to log file
+        old_logname = model.end_profiling()
+        logger.warning(f"Renaming {old_logname} to {new_logname}")
+        os.rename(old_logname, os.path.join(args.log_folder, new_logname))
+
+        return
+
+    # ORT evaluation
+    logger.info("\nEvaluating ONNX Runtime...")
+    ort_evaluate_inputs = ort_inputs
+
+    time_fn(args, generate_fn, ort_evaluate_inputs)
+    ort_outputs = generate_fn(ort_inputs)
+    if args.device != "cpu":
+        ort_outputs = ort_outputs.copy_outputs_to_cpu()
+    ort_outputs = ort_outputs[0]
+
+    if args.has_audio_stream:
+        # ONNX E2E model from Olive produces transcribed output
+        logger.info(f"Transcription: {ort_outputs[0][0]}")
+    else:
+        # convert_to_onnx model produces generated ids
+        actual_output = handle_output(ort_outputs[0][0])
+        logger.info(f"Generated token length: {len(actual_output)} tokens")
+        transcription = args.processor.batch_decode(ort_outputs[0], skip_special_tokens=True)[0]
+        # print to stdout as the output for comparison
+        print(f"{transcription}")
+
+    measure_fn(args, generate_fn, ort_inputs)
+
+
+def run_inference(args, inputs, model):
+    if args.benchmark_type in {"hf-pt-eager", "hf-pt-compile", "hf-ort"}:
+        run_hf_inference(args, inputs, model)
+    elif args.benchmark_type == "ort":
+        run_ort_inference(args, inputs, model)
+    else:
+        raise Exception(f"Cannot recognize {args.benchmark_type}")
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-bt",
+        "--benchmark-type",
+        type=str,
+        required=True,
+        choices=["hf-pt-eager", "hf-pt-compile", "hf-ort", "ort"],
+    )
+
+    parser.add_argument(
+        "-m",
+        "--model-name",
+        type=str,
+        required=True,
+        help="Hugging Face name of model (e.g. 'openai/whisper-large-v2')",
+    )
+    parser.add_argument(
+        "-p",
+        "--precision",
+        type=str,
+        required=True,
+        default="fp32",
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision for model. For ONNX models, the model's precision should be set before running this script.",
+    )
+
+    parser.add_argument(
+        "--hf-pt-model-path",
+        type=str,
+        default="",
+        help="Path to directory containing all PyTorch files (e.g. tokenizer, PyTorch model)",
+    )
+    parser.add_argument(
+        "--hf-ort-dir-path",
+        type=str,
+        default="",
+        help="Path to directory containing all ONNX files (e.g. tokenizer, encoder, decoder, decoder_with_past)",
+    )
+    parser.add_argument(
+        "--ort-model-path",
+        type=str,
+        default="",
+        help="Path to ONNX model",
+    )
+
+    # Args for running and evaluating the model
+    parser.add_argument("-a", "--audio-path", type=str, required=True, help="Path to audio file for E2E evaluation")
+    parser.add_argument(
+        "-d",
+        "--device",
+        type=str,
+        default="cuda" if torch.cuda.is_available() else "cpu",
+        choices=["cpu", "cuda"],
+    )
+    parser.add_argument("-id", "--device-id", type=int, default=0)
+    parser.add_argument("-w", "--warmup-runs", type=int, default=5)
+    parser.add_argument("-n", "--num-runs", type=int, default=10)
+    parser.add_argument("--seed", type=int, default=2)
+
+    # Optional args:
+    parser.add_argument("--sampling-rate", type=int, default=16000, help="Sampling rate for audio (in Hz)")
+
+    # Args for decoding logic
+    # Required args:
+    parser.add_argument("--max-length", type=int, default=448)
+    parser.add_argument("--min-length", type=int, default=0)
+    parser.add_argument("--num-beams", type=int, default=1)
+    parser.add_argument("--num-return-sequences", type=int, default=1)
+    parser.add_argument("--length-penalty", type=float, default=1.0)
+    parser.add_argument("--repetition-penalty", type=float, default=1.0)
+    parser.add_argument("--no-repeat-ngram-size", type=int, default=3)
+
+    # Optional args for E2E solution:
+    parser.add_argument(
+        "--decoder-input-ids",
+        type=str,
+        default="[]",
+        help="The forced decoder ids for generation. Format is [start token, timestamp token, language token, task token]. Default is [start token]. See `decoder_input_ids` in https://github.com/microsoft/Olive/tree/main/examples/whisper for details.",
+    )
+    parser.add_argument(
+        "--logits-processor",
+        type=int,
+        default=1,
+        help="Whether to use timestamps logits processor or not (0 for false, 1 for true).",
+    )
+    parser.add_argument(
+        "--temperature",
+        type=float,
+        default=1.0,
+        help="Temperature value for generation.",
+    )
+
+    # Args for accessing detailed info
+    parser.add_argument("--profile", default=False, action="store_true")
+    parser.add_argument(
+        "--pt-filter-by", type=str, default="self_cpu_time_total", help="What to filter PyTorch profiler by"
+    )
+    parser.add_argument("--pt-num-rows", type=int, default=1000, help="Number of rows for PyTorch profiler to display")
+    parser.add_argument("--verbose", default=False, action="store_true")
+    parser.add_argument("--log-folder", type=str, default=os.path.join("."), help="Folder to cache log files")
+
+    args = parser.parse_args()
+
+    # Set seed properties
+    np.random.seed(args.seed)
+    torch.manual_seed(args.seed)
+
+    args.monitor_type = args.device
+    # Set runtime properties
+    if "ort" in args.benchmark_type:
+        args.execution_provider = f"{args.device.upper()}ExecutionProvider"
+        if args.execution_provider == "CUDAExecutionProvider":
+            args.execution_provider = (args.execution_provider, {"device_id": args.device_id})
+
+    # Check that model paths have been specified for any benchmarking with ORT
+    if args.benchmark_type == "hf-ort":
+        assert args.hf_ort_dir_path, "Please specify a path to `--hf-ort-dir-path`"
+    if args.benchmark_type == "ort":
+        assert args.ort_model_path, "Please specify a path to `--ort-model-path`"
+
+    # Convert decoder_input_ids string to list of ids
+    # (e.g. "[1, 50257]" for Hugging Face or "[50257]" for ORT)
+    args.decoder_input_ids = ast.literal_eval(args.decoder_input_ids)
+
+    return args
+
+
+def main():
+    args = parse_args()
+    setup_logger(args.verbose)
+    logger.info(args.__dict__)
+    torch.backends.cudnn.benchmark = True
+
+    config = WhisperConfig.from_pretrained(args.model_name)
+    processor = WhisperProcessor.from_pretrained(args.model_name)
+    target_device = f"cuda:{args.device_id}" if args.device != "cpu" else args.device
+    use_fp16 = args.precision == "fp16" or (args.precision in {"int8", "int4"} and args.device != "cpu")
+
+    setattr(args, "processor", processor)  # noqa: B010
+    setattr(args, "target_device", target_device)  # noqa: B010
+    setattr(args, "use_fp16", use_fp16)  # noqa: B010
+    setattr(args, "has_audio_stream", False)  # noqa: B010
+    setattr(args, "eos_token_id", config.eos_token_id)  # noqa: B010
+
+    logger.info(f"Forced decoder prompt ids: {args.decoder_input_ids}")
+
+    # Measure cost to transcribe audio
+    model = get_model(args)
+    if args.benchmark_type == "ort":
+        # Check for optional inputs that could have been added during export
+        ort_model_inputs = {model_input.name for model_input in model.get_inputs()}
+        args.has_audio_stream = "audio_stream" in ort_model_inputs
+        setattr(args, "has_decoder_input_ids", "decoder_input_ids" in ort_model_inputs)  # noqa: B010
+        setattr(args, "has_logits_processor", "logits_processor" in ort_model_inputs)  # noqa: B010
+        setattr(args, "has_temperature", "temperature" in ort_model_inputs)  # noqa: B010
+
+        if args.decoder_input_ids == []:
+            args.decoder_input_ids = [config.decoder_start_token_id]
+
+    inputs = get_inputs(args)
+    run_inference(args, inputs, model)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark_all.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark_all.py
new file mode 100644
index 0000000000000000000000000000000000000000..57b763f7f7883f97bd92518ce4687dead856d952
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/benchmark_all.py
@@ -0,0 +1,526 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import datetime
+import json
+import logging
+import os
+import subprocess
+
+import librosa
+import torch
+from benchmark_helper import setup_logger
+from metrics import BenchmarkRecord
+from transformers import WhisperConfig, WhisperProcessor
+
+logger = logging.getLogger(__name__)
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-a",
+        "--audio-path",
+        type=str,
+        required=True,
+        help="Path to folder of audio files for E2E evaluation",
+    )
+
+    parser.add_argument(
+        "-l",
+        "--language",
+        default=None,
+        help="Language of audio file",
+    )
+
+    parser.add_argument(
+        "-t",
+        "--task",
+        default=None,
+        choices=["transcribe", "translate"],
+        help="Task to complete",
+    )
+
+    parser.add_argument(
+        "-w",
+        "--warmup-runs",
+        type=int,
+        default=5,
+    )
+
+    parser.add_argument(
+        "-n",
+        "--num-runs",
+        type=int,
+        default=10,
+    )
+
+    parser.add_argument(
+        "--hf-pt-eager",
+        default=False,
+        action="store_true",
+        help="Benchmark in PyTorch without `torch.compile`",
+    )
+
+    parser.add_argument(
+        "--hf-pt-compile",
+        default=False,
+        action="store_true",
+        help="Benchmark in PyTorch with `torch.compile`",
+    )
+
+    parser.add_argument(
+        "--hf-ort-dir-path",
+        type=str,
+        help="Path to folder containing ONNX models for Optimum + ORT benchmarking",
+    )
+
+    parser.add_argument(
+        "--ort-model-path",
+        type=str,
+        help="Path to ONNX model for ORT benchmarking",
+    )
+
+    parser.add_argument(
+        "--model-name",
+        type=str,
+        required=True,
+        help="Model name in Hugging Face (e.g. openai/whisper-large-v2)",
+    )
+
+    parser.add_argument(
+        "--precision",
+        type=str,
+        required=True,
+        choices=["int4", "int8", "fp16", "fp32"],
+        help="Precision to run model",
+    )
+
+    parser.add_argument(
+        "--device",
+        type=str,
+        required=True,
+        choices=["cpu", "cuda"],
+        help="Device to benchmark models",
+    )
+
+    parser.add_argument(
+        "--device-id",
+        type=int,
+        default=0,
+        help="GPU device ID",
+    )
+
+    parser.add_argument(
+        "--verbose",
+        default=False,
+        action="store_true",
+        help="Print detailed logs",
+    )
+
+    parser.add_argument(
+        "--timeout",
+        type=int,
+        default=5,
+        help="Number of mins to attempt the benchmark before moving on",
+    )
+
+    parser.add_argument(
+        "--log-folder",
+        type=str,
+        default=None,
+        help="Path to folder to save logs and results",
+    )
+
+    parser.add_argument("--tune", default=False, action="store_true")
+
+    args = parser.parse_args()
+
+    setattr(args, "model_size", args.model_name.split("/")[-1].replace(".", "-"))  # noqa: B010
+    log_folder_name = f"./{args.model_size}-{args.precision}"
+    if not args.log_folder:
+        args.log_folder = log_folder_name
+    os.makedirs(args.log_folder, exist_ok=True)
+
+    # Convert timeout value to secs
+    args.timeout *= 60
+
+    return args
+
+
+def process_log_file(device_id, log_file, base_results):
+    entries = []
+
+    # Detect steps in speech pipeline
+    step = None
+    load_audio_pattern = "Load audio: "
+    feat_ext_pattern = "Feature extraction: "
+    pytorch_pattern = "Evaluating PyTorch..."
+    onnxruntime_pattern = "Evaluating ONNX Runtime..."
+
+    load_audio_latency_s, load_audio_throughput_s = None, None
+    feat_ext_latency_s, feat_ext_throughput_s = None, None
+    token_length, latency_s, per_token_latency_s, per_token_latency_ms = None, None, None, None
+    throughput, memory = None, None
+
+    # Detect metrics
+    latency_pattern = "Latency: "
+    throughput_pattern = "Throughput: "
+    token_length_pattern = "Generated token length: "
+    memory_pattern = "peak="
+
+    with open(log_file) as f:
+        for input_line in f:
+            line = input_line.replace("\n", "")
+
+            # Get step in speech recognition pipeline
+            if load_audio_pattern in line:
+                step = "load-audio"
+            elif feat_ext_pattern in line:
+                step = "feature-extraction"
+            elif pytorch_pattern in line or onnxruntime_pattern in line:
+                step = "process"
+
+            # Check metrics
+            if latency_pattern in line:
+                latency_s = float(line[len(latency_pattern) : line.rfind(" ")])
+            elif throughput_pattern in line:
+                throughput = float(line[len(throughput_pattern) : line.rfind(" ")])
+                if step == "load-audio":
+                    load_audio_latency_s, load_audio_throughput_s = latency_s, throughput
+                    step = None
+                if step == "feature-extraction":
+                    feat_ext_latency_s, feat_ext_throughput_s = latency_s, throughput
+                    step = None
+            elif token_length_pattern in line:
+                token_length = int(line[len(token_length_pattern) : line.rfind(" ")])
+                per_token_latency_s = latency_s / token_length
+                per_token_latency_ms = per_token_latency_s * 1000
+            elif memory_pattern in line:
+                if "CPU" in line:
+                    # Example format for log entry:
+                    # CPU memory usage: before=1000.0 MB, peak=2000.0 MB
+                    memory = float(line[line.rfind("=") + 1 : line.rfind(" MB")]) / 1000
+                else:
+                    # Example format for log entry:
+                    # GPU memory usage: before=[{'device_id': 0, 'name': 'Tesla V100-PCIE-16GB', 'max_used_MB': 1638.875}, {'device_id': 1, 'name': 'Tesla V100-PCIE-16GB', 'max_used_MB': 236.875},  peak=[{'device_id': 0, 'name': 'Tesla V100-PCIE-16GB', 'max_used_MB': 1780.875}, {'device_id': 1, 'name': 'Tesla V100-PCIE-16GB', 'max_used_MB': 236.875}]
+                    peak = line[line.find(memory_pattern) + len(memory_pattern) :].replace("'", '"')
+                    usage = json.loads(peak)[device_id]["max_used_MB"]
+                    memory = float(usage) / 1000
+
+                # Calculate real-time factor (RTF):
+                # RTF = total latency / audio duration
+                total_latency = (
+                    (load_audio_latency_s if load_audio_latency_s else 0)
+                    + (feat_ext_latency_s if feat_ext_latency_s else 0)
+                    + (latency_s if latency_s else 0)
+                )
+                audio_duration = base_results[-1]
+                rtf = (total_latency / audio_duration) if audio_duration else -1
+                logger.info(f"Total latency: {total_latency} s")
+                logger.info(f"Audio duration: {audio_duration} s")
+                logger.info(f"Real-time factor: {rtf}")
+
+                # Append log entry to list of entries
+                entry = base_results + [  # noqa: RUF005
+                    token_length,
+                    load_audio_latency_s,
+                    load_audio_throughput_s,
+                    feat_ext_latency_s if feat_ext_latency_s else -1,
+                    feat_ext_throughput_s if feat_ext_throughput_s else -1,
+                    latency_s,
+                    per_token_latency_ms,
+                    throughput,
+                    memory,
+                    rtf,
+                ]
+                entries.append(entry)
+
+    return entries
+
+
+def save_results(results, filename):
+    import pandas as pd  # noqa: PLC0415
+
+    df = pd.DataFrame(
+        results,
+        columns=[
+            "Warmup Runs",
+            "Measured Runs",
+            "Model Name",
+            "Engine",
+            "Precision",
+            "Device",
+            "Audio File",
+            "Duration (s)",
+            "Token Length",
+            "Load Audio Latency (s)",
+            "Load Audio Throughput (qps)",
+            "Feature Extractor Latency (s)",
+            "Feature Extractor Throughput (qps)",
+            "Latency (s)",
+            "Per Token Latency (ms/token)",
+            "Throughput (qps)",
+            "Memory (GB)",
+            "Real Time Factor (RTF)",
+        ],
+    )
+
+    # Set column types
+    df["Warmup Runs"] = df["Warmup Runs"].astype("int")
+    df["Measured Runs"] = df["Measured Runs"].astype("int")
+    df["Duration (s)"] = df["Duration (s)"].astype("float")
+    df["Token Length"] = df["Token Length"].astype("int")
+    df["Load Audio Latency (s)"] = df["Load Audio Latency (s)"].astype("float")
+    df["Load Audio Throughput (qps)"] = df["Load Audio Throughput (qps)"].astype("float")
+    df["Feature Extractor Latency (s)"] = df["Feature Extractor Latency (s)"].astype("float")
+    df["Feature Extractor Throughput (qps)"] = df["Feature Extractor Throughput (qps)"].astype("float")
+    df["Latency (s)"] = df["Latency (s)"].astype("float")
+    df["Per Token Latency (ms/token)"] = df["Per Token Latency (ms/token)"].astype("float")
+    df["Throughput (qps)"] = df["Throughput (qps)"].astype("float")
+    df["Memory (GB)"] = df["Memory (GB)"].astype("float")
+    df["Real Time Factor (RTF)"] = df["Real Time Factor (RTF)"].astype("float")
+
+    # get package name and version
+    import pkg_resources  # noqa: PLC0415
+
+    installed_packages = pkg_resources.working_set
+    installed_packages_list = sorted(
+        [f"{i.key}=={i.version}" for i in installed_packages if i.key in ["onnxruntime", "onnxruntime-gpu"]]
+    )
+    ort_pkg_name = ""
+    ort_pkg_version = ""
+    if installed_packages_list:
+        ort_pkg_name = installed_packages_list[0].split("==")[0]
+        ort_pkg_version = installed_packages_list[0].split("==")[1]
+
+    # Save results to csv with standard format
+    records = []
+    for _, row in df.iterrows():
+        if row["Engine"] == "onnxruntime":
+            record = BenchmarkRecord(
+                row["Model Name"], row["Precision"], row["Engine"], row["Device"], ort_pkg_name, ort_pkg_version
+            )
+        else:
+            record = BenchmarkRecord(
+                row["Model Name"], row["Precision"], row["Engine"], row["Device"], torch.__name__, torch.__version__
+            )
+        record.config.customized["audio_file"] = row["Audio File"]
+        record.config.warmup_runs = row["Warmup Runs"]
+        record.config.measured_runs = row["Measured Runs"]
+
+        record.metrics.customized["duration"] = row["Duration (s)"]
+        record.metrics.customized["token_length"] = row["Token Length"]
+        record.metrics.customized["load_audio_latency"] = row["Load Audio Latency (s)"]
+        record.metrics.customized["load_audio_throughput"] = row["Load Audio Throughput (qps)"]
+        record.metrics.customized["feature_extractor_latency_s"] = row["Feature Extractor Latency (s)"]
+        record.metrics.customized["feature_extractor_throughput_qps"] = row["Feature Extractor Throughput (qps)"]
+        record.metrics.customized["per_token_latency_ms"] = row["Per Token Latency (ms/token)"]
+        record.metrics.customized["rtf"] = row["Real Time Factor (RTF)"]
+
+        record.metrics.latency_ms_mean = row["Latency (s)"] * 1000
+        record.metrics.throughput_qps = row["Throughput (qps)"]
+        record.metrics.max_memory_usage_GB = row["Memory (GB)"]
+
+        records.append(record)
+
+    BenchmarkRecord.save_as_csv(filename, records)
+    BenchmarkRecord.save_as_json(filename.replace(".csv", ".json"), records)
+    logger.info(f"Results saved in {filename}!")
+
+
+def benchmark(args, benchmark_cmd, engine, audio_file, duration):
+    log_filename = f"{engine}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}.log"
+    log_path = os.path.join(args.log_folder, log_filename)
+    with open(log_path, "w") as log_file:
+        process = subprocess.Popen(benchmark_cmd, stdout=log_file, stderr=log_file)
+        try:
+            process.wait(args.timeout)
+        except subprocess.TimeoutExpired:
+            process.kill()
+
+    # Create entries for csv
+    logger.info("Gathering data from log files...")
+    base_results = [
+        args.warmup_runs,
+        args.num_runs,
+        args.model_name,
+        engine,
+        args.precision,
+        args.device,
+        audio_file,
+        duration,
+    ]
+    results = process_log_file(args.device_id, log_path, base_results)
+
+    return results
+
+
+def main():
+    args = get_args()
+    setup_logger(args.verbose)
+    logger.info(args.__dict__)
+    torch.backends.cudnn.benchmark = True
+
+    config = WhisperConfig.from_pretrained(args.model_name)
+    processor = WhisperProcessor.from_pretrained(args.model_name)
+
+    # Calculate forced decoder input ids
+    hf_forced_decoder_ids = processor.get_decoder_prompt_ids(language=args.language, task=args.task)
+    ort_forced_decoder_ids = [config.decoder_start_token_id] + [token_id[1] for token_id in hf_forced_decoder_ids]
+    hf_decoder_input_ids_cmd = (
+        ["--decoder-input-ids", str(hf_forced_decoder_ids)] if args.language and args.task else []
+    )
+    ort_decoder_input_ids_cmd = (
+        ["--decoder-input-ids", str(ort_forced_decoder_ids)] if args.language and args.task else []
+    )
+    ort_tune_cmd = ["--tune"] if args.tune else []
+
+    all_results = []
+    for audio_file in os.listdir(args.audio_path):
+        audio_path = os.path.join(args.audio_path, audio_file)
+        try:
+            duration = librosa.get_duration(path=audio_path)
+        except Exception as e:
+            duration = -1
+            logger.warning(f"An error occurred while trying to calculate the audio duration: {e}", exc_info=True)
+            logger.warning(
+                f"If you get an error that says:\n\tsoundfile.LibsndfileError: Error opening '{audio_file}': File contains data in an unknown format.\nyou may not have installed `ffmpeg` in addition to installing `librosa`."
+            )
+        logger.info(f"Testing {audio_path}...")
+
+        # Benchmark PyTorch without torch.compile
+        if args.hf_pt_eager:
+            benchmark_cmd = [  # noqa: RUF005
+                "python",
+                "-m",
+                "models.whisper.benchmark",
+                "--audio-path",
+                audio_path,
+                "--benchmark-type",
+                "hf-pt-eager",
+                "--model-name",
+                args.model_name,
+                "--precision",
+                args.precision,
+                "--device",
+                args.device,
+                "--device-id",
+                str(args.device_id),
+                "--warmup-runs",
+                str(args.warmup_runs),
+                "--num-runs",
+                str(args.num_runs),
+                "--log-folder",
+                args.log_folder,
+            ] + hf_decoder_input_ids_cmd
+            logger.info("Benchmark PyTorch without torch.compile")
+            results = benchmark(args, benchmark_cmd, "pytorch-eager", audio_file, duration)
+            all_results.extend(results)
+
+        # Benchmark PyTorch with torch.compile
+        if args.hf_pt_compile:
+            benchmark_cmd = [  # noqa: RUF005
+                "python",
+                "-m",
+                "models.whisper.benchmark",
+                "--audio-path",
+                audio_path,
+                "--benchmark-type",
+                "hf-pt-compile",
+                "--model-name",
+                args.model_name,
+                "--precision",
+                args.precision,
+                "--device",
+                args.device,
+                "--device-id",
+                str(args.device_id),
+                "--warmup-runs",
+                str(args.warmup_runs),
+                "--num-runs",
+                str(args.num_runs),
+                "--log-folder",
+                args.log_folder,
+            ] + hf_decoder_input_ids_cmd
+            logger.info("Benchmark PyTorch with torch.compile")
+            results = benchmark(args, benchmark_cmd, "pytorch-compile", audio_file, duration)
+            all_results.extend(results)
+
+        # Benchmark Optimum + ONNX Runtime
+        if args.hf_ort_dir_path:
+            benchmark_cmd = [  # noqa: RUF005
+                "python",
+                "-m",
+                "models.whisper.benchmark",
+                "--audio-path",
+                audio_path,
+                "--benchmark-type",
+                "hf-ort",
+                "--hf-ort-dir-path",
+                args.hf_ort_dir_path,
+                "--model-name",
+                args.model_name,
+                "--precision",
+                args.precision,
+                "--device",
+                args.device,
+                "--device-id",
+                str(args.device_id),
+                "--warmup-runs",
+                str(args.warmup_runs),
+                "--num-runs",
+                str(args.num_runs),
+                "--log-folder",
+                args.log_folder,
+            ] + hf_decoder_input_ids_cmd
+            logger.info("Benchmark Optimum + ONNX Runtime")
+            results = benchmark(args, benchmark_cmd, "optimum-ort", audio_file, duration)
+            all_results.extend(results)
+
+        # Benchmark ONNX Runtime
+        if args.ort_model_path:
+            benchmark_cmd = (
+                [  # noqa: RUF005
+                    "python",
+                    "-m",
+                    "models.whisper.benchmark",
+                    "--audio-path",
+                    audio_path,
+                    "--benchmark-type",
+                    "ort",
+                    "--ort-model-path",
+                    args.ort_model_path,
+                    "--model-name",
+                    args.model_name,
+                    "--precision",
+                    args.precision,
+                    "--device",
+                    args.device,
+                    "--device-id",
+                    str(args.device_id),
+                    "--warmup-runs",
+                    str(args.warmup_runs),
+                    "--num-runs",
+                    str(args.num_runs),
+                    "--log-folder",
+                    args.log_folder,
+                ]
+                + ort_decoder_input_ids_cmd
+                + ort_tune_cmd
+            )
+            logger.info("Benchmark ONNX Runtime")
+            results = benchmark(args, benchmark_cmd, "onnxruntime", audio_file, duration)
+            all_results.extend(results)
+
+    csv_file = f"{args.model_size}-{args.precision}_{datetime.datetime.now():%Y-%m-%d_%H:%M:%S}.csv"
+    save_results(all_results, os.path.join(args.log_folder, csv_file))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/convert_to_onnx.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/convert_to_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b763fff8fe8c06e0de9161c1a1e6be64c7b657b
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/convert_to_onnx.py
@@ -0,0 +1,609 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import argparse
+import logging
+import os
+import warnings
+
+import onnx
+import torch
+from benchmark_helper import Precision, create_onnxruntime_session, prepare_environment, setup_logger
+from whisper_chain import chain_model
+from whisper_encoder import WhisperEncoder
+from whisper_helper import PRETRAINED_WHISPER_MODELS, WhisperHelper
+
+from onnxruntime.quantization.matmul_nbits_quantizer import (
+    KQuantWeightOnlyQuantConfig,
+    MatMulNBitsQuantizer,
+    QuantFormat,
+)
+
+logger = logging.getLogger("")
+
+PROVIDERS = {
+    "cpu": "CPUExecutionProvider",
+    "cuda": "CUDAExecutionProvider",
+}
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    conversion_args = parser.add_argument_group("Conversion Process Args")
+    optional_inputs = parser.add_argument_group("Optional Inputs (for WhisperBeamSearch op)")
+    optional_outputs = parser.add_argument_group("Optional Outputs (for WhisperBeamSearch op)")
+    quant_args = parser.add_argument_group("INT8 Quantization Args")
+
+    #################################
+    # Conversion options for Whisper
+    #################################
+
+    conversion_args.add_argument(
+        "-m",
+        "--model_name_or_path",
+        required=False,
+        default=PRETRAINED_WHISPER_MODELS[0],
+        type=str,
+        help="Model path, or pretrained model name in the list: " + ", ".join(PRETRAINED_WHISPER_MODELS),
+    )
+
+    conversion_args.add_argument(
+        "--model_impl",
+        required=False,
+        default="hf",
+        choices=["hf", "openai"],
+        type=str,
+        help="Select implementation for export of encoder and decoder subgraphs",
+    )
+
+    conversion_args.add_argument(
+        "--cache_dir",
+        required=False,
+        type=str,
+        default=os.path.join(".", "cache_models"),
+        help="Directory to cache pre-trained models",
+    )
+
+    conversion_args.add_argument(
+        "--output",
+        required=False,
+        type=str,
+        default=os.path.join(".", "onnx_models"),
+        help="Output directory",
+    )
+
+    conversion_args.add_argument(
+        "-o",
+        "--optimize_onnx",
+        required=False,
+        action="store_true",
+        help="Use optimizer.py to optimize onnx model",
+    )
+    conversion_args.set_defaults(optimize_onnx=False)
+
+    conversion_args.add_argument(
+        "--use_gpu",
+        required=False,
+        action="store_true",
+        help="Use GPU for model inference",
+    )
+    conversion_args.set_defaults(use_gpu=False)
+
+    conversion_args.add_argument(
+        "-p",
+        "--precision",
+        required=False,
+        type=Precision,
+        default=Precision.FLOAT32,
+        choices=[Precision.FLOAT32, Precision.FLOAT16, Precision.INT8, Precision.INT4],
+        help="Precision of model to run. fp32 for full precision, fp16 for half precision, int8/int4 for quantization",
+    )
+
+    conversion_args.add_argument(
+        "--use_int64_inputs",
+        required=False,
+        action="store_true",
+        help="Use int64 instead of int32 for input_ids and attention_mask.",
+    )
+    conversion_args.set_defaults(use_int64_inputs=False)
+
+    conversion_args.add_argument(
+        "-r",
+        "--provider",
+        required=False,
+        type=str,
+        default="cpu",
+        choices=list(PROVIDERS.keys()),
+        help="Provider to benchmark. Default is CPUExecutionProvider.",
+    )
+
+    conversion_args.add_argument(
+        "--verbose",
+        required=False,
+        action="store_true",
+        help="Enable verbose logging",
+    )
+    conversion_args.set_defaults(verbose=False)
+
+    conversion_args.add_argument(
+        "-e",
+        "--use_external_data_format",
+        required=False,
+        action="store_true",
+        help="Save weights in external file. Necessary for 'small', 'medium', and 'large' models. Optional for 'tiny' and 'base' models.",
+    )
+    conversion_args.set_defaults(use_external_data_format=False)
+
+    conversion_args.add_argument(
+        "-w",
+        "--overwrite",
+        required=False,
+        action="store_true",
+        help="Overwrite existing ONNX model",
+    )
+    conversion_args.set_defaults(overwrite=False)
+
+    conversion_args.add_argument(
+        "--separate_encoder_and_decoder_init",
+        required=False,
+        action="store_true",
+        help="Do not merge encoder and decoder init to initialize past KV caches. Output 3 instead of 2 ONNX models.",
+    )
+    conversion_args.set_defaults(separate_encoder_and_decoder_init=False)
+
+    conversion_args.add_argument(
+        "--no_beam_search_op",
+        required=False,
+        action="store_true",
+        help="Do not produce model with WhisperBeamSearch op, which chains encdecinit and decoder models into one op.",
+    )
+    conversion_args.set_defaults(no_beam_search_op=False)
+
+    conversion_args.add_argument(
+        "--use_decoder_masked_mha",
+        required=False,
+        action="store_true",
+        help="Use DecoderMaskedMultiHeadAttention kernel for improved performance. This is currently an experimental feature.",
+    )
+    conversion_args.set_defaults(use_decoder_masked_mha=False)
+
+    #############################################################
+    # Optional inputs for Whisper
+    # (listed below in the order that WhisperBeamSearch expects)
+    #############################################################
+
+    optional_inputs.add_argument(
+        "-v",
+        "--use_vocab_mask",
+        required=False,
+        action="store_true",
+        help="Use vocab_mask as an extra graph input to enable specific logits processing",
+    )
+    optional_inputs.set_defaults(use_vocab_mask=False)
+
+    optional_inputs.add_argument(
+        "-u",
+        "--use_prefix_vocab_mask",
+        required=False,
+        action="store_true",
+        help="Use prefix_vocab_mask as an extra graph input to enable specific logits processing",
+    )
+    optional_inputs.set_defaults(use_prefix_vocab_mask=False)
+
+    optional_inputs.add_argument(
+        "-f",
+        "--use_forced_decoder_ids",
+        required=False,
+        action="store_true",
+        help="Use decoder_input_ids as an extra graph input to the beam search op",
+    )
+    optional_inputs.set_defaults(use_forced_decoder_ids=False)
+
+    optional_inputs.add_argument(
+        "-l",
+        "--use_logits_processor",
+        required=False,
+        action="store_true",
+        help="Use logits_processor as an extra graph input to enable specific logits processing",
+    )
+    optional_inputs.set_defaults(use_specific_logits_processor=False)
+
+    optional_inputs.add_argument(
+        "--collect_cross_qk",
+        required=False,
+        action="store_true",
+        help="Beam search model collect stacked cross QK.",
+    )
+    optional_inputs.set_defaults(collect_cross_qk=False)
+
+    optional_inputs.add_argument(
+        "--extra_decoding_ids",
+        required=False,
+        action="store_true",
+        help="Need extra starting decoding ids for some feature like cross qk. Default if false.",
+    )
+    optional_inputs.set_defaults(extra_decoding_ids=False)
+
+    optional_inputs.add_argument(
+        "-t",
+        "--use_temperature",
+        required=False,
+        action="store_true",
+        help="Use temperature as an extra graph input for the WhisperBeamSearch op",
+    )
+    optional_inputs.set_defaults(use_temperature=False)
+
+    optional_inputs.add_argument(
+        "--no_repeat_ngram_size",
+        type=int,
+        default=0,
+        help="default to 0",
+    )
+
+    #############################################################
+    # Optional outputs for Whisper
+    # (listed below in the order that WhisperBeamSearch expects)
+    #############################################################
+
+    optional_outputs.add_argument(
+        "--output_sequence_scores",
+        required=False,
+        action="store_true",
+        help="Beam search model output scores for each generated sequence.",
+    )
+    optional_outputs.set_defaults(output_sequence_scores=False)
+
+    optional_outputs.add_argument(
+        "--output_scores",
+        required=False,
+        action="store_true",
+        help="Beam search model output scores over vocab per generated token.",
+    )
+    optional_outputs.set_defaults(output_scores=False)
+
+    optional_outputs.add_argument(
+        "--output_cross_qk",
+        required=False,
+        action="store_true",
+        help="Beam search model output collected qk as output. Also hint collect_cross_qk",
+    )
+    optional_outputs.set_defaults(output_cross_qk=False)
+
+    optional_outputs.add_argument(
+        "--cross_qk_onnx_model",
+        required=False,
+        type=str,
+        default=None,
+        help="The model which consumes cross_qk outputs.",
+    )
+
+    optional_outputs.add_argument(
+        "--output_no_speech_probs",
+        required=False,
+        action="store_true",
+        help="Beam search model output no speech probs which is computed from the encoder/context-decoder graph.",
+    )
+    optional_outputs.set_defaults(output_no_speech_probs=False)
+
+    ###################################
+    # Quantization options for Whisper
+    ###################################
+
+    quant_args.add_argument(
+        "--accuracy_level",
+        default=0,
+        required=False,
+        type=int,
+        help="Accuracy level of the 4-bit quantized MatMul computation.",
+    )
+
+    quant_args.add_argument(
+        "--quantize_symmetric",
+        required=False,
+        action="store_true",
+        help="Quantize weights symmetrically",
+    )
+    quant_args.set_defaults(quantize_symmetric=False)
+
+    args = parser.parse_args(argv)
+
+    # Collect cross QKs if either flag is enabled
+    args.collect_cross_qk = args.collect_cross_qk or args.output_cross_qk
+
+    # FP32 CPU can be supported here once the DMMHA CPU kernel bugs are fixed
+    args.use_decoder_masked_mha = args.use_decoder_masked_mha and args.provider == "cuda"
+
+    return args
+
+
+# quant_method is reserved for mixed precision in future
+def make_quant_algo_config(precision, quant_method: str, matmul_nodes=None):
+    customized_weight_config = {}
+    quant_algo_config = None
+
+    # need to use k_quant for int8
+    if precision == Precision.INT8:
+        for node_name in matmul_nodes:
+            customized_weight_config[node_name] = {"bits": 8}
+        quant_algo_config = KQuantWeightOnlyQuantConfig(customized_weight_config=customized_weight_config)
+    else:
+        quant_algo_config = KQuantWeightOnlyQuantConfig(customized_weight_config=customized_weight_config)
+
+    return quant_algo_config
+
+
+def export_onnx_models(
+    model_name_or_path,
+    model_impl,
+    cache_dir,
+    output_dir,
+    use_gpu,
+    use_external_data_format,
+    optimize_onnx,
+    precision,
+    verbose,
+    use_forced_decoder_ids: bool = False,
+    merge_encoder_and_decoder_init: bool = True,
+    no_beam_search_op: bool = False,
+    use_decoder_masked_mha: bool = False,
+    output_qk: bool = False,
+    overwrite: bool = False,
+    use_int32_inputs: bool = True,
+    accuracy_level: int = 0,
+    quantize_symmetric: bool = False,
+    provider: str = "cpu",
+):
+    device = torch.device("cuda" if use_gpu else "cpu")
+    if not use_gpu:
+        accuracy_level = 4  # change to 4 for CPU EP
+    use_fp16_inputs = precision == Precision.FLOAT16 or (precision in (Precision.INT8, Precision.INT4) and use_gpu)
+
+    models = WhisperHelper.load_model(
+        model_name_or_path,
+        model_impl,
+        cache_dir,
+        device,
+        torch.float16 if use_fp16_inputs else torch.float32,
+        merge_encoder_and_decoder_init,
+        no_beam_search_op,
+        output_qk,
+    )
+    config = models["decoder"].config
+
+    if (not use_external_data_format) and (config.num_hidden_layers > 24):
+        logger.warning("You MUST pass `--use_external_data_format` because model size > 2GB")
+        raise Exception("Please pass `--use_external_data_format` for this model.")
+
+    output_paths = []
+    for name, model in models.items():
+        print(f"========> Handling {name} model......")
+        filename_suffix = "_" + name
+
+        onnx_path = WhisperHelper.get_onnx_path(
+            output_dir,
+            model_name_or_path,
+            suffix=filename_suffix,
+            new_folder=False,
+        )
+
+        # Export to ONNX
+        if overwrite or not os.path.exists(onnx_path):
+            logger.info(f"Exporting ONNX model to {onnx_path}")
+            WhisperHelper.export_onnx(
+                model,
+                onnx_path,
+                PROVIDERS[provider],
+                verbose,
+                use_external_data_format,
+                use_fp16_inputs=use_fp16_inputs,
+                use_int32_inputs=use_int32_inputs,
+                use_encoder_hidden_states=(name == "decoder_init"),
+                use_kv_cache_inputs=(name == "decoder"),
+            )
+        else:
+            logger.info(f"Skip exporting: existing ONNX model {onnx_path}")
+
+        # Optimize ONNX model
+        if optimize_onnx or precision != Precision.FLOAT32:
+            output_path = WhisperHelper.get_onnx_path(
+                output_dir,
+                model_name_or_path,
+                suffix=filename_suffix + "_" + str(precision),
+                new_folder=False,
+            )
+
+            if overwrite or not os.path.exists(output_path):
+                if optimize_onnx:
+                    logger.info(f"Optimizing model to {output_path}")
+                    WhisperHelper.optimize_onnx(
+                        onnx_path,
+                        output_path,
+                        precision == Precision.FLOAT16,
+                        model.config.encoder_attention_heads,
+                        model.config.d_model,
+                        model.config.decoder_layers,
+                        use_external_data_format,
+                        use_gpu=use_gpu,
+                        provider=provider,
+                        is_decoder=(name == "decoder"),
+                        no_beam_search_op=no_beam_search_op,
+                        use_decoder_masked_mha=use_decoder_masked_mha,
+                        output_qk=output_qk,
+                    )
+                    # Remove old ONNX model and old data file
+                    if os.path.exists(onnx_path):
+                        os.remove(onnx_path)
+                    if os.path.exists(onnx_path + ".data"):
+                        os.remove(onnx_path + ".data")
+                    onnx_path = output_path
+
+                    if isinstance(model, WhisperEncoder):
+                        model.verify_onnx(
+                            onnx_path,
+                            PROVIDERS[provider],
+                            use_fp16_inputs=use_fp16_inputs,
+                        )
+                    else:
+                        model.verify_onnx(
+                            onnx_path,
+                            PROVIDERS[provider],
+                            use_fp16_inputs=use_fp16_inputs,
+                            use_int32_inputs=use_int32_inputs,
+                        )
+
+                if precision in (Precision.INT8, Precision.INT4):
+                    onnx_model = onnx.load(onnx_path, load_external_data=True)
+                    matmul_nodes = [node.name for node in onnx_model.graph.node if node.op_type == "MatMul"]
+                    quant_algo_config = make_quant_algo_config(precision, "k_quant", matmul_nodes)
+
+                    quant = MatMulNBitsQuantizer(
+                        model=onnx_model,
+                        block_size=32,
+                        is_symmetric=quantize_symmetric,
+                        accuracy_level=accuracy_level,
+                        quant_format=QuantFormat.QOperator,
+                        op_types_to_quantize=("MatMul",),
+                        algo_config=quant_algo_config,
+                    )
+                    quant.process()
+                    if os.path.exists(output_path):
+                        os.remove(output_path)
+                    if os.path.exists(output_path + ".data"):
+                        os.remove(output_path + ".data")
+                    onnx.save_model(
+                        quant.model.model,
+                        output_path,
+                        save_as_external_data=True,
+                        all_tensors_to_one_file=True,
+                        location=os.path.basename(output_path) + ".data",
+                        size_threshold=0,
+                        convert_attribute=False,
+                    )
+            else:
+                logger.info(f"Skip optimizing: existing ONNX model {onnx_path}")
+        else:
+            output_path = onnx_path
+
+        output_paths.append(output_path)
+
+    return output_paths
+
+
+def main(argv=None):
+    warnings.warn(
+        "This example is deprecated. Use the Olive recipe instead: "
+        "https://github.com/microsoft/olive-recipes/tree/main",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+    args = parse_arguments(argv)
+
+    setup_logger(args.verbose)
+
+    logger.info(f"Arguments:{args}")
+
+    cache_dir = args.cache_dir
+    output_dir = args.output if not args.output.endswith(".onnx") else os.path.dirname(args.output)
+    prepare_environment(cache_dir, output_dir, args.use_gpu)
+
+    if args.precision == Precision.FLOAT16:
+        assert args.use_gpu, "fp16 requires --use_gpu"
+
+    output_paths = export_onnx_models(
+        args.model_name_or_path,
+        args.model_impl,
+        cache_dir,
+        output_dir,
+        args.use_gpu,
+        args.use_external_data_format,
+        args.optimize_onnx,
+        args.precision,
+        args.verbose,
+        args.use_forced_decoder_ids,
+        not args.separate_encoder_and_decoder_init,
+        args.no_beam_search_op,
+        args.use_decoder_masked_mha,
+        args.output_cross_qk,
+        args.overwrite,
+        not args.use_int64_inputs,
+        args.accuracy_level,
+        args.quantize_symmetric,
+        args.provider,
+    )
+
+    max_diff = 0
+    if not args.no_beam_search_op:
+        logger.info("Chaining model ... :")
+        args.beam_model_output_dir = WhisperHelper.get_onnx_path(
+            output_dir,
+            args.model_name_or_path,
+            suffix="_beamsearch",
+            new_folder=False,
+        )
+        for path in output_paths:
+            if "encoder_decoder" in path or "encoder" in path:
+                args.encoder_path = path
+            elif "decoder" in path:
+                args.decoder_path = path
+        chain_model(args)
+        output_paths.append(args.beam_model_output_dir)
+
+        # Check chained model
+        ort_session = create_onnxruntime_session(
+            args.beam_model_output_dir,
+            use_gpu=args.use_gpu,
+            provider=args.provider,
+        )
+        device = torch.device("cuda" if args.use_gpu else "cpu")
+
+        # Wrap parity check in try-except to allow export to continue in case this produces an error
+        try:
+            with torch.no_grad():
+                # Verify batched decoding with prompts for OpenAI implementation
+                if args.model_impl == "openai" and args.use_forced_decoder_ids:
+                    max_diff = WhisperHelper.verify_onnx(
+                        args.model_name_or_path, cache_dir, ort_session, device, batch_size=2, prompt_mode=True
+                    )
+                else:
+                    max_diff = WhisperHelper.verify_onnx(args.model_name_or_path, cache_dir, ort_session, device)
+            if max_diff > 1e-4:
+                logger.warning("PyTorch and ONNX Runtime results are NOT close")
+            else:
+                logger.info("PyTorch and ONNX Runtime results are close")
+        except Exception as e:
+            logger.warning(
+                f"An error occurred while trying to verify parity between PyTorch and ONNX Runtime: {e}", exc_info=True
+            )
+
+        # Remove extra ONNX models saved in output directory
+        for _file in os.listdir(output_dir):
+            if "_beamsearch" not in _file and "_jump_times" not in _file:
+                path = os.path.join(output_dir, _file)
+                os.remove(path)
+                if path in output_paths:
+                    output_paths.remove(path)
+
+    else:
+        # Create ancillary JSON files for ONNX Runtime GenAI and/or Hugging Face's Optimum
+        WhisperHelper.save_processing(
+            args.model_name_or_path,
+            args.provider,
+            args.separate_encoder_and_decoder_init,
+            args.use_decoder_masked_mha,
+            args.output_cross_qk,
+            next(iter(filter(lambda path: "encoder" in path, output_paths))),
+            next(iter(filter(lambda path: "decoder" in path, output_paths))),
+            output_dir,
+            cache_dir,
+        )
+
+    logger.info(f"Done! Outputs: {output_paths}")
+    return max_diff
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_chain.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_chain.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ba6d47d36610b7eb4cb6286354816960d84adc2
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_chain.py
@@ -0,0 +1,334 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+
+import onnx
+from benchmark_helper import Precision
+from convert_generation import (
+    get_shared_initializers,
+    update_decoder_subgraph_output_cross_attention,
+    update_decoder_subgraph_share_buffer_and_use_decoder_masked_mha,
+)
+from onnx import TensorProto, helper
+from transformers import WhisperConfig, WhisperTokenizer
+
+logger = logging.getLogger(__name__)
+
+
+def verify_inputs(beam_inputs, graph_inputs):
+    # Verify that ONNX graph's inputs match beam search op's inputs
+    beam_required_inputs = list(filter(lambda beam_input: beam_input, beam_inputs))
+    assert len(graph_inputs) == len(beam_required_inputs)
+    for graph_input, beam_input in zip(graph_inputs, beam_required_inputs, strict=False):
+        # Check if graph_input is in beam_input to handle beam_input names with the "_fp16" suffix
+        assert graph_input.name in beam_input
+
+
+def clean_list(arr, remove_all_strings=True):
+    if remove_all_strings:
+        # Remove all empty strings in list
+        return list(filter(lambda elm: elm != "", arr))
+
+    # Remove empty strings at end of list
+    while len(arr) > 0:
+        if arr[-1] == "":
+            arr.pop()
+        else:
+            break
+    return arr
+
+
+def chain_model(args):
+    # Load encoder/decoder and insert necessary (but unused) graph inputs expected by WhisperBeamSearch op
+    encoder_model = onnx.load_model(args.encoder_path, load_external_data=True)
+    encoder_model.graph.name = "encoderdecoderinit subgraph"
+
+    decoder_model = onnx.load_model(args.decoder_path, load_external_data=True)
+    decoder_model.graph.name = "decoder subgraph"
+
+    config = WhisperConfig.from_pretrained(args.model_name_or_path, cache_dir=args.cache_dir)
+    tokenizer = WhisperTokenizer.from_pretrained(args.model_name_or_path, cache_dir=args.cache_dir)
+
+    use_fp16_inputs = args.precision == Precision.FLOAT16 or (
+        args.precision in (Precision.INT8, Precision.INT4) and args.use_gpu
+    )
+    # Create inputs/outputs for WhisperBeamSearch op
+    temperature_name = "temperature_fp16" if use_fp16_inputs else "temperature"
+    beam_inputs = [
+        "input_features_fp16" if use_fp16_inputs else "input_features",
+        "max_length",
+        "min_length",
+        "num_beams",
+        "num_return_sequences",
+        "length_penalty_fp16" if use_fp16_inputs else "length_penalty",
+        "repetition_penalty_fp16" if use_fp16_inputs else "repetition_penalty",
+        "vocab_mask" if args.use_vocab_mask else "",
+        "prefix_vocab_mask" if args.use_prefix_vocab_mask else "",
+        "",  # attention mask
+        "decoder_input_ids" if args.use_forced_decoder_ids else "",
+        "logits_processor" if args.use_logits_processor else "",
+        "cross_qk_layer_head" if args.collect_cross_qk else "",
+        "extra_decoding_ids" if args.extra_decoding_ids else "",
+        temperature_name if args.use_temperature else "",
+    ]
+
+    sequence_scores_name = "sequence_scores_fp16" if use_fp16_inputs else "sequence_scores"
+    scores_name = "scores_fp16" if use_fp16_inputs else "scores"
+    beam_outputs = [
+        "sequences",
+        sequence_scores_name if args.output_sequence_scores else "",
+        scores_name if args.output_scores else "",
+        "cross_qk" if args.collect_cross_qk else "",
+        "no_speech_probs_beam" if args.output_no_speech_probs else "",
+    ]
+
+    graph_nodes = []
+    if use_fp16_inputs:
+        input_features_cast_node = helper.make_node(
+            "Cast",
+            inputs=["input_features"],
+            outputs=["input_features_fp16"],
+            name="CastInputFeaturesToFp16",
+            to=TensorProto.FLOAT16,
+        )
+        len_pen_cast_node = helper.make_node(
+            "Cast",
+            inputs=["length_penalty"],
+            outputs=["length_penalty_fp16"],
+            name="CastLengthPenaltyToFp16",
+            to=TensorProto.FLOAT16,
+        )
+        rep_pen_cast_node = helper.make_node(
+            "Cast",
+            inputs=["repetition_penalty"],
+            outputs=["repetition_penalty_fp16"],
+            name="CastRepetitionPenaltyToFp16",
+            to=TensorProto.FLOAT16,
+        )
+        graph_nodes.extend([input_features_cast_node, len_pen_cast_node, rep_pen_cast_node])
+
+        if args.use_temperature:
+            temp_cast_node = helper.make_node(
+                "Cast",
+                inputs=["temperature"],
+                outputs=["temperature_fp16"],
+                name="temperature_to_fp16",
+                to=TensorProto.FLOAT16,
+            )
+            graph_nodes.append(temp_cast_node)
+
+        if args.output_sequence_scores:
+            output_sequence_scores_cast_node = helper.make_node(
+                "Cast",
+                inputs=["sequence_scores_fp16"],
+                outputs=["sequence_scores"],
+                name="CastOutputSequenceScoresToFp32",
+                to=TensorProto.FLOAT,
+            )
+            graph_nodes.append(output_sequence_scores_cast_node)
+
+        if args.output_scores:
+            output_scores_cast_node = helper.make_node(
+                "Cast",
+                inputs=["scores_fp16"],
+                outputs=["scores"],
+                name="CastScoresToFp32",
+                to=TensorProto.FLOAT,
+            )
+            graph_nodes.append(output_scores_cast_node)
+
+    # Create WhisperBeamSearch op
+    beam_search_attrs = [
+        helper.make_attribute("eos_token_id", config.eos_token_id),
+        helper.make_attribute("pad_token_id", config.pad_token_id),
+        helper.make_attribute(
+            "decoder_start_token_id", config.decoder_start_token_id
+        ),  # same as tokenizer.convert_tokens_to_ids(['<|startoftranscript|>'])[0]
+        helper.make_attribute("translate_token_id", tokenizer.convert_tokens_to_ids(["<|translate|>"])[0]),
+        helper.make_attribute("transcribe_token_id", tokenizer.convert_tokens_to_ids(["<|transcribe|>"])[0]),
+        helper.make_attribute("start_of_lm_token_id", tokenizer.convert_tokens_to_ids(["<|startoflm|>"])[0]),
+        (
+            helper.make_attribute("no_speech_token_id", tokenizer.convert_tokens_to_ids(["<|nospeech|>"])[0])
+            if args.output_no_speech_probs
+            else ""
+        ),
+        helper.make_attribute("no_timestamps_token_id", tokenizer.convert_tokens_to_ids(["<|notimestamps|>"])[0]),
+        helper.make_attribute("beginning_timestamp_token_id", tokenizer.convert_tokens_to_ids(["<|0.00|>"])[0]),
+        helper.make_attribute("no_repeat_ngram_size", args.no_repeat_ngram_size),
+        helper.make_attribute("early_stopping", True),
+        helper.make_attribute("model_type", 2),
+        helper.make_attribute("decoder_output_cross_qk", 1) if args.collect_cross_qk else "",
+    ]
+    node = helper.make_node(
+        "WhisperBeamSearch",
+        inputs=clean_list(beam_inputs, remove_all_strings=False),
+        outputs=clean_list(beam_outputs, remove_all_strings=False),
+        name="BeamSearch",
+        domain="com.microsoft",
+    )
+    node.attribute.extend(clean_list(beam_search_attrs, remove_all_strings=True))
+
+    # Graph inputs
+    input_features = helper.make_tensor_value_info(
+        "input_features", TensorProto.FLOAT, ["batch_size", "feature_size", "sequence_length"]
+    )
+    max_length = helper.make_tensor_value_info("max_length", TensorProto.INT32, [1])
+    min_length = helper.make_tensor_value_info("min_length", TensorProto.INT32, [1])
+    num_beams = helper.make_tensor_value_info("num_beams", TensorProto.INT32, [1])
+    num_return_sequences = helper.make_tensor_value_info("num_return_sequences", TensorProto.INT32, [1])
+    length_penalty = helper.make_tensor_value_info("length_penalty", TensorProto.FLOAT, [1])
+    repetition_penalty = helper.make_tensor_value_info("repetition_penalty", TensorProto.FLOAT, [1])
+    vocab_mask = helper.make_tensor_value_info("vocab_mask", TensorProto.INT32, [config.vocab_size])
+    prefix_vocab_mask = helper.make_tensor_value_info(
+        "prefix_vocab_mask", TensorProto.INT32, ["batch_size", config.vocab_size]
+    )
+    decoder_input_ids = helper.make_tensor_value_info(
+        "decoder_input_ids", TensorProto.INT32, ["batch_size", "initial_sequence_length"]
+    )
+    logits_processor = helper.make_tensor_value_info("logits_processor", TensorProto.INT32, [1])
+    cross_qk_layer_head = helper.make_tensor_value_info("cross_qk_layer_head", TensorProto.INT32, ["num_layer_head", 2])
+    extra_decoding_ids = helper.make_tensor_value_info(
+        "extra_decoding_ids", TensorProto.INT32, ["batch_size", "extra_decoding_ids_len"]
+    )
+    temperature = helper.make_tensor_value_info("temperature", TensorProto.FLOAT, [1])
+
+    graph_inputs = clean_list(
+        [
+            input_features,
+            max_length,
+            min_length,
+            num_beams,
+            num_return_sequences,
+            length_penalty,
+            repetition_penalty,
+            vocab_mask if args.use_vocab_mask else "",
+            prefix_vocab_mask if args.use_prefix_vocab_mask else "",
+            decoder_input_ids if args.use_forced_decoder_ids else "",
+            logits_processor if args.use_logits_processor else "",
+            cross_qk_layer_head if args.collect_cross_qk else "",
+            extra_decoding_ids if args.extra_decoding_ids else "",
+            temperature if args.use_temperature else "",
+        ]
+    )
+
+    # Graph outputs
+    sequences = helper.make_tensor_value_info(
+        "sequences", TensorProto.INT32, ["batch_size", "num_return_sequences", "max_length"]
+    )
+    sequence_scores = helper.make_tensor_value_info("sequence_scores", TensorProto.FLOAT, ["batch_size"])
+    scores = helper.make_tensor_value_info("scores", TensorProto.FLOAT, ["batch_size"])
+    cross_qk = helper.make_tensor_value_info(
+        "cross_qk",
+        TensorProto.FLOAT,
+        ["batch_size", "num_return_sequences", "num_layer_head_cross_qk", "max_length", "frames"],
+    )
+    no_speech_probs = helper.make_tensor_value_info("no_speech_probs", TensorProto.FLOAT, ["batch_size"])
+
+    graph_outputs = clean_list(
+        [
+            sequences,
+            sequence_scores if args.output_sequence_scores else "",
+            scores if args.output_scores else "",
+            cross_qk if args.output_cross_qk or (not args.cross_qk_onnx_model and args.collect_cross_qk) else "",
+            no_speech_probs if args.output_no_speech_probs else "",
+        ]
+    )
+
+    # Replace MultiHeadAttention with DecoderMaskedMultiHeadAttention for CUDA EP inference
+    if hasattr(args, "use_gpu") and args.use_gpu:
+        if update_decoder_subgraph_share_buffer_and_use_decoder_masked_mha(decoder_model.graph):
+            logger.info("Updated whisper decoder subgraph to use DecoderMaskedMultiHeadAttention successfully!")
+        else:
+            logger.warning("DecoderMaskedMultiHeadAttention could not be applied to whisper decoder subgraph")
+        if hasattr(args, "collect_cross_qk") and args.collect_cross_qk:
+            update_decoder_subgraph_output_cross_attention(decoder_model.graph)
+
+    # Initializers/opsets
+    # Delete shared data between decoder/encoder and move to larger graph initializers
+    initializers = get_shared_initializers(encoder_model, decoder_model)
+    node.attribute.extend(
+        [
+            helper.make_attribute("decoder", decoder_model.graph),
+            helper.make_attribute("encoder", encoder_model.graph),
+        ]
+    )
+
+    opset_import = [helper.make_opsetid(domain="com.microsoft", version=1), helper.make_opsetid(domain="", version=17)]
+
+    graph_nodes.append(node)
+    if args.output_no_speech_probs:
+        prob_cast_node = helper.make_node(
+            "Cast",
+            inputs=["no_speech_probs_beam"],
+            outputs=["no_speech_probs"],
+            name="no_speech_probs_cast_to_fp32",
+            to=TensorProto.FLOAT,
+        )
+        graph_nodes.append(prob_cast_node)
+
+    # Make graph with WhisperBeamSearch op
+    beam_graph = helper.make_graph(
+        graph_nodes,
+        name="WhisperBeamSearch Graph",
+        inputs=graph_inputs,
+        outputs=graph_outputs,
+        initializer=initializers,
+    )
+    beam_graph_input_names = [gi.name for gi in graph_inputs]
+    beam_graph_output_names = [go.name for go in graph_outputs]
+
+    if args.cross_qk_onnx_model:
+        post_qk_model = onnx.load_model(args.cross_qk_onnx_model, load_external_data=True)
+        post_qk_graph = post_qk_model.graph
+        beam_graph.initializer.extend(post_qk_graph.initializer)
+        beam_graph.node.extend(post_qk_graph.node)
+        # If tensor from cross_qk_onnx_model has same name as tensor in beamsearch graph, treat them as same tensor.
+        # User should notice this rule when provide cross_qk_onnx_model to append to the beamsearch node.
+        for pgi in post_qk_graph.input:
+            if (
+                (pgi.name not in beam_graph_input_names)
+                and (pgi.name not in beam_graph_output_names)
+                and (pgi.name != "cross_qk")
+            ):
+                beam_graph.input.extend([pgi])
+        beam_graph.output.extend(post_qk_graph.output)
+
+    # Verify graph's inputs match beam search's inputs
+    verify_inputs(beam_inputs, graph_inputs)
+
+    assert decoder_model.ir_version == encoder_model.ir_version
+    logger.info(f"Using IR version {decoder_model.ir_version} for chained model")
+
+    # Set IR version of chained model to IR version of subgraphs in order to generate a working E2E model
+    beam_model = helper.make_model_gen_version(
+        beam_graph,
+        producer_name="onnxruntime.transformers",
+        opset_imports=opset_import,
+        ir_version=decoder_model.ir_version,
+    )
+
+    # Save WhisperBeamSearch graph and external data
+    if os.path.isfile(args.beam_model_output_dir):
+        logger.info(f"Overwriting {args.beam_model_output_dir} and {args.beam_model_output_dir + '.data'}")
+        if os.path.exists(args.beam_model_output_dir):
+            os.remove(args.beam_model_output_dir)
+        if os.path.exists(args.beam_model_output_dir + ".data"):
+            os.remove(args.beam_model_output_dir + ".data")
+
+    onnx.save(
+        beam_model,
+        args.beam_model_output_dir,
+        save_as_external_data=args.use_external_data_format,
+        all_tensors_to_one_file=True,
+        convert_attribute=True,
+        location=f"{os.path.basename(args.beam_model_output_dir)}.data",
+    )
+    try:
+        onnx.checker.check_model(args.beam_model_output_dir, full_check=True)
+    except Exception as e:
+        logger.error(f"An error occurred while running the ONNX checker: {e}", exc_info=True)  # noqa: G201
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_decoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_decoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..98f9f8e61139c3195826ebd852ec0c7868a5b19e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_decoder.py
@@ -0,0 +1,465 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import tempfile
+from itertools import chain
+from pathlib import Path
+
+import numpy as np
+import onnx
+import torch
+from float16 import convert_float_to_float16
+from google.protobuf.internal.containers import RepeatedCompositeFieldContainer
+from onnx import ModelProto, ValueInfoProto
+from onnx_model import OnnxModel
+from past_helper import PastKeyValuesHelper
+from transformers import WhisperConfig
+from whisper_inputs import (
+    convert_inputs_for_ort,
+    get_model_dynamic_axes,
+    get_sample_decoder_inputs,
+    group_past_key_values,
+)
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+class WhisperDecoder(torch.nn.Module):
+    """A Whisper decoder with optional past key values"""
+
+    def __init__(self, config: WhisperConfig, model: torch.nn.Module, model_impl: str, no_beam_search_op: bool = False):
+        super().__init__()
+        self.config = config
+        self.device = model.device
+        self.model_impl = model_impl
+        self.no_beam_search_op = no_beam_search_op
+
+        self.decoder = None if model_impl == "openai" else model.model.decoder
+        self.proj_out = None if model_impl == "openai" else model.proj_out
+        self.model = model if model_impl == "openai" else None
+
+        self.max_source_positions = self.config.max_source_positions
+        self.num_heads = self.config.decoder_attention_heads
+        self.head_size = self.config.d_model // self.num_heads
+
+    def hf_forward(
+        self,
+        decoder_input_ids: torch.Tensor,
+        encoder_hidden_states: torch.Tensor | None = None,
+        past_key_values: list[tuple[torch.Tensor]] | None = None,
+    ):
+        outputs = self.decoder(
+            encoder_hidden_states=encoder_hidden_states,
+            input_ids=decoder_input_ids,
+            past_key_values=past_key_values,
+            use_cache=True,
+        )
+        logits = self.proj_out(outputs.last_hidden_state)
+        present_key_values = outputs.past_key_values
+
+        if past_key_values is None:
+            # Return present_self_* and present_cross_* for decoder-init
+            return logits, present_key_values
+
+        # Before: (past_key_self_0, past_value_self_0, past_key_cross_0, past_value_cross_0),
+        #         (past_key_self_1, past_value_self_1, past_key_cross_1, past_value_cross_1),
+        # After:  (past_key_self_0, past_value_self_0, past_key_self_1, past_value_self_1), ...,
+        #         (past_key_cross_0, past_value_cross_0, past_key_cross_1, past_value_cross_1), ...
+        present_self, present_cross = PastKeyValuesHelper.group_by_self_and_cross(present_key_values)
+
+        # Return present_self_* for decoder-with-past since past_cross_* and present_cross_* are identical
+        return logits, present_self
+
+    def oai_forward(
+        self,
+        decoder_input_ids: torch.Tensor,
+        encoder_hidden_states: torch.Tensor | None = None,
+        past_key_values: list[tuple[torch.Tensor]] | None = None,
+    ):
+        past_kv_cache = {}
+        if past_key_values is not None:
+            # Convert past KV caches (BxNxSxH --> BxSxNxH --> BxSxD) for OpenAI's forward pass
+            self_attn_kv_caches, cross_attn_kv_caches = group_past_key_values(past_key_values)
+            self_attn_kv_caches = [past_kv.transpose(1, 2) for past_kv in self_attn_kv_caches]
+            self_attn_kv_caches = [past_kv.reshape((*past_kv.shape[:2], -1)) for past_kv in self_attn_kv_caches]
+            cross_attn_kv_caches = [past_kv.transpose(1, 2) for past_kv in cross_attn_kv_caches]
+            cross_attn_kv_caches = [past_kv.reshape((*past_kv.shape[:2], -1)) for past_kv in cross_attn_kv_caches]
+
+            for idx, block in enumerate(self.model.decoder.blocks):
+                past_kv_cache[block.attn.key] = self_attn_kv_caches[2 * idx]
+                past_kv_cache[block.attn.value] = self_attn_kv_caches[2 * idx + 1]
+                past_kv_cache[block.cross_attn.key] = cross_attn_kv_caches[2 * idx]
+                past_kv_cache[block.cross_attn.value] = cross_attn_kv_caches[2 * idx + 1]
+
+        # Install OpenAI's hooks on the forward pass of each nn.Linear for key and value
+        # since the hooks will capture the output of the key and value MatMuls, which
+        # represent the current keys and values.
+        #
+        # For OpenAI's forward pass, the hook function will also perform the concat
+        # operation (past_kv + curr_kv --> pres_kv) if needed. However, the ONNX model
+        # will not contain this concat operation because the present KV caches aren't
+        # returned by OpenAI's forward pass.
+        kv_cache, hooks = self.model.install_kv_cache_hooks()
+
+        # Run forward pass
+        # NOTE: There is a bug with openai-whisper==20240930 with the introduction of SDPA.
+        # In the Whisper codebase, the following line
+        #
+        # is_causal = mask is not None and n_ctx > 1
+        #
+        # has been added where `mask` is a torch tensor. The right-hand side evaluates to `tensor(True/False)`
+        # but `is_causal` only accepts the boolean value. The fix is to apply `.item()` after the right-hand
+        # side has been evaluated. In other words, the line should be
+        #
+        # is_causal = (mask is not None and n_ctx > 1).item()
+        #
+        # instead.
+        logits = self.model.decoder(x=decoder_input_ids, xa=encoder_hidden_states, kv_cache=past_kv_cache)
+
+        # Re-do concat operation on self attention KV caches for ONNX export (if past self attention KV caches exist)
+        if past_key_values is not None:
+            for block in self.model.decoder.blocks:
+                kv_cache[block.attn.key] = torch.cat(
+                    [past_kv_cache[block.attn.key], kv_cache[block.attn.key]], dim=1
+                ).detach()
+                kv_cache[block.attn.value] = torch.cat(
+                    [past_kv_cache[block.attn.value], kv_cache[block.attn.value]], dim=1
+                ).detach()
+
+        present_self, present_cross = [], []
+        for block in self.model.decoder.blocks:
+            # Group self and cross values
+            present_self.append(kv_cache[block.attn.key])
+            present_self.append(kv_cache[block.attn.value])
+            if past_key_values is None:
+                # Return present_self_* and present_cross_* for decoder-init
+                present_cross.append(kv_cache[block.cross_attn.key])
+                present_cross.append(kv_cache[block.cross_attn.value])
+
+        # Convert present KV caches (BxSxD --> BxSxNxH --> BxNxSxH) after OpenAI's forward pass
+        present_self = [
+            present_kv.reshape((*present_kv.shape[:2], -1, self.head_size)).transpose(1, 2)
+            for present_kv in present_self
+        ]
+        present_cross = [
+            present_kv.reshape((*present_kv.shape[:2], -1, self.head_size)).transpose(1, 2)
+            for present_kv in present_cross
+        ]
+
+        # Remove OpenAI's hooks since they can persist after this function completes
+        for hook in hooks:
+            hook.remove()
+
+        if past_key_values is None:
+            # Return present_self_* and present_cross_* for decoder-init
+            present_key_values = PastKeyValuesHelper.group_by_layer(
+                present_self + present_cross, len(present_self) // 2
+            )
+            return logits, present_key_values
+
+        # Return present_self_* for decoder-with-past since past_cross_* and present_cross_* are identical
+        return logits, present_self
+
+    def forward(
+        self,
+        decoder_input_ids: torch.Tensor,
+        encoder_hidden_states: torch.Tensor | None = None,
+        past_key_values: list[tuple[torch.Tensor]] | None = None,
+    ):
+        if self.model_impl == "openai":
+            return self.oai_forward(decoder_input_ids, encoder_hidden_states, past_key_values)
+        return self.hf_forward(decoder_input_ids, encoder_hidden_states, past_key_values)
+
+    def input_names(self):
+        if self.first_pass:
+            input_names = ["input_ids", "encoder_hidden_states"]
+        else:
+            input_names = [
+                "input_ids",
+                "encoder_hidden_states",
+                *list(
+                    chain.from_iterable(
+                        (f"past_key_self_{i}", f"past_value_self_{i}", f"past_key_cross_{i}", f"past_value_cross_{i}")
+                        for i in range(self.config.decoder_layers)
+                    )
+                ),
+            ]
+        return input_names
+
+    def output_names(self):
+        if self.first_pass:
+            output_names = [
+                "logits",
+                *list(
+                    chain.from_iterable(
+                        (
+                            f"present_key_self_{i}",
+                            f"present_value_self_{i}",
+                            f"present_key_cross_{i}",
+                            f"present_value_cross_{i}",
+                        )
+                        for i in range(self.config.decoder_layers)
+                    )
+                ),
+            ]
+        else:
+            output_names = [
+                "logits",
+                *list(
+                    chain.from_iterable(
+                        (f"present_key_self_{i}", f"present_value_self_{i}") for i in range(self.config.decoder_layers)
+                    )
+                ),
+            ]
+        return output_names
+
+    def dynamic_axes(self, input_names, output_names):
+        dynamic_axes = get_model_dynamic_axes(self.config, input_names, output_names)
+        if "input_ids" in dynamic_axes and not self.no_beam_search_op:
+            # Set dynamic axes for `input_ids` when using beam search op to {0: "batch_size"} only
+            del dynamic_axes["input_ids"][1]
+        return dynamic_axes
+
+    def inputs(self, use_fp16_inputs: bool, use_int32_inputs: bool, return_dict: bool = False):
+        inputs = get_sample_decoder_inputs(
+            self.config,
+            self.device,
+            batch_size=2,
+            past_sequence_length=(0 if self.first_pass else 6),
+            sequence_length=(6 if self.first_pass else 1),
+            use_fp16=use_fp16_inputs,
+            use_int32=use_int32_inputs,
+        )
+        if return_dict:
+            if self.first_pass:
+                del inputs["past_key_values"]
+            return inputs
+
+        if self.first_pass:
+            return (
+                inputs["decoder_input_ids"],
+                inputs["encoder_hidden_states"],
+            )
+        return (
+            inputs["decoder_input_ids"],
+            inputs["encoder_hidden_states"],
+            inputs["past_key_values"],
+        )
+
+    def fix_key_value_cache_dims(self, io: ValueInfoProto, is_cross: bool = False, is_output: bool = False):
+        # Shape should be (batch_size, num_heads, sequence_length, head_size) for self attention KV caches
+        # and (batch_size, num_heads, num_frames // 2, head_size) for cross attention KV caches
+        num_heads = io.type.tensor_type.shape.dim[1]
+        if "_dim_" in num_heads.dim_param:
+            num_heads.Clear()
+            num_heads.dim_value = self.num_heads
+        sequence_length = io.type.tensor_type.shape.dim[2]
+        if "_dim_" in sequence_length.dim_param:
+            sequence_length.Clear()
+            if is_cross:
+                sequence_length.dim_value = self.max_source_positions
+            else:
+                sequence_length.dim_param = "total_sequence_length" if is_output else "past_sequence_length"
+        head_size = io.type.tensor_type.shape.dim[3]
+        if "_dim_" in head_size.dim_param:
+            head_size.Clear()
+            head_size.dim_value = self.head_size
+        return io
+
+    def fix_io(self, io_list: RepeatedCompositeFieldContainer, is_output: bool = False):
+        # Fix order of inputs/outputs and each dim_value of input/output
+        reordered_io = []
+        self_attn_kv_caches = []
+        cross_attn_kv_caches = []
+
+        for io in io_list:
+            if "past" not in io.name and "present" not in io.name:
+                reordered_io.append(io)
+            elif "self" in io.name:
+                # Self attention KV caches
+                new_io = self.fix_key_value_cache_dims(io, is_cross=False, is_output=is_output)
+                if self.no_beam_search_op:
+                    reordered_io.append(new_io)
+                else:
+                    self_attn_kv_caches.append(new_io)
+            else:
+                # Cross attention KV caches
+                new_io = self.fix_key_value_cache_dims(io, is_cross=True, is_output=is_output)
+                if self.no_beam_search_op:
+                    reordered_io.append(new_io)
+                else:
+                    cross_attn_kv_caches.append(new_io)
+
+        if not self.no_beam_search_op:
+            reordered_io += self_attn_kv_caches + cross_attn_kv_caches
+        return reordered_io
+
+    def fix_inputs_and_outputs(self, model: ModelProto):
+        # ONNX exporter might mark dimensions like 'Transposepresent_value_self_1_dim_2' in shape inference.
+        # We now change the dim_values to the correct one.
+        reordered_inputs = self.fix_io(model.graph.input, is_output=False)
+        while len(model.graph.input) > 0:
+            model.graph.input.pop()
+        model.graph.input.extend(reordered_inputs)
+
+        reordered_outputs = self.fix_io(model.graph.output, is_output=True)
+        while len(model.graph.output) > 0:
+            model.graph.output.pop()
+        model.graph.output.extend(reordered_outputs)
+        return model
+
+    def fix_layernorm_weights(self, model: ModelProto, use_fp16_inputs: bool):
+        if self.model_impl == "openai" and use_fp16_inputs:
+            # Cast ONNX model to float16 to ensure LayerNorm weights are converted from
+            # float32 to float16 since exported model already has float16 weights everywhere
+            # except for LayerNorm ops. This happens because OpenAI always upcasts to float32
+            # when computing LayerNorm.
+            #
+            # Reference:
+            # https://github.com/openai/whisper/blob/90db0de1896c23cbfaf0c58bc2d30665f709f170/whisper/model.py#L41
+            model = convert_float_to_float16(model)
+        return model
+
+    def export_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_fp16_inputs: bool = False,
+        use_int32_inputs: bool = True,
+        use_encoder_hidden_states: bool = False,
+        use_kv_cache_inputs: bool = True,
+    ):
+        """Export decoder to ONNX
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): provider to use for verifying parity on ONNX model
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_fp16_inputs (bool, optional): use float16 inputs for the KV caches. Defaults to False.
+            use_int32_inputs (bool, optional): use int32 inputs for the decoder_input_ids. Defaults to True.
+            use_encoder_hidden_states (bool, optional): use encoder_hidden_states as model input for decoder-init/decoder-without-past models. Defaults to False.
+            use_kv_cache_inputs (bool, optional): use KV caches as model inputs for decoder-with-past models. Defaults to True.
+        """
+        # Shape of decoder's tensors:
+        # Required Inputs:
+        #    decoder_input_ids: (batch_size, sequence_length)
+        # Optional Inputs:
+        #    encoder_hidden_states (comes from encoder's outputs): (batch_size, num_frames // 2, hidden_size)
+        #    past_{key/value}_self_* (past self attention KV caches): (batch_size, num_heads, past_sequence_length, head_size)
+        #    past_{key/value}_cross_* (past cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+        # Outputs:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    present_{key/value}_self_* (present self attention KV caches): (batch_size, num_heads, past_sequence_length + sequence_length, head_size)
+        #    present_{key/value}_cross_* (present cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+
+        # For the first pass through the decoder (i.e. decoder-init/decoder-without-past)
+        self.first_pass = use_encoder_hidden_states and not use_kv_cache_inputs
+
+        # For subsequent passes through the decoder (i.e. decoder-with-past)
+        self.later_pass = not use_encoder_hidden_states and use_kv_cache_inputs
+
+        assert self.first_pass or self.later_pass, (
+            "Only one of `use_encoder_hidden_states` and `use_kv_cache_inputs` can be true at once."
+        )
+
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs)
+        input_names = self.input_names()
+        output_names = self.output_names()
+        dynamic_axes = self.dynamic_axes(input_names, output_names)
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "decoder.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            out_path = temp_onnx_model_path if use_external_data_format else onnx_model_path
+
+            torch.onnx.export(
+                self,
+                args=inputs,
+                f=out_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=18,
+                do_constant_folding=True,
+                dynamo=False,
+                verbose=verbose,
+            )
+
+            model = onnx.load_model(out_path, load_external_data=use_external_data_format)
+            model = self.fix_inputs_and_outputs(model)
+            model = self.fix_layernorm_weights(model, use_fp16_inputs)
+            OnnxModel.save(
+                model,
+                onnx_model_path,
+                save_as_external_data=use_external_data_format,
+                all_tensors_to_one_file=True,
+            )
+
+        self.verify_onnx(onnx_model_path, provider, use_fp16_inputs, use_int32_inputs)
+
+    def verify_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        use_fp16_inputs: bool,
+        use_int32_inputs: bool,
+    ):
+        """Verify ONNX model outputs and PyTorch model outputs match
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): execution provider for ONNX model
+            use_fp16_inputs (bool, optional): use float16 inputs for the KV caches
+            use_int32_inputs (bool, optional): use int32 inputs for the decoder_input_ids
+        """
+        # Shape of decoder's tensors:
+        # Required Inputs:
+        #    decoder_input_ids: (batch_size, sequence_length)
+        # Optional Inputs:
+        #    encoder_hidden_states (comes from encoder's outputs): (batch_size, num_frames // 2, hidden_size)
+        #    past_{key/value}_self_* (past self attention KV caches): (batch_size, num_heads, past_sequence_length, head_size)
+        #    past_{key/value}_cross_* (past cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+        # Outputs:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    present_{key/value}_self_* (present self attention KV caches): (batch_size, num_heads, past_sequence_length + sequence_length, head_size)
+        #    present_{key/value}_cross_* (present cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+
+        # Run PyTorch model
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs, return_dict=True)
+        pt_outputs = []
+        if self.first_pass:
+            out = self.forward(**inputs)
+            pt_outputs.append(out[0].detach().cpu().numpy())
+            for present_key_value_layer in out[1]:
+                for present_key_value in present_key_value_layer:
+                    pt_outputs.append(present_key_value.detach().cpu().numpy())
+        else:
+            out = self.forward(**inputs)
+            pt_outputs.append(out[0].detach().cpu().numpy())
+            for present_self_key_value in out[1]:
+                pt_outputs.append(present_self_key_value.detach().cpu().numpy())
+
+        # Run ONNX model
+        sess = InferenceSession(onnx_model_path, providers=[provider])
+        ort_outputs = sess.run(None, convert_inputs_for_ort(inputs, sess))
+
+        # Calculate output difference
+        try:
+            for i, output_name in enumerate(self.output_names()):
+                diff = np.abs(pt_outputs[i] - ort_outputs[i])
+                logger.warning(f"Comparing {output_name}...")
+                logger.warning(f"Max diff: {np.max(diff)}")
+        except:  # noqa: E722
+            pass
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder.py
new file mode 100644
index 0000000000000000000000000000000000000000..e234715467e79de73b40a16593cbfb6840008df1
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder.py
@@ -0,0 +1,165 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import tempfile
+from pathlib import Path
+
+import numpy as np
+import onnx
+import torch
+from float16 import convert_float_to_float16
+from onnx import ModelProto
+from onnx_model import OnnxModel
+from transformers import WhisperConfig
+from whisper_inputs import get_model_dynamic_axes, get_sample_encoder_inputs
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+class WhisperEncoder(torch.nn.Module):
+    """Whisper encoder component"""
+
+    def __init__(self, config: WhisperConfig, model: torch.nn.Module, model_impl: str):
+        super().__init__()
+        self.config = config
+        self.device = model.device
+        self.model_impl = model_impl
+
+        self.encoder = model.encoder if model_impl == "openai" else model.model.encoder
+
+    def forward(self, audio_features: torch.Tensor):
+        outputs = self.encoder(audio_features)
+        return outputs if self.model_impl == "openai" else outputs.last_hidden_state
+
+    def input_names(self):
+        input_names = ["audio_features"]
+        return input_names
+
+    def output_names(self):
+        output_names = ["encoder_hidden_states"]
+        return output_names
+
+    def dynamic_axes(self, input_names, output_names):
+        dynamic_axes = get_model_dynamic_axes(self.config, input_names, output_names)
+        return dynamic_axes
+
+    def fix_layernorm_weights(self, model: ModelProto, use_fp16_inputs: bool):
+        if self.model_impl == "openai" and use_fp16_inputs:
+            # Cast ONNX model to float16 to ensure LayerNorm weights are converted from
+            # float32 to float16 since exported model already has float16 weights everywhere
+            # except for LayerNorm ops. This happens because OpenAI always upcasts to float32
+            # when computing LayerNorm.
+            #
+            # Reference:
+            # https://github.com/openai/whisper/blob/90db0de1896c23cbfaf0c58bc2d30665f709f170/whisper/model.py#L41
+            model = convert_float_to_float16(model)
+        return model
+
+    def export_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_fp16_inputs: bool = False,
+    ):
+        """Export encoder to ONNX
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): provider to use for verifying parity on ONNX model
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_fp16_inputs (bool, optional): use float16 inputs for the audio_features. Defaults to False.
+        """
+        # Shape of encoder's tensors:
+        # Inputs:
+        #    audio_features: (batch_size, num_mels, num_frames)
+        # Outputs:
+        #    encoder_hidden_states: (batch_size, num_frames // 2, hidden_size)
+
+        inputs = get_sample_encoder_inputs(
+            self.config,
+            self.device,
+            batch_size=2,
+            use_fp16=use_fp16_inputs,
+        )
+
+        input_names = self.input_names()
+        output_names = self.output_names()
+        dynamic_axes = self.dynamic_axes(input_names, output_names)
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "encoder.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            out_path = temp_onnx_model_path if use_external_data_format else onnx_model_path
+
+            torch.onnx.export(
+                self,
+                args=(inputs["audio_features"]),
+                f=out_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=18,
+                do_constant_folding=True,
+                dynamo=False,
+                verbose=verbose,
+            )
+
+            model = onnx.load_model(out_path, load_external_data=use_external_data_format)
+            model = self.fix_layernorm_weights(model, use_fp16_inputs)
+            OnnxModel.save(
+                model,
+                onnx_model_path,
+                save_as_external_data=use_external_data_format,
+                all_tensors_to_one_file=True,
+            )
+
+        self.verify_onnx(onnx_model_path, provider, use_fp16_inputs)
+
+    def verify_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        use_fp16_inputs: bool,
+    ):
+        """Verify ONNX model outputs and PyTorch model outputs match
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): execution provider for ONNX model
+            use_fp16_inputs (bool, optional): use float16 inputs for the audio_features
+        """
+        # Shape of encoder's tensors:
+        # Inputs:
+        #    audio_features: (batch_size, num_mels, num_frames)
+        # Outputs:
+        #    encoder_hidden_states: (batch_size, num_frames // 2, hidden_size)
+        inputs = get_sample_encoder_inputs(
+            self.config,
+            self.device,
+            batch_size=2,
+            use_fp16=use_fp16_inputs,
+        )
+
+        # Run PyTorch model
+        pt_outputs = self.forward(inputs["audio_features"]).detach().cpu().numpy()
+
+        # Run ONNX model
+        sess = InferenceSession(onnx_model_path, providers=[provider])
+        ort_outputs = sess.run(None, {"audio_features": inputs["audio_features"].detach().cpu().numpy()})[0]
+
+        # Calculate output difference
+        diff = np.abs(pt_outputs - ort_outputs)
+        logger.warning("Comparing encoder_hidden_states...")
+        logger.warning(f"Max diff: {np.max(diff)}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder_decoder_init.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder_decoder_init.py
new file mode 100644
index 0000000000000000000000000000000000000000..3dbaa1f7c4c4a543a9a951a1571b8ae0d62b1ce9
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_encoder_decoder_init.py
@@ -0,0 +1,372 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import tempfile
+from itertools import chain
+from pathlib import Path
+
+import numpy as np
+import onnx
+import torch
+from float16 import convert_float_to_float16
+from onnx import ModelProto, ValueInfoProto
+from onnx_model import OnnxModel
+from transformers import WhisperConfig
+from whisper_decoder import WhisperDecoder
+from whisper_encoder import WhisperEncoder
+from whisper_inputs import (
+    convert_inputs_for_ort,
+    get_model_dynamic_axes,
+    get_sample_encoder_decoder_init_inputs,
+    group_past_key_values,
+)
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+class WhisperEncoderDecoderInit(torch.nn.Module):
+    """Whisper encoder component + first pass through Whisper decoder component to initialize KV caches"""
+
+    def __init__(self, config: WhisperConfig, model: torch.nn.Module, model_impl: str, no_beam_search_op: bool = False):
+        super().__init__()
+        self.config = config
+        self.device = model.device
+        self.model_impl = model_impl
+        self.no_beam_search_op = no_beam_search_op
+
+        self.encoder = WhisperEncoder(config, model, model_impl)
+        self.decoder = WhisperDecoder(config, model, model_impl, no_beam_search_op)
+
+        self.max_source_positions = self.config.max_source_positions
+        self.num_heads = self.config.decoder_attention_heads
+        self.head_size = self.config.d_model // self.num_heads
+
+    def hf_forward_for_beam_search_op(self, audio_features: torch.Tensor, decoder_input_ids: torch.Tensor):
+        encoder_hidden_states = self.encoder(audio_features)
+        logits, present_key_values = self.decoder(decoder_input_ids, encoder_hidden_states)
+        return logits, encoder_hidden_states, present_key_values
+
+    def hf_forward_for_no_beam_search_op(self, audio_features: torch.Tensor):
+        encoder_hidden_states = self.encoder(audio_features)
+
+        # Get cross attention KV caches and return them for this model
+        # We do this because these MatMuls are only run once before their outputs are being re-used in the decoder
+        present_cross_attention_key_value_caches = []
+        for layer in self.decoder.decoder.layers:
+            cross_attn_key_cache = (
+                layer.encoder_attn.k_proj(encoder_hidden_states)
+                .view(-1, self.max_source_positions, self.num_heads, self.head_size)
+                .transpose(1, 2)
+            )
+            cross_attn_value_cache = (
+                layer.encoder_attn.v_proj(encoder_hidden_states)
+                .view(-1, self.max_source_positions, self.num_heads, self.head_size)
+                .transpose(1, 2)
+            )
+            present_cross_attention_key_value_caches.append(cross_attn_key_cache)
+            present_cross_attention_key_value_caches.append(cross_attn_value_cache)
+
+        return encoder_hidden_states, present_cross_attention_key_value_caches
+
+    def oai_forward_for_beam_search_op(self, audio_features: torch.Tensor, decoder_input_ids: torch.Tensor):
+        encoder_hidden_states = self.encoder(audio_features)
+        logits, present_key_values = self.decoder(decoder_input_ids, encoder_hidden_states)
+        return logits, encoder_hidden_states, present_key_values
+
+    def oai_forward_for_no_beam_search_op(self, audio_features: torch.Tensor):
+        encoder_hidden_states = self.encoder(audio_features)
+
+        # Get cross attention KV caches and return them for this model
+        # We do this because these MatMuls are only run once before their outputs are being re-used in the decoder
+        present_cross_attention_key_value_caches = []
+        for block in self.decoder.model.decoder.blocks:
+            cross_attn_key_cache = (
+                block.cross_attn.key(encoder_hidden_states)
+                .view(-1, self.max_source_positions, self.num_heads, self.head_size)
+                .transpose(1, 2)
+            )
+            cross_attn_value_cache = (
+                block.cross_attn.value(encoder_hidden_states)
+                .view(-1, self.max_source_positions, self.num_heads, self.head_size)
+                .transpose(1, 2)
+            )
+            present_cross_attention_key_value_caches.append(cross_attn_key_cache)
+            present_cross_attention_key_value_caches.append(cross_attn_value_cache)
+
+        return encoder_hidden_states, present_cross_attention_key_value_caches
+
+    def forward(self, audio_features: torch.Tensor, decoder_input_ids: torch.Tensor | None = None):
+        if self.model_impl == "openai":
+            if self.no_beam_search_op:
+                return self.oai_forward_for_no_beam_search_op(audio_features)
+            return self.oai_forward_for_beam_search_op(audio_features, decoder_input_ids)
+
+        # Hugging Face implementation
+        if self.no_beam_search_op:
+            return self.hf_forward_for_no_beam_search_op(audio_features)
+        return self.hf_forward_for_beam_search_op(audio_features, decoder_input_ids)
+
+    def input_names(self):
+        if self.no_beam_search_op:
+            input_names = ["audio_features"]
+        else:
+            input_names = ["encoder_input_ids", "decoder_input_ids"]
+        return input_names
+
+    def output_names(self):
+        if self.no_beam_search_op:
+            output_names = [
+                "encoder_hidden_states",
+                *list(
+                    chain.from_iterable(
+                        (f"present_key_cross_{i}", f"present_value_cross_{i}")
+                        for i in range(self.config.decoder_layers)
+                    )
+                ),
+            ]
+        else:
+            output_names = [
+                "logits",
+                "encoder_hidden_states",
+                *list(
+                    chain.from_iterable(
+                        (
+                            f"present_key_self_{i}",
+                            f"present_value_self_{i}",
+                            f"present_key_cross_{i}",
+                            f"present_value_cross_{i}",
+                        )
+                        for i in range(self.config.decoder_layers)
+                    )
+                ),
+            ]
+        return output_names
+
+    def dynamic_axes(self, input_names, output_names):
+        dynamic_axes = get_model_dynamic_axes(self.config, input_names, output_names)
+        return dynamic_axes
+
+    def inputs(self, use_fp16_inputs: bool, use_int32_inputs: bool, return_dict: bool = False):
+        inputs = get_sample_encoder_decoder_init_inputs(
+            self.config,
+            self.device,
+            batch_size=2,
+            decoder_sequence_length=6,
+            use_fp16=use_fp16_inputs,
+            use_int32=use_int32_inputs,
+        )
+        if return_dict:
+            if self.no_beam_search_op:
+                del inputs["decoder_input_ids"]
+            return inputs
+
+        if self.no_beam_search_op:
+            return (inputs["audio_features"],)
+        return (
+            inputs["audio_features"],
+            inputs["decoder_input_ids"],
+        )
+
+    def fix_key_value_cache_dims(self, output: ValueInfoProto, is_cross: bool = False):
+        # Shape should be (batch_size, num_heads, sequence_length, head_size) for self attention KV caches
+        # and (batch_size, num_heads, num_frames // 2, head_size) for cross attention KV caches
+        num_heads = output.type.tensor_type.shape.dim[1]
+        if "_dim_" in num_heads.dim_param:
+            num_heads.Clear()
+            num_heads.dim_value = self.num_heads
+        sequence_length = output.type.tensor_type.shape.dim[2]
+        if "_dim_" in sequence_length.dim_param:
+            sequence_length.Clear()
+            if is_cross:
+                sequence_length.dim_value = self.max_source_positions
+            else:
+                sequence_length.dim_param = "total_sequence_length"
+        head_size = output.type.tensor_type.shape.dim[3]
+        if "_dim_" in head_size.dim_param:
+            head_size.Clear()
+            head_size.dim_value = self.head_size
+        return output
+
+    def fix_outputs(self, model: ModelProto):
+        # ONNX exporter might mark dimensions like 'Transposepresent_value_self_1_dim_2' in shape inference.
+        # We now change the dim_values to the correct one.
+        reordered_outputs = []
+        self_attn_kv_caches = []
+        cross_attn_kv_caches = []
+
+        for output in model.graph.output:
+            if "present" not in output.name:
+                reordered_outputs.append(output)
+
+            elif "self" in output.name:
+                # Self attention KV caches
+                new_output = self.fix_key_value_cache_dims(output, is_cross=False)
+                if self.no_beam_search_op:
+                    reordered_outputs.append(new_output)
+                else:
+                    self_attn_kv_caches.append(new_output)
+            else:
+                # Cross attention KV caches
+                new_output = self.fix_key_value_cache_dims(output, is_cross=True)
+                if self.no_beam_search_op:
+                    reordered_outputs.append(new_output)
+                else:
+                    cross_attn_kv_caches.append(new_output)
+
+        if not self.no_beam_search_op:
+            reordered_outputs += self_attn_kv_caches + cross_attn_kv_caches
+
+        while len(model.graph.output) > 0:
+            model.graph.output.pop()
+        model.graph.output.extend(reordered_outputs)
+        return model
+
+    def fix_layernorm_weights(self, model: ModelProto, use_fp16_inputs: bool):
+        if self.model_impl == "openai" and use_fp16_inputs:
+            # Cast ONNX model to float16 to ensure LayerNorm weights are converted from
+            # float32 to float16 since exported model already has float16 weights everywhere
+            # except for LayerNorm ops. This happens because OpenAI always upcasts to float32
+            # when computing LayerNorm.
+            #
+            # Reference:
+            # https://github.com/openai/whisper/blob/90db0de1896c23cbfaf0c58bc2d30665f709f170/whisper/model.py#L41
+            model = convert_float_to_float16(model)
+        return model
+
+    def export_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_fp16_inputs: bool = False,
+        use_int32_inputs: bool = True,
+    ):
+        """Export encoder-decoder-init to ONNX
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): provider to use for verifying parity on ONNX model
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_fp16_inputs (bool, optional): use float16 inputs for the audio_features. Defaults to False.
+            use_int32_inputs (bool, optional): use int32 inputs for the decoder_input_ids. Defaults to True.
+        """
+        # Shape of encoder's tensors:
+        # Inputs:
+        #    audio_features: (batch_size, num_mels, num_frames)
+        # Outputs:
+        #    encoder_hidden_states: (batch_size, num_frames // 2, hidden_size)
+
+        # Shape of decoder's tensors:
+        # Inputs:
+        #    decoder_input_ids: (batch_size, sequence_length)
+        #    encoder_hidden_states (comes from encoder's outputs): (batch_size, num_frames // 2, hidden_size)
+        # Outputs:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    present_{key/value}_self_* (present self attention KV caches): (batch_size, num_heads, past_sequence_length + sequence_length, head_size)
+        #    present_{key/value}_cross_* (present cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs)
+        input_names = self.input_names()
+        output_names = self.output_names()
+        dynamic_axes = self.dynamic_axes(input_names, output_names)
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "encoder_decoder_init.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            out_path = temp_onnx_model_path if use_external_data_format else onnx_model_path
+
+            torch.onnx.export(
+                self,
+                args=inputs,
+                f=out_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=18,
+                do_constant_folding=True,
+                dynamo=False,
+                verbose=verbose,
+            )
+
+            model = onnx.load_model(out_path, load_external_data=use_external_data_format)
+            model = self.fix_outputs(model)
+            model = self.fix_layernorm_weights(model, use_fp16_inputs)
+            OnnxModel.save(
+                model,
+                onnx_model_path,
+                save_as_external_data=use_external_data_format,
+                all_tensors_to_one_file=True,
+            )
+
+        self.verify_onnx(onnx_model_path, provider, use_fp16_inputs, use_int32_inputs)
+
+    def verify_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        use_fp16_inputs: bool,
+        use_int32_inputs: bool,
+    ):
+        """Verify ONNX model outputs and PyTorch model outputs match
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): execution provider for ONNX model
+            use_fp16_inputs (bool, optional): use float16 inputs for the audio_features
+            use_int32_inputs (bool, optional): use int32 inputs for the decoder_input_ids
+        """
+        # Shape of encoder's tensors:
+        # Inputs:
+        #    audio_features: (batch_size, num_mels, num_frames)
+        # Outputs:
+        #    encoder_hidden_states: (batch_size, num_frames // 2, hidden_size)
+
+        # Shape of decoder's tensors:
+        # Inputs:
+        #    decoder_input_ids: (batch_size, sequence_length)
+        #    encoder_hidden_states (comes from encoder's outputs): (batch_size, num_frames // 2, hidden_size)
+        # Outputs:
+        #    logits: (batch_size, sequence_length, vocab_size)
+        #    present_{key/value}_self_* (present self attention KV caches): (batch_size, num_heads, past_sequence_length + sequence_length, head_size)
+        #    present_{key/value}_cross_* (present cross attention KV caches): (batch_size, num_heads, num_frames // 2, head_size)
+
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs, return_dict=True)
+
+        # Run PyTorch model
+        pt_outputs = []
+        if self.no_beam_search_op:
+            out = self.forward(**inputs)
+            pt_outputs.append(out[0].detach().cpu().numpy())
+            for present_cross_attn_cache in out[1]:
+                pt_outputs.append(present_cross_attn_cache.detach().cpu().numpy())
+        else:
+            out = self.forward(**inputs)
+            pt_outputs.append(out[0].detach().cpu().numpy())
+            pt_outputs.append(out[1].detach().cpu().numpy())
+
+            (self_attn_kv_caches, cross_attn_kv_caches) = group_past_key_values(out[2])
+            pt_outputs.extend([self_attn_kv_cache.detach().cpu().numpy() for self_attn_kv_cache in self_attn_kv_caches])
+            pt_outputs.extend(
+                [cross_attn_kv_cache.detach().cpu().numpy() for cross_attn_kv_cache in cross_attn_kv_caches]
+            )
+
+        # Run ONNX model
+        sess = InferenceSession(onnx_model_path, providers=[provider])
+        ort_outputs = sess.run(None, convert_inputs_for_ort(inputs, sess))
+
+        # Calculate output difference
+        for i, output_name in enumerate(self.output_names()):
+            diff = np.abs(pt_outputs[i] - ort_outputs[i])
+            logger.warning(f"Comparing {output_name}...")
+            logger.warning(f"Max diff: {np.max(diff)}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..883e9508e4f345bf519a44da89e7e02ed523b920
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_helper.py
@@ -0,0 +1,1035 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import json
+import logging
+import os
+from pathlib import Path
+
+import numpy as np
+import torch
+from convert_generation import add_cache_indirection_to_mha, add_output_qk_to_mha, fix_past_sequence_length
+from optimizer import optimize_model
+from transformers import AutoTokenizer, WhisperConfig, WhisperForConditionalGeneration, WhisperProcessor
+from whisper_decoder import WhisperDecoder
+from whisper_encoder import WhisperEncoder
+from whisper_encoder_decoder_init import WhisperEncoderDecoderInit
+from whisper_jump_times import WhisperJumpTimes
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+PRETRAINED_WHISPER_MODELS = [
+    "whisper-tiny",
+    "whisper-tiny.en",
+    "whisper-base",
+    "whisper-base.en",
+    "whisper-small",
+    "whisper-small.en",
+    "whisper-medium",
+    "whisper-medium.en",
+    "whisper-large",
+    "whisper-large-v2",
+    "whisper-large-v3",
+    "whisper-large-v3-turbo",
+]
+
+
+class WhisperHelper:
+    @staticmethod
+    def get_onnx_path(
+        output_dir: str,
+        model_name_or_path: str,
+        suffix: str = "",
+        new_folder: bool = False,
+    ) -> str:
+        """Build onnx path
+
+        Args:
+            output_dir (str): output directory
+            model_name_or_path (str): pretrained model name, or path to the model checkpoint
+            suffix (str, optional): suffix like "_encoder" or "_decoder_fp16" will be appended to file name. Defaults to None.
+            new_folder (bool, optional): create a new directory for the model. Defaults to False.
+        Returns:
+            str: path of onnx model
+        """
+        model_name = model_name_or_path
+        if os.path.isdir(model_name_or_path):
+            model_name = Path(model_name_or_path).parts[-1]
+        else:
+            model_name = model_name.split("/")[-1]
+
+        model_name += suffix
+
+        directory = os.path.join(output_dir, model_name) if new_folder else output_dir
+        return os.path.join(directory, model_name + ".onnx")
+
+    @staticmethod
+    def save_processing(
+        model_name_or_path: str,
+        provider: str,
+        separate_encoder_and_decoder_init: bool,
+        use_decoder_masked_mha: bool,
+        output_qk: bool,
+        encoder_path: str,
+        decoder_path: str,
+        output_dir: str,
+        cache_dir: str,
+    ) -> None:
+        config = WhisperConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        config.save_pretrained(output_dir)
+
+        tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        tokenizer.save_pretrained(output_dir)
+
+        processor = WhisperProcessor.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        processor.save_pretrained(output_dir)
+
+        # Return early since the next files are for ONNX Runtime GenAI
+        if separate_encoder_and_decoder_init:
+            return
+
+        audio_processor_cfg = {
+            "feature_extraction": {
+                "sequence": [
+                    {"operation": {"name": "audio_decoder", "type": "AudioDecoder"}},
+                    {
+                        "operation": {
+                            "name": "STFT",
+                            "type": "STFTNorm",
+                            "attrs": {
+                                "n_fft": 400,
+                                "frame_length": 400,
+                                "hop_length": 160,
+                                "_comment": [
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+                                    0.2061072587966919,
+                                    0.19978976249694824,
+                                    0.1935463547706604,
+                                    0.18737855553627014,
+                                    0.18128788471221924,
+                                    0.17527586221694946,
+                                    0.1693439483642578,
+                                    0.16349363327026367,
+                                    0.15772631764411926,
+                                    0.15204349160194397,
+                                    0.14644649624824524,
+                                    0.1409367322921753,
+                                    0.13551557064056396,
+                                    0.1301843225955963,
+                                    0.12494435906410217,
+                                    0.11979690194129944,
+                                    0.11474326252937317,
+                                    0.10978469252586365,
+                                    0.10492238402366638,
+                                    0.10015755891799927,
+                                    0.09549137949943542,
+                                    0.09092503786087036,
+                                    0.08645960688591003,
+                                    0.08209621906280518,
+                                    0.07783591747283936,
+                                    0.07367980480194092,
+                                    0.06962886452674866,
+                                    0.06568413972854614,
+                                    0.06184655427932739,
+                                    0.0581170916557312,
+                                    0.0544966459274292,
+                                    0.05098611116409302,
+                                    0.04758638143539429,
+                                    0.044298261404037476,
+                                    0.04112258553504944,
+                                    0.038060128688812256,
+                                    0.03511166572570801,
+                                    0.03227788209915161,
+                                    0.02955952286720276,
+                                    0.02695724368095398,
+                                    0.024471670389175415,
+                                    0.02210339903831482,
+                                    0.01985308527946472,
+                                    0.017721205949783325,
+                                    0.015708357095718384,
+                                    0.0138150155544281,
+                                    0.012041598558425903,
+                                    0.010388582944869995,
+                                    0.008856356143951416,
+                                    0.007445335388183594,
+                                    0.006155818700790405,
+                                    0.004988163709640503,
+                                    0.003942638635635376,
+                                    0.0030195116996765137,
+                                    0.0022190213203430176,
+                                    0.0015413165092468262,
+                                    0.000986635684967041,
+                                    0.0005550682544708252,
+                                    0.0002467334270477295,
+                                    0.0000616908073425293,
+                                ],
+                            },
+                        }
+                    },
+                    {
+                        "operation": {
+                            "name": "log_mel_spectrogram",
+                            "type": "LogMelSpectrum",
+                            "attrs": {"chunk_size": 30, "hop_length": 160, "n_fft": 400, "n_mel": config.num_mel_bins},
+                        }
+                    },
+                ]
+            }
+        }
+        audio_processor_json = json.dumps(audio_processor_cfg, indent=4)
+
+        with open(os.path.join(output_dir, "audio_processor_config.json"), "w") as f:
+            f.write(audio_processor_json)
+
+        provider_options = [] if "cpu" in provider else [{f"{provider}": {}}]
+        genai_config = {
+            "model": {
+                "bos_token_id": config.bos_token_id,
+                "context_length": config.max_length,
+                "decoder": {
+                    "session_options": {
+                        "log_id": "onnxruntime-genai",
+                        "provider_options": provider_options,
+                    },
+                    "filename": os.path.basename(decoder_path),
+                    "head_size": config.d_model // config.decoder_attention_heads,
+                    "hidden_size": config.d_model,
+                    "inputs": {
+                        "input_ids": "input_ids",
+                        "past_key_names": "past_key_self_%d",
+                        "past_value_names": "past_value_self_%d",
+                        "cross_past_key_names": "past_key_cross_%d",
+                        "cross_past_value_names": "past_value_cross_%d",
+                    },
+                    "outputs": {
+                        "logits": "logits",
+                        "present_key_names": "present_key_self_%d",
+                        "present_value_names": "present_value_self_%d",
+                    },
+                    "num_attention_heads": config.decoder_attention_heads,
+                    "num_hidden_layers": config.decoder_layers,
+                    "num_key_value_heads": config.decoder_attention_heads,
+                },
+                "encoder": {
+                    "session_options": {
+                        "log_id": "onnxruntime-genai",
+                        "provider_options": provider_options,
+                    },
+                    "filename": os.path.basename(encoder_path),
+                    "head_size": config.d_model // config.encoder_attention_heads,
+                    "hidden_size": config.d_model,
+                    "inputs": {"audio_features": "audio_features"},
+                    "outputs": {
+                        "encoder_hidden_states": "encoder_hidden_states",
+                        "cross_present_key_names": "present_key_cross_%d",
+                        "cross_present_value_names": "present_value_cross_%d",
+                    },
+                    "num_attention_heads": config.encoder_attention_heads,
+                    "num_hidden_layers": config.encoder_layers,
+                    "num_key_value_heads": config.encoder_attention_heads,
+                },
+                "eos_token_id": config.eos_token_id,
+                "pad_token_id": config.pad_token_id,
+                "type": "whisper",
+                "vocab_size": config.vocab_size,
+            },
+            "search": {
+                "diversity_penalty": 0.0,
+                "do_sample": False,
+                "early_stopping": True,
+                "length_penalty": 1.0,
+                "max_length": config.max_length,
+                "min_length": 0,
+                "no_repeat_ngram_size": 0,
+                "num_beams": 1,
+                "num_return_sequences": 1,
+                "past_present_share_buffer": use_decoder_masked_mha,
+                "repetition_penalty": 1.0,
+                "temperature": 1.0,
+                "top_k": 1,
+                "top_p": 1.0,
+            },
+        }
+
+        # Requirements for the DMMHA kernel:
+        # - Buffer sharing = true
+        # - New input: past_sequence_length
+        # - New input: cache_indirection
+        # Otherwise, buffer sharing should be false and the new inputs should not be added
+        # for beam search to work in ORT GenAI.
+        if use_decoder_masked_mha:
+            genai_config["model"]["decoder"]["inputs"].update(
+                {
+                    "past_sequence_length": "past_sequence_length",
+                    "cache_indirection": "cache_indirection",
+                }
+            )
+
+        if output_qk:
+            genai_config["model"]["decoder"]["outputs"].update(
+                {
+                    "output_cross_qk_names": "output_cross_qk_%d",
+                }
+            )
+
+        with open(os.path.join(output_dir, "genai_config.json"), "w") as f:
+            json.dump(genai_config, f, indent=4)
+
+    @staticmethod
+    def load_model(
+        model_name_or_path: str,
+        model_impl: str,
+        cache_dir: str,
+        device: torch.device,
+        dtype: torch.dtype,
+        merge_encoder_and_decoder_init: bool = True,
+        no_beam_search_op: bool = False,
+        output_qk: bool = False,
+    ) -> dict[str, torch.nn.Module]:
+        """Load model given a pretrained name or path, then build models for ONNX conversion.
+
+        Args:
+            model_name_or_path (str): pretrained model name or path
+            model_impl (str): library to load model from
+            cache_dir (str): cache directory
+            device (torch.device): device to run the model
+            dtype (torch.dtype): dtype to run the model
+            merge_encoder_and_decoder_init (bool, optional): Whether merge encoder and decoder initialization into one ONNX model. Defaults to True.
+            no_beam_search_op (bool, optional): Whether to use beam search op or not. Defaults to False.
+            output_qk (bool, optional): Whether to output QKs to calculate batched jump times for word-level timestamps. Defaults to False.
+        Returns:
+            Dict[str, torch.nn.Module]: mapping from name to modules for ONNX conversion.
+        """
+        # Load PyTorch model
+        if model_impl == "hf":
+            # Load from Hugging Face
+            model = WhisperForConditionalGeneration.from_pretrained(
+                model_name_or_path, cache_dir=cache_dir, attn_implementation="eager"
+            )
+        else:
+            # Load from OpenAI
+            import whisper  # noqa: PLC0415
+
+            if not os.path.exists(model_name_or_path):
+                name_or_path = model_name_or_path.split("/")[-1][8:]
+            else:
+                name_or_path = model_name_or_path
+            model = whisper.load_model(name_or_path, device, download_root=cache_dir, in_memory=True)
+
+        # Set PyTorch model properties
+        model.eval().to(device=device)
+        if model_impl == "hf":
+            model.to(dtype=dtype)
+        config = WhisperConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+
+        # Load each component of PyTorch model
+        decoder = WhisperDecoder(config, model, model_impl, no_beam_search_op).eval()
+        components = {"decoder": decoder}
+        if merge_encoder_and_decoder_init:
+            encoder_decoder_init = WhisperEncoderDecoderInit(config, model, model_impl, no_beam_search_op).eval()
+            components.update({"encoder": encoder_decoder_init})
+        else:
+            encoder = WhisperEncoder(config, model, model_impl).eval()
+            components.update({"encoder": encoder, "decoder_init": decoder})
+
+        if output_qk:
+            batched_jump_times = WhisperJumpTimes(config, device, cache_dir).eval()
+            components.update({"jump_times": batched_jump_times})
+        return components
+
+    @staticmethod
+    def export_onnx(
+        model: WhisperEncoder | WhisperEncoderDecoderInit | WhisperDecoder,
+        onnx_model_path: str,
+        provider: str,
+        verbose: bool,
+        use_external_data_format: bool,
+        use_fp16_inputs: bool,
+        use_int32_inputs: bool,
+        use_encoder_hidden_states: bool,
+        use_kv_cache_inputs: bool,
+    ):
+        """Export model component to ONNX
+
+        Args:
+            model (class): PyTorch class to export
+            onnx_model_path (str): path to save ONNX model
+            provider (str): provider to use for verifying parity on ONNX model
+            verbose (bool): print verbose information.
+            use_external_data_format (bool): use external data format or not.
+            use_fp16_inputs (bool): use float16 inputs for the audio_features, encoder_hidden_states, logits, and KV caches.
+            use_int32_inputs (bool): use int32 inputs for the decoder_input_ids.
+            use_encoder_hidden_states (bool): use encoder_hidden_states as model input for decoder-init/decoder-without-past models.
+            use_kv_cache_inputs (bool): use KV caches as model inputs for decoder-with-past models.
+        """
+        if isinstance(model, WhisperEncoder):
+            model.export_onnx(
+                onnx_model_path,
+                provider,
+                verbose,
+                use_external_data_format,
+                use_fp16_inputs,
+            )
+        elif isinstance(model, WhisperEncoderDecoderInit):
+            model.export_onnx(
+                onnx_model_path,
+                provider,
+                verbose,
+                use_external_data_format,
+                use_fp16_inputs,
+                use_int32_inputs,
+            )
+        elif isinstance(model, WhisperDecoder):
+            model.export_onnx(
+                onnx_model_path,
+                provider,
+                verbose,
+                use_external_data_format,
+                use_fp16_inputs,
+                use_int32_inputs,
+                use_encoder_hidden_states,
+                use_kv_cache_inputs,
+            )
+        elif isinstance(model, WhisperJumpTimes):
+            model.export_onnx(
+                onnx_model_path,
+                provider,
+                verbose,
+                use_external_data_format,
+                use_fp16_inputs,
+                use_int32_inputs,
+            )
+        else:
+            raise ValueError(f"Unknown instance for model detected: {type(model)}")
+
+    @staticmethod
+    def optimize_onnx(
+        onnx_model_path: str,
+        optimized_model_path: str,
+        is_float16: bool,
+        num_attention_heads: int,
+        hidden_size: int,
+        num_decoder_layers: int,
+        use_external_data_format: bool = False,
+        use_gpu: bool = False,
+        provider: str = "cpu",
+        is_decoder: bool = False,
+        no_beam_search_op: bool = False,
+        use_decoder_masked_mha: bool = False,
+        output_qk: bool = False,
+    ):
+        """Optimize ONNX model with an option to convert it to use mixed precision."""
+
+        from fusion_options import FusionOptions  # noqa: PLC0415
+
+        optimization_options = FusionOptions("bart")
+        optimization_options.use_multi_head_attention = True
+        optimization_options.disable_multi_head_attention_bias = False
+
+        m = optimize_model(
+            onnx_model_path,
+            model_type="bart",
+            num_heads=num_attention_heads,
+            hidden_size=hidden_size,
+            opt_level=0,
+            optimization_options=optimization_options,
+            use_gpu=use_gpu,
+            only_onnxruntime=False,
+        )
+
+        # Add `past_sequence_length`, `cache_indirection`, and `output_qk` to `MultiHeadAttention` ops
+        if is_decoder and no_beam_search_op:
+            if use_decoder_masked_mha:
+                # FP16 CUDA, FP32 CUDA, and FP32 CPU use the `DecoderMaskedMultiHeadAttention` kernel
+                # via `MultiHeadAttention`, which requires the `past_sequence_length` and
+                # `cache_indirection` inputs
+                m, past_seq_len_name = fix_past_sequence_length(m)
+                m = add_cache_indirection_to_mha(m, past_seq_len_name)
+
+            if output_qk:
+                m = add_output_qk_to_mha(m, skip_node_idxs=list(range(0, 2 * num_decoder_layers, 2)))
+
+        m.save_model_to_file(optimized_model_path, use_external_data_format, all_tensors_to_one_file=True)
+
+    @staticmethod
+    def pt_transcription_for_verify_onnx(
+        processor: WhisperProcessor,
+        pt_model: torch.nn.Module,
+        device: torch.device,
+        batch_size: int = 1,
+        prompt_mode: bool = False,
+    ):
+        # Try to import `datasets` pip package
+        try:
+            from datasets import load_dataset  # noqa: PLC0415
+        except Exception as e:
+            logger.error(f"An error occurred while importing `datasets`: {e}", exc_info=True)  # noqa: G201
+            install_cmd = "pip install datasets"
+            logger.warning(f"Could not import `datasets`. Attempting to install `datasets` via `{install_cmd}`.")
+            os.system(install_cmd)
+
+        from datasets import load_dataset  # noqa: PLC0415
+
+        ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+        input_features_ = []
+        if batch_size == 1:
+            input_features = processor([ds[0]["audio"]["array"]], return_tensors="pt").input_features
+        else:
+            input_features_ = [
+                processor([ds[3]["audio"]["array"]], return_tensors="pt").input_features,
+                processor([ds[3]["audio"]["array"]], return_tensors="pt").input_features,
+            ]
+            assert len(input_features_) == batch_size
+            input_features = torch.cat((input_features_[0], input_features_[1]))
+
+        max_length, min_length, num_beams, num_return_sequences = 30, 0, 1, 1
+        length_penalty, repetition_penalty = 1.0, 1.0
+        inputs = {
+            "input_features": input_features.to(device),
+            "max_length": max_length,
+            "min_length": min_length,
+            "num_beams": num_beams,
+            "num_return_sequences": num_return_sequences,
+            "length_penalty": length_penalty,
+            "repetition_penalty": repetition_penalty,
+            "early_stopping": True,
+            "use_cache": True,
+        }
+
+        if prompt_mode:
+            prompts = ["John has doubts", "Maria has grave doubts"]
+            prompt_ids = [processor.get_prompt_ids(p) for p in prompts]
+            pt_transcription = []
+            pt_outputs = []
+            # The looping for model.generate is necessary here due to the limitation as per
+            # https://huggingface.co/docs/transformers/model_doc/whisper#transformers.WhisperForConditionalGeneration.generate.prompt_ids
+            # prompt_ids input requires a tensor of rank 1
+            for i in range(batch_size):
+                inputs["prompt_ids"] = torch.from_numpy(prompt_ids[i]).to(device=device)
+                inputs["input_features"] = input_features_[i].to(device)
+                pt_output = pt_model.generate(**inputs).detach().cpu().numpy()
+                pt_outputs.append(pt_output)
+                pt_transcription.append(processor.batch_decode(pt_output, skip_special_tokens=True)[0])
+            inputs["input_features"] = input_features
+            del inputs["prompt_ids"]
+        else:
+            prompt_ids = []
+            pt_outputs = pt_model.generate(**inputs).detach().cpu().numpy()
+            pt_transcription = [processor.batch_decode(pt_outputs, skip_special_tokens=True)[0]]
+            pt_outputs = list(pt_outputs)
+        del inputs["early_stopping"]
+        del inputs["use_cache"]
+        return inputs, pt_transcription, pt_outputs, prompt_ids
+
+    @staticmethod
+    def select_transcription_options(
+        batch_size: int,
+        prompt_mode: bool,
+    ):
+        if batch_size > 1 and prompt_mode:
+            expected_transcription_no_comma_prompt1 = " John has doubts whether Sir Frederick Layton's work is really Greek after all and can discover in it but little of Rocky I"
+            expected_transcription_misspelled_prompt1 = " John has doubts whether Sir Frederick Latins work is really Greek after all and can discover in it but little of Rocky I"
+            expected_transcription_no_comma_prompt2 = " Maria has grave doubts whether Sir Frederick Layton's work is really Greek after all and can discover in it but little of Rocky"
+            expected_transcription_misspelled_prompt2 = " Maria has grave doubts whether Sir Frederick Latins work is really Greek after all and can discover in it but little of Rocky I"
+            expected_transcription_options = {
+                expected_transcription_no_comma_prompt1,
+                expected_transcription_no_comma_prompt2,
+                expected_transcription_misspelled_prompt1,
+                expected_transcription_misspelled_prompt2,
+            }
+        else:
+            expected_transcription_no_comma = (
+                " Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel."
+            )
+            expected_transcription_with_comma = (
+                " Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel."
+            )
+            expected_transcription_with_quote_and_comma = (
+                ' "Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.'
+            )
+            expected_transcription_options = {
+                expected_transcription_no_comma,
+                expected_transcription_with_comma,
+                expected_transcription_with_quote_and_comma,
+            }
+        return expected_transcription_options
+
+    @staticmethod
+    def get_outputs(
+        pt_outputs: np.ndarray,
+        ort_outputs: np.ndarray,
+        i: int,
+    ):
+        """Get PyTorch and ONNX Runtime output token ids at index i"""
+        pt_output, ort_output = pt_outputs[i], ort_outputs[i]
+        pt_shape, ort_shape = pt_output.shape, ort_output.shape
+
+        # Hugging Face impl. + Beam Search op: PyTorch = (26,) and ORT = (30,)
+        # OpenAI impl. + Beam Search op: PyTorch = (1, 30) and ORT = (30,)
+        if pt_shape != ort_shape:
+            if len(pt_shape) > 1:
+                pt_output = pt_output[0]
+                pt_shape = pt_output.shape
+            if len(ort_shape) > 1:
+                ort_output = ort_output[0]
+                ort_shape = ort_output.shape
+            if pt_shape[0] != ort_shape[0]:
+                min_len = min(pt_shape[0], ort_shape[0])
+                pt_output = pt_output[:min_len]
+                ort_output = ort_output[:min_len]
+
+        assert pt_output.shape == ort_output.shape
+        return pt_output, ort_output
+
+    @staticmethod
+    def verify_onnx(
+        model_name_or_path: str,
+        cache_dir: str,
+        ort_session: InferenceSession,
+        device: torch.device,
+        batch_size: int = 1,
+        prompt_mode: bool = False,
+    ):
+        """Compare the result from PyTorch and ONNX Runtime to verify the ONNX model is good."""
+        pt_model = WhisperForConditionalGeneration.from_pretrained(
+            model_name_or_path, cache_dir=cache_dir, attn_implementation="eager"
+        ).to(device)
+        processor = WhisperProcessor.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+        config = WhisperConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir)
+
+        inputs, pt_transcription, pt_outputs, decoder_prompt_ids = WhisperHelper.pt_transcription_for_verify_onnx(
+            processor,
+            pt_model,
+            device,
+            batch_size=batch_size,
+            prompt_mode=prompt_mode,
+        )
+
+        start_id = [config.decoder_start_token_id]  # ex: [50258]
+        prompt_ids = processor.get_decoder_prompt_ids(language="english", task="transcribe")
+        prompt_ids = [token[1] for token in prompt_ids]  # ex: [50259, 50358, 50363]
+        forced_decoder_ids = start_id + prompt_ids  # ex: [50258, 50259, 50358, 50363]
+
+        ort_names = [entry.name for entry in ort_session.get_inputs()]
+        ort_dtypes = [entry.type for entry in ort_session.get_inputs()]
+        ort_to_np = {
+            "tensor(float)": np.float32,
+            "tensor(float16)": np.float16,
+            "tensor(int64)": np.int64,
+            "tensor(int32)": np.int32,
+            "tensor(int8)": np.int8,
+            "tensor(uint8)": np.uint8,
+        }
+
+        use_extra_decoding_ids = "extra_decoding_ids" in ort_names
+        for name, dtype in zip(ort_names, ort_dtypes, strict=False):
+            if name == "input_features":
+                inputs[name] = inputs[name].detach().cpu().numpy()
+            elif name == "vocab_mask":
+                inputs[name] = np.ones(config.vocab_size, dtype=ort_to_np[dtype])
+            elif name == "prefix_vocab_mask":
+                inputs[name] = np.ones((batch_size, config.vocab_size), dtype=ort_to_np[dtype])
+            elif name == "decoder_input_ids":
+                if not prompt_mode:
+                    raw_input_ids = [start_id] if use_extra_decoding_ids else [forced_decoder_ids]
+                    inputs[name] = np.array(raw_input_ids, dtype=ort_to_np[dtype])
+                else:
+                    # This logic handles the scenario for when prompts are not of the same size
+                    # For example if our prompt ids are [p1_id_1, p1_id_2] and [p2_id_1]
+                    # The final decoder_input_ids will look as such after padding
+                    # [prev_token, p1_id_1, p1_id_2, start_token, lang_token, transcribe_token]
+                    # [prev_token, p2_id_1, PAD_TOKEN, start_token, lang_token, transcribe_token]
+                    ort_prompts = []
+                    for i in range(batch_size):
+                        ort_prompts.append(decoder_prompt_ids[i].tolist())
+                    max_len = max(len(p) for p in ort_prompts)
+                    padded_prompts = []
+                    for p in ort_prompts:
+                        padded_prompt = [*p, *([config.pad_token_id] * (max_len - len(p)))]
+                        padded_prompts.append(padded_prompt + forced_decoder_ids)
+                    inputs[name] = np.array(padded_prompts, dtype=ort_to_np[dtype])
+            elif name == "logits_processor":
+                inputs[name] = np.array([1], dtype=ort_to_np[dtype])
+            elif name == "cross_qk_layer_head":
+                inputs[name] = np.array([[0, 0]], dtype=ort_to_np[dtype])
+            elif name == "extra_decoding_ids":
+                inputs[name] = np.repeat(np.array([prompt_ids], dtype=ort_to_np[dtype]), batch_size, 0)
+            elif name == "temperature":
+                inputs[name] = np.array([1.0], dtype=ort_to_np[dtype])
+            else:
+                inputs[name] = np.array([inputs[name]], dtype=ort_to_np[dtype])
+
+        ort_outputs = ort_session.run(None, inputs)[0][:, 0, :]
+        ort_transcription = processor.batch_decode(ort_outputs, skip_special_tokens=True)
+        expected_transcription_options = WhisperHelper.select_transcription_options(batch_size, prompt_mode)
+
+        parity = 1
+        for i in range(batch_size):
+            pt_output, ort_output = WhisperHelper.get_outputs(pt_outputs, ort_outputs, i)
+
+            # Check if token ids match
+            parity *= np.allclose(pt_output, ort_output)
+
+            # Check if transcribed outputs match
+            parity *= (
+                pt_transcription[i] in expected_transcription_options
+                and ort_transcription[i] in expected_transcription_options
+            )
+        max_diff = 0
+
+        if not parity:
+            for i in range(batch_size):
+                pt_output, ort_output = WhisperHelper.get_outputs(pt_outputs, ort_outputs, i)
+                diff = pt_output - ort_output
+
+                max_diff_i = max(diff.min(), diff.max(), key=abs)
+                max_diff = max(max_diff, max_diff_i)
+
+        if max_diff != 0:
+            logger.warning(f"PyTorch outputs: {pt_transcription}")
+            logger.warning(f"ONNX Runtime outputs: {ort_transcription}")
+
+        return 0
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_inputs.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_inputs.py
new file mode 100644
index 0000000000000000000000000000000000000000..4be914689492e16788799404153f27ea1f959367
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_inputs.py
@@ -0,0 +1,380 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+
+import numpy as np
+import torch
+from transformers import WhisperConfig
+
+from onnxruntime import InferenceSession
+
+logger = logging.getLogger(__name__)
+
+
+# Create audio_features for encoder
+# Shape is (batch_size, feature_size, sequence_length) = (batch_size, num_mel_filters, num_frames)
+# where num_mel_filters is a model attribute and num_frames = (chunk_length * sample_rate) // hop_length.
+#
+# Hard-coded audio hyperparameters:
+# SAMPLE_RATE = 16000
+# N_FFT = 400
+# HOP_LENGTH = 160
+# CHUNK_LENGTH = 30  (i.e. 30-second chunk of audio)
+# N_SAMPLES = CHUNK_LENGTH * SAMPLE_RATE = 30 * 16000 = 480000  (i.e. 480,000 samples in a 30-second chunk of audio)
+# N_FRAMES = N_SAMPLES // HOP_LENGTH = 480000 // 160 = 3000  (i.e. 3000 frames in a mel spectrogram input)
+#
+# N_SAMPLES_PER_TOKEN = HOP_LENGTH * 2 = 160 * 2 = 320
+# FRAMES_PER_TOKEN = SAMPLE_RATE // HOP_LENGTH = 16000 // 160 = 100  (i.e. 10 ms per audio frame)
+# TOKENS_PER_SECOND = SAMPLE_RATE // N_SAMPLES_PER_TOKEN = 16000 // 320 = 50  (i.e. 20 ms per audio token)
+def get_sample_audio_features(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    sequence_length: int = 3000,
+    use_fp16: bool = False,
+):
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+    audio_features = torch.randn(batch_size, config.num_mel_bins, sequence_length, device=device, dtype=torch_dtype)
+    return audio_features
+
+
+# Create input_ids for decoder
+# Shape is (batch_size, sequence_length) where sequence_length is the initial decoder sequence length
+def get_sample_decoder_input_ids(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    sequence_length: int,
+    use_int32: bool = True,
+):
+    torch_dtype = torch.int32 if use_int32 else torch.int64
+    decoder_input_ids = torch.randint(
+        low=0, high=config.vocab_size, size=(batch_size, sequence_length), device=device, dtype=torch_dtype
+    )
+    return decoder_input_ids
+
+
+# Create encoder_hidden_states for decoder-init
+# Shape is (batch_size, num_frames // 2, hidden_size)
+def get_sample_encoder_hidden_states(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    use_fp16: bool = False,
+):
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+    encoder_hidden_states = torch.randn(
+        batch_size, config.max_source_positions, config.d_model, device=device, dtype=torch_dtype
+    )
+    return encoder_hidden_states
+
+
+# Create past_key_values
+# Self-attention KV caches are of shape (batch_size, num_heads, past_sequence_length, head_size)
+# Cross-attention KV caches are of shape (batch_size, num_heads, num_frames // 2, head_size)
+def get_sample_past_key_values(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    past_seq_len: int,
+    use_fp16: bool = False,
+):
+    num_heads = config.decoder_attention_heads
+    head_size = config.d_model // num_heads
+    max_source_positions = (
+        config.max_source_positions
+    )  # equal to num_frames // 2 = encoder's sequence_length // 2 = 3000 // 2 = 1500
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+    self_attention_kv_caches = [
+        (
+            torch.rand(batch_size, num_heads, past_seq_len, head_size, device=device, dtype=torch_dtype),
+            torch.rand(batch_size, num_heads, past_seq_len, head_size, device=device, dtype=torch_dtype),
+        )
+        for _ in range(config.decoder_layers)
+    ]
+    cross_attention_kv_caches = [
+        (
+            torch.rand(batch_size, num_heads, max_source_positions, head_size, device=device, dtype=torch_dtype),
+            torch.rand(batch_size, num_heads, max_source_positions, head_size, device=device, dtype=torch_dtype),
+        )
+        for _ in range(config.decoder_layers)
+    ]
+    return flatten_past_key_values(self_attention_kv_caches, cross_attention_kv_caches)
+
+
+# Flatten KV caches into pairs-of-4 where each pair is defined as:
+# (self_attn_key_cache, self_attn_value_cache, cross_attn_key_cache, cross_attn_value_cache)
+def flatten_past_key_values(
+    self_attn_kv_caches: list[tuple[torch.Tensor, torch.Tensor]],
+    cross_attn_kv_caches: list[tuple[torch.Tensor, torch.Tensor]],
+):
+    past_key_values = []
+    for (self_k_cache, self_v_cache), (cross_k_cache, cross_v_cache) in zip(
+        self_attn_kv_caches, cross_attn_kv_caches, strict=False
+    ):
+        layer_kv_caches = (self_k_cache, self_v_cache, cross_k_cache, cross_v_cache)
+        past_key_values.append(layer_kv_caches)
+    return past_key_values
+
+
+# Group KV caches into two 1D lists where one list contains the self attention KV caches and
+# one list contains the cross attention KV caches
+def group_past_key_values(
+    kv_caches: list[tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]],
+):
+    self_attn_kv_caches, cross_attn_kv_caches = [], []
+    for self_k_cache, self_v_cache, cross_k_cache, cross_v_cache in kv_caches:
+        self_attn_kv_caches.append(self_k_cache)
+        self_attn_kv_caches.append(self_v_cache)
+        cross_attn_kv_caches.append(cross_k_cache)
+        cross_attn_kv_caches.append(cross_v_cache)
+    return self_attn_kv_caches, cross_attn_kv_caches
+
+
+# Create alignment heads for timestamps
+# Shape is (num_alignment_heads, 2)
+def get_sample_alignment_heads(
+    config: WhisperConfig,
+    device: torch.device,
+    num_alignment_heads: int = 6,
+    use_int32: bool = True,
+):
+    torch_dtype = torch.int32 if use_int32 else torch.int64
+    alignment_heads = torch.ones((num_alignment_heads, 2), device=device, dtype=torch_dtype)
+    return alignment_heads
+
+
+# Create length of start-of-transcription sequence for timestamps
+# Shape is (1)
+def get_sample_sot_sequence_length(
+    device: torch.device,
+    sot_sequence_length: int,
+    use_int32: bool = False,
+):
+    torch_dtype = torch.int32 if use_int32 else torch.int64
+    sot_length = torch.tensor([sot_sequence_length], device=device, dtype=torch_dtype)
+    return sot_length
+
+
+# Create segment length for timestamps
+# Shape is (1)
+def get_sample_segment_length(
+    device: torch.device,
+    segment_length: int,
+    use_int32: bool = False,
+):
+    torch_dtype = torch.int32 if use_int32 else torch.int64
+    segment_size = torch.tensor([segment_length], device=device, dtype=torch_dtype)
+    return segment_size
+
+
+# Create QKs for timestamps
+# Shape is (batch_size, num_heads, sequence_length, num_frames // 2)
+def get_sample_QKs(  # noqa: N802
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    sequence_length: int,
+    use_fp16: bool = False,
+):
+    num_heads = config.decoder_attention_heads
+    torch_dtype = torch.float16 if use_fp16 else torch.float32
+    QKs = [  # noqa: N806
+        torch.rand(
+            batch_size, num_heads, sequence_length, config.max_source_positions, device=device, dtype=torch_dtype
+        )
+        for _ in range(config.decoder_layers)
+    ]
+    return QKs
+
+
+# Create inputs for encoder component of Whisper
+def get_sample_encoder_inputs(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    sequence_length: int = 3000,
+    use_fp16: bool = False,
+):
+    audio_features = get_sample_audio_features(config, device, batch_size, sequence_length, use_fp16)
+    return {"audio_features": audio_features}
+
+
+# Create inputs for encoder component + first pass through decoder component of Whisper
+def get_sample_encoder_decoder_init_inputs(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    decoder_sequence_length: int,
+    encoder_sequence_length: int = 3000,
+    use_fp16: bool = False,
+    use_int32: bool = True,
+):
+    audio_features = get_sample_audio_features(config, device, batch_size, encoder_sequence_length, use_fp16)
+    decoder_input_ids = get_sample_decoder_input_ids(config, device, batch_size, decoder_sequence_length, use_int32)
+    return {"audio_features": audio_features, "decoder_input_ids": decoder_input_ids}
+
+
+# Create inputs for decoder component of Whisper
+# Inputs for first pass through the decoder (i.e. decoder-init): decoder_input_ids, encoder_hidden_states
+# Inputs for subsequent passes through the decoder (i.e. decoder-with-past): decoder_input_ids, past_key_values
+def get_sample_decoder_inputs(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    past_sequence_length: int,
+    sequence_length: int,
+    use_fp16: bool = False,
+    use_int32: bool = True,
+):
+    decoder_input_ids = get_sample_decoder_input_ids(config, device, batch_size, sequence_length, use_int32)
+    encoder_hidden_states = get_sample_encoder_hidden_states(config, device, batch_size, use_fp16)
+    past_key_values = get_sample_past_key_values(config, device, batch_size, past_sequence_length, use_fp16)
+    return {
+        "decoder_input_ids": decoder_input_ids,
+        "encoder_hidden_states": encoder_hidden_states,
+        "past_key_values": past_key_values,
+    }
+
+
+# Create inputs for timestamps component of Whisper
+def get_sample_jump_times_inputs(
+    config: WhisperConfig,
+    device: torch.device,
+    batch_size: int,
+    sequence_length: int,
+    num_alignment_heads: int,
+    sot_sequence_length: int,
+    segment_length: int,
+    use_fp16: bool = False,
+    use_int32: bool = True,
+):
+    alignment_heads = get_sample_alignment_heads(config, device, num_alignment_heads, use_int32)
+    # lengths need to be int64 because subsequent 'Slice' ops only take int64 inputs
+    sot_sequence_length = get_sample_sot_sequence_length(device, sot_sequence_length)
+    segment_length = get_sample_segment_length(device, segment_length)
+    QKs = get_sample_QKs(config, device, batch_size, sequence_length, use_fp16)  # noqa: N806
+    return {
+        "alignment_heads": alignment_heads,
+        "sot_sequence_length": sot_sequence_length,
+        "segment_length": segment_length,
+        "QKs": QKs,
+    }
+
+
+# Convert PyTorch inputs to ONNX Runtime inputs
+def convert_inputs_for_ort(
+    inputs: dict,
+    model: InferenceSession,
+):
+    self_attn_kv_caches, cross_attn_kv_caches = None, None
+    batch_size, num_heads, past_seq_len, head_size = 0, 0, 0, 0
+    num_beams, max_seq_len = 1, 448
+    if "past_key_values" in inputs:
+        (self_attn_kv_caches, cross_attn_kv_caches) = group_past_key_values(inputs["past_key_values"])
+        batch_size, num_heads, past_seq_len, head_size = self_attn_kv_caches[0].shape
+
+    ort_inputs = {}
+    model_inputs = list(map(lambda i: i.name, model.get_inputs()))  # noqa: C417
+    use_buffer_sharing = "cache_indirection" in model_inputs
+    for name in model_inputs:
+        if name in {"audio_features", "encoder_input_ids"}:
+            # Encoder input
+            ort_inputs[name] = inputs["audio_features"].detach().cpu().numpy()
+        elif name == "encoder_hidden_states":
+            # Encoder output
+            ort_inputs[name] = inputs["encoder_hidden_states"].detach().cpu().numpy()
+        elif name in {"decoder_input_ids", "input_ids"}:
+            # Decoder input
+            ort_inputs[name] = inputs["decoder_input_ids"].detach().cpu().numpy()
+        elif "past_key_self" in name or "past_value_self" in name:
+            # Decoder input
+            orig_kv_cache = self_attn_kv_caches.pop(0).detach().cpu().numpy()
+            if use_buffer_sharing:
+                new_kv_cache = np.zeros((batch_size, num_heads, max_seq_len, head_size), dtype=orig_kv_cache.dtype)
+                new_kv_cache[:batch_size, :num_heads, :past_seq_len, :head_size] = orig_kv_cache
+                ort_inputs[name] = new_kv_cache
+            else:
+                ort_inputs[name] = orig_kv_cache
+        elif "past_key_cross" in name or "past_value_cross" in name:
+            # Decoder input
+            orig_kv_cache = cross_attn_kv_caches.pop(0).detach().cpu().numpy()
+            ort_inputs[name] = orig_kv_cache
+        elif name == "past_sequence_length":
+            # Decoder input
+            ort_inputs[name] = np.array([past_seq_len], dtype=np.int32)
+        elif name == "cache_indirection":
+            # Decoder input
+            ort_inputs[name] = np.zeros((batch_size, num_beams, max_seq_len), dtype=np.int32)
+        elif name == "alignment_heads":
+            # Jump times input
+            ort_inputs[name] = inputs["alignment_heads"].detach().cpu().numpy()
+        elif name == "sot_sequence_length":
+            # Jump times input
+            ort_inputs[name] = inputs["sot_sequence_length"].detach().cpu().numpy()
+        elif name == "segment_length":
+            # Jump times input
+            ort_inputs[name] = inputs["segment_length"].detach().cpu().numpy()
+        elif "cross_qk" in name:
+            # Jump times input
+            ort_inputs[name] = inputs["QKs"].pop(0).detach().cpu().numpy()
+        else:
+            raise ValueError(f"Unknown name not recognized: {name}")
+
+    return ort_inputs
+
+
+# Get dynamic axes for all inputs and outputs to the model
+def get_model_dynamic_axes(
+    config: WhisperConfig,
+    input_names: list[str],
+    output_names: list[str],
+):
+    dynamic_axes = {}
+    for name in input_names + output_names:
+        if name in {"audio_features", "encoder_input_ids"}:
+            # shape is (batch_size, num_mels, num_frames)
+            dynamic_axes[name] = {0: "batch_size"}
+        elif name in {"input_ids", "decoder_input_ids"}:
+            # shape is (batch_size, sequence_length)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif name == "alignment_heads":
+            # shape is (num_alignment_heads, 2)
+            dynamic_axes[name] = {0: "num_alignment_heads"}
+        elif name in {"sot_sequence_length", "segment_length"}:
+            # shape is (1)
+            pass
+        elif name == "logits":
+            # shape is (batch_size, sequence_length, vocab_size)
+            dynamic_axes[name] = {0: "batch_size", 1: "sequence_length"}
+        elif name == "encoder_hidden_states":
+            # shape is (batch_size, num_frames // 2, hidden_size)
+            dynamic_axes[name] = {0: "batch_size"}
+        elif "past_key_self" in name or "past_value_self" in name:
+            # shape is (batch_size, num_heads, past_sequence_length, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "past_sequence_length"}
+        elif "present_key_self" in name or "present_value_self" in name:
+            # shape is (batch_size, num_heads, past_sequence_length + sequence_length, head_size),
+            # which is equal to (batch_size, num_heads, total_sequence_length, head_size)
+            dynamic_axes[name] = {0: "batch_size", 2: "total_sequence_length"}
+        elif (
+            "past_key_cross" in name
+            or "past_value_cross" in name
+            or "present_key_cross" in name
+            or "present_value_cross" in name
+        ):
+            # shape is (batch_size, num_heads, num_frames // 2, head_size)
+            dynamic_axes[name] = {0: "batch_size"}
+        elif "cross_qk" in name:
+            # shape is (batch_size, num_heads, source_sequence_length, target_sequence_length)
+            dynamic_axes[name] = {0: "batch_size", 2: "sequence_length"}
+        elif "jump_times" in name:
+            # shape is (batch_size, max_length)
+            dynamic_axes[name] = {0: "batch_size", 1: "max_length"}
+        else:
+            raise Exception(f"Unknown input or output name found: {name}")
+    return dynamic_axes
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_jump_times.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_jump_times.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c81867a4f7a7b7d1d39b44154fb0e06fdc9da61
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/models/whisper/whisper_jump_times.py
@@ -0,0 +1,479 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import subprocess
+import sys
+import tempfile
+import textwrap
+from pathlib import Path
+
+import numpy as np
+import onnx
+import torch
+import torch.nn.functional as F
+import torch.utils.cpp_extension
+from onnx_model import OnnxModel
+from transformers import WhisperConfig
+from whisper_inputs import convert_inputs_for_ort, get_model_dynamic_axes, get_sample_jump_times_inputs
+
+from onnxruntime import InferenceSession
+from onnxruntime.tools import pytorch_export_contrib_ops
+
+logger = logging.getLogger(__name__)
+
+##################################################
+# Functions that have to be outside of the class
+# for torch.jit.script_if_tracing to work
+##################################################
+
+
+@torch.jit.script_if_tracing
+def index_QKs(alignment_heads: torch.Tensor, QKs: list[torch.Tensor]):  # noqa: N802
+    """
+    Compute the following to get stacked QK tensor that has been indexed for the desired attention heads:
+    weights = torch.stack([QKs[_l][:, _h] for _l, _h in alignment_heads], dim=1)
+    """
+    indexed_QKs = []  # noqa: N806
+    for pair in alignment_heads:
+        # Each QK is of shape (batch_size, num_heads, sequence_length, num_frames // 2)
+        # The `QKs[_l]` selects the right QK from the list of QKs
+        # The `QKs[_l][:, _h]` selects the right attention heads from the chosen QK. The `:` is to do this for the batch dim.
+        #
+        # PyTorch:
+        # QKs[_l] is of shape (batch_size, num_heads, sequence_length, num_frames // 2)
+        # QKs[_l][:, _h] is of shape (batch_size, sequence_length, num_frames // 2)
+        #
+        # ONNX:
+        # QKs[_l] is of shape (batch_size, num_heads, sequence_length, num_frames // 2)
+        # QKs[_l][:, _h] is of shape (batch_size, 1, sequence_length, num_frames // 2) because
+        # the `[:, _h]` operation maps to a Gather op and that op does not reduce dimensions
+        _l, _h = pair[0], pair[1]
+        indexed_QKs.append(QKs[_l][:, _h])
+
+    # PyTorch:
+    # torch.stack will return a tensor of shape (batch_size, num_alignment_heads, sequence_length, num_frames // 2).
+    #
+    # ONNX:
+    # torch.stack will return a tensor of shape (batch_size, num_alignment_heads, 1, sequence_length, num_frames // 2)
+    # because the Gather op does not reduce dimensions. To remove the unneeded dimension, torch.squeeze with a specified
+    # dim (dim = 2) is added. The torch.squeeze op with a specified dim only runs if the specified dim has a size of 1.
+    # Since the dim won't be of size 1 in the PyTorch tensor but it is of size 1 in the ONNX tensor, it will be a no-op
+    # in PyTorch and an op in ONNX. Thus, the Squeeze op will only affect the ONNX model.
+    weights = torch.stack(indexed_QKs, dim=1)
+    weights = torch.squeeze(weights, dim=2)
+    return weights
+
+
+def jump_timings(text_indices, time_indices):
+    """
+    Calculate jump times from text_indices and time_indices where
+    text_indices and time_indices are both 1d vectors
+    """
+    TOKENS_PER_SECOND = 50.0  # noqa: N806
+    diff = text_indices[1:] - text_indices[:-1]
+    padding = torch.tensor([1], dtype=torch.int32)
+    jumps = torch.cat((padding, diff)).to(torch.bool)
+    jump_times = time_indices[jumps].to(torch.float) / TOKENS_PER_SECOND
+    return jump_times
+
+
+def padded_jump_from_dtw(matrix_2d: torch.Tensor, max_length: torch.Tensor):
+    """
+    Run Dynamic Time Warping (DTW) on batched tensor
+    """
+    trace = torch.ops.onnxruntime.DynamicTimeWarping(matrix_2d)
+    text_indices = trace[0, :]
+    time_indices = trace[1, :]
+    jump_times = jump_timings(text_indices, time_indices)
+    return F.pad(jump_times, [0, int((max_length - jump_times.size(-1)).item())], mode="constant", value=-1.0)
+
+
+@torch.jit.script_if_tracing
+def batch_jump_times(matrix: torch.Tensor, max_decoded_length: torch.Tensor):
+    """
+    Compute the following to calculate jump times for all batches:
+    batched_jump_times = torch.stack([self.padded_jump_from_dtw(matrix[b], max_decoded_length) for b in range(matrix.size(0))])
+    """
+    list_of_jump_times = []
+    for b in range(matrix.size(0)):
+        jump_times = padded_jump_from_dtw(matrix[b], max_decoded_length)
+        list_of_jump_times.append(jump_times)
+    batched_jump_times = torch.stack(list_of_jump_times)
+    return batched_jump_times
+
+
+class WhisperJumpTimes(torch.nn.Module):
+    """Whisper jump times component"""
+
+    def __init__(self, config: WhisperConfig, device: torch.device, cache_dir: str | os.PathLike):
+        super().__init__()
+        self.config = config
+        self.device = device
+        self.cache_dir = cache_dir
+
+        self.filter_width = 7
+        self.qk_scale = 1.0
+
+    def median_filter(self, weights: torch.Tensor):
+        """
+        Apply a median filter of width `filter_width` along the last dimension of `weights`
+        """
+        pad_width = self.filter_width // 2
+        x = F.pad(weights, (pad_width, pad_width, 0, 0), mode="reflect")
+        x_unfolded = torch.ops.onnxruntime.UnfoldTensor(x, -1, self.filter_width, 1)
+        result = torch.select(x_unfolded.sort()[0], dim=-1, index=pad_width)
+        return result
+
+    def forward(
+        self,
+        alignment_heads: torch.Tensor,
+        sot_sequence_length: torch.Tensor,
+        segment_length: torch.Tensor,
+        QKs: list[torch.Tensor],
+    ):
+        # Get stacked QKs tensor
+        weights = index_QKs(alignment_heads, QKs)
+        weights = weights[:, :, : segment_length // 2]
+        weights = weights.to(torch.float32)
+
+        weights = (weights * self.qk_scale).softmax(dim=-1)
+        std, mean = torch.std_mean(weights, dim=-2, keepdim=True, unbiased=False)
+        weights = (weights - mean) / std
+        weights = self.median_filter(weights)
+
+        matrix = torch.mean(weights, 1)
+        matrix = -matrix[:, sot_sequence_length:-1]
+
+        max_decoded_length = torch.tensor([matrix.size(1)], dtype=torch.int64)
+        batched_jump_times = batch_jump_times(matrix, max_decoded_length)
+        return batched_jump_times
+
+    def input_names(self):
+        input_names = [
+            "alignment_heads",
+            "sot_sequence_length",
+            "segment_length",
+            *[f"cross_qk_{i}" for i in range(self.config.decoder_layers)],
+        ]
+        return input_names
+
+    def output_names(self):
+        output_names = ["jump_times"]
+        return output_names
+
+    def inputs(self, use_fp16_inputs: bool, use_int32_inputs: bool, return_dict: bool = False):
+        inputs = get_sample_jump_times_inputs(
+            self.config,
+            self.device,
+            batch_size=2,
+            sequence_length=8,
+            num_alignment_heads=6,
+            sot_sequence_length=3,
+            segment_length=1332,
+            use_fp16=use_fp16_inputs,
+            use_int32=use_int32_inputs,
+        )
+        if return_dict:
+            return inputs
+        return (
+            inputs["alignment_heads"],
+            inputs["sot_sequence_length"],
+            inputs["segment_length"],
+            inputs["QKs"],
+        )
+
+    def create_torch_ops(self):
+        """
+        1) Create UnfoldTensor and DynamicTimeWarping as torch ops
+        3) Provide a symbolic mapping from torch ops to ORT contrib ops
+
+        See https://pytorch.org/tutorials/advanced/torch_script_custom_ops.html#building-with-jit-compilation
+        for more details on how this works.
+        """
+        # Set torch extensions directory to cache directory
+        os.environ["TORCH_EXTENSIONS_DIR"] = self.cache_dir
+
+        # Try to import `ninja` pip package
+        try:
+            assert torch.utils.cpp_extension.verify_ninja_availability()
+        except Exception as e:
+            logger.error(f"An error occurred while verifying `ninja` is available: {e}", exc_info=True)  # noqa: G201
+            install_cmd = [sys.executable, "-m", "pip", "install", "ninja"]
+            logger.warning("Could not import `ninja`. Attempting to install `ninja` via `%s`.", " ".join(install_cmd))
+            subprocess.run(install_cmd, check=True)
+
+        # Create UnfoldTensor torch op
+        unfold_op_source = textwrap.dedent("""\
+        #include "torch/script.h"
+
+        torch::Tensor UnfoldTensor(torch::Tensor input, int64_t dim, int64_t size, int64_t step) {
+          return input.unfold(dim, size, step);
+        }
+
+        // namespace is onnxruntime
+        static auto registry = torch::RegisterOperators("onnxruntime::UnfoldTensor", &UnfoldTensor);
+        """)
+
+        torch.utils.cpp_extension.load_inline(
+            name="UnfoldTensor",
+            cpp_sources=unfold_op_source,
+            is_python_module=False,
+            verbose=True,
+        )
+
+        # Create DynamicTimeWarping torch op
+        dtw_op_source = textwrap.dedent("""\
+        #include "torch/script.h"
+        #include "torch/torch.h"
+        #include <stdexcept>
+        #include <tuple>
+        #include <vector>
+
+        torch::Tensor Backtrace(torch::Tensor trace) {
+          int64_t i = trace.size(0) - 1;
+          int64_t j = trace.size(1) - 1;
+          trace.index({0, torch::indexing::Slice()}) = 2;
+          trace.index({torch::indexing::Slice(), 0}) = 1;
+
+          std::vector<int32_t> result_vec;
+          while (i > 0 || j > 0) {
+            result_vec.push_back(static_cast<int32_t>(i - 1));
+            result_vec.push_back(static_cast<int32_t>(j - 1));
+            int value = trace[i][j].item<int>();
+
+            if (value == 0) {
+              i--;
+              j--;
+            } else if (value == 1) {
+              i--;
+            } else if (value == 2) {
+              j--;
+            } else {
+              throw std::runtime_error("Unexpected trace[i, j]");
+            }
+          }
+
+          // Compute result[::-1, :].T
+          torch::Tensor result = torch::from_blob(result_vec.data(), {static_cast<long int>(result_vec.size() / 2), 2}, torch::kInt32).clone();
+          torch::Tensor reversed = result.flip(0); // result[::-1, :]
+          torch::Tensor transposed = reversed.transpose(0, 1); // .T
+          return transposed;
+        }
+
+        torch::Tensor DynamicTimeWarping(torch::Tensor x) {
+          int64_t N = x.size(0);
+          int64_t M = x.size(1);
+          torch::Tensor cost = torch::full({N + 1, M + 1}, std::numeric_limits<float>::infinity(), torch::dtype(torch::kFloat32));
+          torch::Tensor trace = torch::full({N + 1, M + 1}, -1, torch::dtype(torch::kFloat32));
+
+          cost[0][0] = 0;
+          for (int j = 1; j < M + 1; j++) {
+            for (int i = 1; i < N + 1; i++) {
+              float c0 = cost[i - 1][j - 1].item<float>();
+              float c1 = cost[i - 1][j].item<float>();
+              float c2 = cost[i][j - 1].item<float>();
+
+              float c = 0;
+              float t = 0;
+
+              if (c0 < c1 && c0 < c2) {
+                c = c0;
+                t = 0;
+              } else if (c1 < c0 && c1 < c2) {
+                c = c1;
+                t = 1;
+              } else {
+                c = c2;
+                t = 2;
+              }
+
+              cost[i][j] = x[i - 1][j - 1].item<float>() + c;
+              trace[i][j] = t;
+            }
+          }
+
+          return Backtrace(trace);
+        }
+
+        // namespace is onnxruntime
+        static auto registry = torch::RegisterOperators("onnxruntime::DynamicTimeWarping", &DynamicTimeWarping);
+        """)
+
+        torch.utils.cpp_extension.load_inline(
+            name="DynamicTimeWarping",
+            cpp_sources=dtw_op_source,
+            is_python_module=False,
+            verbose=True,
+        )
+
+        # Create symbolic mapping from torch ops to ORT contrib ops
+        pytorch_export_contrib_ops.register()
+
+    def export_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        verbose: bool = True,
+        use_external_data_format: bool = False,
+        use_fp16_inputs: bool = False,
+        use_int32_inputs: bool = True,
+    ):
+        """Export word-level timestamps to ONNX
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): provider to use for verifying parity on ONNX model
+            verbose (bool, optional): print verbose information. Defaults to True.
+            use_external_data_format (bool, optional): use external data format or not. Defaults to False.
+            use_fp16_inputs (bool, optional): use float16 inputs for the audio_features. Defaults to False.
+            use_int32_inputs (bool, optional): use int32 inputs for the decoder_input_ids. Defaults to True.
+        """
+        # Shape of timestamps's tensors:
+        # Inputs:
+        #    alignment_heads: (num_alignment_heads, 2)
+        #    sot_sequence_length: (1)
+        #    segment_length: (1)
+        #    cross_qk_*: (batch_size, num_heads, sequence_length, num_frames // 2)
+        # Outputs:
+        #    jump_times: (batch_size, max_length)
+
+        # Definitions:
+        # alignment_heads: the attention head indices where the Q*K values are highly correlated with word-level timestamps
+        # (i.e. the alignment between audio and text tokens)
+        # This is calculated as follows:
+        #
+        # ```
+        # import base64
+        # import gzip
+        # import numpy as np
+        # import torch
+        #
+        # # base85-encoded (n_layers, n_heads) boolean arrays indicating the cross-attention heads that are
+        # # highly correlated to the word-level timing, i.e. the alignment between audio and text tokens.
+        # _ALIGNMENT_HEADS = {
+        #     "tiny.en": b"ABzY8J1N>@0{>%R00Bk>$p{7v037`oCl~+#00",
+        #     "tiny": b"ABzY8bu8Lr0{>%RKn9Fp%m@SkK7Kt=7ytkO",
+        #     "base.en": b"ABzY8;40c<0{>%RzzG;p*o+Vo09|#PsxSZm00",
+        #     "base": b"ABzY8KQ!870{>%RzyTQH3`Q^yNP!>##QT-<FaQ7m",
+        #     "small.en": b"ABzY8>?_)10{>%RpeA61k&I|OI3I$65C{;;pbCHh0B{qLQ;+}v00",
+        #     "small": b"ABzY8DmU6=0{>%Rpa?J`kvJ6qF(V^F86#Xh7JUGMK}P<N0000",
+        #     "medium.en": b"ABzY8usPae0{>%R7<zz_OvQ{)4kMa0BMw6u5rT}kRKX;$NfYBv00*Hl@qhsU00",
+        #     "medium": b"ABzY8B0Jh+0{>%R7}kK1fFL7w6%<-Pf*t^=N)Qr&0RR9",
+        #     "large-v1": b"ABzY8r9j$a0{>%R7#4sLmoOs{s)o3~84-RPdcFk!JR<kSfC2yj",
+        #     "large-v2": b"ABzY8zd+h!0{>%R7=D0pU<_bnWW*tkYAhobTNnu$jnkEkXqp)j;w1Tzk)UH3X%SZd&fFZ2fC2yj",
+        #     "large-v3": b"ABzY8gWO1E0{>%R7(9S+Kn!D~%ngiGaR?*L!iJG9p-nab0JQ=-{D1-g00",
+        #     "large": b"ABzY8gWO1E0{>%R7(9S+Kn!D~%ngiGaR?*L!iJG9p-nab0JQ=-{D1-g00",
+        #     "large-v3-turbo": b"ABzY8j^C+e0{>%RARaKHP%t(lGR*)0g!tONPyhe`",
+        #     "turbo": b"ABzY8j^C+e0{>%RARaKHP%t(lGR*)0g!tONPyhe`",
+        # }
+        #
+        # model_name = "large-v3-turbo"
+        # array = np.frombuffer(
+        #     gzip.decompress(base64.b85decode(_ALIGNMENT_HEADS[model_name])), dtype=bool
+        # ).copy()
+        # mask = torch.from_numpy(array).reshape(
+        #     self.dims.n_text_layer, self.dims.n_text_head
+        # )
+        # self.alignment_heads = mask.to_sparse().indices().T
+        # ```
+        #
+        # sot_sequence_length: the length of the start-of-transcription sequence before the first token is generated
+        # Typically the start-of-transcription sequence is [<|startoftranscription|>, <|language_token|>, <|task_token|>]
+        # so its length is 3.
+        #
+        # segment_length: the length (in frames) of the audio segment that is being transcribed
+        #
+        # cross_qk_*: the Q*K values for the cross-attention blocks in the decoder
+        # Every decoder layer has a self-attention block and a cross-attention block so there are `n` cross-attention blocks
+        # where `n` is the number of decoder layers.
+        #
+        # jump_times: the timings where jumps occur in speech
+        # This allows us to detect when a word began to be spoken by the speaker (start_times) and when a word was finished
+        # being spoken by the speaker (end_times).
+
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs)
+        input_names = self.input_names()
+        output_names = self.output_names()
+        dynamic_axes = get_model_dynamic_axes(self.config, input_names, output_names)
+
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+        with tempfile.TemporaryDirectory() as tmp_dir_name:
+            temp_onnx_model_path = os.path.join(tmp_dir_name, "encoder.onnx")
+            Path(temp_onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+            out_path = temp_onnx_model_path if use_external_data_format else onnx_model_path
+
+            # Create torch ops and map them to ORT contrib ops before export
+            self.create_torch_ops()
+            torch.onnx.export(
+                self,
+                args=inputs,
+                f=out_path,
+                export_params=True,
+                input_names=input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                opset_version=17,
+                do_constant_folding=True,
+                verbose=verbose,
+                custom_opsets={"com.microsoft": 1},
+            )
+
+            if use_external_data_format:
+                model = onnx.load_model(out_path, load_external_data=use_external_data_format)
+                OnnxModel.save(
+                    model,
+                    onnx_model_path,
+                    save_as_external_data=True,
+                    all_tensors_to_one_file=True,
+                )
+
+        self.verify_onnx(onnx_model_path, provider, use_fp16_inputs, use_int32_inputs)
+
+    def verify_onnx(
+        self,
+        onnx_model_path: str,
+        provider: str,
+        use_fp16_inputs: bool,
+        use_int32_inputs: bool,
+    ):
+        """Verify ONNX model outputs and PyTorch model outputs match
+
+        Args:
+            onnx_model_path (str): path to save ONNX model
+            provider (str): execution provider for ONNX model
+            use_fp16_inputs (bool, optional): use float16 inputs for the cross_qk_{i}
+            use_int32_inputs (bool, optional): use int32 inputs for the alignment_heads and sot_sequence_length
+        """
+        # Shape of jump times's tensors:
+        # Inputs:
+        #    alignment_heads: (num_alignment_heads, 2)
+        #    sot_sequence_length: (1)
+        #    segment_length: (1)
+        #    cross_qk_*: (batch_size, num_heads, sequence_length, num_frames // 2)
+        # Outputs:
+        #    jump_times: (batch_size, max_length)
+        inputs = self.inputs(use_fp16_inputs=use_fp16_inputs, use_int32_inputs=use_int32_inputs, return_dict=True)
+
+        # Run PyTorch model
+        pt_outputs = (
+            self.forward(
+                inputs["alignment_heads"], inputs["sot_sequence_length"], inputs["segment_length"], inputs["QKs"]
+            )
+            .detach()
+            .cpu()
+            .numpy()
+        )
+
+        # Run ONNX model
+        sess = InferenceSession(onnx_model_path, providers=[provider])
+        ort_outputs = sess.run(None, convert_inputs_for_ort(inputs, sess))
+
+        # Calculate output difference
+        diff = np.abs(pt_outputs - ort_outputs)
+        print("Comparing batched jump_times...", flush=True)
+        print(f"Max diff: {np.max(diff)}", flush=True)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_exporter.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_exporter.py
new file mode 100644
index 0000000000000000000000000000000000000000..6b8cadc41c3b3eba2c9103cb3ed23233b07262ca
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_exporter.py
@@ -0,0 +1,719 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+from pathlib import Path
+
+import numpy
+import torch
+from affinity_helper import AffinitySetting
+from benchmark_helper import OptimizerInfo, Precision, create_onnxruntime_session
+from huggingface_models import MODEL_CLASSES
+from quantize_helper import QuantizeHelper
+from torch_onnx_export_helper import torch_onnx_export
+from transformers import AutoConfig, AutoFeatureExtractor, AutoTokenizer, LxmertConfig, TransfoXLConfig
+
+from onnxruntime.transformers.models.gpt2.gpt2_helper import (
+    PRETRAINED_GPT2_MODELS,
+    GPT2ModelNoPastState,
+    TFGPT2ModelNoPastState,
+)
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+
+logger = logging.getLogger(__name__)
+
+# Workaround by replacing torch.triu using self-defined op
+# Since torch.triu cannot be exported to ONNX. See https://github.com/pytorch/pytorch/issues/32968
+torch_func = {"triu": torch.triu}
+
+
+def triu_onnx(x, diagonal=0, out=None):
+    assert out is None
+    assert len(x.shape) == 2 and x.size(0) == x.size(1)
+
+    torch_triu = torch_func["triu"]
+    template = torch_triu(torch.ones((1024, 1024), dtype=torch.uint8), diagonal)
+    mask = template[: x.size(0), : x.size(1)]
+    return torch.where(mask.bool(), x, torch.zeros_like(x))
+
+
+def replace_torch_functions():
+    torch.triu = triu_onnx
+
+
+def restore_torch_functions():
+    torch.triu = torch_func["triu"]
+
+
+def create_onnxruntime_input(vocab_size, batch_size, sequence_length, input_names, config, data_type=numpy.int64):
+    if config.model_type in ["vit", "swin"]:
+        input_ids = numpy.random.rand(batch_size, 3, config.image_size, config.image_size).astype(numpy.float32)
+        inputs = {"pixel_values": input_ids}
+        return inputs
+
+    input_ids = numpy.random.randint(low=0, high=vocab_size - 1, size=(batch_size, sequence_length), dtype=data_type)
+    inputs = {"input_ids": input_ids}
+
+    if "attention_mask" in input_names:
+        attention_mask = numpy.ones([batch_size, sequence_length], dtype=data_type)
+        inputs["attention_mask"] = attention_mask
+
+    if "token_type_ids" in input_names:
+        segment_ids = numpy.zeros([batch_size, sequence_length], dtype=data_type)
+        inputs["token_type_ids"] = segment_ids
+
+    if config.is_encoder_decoder:
+        inputs["decoder_input_ids"] = input_ids
+
+    if isinstance(config, LxmertConfig):
+        inputs["visual_feats"] = numpy.random.randn(1, 1, config.visual_feat_dim).astype(numpy.float32)
+        inputs["visual_pos"] = numpy.random.randn(1, 1, config.visual_pos_dim).astype(numpy.float32)
+    if isinstance(config, TransfoXLConfig):
+        inputs["tf_transfo_xl_model/transformer/pos_emb/einsum/Einsum/inputs_1:0"] = numpy.zeros(
+            [config.hidden_size], dtype=numpy.float32
+        )
+    return inputs
+
+
+def filter_inputs(inputs, input_names):
+    remaining_model_inputs = {}
+    for input_name in input_names:
+        if input_name in inputs:
+            remaining_model_inputs[input_name] = inputs[input_name]
+    return remaining_model_inputs
+
+
+def flatten(inputs):
+    return [[flatten(i) for i in inputs] if isinstance(inputs, (list, tuple)) else inputs]
+
+
+def update_flatten_list(inputs, res_list):
+    for i in inputs:
+        res_list.append(i) if not isinstance(i, (list, tuple)) else update_flatten_list(i, res_list)
+    return res_list
+
+
+def build_dynamic_axes(example_inputs, outputs_flatten):
+    sequence_length = example_inputs["input_ids"].shape[-1]
+
+    dynamic_axes = {key: {0: "batch_size", 1: "seq_len"} for key in example_inputs}
+
+    output_names = ["output_" + str(i + 1) for i in range(len(outputs_flatten))]
+    for i, output_name in enumerate(output_names):
+        dynamic_axes[output_name] = {0: "batch_size"}
+        dims = outputs_flatten[i].shape
+        for j, dim in enumerate(dims):
+            if dim == sequence_length:
+                dynamic_axes[output_name].update({j: "seq_len"})
+    return dynamic_axes, output_names
+
+
+def validate_onnx_model(
+    onnx_model_path,
+    example_inputs,
+    example_outputs_flatten,
+    use_gpu,
+    fp16,
+    output_names=None,
+):
+    test_session = create_onnxruntime_session(onnx_model_path, use_gpu, enable_all_optimization=False)
+    if test_session is None:
+        logger.error(f"{onnx_model_path} is an invalid ONNX model")
+        return False
+
+    logger.info(f"{onnx_model_path} is a valid ONNX model")
+
+    # Compare the inference result with PyTorch or Tensorflow
+    example_ort_inputs = {k: t.numpy() for k, t in example_inputs.items()}
+    example_ort_outputs = test_session.run(output_names, example_ort_inputs)
+    if len(example_outputs_flatten) != len(example_ort_outputs):
+        logger.error(
+            f"Number of output tensors expected {len(example_outputs_flatten)}, got {len(example_ort_outputs)}"
+        )
+        return False
+
+    for i in range(len(example_outputs_flatten)):
+        abs_diff = numpy.amax(numpy.abs(example_ort_outputs[i] - example_outputs_flatten[i].cpu().numpy()))
+        if abs_diff > 1e-4:
+            logger.info(f"Max absolute diff={abs_diff} for output tensor {i}")
+
+        rtol = 5e-02 if fp16 else 1e-4
+        atol = 1e-01 if fp16 else 1e-4
+        if not numpy.allclose(
+            example_ort_outputs[i],
+            example_outputs_flatten[i].cpu().numpy(),
+            rtol=rtol,
+            atol=atol,
+        ):
+            logger.error(f"Output tensor {i} is not close: rtol={rtol}, atol={atol}")
+            return False
+
+    logger.info(f"inference result of onnxruntime is validated on {onnx_model_path}")
+    return True
+
+
+def get_onnx_file_path(
+    onnx_dir: str,
+    model_name: str,
+    input_count: int,
+    optimized_by_script: bool,
+    use_gpu: bool,
+    precision: Precision,
+    optimized_by_onnxruntime: bool,
+    use_external_data: bool,
+):
+    from re import sub  # noqa: PLC0415
+
+    normalized_model_name = sub(r"[^a-zA-Z0-9_]", "_", model_name)
+
+    if not optimized_by_script:
+        filename = f"{normalized_model_name}_{input_count}"
+    else:
+        device = "gpu" if use_gpu else "cpu"
+        filename = f"{normalized_model_name}_{input_count}_{precision}_{device}"
+
+    if optimized_by_onnxruntime:
+        filename += "_ort"
+
+    directory = onnx_dir
+    # ONNXRuntime will not write external data so the raw and optimized models shall be in same directory.
+    if use_external_data and not optimized_by_onnxruntime:
+        directory = os.path.join(onnx_dir, filename)
+        if not os.path.exists(directory):
+            os.makedirs(directory)
+
+    return os.path.join(directory, f"{filename}.onnx")
+
+
+def add_filename_suffix(file_path: str, suffix: str) -> str:
+    """
+    Append a suffix at the filename (before the extension).
+    Args:
+        path: pathlib.Path The actual path object we would like to add a suffix
+        suffix: The suffix to add
+    Returns: path with suffix appended at the end of the filename and before extension
+    """
+    path = Path(file_path)
+    return str(path.parent.joinpath(path.stem + suffix).with_suffix(path.suffix))
+
+
+def optimize_onnx_model_by_ort(onnx_model_path, ort_model_path, use_gpu, overwrite, model_fusion_statistics):
+    if overwrite or not os.path.exists(ort_model_path):
+        Path(ort_model_path).parent.mkdir(parents=True, exist_ok=True)
+        from optimizer import get_fusion_statistics, optimize_by_onnxruntime  # noqa: PLC0415
+
+        # Use onnxruntime to optimize model, which will be saved to *_ort.onnx
+        _ = optimize_by_onnxruntime(
+            onnx_model_path,
+            use_gpu=use_gpu,
+            optimized_model_path=ort_model_path,
+            opt_level=99,
+        )
+        model_fusion_statistics[ort_model_path] = get_fusion_statistics(ort_model_path)
+    else:
+        logger.info(f"Skip optimization since model existed: {ort_model_path}")
+
+
+def optimize_onnx_model(
+    onnx_model_path,
+    optimized_model_path,
+    model_type,
+    num_attention_heads,
+    hidden_size,
+    use_gpu,
+    precision,
+    use_raw_attention_mask,
+    overwrite,
+    model_fusion_statistics,
+    use_external_data_format,
+    optimization_options=None,
+):
+    if overwrite or not os.path.exists(optimized_model_path):
+        Path(optimized_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+        from fusion_options import FusionOptions  # noqa: PLC0415
+        from optimizer import optimize_model  # noqa: PLC0415
+
+        if optimization_options is None:
+            optimization_options = FusionOptions(model_type)
+        optimization_options.use_raw_attention_mask(use_raw_attention_mask)
+        if precision == Precision.FLOAT16:
+            optimization_options.enable_gelu_approximation = True
+        if precision == Precision.INT8:
+            optimization_options.enable_embed_layer_norm = False
+
+        # For swin models, the num_attention_heads is a list, which isn't supported yet, so set to 0 for now
+        if model_type == "swin":
+            num_attention_heads = 0
+            hidden_size = 0
+
+        # Use script to optimize model.
+        # Use opt_level <= 1 for models to be converted to fp16, because some fused op (like FusedGemm) has only fp32 and no fp16.
+        # It is better to be conservative so we use opt_level=0 here, in case MemcpyFromHost is added to the graph by OnnxRuntime.
+        opt_model = optimize_model(
+            onnx_model_path,
+            model_type,
+            num_heads=num_attention_heads,
+            hidden_size=hidden_size,
+            opt_level=0,
+            optimization_options=optimization_options,
+            use_gpu=use_gpu,
+            only_onnxruntime=False,
+        )
+        if model_type == "bert_keras" or model_type == "bert_tf":
+            opt_model.use_dynamic_axes()
+
+        model_fusion_statistics[optimized_model_path] = opt_model.get_fused_operator_statistics()
+
+        if precision == Precision.FLOAT16:
+            opt_model.convert_float_to_float16(keep_io_types=True)
+
+        opt_model.save_model_to_file(optimized_model_path, use_external_data_format)
+    else:
+        logger.info(f"Skip optimization since model existed: {optimized_model_path}")
+
+
+def modelclass_dispatcher(model_name, custom_model_class):
+    if custom_model_class is not None:
+        if custom_model_class in MODEL_CLASSES:
+            return custom_model_class
+        else:
+            raise Exception("Valid model class: " + " ".join(MODEL_CLASSES))
+
+    if model_name in PRETRAINED_GPT2_MODELS:
+        return "GPT2ModelNoPastState"
+
+    import re  # noqa: PLC0415
+
+    if re.search("-squad$", model_name) is not None:
+        return "AutoModelForQuestionAnswering"
+    elif re.search("-mprc$", model_name) is not None:
+        return "AutoModelForSequenceClassification"
+    elif re.search("gpt2", model_name) is not None:
+        return "AutoModelWithLMHead"
+
+    return "AutoModel"
+
+
+def load_pretrained_model(model_name, config, cache_dir, custom_model_class, is_tf_model=False):
+    model_class_name = modelclass_dispatcher(model_name, custom_model_class)
+
+    if model_class_name == "GPT2ModelNoPastState":
+        if is_tf_model:
+            return TFGPT2ModelNoPastState.from_pretrained(model_name, config=config, cache_dir=cache_dir)
+        else:
+            return GPT2ModelNoPastState.from_pretrained(model_name, config=config, cache_dir=cache_dir)
+
+    if is_tf_model:
+        model_class_name = "TF" + model_class_name
+
+    transformers_module = __import__("transformers", fromlist=[model_class_name])
+    logger.info(f"Model class name: {model_class_name}")
+    model_class = getattr(transformers_module, model_class_name)
+
+    return model_class.from_pretrained(model_name, config=config, cache_dir=cache_dir)
+
+
+def load_pt_model(model_name, model_class, cache_dir, config_modifier):
+    config = AutoConfig.from_pretrained(model_name, cache_dir=cache_dir)
+    if hasattr(config, "return_dict"):
+        config.return_dict = False
+
+    config_modifier.modify(config)
+
+    model = load_pretrained_model(model_name, config=config, cache_dir=cache_dir, custom_model_class=model_class)
+
+    return config, model
+
+
+def load_tf_model(model_name, model_class, cache_dir, config_modifier):
+    config = AutoConfig.from_pretrained(model_name, cache_dir=cache_dir)
+
+    config_modifier.modify(config)
+    # Loading tf model from transformers limits the cpu affinity to {0} when KMP_AFFINITY is set
+    # Restore the affinity after model loading for expected ORT performance
+    affinity_setting = AffinitySetting()
+    affinity_setting.get_affinity()
+    model = load_pretrained_model(
+        model_name,
+        config=config,
+        cache_dir=cache_dir,
+        custom_model_class=model_class,
+        is_tf_model=True,
+    )
+    affinity_setting.set_affinity()
+
+    return config, model
+
+
+# For test only
+def load_pt_model_from_tf(model_name):
+    # Note that we could get pt model from tf, but model source and its structure in this case is different from directly using
+    # load_pt_model() and load_tf_model() even with the same name. Therefore it should not be used for comparing with them
+    from convert_tf_models_to_pytorch import tf2pt_pipeline  # noqa: PLC0415
+
+    config, model = tf2pt_pipeline(model_name)
+
+    return config, model
+
+
+def validate_and_optimize_onnx(
+    model_name,
+    use_external_data_format,
+    model_type,
+    onnx_dir,
+    input_names,
+    use_gpu,
+    precision,
+    optimize_info,
+    validate_onnx,
+    use_raw_attention_mask,
+    overwrite,
+    config,
+    model_fusion_statistics,
+    onnx_model_path,
+    example_inputs,
+    example_outputs_flatten,
+    output_names,
+    fusion_options,
+):
+    is_valid_onnx_model = True
+    if validate_onnx:
+        is_valid_onnx_model = validate_onnx_model(
+            onnx_model_path,
+            example_inputs,
+            example_outputs_flatten,
+            use_gpu,
+            False,
+            output_names,
+        )
+    if optimize_info.name == OptimizerInfo.NOOPT.name:
+        return onnx_model_path, is_valid_onnx_model, config.vocab_size
+
+    if (
+        optimize_info.name == OptimizerInfo.BYSCRIPT.name
+        or precision == Precision.FLOAT16
+        or precision == Precision.INT8
+    ):  # Use script (optimizer.py) to optimize
+        optimized_model_path = get_onnx_file_path(
+            onnx_dir,
+            model_name,
+            len(input_names),
+            True,
+            use_gpu,
+            precision,
+            False,
+            use_external_data_format,
+        )
+        optimize_onnx_model(
+            onnx_model_path,
+            optimized_model_path,
+            model_type,
+            config.num_attention_heads,
+            config.hidden_size,
+            use_gpu,
+            precision,
+            use_raw_attention_mask,
+            overwrite,
+            model_fusion_statistics,
+            use_external_data_format,
+            fusion_options,
+        )
+
+        onnx_model_path = optimized_model_path
+        if validate_onnx:
+            is_valid_onnx_model = validate_onnx_model(
+                onnx_model_path,
+                example_inputs,
+                example_outputs_flatten,
+                use_gpu,
+                precision == Precision.FLOAT16,
+                output_names,
+            )
+
+        if precision == Precision.INT8:
+            logger.info(f"Quantizing model: {onnx_model_path}")
+            QuantizeHelper.quantize_onnx_model(onnx_model_path, onnx_model_path, use_external_data_format)
+            logger.info(f"Finished quantizing model: {onnx_model_path}")
+
+    if optimize_info.name == OptimizerInfo.BYORT.name:  # Use OnnxRuntime to optimize
+        if is_valid_onnx_model:
+            ort_model_path = add_filename_suffix(onnx_model_path, "_ort")
+            optimize_onnx_model_by_ort(
+                onnx_model_path,
+                ort_model_path,
+                use_gpu,
+                overwrite,
+                model_fusion_statistics,
+            )
+
+    return (
+        onnx_model_path,
+        is_valid_onnx_model,
+        config.num_labels if model_type in ["vit", "swin"] else config.vocab_size,
+    )
+
+
+def export_onnx_model_from_pt(
+    model_name,
+    opset_version,
+    use_external_data_format,
+    model_type,
+    model_class,
+    config_modifier,
+    cache_dir,
+    onnx_dir,
+    input_names,
+    use_gpu,
+    precision,
+    optimizer_info,
+    validate_onnx,
+    use_raw_attention_mask,
+    overwrite,
+    model_fusion_statistics,
+    fusion_options,
+):
+    config, model = load_pt_model(model_name, model_class, cache_dir, config_modifier)
+    # config, model = load_pt_model_from_tf(model_name)
+    model.cpu()
+
+    example_inputs = None
+    max_input_size = None
+
+    if model_type in ["vit", "swin"]:
+        image_processor = AutoFeatureExtractor.from_pretrained(model_name, cache_dir=cache_dir)
+        data = numpy.random.randint(
+            low=0, high=256, size=config.image_size * config.image_size * 3, dtype=numpy.uint8
+        ).reshape(config.image_size, config.image_size, 3)
+
+        example_inputs = image_processor(data, return_tensors="pt")
+    else:
+        tokenizer = AutoTokenizer.from_pretrained(model_name, cache_dir=cache_dir)
+        max_input_size = tokenizer.model_max_length
+        example_inputs = tokenizer.encode_plus("This is a sample input", return_tensors="pt")
+
+    example_inputs = filter_inputs(example_inputs, input_names)
+
+    example_outputs = model(**example_inputs)
+
+    assert isinstance(example_outputs, (list, tuple)), f"type of output is not list or tuple: {type(example_outputs)}"
+
+    # Flatten is needed for gpt2 and distilgpt2.
+    example_outputs_flatten = flatten(example_outputs)
+    example_outputs_flatten = update_flatten_list(example_outputs_flatten, [])
+
+    onnx_model_path = get_onnx_file_path(
+        onnx_dir,
+        model_name,
+        len(input_names),
+        False,
+        use_gpu,
+        precision,
+        False,
+        use_external_data_format,
+    )
+
+    if overwrite or not os.path.exists(onnx_model_path):
+        logger.info(f"Exporting ONNX model to {onnx_model_path}")
+        Path(onnx_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+        dynamic_axes = None
+        output_names = None
+
+        if model_type in ["vit", "swin"]:
+            dynamic_axes, output_names = {key: {0: "pixel_values"} for key in example_inputs}, ["logits"]
+        else:
+            dynamic_axes, output_names = build_dynamic_axes(example_inputs, example_outputs_flatten)
+
+        replace_torch_functions()
+        torch_onnx_export(
+            model=model,
+            args=tuple(example_inputs.values()),
+            f=onnx_model_path,
+            input_names=list(example_inputs.keys()),
+            output_names=output_names,
+            dynamic_axes=dynamic_axes,
+            do_constant_folding=True,
+            opset_version=opset_version,
+            use_external_data_format=use_external_data_format,
+        )
+        restore_torch_functions()
+    else:
+        logger.info(f"Skip export since model existed: {onnx_model_path}")
+
+    onnx_model_file, is_valid_onnx_model, vocab_size = validate_and_optimize_onnx(
+        model_name,
+        use_external_data_format,
+        model_type,
+        onnx_dir,
+        input_names,
+        use_gpu,
+        precision,
+        optimizer_info,
+        validate_onnx,
+        use_raw_attention_mask,
+        overwrite,
+        config,
+        model_fusion_statistics,
+        onnx_model_path,
+        example_inputs,
+        example_outputs_flatten,
+        None,
+        fusion_options,
+    )
+
+    return onnx_model_file, is_valid_onnx_model, vocab_size, max_input_size
+
+
+def export_onnx_model_from_tf(
+    model_name,
+    opset_version,
+    use_external_data_format,
+    model_type,
+    model_class,
+    config_modifier,
+    cache_dir,
+    onnx_dir,
+    input_names,
+    use_gpu,
+    precision,
+    optimizer_info,
+    validate_onnx,
+    use_raw_attention_mask,
+    overwrite,
+    model_fusion_statistics,
+    fusion_options,
+):
+    # Use CPU to export
+    import tensorflow as tf  # noqa: PLC0415
+
+    tf.config.set_visible_devices([], "GPU")
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name, cache_dir=cache_dir)
+    # Fix "Using pad_token, but it is not set yet" error.
+    if tokenizer.pad_token is None:
+        tokenizer.add_special_tokens({"pad_token": "[PAD]"})
+    max_input_size = tokenizer.model_max_length
+
+    config, model = load_tf_model(model_name, model_class, cache_dir, config_modifier)
+    model.resize_token_embeddings(len(tokenizer))
+
+    example_inputs = tokenizer.encode_plus(
+        "This is a sample input",
+        return_tensors="tf",
+        max_length=max_input_size,
+        padding="max_length",
+        truncation=True,
+    )
+    example_inputs = filter_inputs(example_inputs, input_names)
+
+    if config.is_encoder_decoder:
+        example_inputs["decoder_input_ids"] = tokenizer.encode_plus(
+            "This is a sample input",
+            return_tensors="tf",
+            max_length=max_input_size,
+            padding="max_length",
+            truncation=True,
+        ).input_ids
+    if model_name == "unc-nlp/lxmert-base-uncased":
+        example_inputs["visual_feats"] = tf.random.normal([1, 1, config.visual_feat_dim])
+        example_inputs["visual_pos"] = tf.random.normal([1, 1, config.visual_pos_dim])
+
+    try:
+        # Use no past state for these models
+        if config.use_cache:
+            config.use_cache = False
+    except Exception:
+        pass
+
+    example_outputs = model(example_inputs, training=False)
+    output_names = None
+
+    # For xlnet models, only compare the last_hidden_state output.
+    if model_name == "xlnet-base-cased" or model_name == "xlnet-large-cased":
+        output_names = ["last_hidden_state"]
+        example_outputs = example_outputs["last_hidden_state"]
+
+    # Flatten is needed for gpt2 and distilgpt2. Output name sorting is needed for tf2onnx outputs to match onnx outputs.
+    from tensorflow.python.util import nest  # noqa: PLC0415
+
+    example_outputs_flatten = nest.flatten(example_outputs)
+
+    onnx_model_path = get_onnx_file_path(
+        onnx_dir,
+        model_name,
+        len(input_names),
+        False,
+        use_gpu,
+        precision,
+        False,
+        use_external_data_format,
+    )
+    tf_internal_model_path = onnx_model_path[:-5] if use_external_data_format else onnx_model_path
+
+    if overwrite or not os.path.exists(tf_internal_model_path):
+        logger.info(f"Exporting ONNX model to {onnx_model_path}")
+        if not use_external_data_format:
+            Path(tf_internal_model_path).parent.mkdir(parents=True, exist_ok=True)
+
+        import zipfile  # noqa: PLC0415
+
+        import tf2onnx  # noqa: PLC0415
+
+        tf2onnx.logging.set_level(tf2onnx.logging.ERROR)
+        specs = []
+        for name, value in example_inputs.items():
+            dims = [None] * len(value.shape)
+            specs.append(tf.TensorSpec(tuple(dims), value.dtype, name=name))
+        _, _ = tf2onnx.convert.from_keras(
+            model,
+            input_signature=tuple(specs),
+            opset=opset_version,
+            large_model=use_external_data_format,
+            output_path=tf_internal_model_path,
+        )
+        if use_external_data_format:
+            # need to unpack the zip for run_onnxruntime()
+            with zipfile.ZipFile(tf_internal_model_path, "r") as z:
+                z.extractall(os.path.dirname(tf_internal_model_path))
+            tf_internal_model_path = os.path.join(os.path.dirname(tf_internal_model_path), "__MODEL_PROTO.onnx")
+            if os.path.exists(onnx_model_path):
+                os.remove(onnx_model_path)
+            os.rename(tf_internal_model_path, onnx_model_path)
+
+    else:
+        logger.info(f"Skip export since model existed: {onnx_model_path}")
+
+    model_type = model_type + "_tf"
+    optimized_onnx_path, is_valid_onnx_model, vocab_size = validate_and_optimize_onnx(
+        model_name,
+        use_external_data_format,
+        model_type,
+        onnx_dir,
+        input_names,
+        use_gpu,
+        precision,
+        optimizer_info,
+        validate_onnx,
+        use_raw_attention_mask,
+        overwrite,
+        config,
+        model_fusion_statistics,
+        onnx_model_path,
+        example_inputs,
+        example_outputs_flatten,
+        output_names,
+        fusion_options,
+    )
+
+    return (
+        optimized_onnx_path,
+        is_valid_onnx_model,
+        vocab_size,
+        max_input_size,
+    )
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..ad1151b216b1b7817703a82d9ecf06d8ed56e21d
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model.py
@@ -0,0 +1,1636 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import itertools
+import logging
+import os
+import sys
+from collections import deque
+from pathlib import Path
+
+from float16 import convert_float_to_float16
+from onnx import (
+    AttributeProto,
+    GraphProto,
+    ModelProto,
+    NodeProto,
+    TensorProto,
+    ValueInfoProto,
+    helper,
+    numpy_helper,
+    save_model,
+)
+from onnx.external_data_helper import load_external_data_for_tensor, uses_external_data
+from shape_infer_helper import SymbolicShapeInferenceHelper
+
+logger = logging.getLogger(__name__)
+
+
+class OnnxModel:
+    def __init__(self, model):
+        self.initialize(model)
+
+    def initialize(self, model):
+        self.model: ModelProto = model
+        self._node_name_suffix: dict[str, int] = {}  # key is node name prefix, value is the last suffix generated
+        self.shape_infer_helper: SymbolicShapeInferenceHelper = None
+        self.enable_shape_infer: bool = True
+        self.all_graphs: list[GraphProto] | None = None
+
+        # Cache of shape and data type from onnx graph to speed up optimization.
+        # Be careful that fusion shall not reuse node output name for different shape/type (in adding/removing nodes)
+        # Note that these do not cache the symbolic shape inference result.
+        self._dtype_dict: dict[str, int] | None = None
+        self._shape_dict: dict[str, list] | None = None
+
+    def disable_shape_inference(self):
+        self.enable_shape_infer = False
+
+    def infer_runtime_shape(self, dynamic_axis_mapping={}, update=False):  # noqa: B006
+        if self.enable_shape_infer:
+            if self.shape_infer_helper is None or update:
+                self.shape_infer_helper = SymbolicShapeInferenceHelper(self.model)
+
+            try:
+                if self.shape_infer_helper.infer(dynamic_axis_mapping):
+                    return self.shape_infer_helper
+            except Exception:
+                self.enable_shape_infer = False  # disable shape inference to suppress same error message.
+                print("failed in shape inference", sys.exc_info()[0])
+
+        return None
+
+    def input_name_to_nodes(self, exclude_subgraphs=False):
+        input_name_to_nodes = {}
+        nodes_to_search = self.nodes() if not exclude_subgraphs else self.model.graph.node
+        for node in nodes_to_search:
+            for input_name in node.input:
+                if input_name:  # could be empty when it is optional
+                    if input_name not in input_name_to_nodes:
+                        input_name_to_nodes[input_name] = [node]
+                    else:
+                        input_name_to_nodes[input_name].append(node)
+        return input_name_to_nodes
+
+    def output_name_to_node(self, exclude_subgraphs=False):
+        output_name_to_node = {}
+        nodes_to_search = self.nodes() if not exclude_subgraphs else self.model.graph.node
+        for node in nodes_to_search:
+            for output_name in node.output:
+                if output_name:  # could be empty when it is optional
+                    output_name_to_node[output_name] = node
+        return output_name_to_node
+
+    def functions(self):
+        all_functions = [list(self.model.functions)]
+        return all_functions
+
+    def nodes(self):
+        all_nodes = []
+        for graph in self.graphs():
+            for node in graph.node:
+                all_nodes.append(node)  # noqa: PERF402
+        return all_nodes
+
+    def graph(self):
+        return self.model.graph
+
+    def graphs(self):
+        if self.all_graphs is not None:
+            return self.all_graphs
+        self.all_graphs = []
+        graph_queue = [self.model.graph]
+        while graph_queue:
+            graph = graph_queue.pop(0)
+            self.all_graphs.append(graph)
+            for node in graph.node:
+                for attr in node.attribute:
+                    if attr.type == AttributeProto.AttributeType.GRAPH:
+                        assert isinstance(attr.g, GraphProto)
+                        graph_queue.append(attr.g)
+                    if attr.type == AttributeProto.AttributeType.GRAPHS:
+                        for g in attr.graphs:
+                            assert isinstance(g, GraphProto)
+                            graph_queue.append(g)
+        return self.all_graphs
+
+    def get_graphs_input_names(self):
+        input_names = []
+        for graph in self.graphs():
+            for input in graph.input:
+                input_names.append(input.name)
+        return input_names
+
+    def get_graphs_output_names(self):
+        output_names = []
+        for graph in self.graphs():
+            for output in graph.output:
+                output_names.append(output.name)
+        return output_names
+
+    def get_graph_by_node(self, node):
+        for graph in self.graphs():
+            if node in graph.node:
+                return graph
+        return None
+
+    def get_graph_by_name(self, graph_name):
+        for graph in self.graphs():
+            if graph_name == graph.name:
+                return graph
+        return None
+
+    def get_topological_insert_id(self, graph, outputs):
+        for idx, node in enumerate(graph.node):
+            for input in node.input:
+                if input in outputs:
+                    return idx
+        return len(graph.node)
+
+    def remove_node(self, node):
+        for graph in self.graphs():
+            if node in graph.node:
+                graph.node.remove(node)
+                return
+        logger.warning("Failed to remove node %s", node)  # It might be a bug to hit this line.
+
+    def remove_nodes(self, nodes_to_remove):
+        for node in nodes_to_remove:
+            self.remove_node(node)
+
+    def add_node(self, node, graph_name=None):
+        if graph_name is None or graph_name == self.model.graph.name:
+            self.model.graph.node.extend([node])
+        else:
+            graph = self.get_graph_by_name(graph_name)
+            insert_idx = self.get_topological_insert_id(graph, node.output)
+            graph.node.insert(insert_idx, node)
+
+    def add_nodes(self, nodes_to_add, node_name_to_graph_name=None):
+        if node_name_to_graph_name is None:
+            self.model.graph.node.extend(nodes_to_add)
+        else:
+            for node in nodes_to_add:
+                graph_name = node_name_to_graph_name[node.name]
+                self.add_node(node, graph_name)
+
+    def add_initializer(self, tensor, graph_name=None):
+        if graph_name is None or graph_name == self.model.graph.name:
+            self.model.graph.initializer.extend([tensor])
+        else:
+            graph = self.get_graph_by_name(graph_name)
+            graph.initializer.extend([tensor])
+
+    def add_input(self, input, graph_name=None):
+        if graph_name is None or graph_name == self.model.graph.name:
+            self.model.graph.input.extend([input])
+        else:
+            graph = self.get_graph_by_name(graph_name)
+            graph.input.extend([input])
+
+    @staticmethod
+    def replace_node_input(node, old_input_name, new_input_name):
+        assert isinstance(old_input_name, str) and isinstance(new_input_name, str)
+        for j in range(len(node.input)):
+            if node.input[j] == old_input_name:
+                node.input[j] = new_input_name
+
+    def replace_input_of_all_nodes(self, old_input_name, new_input_name):
+        for node in self.nodes():
+            OnnxModel.replace_node_input(node, old_input_name, new_input_name)
+
+    @staticmethod
+    def replace_node_output(node, old_output_name, new_output_name):
+        assert isinstance(old_output_name, str) and isinstance(new_output_name, str)
+        for j in range(len(node.output)):
+            if node.output[j] == old_output_name:
+                node.output[j] = new_output_name
+
+    def replace_output_of_all_nodes(self, old_output_name, new_output_name):
+        # This function shall be used carefully. For example:
+        #       Add --[old_name]--> Cast ---> [new_name]
+        #        |
+        #        +----[old_name]--> Transpose -->
+        # If we want to remove the Cast node: replace output of Add to new_name is not enough;
+        # The input of Transpose shall also be updated to new_name.
+        for node in self.model.graph.node:
+            OnnxModel.replace_node_output(node, old_output_name, new_output_name)
+
+    def get_initializer(self, name):
+        for graph in self.graphs():
+            for tensor in graph.initializer:
+                if tensor.name == name:
+                    return tensor
+        return None
+
+    def get_nodes_by_op_type(self, op_type):
+        nodes = []
+        for node in self.nodes():
+            if node.op_type == op_type:
+                nodes.append(node)
+        return nodes
+
+    def get_children(self, node, input_name_to_nodes=None, output_index=None):
+        if input_name_to_nodes is None:
+            input_name_to_nodes = self.input_name_to_nodes()
+
+        children = []
+        if output_index is not None:
+            if output_index < len(node.output):
+                output = node.output[output_index]
+                if output in input_name_to_nodes:
+                    children = list(input_name_to_nodes[output])
+        else:
+            for output in node.output:
+                if output in input_name_to_nodes:
+                    children.extend(input_name_to_nodes[output])
+
+        return children
+
+    def get_parents(self, node, output_name_to_node=None):
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        parents = []
+        for input in node.input:
+            if input in output_name_to_node:
+                parents.append(output_name_to_node[input])
+        return parents
+
+    def get_parent(self, node, i, output_name_to_node=None):
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        if len(node.input) <= i:
+            return None
+
+        input = node.input[i]
+        if input not in output_name_to_node:
+            return None
+
+        return output_name_to_node[input]
+
+    def match_first_parent(self, node, parent_op_type, output_name_to_node, exclude=[]):  # noqa: B006
+        """
+        Find parent node based on constraints on op_type.
+
+        Args:
+            node (str): current node name.
+            parent_op_type (str): constraint of parent node op_type.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+
+        Returns:
+            parent: The matched parent node. None if not found.
+            index: The input index of matched parent node. None if not found.
+        """
+        for i, input in enumerate(node.input):
+            if input in output_name_to_node:
+                parent = output_name_to_node[input]
+                if parent.op_type == parent_op_type and parent not in exclude:
+                    return parent, i
+                else:
+                    logger.debug(f"To find first {parent_op_type}, current {parent.op_type}")
+        return None, None
+
+    def match_parent(
+        self,
+        node,
+        parent_op_type,
+        input_index=None,
+        output_name_to_node=None,
+        exclude=[],  # noqa: B006
+        return_indice=None,
+    ):
+        """
+        Find parent node based on constraints on op_type and index.
+        When input_index is None, we will find the first parent node based on constraints,
+        and return_indice will be appended the corresponding input index.
+
+        Args:
+            node (str): current node name.
+            parent_op_type (str): constraint of parent node op_type.
+            input_index (int or None): only check the parent given input index of current node.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            exclude (list): list of nodes that are excluded (not allowed to match as parent).
+            return_indice (list): a list to append the input index when input_index is None.
+
+        Returns:
+            parent: The matched parent node.
+        """
+        assert node is not None
+        assert input_index is None or input_index >= 0
+
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        if input_index is None:
+            parent, index = self.match_first_parent(node, parent_op_type, output_name_to_node, exclude)
+            if return_indice is not None:
+                return_indice.append(index)
+            return parent
+
+        if input_index >= len(node.input):
+            logger.debug(f"input_index {input_index} >= node inputs {len(node.input)}")
+            return None
+
+        parent = self.get_parent(node, input_index, output_name_to_node)
+        if parent is not None and parent.op_type == parent_op_type and parent not in exclude:
+            return parent
+
+        if parent is not None:
+            logger.debug(f"Expect {parent_op_type}, Got {parent.op_type}")
+
+        return None
+
+    def match_parent_paths(self, node, paths, output_name_to_node):
+        for i, path in enumerate(paths):
+            assert isinstance(path, (list, tuple))
+            return_indice = []
+            matched = self.match_parent_path(node, path[0], path[1], output_name_to_node, return_indice)
+            if matched:
+                return i, matched, return_indice
+        return -1, None, None
+
+    def match_parent_paths_all(self, node, paths, output_name_to_node):
+        match_i, matches, return_indices = [], [], []
+        for i, path in enumerate(paths):
+            assert isinstance(path, (list, tuple))
+            return_indice = []
+            matched = self.match_parent_path(node, path[0], path[1], output_name_to_node, return_indice)
+            if matched:
+                match_i.append(i)
+                matches.append(matched)
+                return_indices.append(return_indice)
+        return match_i, matches, return_indices
+
+    def match_parent_path(
+        self,
+        node,
+        parent_op_types,
+        parent_input_index=None,
+        output_name_to_node=None,
+        return_indice=None,
+    ):
+        """
+        Find a sequence of input edges based on constraints on parent op_type and index.
+        When input_index is None, we will find the first parent node based on constraints,
+        and return_indice will be appended the corresponding input index.
+
+        Args:
+            node (str): current node name.
+            parent_op_types (str): constraint of parent node op_type of each input edge.
+            parent_input_index (list): constraint of input index of each input edge. None means no constraint.
+            output_name_to_node (dict): dictionary with output name as key, and node as value.
+            return_indice (list): a list to append the input index
+                                  When there is no constraint on input index of an edge.
+
+        Returns:
+            parents: a list of matched parent node.
+        """
+        if parent_input_index is not None:
+            assert len(parent_input_index) == len(parent_op_types)
+
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        current_node = node
+        matched_parents = []
+        for i, op_type in enumerate(parent_op_types):
+            matched_parent = self.match_parent(
+                current_node,
+                op_type,
+                parent_input_index[i] if parent_input_index is not None else None,
+                output_name_to_node,
+                exclude=[],
+                return_indice=return_indice,
+            )
+            if matched_parent is None:
+                if parent_input_index is not None:
+                    logger.debug(
+                        f"Failed to match index={i} parent_input_index={parent_input_index[i]} op_type={op_type}",
+                        stack_info=True,
+                    )
+                else:
+                    logger.debug(f"Failed to match index={i} op_type={op_type}", stack_info=True)
+                return None
+
+            matched_parents.append(matched_parent)
+            current_node = matched_parent
+
+        return matched_parents
+
+    def find_first_child_by_type(self, node, child_type, input_name_to_nodes=None, recursive=True):
+        children = self.get_children(node, input_name_to_nodes)
+        dq = deque(children)
+        while len(dq) > 0:
+            current_node = dq.pop()
+            if current_node.op_type == child_type:
+                return current_node
+
+            if recursive:
+                children = self.get_children(current_node, input_name_to_nodes)
+                for child in children:
+                    dq.appendleft(child)
+
+        return None
+
+    def match_child_path(
+        self,
+        node,
+        child_op_types,
+        edges: list[tuple[int, int]] | None = None,
+        input_name_to_nodes=None,
+        exclude=[],  # noqa: B006
+    ):
+        """
+        Find a sequence of input edges based on constraints on parent op_type and index.
+        Note that we use greedy approach and only consider the first matched child, so it has chance to miss matching.
+
+        Args:
+            node (str): current node name.
+            child_op_types (str): constraint of child node op_type of each input edge.
+            edges (list): each edge is represented by two integers: output index of parent node, input index of child node.
+                         None means no constraint.
+            exclude(list): list of nodes that are excluded (not allowed to match as child).
+
+        Returns:
+            children: a list of matched children node.
+        """
+        if edges is not None:
+            assert len(edges) == len(child_op_types)
+            for edge in edges:
+                assert (
+                    isinstance(edge, tuple) and len(edge) == 2 and isinstance(edge[0], int) and isinstance(edge[1], int)
+                )
+
+        if input_name_to_nodes is None:
+            input_name_to_nodes = self.input_name_to_nodes()
+
+        current_node = node
+        matched_children = []
+        for i, op_type in enumerate(child_op_types):
+            matched_child = None
+
+            if edges is None:
+                children_nodes = self.get_children(current_node, input_name_to_nodes=input_name_to_nodes)
+            else:
+                children_nodes = self.get_children(
+                    current_node, input_name_to_nodes=input_name_to_nodes, output_index=edges[i][0]
+                )
+
+            for child in children_nodes:
+                if child.op_type == op_type and child not in exclude:
+                    if edges is not None and child.input[edges[i][1]] != current_node.output[edges[i][0]]:
+                        continue
+
+                    # Here we use greedy approach and only consider the first matched child.
+                    # TODO: match recursively if we encounter cases that the correct child is not the first matched.
+                    matched_child = child
+                    break
+
+            if matched_child is None:
+                logger.debug(f"Failed to match child {i} op_type={op_type}", stack_info=True)
+                return None
+
+            matched_children.append(matched_child)
+            current_node = matched_child
+
+        return matched_children
+
+    def find_first_parent_by_type(self, node, parent_type, output_name_to_node=None, recursive=True):
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        parents = self.get_parents(node, output_name_to_node)
+        dq = deque(parents)
+        while len(dq) > 0:
+            current_node = dq.pop()
+            if current_node.op_type == parent_type:
+                return current_node
+
+            if recursive:
+                parents = self.get_parents(current_node, output_name_to_node)
+                for parent in parents:
+                    dq.appendleft(parent)
+
+        return None
+
+    def get_constant_value(self, output_name):
+        for node in self.get_nodes_by_op_type("Constant"):
+            if node.output[0] == output_name:
+                for att in node.attribute:
+                    if att.name == "value":
+                        return numpy_helper.to_array(att.t)
+
+        # Fall back to intializer since constant folding might have been applied.
+        initializer = self.get_initializer(output_name)
+        if initializer is not None:
+            return numpy_helper.to_array(initializer)
+
+        return None
+
+    def get_constant_input(self, node):
+        for i, input in enumerate(node.input):
+            value = self.get_constant_value(input)
+            if value is not None:
+                return i, value
+
+        return None, None
+
+    def find_constant_input(self, node, expected_value, delta=0.000001):
+        i, value = self.get_constant_input(node)
+        if value is not None and value.size == 1 and abs(value - expected_value) < delta:
+            return i
+
+        return -1
+
+    def is_constant_with_specified_dimension(self, output_name, dimensions, description):
+        value = self.get_constant_value(output_name)
+        if value is None:
+            logger.debug(f"{description} {output_name} is not initializer.")
+            return False
+
+        if len(value.shape) != dimensions:
+            logger.debug(f"{description} {output_name} shall have {dimensions} dimensions. Got shape {value.shape}")
+            return False
+
+        return True
+
+    def has_constant_input(self, node, expected_value, delta=0.000001):
+        return self.find_constant_input(node, expected_value, delta) >= 0
+
+    def get_children_subgraph_nodes(self, root_node, stop_nodes, input_name_to_nodes=None):
+        if input_name_to_nodes is None:
+            input_name_to_nodes = self.input_name_to_nodes()
+
+        children = input_name_to_nodes[root_node.output[0]]
+
+        unique_nodes = []
+
+        dq = deque(children)
+        while len(dq) > 0:
+            current_node = dq.pop()
+            if current_node in stop_nodes:
+                continue
+
+            if current_node not in unique_nodes:
+                unique_nodes.append(current_node)
+
+                for output in current_node.output:
+                    if output in input_name_to_nodes:
+                        children = input_name_to_nodes[output]
+                        for child in children:
+                            dq.appendleft(child)
+
+        return unique_nodes
+
+    def tensor_shape_to_list(self, tensor_type):
+        """Convert tensor shape to list"""
+        shape_list = []
+        for d in tensor_type.shape.dim:
+            if d.HasField("dim_value"):
+                shape_list.append(d.dim_value)  # known dimension
+            elif d.HasField("dim_param"):
+                shape_list.append(d.dim_param)  # unknown dimension with symbolic name
+            else:
+                shape_list.append("?")  # shall not happen
+        return shape_list
+
+    def get_dtype(self, name: str, symbolic_shape_helper: SymbolicShapeInferenceHelper | None = None):
+        """Try get data type given a name (could be initializer, input or output of graph or node)."""
+
+        if self._dtype_dict is None:
+            self._dtype_dict = {}
+            for value_info in itertools.chain(
+                self.model.graph.value_info,
+                self.model.graph.input,
+                self.model.graph.output,
+            ):
+                self._dtype_dict[value_info.name] = value_info.type.tensor_type.elem_type
+
+            for initializer in self.model.graph.initializer:
+                if initializer.name not in self._dtype_dict:
+                    self._dtype_dict[initializer.name] = initializer.data_type
+
+        if name in self._dtype_dict:
+            return self._dtype_dict[name]
+
+        if symbolic_shape_helper is not None and name in symbolic_shape_helper.known_vi_:
+            value_info = symbolic_shape_helper.known_vi_[name]
+            return value_info.type.tensor_type.elem_type
+
+        return None
+
+    def get_shape(self, name: str, symbolic_shape_helper: SymbolicShapeInferenceHelper | None = None):
+        """Try get shape given a name (could be initializer, input or output of graph or node)."""
+
+        if self._shape_dict is None:
+            self._shape_dict = {}
+            for value_info in itertools.chain(
+                self.model.graph.value_info,
+                self.model.graph.input,
+                self.model.graph.output,
+            ):
+                if value_info.type.tensor_type.HasField("shape"):
+                    shape = []
+                    for dim in value_info.type.tensor_type.shape.dim:
+                        if dim.dim_param:
+                            shape.append(dim.dim_param)
+                        else:
+                            shape.append(dim.dim_value)
+                    self._shape_dict[value_info.name] = shape
+
+            for initializer in self.model.graph.initializer:
+                if initializer.name not in self._shape_dict:
+                    self._shape_dict[initializer.name] = initializer.dims
+
+        if name in self._shape_dict:
+            return self._shape_dict[name]
+
+        if symbolic_shape_helper is not None and name in symbolic_shape_helper.known_vi_:
+            value_info = symbolic_shape_helper.known_vi_[name]
+            return value_info.type.tensor_type.elem_type
+
+        return None
+
+    @staticmethod
+    def get_node_attribute(node: NodeProto, attribute_name: str):
+        for attr in node.attribute:
+            if attr.name == attribute_name:
+                value = helper.get_attribute_value(attr)
+                return value
+        return None
+
+    def remove_cascaded_cast_nodes(self):
+        """Remove Cast node that are followed by another Cast node like  --> Cast --> Cast -->
+        Note that this shall be used carefully since it might introduce semantic change.
+        For example, float -> int -> float could get different value than the original float value.
+        So, it is recommended to used only in post-processing of mixed precision conversion.
+        """
+        output_name_to_node = self.output_name_to_node()
+        removed_count = 0
+        for node in self.nodes():
+            if node.op_type == "Cast":
+                parent = self.get_parent(node, 0, output_name_to_node=output_name_to_node)
+                if parent and parent.op_type == "Cast":
+                    node.input[0] = parent.input[0]
+                    removed_count += 1
+
+        if removed_count > 0:
+            logger.info("Removed %d cascaded Cast nodes", removed_count)
+            self.prune_graph()
+
+    def remove_useless_cast_nodes(self):
+        """Remove cast nodes that are not needed: input and output has same data type."""
+        shape_infer = self.infer_runtime_shape(update=True)
+        if self.enable_shape_infer and shape_infer is None:
+            logger.warning("shape inference failed which might impact useless cast node detection.")
+
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Cast":
+                input_dtype = self.get_dtype(node.input[0], shape_infer)
+                output_dtype = self.get_dtype(node.output[0], shape_infer)
+                if input_dtype and input_dtype == output_dtype:
+                    nodes_to_remove.append(node)
+
+        if nodes_to_remove:
+            graph_input_names = set(self.get_graphs_input_names())
+            graph_output_names = set(self.get_graphs_output_names())
+            for node in nodes_to_remove:
+                if bool(set(node.output) & graph_output_names):
+                    if (not bool(set(node.input) & graph_input_names)) and len(
+                        self.input_name_to_nodes()[node.input[0]]
+                    ) == 1:
+                        self.replace_output_of_all_nodes(node.input[0], node.output[0])
+                    else:
+                        continue
+                else:
+                    self.replace_input_of_all_nodes(node.output[0], node.input[0])
+                self.remove_node(node)
+
+            logger.info(
+                "Removed %d Cast nodes with output type same as input",
+                len(nodes_to_remove),
+            )
+
+    def convert_model_float32_to_float16(self, cast_input_output=True):
+        logger.warning(
+            "The function convert_model_float32_to_float16 is deprecated. Use convert_float_to_float16 instead!"
+        )
+        self.convert_float_to_float16(use_symbolic_shape_infer=True, keep_io_types=cast_input_output)
+
+    def convert_float_to_float16(self, use_symbolic_shape_infer=True, **kwargs):
+        """Convert a model to half (default) or mixed precision.
+           To use mixed precision, user need specify which graph inputs, outputs, operator type
+           or list of nodes shall keep in float32.
+
+           Note that the conversion might not proceed without type information for the whole graph.
+
+           By default, we use symbolic shape inference to get type information. The benefit of symbolic shape inference
+           is that it could handle fused operators in com.microsoft domain. Those operators cannot be handled in onnx shape
+           inference so symbolic shape inference is recommended for optimized model.
+
+           When symbolic shape inference is used (even if it failed), ONNX shape inference will be disabled.
+
+           Note that onnx shape inference will fail for model larger than 2GB. For large model, you have to enable
+           symbolic shape inference. If your model is not optimized, you can also use model path to call
+           convert_float_to_float16 in float16.py (see https://github.com/microsoft/onnxruntime/pull/15067) to
+           avoid the 2GB limit.
+
+        Args:
+            use_symbolic_shape_infer (bool, optional): use symbolic shape inference instead of onnx shape inference.
+                                                       Defaults to True.
+            keep_io_types (Union[bool, List[str]], optional): boolean or a list of float32 input/output names.
+                                                              If True, model inputs/outputs should be left as float32.
+                                                              Defaults to True.
+            op_block_list (List[str], optional): List of operator types to leave as float32.
+                                                 Defaults to None, which will use `float16.DEFAULT_OP_BLOCK_LIST`.
+            node_block_list (List[str], optional): List of node names to leave as float32. Defaults to None.
+            force_fp16_initializers(bool): force converting all float initializers to float16.
+                                           Default to false.
+            min_positive_val (float, optional): minimal positive value. Defaults to 1e-7.
+            max_finite_val (float, optional): maximal finite value. Defaults to 1e4.
+            force_fp16_inputs(Dict[str, List[int]]): Force the conversion of the inputs of some operators to float16, even if
+                                                     this script's preference it to keep them in float32.
+        """
+        if "keep_io_types" not in kwargs:
+            kwargs["keep_io_types"] = True
+
+        model = self.model
+        if use_symbolic_shape_infer:
+            # Use symbolic shape inference since custom operators (like Gelu, SkipLayerNormalization etc)
+            # are not recognized by onnx shape inference.
+            shape_infer_helper = SymbolicShapeInferenceHelper(model)
+            try:
+                model_with_shape = shape_infer_helper.infer_shapes(model, auto_merge=True, guess_output_rank=False)
+
+                # auto_merge might cause issue (see https://github.com/microsoft/onnxruntime/issues/15521)
+                # we only merge tensor data type but not shape information back to the original onnx model.
+                # Note that float16 conversion need data type but not shape information.
+                if model_with_shape is not None:
+                    name_vi = {}
+                    for vi in model_with_shape.graph.value_info:
+                        if (
+                            hasattr(vi.type, "tensor_type")
+                            and hasattr(vi.type.tensor_type, "elem_type")
+                            and vi.type.tensor_type.elem_type != TensorProto.UNDEFINED
+                            and vi.name
+                        ):
+                            vi_copy = ValueInfoProto()
+                            vi_copy.CopyFrom(vi)
+                            if hasattr(vi_copy.type.tensor_type, "shape"):
+                                vi_copy.type.tensor_type.ClearField("shape")
+                            name_vi[vi.name] = vi_copy
+                    for vi in model.graph.value_info:
+                        if vi.name in name_vi:
+                            del name_vi[vi.name]
+                    for vi in name_vi.values():
+                        model.graph.value_info.append(vi)
+            except Exception:
+                logger.warning(
+                    "Failed to run symbolic shape inference. Please file an issue in https://github.com/microsoft/onnxruntime."
+                )
+
+        parameters = {"disable_shape_infer": use_symbolic_shape_infer}
+        parameters.update(
+            {
+                key: kwargs[key]
+                for key in [
+                    "keep_io_types",
+                    "min_positive_val",
+                    "max_finite_val",
+                    "op_block_list",
+                    "node_block_list",
+                    "force_fp16_initializers",
+                    "force_fp16_inputs",
+                    "use_bfloat16_as_blocked_nodes_dtype",
+                ]
+                if key in kwargs
+            }
+        )
+
+        fp16_model = convert_float_to_float16(model, **parameters)
+        self.initialize(fp16_model)
+
+        self.remove_cascaded_cast_nodes()
+
+        self.remove_useless_cast_nodes()
+
+    def create_node_name(self, op_type, name_prefix=None):
+        """Create a unique node name that starts with a prefix (default is operator type).
+           The name will not be duplicated with any name that generated or existed in current graphs.
+        Args:
+            op_type (str): operator type
+            name_prefix (str, optional): prefix of node name. Defaults to None.
+
+        Returns:
+            str: node name
+        """
+
+        if name_prefix:
+            prefix = name_prefix if name_prefix.endswith("_") else (name_prefix + "_")
+        else:
+            prefix = op_type + "_"
+
+        suffix: int = 0
+        if prefix in self._node_name_suffix:
+            suffix = self._node_name_suffix[prefix] + 1
+        else:
+            # Check existed node name only once for a prefix
+            # as we assume create_node_name is called for every new node in fusion.
+            for node in self.nodes():
+                if node.name and node.name.startswith(prefix):
+                    try:
+                        index = int(node.name[len(prefix) :])
+                        suffix = max(index + 1, suffix)
+                    except ValueError:
+                        continue
+
+        # Record the generated suffix so that we can avoid generating duplicated name.
+        self._node_name_suffix[prefix] = suffix
+
+        return prefix + str(suffix)
+
+    def find_graph_input(self, input_name):
+        for input in self.model.graph.input:
+            if input.name == input_name:
+                return input
+        return None
+
+    def find_graph_output(self, output_name):
+        for output in self.model.graph.output:
+            if output.name == output_name:
+                return output
+        return None
+
+    def get_parent_subgraph_nodes(self, node, stop_nodes, output_name_to_node=None):
+        if output_name_to_node is None:
+            output_name_to_node = self.output_name_to_node()
+
+        unique_nodes = []
+
+        parents = self.get_parents(node, output_name_to_node)
+        dq = deque(parents)
+        while len(dq) > 0:
+            current_node = dq.pop()
+            if current_node in stop_nodes:
+                continue
+
+            if current_node not in unique_nodes:
+                unique_nodes.append(current_node)
+
+                for input in current_node.input:
+                    if input in output_name_to_node:
+                        dq.appendleft(output_name_to_node[input])
+
+        return unique_nodes
+
+    def get_graph_inputs(self, current_node, recursive=False):
+        """
+        Find graph inputs that linked to current node.
+        """
+        graph_inputs = []
+        for input in current_node.input:
+            if self.find_graph_input(input) and input not in graph_inputs:
+                graph_inputs.append(input)
+
+        if recursive:
+            parent_nodes = self.get_parent_subgraph_nodes(current_node, [])
+            for node in parent_nodes:
+                for input in node.input:
+                    if self.find_graph_input(input) and input not in graph_inputs:
+                        graph_inputs.append(input)
+        return graph_inputs
+
+    @staticmethod
+    def input_index(node_output, child_node):
+        for index, input in enumerate(child_node.input):
+            if input == node_output:
+                return index
+        return -1
+
+    def remove_unused_constant(self):
+        input_name_to_nodes = self.input_name_to_nodes()
+
+        # remove unused constant
+        unused_nodes = []
+        nodes = self.nodes()
+        for node in nodes:
+            if node.op_type == "Constant" and node.output[0] not in input_name_to_nodes:
+                unused_nodes.append(node)
+
+        self.remove_nodes(unused_nodes)
+
+        if len(unused_nodes) > 0:
+            logger.debug(f"Removed unused constant nodes: {len(unused_nodes)}")
+
+    def _get_subgraph_inputs_of_node(self, node):
+        """
+        Get inputs to all nodes in all subgraphs of a node
+        """
+        # Note: This function only handles one-level subgraphs of child nodes.
+        subgraph_nodes_inputs = set()
+        for attr in node.attribute:
+            if attr.type == AttributeProto.GRAPH:
+                child_nodes = attr.g.node
+                for child_node in child_nodes:
+                    subgraph_nodes_inputs.update(child_node.input)
+        return subgraph_nodes_inputs
+
+    def _get_subgraph_nodes_and_inputs(self, ops_with_graph_attrs):
+        """
+        Get input names to all nodes in all subgraphs where subgraphs are
+        graph attributes of a node in the main graph
+        """
+        subgraph_nodes = list(filter(lambda node: node.op_type in ops_with_graph_attrs, self.model.graph.node))
+        subgraph_nodes_inputs = set()
+        for parent_node in subgraph_nodes:
+            subgraph_inputs_of_parent_node = self._get_subgraph_inputs_of_node(parent_node)
+            subgraph_nodes_inputs.update(subgraph_inputs_of_parent_node)
+        return subgraph_nodes, subgraph_nodes_inputs
+
+    def prune_graph(self, outputs=None, allow_remove_graph_inputs=True):
+        """
+        Prune graph to keep only required outputs. It removes unnecessary nodes that are not linked
+        (directly or indirectly) to any required output.
+
+        There is also an option to remove graph inputs that are not used to generate any required output.
+
+        Args:
+            outputs (list): a list of graph outputs to retain. If it is None, all graph outputs will be kept.
+            allow_remove_graph_inputs (bool): allow remove graph inputs.
+        """
+
+        keep_outputs = [output.name for output in self.model.graph.output] if outputs is None else outputs
+
+        input_name_to_nodes_for_main_graph = self.input_name_to_nodes(exclude_subgraphs=True)
+        output_name_to_node = self.output_name_to_node()
+
+        def get_first_output(node):
+            if node.output[0]:
+                return node.output[0]
+            return next(iter([o for o in node.output if o]), None)
+
+        if len(self.graphs()) > 1:
+            # Get input names for all nodes in all subgraphs
+            subgraph_nodes, subgraph_nodes_inputs = self._get_subgraph_nodes_and_inputs(
+                ops_with_graph_attrs={"Loop", "Scan", "If"}
+            )
+            if len(subgraph_nodes) == 0:
+                # TODO: support other ops such as `BeamSearch` that have subgraphs as op attributes
+                logger.debug("Skip prune_graph since graph has subgraph")
+                return
+
+            # For graphs with subgraphs, add dangling outputs from parent graph nodes to list of outputs to keep
+            for node in self.model.graph.node:
+                # TODO: This for-loop logic currently assumes that Loop/Scan/If nodes will not be
+                # pruned because their subgraphs are needed for computations. This might not be
+                # true in all cases.
+                if node in subgraph_nodes:
+                    continue
+
+                # Check if node output is an input of a subgraph node and not an input to a node in the main graph
+                for output in node.output:
+                    if output in subgraph_nodes_inputs and output not in input_name_to_nodes_for_main_graph:
+                        keep_outputs += [output]
+
+        # Keep track of nodes to keep. The key is first output of node, and the value is the node.
+        output_to_node = {}
+
+        # Start from graph outputs, and find parent nodes recursively, and add nodes to the output_to_node dictionary.
+        dq = deque()
+        for output in keep_outputs:
+            if output in output_name_to_node:
+                dq.append(output_name_to_node[output])
+        while len(dq) > 0:
+            node = dq.pop()
+            first_output = get_first_output(node)
+            if first_output and (first_output not in output_to_node):
+                output_to_node[first_output] = node
+                for name in node.input:
+                    if len(name) > 0 and (name in output_name_to_node) and (name not in output_to_node):
+                        dq.appendleft(output_name_to_node[name])
+
+        # Keep only those nodes in the output_to_node dictionary.
+        nodes_to_keep = []
+        num_nodes_removed = 0
+        for node in self.model.graph.node:
+            first_output = get_first_output(node)
+            kept_node = output_to_node.get(first_output)
+
+            # Need to double check the node since fused node might reuse output name of some nodes to be removed.
+            # It is slow to compare whole node, so we compare op_type first to avoid comparing node in most cases.
+            if kept_node and kept_node.op_type == node.op_type and kept_node == node:
+                nodes_to_keep.append(node)
+            else:
+                num_nodes_removed += 1
+
+        self.all_graphs = (
+            None  # to prevent pass-by-copy after ClearField(), forces the use of pass-by-reference instead
+        )
+        self.model.graph.ClearField("node")
+        self.model.graph.node.extend(nodes_to_keep)
+
+        # Remove graph outputs not in list
+        output_to_remove = []
+        if outputs is not None:
+            for output in self.model.graph.output:
+                if output.name not in outputs:
+                    output_to_remove.append(output)
+            for output in output_to_remove:
+                self.model.graph.output.remove(output)
+
+        # Remove graph inputs not used by any node.
+        input_to_remove = []
+        if allow_remove_graph_inputs:
+            input_name_to_nodes = self.input_name_to_nodes()
+            input_to_remove = [input for input in self.model.graph.input if input.name not in input_name_to_nodes]
+            for name in input_to_remove:
+                self.model.graph.input.remove(name)
+
+        if input_to_remove or output_to_remove or num_nodes_removed > 0:
+            removed = []
+            if input_to_remove:
+                removed.append(f"{len(input_to_remove)} inputs")
+            if output_to_remove:
+                removed.append(f"{len(output_to_remove)} outputs")
+            if num_nodes_removed > 0:
+                removed.append(f"{num_nodes_removed} nodes")
+            logger.info("Removed %s", ", ".join(removed))
+
+        self.update_graph()
+
+    def update_graph(self, verbose=False, allow_remove_graph_inputs=False):
+        graph = self.model.graph
+
+        remaining_input_names = set()
+        for node in graph.node:
+            if node.op_type in ["Loop", "Scan", "If"]:
+                # Add input names of nodes in subgraphs
+                subgraph_inputs_of_node = self._get_subgraph_inputs_of_node(node)
+                remaining_input_names.update(subgraph_inputs_of_node)
+
+            if node.op_type != "Constant":
+                remaining_input_names.update(node.input)
+        if verbose:
+            logger.debug(f"remaining input names: {remaining_input_names}")
+
+        # remove graph input that is not used
+        inputs_to_remove = []
+        if allow_remove_graph_inputs:
+            for input in graph.input:
+                if input.name not in remaining_input_names:
+                    inputs_to_remove.append(input)
+            for input in inputs_to_remove:
+                graph.input.remove(input)
+
+        names_to_remove = [input.name for input in inputs_to_remove]
+        logger.debug(f"remove {len(inputs_to_remove)} unused inputs: {names_to_remove}")
+
+        # remove weights that are not used
+        weights_to_remove = []
+        weights_to_keep = []
+        for initializer in graph.initializer:
+            if initializer.name not in remaining_input_names and not self.find_graph_output(initializer.name):
+                weights_to_remove.append(initializer)
+            else:
+                weights_to_keep.append(initializer.name)
+        for initializer in weights_to_remove:
+            graph.initializer.remove(initializer)
+
+        names_to_remove = [initializer.name for initializer in weights_to_remove]
+        logger.debug(f"remove {len(weights_to_remove)} unused initializers: {names_to_remove}")
+        if verbose:
+            logger.debug(f"remaining initializers:{weights_to_keep}")
+
+        self.remove_unused_constant()
+
+    def is_safe_to_fuse_nodes(self, nodes_to_remove, keep_outputs, input_name_to_nodes, output_name_to_node):
+        for node_to_remove in nodes_to_remove:
+            for output_to_remove in node_to_remove.output:
+                if output_to_remove in keep_outputs:
+                    continue
+
+                if output_to_remove in input_name_to_nodes:
+                    for impacted_node in input_name_to_nodes[output_to_remove]:
+                        if impacted_node not in nodes_to_remove:
+                            logger.debug(
+                                "it is not safe to remove nodes since output %s is used by %s",
+                                output_to_remove,
+                                impacted_node,
+                            )
+                            return False
+        return True
+
+    @staticmethod
+    def graph_topological_sort(graph, is_deterministic=False):
+        deps_set = set()  # dependency set of all node
+        sorted_node_set = set()  # sorted node set
+        sorted_nodes = []  # initialize sorted_nodes
+
+        initializer_names = [init.name for init in graph.initializer]
+        graph_input_names = [input.name for input in graph.input]
+        input_names = initializer_names + graph_input_names
+
+        if is_deterministic:
+            input_names.sort()
+
+        for input_name in input_names:
+            deps_set.add(input_name)
+
+        sorted_node_set_len = -1
+        graph_nodes = graph.node if not is_deterministic else sorted(graph.node, key=lambda x: x.name)
+
+        last_node_name = None
+        while len(sorted_node_set) != len(graph_nodes):
+            if len(sorted_node_set) == sorted_node_set_len:
+                break
+            sorted_node_set_len = len(sorted_node_set)
+            for node_idx, node in enumerate(graph_nodes):
+                if node_idx in sorted_node_set:
+                    continue
+                input_count = sum(1 for _ in node.input if _)
+                if input_count == 0:
+                    sorted_nodes.append(node)
+                    sorted_node_set.add(node_idx)
+                    for output in node.output:
+                        if output:
+                            deps_set.add(output)
+                    continue
+                failed = False
+                for input_name in node.input:
+                    if input_name and input_name not in deps_set:
+                        failed = True
+                        last_node_name = node.name
+                if not failed:
+                    sorted_nodes.append(node)
+                    sorted_node_set.add(node_idx)
+                    for output in node.output:
+                        if output:
+                            deps_set.add(output)
+                else:
+                    continue
+
+        if len(sorted_node_set) != len(graph.node):
+            raise RuntimeError(
+                f"Graph is not a DAG: len(sorted_node_set)={len(sorted_node_set)}, len(graph.node)={len(graph.node)}, failed at node {last_node_name}"
+            )
+
+        graph.ClearField("node")
+        graph.node.extend(sorted_nodes)
+
+    def topological_sort(self, is_deterministic=False, dump_model_on_failure=False):
+        # TODO: support graph_topological_sort() in subgraphs
+        # for graph in self.graphs():
+        #    self.graph_topological_sort(graph)
+        try:
+            OnnxModel.graph_topological_sort(self.model.graph, is_deterministic)
+        except RuntimeError as e:
+            if dump_model_on_failure:
+                logger.info(
+                    "Failed to sort graph in topological order. Dumping model to _topo_sort_failed.onnx for debugging."
+                )
+                OnnxModel.save(
+                    self.model, "_topo_sort_failed.onnx", save_as_external_data=True, all_tensors_to_one_file=True
+                )
+            raise e
+
+    @staticmethod
+    def save(
+        model,
+        output_path,
+        save_as_external_data=False,
+        all_tensors_to_one_file=True,
+        size_threshold=1024,
+        convert_attribute=False,
+    ):
+        Path(output_path).parent.mkdir(parents=True, exist_ok=True)
+
+        # Add ms domain if needed
+        ms_opset = [opset for opset in model.opset_import if opset.domain == "com.microsoft"]
+        # Check whether there is custom op in top level graph (our fusion is on top level right now).
+        # May need to extend to subgraph if our fusion are extended to subgraphs.
+        ms_node = [node for node in model.graph.node if node.domain == "com.microsoft"]
+        if ms_node and not ms_opset:
+            opset = model.opset_import.add()
+            opset.version = 1
+            opset.domain = "com.microsoft"
+
+        if save_as_external_data:
+            # Save model to external data, which is needed for model size > 2GB
+            output_dir = Path(output_path).parent
+            output_dir.mkdir(parents=True, exist_ok=True)
+            external_data_path = output_path + ".data"
+            location = Path(external_data_path).name if all_tensors_to_one_file else None
+
+            if os.path.exists(output_path):
+                logger.info(f"Delete the existing onnx file: {output_path}")
+                os.remove(output_path)
+
+            if all_tensors_to_one_file:
+                if os.path.exists(external_data_path):
+                    # Delete the external data file. Otherwise, data will be appended to existing file.
+                    logger.info(f"Delete the existing external data file: {external_data_path}")
+                    os.remove(external_data_path)
+            else:
+                if os.listdir(output_dir):
+                    raise RuntimeError(f"Output directory ({output_dir}) for external data is not empty.")
+
+            save_model(
+                model,
+                output_path,
+                save_as_external_data=True,
+                all_tensors_to_one_file=all_tensors_to_one_file,
+                location=location,
+                size_threshold=size_threshold,
+                convert_attribute=convert_attribute,
+            )
+        else:
+            save_model(model, output_path)
+
+    def save_model_to_file(
+        self,
+        output_path,
+        use_external_data_format=False,
+        all_tensors_to_one_file=True,
+        size_threshold=1024,
+        convert_attribute=False,
+    ):
+        logger.info("Sort graphs in topological order")
+        self.topological_sort()
+
+        # Note: After the model is saved to another directory with external data,
+        #       You need reload the onnx model if you want to read tensor from self.model object.
+        #       It is because the base directory is not updated for self.model object so attempt to read tensor data
+        #       might encounter error since external data cannot be located.
+        OnnxModel.save(
+            self.model,
+            output_path,
+            use_external_data_format,
+            all_tensors_to_one_file,
+            size_threshold,
+            convert_attribute,
+        )
+        logger.info(f"Model saved to {output_path}")
+
+    def get_graph_inputs_excluding_initializers(self):
+        """
+        Returns real graph inputs (excluding initializers from older onnx model).
+        """
+        graph_inputs = []
+        for input in self.model.graph.input:
+            if self.get_initializer(input.name) is None:
+                graph_inputs.append(input)
+        return graph_inputs
+
+    def get_opset_version(self):
+        """Get opset version of onnx domain
+
+        Raises:
+            RuntimeError: ONNX model has no opset for default domain.
+
+        Returns:
+            int: opset version of onnx domain.
+        """
+        for opset in self.model.opset_import:
+            if opset.domain in ["", "ai.onnx"]:
+                return opset.version
+        raise RuntimeError("ONNX model has no opset for default domain")
+
+    def get_operator_statistics(self, include_domain=False):
+        """
+        Returns node count of operators.
+        """
+        op_count = {}
+        for node in self.nodes():
+            op = (node.domain + ":" if include_domain and node.domain else "") + node.op_type
+            op_count[op] = 1 if op not in op_count else (op_count[op] + 1)
+
+        # Sorted by count in the descending order, then by key in alphabetical order.
+        logger.info(f"Operators:{sorted(op_count.items(), key=lambda kv: (-kv[1], kv[0]))}")
+
+        return op_count
+
+    @staticmethod
+    def to_data_hash(tensor: TensorProto, base_dir: str = "") -> int:
+        """Converts a tensor def object to a hash for data comparison purposes.
+        Args:
+            tensor: a TensorProto object.
+            base_dir: if external tensor exists, base_dir can help to find the path to it
+        Returns:
+            hash: a hash of the data.
+        """
+        if tensor.HasField("segment"):
+            raise ValueError("Currently not supporting loading segments.")
+        if tensor.data_type == TensorProto.UNDEFINED:
+            raise TypeError("The element type in the input tensor is not defined.")
+        tensor_dtype = tensor.data_type
+        storage_field = helper.tensor_dtype_to_field(tensor_dtype)
+
+        if tensor.data_type == TensorProto.STRING:
+            utf8_strings = getattr(tensor, storage_field)
+            return hash(tuple(s.decode("utf-8") for s in utf8_strings))
+        # Load raw data from external tensor if it exists
+        if uses_external_data(tensor):
+            load_external_data_for_tensor(tensor, base_dir)
+        if tensor.HasField("raw_data"):
+            return hash(tensor.raw_data)
+        else:
+            np_data = numpy_helper.to_array(tensor)
+            return hash(np_data.tobytes())
+
+    @staticmethod
+    def has_same_value(
+        tensor1: TensorProto,
+        tensor2: TensorProto,
+        signature_cache1: dict | None = None,
+        signature_cache2: dict | None = None,
+        rtol: float = 1e-05,
+        atol: float = 1e-08,
+    ) -> bool:
+        """Returns True when two tensors have same value.
+           Note that name can be different.
+
+        Args:
+            tensor1 (TensorProto): initializer 1
+            tensor2 (TensorProto): initializer 2
+            signature_cache1 (dict): Optional dictionary to store data signatures of tensor1 in order to speed up comparison.
+            signature_cache2 (dict): Optional dictionary to store data signatures of tensor2 in order to speed up comparison.
+            rtol (float): Optional relative difference threshold for minor precision differences
+            atol (float): Optional absolute difference threshold for minor precision differences
+        Returns:
+            bool: True when two initializers has same value.
+        """
+        sig1 = (
+            signature_cache1[tensor1.name]
+            if signature_cache1 and tensor1.name in signature_cache1
+            else OnnxModel.to_data_hash(tensor1)
+        )
+        sig2 = (
+            signature_cache2[tensor2.name]
+            if signature_cache2 and tensor2.name in signature_cache2
+            else OnnxModel.to_data_hash(tensor2)
+        )
+        if signature_cache1 is not None:
+            signature_cache1[tensor1.name] = sig1
+        if signature_cache2 is not None:
+            signature_cache2[tensor2.name] = sig2
+        if tensor1.data_type == tensor2.data_type and tensor1.dims == tensor2.dims:
+            n1 = numpy_helper.to_array(tensor1)
+            n2 = numpy_helper.to_array(tensor2)
+            if sig1 == sig2:
+                # Same signature, now do the expensive check to confirm the data is the same
+                return (n1 == n2).all()
+            else:
+                # Check if tensors are allclose
+                from numpy import allclose  # noqa: PLC0415
+
+                return allclose(n1, n2, rtol=rtol, atol=atol)
+
+        return False
+
+    def remove_initializer(self, tensor):
+        for graph in self.graphs():
+            if tensor in graph.initializer:
+                graph.initializer.remove(tensor)
+                return
+        logger.warning("Failed to remove initializer %s", tensor)  # It might be a bug to hit this line.
+
+    def remove_duplicated_initializer(self, cache: dict | None):
+        """Remove initializers with duplicated values, and only keep the first one.
+        It could help reduce size of models (like ALBert) with shared weights.
+        If require_raw_data passed, method will only compare raw_data initializers to speed runtime
+        Note: this function does not process subgraph.
+        """
+        if len(self.graphs()) > 1:
+            logger.warning("remove_duplicated_initializer does not process subgraphs.")
+
+        initializer_count = len(self.model.graph.initializer)
+
+        same = [-1] * initializer_count
+        for i in range(initializer_count - 1):
+            if same[i] >= 0:
+                continue
+            for j in range(i + 1, initializer_count):
+                if OnnxModel.has_same_value(
+                    self.model.graph.initializer[i],
+                    self.model.graph.initializer[j],
+                    cache,
+                    cache,
+                ):
+                    same[j] = i
+
+        count = 0
+        for i in range(initializer_count):
+            if same[i] >= 0:
+                count += 1
+                self.replace_input_of_all_nodes(
+                    self.model.graph.initializer[i].name,
+                    self.model.graph.initializer[same[i]].name,
+                )
+
+        if count > 0:
+            self.update_graph()
+            print(f"Removed {count} initializers with duplicated value")
+
+    def add_prefix_to_names(self, prefix: str):
+        """Add prefix to initializer or intermediate outputs in graph. Main graph inputs and outputs are excluded.
+        It could help avoid conflicting in name of node_args when merging two graphs.
+        Note: this function does not process subgraph.
+        """
+        if len(self.graphs()) > 1:
+            logger.warning("add_prefix_to_names does not process subgraphs.")
+
+        # Exclude the names of inputs and outputs of main graph (but not subgraphs)
+        # and empty names ("") as they have special meaning to denote missing optional inputs
+        excluded = [i.name for i in self.model.graph.input] + [o.name for o in self.model.graph.output] + [""]
+
+        for initializer in self.model.graph.initializer:
+            if initializer.name not in excluded:
+                if prefix + initializer.name not in excluded:
+                    initializer.name = prefix + initializer.name
+
+        for node in self.model.graph.node:
+            # update name of node inputs
+            for j in range(len(node.input)):
+                if node.input[j] not in excluded:
+                    if prefix + node.input[j] not in excluded:
+                        node.input[j] = prefix + node.input[j]
+
+            # update name of node outputs
+            for j in range(len(node.output)):
+                if node.output[j] not in excluded:
+                    if prefix + node.output[j] not in excluded:
+                        node.output[j] = prefix + node.output[j]
+
+        for value_info in self.model.graph.value_info:
+            if value_info.name not in excluded:
+                value_info.name = prefix + value_info.name
+
+    def clean_shape_infer(self):
+        self.model.graph.ClearField("value_info")
+
+    def use_float16(self):
+        """Check whether the model uses float16"""
+        queue = []  # queue for BFS
+        queue.append(self.model.graph)
+        while queue:
+            sub_graphs = []
+            for graph in queue:
+                if not isinstance(graph, GraphProto):
+                    continue
+
+                for v in itertools.chain(graph.input, graph.output, graph.value_info):
+                    if v.type.tensor_type.elem_type == TensorProto.FLOAT16:
+                        return True
+                    if v.type.HasField("sequence_type"):
+                        if v.type.sequence_type.elem_type.tensor_type.elem_type == TensorProto.FLOAT16:
+                            return True
+
+                for t in graph.initializer:
+                    if t.data_type == TensorProto.FLOAT16:
+                        return True
+
+                for node in graph.node:
+                    if node.op_type == "Cast":
+                        for attr in node.attribute:
+                            if attr.name == "to" and attr.i == TensorProto.FLOAT16:
+                                return True
+
+                    for attr in node.attribute:
+                        if attr.type == AttributeProto.GRAPH:
+                            sub_graphs.append(attr.g)
+
+                        for g in attr.graphs:
+                            sub_graphs.append(g)  # noqa: PERF402
+
+                        if isinstance(attr.t, TensorProto) and attr.t.data_type == TensorProto.FLOAT16:
+                            return True
+
+                        for t in attr.tensors:
+                            if isinstance(t, TensorProto) and t.data_type == TensorProto.FLOAT16:
+                                return True
+
+            queue = sub_graphs
+
+        return False
+
+    def change_graph_input_type(
+        self,
+        graph_input: ValueInfoProto,
+        new_type: int,
+    ):
+        """Change graph input type, and add Cast node if needed.
+
+        Args:
+            graph_input (ValueInfoProto): input of the graph
+            new_type (int): new data type like TensorProto.INT32.
+
+        Returns:
+            NodeProto: a new Cast node that added. None if Cast node is not added.
+            List[NodeProto]: Cast nodes that have been removed.
+        """
+        assert isinstance(graph_input, ValueInfoProto)
+        assert self.find_graph_input(graph_input.name)
+
+        if graph_input.type.tensor_type.elem_type == int(new_type):
+            return None, []
+
+        graph = self.graph()
+        new_cast_node = None
+        nodes_to_remove = []
+
+        input_name_to_nodes = self.input_name_to_nodes()
+        if graph_input.name in input_name_to_nodes:
+            nodes = input_name_to_nodes[graph_input.name]
+
+            # For children that is not Cast node, insert a Cast node to convert int32 to original data type.
+            nodes_not_cast = [node for node in nodes if node.op_type != "Cast"]
+            if nodes_not_cast:
+                node_name = self.create_node_name("Cast")
+                output_name = node_name + "_" + graph_input.name
+                new_value_info = graph.value_info.add()
+                new_value_info.CopyFrom(graph_input)
+                new_value_info.name = output_name
+                new_cast_node = helper.make_node(
+                    "Cast",
+                    [graph_input.name],
+                    [output_name],
+                    to=int(graph_input.type.tensor_type.elem_type),
+                    name=node_name,
+                )
+                graph.node.extend([new_cast_node])
+
+                for node in nodes_not_cast:
+                    OnnxModel.replace_node_input(node, graph_input.name, output_name)
+
+            # For children that is Cast node, no need to insert Cast.
+            # When the children is Cast to int32, we can remove that Cast node since input type is int32 now.
+            nodes_cast = [node for node in nodes if node.op_type == "Cast"]
+            for node in nodes_cast:
+                if OnnxModel.get_node_attribute(node, "to") == int(new_type):
+                    self.replace_input_of_all_nodes(node.output[0], graph_input.name)
+                if not self.find_graph_output(node.output[0]):
+                    nodes_to_remove.append(node)
+            if nodes_to_remove:
+                self.remove_nodes(nodes_to_remove)
+
+        graph_input.type.tensor_type.elem_type = int(new_type)
+        return new_cast_node, nodes_to_remove
+
+    def change_graph_output_type(
+        self,
+        graph_output: ValueInfoProto,
+        new_type: int,
+    ):
+        """Change graph input type, and add Cast node if needed.
+
+        Args:
+            graph_input (str | ValueInfoProto): output of the graph
+            new_type (int): new data type.
+
+        Returns:
+            NodeProto: a new Cast node that added. None if Cast node is not added.
+        """
+        assert isinstance(graph_output, ValueInfoProto)
+        assert self.find_graph_output(graph_output.name)
+
+        if graph_output.type.tensor_type.elem_type == int(new_type):
+            return None
+
+        cast_node = None
+        graph = self.graph()
+
+        # Add a cast node
+        node_name = self.create_node_name("Cast")
+        input_name = node_name + "_" + graph_output.name
+        self.replace_input_of_all_nodes(graph_output.name, input_name)
+        new_value_info = graph.value_info.add()
+        new_value_info.CopyFrom(graph_output)
+        new_value_info.name = input_name
+        cast_node = helper.make_node(
+            "Cast",
+            [input_name],
+            [graph_output.name],
+            to=int(new_type),
+            name=node_name,
+        )
+        graph.node.extend([cast_node])
+        graph_output.type.tensor_type.elem_type = int(new_type)
+        return cast_node
+
+    def rename_graph_output(self, old_name: str, new_name: str):
+        if new_name in self.output_name_to_node():
+            raise RuntimeError("{new_name} exists in graph")
+
+        graph = self.graph()
+        for output in graph.output:
+            if output.name == old_name:
+                logger.debug("replace output name from %s to %s", old_name, new_name)
+                self.replace_input_of_all_nodes(old_name, new_name)
+                self.replace_output_of_all_nodes(old_name, new_name)
+                output.name = new_name
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bart.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bart.py
new file mode 100644
index 0000000000000000000000000000000000000000..5971c2432259971af6f040f4323d2e6cbc8704f4
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bart.py
@@ -0,0 +1,141 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+from fusion_attention import AttentionMask
+from fusion_bart_attention import FusionBartAttention
+from fusion_options import FusionOptions
+from fusion_reshape import FusionReshape
+from onnx import numpy_helper
+from onnx_model import OnnxModel
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class FusionBartReshape(FusionReshape):
+    def __init__(self, model: OnnxModel):
+        super().__init__(model)
+
+    def fuse(self, reshape_node, input_name_to_nodes, output_name_to_node):
+        if reshape_node.input[1] not in output_name_to_node:
+            return
+
+        concat_node = output_name_to_node[reshape_node.input[1]]
+        if concat_node.op_type != "Concat" or len(concat_node.input) != 4:
+            return
+
+        path0 = self.model.match_parent_path(
+            concat_node,
+            ["Unsqueeze", "Gather", "Shape"],
+            [0, 0, 0],
+            output_name_to_node,
+        )
+        if path0 is None:
+            return
+
+        (_, gather_0, shape_0) = path0
+
+        shape = []
+        gather_value = self.model.get_constant_value(gather_0.input[1])
+        if gather_value == 0:
+            shape.append(0)
+
+        path1 = self.model.match_parent_path(
+            concat_node,
+            ["Unsqueeze", "Gather", "Shape"],
+            [1, 0, 0],
+            output_name_to_node,
+        )
+        if path1 is None:
+            input_1_proto = self.model.get_initializer(concat_node.input[1])
+            input_2_proto = self.model.get_initializer(concat_node.input[2])
+            input_3_proto = self.model.get_initializer(concat_node.input[3])
+            if input_1_proto is None or input_2_proto is None or input_3_proto is None:
+                return
+
+            input_1 = numpy_helper.to_array(input_1_proto)
+            input_2 = numpy_helper.to_array(input_2_proto)
+            input_3 = numpy_helper.to_array(input_3_proto)
+            if len(input_1) != 1 or len(input_2) != 1 or len(input_3) != 1:
+                return
+
+            if not (input_1[0] == -1 and input_2[0] > 0 and input_3[0] > 0):
+                return
+
+            shape.extend(input_1)
+            shape.extend(input_2)
+            shape.extend(input_3)
+            gemm_path_with_bias = self.model.match_parent_path(
+                reshape_node, ["Add", "MatMul"], [0, 1], output_name_to_node
+            )
+            gemm_path_no_bias = self.model.match_parent_path(reshape_node, ["MatMul"], [0], output_name_to_node)
+            if gemm_path_with_bias is not None:
+                gemm_path = gemm_path_with_bias
+            elif gemm_path_no_bias is not None:
+                gemm_path = gemm_path_no_bias
+            else:
+                return
+
+            top_matmul = gemm_path[-1]
+            root_input = top_matmul.input[0]
+
+            self.replace_reshape_node(shape, reshape_node, concat_node)
+        else:
+            (_, gather_1, shape_1) = path1
+
+            gather_value = self.model.get_constant_value(gather_1.input[1])
+            if gather_value == 1:
+                shape.append(0)
+
+            input_2_proto = self.model.get_initializer(concat_node.input[2])
+            input_3_proto = self.model.get_initializer(concat_node.input[3])
+            if input_2_proto is None or input_3_proto is None:
+                return
+
+            input_2 = numpy_helper.to_array(input_2_proto)
+            input_3 = numpy_helper.to_array(input_3_proto)
+            if len(input_2) != 1 or len(input_3) != 1:
+                return
+
+            if not (input_2[0] > 0 and input_3[0] > 0):
+                return
+
+            shape.extend(input_2)
+            shape.extend(input_3)
+            gemm_path = self.model.match_parent_path(
+                reshape_node, ["Mul", "Add", "MatMul"], [0, 0, 1], output_name_to_node
+            )
+            if gemm_path is None:
+                return
+
+            top_matmul = gemm_path[-1]
+            root_input = top_matmul.input[0]
+            if shape_0.input[0] != root_input or shape_1.input[0] != root_input:
+                return
+
+            self.replace_reshape_node(shape, reshape_node, concat_node)
+
+
+class BartOnnxModel(BertOnnxModel):
+    def __init__(self, model, num_heads, hidden_size, model_impl="hf"):
+        super().__init__(model, num_heads, hidden_size)
+        self.attention_mask = AttentionMask(self)
+        self.attention_fusion = FusionBartAttention(self, self.hidden_size, self.num_heads, self.attention_mask)
+        self.bart_reshape_fusion_preprocess = FusionBartReshape(self)
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        self.attention_fusion.use_multi_head_attention = False if options is None else options.use_multi_head_attention
+        self.attention_fusion.disable_multi_head_attention_bias = (
+            False if options is None else options.disable_multi_head_attention_bias
+        )
+        super().optimize(options, add_dynamic_axes)
+
+    def fuse_attention(self):
+        self.attention_fusion.apply()
+
+    def preprocess(self):
+        self.adjust_reshape_and_expand()
+        self.bart_reshape_fusion_preprocess.apply()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert.py
new file mode 100644
index 0000000000000000000000000000000000000000..79ebc2723b8825dfd5998b66530667d49e729271
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert.py
@@ -0,0 +1,512 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from logging import getLogger
+
+import numpy as np
+from convert_to_packing_mode import PackingMode
+from fusion_attention import AttentionMask, FusionAttention
+from fusion_bart_attention import FusionBartAttention
+from fusion_biasgelu import FusionBiasGelu
+from fusion_constant_fold import FusionConstantFold
+from fusion_embedlayer import FusionEmbedLayerNormalization
+from fusion_fastgelu import FusionFastGelu
+from fusion_gelu import FusionGelu
+from fusion_gelu_approximation import FusionGeluApproximation
+from fusion_gemmfastgelu import FusionGemmFastGelu
+from fusion_layernorm import FusionLayerNormalization, FusionLayerNormalizationTF
+from fusion_options import AttentionMaskFormat, FusionOptions
+from fusion_qordered_attention import FusionQOrderedAttention
+from fusion_qordered_gelu import FusionQOrderedGelu
+from fusion_qordered_layernorm import FusionQOrderedLayerNormalization
+from fusion_qordered_matmul import FusionQOrderedMatMul
+from fusion_quickgelu import FusionQuickGelu
+from fusion_reshape import FusionReshape
+from fusion_rotary_attention import FusionRotaryEmbeddings
+from fusion_shape import FusionShape
+from fusion_simplified_layernorm import FusionSimplifiedLayerNormalization, FusionSkipSimplifiedLayerNormalization
+from fusion_skiplayernorm import FusionBiasSkipLayerNormalization, FusionSkipLayerNormalization
+from fusion_utils import FusionUtils
+from onnx import ModelProto, TensorProto, helper, numpy_helper
+from onnx_model import OnnxModel
+
+logger = getLogger(__name__)
+
+
+class BertOnnxModel(OnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        """Initialize BERT ONNX Model.
+
+        Args:
+            model (ModelProto): the ONNX model
+            num_heads (int, optional): number of attention heads. Defaults to 0 (detect the parameter automatically).
+            hidden_size (int, optional): hidden dimension. Defaults to 0 (detect the parameter automatically).
+        """
+        assert (num_heads == 0 and hidden_size == 0) or (num_heads > 0 and hidden_size % num_heads == 0)
+
+        super().__init__(model)
+        self.num_heads = num_heads
+        self.hidden_size = hidden_size
+
+        self.attention_mask = AttentionMask(self)
+        self.attention_fusion = FusionAttention(self, self.hidden_size, self.num_heads, self.attention_mask)
+        self.qordered_attention_fusion = FusionQOrderedAttention(
+            self, self.hidden_size, self.num_heads, self.attention_mask
+        )
+        self.utils = FusionUtils(self)
+
+    def fuse_constant_fold(self):
+        fusion = FusionConstantFold(self)
+        fusion.apply()
+
+    def fuse_attention(self):
+        self.attention_fusion.apply()
+        # Only relevant in models with Q-DQ nodes
+        self.qordered_attention_fusion.apply()
+
+    def fuse_gelu(self):
+        fusion = FusionGelu(self)
+        fusion.apply()
+        fusion = FusionFastGelu(self)
+        fusion.apply()
+        fusion = FusionQuickGelu(self)
+        fusion.apply()
+        # Only relevant in models with Q-DQ nodes
+        fusion = FusionQOrderedGelu(self)
+        fusion.apply()
+
+    def fuse_bias_gelu(self, is_fastgelu):
+        fusion = FusionBiasGelu(self, is_fastgelu)
+        fusion.apply()
+
+    def gelu_approximation(self):
+        fusion = FusionGeluApproximation(self)
+        fusion.apply()
+
+    def fuse_gemm_fast_gelu(self):
+        fusion = FusionGemmFastGelu(self)
+        fusion.apply()
+
+    def fuse_add_bias_skip_layer_norm(self):
+        fusion = FusionBiasSkipLayerNormalization(self)
+        fusion.apply()
+
+    def fuse_reshape(self):
+        fusion = FusionReshape(self)
+        fusion.apply()
+
+    def fuse_shape(self):
+        fusion = FusionShape(self)
+        fusion.apply()
+
+    def fuse_embed_layer(self, use_mask_index):
+        fusion = FusionEmbedLayerNormalization(self, use_mask_index)
+        fusion.apply()
+
+    def fuse_layer_norm(self):
+        fusion = FusionLayerNormalization(self)
+        fusion.apply()
+
+        fusion = FusionLayerNormalizationTF(self)
+        fusion.apply()
+
+        # Only relevant in models with Q-DQ nodes
+        fusion = FusionQOrderedLayerNormalization(self)
+        fusion.apply()
+
+    def fuse_simplified_layer_norm(self):
+        fusion = FusionSimplifiedLayerNormalization(self)
+        fusion.apply()
+
+    def fuse_skip_layer_norm(self, shape_infer=True):
+        fusion = FusionSkipLayerNormalization(self, shape_infer=shape_infer)
+        fusion.apply()
+
+    def fuse_skip_simplified_layer_norm(self):
+        fusion = FusionSkipSimplifiedLayerNormalization(self)
+        fusion.apply()
+
+    def fuse_rotary_embeddings(self):
+        fusion = FusionRotaryEmbeddings(self)
+        fusion.apply()
+        # Remove non-MS domain functions
+        rot_emb_nodes = list(
+            filter(
+                lambda node: node.op_type == "RotaryEmbedding" and node.domain != "com.microsoft",
+                self.model.graph.node,
+            )
+        )
+        non_ms_domains_to_keep = {node.domain for node in rot_emb_nodes}
+        i = 0
+        while i < len(self.model.functions):
+            fn = self.model.functions[i]
+            if "RotaryEmbedding" in fn.name and fn.domain not in non_ms_domains_to_keep:
+                self.model.functions.remove(fn)
+            else:
+                i += 1
+
+    # Only relevant in models with Q-DQ nodes
+    def fuse_qordered_mamtul(self):
+        fusion = FusionQOrderedMatMul(self)
+        fusion.apply()
+
+    def get_graph_inputs_from_node_type(self, op_type: str, input_indices: list[int], casted: bool):
+        """
+        Get graph inputs that feed into node type (like EmbedLayerNormalization or Attention).
+        Returns a list of the graph input names based on the filter whether it is casted or not.
+        """
+        graph_inputs = []
+
+        output_name_to_node = self.output_name_to_node()
+        nodes = self.get_nodes_by_op_type(op_type)
+        for node in nodes:
+            bert_inputs = [node.input[i] for i in input_indices if i < len(node.input)]
+            for bert_input in bert_inputs:
+                if self.find_graph_input(bert_input):
+                    if not casted:
+                        graph_inputs.append(bert_input)
+                elif bert_input in output_name_to_node:
+                    parent = output_name_to_node[bert_input]
+                    if parent.op_type == "Cast" and self.find_graph_input(parent.input[0]) is not None:
+                        if casted:
+                            graph_inputs.append(parent.input[0])
+        return graph_inputs
+
+    def get_graph_inputs_from_fused_nodes(self, casted: bool):
+        inputs = self.get_graph_inputs_from_node_type("EmbedLayerNormalization", [0, 1, 7], casted)
+        inputs += self.get_graph_inputs_from_node_type("Attention", [3], casted)
+        return inputs
+
+    def change_graph_inputs_to_int32(self):
+        """Change data type of all graph inputs to int32 type, and add Cast node if needed."""
+        graph = self.graph()
+        add_cast_count = 0
+        remove_cast_count = 0
+        for graph_input in graph.input:
+            new_node, removed_nodes = self.change_graph_input_type(graph_input, TensorProto.INT32)
+            if new_node:
+                add_cast_count += 1
+            remove_cast_count += len(removed_nodes)
+        logger.info(
+            f"Graph inputs are changed to int32. Added {add_cast_count} Cast nodes, and removed {remove_cast_count} Cast nodes."
+        )
+
+    def use_dynamic_axes(self, dynamic_batch_dim="batch_size", dynamic_seq_len="max_seq_len"):
+        """
+        Update input and output shape to use dynamic axes.
+        """
+        bert_graph_inputs = self.get_graph_inputs_from_fused_nodes(
+            casted=True
+        ) + self.get_graph_inputs_from_fused_nodes(casted=False)
+
+        for input in self.model.graph.input:
+            if input.name in bert_graph_inputs:
+                dim_proto = input.type.tensor_type.shape.dim[0]
+                dim_proto.dim_param = dynamic_batch_dim
+                if dynamic_seq_len is not None:
+                    dim_proto = input.type.tensor_type.shape.dim[1]
+                    dim_proto.dim_param = dynamic_seq_len
+
+        for output in self.model.graph.output:
+            dim_proto = output.type.tensor_type.shape.dim[0]
+            dim_proto.dim_param = dynamic_batch_dim
+
+    def preprocess(self):
+        self.adjust_reshape_and_expand()
+        return
+
+    def adjust_reshape_and_expand(self):
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Reshape":
+                # Clean up unnecessary reshape nodes.
+                # Find reshape nodes with no actually data in "shape" attribute and remove.
+                reshape_shape = self.get_constant_value(node.input[1])
+                if reshape_shape is not None and reshape_shape.size == 0:
+                    nodes_to_remove.extend([node])
+                    self.replace_input_of_all_nodes(node.output[0], node.input[0])
+                    continue
+
+                # Find path "Slice" -> "Reshape" -> "Expand" -> "Expand" -> current "Reshape", simplify the graph by
+                # changing current reshape's input to output of slice.
+                reshape_path = self.match_parent_path(
+                    node,
+                    ["Expand", "Expand", "Reshape", "Slice"],
+                    [0, 0, 0, 0],
+                    self.output_name_to_node(),
+                )
+                if reshape_path is not None:
+                    expand_node = reshape_path[-3]
+                    expand_shape_value = self.get_constant_value(expand_node.input[1])
+
+                    reshape_before_expand = reshape_path[-2]
+                    shape_value = self.get_constant_value(reshape_before_expand.input[1])
+
+                    slice_node = reshape_path[-1]
+                    if (
+                        expand_shape_value is not None
+                        and shape_value is not None
+                        and len(expand_shape_value) == 2
+                        and len(shape_value) == 1
+                        and expand_shape_value[1] == shape_value[0]
+                    ):
+                        node.input[0] = slice_node.output[0]
+
+        if nodes_to_remove:
+            self.remove_nodes(nodes_to_remove)
+            logger.info(f"Removed Reshape and Expand count: {len(nodes_to_remove)}")
+
+    def clean_graph(self):
+        output_name_to_node = self.output_name_to_node()
+        nodes_to_remove = []
+        for node in self.nodes():
+            # Before:
+            #  input_ids --> Shape --> Gather(indices=0) --> Unsqueeze ------+
+            #          |                                                     |
+            #          |                                                     v
+            #          +----> Shape --> Gather(indices=1) --> Unsqueeze--->  Concat --> ConstantOfShape -->Cast --> EmbedLayerNormaliation/ReduceSum
+            # After (Concat path simplified, Cast merged into ConstantOfShape):
+            #  input_ids --> Shape --> ConstantOfShape --> EmbedLayerNormalization/ReduceSum
+            op_input_id = {"EmbedLayerNormalization": 1, "ReduceSum": 0, "Attention": 3}
+            if node.op_type in op_input_id:
+                i = op_input_id[node.op_type]
+                parent_nodes = self.match_parent_path(
+                    node,
+                    [
+                        "Cast",
+                        "ConstantOfShape",
+                        "Concat",
+                        "Unsqueeze",
+                        "Gather",
+                        "Shape",
+                    ],
+                    [i, 0, 0, 0, 0, 0],
+                    output_name_to_node,
+                )
+                if parent_nodes is not None:
+                    (
+                        cast,
+                        constant_of_shape,
+                        concat,
+                        unsqueeze,
+                        gather,
+                        shape,
+                    ) = parent_nodes
+                    if shape.input[0] == self.graph().input[0].name:
+                        constant_of_shape.input[0] = shape.output[0]
+
+                        # Merge ConstantOfShape → Cast: update the value attribute dtype
+                        # so ConstantOfShape directly produces the target type.
+                        cast_to_type = OnnxModel.get_node_attribute(cast, "to")
+                        cos_tensor = OnnxModel.get_node_attribute(constant_of_shape, "value")
+                        if cast_to_type is not None and cos_tensor is not None:
+                            fill_val = numpy_helper.to_array(cos_tensor).flat[0]
+                            np_dtype = helper.tensor_dtype_to_np_dtype(cast_to_type)
+                            new_val = numpy_helper.from_array(np.array([fill_val], dtype=np_dtype))
+                            for i, attr in enumerate(constant_of_shape.attribute):
+                                if attr.name == "value":
+                                    constant_of_shape.attribute[i].CopyFrom(helper.make_attribute("value", new_val))
+                                    break
+                            self.replace_input_of_all_nodes(cast.output[0], constant_of_shape.output[0])
+                            nodes_to_remove.append(cast)
+
+                        output_name_to_node = self.output_name_to_node()
+
+            if node.op_type == "Attention":
+                # Before (Cast present or already merged into ConstantOfShape):
+                #   input_ids --> Shape --> ConstantOfShape [--> Cast] --> ReduceSum --> Attention
+                # After:
+                #   remove this path, and remove the optional mask_index input of Attention node.
+                parent_nodes = self.match_parent_path(
+                    node,
+                    ["ReduceSum", "Cast", "ConstantOfShape", "Shape"],
+                    [3, 0, 0, 0],
+                    output_name_to_node,
+                )
+                if parent_nodes is None:
+                    # Also try merged pattern (Cast already folded into ConstantOfShape).
+                    parent_nodes = self.match_parent_path(
+                        node,
+                        ["ReduceSum", "ConstantOfShape", "Shape"],
+                        [3, 0, 0],
+                        output_name_to_node,
+                    )
+                if parent_nodes is not None:
+                    if parent_nodes[-1].input[0] == self.graph().input[0].name:
+                        attention_node = helper.make_node(
+                            "Attention",
+                            inputs=node.input[0 : len(node.input) - 1],
+                            outputs=node.output,
+                            name=node.name + "_remove_mask",
+                        )
+                        attention_node.domain = "com.microsoft"
+                        attention_node.attribute.extend([helper.make_attribute("num_heads", self.num_heads)])
+                        self.add_node(attention_node, self.get_graph_by_node(node).name)
+                        nodes_to_remove.append(node)
+        self.remove_nodes(nodes_to_remove)
+
+    def postprocess(self):
+        self.clean_graph()
+        self.prune_graph()
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        if (options is not None) and not options.enable_shape_inference:
+            self.disable_shape_inference()
+
+        self.utils.remove_identity_nodes()
+
+        # Remove cast nodes that having same data type of input and output based on symbolic shape inference.
+        self.utils.remove_useless_cast_nodes()
+
+        # Apply any missed constant-folding model optimizations (e.g. for Dynamo-exported models)
+        self.fuse_constant_fold()
+
+        if (options is None) or options.enable_layer_norm:
+            self.fuse_layer_norm()
+            self.fuse_simplified_layer_norm()
+
+        if (options is None) or options.enable_gelu:
+            self.fuse_gelu()
+
+        self.preprocess()
+
+        self.fuse_reshape()
+
+        if (options is None) or options.enable_skip_layer_norm:
+            self.fuse_skip_layer_norm(options.enable_shape_inference)
+            self.fuse_skip_simplified_layer_norm()
+
+        if (options is None) or options.enable_rotary_embeddings:
+            self.fuse_rotary_embeddings()
+
+        if options is not None:
+            self.attention_mask.set_mask_format(options.attention_mask_format)
+            if options.use_multi_head_attention and not isinstance(self.attention_fusion, FusionBartAttention):
+                self.attention_fusion = FusionAttention(
+                    self,
+                    self.hidden_size,
+                    self.num_heads,
+                    self.attention_mask,
+                    options.use_multi_head_attention,
+                )
+
+        if (options is None) or options.enable_attention:
+            self.fuse_attention()
+
+        # Perform the MatMul fusion after the Attention fusion as we do not
+        # want to fuse the MatMuls inside the Attention subgraphs
+        if (options is None) or options.enable_qordered_matmul:
+            self.fuse_qordered_mamtul()
+
+        self.fuse_shape()
+
+        if (options is None) or options.enable_embed_layer_norm:
+            use_mask_index = options.attention_mask_format == AttentionMaskFormat.MaskIndexEnd
+            self.fuse_embed_layer(use_mask_index)
+
+        # Remove reshape nodes that having same shape of input and output based on symbolic shape inference.
+        self.utils.remove_useless_reshape_nodes()
+
+        self.postprocess()
+
+        # Bias fusion is done after postprocess to avoid extra Reshape between bias and Gelu/FastGelu/SkipLayerNormalization
+        if (options is None) or options.enable_bias_gelu:
+            # Fuse Gelu and Add Bias before it.
+            self.fuse_bias_gelu(is_fastgelu=True)
+            self.fuse_bias_gelu(is_fastgelu=False)
+
+        if (options is None) or options.enable_bias_skip_layer_norm:
+            # Fuse SkipLayerNormalization and Add Bias before it.
+            self.fuse_add_bias_skip_layer_norm()
+
+        if options is not None and options.enable_gelu_approximation:
+            self.gelu_approximation()
+
+        if options is not None and options.enable_gemm_fast_gelu:
+            self.fuse_gemm_fast_gelu()
+
+        self.remove_unused_constant()
+
+        # Use symbolic batch dimension in input and output.
+        if add_dynamic_axes:
+            self.use_dynamic_axes()
+
+        logger.info(f"opset version: {self.get_opset_version()}")
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "EmbedLayerNormalization",
+            "Attention",
+            "MultiHeadAttention",
+            "Gelu",
+            "FastGelu",
+            "BiasGelu",
+            "GemmFastGelu",
+            "LayerNormalization",
+            "SimplifiedLayerNormalization",
+            "SkipLayerNormalization",
+            "SkipSimplifiedLayerNormalization",
+            "RotaryEmbedding",
+        ]
+        q_ops = [
+            "QOrderedAttention",
+            "QOrderedGelu",
+            "QOrderedLayerNormalization",
+            "QOrderedMatMul",
+        ]
+        for op in ops + q_ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators: {op_count}")
+        return op_count
+
+    def is_fully_optimized(self, fused_op_count=None):
+        """
+        Returns True when the model is fully optimized.
+        """
+        if fused_op_count is None:
+            fused_op_count = self.get_fused_operator_statistics()
+
+        def op_count(op_name: str):
+            return fused_op_count.get(op_name) or 0
+
+        embed = op_count("EmbedLayerNormalization")
+        attention = op_count("Attention") + op_count("MultiHeadAttention") + op_count("QOrderedAttention")
+        gelu = op_count("Gelu") + op_count("BiasGelu") + op_count("FastGelu")
+        layer_norm = op_count("LayerNormalization") + op_count("SkipLayerNormalization")
+        simple_layer_norm = op_count("SimplifiedLayerNormalization") + op_count("SkipSimplifiedLayerNormalization")
+
+        is_perfect = (
+            (embed > 0)
+            and (attention > 0)
+            and (attention == gelu)
+            and ((layer_norm >= 2 * attention) or (simple_layer_norm >= 2 * attention))
+        )
+
+        if layer_norm == 0:
+            logger.debug("Layer Normalization not fused")
+
+        if simple_layer_norm == 0:
+            logger.debug("Simple Layer Normalization not fused")
+
+        if gelu == 0:
+            logger.debug("Gelu (or FastGelu) not fused")
+
+        if embed == 0:
+            logger.debug("EmbedLayerNormalization not fused")
+
+        if attention == 0:
+            logger.warning("Attention (or MultiHeadAttention) not fused")
+
+        return is_perfect
+
+    def convert_to_packing_mode(self, use_symbolic_shape_infer: bool = False):
+        packing_mode = PackingMode(self)
+        packing_mode.convert(use_symbolic_shape_infer)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_keras.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_keras.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4e885c5aad10dac705b23b34042f0b5f7758a2e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_keras.py
@@ -0,0 +1,474 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+import onnx
+from onnx import numpy_helper
+from onnx_model_bert_tf import BertOnnxModelTF
+
+logger = logging.getLogger(__name__)
+
+
+class BertOnnxModelKeras(BertOnnxModelTF):
+    def __init__(self, model, num_heads, hidden_size):
+        super().__init__(model, num_heads, hidden_size)
+
+    def match_mask_path(self, add_or_sub_before_softmax):
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Reshape", "Cast"],
+            [1, None, 1, 0],
+        )
+        if mask_nodes is not None:
+            return mask_nodes
+
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Cast", "Slice", "Unsqueeze"],
+            [1, 1, 1, 0, 0],
+        )
+        if mask_nodes is not None:
+            return mask_nodes
+
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+            [1, None, 1, 0, 0],
+        )
+        return mask_nodes
+
+    def check_attention_input(self, matmul_q, matmul_k, matmul_v, parent, output_name_to_node):
+        reshape_nodes = []
+
+        for x in [matmul_q, matmul_k, matmul_v]:
+            root_input = x.input[0]
+            root_node = output_name_to_node[root_input]
+            if root_node == parent:
+                continue
+            if root_node.op_type == "Reshape" and root_node.input[0] == parent.output[0]:
+                reshape_nodes.append(root_node)
+                continue
+            logger.debug(f"Check attention input failed:{root_input}, {parent.output[0]}")
+            return False, []
+
+        return True, reshape_nodes
+
+    def fuse_attention(self):
+        self.input_name_to_nodes()
+        output_name_to_node = self.output_name_to_node()
+
+        nodes_to_remove = []
+        attention_count = 0
+
+        skip_layer_norm_nodes = self.get_nodes_by_op_type("SkipLayerNormalization")
+        for normalize_node in skip_layer_norm_nodes:
+            # SkipLayerNormalization has two inputs, and one of them is the root input for attention.
+            parent = self.get_parent(normalize_node, 0)
+            if parent is None or parent.op_type not in [
+                "SkipLayerNormalization",
+                "EmbedLayerNormalization",
+            ]:
+                if parent.op_type == "Add":
+                    parent = self.get_parent(normalize_node, 1)
+                    if parent is None or parent.op_type not in [
+                        "SkipLayerNormalization",
+                        "EmbedLayerNormalization",
+                    ]:
+                        logger.debug(f"First input for skiplayernorm: {parent.op_type if parent is not None else None}")
+                        continue
+                else:
+                    logger.debug(f"First input for skiplayernorm: {parent.op_type if parent is not None else None}")
+                    continue
+            else:
+                # TODO: shall we add back the checking of children op types.
+                pass
+
+            qkv_nodes = self.match_parent_path(
+                normalize_node,
+                ["Add", "Reshape", "MatMul", "Reshape", "Transpose", "MatMul"],
+                [None, 0, 0, 0, 0, 0],
+            )
+            if qkv_nodes is None:
+                logger.debug("Failed to match qkv nodes")
+                continue
+            (
+                add,
+                extra_reshape_0,
+                matmul,
+                reshape_qkv,
+                transpose_qkv,
+                matmul_qkv,
+            ) = qkv_nodes
+            logger.debug("Matched qkv nodes")
+
+            v_nodes = self.match_parent_path(
+                matmul_qkv,
+                ["Transpose", "Reshape", "Add", "Reshape", "MatMul"],
+                [1, 0, 0, 0, 0],
+            )
+            if v_nodes is None:
+                logger.debug("Failed to match v path")
+                continue
+            (transpose_v, reshape_v, add_v, extra_reshape_1, matmul_v) = v_nodes
+
+            qk_nodes = self.match_parent_path(matmul_qkv, ["Softmax", "Sub", "MatMul"], [0, 0, 0])
+            if qk_nodes is not None:
+                (softmax_qk, sub_qk, matmul_qk) = qk_nodes
+                q_nodes = self.match_parent_path(
+                    matmul_qk,
+                    ["Mul", "Transpose", "Reshape", "Add", "Reshape", "MatMul"],
+                    [0, None, 0, 0, 0, 0],
+                )
+                if q_nodes is not None:
+                    (
+                        mul_q,
+                        transpose_q,
+                        reshape_q,
+                        add_q,
+                        extra_reshape_2,
+                        matmul_q,
+                    ) = q_nodes
+
+            else:
+                qk_nodes = self.match_parent_path(matmul_qkv, ["Softmax", "Add", "Mul", "MatMul"], [0, 0, 0, None])
+                if qk_nodes is None:
+                    qk_nodes = self.match_parent_path(matmul_qkv, ["Softmax", "Add", "Div", "MatMul"], [0, 0, 0, None])
+                    if qk_nodes is None:
+                        logger.debug("Failed to match qk path")
+                        continue
+                (softmax_qk, add_qk, mul_qk, matmul_qk) = qk_nodes
+
+                q_nodes = self.match_parent_path(
+                    matmul_qk,
+                    ["Transpose", "Reshape", "Add", "Reshape", "MatMul"],
+                    [0, 0, 0, 0, 0],
+                )
+                if q_nodes is not None:
+                    (transpose_q, reshape_q, add_q, extra_reshape_2, matmul_q) = q_nodes
+
+            if q_nodes is None:
+                logger.debug("Failed to match q path")
+                continue
+
+            k_nodes = self.match_parent_path(
+                matmul_qk,
+                ["Transpose", "Reshape", "Add", "Reshape", "MatMul"],
+                [1, 0, 0, 0, 0],
+            )
+            if k_nodes is None:
+                logger.debug("Failed to match k path")
+                continue
+            (transpose_k, reshape_k, add_k, extra_reshape_3, matmul_k) = k_nodes
+
+            mask_nodes = self.match_mask_path(qk_nodes[1])
+            if mask_nodes is None:
+                logger.debug("Failed to match mask path")
+                continue
+            if not self.has_constant_input(mask_nodes[1], 1):
+                logger.debug("Sub node expected to have an input with constant value 1.0.")
+                continue
+
+            is_same_root, reshape_nodes = self.check_attention_input(
+                matmul_q, matmul_k, matmul_v, parent, output_name_to_node
+            )
+            if is_same_root:
+                mask_index = self.attention_mask.process_mask(mask_nodes[-1].input[0])
+                logger.debug("Create an Attention node.")
+                attention_node = self.attention_fusion.create_attention_node(
+                    mask_index=mask_index,
+                    q_matmul=matmul_q,
+                    k_matmul=matmul_k,
+                    v_matmul=matmul_v,
+                    q_add=add_q,
+                    k_add=add_k,
+                    v_add=add_v,
+                    num_heads=self.num_heads,
+                    hidden_size=self.hidden_size,
+                    first_input=parent.output[0],
+                    output=reshape_qkv.output[0],
+                )
+                if attention_node is None:
+                    continue
+
+                self.add_node(attention_node)
+                attention_count += 1
+
+                nodes_to_remove.extend([reshape_qkv, transpose_qkv, matmul_qkv])
+                nodes_to_remove.extend(qk_nodes)
+                nodes_to_remove.extend(q_nodes)
+                nodes_to_remove.extend(k_nodes)
+                nodes_to_remove.extend(v_nodes)
+                nodes_to_remove.extend(mask_nodes)
+                nodes_to_remove.extend(reshape_nodes)
+                nodes_to_remove.append(extra_reshape_0)
+                self.replace_node_input(add, extra_reshape_0.output[0], matmul.output[0])
+            else:
+                logger.debug("Root node not matched.")
+                continue
+        self.remove_nodes(nodes_to_remove)
+        self.update_graph()
+        logger.info(f"Fused Attention count:{attention_count}")
+
+    def preprocess(self):
+        self.process_embedding()
+        self.fuse_mask()
+        self.skip_reshape()
+
+    def skip_reshape(self):
+        self.input_name_to_nodes()
+        self.output_name_to_node()
+
+        count = 0
+        reshape_nodes = self.get_nodes_by_op_type("Reshape")
+        for reshape_node in reshape_nodes:
+            parent = self.get_parent(reshape_node, 0)
+            if parent is not None and parent.op_type == "Reshape":
+                reshape_node.input[0] = parent.input[0]
+                count += 1
+
+        if count > 0:
+            logger.info(f"Skip consequent Reshape count: {count}")
+
+    def fuse_embedding(self, node, output_name_to_node):
+        assert node.op_type == "LayerNormalization"
+        logger.debug(f"start fusing embedding from node with output={node.output[0]}...")
+        word_embed_path = self.match_parent_path(node, ["Add", "Add", "Gather"], [0, 0, 0], output_name_to_node)
+        if word_embed_path is None:
+            logger.debug("failed to match word_embed_path")
+            return False
+
+        skip_node, add_node, gather_node = word_embed_path
+
+        word_initializer = self.get_initializer(gather_node.input[0])
+        if word_initializer is None:
+            logger.debug("failed to get word initializer")
+            return False
+
+        temp = numpy_helper.to_array(word_initializer)
+        if len(temp.shape) == 2:
+            logger.info(f"Found word embedding. name:{word_initializer.name}, shape:{temp.shape}")
+            word_embedding = word_initializer.name
+        else:
+            logger.info(f"Failed to find word embedding. name:{word_initializer.name}, shape:{temp.shape}")
+            return False
+
+        pos_initializer = self.get_initializer(add_node.input[1])
+        if pos_initializer is not None:
+            temp = numpy_helper.to_array(pos_initializer)
+            if len(temp.shape) == 3 and temp.shape[0] == 1:
+                tensor = numpy_helper.from_array(temp.reshape((temp.shape[1], temp.shape[2])), "position_embedding")
+                self.add_initializer(tensor)
+                logger.info(f"Found position embedding. name:{pos_initializer.name}, shape:{temp.shape[1:]}")
+                position_embedding = "position_embedding"
+            else:
+                logger.info(f"Failed to find position embedding. name:{pos_initializer.name}, shape:{temp.shape}")
+                return False
+        else:
+            pos_embed_path = self.match_parent_path(add_node, ["Gather", "Slice"], [1, 1], output_name_to_node)
+            if pos_embed_path is None:
+                logger.debug("failed to match pos_embed_path")
+                return False
+
+            pos_gather, pos_slice = pos_embed_path
+            pos_initializer = self.get_initializer(pos_gather.input[0])
+            if pos_initializer is None:
+                logger.debug("failed to get pos initializer")
+                return False
+
+            temp = numpy_helper.to_array(pos_initializer)
+            if len(temp.shape) == 2:
+                logger.info(f"Found word embedding. name:{pos_initializer.name}, shape:{temp.shape}")
+                position_embedding = pos_initializer.name
+            else:
+                logger.info(f"Failed to find position embedding. name:{pos_initializer.name}, shape:{temp.shape}")
+                return False
+
+        gather = self.get_parent(skip_node, 1, output_name_to_node)
+        if gather is None or gather.op_type != "Gather":
+            logger.debug("failed to get gather")
+            return False
+
+        segment_initializer = self.get_initializer(gather.input[0])
+        if segment_initializer is None:
+            logger.debug("failed to get segment initializer")
+            return False
+
+        temp = numpy_helper.to_array(segment_initializer)
+        if len(temp.shape) == 2:
+            logger.info(f"Found segment embedding. name:{segment_initializer.name}, shape:{temp.shape}")
+            segment_embedding = segment_initializer.name
+        else:
+            logger.info(f"Failed to find segment embedding. name:{segment_initializer.name}, shape:{temp.shape}")
+            return False
+
+        logger.info("Create Embedding node")
+        self.create_embedding_subgraph(node, word_embedding, segment_embedding, position_embedding)
+        return True
+
+    def process_embedding(self):
+        """
+        Automatically detect word, segment and position embeddings.
+        """
+        logger.info("start processing embedding layer...")
+        output_name_to_node = self.output_name_to_node()
+        for node in self.nodes():
+            if node.op_type == "LayerNormalization":
+                if self.fuse_embedding(node, output_name_to_node):
+                    return
+                break
+
+    def fuse_mask(self):
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Mul" and self.has_constant_input(node, -10000):
+                mask_path = self.match_parent_path(node, ["Sub", "Cast", "Slice", "Unsqueeze"], [0, 1, 0, 0])
+                if mask_path is None:
+                    continue
+                sub_node, cast_node, slice_node, unsqueeze_node = mask_path
+
+                mask_input_name = self.attention_mask.get_first_mask()
+                if unsqueeze_node.input[0] != mask_input_name:
+                    print(f"Cast input {unsqueeze_node.input[0]} is not mask input {mask_input_name}")
+                    continue
+
+                unsqueeze_added_1 = onnx.helper.make_node(
+                    "Unsqueeze",
+                    inputs=[mask_input_name],
+                    outputs=["mask_fuse_unsqueeze1_output"],
+                    name="Mask_UnSqueeze_1",
+                    axes=[1],
+                )
+
+                unsqueeze_added_2 = onnx.helper.make_node(
+                    "Unsqueeze",
+                    inputs=["mask_fuse_unsqueeze1_output"],
+                    outputs=["mask_fuse_unsqueeze2_output"],
+                    name="Mask_UnSqueeze_2",
+                    axes=[2],
+                )
+
+                # self.replace_node_input(cast_node, cast_node.input[0], 'mask_fuse_unsqueeze2_output')
+                cast_node_2 = onnx.helper.make_node(
+                    "Cast",
+                    inputs=["mask_fuse_unsqueeze2_output"],
+                    outputs=["mask_fuse_cast_output"],
+                )
+                cast_node_2.attribute.extend([onnx.helper.make_attribute("to", 1)])
+                self.replace_node_input(sub_node, sub_node.input[1], "mask_fuse_cast_output")
+
+                nodes_to_remove.extend([slice_node, unsqueeze_node, cast_node])
+                self.add_node(unsqueeze_added_1)
+                self.add_node(unsqueeze_added_2)
+                self.add_node(cast_node_2)
+
+        self.remove_nodes(nodes_to_remove)
+
+        # Prune graph is done after removing nodes to remove island nodes.
+        if len(nodes_to_remove) > 0:
+            self.prune_graph()
+
+        logger.info("Fused mask" if len(nodes_to_remove) > 0 else "Failed to fuse mask")
+
+    def remove_extra_reshape(self):
+        skiplayernorm_nodes = self.get_nodes_by_op_type("SkipLayerNormalization")
+        reshape_removed = 0
+        for skiplayernorm_node in skiplayernorm_nodes:
+            path = self.match_parent_path(
+                skiplayernorm_node,
+                [
+                    "Add",
+                    "Reshape",
+                    "MatMul",
+                    "Reshape",
+                    "Gelu",
+                    "Add",
+                    "Reshape",
+                    "MatMul",
+                    "SkipLayerNormalization",
+                ],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0],
+            )
+            if path is None:
+                continue
+
+            (
+                add_1,
+                reshape_1,
+                matmul_1,
+                reshape_2,
+                gelu,
+                add_2,
+                reshape_3,
+                matmul_2,
+                skiplayernorm,
+            ) = path
+            add_2.input[0] = matmul_2.output[0]
+            self.remove_node(reshape_3)
+            matmul_1.input[0] = gelu.output[0]
+            self.remove_node(reshape_2)
+            add_1.input[0] = matmul_1.output[0]
+            self.remove_node(reshape_1)
+            reshape_removed += 3
+
+        return reshape_removed
+
+    def remove_extra_reshape_2(self):
+        skiplayernorm_nodes = self.get_nodes_by_op_type("SkipLayerNormalization")
+        reshape_removed = 0
+        for skiplayernorm_node in skiplayernorm_nodes:
+            path = self.match_parent_path(
+                skiplayernorm_node,
+                [
+                    "Add",
+                    "Reshape",
+                    "MatMul",
+                    "Reshape",
+                    "Gelu",
+                    "Add",
+                    "Reshape",
+                    "MatMul",
+                    "Reshape",
+                    "SkipLayerNormalization",
+                ],
+                [None, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+            )
+            if path is None:
+                continue
+
+            (
+                add_1,
+                reshape_1,
+                matmul_1,
+                reshape_2,
+                gelu,
+                add_2,
+                reshape_3,
+                matmul_2,
+                reshape_4,
+                skiplayernorm,
+            ) = path
+
+            matmul_2.input[0] = skiplayernorm.output[0]
+            self.remove_node(reshape_4)
+
+            add_2.input[0] = matmul_2.output[0]
+            self.remove_node(reshape_3)
+
+            matmul_1.input[0] = gelu.output[0]
+            self.remove_node(reshape_2)
+
+            add_1.input[0] = matmul_1.output[0]
+            self.remove_node(reshape_1)
+
+            reshape_removed += 4
+
+        return reshape_removed
+
+    def postprocess(self):
+        reshape_removed = self.remove_extra_reshape() + self.remove_extra_reshape_2()
+        logger.info(f"Remove {reshape_removed} Reshape nodes.")
+
+        self.prune_graph()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_tf.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_tf.py
new file mode 100644
index 0000000000000000000000000000000000000000..80d1cab7ba05f381418425205b82edcadb2ecb32
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_bert_tf.py
@@ -0,0 +1,588 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+import numpy as np
+import onnx
+from onnx import TensorProto, helper, numpy_helper
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class BertOnnxModelTF(BertOnnxModel):
+    def __init__(self, model, num_heads, hidden_size):
+        super().__init__(model, num_heads, hidden_size)
+
+    def remove_identity(self):
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Identity":
+                if not self.find_graph_output(node.output[0]):
+                    self.replace_input_of_all_nodes(node.output[0], node.input[0])
+                    nodes_to_remove.append(node)
+        self.remove_nodes(nodes_to_remove)
+        logger.info(f"Removed Identity count: {len(nodes_to_remove)}")
+
+    def match_mask_path(self, add_or_sub_before_softmax):
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Reshape", "Cast"],
+            [1, None, 1, 0],
+        )
+        if mask_nodes is not None:
+            return mask_nodes
+
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Cast", "Slice", "Unsqueeze"],
+            [1, 0, 1, 0, 0],
+        )
+        if mask_nodes is not None:
+            return mask_nodes
+
+        mask_nodes = self.match_parent_path(
+            add_or_sub_before_softmax,
+            ["Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+            [1, None, 1, 0, 0],
+        )
+
+        return mask_nodes
+
+    def get_2d_initializers_from_parent_subgraphs(self, current_node):
+        """
+        Find initializers that is 2D. Returns a dictionary with name as key and shape as value.
+        """
+        parent_nodes = self.get_parent_subgraph_nodes(current_node, [])
+        initializers = {}
+        for node in parent_nodes:
+            for input in node.input:
+                initializer = self.get_initializer(input)
+                if initializer:
+                    temp = numpy_helper.to_array(initializer)
+                    if len(temp.shape) == 2:
+                        initializers[initializer.name] = temp.shape
+
+        return initializers
+
+    def find_segment_ids(self, segment_embedding, input_ids):
+        input_name_to_nodes = self.input_name_to_nodes()
+        if segment_embedding not in input_name_to_nodes:
+            return None
+
+        nodes = input_name_to_nodes[segment_embedding]
+        if len(nodes) != 1:
+            return None
+
+        graph_inputs = self.get_graph_inputs(nodes[0], recursive=True)
+        if len(graph_inputs) > 1:
+            print("Found multiple candidates of segment_ids", graph_inputs)
+            return None
+        # Find segment ids in graph inputs. The segment id input must not be the same as input_ids.
+        if len(graph_inputs) == 1 and graph_inputs[0] != input_ids:
+            return graph_inputs[0]
+
+        # If the segment id candidate is the same as the input_ids, try to assign alternative segment ids and simplify the graph if needed.
+        segment_ids = nodes[0].input[1]
+        _, segment_id_path, _ = self.match_parent_paths(
+            nodes[0],
+            [
+                (
+                    ["ConstantOfShape", "Cast", "Concat", "Slice", "Cast", "Shape"],
+                    [1, 0, 0, 0, 0, 0],
+                ),
+                (
+                    [
+                        "ConstantOfShape",
+                        "Cast",
+                        "Concat",
+                        "Unsqueeze",
+                        "Squeeze",
+                        "Slice",
+                        "Cast",
+                        "Shape",
+                    ],
+                    [1, 0, 0, 0, 0, 0, 0, 0],
+                ),
+            ],
+            None,
+        )
+
+        if segment_id_path and input_ids and input_ids == segment_id_path[-1].input[0]:
+            logger.debug("Simplify semgent id path...")
+            constantofshape_node = segment_id_path[0]
+            graph_name = self.get_graph_by_node(constantofshape_node).name
+            self.add_node(
+                helper.make_node("Shape", inputs=[input_ids], outputs=["input_shape"]),
+                graph_name,
+            )
+            constantofshape_value = helper.get_attribute_value(constantofshape_node.attribute[0])
+            self.add_node(
+                helper.make_node(
+                    "ConstantOfShape",
+                    inputs=["input_shape"],
+                    outputs=["zeros_for_input_shape"],
+                    value=constantofshape_value,
+                ),
+                graph_name,
+            )
+            segment_ids = "zeros_for_input_shape"
+        return segment_ids
+
+    def find_input_ids(self, word_embedding):
+        input_name_to_nodes = self.input_name_to_nodes()
+        if word_embedding not in input_name_to_nodes:
+            return None
+
+        nodes = input_name_to_nodes[word_embedding]
+        if len(nodes) != 1:
+            return None
+
+        graph_inputs = self.get_graph_inputs(nodes[0], recursive=True)
+        if len(graph_inputs) == 1:
+            return graph_inputs[0]
+
+        print("Found multiple candidates of input_ids", graph_inputs)
+        return None
+
+    def find_mask_input(self, excluded_graph_inputs):
+        for node in self.nodes():
+            if node.op_type == "Softmax":
+                mask_path = self.match_parent_path(
+                    node,
+                    ["Add", "Mul", "Sub", "Cast", "Slice", "Unsqueeze"],
+                    [0, 1, None, 1, 0, 0],
+                )
+                if mask_path is None:
+                    continue
+                (
+                    add_node,
+                    mul_node,
+                    sub_node,
+                    cast_node,
+                    slice_node,
+                    unsqueeze_node,
+                ) = mask_path
+                if self.has_constant_input(mul_node, -10000) and self.has_constant_input(sub_node, 1):
+                    graph_inputs = self.get_graph_inputs(sub_node, recursive=True)
+                    inputs = [input for input in graph_inputs if input not in excluded_graph_inputs]
+                    if len(inputs) > 1:
+                        print("Found multiple candidates of mask input", inputs)
+                        return None
+                    if len(inputs) == 1:
+                        return inputs[0]
+                    # Duplicated input found. Try to simplify the graph.
+                    path_to_be_simplified = self.match_parent_path(
+                        mask_path[-1],
+                        [
+                            "ConstantOfShape",
+                            "Cast",
+                            "Concat",
+                            "Unsqueeze",
+                            "Squeeze",
+                            "Slice",
+                            "Cast",
+                            "Shape",
+                        ],
+                        [0, 0, 0, 0, 0, 0, 0, 0],
+                    )
+                    duplicated_inputs = [input for input in graph_inputs if input in excluded_graph_inputs]
+                    # Simplify graph for dynamic axes.
+                    if (
+                        path_to_be_simplified
+                        and duplicated_inputs
+                        and len(duplicated_inputs) == 1
+                        and duplicated_inputs[0] == path_to_be_simplified[-1].input[0]
+                    ):
+                        logger.debug("Simplify semgent id path...")
+                        constantofshape_node = path_to_be_simplified[0]
+                        constantofshape_value = helper.get_attribute_value(constantofshape_node.attribute[0])
+                        graph_name = self.get_graph_by_node(constantofshape_node).name
+                        self.add_node(
+                            helper.make_node(
+                                "Shape",
+                                inputs=[duplicated_inputs[0]],
+                                outputs=["input_shape_for_mask"],
+                            ),
+                            graph_name,
+                        )
+                        self.add_node(
+                            helper.make_node(
+                                "ConstantOfShape",
+                                inputs=["input_shape_for_mask"],
+                                outputs=[unsqueeze_node.input[0]],
+                                value=constantofshape_value,
+                            ),
+                            graph_name,
+                        )
+                    return unsqueeze_node.input[0]
+        return None
+
+    def create_embedding_subgraph(self, normalize_node, word_embedding, segment_embedding, position_embedding):
+        input_ids = self.find_input_ids(word_embedding)
+        if input_ids is None:
+            logger.info("Failed to find input_ids. Cannot fuse embedding layer.")
+            return False
+
+        segment_ids = self.find_segment_ids(segment_embedding, input_ids)
+        if segment_ids is None:
+            logger.info("Failed to find segment_ids. Cannot fuse embedding layer.")
+            return False
+
+        mask_input = self.find_mask_input([segment_ids, input_ids])
+        if mask_input is None:
+            logger.info("Failed to find input_mask. Cannot fuse embedding layer.")
+            return False
+
+        self.bert_inputs = [input_ids, segment_ids, mask_input]
+
+        mask_index = self.create_node_name("mask_index")
+        self.attention_mask.set_mask_indice(mask_input, mask_index)
+
+        if self.find_graph_input(input_ids).type.tensor_type.elem_type != TensorProto.INT32:
+            casted, input_ids = self.utils.cast_graph_input_to_int32(input_ids)
+
+        if self.find_graph_input(segment_ids):
+            casted, segment_ids = self.utils.cast_graph_input_to_int32(segment_ids)
+        else:
+            segment_ids, segment_id_cast_node = self.utils.cast_input_to_int32(segment_ids)
+
+        if self.find_graph_input(mask_input):
+            casted, mask_input = self.utils.cast_graph_input_to_int32(mask_input)
+        else:
+            mask_input, mask_input_cast_node = self.utils.cast_input_to_int32(mask_input)
+
+        embed_output = self.create_node_name("embed_output")
+        embed_node = onnx.helper.make_node(
+            "EmbedLayerNormalization",
+            inputs=[
+                input_ids,
+                segment_ids,
+                word_embedding,
+                position_embedding,
+                segment_embedding,
+                normalize_node.input[1],  # gamma
+                normalize_node.input[2],  # beta
+                mask_input,
+            ],
+            outputs=[embed_output, mask_index],
+            name="EmbedLayer",
+        )
+        embed_node.domain = "com.microsoft"
+        self.replace_input_of_all_nodes(normalize_node.output[0], embed_output)
+        self.add_node(embed_node, self.get_graph_by_node(normalize_node).name)
+
+    def process_embedding(self):
+        """
+        Automatically detect word, segment and position embeddings.
+        """
+        logger.info("start processing embedding layer...")
+        output_name_to_node = self.output_name_to_node()
+
+        layer_norm_nodes = self.get_nodes_by_op_type("LayerNormalization")
+        for layer_norm_node in layer_norm_nodes:
+            pos_embed_path = self.match_parent_path(
+                layer_norm_node,
+                ["Add", "Reshape", "Slice"],
+                [0, 1, 0],
+                output_name_to_node,
+            )
+            if pos_embed_path is None:
+                continue
+
+            add_node, reshape_node, slice_node = pos_embed_path
+            initializer = self.get_initializer(slice_node.input[0])
+            if initializer is None:
+                continue
+
+            temp = numpy_helper.to_array(initializer)
+            if len(temp.shape) == 2:
+                logger.info(f"Found position embedding. name:{initializer.name}, shape:{temp.shape}")
+                position_embedding = initializer.name
+            else:
+                logger.info(f"Failed to find position embedding. name:{initializer.name}, shape:{temp.shape}")
+                return
+
+            first_parent = self.get_parent(add_node, 0, output_name_to_node)
+            if first_parent is not None and first_parent.op_type == "Add":
+                embeddings = self.get_2d_initializers_from_parent_subgraphs(first_parent)
+                if len(embeddings) != 2:
+                    logger.warning(
+                        f"Failed to find two embeddings (word and segment) from Add node. Found {embeddings}"
+                    )
+                    return
+
+                word_embedding = None
+                segment_embedding = None
+                for name, shape in embeddings.items():
+                    if shape[0] == 2:
+                        segment_embedding = name
+                        logger.info(f"Found segment embedding. name:{name}, shape:{shape}")
+                    else:
+                        word_embedding = name
+                        logger.info(f"Found words embedding. name:{name}, shape:{shape}")
+
+                if word_embedding is None or segment_embedding is None:
+                    logger.info("Failed to find both word and segment embedding")
+                    return
+
+                logger.info("Create Embedding node")
+                self.create_embedding_subgraph(
+                    layer_norm_node,
+                    word_embedding,
+                    segment_embedding,
+                    position_embedding,
+                )
+                # Prune graph to remove those original embedding nodes.
+                self.prune_graph()
+                break
+
+    def check_attention_input(self, matmul_q, matmul_k, matmul_v, parent, output_name_to_node):
+        for x in [matmul_q, matmul_k, matmul_v]:
+            root_input = x.input[0]
+            root_node = output_name_to_node[root_input]
+            if root_node == parent:
+                continue
+            logger.debug(f"Check attention input failed:{root_input}, {parent.output[0]}")
+            return False
+
+        return True
+
+    def fuse_attention(self):
+        output_name_to_node = self.output_name_to_node()
+
+        nodes_to_remove = []
+        attention_count = 0
+
+        start_nodes = []
+        skip_layer_norm_nodes = self.get_nodes_by_op_type("SkipLayerNormalization")
+        layer_norm_nodes = self.get_nodes_by_op_type("LayerNormalization")
+        # Sometimes we can not fuse skiplayernormalization since the add before layernorm has an output that used by nodes outside skiplayernorm
+        # Conceptually we treat add before layernorm as skiplayernorm node since they share the same pattern
+        start_nodes.extend(skip_layer_norm_nodes)
+        start_nodes.extend(layer_norm_nodes)
+
+        for normalize_node in start_nodes:
+            graph_name = self.get_graph_by_node(normalize_node).name
+            # SkipLayerNormalization has two inputs, and one of them is the root input for attention.
+            if normalize_node.op_type == "LayerNormalization":
+                add_before_layernorm = self.match_parent(normalize_node, "Add", 0)
+                if add_before_layernorm is not None:
+                    normalize_node = add_before_layernorm  # noqa: PLW2901
+                else:
+                    continue
+            parent = self.get_parent(normalize_node, 1)
+            if parent is None or parent.op_type not in [
+                "SkipLayerNormalization",
+                "LayerNormalization",
+                "Reshape",
+            ]:
+                parent = self.get_parent(normalize_node, 0)
+                if parent is None or parent.op_type not in [
+                    "SkipLayerNormalization",
+                    "LayerNormalization",
+                    "Reshape",
+                ]:
+                    logger.debug("Failed to match parent of normalize_node")
+                    continue
+
+            qkv_nodes = self.match_parent_path(
+                normalize_node,
+                ["Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+                [0, 0, 0, 0, 0],
+            )
+            if qkv_nodes is None:
+                qkv_nodes = self.match_parent_path(
+                    normalize_node,
+                    ["MatMul", "Reshape", "Transpose", "MatMul"],
+                    [1, 0, 0, 0],
+                )
+                if qkv_nodes is None:
+                    qkv_nodes = self.match_parent_path(normalize_node, ["Add", "Einsum", "Einsum"], [0, 0, 0])
+                    if qkv_nodes is None:
+                        logger.debug("Failed to match qkv nodes")
+                        continue
+
+            matmul_qkv = qkv_nodes[-1]
+            v_nodes = self.match_parent_path(matmul_qkv, ["Transpose", "Reshape", "Add", "MatMul"], [1, 0, 0, 0])
+            if v_nodes is None:
+                v_nodes = self.match_parent_path(matmul_qkv, ["Add", "Einsum"], [1, 0])
+                if v_nodes is None:
+                    logger.debug("Failed to match v path")
+                    continue
+
+            add_v = v_nodes[-2]
+            matmul_v = v_nodes[-1]
+            qk_nodes = self.match_parent_path(matmul_qkv, ["Softmax", "Add", "Mul", "MatMul"], [0, 0, 0, 0])
+            if qk_nodes is None:
+                qk_nodes = self.match_parent_path(matmul_qkv, ["Softmax", "Add", "Einsum"], [0, 0, 0])
+                if qk_nodes is None:
+                    logger.debug("Failed to match qk_paths")
+                    continue
+            matmul_qk = qk_nodes[-1]
+
+            q_nodes = self.match_parent_path(matmul_qk, ["Transpose", "Reshape", "Add", "MatMul"], [0, 0, 0, 0])
+            if q_nodes is None:
+                q_nodes = self.match_parent_path(matmul_qk, ["Add", "Einsum"], [0, 0])
+                if q_nodes is None:
+                    logger.debug("Failed to match q path")
+                    continue
+
+            add_q = q_nodes[-2]
+            matmul_q = q_nodes[-1]
+
+            k_nodes = self.match_parent_path(matmul_qk, ["Transpose", "Reshape", "Add", "MatMul"], [1, 0, 0, 0])
+            if k_nodes is None:
+                k_nodes = self.match_parent_path(matmul_qk, ["Mul", "Add", "Einsum"], [1, 0, 0])
+                if k_nodes is None:
+                    logger.debug("Failed to match k path")
+                    continue
+            add_k = k_nodes[-2]
+            matmul_k = k_nodes[-1]
+
+            mask_nodes = self.match_mask_path(qk_nodes[1])
+
+            if mask_nodes is None:
+                logger.debug("Cannot find mask_nodes.")
+                continue
+
+            if not self.has_constant_input(mask_nodes[1], 1):
+                logger.debug("Sub node expected to have an input with constant value 1.0.")
+                continue
+
+            # add a squeeze node to convert a 3-d mask to 2-d
+            squeeze_node = self.match_parent_path(mask_nodes[-1], ["Squeeze"], [0]) or self.match_parent_path(
+                mask_nodes[-1], ["Expand"], [0]
+            )
+            squeeze_node_name = "Squeeze_3d_to_2d_mask"
+            squeeze_output_name = squeeze_node_name + "_output"
+            if squeeze_node is None and len(mask_nodes) == 5 and self.find_graph_input(mask_nodes[-1].input[0]) is None:
+                mask_input = mask_nodes[-1].input[1]
+                self.add_node(
+                    helper.make_node(
+                        "Squeeze",
+                        [mask_input],
+                        [squeeze_output_name],
+                        squeeze_node_name,
+                        axes=[1],
+                    ),
+                    graph_name,
+                )
+                mask_nodes[-1].input[0] = squeeze_output_name
+
+            is_same_root = self.check_attention_input(matmul_q, matmul_k, matmul_v, parent, output_name_to_node)
+            if is_same_root:
+                mask_index = self.attention_mask.process_mask(mask_nodes[-1].input[0])
+                logger.debug("Create an Attention node.")
+
+                # For tf models, q and v are flipped.
+                attention_node = self.attention_fusion.create_attention_node(
+                    mask_index=mask_index,
+                    q_matmul=matmul_k,
+                    k_matmul=matmul_q,
+                    v_matmul=matmul_v,
+                    q_add=add_k,
+                    k_add=add_q,
+                    v_add=add_v,
+                    num_heads=self.num_heads,
+                    hidden_size=self.hidden_size,
+                    first_input=parent.output[0],
+                    output=qkv_nodes[2].output[0],
+                )
+                if attention_node is None:
+                    continue
+
+                if qkv_nodes[1].op_type == "Einsum":
+                    # add reshape before einsum
+                    tensor = helper.make_tensor(
+                        name=qkv_nodes[1].name + "_newshape",
+                        data_type=TensorProto.INT64,
+                        dims=[4],
+                        vals=np.int64(
+                            [
+                                [
+                                    0,
+                                    0,
+                                    self.num_heads,
+                                    int(self.hidden_size / self.num_heads),
+                                ]
+                            ]
+                        ).tobytes(),
+                        raw=True,
+                    )
+                    self.add_initializer(tensor, graph_name)
+                    reshape_ = helper.make_node(
+                        "Reshape",
+                        inputs=[
+                            attention_node.output[0],
+                            qkv_nodes[1].name + "_newshape",
+                        ],
+                        outputs=[qkv_nodes[1].name + "_reshape_output"],
+                        name=qkv_nodes[1].name + "_reshape",
+                    )
+                    qkv_nodes[1].input[0] = qkv_nodes[1].name + "_reshape_output"
+                    self.add_node(reshape_, graph_name)
+                if parent.op_type == "Reshape":
+                    # Temporary work around: we require the skiplayernorm and attention op be fed with 3-d input
+                    hidden_size = numpy_helper.to_array(self.get_initializer(parent.input[1]))[1]
+                    tensor = helper.make_tensor(
+                        name=parent.name + "_modified",
+                        data_type=TensorProto.INT64,
+                        dims=[3],
+                        vals=np.int64([[1, -1, hidden_size]]).tobytes(),
+                        raw=True,
+                    )
+                    self.add_initializer(tensor, graph_name)
+                    parent.input[1] = parent.name + "_modified"
+
+                self.add_node(attention_node, graph_name)
+                attention_count += 1
+
+                nodes_to_remove.extend(qkv_nodes[2:])
+                nodes_to_remove.extend(qk_nodes)
+                nodes_to_remove.extend(q_nodes)
+                nodes_to_remove.extend(k_nodes)
+                nodes_to_remove.extend(v_nodes)
+                nodes_to_remove.extend(mask_nodes)
+            else:
+                logger.debug("Root node not matched.")
+                continue
+        self.remove_nodes(nodes_to_remove)
+        self.update_graph()
+        logger.info(f"Fused Attention count:{attention_count}")
+
+    def preprocess(self):
+        self.remove_identity()
+        self.process_embedding()
+        self.skip_reshape()
+
+    def skip_reshape(self):
+        count = 0
+        reshape_nodes = self.get_nodes_by_op_type("Reshape")
+        for reshape_node in reshape_nodes:
+            parent = self.get_parent(reshape_node, 0)
+            if parent is not None and parent.op_type == "Reshape":
+                reshape_node.input[0] = parent.input[0]
+                count += 1
+
+        if count > 0:
+            logger.info(f"Skip consequent Reshape count: {count}")
+
+    def remove_reshape_before_first_attention(self):
+        attention_nodes = self.get_nodes_by_op_type("Attention")
+        for attention_node in attention_nodes:
+            path = self.match_parent_path(attention_node, ["Reshape", "EmbedLayerNormalization"], [0, 0])
+            if path is None:
+                continue
+            logger.info("Remove Reshape before first Attention node.")
+            reshape, _ = path
+            self.replace_input_of_all_nodes(reshape.output[0], reshape.input[0])
+            self.remove_node(reshape)
+            break
+
+    def postprocess(self):
+        self.remove_reshape_before_first_attention()
+        self.prune_graph()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_clip.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_clip.py
new file mode 100644
index 0000000000000000000000000000000000000000..5f3a5e9bf81410d59b5ae5ef4758009c6434713a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_clip.py
@@ -0,0 +1,42 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from logging import getLogger
+
+from fusion_attention_clip import FusionAttentionClip
+from onnx import ModelProto
+from onnx_model_bert import BertOnnxModel
+
+logger = getLogger(__name__)
+
+
+class ClipOnnxModel(BertOnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        super().__init__(model, num_heads=num_heads, hidden_size=hidden_size)
+        self.clip_attention_fusion = FusionAttentionClip(self, self.hidden_size, self.num_heads)
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "Attention",
+            "FastGelu",
+            "Gelu",
+            "LayerNormalization",
+            "QuickGelu",
+            "BiasGelu",
+            "SkipLayerNormalization",
+        ]
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators:{op_count}")
+        return op_count
+
+    def fuse_attention(self):
+        self.clip_attention_fusion.apply()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_conformer.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_conformer.py
new file mode 100644
index 0000000000000000000000000000000000000000..1135e4ac36bb0c0c636a45dc49b72a31b36fc430
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_conformer.py
@@ -0,0 +1,32 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+from fusion_attention import AttentionMask
+from fusion_conformer_attention import FusionConformerAttention
+from fusion_options import FusionOptions
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class ConformerOnnxModel(BertOnnxModel):
+    def __init__(self, model, num_heads, hidden_size):
+        super().__init__(model, num_heads, hidden_size)
+        self.attention_mask = AttentionMask(self)
+        self.attention_fusion = FusionConformerAttention(self, self.hidden_size, self.num_heads, self.attention_mask)
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        self.attention_fusion.use_multi_head_attention = False if options is None else options.use_multi_head_attention
+        self.attention_fusion.disable_multi_head_attention_bias = (
+            False if options is None else options.disable_multi_head_attention_bias
+        )
+        super().optimize(options, add_dynamic_axes)
+
+    def fuse_attention(self):
+        self.attention_fusion.apply()
+
+    def preprocess(self):
+        self.adjust_reshape_and_expand()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_gpt2.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_gpt2.py
new file mode 100644
index 0000000000000000000000000000000000000000..3d1d5465fa8adc7207ae4dfd934d30f0e5fd92e3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_gpt2.py
@@ -0,0 +1,101 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+import onnx
+from fusion_gpt_attention import FusionGptAttention
+from fusion_gpt_attention_megatron import FusionGptAttentionMegatron
+from fusion_gpt_attention_no_past import FusionGptAttentionNoPast
+from fusion_rotary_attention import FusionRotaryAttention
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class Gpt2OnnxModel(BertOnnxModel):
+    def __init__(self, model, num_heads, hidden_size):
+        super().__init__(model, num_heads, hidden_size)
+
+    def fuse_attention(self):
+        if len(self.model.graph.input) == 1 or len(self.model.graph.output) == 1:
+            fusion = FusionGptAttentionNoPast(self, self.num_heads)
+            fusion.apply()
+        else:
+            fusion = FusionGptAttention(self, self.num_heads)
+            fusion.apply()
+            fusion = FusionGptAttentionMegatron(self, self.num_heads)
+            fusion.apply()
+
+        fusion = FusionRotaryAttention(self, self.hidden_size, self.num_heads)
+        fusion.apply()
+
+    def postprocess(self):
+        """
+        Remove extra reshape nodes.
+        """
+        logger.debug("start postprocessing...")
+
+        input_name_to_nodes = self.input_name_to_nodes()
+        output_name_to_node = self.output_name_to_node()
+
+        reshape_count = 0
+        for gemm_node in self.get_nodes_by_op_type("Gemm"):
+            reshape_after_gemm = self.find_first_child_by_type(
+                gemm_node, "Reshape", input_name_to_nodes, recursive=False
+            )
+
+            nodes = self.match_parent_path(gemm_node, ["Reshape", "FastGelu"], [0, 0], output_name_to_node)
+            if nodes is None:
+                nodes = self.match_parent_path(
+                    gemm_node,
+                    ["Reshape", "LayerNormalization"],
+                    [0, 0],
+                    output_name_to_node,
+                )
+
+                if nodes is None:
+                    nodes = self.match_parent_path(
+                        gemm_node,
+                        ["Reshape", "SkipLayerNormalization"],
+                        [0, 0],
+                        output_name_to_node,
+                    )
+
+                    if nodes is None:
+                        continue
+
+            (reshape_before_gemm, root_node) = nodes
+
+            matmul_node_name = self.create_node_name("MatMul", "FullyConnect_MatMul")
+            matmul_node = onnx.helper.make_node(
+                "MatMul",
+                inputs=[matmul_node_name + "_input", gemm_node.input[1]],
+                outputs=[matmul_node_name + "_output"],
+                name=matmul_node_name,
+            )
+
+            add_node_name = self.create_node_name("Add", "FullyConnect_Add")
+            add_node = onnx.helper.make_node(
+                "Add",
+                inputs=[matmul_node_name + "_output", gemm_node.input[2]],
+                outputs=[add_node_name + "_output"],
+                name=add_node_name,
+            )
+
+            self.replace_input_of_all_nodes(reshape_after_gemm.output[0], add_node_name + "_output")
+
+            # Link root node output with MatMul
+            self.replace_input_of_all_nodes(root_node.output[0], matmul_node_name + "_input")
+            root_node.output[0] = matmul_node_name + "_input"
+
+            self.replace_input_of_all_nodes(reshape_after_gemm.output[0], add_node_name + "_output")
+
+            self.add_node(matmul_node)
+            self.add_node(add_node)
+
+            reshape_count += 2
+
+        self.prune_graph()
+        logger.info(f"postprocess: remove Reshape count: {reshape_count}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_mmdit.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_mmdit.py
new file mode 100644
index 0000000000000000000000000000000000000000..70fed087acc46a442b4ad4688dc0edb16375982e
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_mmdit.py
@@ -0,0 +1,112 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+from fusion_layernorm import FusionLayerNormalization
+from fusion_mha_mmdit import FusionMultiHeadAttentionMMDit
+from fusion_options import FusionOptions
+from import_utils import is_installed
+from onnx import ModelProto
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class MmditOnnxModel(BertOnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        """Initialize Multimodal Diffusion Transformer (MMDiT) ONNX Model.
+
+        Args:
+            model (ModelProto): the ONNX model
+            num_heads (int, optional): number of attention heads. Defaults to 0 (detect the parameter automatically).
+            hidden_size (int, optional): hidden dimension. Defaults to 0 (detect the parameter automatically).
+        """
+        assert (num_heads == 0 and hidden_size == 0) or (num_heads > 0 and hidden_size % num_heads == 0)
+        super().__init__(model, num_heads=num_heads, hidden_size=hidden_size)
+
+    def postprocess(self):
+        self.prune_graph()
+        self.remove_unused_constant()
+
+    def fuse_layer_norm(self):
+        layernorm_support_broadcast = True
+        logger.warning(
+            "The optimized model requires LayerNormalization with broadcast support. "
+            "Please use onnxruntime-gpu>=1.21 for inference."
+        )
+        fusion = FusionLayerNormalization(
+            self, check_constant_and_dimension=not layernorm_support_broadcast, force=True
+        )
+        fusion.apply()
+
+    def fuse_multi_head_attention(self):
+        fusion = FusionMultiHeadAttentionMMDit(self)
+        fusion.apply()
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        assert not add_dynamic_axes
+
+        if is_installed("tqdm"):
+            import tqdm  # noqa: PLC0415
+            from tqdm.contrib.logging import logging_redirect_tqdm  # noqa: PLC0415
+
+            with logging_redirect_tqdm():
+                steps = 5
+                progress_bar = tqdm.tqdm(range(steps), initial=0, desc="fusion")
+                self._optimize(options, progress_bar)
+        else:
+            logger.info("tqdm is not installed. Run optimization without progress bar")
+            self._optimize(options, None)
+
+    def _optimize(self, options: FusionOptions | None = None, progress_bar=None):
+        if (options is not None) and not options.enable_shape_inference:
+            self.disable_shape_inference()
+
+        # Remove cast nodes that having same data type of input and output based on symbolic shape inference.
+        self.utils.remove_useless_cast_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_layer_norm:
+            self.fuse_layer_norm()
+            self.fuse_simplified_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_gelu:
+            self.fuse_gelu()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_attention:
+            self.fuse_multi_head_attention()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.postprocess()
+        if progress_bar:
+            progress_bar.update(1)
+
+        logger.info(f"opset version: {self.get_opset_version()}")
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "FastGelu",
+            "MultiHeadAttention",
+            "LayerNormalization",
+            "SimplifiedLayerNormalization",
+        ]
+
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators:{op_count}")
+        return op_count
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_phi.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_phi.py
new file mode 100644
index 0000000000000000000000000000000000000000..b84d541c1547f8ee9a62dbbca94722a5ea354dfe
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_phi.py
@@ -0,0 +1,929 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from logging import getLogger
+
+import numpy as np
+from dynamo_onnx_helper import DynamoOnnxHelper
+from fusion_base import Fusion
+from fusion_options import AttentionOpType, FusionOptions
+from fusion_skiplayernorm import FusionBiasSkipLayerNormalization, FusionSkipLayerNormalization
+from fusion_utils import NumpyHelper
+from onnx import ModelProto, NodeProto, TensorProto, helper, numpy_helper
+from onnx_model import OnnxModel
+
+logger = getLogger(__name__)
+
+
+class ProcessGemmWFunc:
+    def __call__(self, x):
+        return np.transpose(x, (1, 0))
+
+
+class ProcessMatMulQFunc:
+    def __call__(self, x):
+        return np.transpose(np.split(x, 3, 0)[0], (1, 0))
+
+
+class ProcessMatMulKFunc:
+    def __call__(self, x):
+        return np.transpose(np.split(x, 3, 0)[1], (1, 0))
+
+
+class ProcessMatMulVFunc:
+    def __call__(self, x):
+        return np.transpose(np.split(x, 3, 0)[2], (1, 0))
+
+
+class ProcessBiasQFunc:
+    def __call__(self, x):
+        x = np.split(x, 3, -1)[0]
+        return x
+
+
+class ProcessBiasKFunc:
+    def __call__(self, x):
+        x = np.split(x, 3, -1)[1]
+        return x
+
+
+class ProcessBiasVFunc:
+    def __call__(self, x):
+        x = np.split(x, 3, -1)[2]
+        return x
+
+
+class ProcessRotCacheFunc:
+    def __call__(self, x):
+        # half rotary embedding
+        assert len(x.shape) == 2
+        if x.shape[1] == 32:
+            return x[:, 0:16]
+        return x
+
+
+# TODO: move to a separate file
+class Fission(Fusion):
+    def __init__(
+        self,
+        model: OnnxModel,
+        nodes_to_find: list[str],
+    ):
+        super().__init__(model, "DONOTUSE", nodes_to_find)
+
+    def set_attention_op_type(self, attn_op_type: AttentionOpType):
+        self.attn_op_type = attn_op_type
+
+    def get_uname(self, layer_id, name):
+        return name + "_" + str(layer_id)
+
+    def get_edge_by_name(self, edges, name):
+        for edge in edges:
+            if edge == name or edge.endswith(name) or edge.startswith(name):
+                return edge
+        raise ValueError(f"Edge {name} not found")
+
+    def get_input_by_name(self, node, name):
+        return self.get_edge_by_name(node.input, name)
+
+    def get_output_by_name(self, node, name):
+        return self.get_edge_by_name(node.output, name)
+
+    def process_initializer(self, initializer_name, functor, custom_name=None):
+        i = self.model.get_initializer(initializer_name)
+        i_np_array = NumpyHelper.to_array(i)
+        processed_i_np_array = functor(i_np_array)
+        new_tensor = helper.make_tensor(
+            initializer_name + "_processed" if custom_name is None else custom_name,
+            data_type=TensorProto.FLOAT,
+            dims=processed_i_np_array.shape,
+            vals=processed_i_np_array.flatten().tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(new_tensor, self.this_graph_name)
+        return new_tensor.name
+
+    def add_fp32_value_info(self, name):
+        new_value_info = self.model.graph().value_info.add()
+        new_value_info.name = name
+        new_value_info.type.tensor_type.elem_type = TensorProto.FLOAT
+
+    def add_int64_value_info(self, name):
+        new_value_info = self.model.graph().value_info.add()
+        new_value_info.name = name
+        new_value_info.type.tensor_type.elem_type = TensorProto.INT64
+
+    def replace_fp32_value_info(self, name, shape):
+        for value_info in self.model.graph().value_info:
+            if value_info.name == name:
+                self.model.graph().value_info.remove(value_info)
+                break
+        new_value_info = helper.make_tensor_value_info(
+            name,
+            elem_type=TensorProto.FLOAT,
+            shape=shape,
+        )
+        self.model.graph().value_info.extend([new_value_info])
+
+    def set_unique_name_and_add_nodes(
+        self, subgraph_nodes: list[NodeProto], layer_id: int, layer_known_edges_names: list[str]
+    ):
+        for new_node in subgraph_nodes:
+            for i, name in enumerate(new_node.input):
+                if name == "":
+                    continue
+                elif name not in layer_known_edges_names:
+                    new_node.input[i] = self.get_uname(layer_id, name)
+                    self.add_fp32_value_info(new_node.input[i])
+            for i, name in enumerate(new_node.output):
+                if name == "":
+                    continue
+                elif name not in layer_known_edges_names:
+                    new_node.output[i] = self.get_uname(layer_id, name)
+                    self.add_fp32_value_info(new_node.output[i])
+            new_node.name = self.get_uname(layer_id, new_node.name)
+            self.nodes_to_add.append(new_node)
+            self.node_name_to_graph_name[new_node.name] = self.this_graph_name
+
+    def layernorm(self, inputs: list[str], outputs: list[str], prefix: str = ""):
+        assert len(inputs) == 3
+        assert len(outputs) == 1
+        node = helper.make_node(
+            "LayerNormalization",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "_LayerNormalization",
+            epsilon=9.999999747378752e-06,
+        )
+        return [node]
+
+    def gemm(self, inputs: list[str], outputs: list[str], prefix: str = ""):
+        assert len(inputs) == 3
+        assert len(outputs) == 1
+        matmul = helper.make_node(
+            "MatMul",
+            inputs=[inputs[0], inputs[1]],
+            outputs=[prefix + "matmul_out"],
+            name=prefix + "MatMul",
+        )
+        add = helper.make_node(
+            "Add",
+            inputs=[prefix + "matmul_out", inputs[2]],
+            outputs=outputs,
+            name=prefix + "Bias",
+        )
+        return [matmul, add]
+
+    def rotary(self, inputs: list[str], outputs: list[str], prefix: str = "", rot_dim=32, num_heads=32):
+        assert len(inputs) == 4
+        assert len(outputs) == 1
+        node = helper.make_node(
+            "RotaryEmbedding",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "RotaryEmbedding",
+            domain="com.microsoft",
+            rotary_embedding_dim=rot_dim,
+            num_heads=num_heads,
+        )
+        return [node]
+
+    def fastgelu(self, inputs: list[str], outputs: list[str], prefix: str = ""):
+        assert len(inputs) == 1
+        assert len(outputs) == 1
+        node = helper.make_node(
+            "FastGelu",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "FastGelu",
+            domain="com.microsoft",
+        )
+        return [node]
+
+    def add(self, inputs: list[str], outputs: list[str], prefix: str = ""):
+        assert len(inputs) == 2
+        assert len(outputs) == 1
+        node = helper.make_node(
+            "Add",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "Add",
+        )
+        return [node]
+
+    def mha(self, inputs: list[str], outputs: list[str], prefix: str = "", num_heads=32):
+        assert len(inputs) == 8
+        assert len(outputs) == 3
+        node = helper.make_node(
+            "MultiHeadAttention",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "MultiHeadAttention",
+            domain="com.microsoft",
+            num_heads=num_heads,
+            unidirectional=1,
+        )
+        return [node]
+
+    def gqa(self, inputs: list[str], outputs: list[str], prefix: str = "", num_heads=32):
+        assert len(inputs) == 7
+        assert len(outputs) == 3
+        node = helper.make_node(
+            "GroupQueryAttention",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "GroupQueryAttention",
+            domain="com.microsoft",
+            num_heads=num_heads,
+            kv_num_heads=num_heads,
+        )
+        return [node]
+
+    def attention(self, inputs: list[str], outputs: list[str], prefix: str = "", num_heads=32):
+        assert len(inputs) == 5
+        assert len(outputs) == 2
+        node = helper.make_node(
+            "Attention",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "Attention",
+            domain="com.microsoft",
+            num_heads=num_heads,
+            unidirectional=1,
+            do_rotary=1,
+            rotary_embedding_dim=32,
+        )
+        return [node]
+
+    def paged_attn(
+        self,
+        inputs: list[str],
+        outputs: list[str],
+        prefix: str = "",
+        num_heads=32,
+        head_size=80,
+        scale=0.11180339753627777,
+    ):
+        assert len(inputs) == 6
+        assert len(outputs) == 1
+        node = helper.make_node(
+            "PagedAttention",
+            inputs=inputs,
+            outputs=outputs,
+            name=prefix + "PagedAttention",
+            domain="vllm.ort.ext",
+            num_heads=num_heads,
+            num_kv_heads=num_heads,
+            head_size=head_size,
+            scale=scale,
+        )
+        return [node]
+
+
+class Phi2PreProcessor(DynamoOnnxHelper):
+    def __init__(self, model: ModelProto, num_heads: int, hidden_size: int):
+        super().__init__(model)
+        self.num_hidden_layers = 32
+        self.num_attention_heads = num_heads
+        self.hidden_size = hidden_size
+
+        self.func_name = "modeling_phi_PhiModel_model_1"
+
+    def get_phi2_edge_dict(self) -> dict:
+        edge_dict = {}
+        edge_dict["lm_head_1"] = "logits"
+        edge_dict["l_input_ids_"] = "input_ids"
+        edge_dict["key_states"] = "past_key_0"
+        edge_dict["value_states"] = "past_value_0"
+        for i in range(1, self.num_hidden_layers, 1):
+            edge_dict[f"key_states_{i}"] = f"past_key_{i}"
+            edge_dict[f"value_states_{i}"] = f"past_value_{i}"
+            edge_dict[f"model_layers_{i}_1"] = f"present_key_{i}"
+            edge_dict[f"model_layers_{i}_1_1"] = f"present_value_{i}"
+
+        outputs = [o.name for o in self.model.graph.output]
+        if "model_layers_0_1_1" in outputs and "model_layers_0_1_2" in outputs:
+            edge_dict["model_layers_0_1_1"] = "present_key_0"
+            edge_dict["model_layers_0_1_2"] = "present_value_0"
+        else:
+            assert "model_layers_0_1" in outputs and "model_layers_0_1_1" in outputs
+            edge_dict["model_layers_0_1"] = "present_key_0"
+            edge_dict["model_layers_0_1_1"] = "present_value_0"
+        return edge_dict
+
+    def simplify_phi2_op_type(self):
+        phi2_transformer_layer_name = "modeling_phi_PhiDecoderLayer_model_layers"
+        for node in self.model.graph.node:
+            index = node.op_type.find(phi2_transformer_layer_name)
+            if index != -1:
+                node.op_type = node.op_type[index:]
+
+    def process_graph_io(self, attn_op_type: AttentionOpType):
+        self.use_attn = attn_op_type == AttentionOpType.Attention
+        self.use_vllm = attn_op_type == AttentionOpType.PagedAttention
+        graph = self.model.graph
+        new_inputs = []
+        for vi in graph.input:
+            if "input_ids" in vi.name:
+                vi_iid = helper.make_tensor_value_info(
+                    vi.name,
+                    elem_type=TensorProto.INT32 if not self.use_vllm else TensorProto.INT64,
+                    shape=["batch_size", "seq_len"],
+                )
+                vi_step = helper.make_tensor_value_info(
+                    "step",
+                    elem_type=TensorProto.INT64,
+                    shape=[1],
+                )
+                vi_pid = helper.make_tensor_value_info(
+                    "position_ids",
+                    elem_type=TensorProto.INT64,
+                    shape=["batch_size", "seq_len"],
+                )
+                vi_mask = helper.make_tensor_value_info(
+                    "attention_mask",
+                    elem_type=TensorProto.INT32,
+                    shape=["batch_size", "seq_len"],
+                )
+                vi_meta = helper.make_tensor_value_info(
+                    "input_metadata",
+                    elem_type=TensorProto.INT64,
+                    shape=[1],
+                )
+                (
+                    new_inputs.extend([vi_iid, vi_step, vi_mask])
+                    if not self.use_vllm
+                    else new_inputs.extend([vi_iid, vi_pid, vi_meta])
+                )
+            if self.use_attn:
+                if "past_key" in vi.name:
+                    vi_cache = helper.make_tensor_value_info(
+                        vi.name.replace("past_key", "past"),
+                        elem_type=vi.type.tensor_type.elem_type,
+                        shape=[
+                            2,
+                            "batch_size",
+                            self.num_attention_heads,
+                            "past_seq_len",
+                            self.hidden_size // self.num_attention_heads,
+                        ],
+                    )
+                    new_inputs.extend([vi_cache])
+            elif self.use_vllm:
+                if "past_key" in vi.name:
+                    vi_cache = helper.make_tensor_value_info(
+                        vi.name,
+                        elem_type=vi.type.tensor_type.elem_type,
+                        shape=["num_blocks", "num_heads", "head_size_x", "block_size", "block_x"],
+                    )
+                    new_inputs.extend([vi_cache])
+                if "past_value" in vi.name:
+                    vi_cache = helper.make_tensor_value_info(
+                        vi.name,
+                        elem_type=vi.type.tensor_type.elem_type,
+                        shape=[
+                            "num_blocks",
+                            "num_heads",
+                            "head_size",
+                            "block_size",
+                        ],
+                    )
+                    new_inputs.extend([vi_cache])
+            else:
+                if "past_key" in vi.name or "past_value" in vi.name:
+                    vi_cache = helper.make_tensor_value_info(
+                        vi.name,
+                        elem_type=vi.type.tensor_type.elem_type,
+                        shape=[
+                            "batch_size",
+                            self.num_attention_heads,
+                            "past_seq_len",
+                            self.hidden_size // self.num_attention_heads,
+                        ],
+                    )
+                    new_inputs.extend([vi_cache])
+
+        graph.ClearField("input")
+        graph.input.extend(new_inputs)
+
+        new_outputs = []
+        for i, vi in enumerate(graph.output):
+            if i == 0:
+                new_outputs.extend([vi])
+            else:
+                if self.use_attn:
+                    if "present_key" in vi.name:
+                        vi_cache = helper.make_tensor_value_info(
+                            vi.name.replace("present_key", "present"),
+                            elem_type=vi.type.tensor_type.elem_type,
+                            shape=[
+                                2,
+                                "batch_size",
+                                self.num_attention_heads,
+                                "total_seq_len",
+                                self.hidden_size // self.num_attention_heads,
+                            ],
+                        )
+                        new_outputs.extend([vi_cache])
+                elif self.use_vllm:
+                    pass
+                else:
+                    vi_cache = helper.make_tensor_value_info(
+                        vi.name,
+                        elem_type=vi.type.tensor_type.elem_type,
+                        shape=[
+                            "batch_size",
+                            self.num_attention_heads,
+                            "total_seq_len",
+                            self.hidden_size // self.num_attention_heads,
+                        ],
+                    )
+                    new_outputs.extend([vi_cache])
+
+        graph.ClearField("output")
+        graph.output.extend(new_outputs)
+
+    def preprocess_onnx(self, attn_op_type: AttentionOpType):
+        function_name = None
+        for func in self.model.functions:
+            if func.name.endswith(self.func_name):
+                function_name = func.name
+                break
+        assert function_name is not None
+        self.unroll_function(function_name)
+        self.update_edges(self.get_phi2_edge_dict())
+        self.simplify_phi2_op_type()
+        self.remove_dropout_layer()
+        if attn_op_type == AttentionOpType.PagedAttention:
+            self.remove_lm_head_layer()
+        self.process_graph_io(attn_op_type)
+
+
+class FissionTransformerEmbeddingPhi(Fission):
+    def __init__(
+        self,
+        model: OnnxModel,
+    ):
+        super().__init__(model, ["torch_nn_modules_sparse_Embedding_model_embed_tokens_1"])
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        logger.info("Optimizing %s...", node.name)
+
+        assert len(node.input) == 2
+        assert len(node.output) == 1
+
+        input = node.input[0]
+        output = node.output[0]
+
+        embedding = self.get_input_by_name(node, "embed_tokens.weight")
+
+        layer_known_edges_names = [input, output, embedding]
+
+        subgraph_nodes = [
+            helper.make_node(
+                "Gather",
+                inputs=[embedding, input],
+                outputs=[output],
+                name="Embedding_Gather",
+            ),
+        ]
+
+        self.set_unique_name_and_add_nodes(subgraph_nodes, 0, layer_known_edges_names)
+        self.nodes_to_remove.append(node)
+        self.prune_graph = True
+
+
+class FissionTransformerLayerNormPhi(Fission):
+    def __init__(
+        self,
+        model: OnnxModel,
+    ):
+        super().__init__(model, ["torch_nn_modules_normalization_LayerNorm_model_final_layernorm_1"])
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        logger.info("Optimizing %s...", node.name)
+
+        assert len(node.input) == 3
+        assert len(node.output) == 1
+
+        input = node.input[0]
+        output = node.output[0]
+
+        ln_weight = self.get_input_by_name(node, "final_layernorm.weight")
+        ln_bias = self.get_input_by_name(node, "final_layernorm.bias")
+
+        layer_known_edges_names = [input, output, ln_weight, ln_bias]
+
+        subgraph_nodes = []
+        subgraph_nodes.extend(self.layernorm([input, ln_weight, ln_bias], [output], "Final"))
+
+        self.set_unique_name_and_add_nodes(subgraph_nodes, 99, layer_known_edges_names)
+
+        self.replace_fp32_value_info(input, ["batch_size", "seq_len", "hidden_size"])
+        self.replace_fp32_value_info(output, ["batch_size", "seq_len", "hidden_size"])
+
+        self.nodes_to_remove.append(node)
+        self.prune_graph = True
+
+
+class FissionTransformerCausalLMHeadPhi(Fission):
+    def __init__(
+        self,
+        model: OnnxModel,
+    ):
+        super().__init__(model, ["torch_nn_modules_linear_Linear_lm_head_1"])
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        logger.info("Optimizing %s...", node.name)
+
+        assert len(node.input) == 5
+        assert len(node.output) == 1
+
+        input = node.input[2]
+        output = node.output[0]
+
+        fc_weight = self.process_initializer(self.get_input_by_name(node, "lm_head.weight"), ProcessGemmWFunc())
+        fc_bias = self.get_input_by_name(node, "lm_head.bias")
+
+        layer_known_edges_names = [input, output, fc_weight, fc_bias]
+
+        subgraph_nodes = []
+        subgraph_nodes.extend(self.gemm([input, fc_weight, fc_bias], [output], "LMHead_"))
+
+        self.set_unique_name_and_add_nodes(subgraph_nodes, 99, layer_known_edges_names)
+
+        self.replace_fp32_value_info(input, ["batch_size", "seq_len", "hidden_size"])
+        self.replace_fp32_value_info(output, ["batch_size", "seq_len", 51200])
+
+        self.nodes_to_remove.append(node)
+        self.prune_graph = True
+
+
+class FissionTransformerBlockPhi(Fission):
+    def __init__(
+        self,
+        model: OnnxModel,
+        num_heads: int,
+    ):
+        self.num_heads = num_heads
+        max_num_layers = 32
+        self.func_to_layer_id = {}
+        nodes_to_find = []
+        for layer in range(max_num_layers):
+            func_name = f"modeling_phi_PhiDecoderLayer_model_layers_{layer}_1"
+            nodes_to_find.append(func_name)
+            self.func_to_layer_id[func_name] = layer
+
+        super().__init__(model, nodes_to_find)
+
+    def get_layer_id(self, node):
+        return self.func_to_layer_id[node.op_type]
+
+    def get_gqa_aux_nodes(self):
+        gqa_aux_nodes = [
+            helper.make_node(
+                "Cast",
+                inputs=["attention_mask"],
+                outputs=["mask_int64"],
+                name="Cast_gqa_aux_0",
+                to=TensorProto.INT64,
+            ),
+            helper.make_node(
+                "ReduceSum",
+                inputs=["mask_int64", "one"],
+                outputs=["mask_row_sums"],
+                name="ReduceSum_gqa_aux",
+            ),
+            helper.make_node(
+                "Sub",
+                inputs=["mask_row_sums", "one"],
+                outputs=["seqlens_k_int64"],
+                name="Sub_gqa_aux",
+            ),
+            helper.make_node(
+                "Cast",
+                inputs=["seqlens_k_int64"],
+                outputs=["seqlens_k"],
+                name="Cast_gqa_aux_1",
+                to=TensorProto.INT32,
+            ),
+            helper.make_node("Shape", inputs=["mask_int64"], outputs=["mask_shape"], name="Shape_gqa_aux_0"),
+            helper.make_node(
+                "Gather",
+                inputs=["mask_shape", "one"],
+                outputs=["total_seq_len_int64"],
+                name="Gather_gqa_aux_0",
+                axis=0,
+            ),
+            helper.make_node(
+                "Cast",
+                inputs=["total_seq_len_int64"],
+                outputs=["total_sequence_length"],
+                name="Cast_gqa_aux_2",
+                to=TensorProto.INT32,
+            ),
+        ]
+        return gqa_aux_nodes
+
+    def pack_qkv_gemm(self, q_w, k_w, v_w, q_b, k_b, v_b, weight_name, bias_name):
+        q_weight = self.model.get_initializer(q_w)
+        k_weight = self.model.get_initializer(k_w)
+        v_weight = self.model.get_initializer(v_w)
+        qw = np.transpose(NumpyHelper.to_array(q_weight), (1, 0))
+        kw = np.transpose(NumpyHelper.to_array(k_weight), (1, 0))
+        vw = np.transpose(NumpyHelper.to_array(v_weight), (1, 0))
+        qkv_weight = np.stack((qw, kw, vw), axis=1)
+
+        q_bias = self.model.get_initializer(q_b)
+        k_bias = self.model.get_initializer(k_b)
+        v_bias = self.model.get_initializer(v_b)
+        qb = NumpyHelper.to_array(q_bias)
+        kb = NumpyHelper.to_array(k_bias)
+        vb = NumpyHelper.to_array(v_bias)
+        qkv_bias = np.stack((qb, kb, vb), axis=0)
+
+        hidden_size = qkv_weight.shape[0]
+
+        weight = helper.make_tensor(
+            weight_name,
+            data_type=TensorProto.FLOAT,
+            dims=[hidden_size, hidden_size * 3],
+            vals=qkv_weight.flatten().tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(weight, self.this_graph_name)
+
+        bias = helper.make_tensor(
+            bias_name,
+            data_type=TensorProto.FLOAT,
+            dims=[hidden_size * 3],
+            vals=qkv_bias.flatten().tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(bias, self.this_graph_name)
+
+        self.add_fp32_value_info(weight.name)
+        self.add_fp32_value_info(bias.name)
+
+        return weight_name, bias_name
+
+    def fuse(
+        self,
+        node,
+        input_name_to_nodes,
+        output_name_to_node,
+    ):
+        logger.info("Optimizing %s...", node.name)
+
+        logger.info(f"AttentionOpType: {self.attn_op_type}")
+
+        layer_id = self.get_layer_id(node)
+
+        i_hidden_states = node.input[0]
+        i_key_cache = self.get_input_by_name(node, "past_key")
+        i_value_cache = self.get_input_by_name(node, "past_value")
+
+        o_hidden_states = node.output[-1]
+        o_key_cache = self.get_output_by_name(node, "present_key")
+        o_value_cache = self.get_output_by_name(node, "present_value")
+
+        ln_weight = self.get_input_by_name(node, "input_layernorm.weight")
+        ln_bias = self.get_input_by_name(node, "input_layernorm.bias")
+
+        attn_q_weight, attn_q_bias, attn_k_weight, attn_k_bias, attn_v_weight, attn_v_bias = (
+            None,
+            None,
+            None,
+            None,
+            None,
+            None,
+        )
+        attn_qkv_weight, attn_qkv_bias = None, None
+        cos_cache, sin_cache = None, None
+
+        if self.attn_op_type != AttentionOpType.Attention:
+            attn_q_weight = self.process_initializer(
+                self.get_input_by_name(node, "self_attn.q_proj.weight"), ProcessGemmWFunc()
+            )
+            attn_k_weight = self.process_initializer(
+                self.get_input_by_name(node, "self_attn.k_proj.weight"), ProcessGemmWFunc()
+            )
+            attn_v_weight = self.process_initializer(
+                self.get_input_by_name(node, "self_attn.v_proj.weight"), ProcessGemmWFunc()
+            )
+            attn_q_bias = self.get_input_by_name(node, "self_attn.q_proj.bias")
+            attn_k_bias = self.get_input_by_name(node, "self_attn.k_proj.bias")
+            attn_v_bias = self.get_input_by_name(node, "self_attn.v_proj.bias")
+
+            cos_cache = self.process_initializer(
+                self.get_input_by_name(node, "rotary_emb.cos_cached"), ProcessRotCacheFunc()
+            )
+            sin_cache = self.process_initializer(
+                self.get_input_by_name(node, "rotary_emb.sin_cached"), ProcessRotCacheFunc()
+            )
+        else:
+            attn_qkv_weight, attn_qkv_bias = self.pack_qkv_gemm(
+                self.get_input_by_name(node, "self_attn.q_proj.weight"),
+                self.get_input_by_name(node, "self_attn.k_proj.weight"),
+                self.get_input_by_name(node, "self_attn.v_proj.weight"),
+                self.get_input_by_name(node, "self_attn.q_proj.bias"),
+                self.get_input_by_name(node, "self_attn.k_proj.bias"),
+                self.get_input_by_name(node, "self_attn.v_proj.bias"),
+                self.get_uname(layer_id, "attn_qkv_weight"),
+                self.get_uname(layer_id, "attn_qkv_bias"),
+            )
+
+        attn_out_weight = self.process_initializer(
+            self.get_input_by_name(node, "self_attn.dense.weight"), ProcessGemmWFunc()
+        )
+        attn_out_bias = self.get_input_by_name(node, "self_attn.dense.bias")
+
+        mlp_fc1_weight = self.process_initializer(self.get_input_by_name(node, "mlp.fc1.weight"), ProcessGemmWFunc())
+        mlp_fc2_weight = self.process_initializer(self.get_input_by_name(node, "mlp.fc2.weight"), ProcessGemmWFunc())
+        mlp_fc1_bias = self.get_input_by_name(node, "mlp.fc1.bias")
+        mlp_fc2_bias = self.get_input_by_name(node, "mlp.fc2.bias")
+
+        layer_known_edges_names = []
+        layer_known_edges_names.extend([i_hidden_states, i_key_cache, i_value_cache])
+        layer_known_edges_names.extend([o_hidden_states, o_key_cache, o_value_cache])
+        layer_known_edges_names.extend([ln_weight, ln_bias])
+        if self.attn_op_type != AttentionOpType.Attention:
+            layer_known_edges_names.extend(
+                [
+                    attn_q_weight,
+                    attn_q_bias,
+                    attn_k_weight,
+                    attn_k_bias,
+                    attn_v_weight,
+                    attn_v_bias,
+                    cos_cache,
+                    sin_cache,
+                ]
+            )
+        else:
+            layer_known_edges_names.extend([attn_qkv_weight, attn_qkv_bias])
+        layer_known_edges_names.extend(
+            [attn_out_weight, attn_out_bias, mlp_fc1_weight, mlp_fc1_bias, mlp_fc2_weight, mlp_fc2_bias]
+        )
+        layer_known_edges_names.extend(
+            ["attention_mask", "step", "seqlens_k", "total_sequence_length", "input_metadata", "position_ids"]
+        )
+
+        subgraph_nodes = []
+        subgraph_nodes.extend(self.layernorm([i_hidden_states, ln_weight, ln_bias], ["ln_out"]))
+        subgraph_nodes.extend(self.gemm(["attn_out", attn_out_weight, attn_out_bias], ["attn_add_out"], "OutProj_"))
+        subgraph_nodes.extend(self.gemm(["ln_out", mlp_fc1_weight, mlp_fc1_bias], ["fc1_out"], "FC1_"))
+        subgraph_nodes.extend(self.fastgelu(["fc1_out"], ["gelu_out"]))
+        subgraph_nodes.extend(self.gemm(["gelu_out", mlp_fc2_weight, mlp_fc2_bias], ["fc2_out"], "FC2_"))
+        subgraph_nodes.extend(self.add(["attn_add_out", "fc2_out"], ["residual_1_out"], "Residual_1"))
+        subgraph_nodes.extend(self.add([i_hidden_states, "residual_1_out"], [o_hidden_states], "Residual_2"))
+        if self.attn_op_type != AttentionOpType.Attention:
+            subgraph_nodes.extend(self.gemm(["ln_out", attn_q_weight, attn_q_bias], ["query"], "Q_"))
+            subgraph_nodes.extend(self.gemm(["ln_out", attn_k_weight, attn_k_bias], ["key"], "K_"))
+            subgraph_nodes.extend(self.gemm(["ln_out", attn_v_weight, attn_v_bias], ["value"], "V_"))
+            # vllm engine requires full position ids as the input
+            pos_ids_name = "position_ids" if self.attn_op_type == AttentionOpType.PagedAttention else "step"
+            subgraph_nodes.extend(self.rotary(["query", pos_ids_name, cos_cache, sin_cache], ["query_rot"], "Q_"))
+            subgraph_nodes.extend(self.rotary(["key", pos_ids_name, cos_cache, sin_cache], ["key_rot"], "K_"))
+            if self.attn_op_type == AttentionOpType.MultiHeadAttention:
+                subgraph_nodes.extend(
+                    self.mha(
+                        ["query_rot", "key_rot", "value", "", "attention_mask", "", i_key_cache, i_value_cache],
+                        ["attn_out", o_key_cache, o_value_cache],
+                    )
+                )
+            elif self.attn_op_type == AttentionOpType.GroupQueryAttention:
+                subgraph_nodes.extend(
+                    self.gqa(
+                        [
+                            "query_rot",
+                            "key_rot",
+                            "value",
+                            i_key_cache,
+                            i_value_cache,
+                            "seqlens_k",
+                            "total_sequence_length",
+                        ],
+                        ["attn_out", o_key_cache, o_value_cache],
+                    )
+                )
+                if layer_id == 0:
+                    gqa_aux_nodes = self.get_gqa_aux_nodes()
+                    for new_node in gqa_aux_nodes:
+                        self.nodes_to_add.append(new_node)
+                        self.node_name_to_graph_name[new_node.name] = self.this_graph_name
+                    self.model.add_initializer(
+                        numpy_helper.from_array(np.array([1], dtype="int64"), name="one"), self.this_graph_name
+                    )
+            elif self.attn_op_type == AttentionOpType.PagedAttention:
+                subgraph_nodes.extend(
+                    self.paged_attn(
+                        ["query_rot", "key_rot", "value", i_key_cache, i_value_cache, "input_metadata"],
+                        ["attn_out"],
+                    )
+                )
+        else:
+            past_name = f"past_{layer_id}"
+            present_name = f"present_{layer_id}"
+            layer_known_edges_names.extend([past_name, present_name])
+            subgraph_nodes.extend(
+                self.attention(
+                    ["ln_out", attn_qkv_weight, attn_qkv_bias, "attention_mask", past_name], ["attn_out", present_name]
+                )
+            )
+
+        self.set_unique_name_and_add_nodes(subgraph_nodes, layer_id, layer_known_edges_names)
+
+        self.replace_fp32_value_info(i_hidden_states, ["batch_size", "seq_len", "hidden_size"])
+        self.replace_fp32_value_info(o_hidden_states, ["batch_size", "seq_len", "hidden_size"])
+
+        self.nodes_to_remove.append(node)
+        self.prune_graph = True
+
+
+class PhiOnnxModel(OnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int, hidden_size: int):
+        super().__init__(model)
+        self.phi2_preprocessor = Phi2PreProcessor(self.model, num_heads, hidden_size)
+        self.fission_transformer_block = FissionTransformerBlockPhi(self, num_heads)
+        self.fission_causal_lm_head = FissionTransformerCausalLMHeadPhi(self)
+        self.fission_transformer_layernorm = FissionTransformerLayerNormPhi(self)
+        self.fission_transformer_embedding = FissionTransformerEmbeddingPhi(self)
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        assert options is not None
+        attn_op_type = options.attention_op_type
+
+        self.fission_transformer_block.set_attention_op_type(attn_op_type)
+
+        self.phi2_preprocessor.preprocess_onnx(attn_op_type)
+
+        self.fission_transformer_block.apply()
+        self.fission_transformer_layernorm.apply()
+        self.fission_causal_lm_head.apply()
+        self.fission_transformer_embedding.apply()
+
+        super().prune_graph()
+
+        # SLN ctor is placed here intentionally to delay the symbolic shape inference
+        self.fuse_sln = FusionSkipLayerNormalization(self)
+        self.fuse_bias_sln = FusionBiasSkipLayerNormalization(self)
+        self.fuse_sln.apply()
+        self.fuse_bias_sln.apply()
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "Attention",
+            "MultiHeadAttention",
+            "GroupQueryAttention",
+            "PagedAttention",
+            "Gelu",
+            "BiasGelu",
+            "FastGelu",
+            "LayerNormalization",
+            "SkipLayerNormalization",
+        ]
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators: {op_count}")
+        return op_count
+
+    def is_fully_optimized(self, fused_op_count=None):
+        """
+        Returns True when the model is fully optimized.
+        """
+        if fused_op_count is None:
+            fused_op_count = self.get_fused_operator_statistics()
+
+        def op_count(op_name: str):
+            return fused_op_count.get(op_name) or 0
+
+        attention = (
+            op_count("Attention")
+            + op_count("MultiHeadAttention")
+            + op_count("GroupQueryAttention")
+            + op_count("PagedAttention")
+        )
+        gelu = op_count("Gelu") + op_count("BiasGelu") + op_count("FastGelu")
+        layer_norm = op_count("LayerNormalization") + op_count("SkipLayerNormalization")
+
+        is_perfect = (attention > 0) and (attention == gelu) and (layer_norm >= attention)
+
+        if layer_norm == 0:
+            logger.debug("Layer Normalization not fused")
+
+        if gelu == 0:
+            logger.debug("Gelu (or FastGelu) not fused")
+
+        if attention == 0:
+            logger.warning("Attention (or MultiHeadAttention) not fused")
+
+        return is_perfect
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_sam2.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_sam2.py
new file mode 100644
index 0000000000000000000000000000000000000000..2f83e89849e7f677a174801747e6f5a8cac1602f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_sam2.py
@@ -0,0 +1,137 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+from fusion_attention_sam2 import FusionMultiHeadAttentionSam2
+from fusion_layernorm import FusionLayerNormalizationNCHW
+from fusion_options import FusionOptions
+from import_utils import is_installed
+from onnx import ModelProto
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class Sam2OnnxModel(BertOnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        """Initialize SAM2 ONNX Model.
+
+        Args:
+            model (ModelProto): the ONNX model
+            num_heads (int, optional): number of attention heads. Defaults to 0 (detect the parameter automatically).
+            hidden_size (int, optional): hidden dimension. Defaults to 0 (detect the parameter automatically).
+        """
+        assert (num_heads == 0 and hidden_size == 0) or (num_heads > 0 and hidden_size % num_heads == 0)
+
+        super().__init__(model, num_heads=num_heads, hidden_size=hidden_size)
+
+    def postprocess(self):
+        self.prune_graph()
+        self.remove_unused_constant()
+
+    def fuse_layer_norm(self):
+        super().fuse_layer_norm()
+
+        fusion = FusionLayerNormalizationNCHW(self)
+        fusion.apply()
+
+    def fuse_multi_head_attention(self, options: FusionOptions | None = None):
+        mha_fusion = FusionMultiHeadAttentionSam2(self, self.hidden_size, self.num_heads)
+        mha_fusion.apply()
+
+    def optimize(self, options: FusionOptions | None = None, add_dynamic_axes: bool = False):
+        if is_installed("tqdm"):
+            import tqdm  # noqa: PLC0415
+            from tqdm.contrib.logging import logging_redirect_tqdm  # noqa: PLC0415
+
+            with logging_redirect_tqdm():
+                steps = 12
+                progress_bar = tqdm.tqdm(range(steps), initial=0, desc="sam2 fusion")
+                self._optimize(options, progress_bar)
+        else:
+            logger.info("tqdm is not installed. Run optimization without progress bar")
+            self._optimize(options, None)
+
+    def _optimize(self, options: FusionOptions | None = None, progress_bar=None):
+        if (options is not None) and not options.enable_shape_inference:
+            self.disable_shape_inference()
+
+        self.utils.remove_identity_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        # Remove cast nodes that having same data type of input and output based on symbolic shape inference.
+        self.utils.remove_useless_cast_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_layer_norm:
+            self.fuse_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_gelu:
+            self.fuse_gelu()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.fuse_reshape()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_attention:
+            self.fuse_multi_head_attention(options)
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_skip_layer_norm:
+            self.fuse_skip_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.fuse_shape()
+        if progress_bar:
+            progress_bar.update(1)
+
+        # Remove reshape nodes that having same shape of input and output based on symbolic shape inference.
+        self.utils.remove_useless_reshape_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_bias_skip_layer_norm:
+            # Fuse SkipLayerNormalization and Add Bias before it.
+            self.fuse_add_bias_skip_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if options is not None and options.enable_gelu_approximation:
+            self.gelu_approximation()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.postprocess()
+        if progress_bar:
+            progress_bar.update(1)
+
+        logger.info(f"opset version: {self.get_opset_version()}")
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "MultiHeadAttention",
+            "LayerNormalization",
+            "SkipLayerNormalization",
+        ]
+
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators:{op_count}")
+        return op_count
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_t5.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_t5.py
new file mode 100644
index 0000000000000000000000000000000000000000..0f98f85617cc0b8434c2f304c8cab1717b2e273a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_t5.py
@@ -0,0 +1,985 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+import numpy as np
+from fusion_attention import AttentionMask, FusionAttention
+from fusion_base import Fusion
+from fusion_simplified_layernorm import FusionSimplifiedLayerNormalization, FusionSkipSimplifiedLayerNormalization
+from fusion_utils import NumpyHelper
+from onnx import NodeProto, TensorProto, helper
+from onnx_model import OnnxModel
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class FusionT5Attention(FusionAttention):
+    """
+    Fuse T5 Attention subgraph into one Attention node.
+    """
+
+    def __init__(
+        self,
+        model: OnnxModel,
+        hidden_size: int,
+        num_heads: int,
+        attention_mask: AttentionMask,
+    ):
+        super().__init__(
+            model,
+            hidden_size,
+            num_heads,
+            attention_mask,
+            use_multi_head_attention=False,
+            search_op_types=["Softmax"],
+        )
+        self.static_kv = 1
+
+    def make_attention_node(
+        self,
+        mask_index: str | None,
+        q_matmul: NodeProto,
+        k_matmul: NodeProto,
+        v_matmul: NodeProto,
+        num_heads: int,
+        hidden_size: int,
+        input: str,
+        output: str,
+        attn_bias: str | None,
+        scale: float,
+    ) -> NodeProto | None:
+        """Create an Attention node.
+        Args:
+            mask_index (str): mask input
+            q_matmul (NodeProto): MatMul node in fully connection for Q
+            k_matmul (NodeProto): MatMul node in fully connection for K
+            v_matmul (NodeProto): MatMul node in fully connection for V
+            num_heads (int): number of attention heads. If a model is pruned, it is the number of heads after pruning.
+            hidden_size (int): hidden dimension. If a model is pruned, it is the hidden dimension after pruning.
+            input (str): input name
+            output (str): output name
+        Returns:
+            Union[NodeProto, None]: the node created or None if failed.
+        """
+        assert num_heads > 0
+
+        if hidden_size > 0 and (hidden_size % num_heads) != 0:
+            logger.debug(f"input hidden size {hidden_size} is not a multiple of num of heads {num_heads}")
+            return None
+
+        q_weight = self.model.get_initializer(q_matmul.input[1])
+        k_weight = self.model.get_initializer(k_matmul.input[1])
+        v_weight = self.model.get_initializer(v_matmul.input[1])
+
+        if q_weight is None or k_weight is None or v_weight is None:
+            matmul = q_matmul if q_weight is None else k_matmul if k_weight is None else v_matmul
+            print(
+                f"{matmul.input[1]} is not an initializer. "
+                "Please set do_constant_folding=True in torch.onnx.export to unblock attention fusion"
+            )
+            return None
+
+        qw = NumpyHelper.to_array(q_weight)
+        kw = NumpyHelper.to_array(k_weight)
+        vw = NumpyHelper.to_array(v_weight)
+
+        # assert q and k have same shape as expected
+        assert qw.shape == kw.shape
+
+        qw_in_size = qw.shape[0]
+        kw_in_size = kw.shape[0]
+        vw_in_size = vw.shape[0]
+
+        assert qw_in_size == kw_in_size == vw_in_size
+
+        if hidden_size > 0 and hidden_size != qw_in_size:
+            logger.warning(
+                f"Input hidden size ({hidden_size}) is not same as weight matrix dimension of q,k,v ({qw_in_size}). "
+                "Please provide a correct input hidden size or pass in 0"
+            )
+
+        qw_out_size = np.prod(qw.shape[1:])
+        qkv_weight = np.stack((qw, kw, vw), axis=1)
+        qkv_weight_dim = 3 * qw_out_size
+
+        attention_node_name = self.model.create_node_name("Attention")
+
+        weight = helper.make_tensor(
+            name=attention_node_name + "_qkv_weight",
+            data_type=TensorProto.FLOAT,
+            dims=[qw_in_size, qkv_weight_dim],
+            vals=qkv_weight.tobytes(),
+            raw=True,
+        )
+
+        self.model.add_initializer(weight, self.this_graph_name)
+
+        attention_inputs = [
+            input,
+            attention_node_name + "_qkv_weight",
+            "",
+        ]
+        if mask_index:
+            attention_inputs.append(mask_index)
+        else:
+            attention_inputs.append("")
+
+        if attn_bias:
+            attention_inputs.append("")  # no past
+            attention_inputs.append(attn_bias)
+
+        while attention_inputs and attention_inputs[-1] == "":
+            attention_inputs.pop()
+
+        attention_node = helper.make_node(
+            "Attention",
+            inputs=attention_inputs,
+            outputs=[output],
+            name=attention_node_name,
+        )
+        attention_node.domain = "com.microsoft"
+        attention_node.attribute.extend([helper.make_attribute("num_heads", num_heads)])
+
+        if scale is not None:
+            attention_node.attribute.extend([helper.make_attribute("scale", scale)])
+
+        if self.mask_filter_value is not None:
+            attention_node.attribute.extend([helper.make_attribute("mask_filter_value", float(self.mask_filter_value))])
+
+        return attention_node
+
+    def create_mha_node(
+        self,
+        query: str,
+        key: str,
+        value: str,
+        mask_index: str | None,
+        attn_bias: str | None,
+        past_key: str | None,
+        past_value: str | None,
+        output: str,
+        present_key: str | None,
+        present_value: str | None,
+        num_heads: int,
+        hidden_size: int,
+    ) -> NodeProto | None:
+        assert num_heads > 0 and hidden_size > 0 and query and key and value
+
+        if (hidden_size % num_heads) != 0:
+            logger.debug(f"input hidden size {hidden_size} is not a multiple of num of heads {num_heads}")
+            return None
+
+        attention_node_name = self.model.create_node_name("MultiHeadAttention")
+        attention_inputs = [
+            query,
+            key,
+            value,
+            "",  # bias
+        ]
+
+        if mask_index:
+            attention_inputs.append(mask_index)
+        else:
+            attention_inputs.append("")
+
+        if attn_bias:
+            attention_inputs.append(attn_bias)
+        else:
+            attention_inputs.append("")
+
+        if past_key:
+            assert past_value
+            attention_inputs.append(past_key)
+            attention_inputs.append(past_value)
+
+        while attention_inputs and attention_inputs[-1] == "":
+            attention_inputs.pop()
+
+        attention_outputs = [output]
+        if present_key:
+            assert present_value
+            attention_outputs.append(present_key)
+            attention_outputs.append(present_value)
+
+        print(f"{attention_inputs=}, {attention_outputs=}, {attention_node_name=}")
+        attention_node = helper.make_node(
+            "MultiHeadAttention",
+            inputs=attention_inputs,
+            outputs=attention_outputs,
+            name=attention_node_name,
+        )
+
+        attention_node.domain = "com.microsoft"
+        attention_node.attribute.extend([helper.make_attribute("num_heads", num_heads)])
+        attention_node.attribute.extend([helper.make_attribute("scale", 1.0)])
+        if self.mask_filter_value is not None:
+            attention_node.attribute.extend([helper.make_attribute("mask_filter_value", float(self.mask_filter_value))])
+
+        self.increase_counter("MultiHeadAttention")
+        return attention_node
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        if self.fuse_t5_encoder(node, input_name_to_nodes, output_name_to_node):
+            return
+
+        self.fuse_t5_decoder(node, input_name_to_nodes, output_name_to_node)
+
+    def fuse_t5_encoder(self, softmax_node, input_name_to_nodes, output_name_to_node):
+        assert softmax_node.op_type == "Softmax"
+        qkv_nodes = self.model.match_child_path(
+            softmax_node,
+            ["MatMul", "Transpose", "Reshape"],
+            edges=[(0, 0), (0, 0), (0, 0)],
+            input_name_to_nodes=input_name_to_nodes,
+        )
+        if qkv_nodes is None:
+            return False
+        matmul_qkv, _, reshape_qkv = qkv_nodes
+
+        qkv_shape_nodes = self.model.match_parent_path(
+            reshape_qkv,
+            ["Concat", "Unsqueeze", "Gather", "Shape"],
+            [1, 0, 0, 0],
+            output_name_to_node,
+        )
+        if qkv_shape_nodes is None:
+            return False
+        input_shape_node = qkv_shape_nodes[-1]
+
+        v_nodes = self.model.match_parent_path(
+            matmul_qkv,
+            ["Transpose", "Reshape", "MatMul"],
+            [1, 0, 0],
+            output_name_to_node,
+        )
+        if v_nodes is None:
+            return False
+        _, reshape_v, matmul_v = v_nodes
+        # todo: check reshape_v parent nodes
+
+        qk_nodes = self.model.match_parent_path(
+            matmul_qkv,
+            ["Softmax", "Add", "MatMul"],
+            [0, 0, 0],
+            output_name_to_node,
+        )
+        if qk_nodes is None:
+            return False
+        _, add_qk, matmul_qk = qk_nodes
+
+        mask_nodes = self.model.match_parent_path(
+            add_qk,
+            ["Add", "Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+            [1, 1, 0, 1, 0, 0],
+            output_name_to_node,
+        )
+
+        is_pattern_for_one_graph_input = mask_nodes is None
+        if mask_nodes is not None:
+            mul_node = mask_nodes[1]
+        else:
+            # Pattern for SD3 and Flux.
+            mask_nodes = self.model.match_parent_path(
+                add_qk,
+                ["Add", "Slice", "Mul", "Sub", "Unsqueeze", "Unsqueeze"],
+                [1, 1, 0, 0, 1, 0],
+                output_name_to_node,
+            )
+
+            # If the model is not optimized by ORT, there might be an additional Cast node.
+            if mask_nodes is None:
+                mask_nodes = self.model.match_parent_path(
+                    add_qk,
+                    ["Add", "Slice", "Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+                    [1, 1, 0, 0, 1, 0, 0],
+                    output_name_to_node,
+                )
+                if mask_nodes is None:
+                    return False
+            mul_node = mask_nodes[2]
+
+        _, mul_val = self.model.get_constant_input(mul_node)
+        if mul_val is None:
+            return False
+
+        if mul_val != -10000:
+            self.mask_filter_value = float(mul_val)
+
+        # If the mask is derived from shape of input_ids, it means there is no padding mask.
+        mask_nodes_2 = self.model.match_parent_path(
+            mask_nodes[-1],
+            ["ConstantOfShape", "Concat", "Unsqueeze", "Gather", "Shape"],
+            [0, 0, 0, 0, 0],
+            output_name_to_node,
+        )
+        mask_nodes_3 = self.model.match_parent_path(
+            mask_nodes[-1],
+            ["ConstantOfShape", "Concat", "Unsqueeze", "Gather", "Shape"],
+            [0, 0, 1, 0, 0],
+            output_name_to_node,
+        )
+        if (
+            mask_nodes_2 is not None
+            and any(input.name == mask_nodes_2[-1].input[0] for input in self.model.graph().input)
+            and mask_nodes_3 is not None
+            and mask_nodes_2[-1].input[0] == mask_nodes_3[-1].input[0]
+            and len(mask_nodes_2[1].input) == 2
+        ):
+            mask_index = ""
+        else:
+            mask_index = self.attention_mask.process_mask(mask_nodes[-1].input[0])
+
+        res_pos_bias = None
+        rpb_nodes = self.model.match_parent_path(
+            add_qk,
+            ["Add", "RelativePositionBias"],
+            [1, 0],
+        )
+        if rpb_nodes is None and is_pattern_for_one_graph_input:
+            # Pattern for SD3 and Flux.
+            rpb_nodes = self.model.match_parent_path(
+                add_qk,
+                ["Add", "Slice", "RelativePositionBias"],
+                [1, 0, 0],
+            )
+        if rpb_nodes is None:
+            return False
+
+        res_pos_bias = rpb_nodes[-1].output[0]
+
+        k_nodes = self.model.match_parent_path(
+            matmul_qk,
+            ["Transpose", "Reshape", "MatMul"],
+            [1, 0, 0],
+        )
+        if k_nodes is None:
+            return False
+        _, _, matmul_k = k_nodes
+        # todo: check reshape_k parent nodes
+
+        q_nodes = self.model.match_parent_path(
+            matmul_qk,
+            ["Transpose", "Reshape", "MatMul"],
+            [0, 0, 0],
+        )
+        if q_nodes is None:
+            return False
+
+        _, reshape_q, matmul_q = q_nodes
+        # todo: check reshape_q parent nodes
+
+        if matmul_q.input[0] != input_shape_node.input[0]:
+            return False
+
+        q_num_heads, q_hidden_size = self.get_num_heads_and_hidden_size(reshape_q)
+
+        new_node = self.make_attention_node(
+            mask_index,
+            matmul_q,
+            matmul_k,
+            matmul_v,
+            num_heads=q_num_heads,
+            hidden_size=q_hidden_size,
+            input=input_shape_node.input[0],
+            output=reshape_qkv.output[0],
+            attn_bias=res_pos_bias,
+            scale=1.0,
+        )
+        if new_node is None:
+            return False
+
+        self.nodes_to_add.append(new_node)
+        self.node_name_to_graph_name[new_node.name] = self.this_graph_name
+
+        self.nodes_to_remove.append(reshape_qkv)
+        self.prune_graph = True
+        return True
+
+    def fuse_t5_decoder(self, softmax_node, input_name_to_nodes, output_name_to_node):
+        assert softmax_node.op_type == "Softmax"
+
+        qkv_nodes = self.model.match_child_path(
+            softmax_node,
+            ["MatMul", "Transpose", "Reshape"],
+            edges=[(0, 0), (0, 0), (0, 0)],
+            input_name_to_nodes=input_name_to_nodes,
+        )
+        if qkv_nodes is None:
+            return
+        matmul_qkv, _transpose_qkv, reshape_qkv = qkv_nodes
+
+        qkv_shape_nodes = self.model.match_parent_path(
+            reshape_qkv,
+            ["Concat", "Unsqueeze", "Gather", "Shape"],
+            [1, 0, 0, 0],
+        )
+        if qkv_shape_nodes is None:
+            return
+        input_shape_node = qkv_shape_nodes[-1]
+
+        value = None
+        past_value = None
+        present_value = None
+        v_nodes = self.model.match_parent_path(
+            matmul_qkv,
+            ["Concat", "Transpose", "Reshape", "MatMul"],
+            [1, 1, 0, 0],
+        )
+        if v_nodes is None:
+            v_nodes = self.model.match_parent_path(
+                matmul_qkv,
+                ["Transpose", "Reshape", "MatMul"],
+                [1, 0, 0],
+            )
+            if v_nodes is not None:
+                transpose_v, reshape_v, matmul_v = v_nodes
+                value = reshape_v.input[0]
+                present_value = transpose_v.output[0]
+                if "present_value" not in present_value:
+                    return
+                if matmul_v.input[0] != input_shape_node.input[0]:
+                    self.static_kv = 1
+                else:
+                    self.static_kv = 0
+            else:
+                past_value = matmul_qkv.input[1]
+                if past_value in output_name_to_node:
+                    return
+                if "past_value_cross" not in past_value:
+                    return
+                self.static_kv = 1
+        else:
+            concat_v, _, reshape_v, _ = v_nodes
+            past_value = concat_v.input[0]
+            if past_value in output_name_to_node:
+                return
+            if "past_value_self" not in past_value:
+                return
+            present_value = concat_v.output[0]
+            if "present_value_self" not in present_value:
+                return
+            value = reshape_v.input[0]
+            self.static_kv = 0
+
+        qk_nodes = self.model.match_parent_path(
+            matmul_qkv,
+            ["Softmax", "Add", "MatMul"],
+            [0, 0, 0],
+        )
+        if qk_nodes is None:
+            return
+        _, add_qk, matmul_qk = qk_nodes
+
+        mask_index = None
+        res_pos_bias = None
+        if self.static_kv == 1:
+            mask_nodes = self.model.match_parent_path(
+                add_qk,
+                ["Add", "Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+                [1, 1, 0, 1, 0, 0],
+            )
+            if mask_nodes is not None:
+                mul_node = mask_nodes[1]
+            else:
+                mask_nodes = self.model.match_parent_path(
+                    add_qk,
+                    ["Add", "Slice", "Mul", "Sub", "Cast", "Unsqueeze", "Unsqueeze"],
+                    [1, 1, 0, 0, 1, 0, 0],
+                )
+                if mask_nodes is None:
+                    return
+                mul_node = mask_nodes[2]
+
+            _, mul_val = self.model.get_constant_input(mul_node)
+            if mul_val != -10000:
+                self.mask_filter_value = mul_val
+
+            mask_index = self.attention_mask.process_mask(mask_nodes[-1].input[0])
+        else:
+            matched_path_index, _, _ = self.model.match_parent_paths(
+                add_qk,
+                [
+                    (["Add", "Slice"], [1, 0]),
+                    (["Add", "RelativePositionBias"], [1, 0]),
+                ],
+                output_name_to_node,
+            )
+            if matched_path_index < 0:
+                logger.debug("Skip MultiHeadAttention fusion since attention bias pattern not matched")
+                return
+
+            res_pos_bias = add_qk.input[1]
+
+        key = None
+        past_key = None
+        present_key = None
+        if self.static_kv == 1:
+            k_nodes = self.model.match_parent_path(
+                matmul_qk,
+                ["Transpose", "Reshape", "MatMul"],
+                [1, 0, 0],
+            )
+            if k_nodes is not None:
+                transpose_k, reshape_k, _ = k_nodes
+                key = reshape_k.input[0]
+                present_key_transpose_nodes = input_name_to_nodes[reshape_k.output[0]]
+                for present_key_transpose_node in present_key_transpose_nodes:
+                    present_key_candidate = self.model.find_graph_output(present_key_transpose_node.output[0])
+                    if present_key_candidate is not None:
+                        present_key = present_key_candidate.name
+                        break
+                if present_key is None:
+                    return
+                if "present_key_cross" not in present_key:
+                    return
+            else:
+                k_nodes = self.model.match_parent_path(
+                    matmul_qk,
+                    ["Transpose"],
+                    [1],
+                )
+                if k_nodes is None:
+                    return
+                transpose_k = k_nodes[0]
+
+                past_key = transpose_k.input[0]
+                if past_key in output_name_to_node:
+                    return
+                if "past_key_cross" not in past_key:
+                    return
+        else:
+            idx, k_nodes, _ = self.model.match_parent_paths(
+                matmul_qk,
+                [
+                    (["Transpose", "Concat", "Reshape", "MatMul"], [1, 0, 1, 0]),
+                    (["Transpose", "Concat", "Transpose", "Reshape", "MatMul"], [1, 0, 1, 0, 0]),
+                ],
+                output_name_to_node,
+            )
+            past_key_transpose_node = None
+            present_key_transpose_nodes = None
+            if k_nodes is not None:
+                concat_k, reshape_k = k_nodes[1], k_nodes[-2]
+                key = reshape_k.input[0]
+
+                if idx == 0:
+                    past_key_transpose_node = output_name_to_node[concat_k.input[0]]
+                    past_key = past_key_transpose_node.input[0]
+                else:
+                    past_key = concat_k.input[0]
+                if past_key in output_name_to_node:
+                    return
+                if "past_key_self" not in past_key:
+                    return
+
+                if idx == 0:
+                    present_key_transpose_nodes = input_name_to_nodes[concat_k.output[0]]
+                    for present_key_transpose_node in present_key_transpose_nodes:
+                        present_key_candidate = self.model.find_graph_output(present_key_transpose_node.output[0])
+                        if present_key_candidate is not None:
+                            present_key = present_key_candidate.name
+                            break
+                else:
+                    present_key = concat_k.output[0]
+                if present_key is None:
+                    return
+                if "present_key_self" not in present_key:
+                    return
+            else:
+                k_nodes = self.model.match_parent_path(
+                    matmul_qk,
+                    ["Transpose", "Reshape", "MatMul"],
+                    [1, 0, 0],
+                )
+                if k_nodes is None:
+                    return
+                _, reshape_k, _ = k_nodes
+                key = reshape_k.input[0]
+                present_key_transpose_nodes = input_name_to_nodes[reshape_k.output[0]]
+                for present_key_transpose_node in present_key_transpose_nodes:
+                    present_key_candidate = self.model.find_graph_output(present_key_transpose_node.output[0])
+                    if present_key_candidate is not None:
+                        present_key = present_key_candidate.name
+                        break
+                if present_key is None:
+                    return
+                if "present_key_self" not in present_key:
+                    return
+
+        q_nodes = self.model.match_parent_path(
+            matmul_qk,
+            ["Transpose", "Reshape", "MatMul"],
+            [0, 0, 0],
+        )
+        if q_nodes is None:
+            return
+
+        transpose_q, reshape_q, matmul_q = q_nodes
+
+        if matmul_q.input[0] != input_shape_node.input[0]:
+            return
+
+        q_num_heads, q_hidden_size = self.get_num_heads_and_hidden_size(reshape_q)
+
+        if self.static_kv == 1 and past_key is not None:
+            key = past_key
+            value = past_value
+            past_key = None
+            past_value = None
+
+        if not (key and value and q_num_heads > 0 and q_hidden_size > 0):
+            return
+
+        new_node = self.create_mha_node(
+            query=matmul_q.output[0],
+            key=key,
+            value=value,
+            mask_index=mask_index,
+            attn_bias=res_pos_bias,
+            past_key=past_key,
+            past_value=past_value,
+            output=reshape_qkv.output[0],
+            present_key=present_key,
+            present_value=present_value,
+            num_heads=q_num_heads,
+            hidden_size=q_hidden_size,
+        )
+
+        if new_node:
+            self.nodes_to_add.append(new_node)
+            self.node_name_to_graph_name[new_node.name] = self.this_graph_name
+
+            # Since present_* is graph output, we need update the graph to avoid circular.
+            if present_key or present_value:
+                for graph_output in [present_key, present_value]:
+                    if not (graph_output and self.model.find_graph_output(graph_output)):
+                        print(f"{graph_output=} does not exist in graph output")
+                        return
+                    assert graph_output in output_name_to_node
+                    output_name_to_node[graph_output].output[0] = graph_output + "_copy"
+                    self.model.replace_input_of_all_nodes(graph_output, graph_output + "_copy")
+
+            self.nodes_to_remove.append(reshape_qkv)
+            self.prune_graph = False
+
+
+class FusionRelativePositionBiasBlock(Fusion):
+    def __init__(self, model: OnnxModel):
+        super().__init__(model, "RelativePositionBias", ["Softmax"])
+
+    def fuse(self, node, input_name_to_nodes, output_name_to_node):
+        compute_bias_nodes = self.model.match_parent_path(
+            node,
+            ["Add", "Add", "Slice", "Unsqueeze", "Transpose", "Gather", "Where"],
+            [0, 1, 0, 0, 0, 0, 1],
+            output_name_to_node,
+        )
+
+        if compute_bias_nodes is None:
+            compute_bias_nodes = self.model.match_parent_path(
+                node,
+                ["Add", "Add", "Slice", "Unsqueeze", "Transpose", "Gather", "Add", "Where"],
+                [0, 1, 0, 0, 0, 0, 1, 1],
+                output_name_to_node,
+            )
+            if compute_bias_nodes is None:
+                return
+
+        gather = compute_bias_nodes[5]
+        where = compute_bias_nodes[-1]
+        slice = compute_bias_nodes[2]
+        unsqueeze = compute_bias_nodes[3]
+
+        # Current fusion will not remove the node until the graph is processed.
+        # This avoids to fuse it again when it is shared by multiple layers.
+        if unsqueeze in self.nodes_to_remove:
+            return
+
+        compute_buckets_nodes = self.model.match_parent_path(
+            where,
+            ["Min", "ConstantOfShape", "Shape", "Add", "Cast", "Mul", "Div", "Log", "Div"],
+            [2, 1, 0, 0, 0, 0, 0, 0, 0],
+            output_name_to_node,
+        )
+        if compute_buckets_nodes is None:
+            return
+
+        # This value is to used to compute max_distance later.
+        log_max = self.model.get_constant_value(compute_buckets_nodes[-3].input[1])
+
+        div = compute_buckets_nodes[-1]
+
+        range_nodes = self.model.match_parent_path(
+            div,
+            ["Cast", "Neg", "Min", "ConstantOfShape", "Shape", "Sub", "Unsqueeze", "Range"],
+            [0, 0, 0, 1, 0, 0, 0, 0],
+            output_name_to_node,
+        )
+
+        is_bidirectional = False
+        if range_nodes is None:
+            range_nodes = self.model.match_parent_path(
+                div, ["Cast", "Abs", "Sub", "Unsqueeze", "Range"], [0, 0, 0, 0, 0], output_name_to_node
+            )
+            is_bidirectional = True
+            if range_nodes is None:
+                return
+        range_node = range_nodes[-1]
+
+        # Double check that the constant relative to max_distance and relative_attention_num_buckets.
+        # Most t5 models use max_distance=128, so we hardcode it unitl we see a model with different value.
+
+        # The log_max is the value of the following formula:
+        #   math.log(max_distance / (relative_attention_num_buckets // (4 if is_bidirectional else 2)))
+        # See https://github.com/huggingface/transformers/blob/608e163b527eaee41e650ffb9eb4c422d2679902/src/transformers/models/t5/modeling_t5.py#L397.
+        # Here is the value based on max_distance=128 and relative_attention_num_buckets=32:
+        max_distance = int(np.round(np.exp(log_max) * (32 // (4 if is_bidirectional else 2))))
+        if max_distance != 128:
+            logger.warning(
+                f"max_distance is {max_distance}, which is different from the default value 128. "
+                "Please double check the model configuration."
+            )
+
+        node_name = self.model.create_node_name(
+            "RelativePositionBias", name_prefix="RelPosBias_" + ("encoder" if is_bidirectional else "decoder")
+        )
+
+        table_weight_i = self.model.get_initializer(gather.input[0])
+        if table_weight_i is None:
+            return
+        table_weight = NumpyHelper.to_array(table_weight_i)
+        table_weight_t = np.transpose(table_weight)
+        bias_table = helper.make_tensor(
+            name=node_name + "_bias_table_weight",
+            data_type=TensorProto.FLOAT,
+            dims=[np.shape(table_weight)[0], np.shape(table_weight)[1]],
+            vals=table_weight_t.tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(bias_table, self.this_graph_name)
+
+        # Relative position is like the following in encoder:
+        #                seq_len
+        #                   |
+        #                Range(0, *)
+        #                /      \
+        #   Unsqueeze(axes=0)    Unsqueeze(axes=1)
+        #                \    /
+        #                  Sub
+        #                   |
+        #                  Abs
+        #
+        # Relative position is like the following in decoder:
+        #       past_seq_len   seq_len
+        #                 \    /
+        #                  Add
+        #                /      \
+        #        Range(0, *)    Range(0, *)
+        #                \    /
+        #                  Sub
+        # Note that the graph will slice the attention bias to get last seq_len rows.
+        #
+        # In new version of transformers, the pattern of decoder is changed like the following
+        #
+        #      total_seq_len    Range(start=past_seq_len, end=total_seq_len)
+        #              |              |
+        #          Range(0, *)   Unsqueeze(axes=1)
+        #              |              |
+        #    Unsqueeze(axes=0)    Cast(to=int64)
+        #                   \     /
+        #                     Sub
+        # Currently, there is still Slice to get last seq_len rows so end result is same.
+        # But need to be careful that the shape of bias tensor is changed before Slice.
+        #
+        # RelativePositionBias operator requires query_length == key_length so we shall pass in total_seq_len.
+        # Here we get the end value of the Range node as length to pass to the RelativePositionBias node.
+
+        # TODO: Optimization opportunity: change RelativePositionBias op to support query_length != key_length.
+        #       only compute seq_len rows, then we can remove the Slice after the RelativePositionBias node.
+        inputs = [bias_table.name, range_node.input[1], range_node.input[1]]
+
+        # Use a new tensor name since the shape might be different as mentioned above.
+        bias_output = node_name + "_rel_pos_bias"
+        slice.input[0] = bias_output
+
+        rpb_node = helper.make_node(
+            "RelativePositionBias",
+            inputs=inputs,
+            outputs=[bias_output],
+            name=node_name,
+        )
+        rpb_node.domain = "com.microsoft"
+        rpb_node.attribute.extend([helper.make_attribute("max_distance", max_distance)])
+        rpb_node.attribute.extend([helper.make_attribute("is_bidirectional", is_bidirectional)])
+        self.node_name_to_graph_name[rpb_node.name] = self.this_graph_name
+        self.nodes_to_add.append(rpb_node)
+        self.prune_graph = True
+
+
+class T5OnnxModel(BertOnnxModel):
+    def __init__(self, model, num_heads: int = 0, hidden_size: int = 0):
+        super().__init__(model, num_heads, hidden_size)
+        self.attention_mask = AttentionMask(self)
+
+        # When the model has only one input (input_ids), there is no padding mask.
+        if len(self.model.graph.input) == 1:
+            from fusion_options import AttentionMaskFormat  # noqa: PLC0415
+
+            self.attention_mask.mask_format = AttentionMaskFormat.NoMask
+
+        self.attention_fusion = FusionT5Attention(self, self.hidden_size, self.num_heads, self.attention_mask)
+        self.layer_norm_fusion = FusionSimplifiedLayerNormalization(self)
+        self.skip_layer_norm_fusion = FusionSkipSimplifiedLayerNormalization(self)
+        self.rpb_fusion = FusionRelativePositionBiasBlock(self)
+
+    def fuse_attention(self):
+        self.attention_fusion.apply()
+
+    def fuse_layer_norm(self):
+        self.layer_norm_fusion.apply()
+
+    def fuse_skip_layer_norm(self, shape_infer=True):
+        self.skip_layer_norm_fusion.apply()
+
+    def adjust_rel_pos_bis_length_input(self):
+        # For T5 encoder, it uses complex logic to compute the query and key length when there is only one graph input (input_ids)
+        # We can directly get the length from shape (the 2nd dimension) of input_ids.
+        for node in self.nodes():
+            if node.op_type == "RelativePositionBias":
+                nodes = self.match_parent_path(
+                    node,
+                    [
+                        "Gather",
+                        "Shape",
+                        "Transpose",
+                        "Reshape",
+                        "Concat",
+                        "Unsqueeze",
+                        "Gather",
+                        "Shape",
+                        "SimplifiedLayerNormalization",
+                        "Gather",
+                    ],
+                    [1, 0, 0, 0, 1, 0, 0, 0, 0, 0],
+                )
+                # TODO: more validation on node attributes
+                if nodes is not None:
+                    graph_input_names = [input.name for input in self.model.graph.input]
+                    if nodes[-1].input[1] in graph_input_names:
+                        node_name = self.create_node_name("Shape", name_prefix="Added_Shape_")
+                        shape_node = helper.make_node(
+                            "Shape",
+                            inputs=[nodes[-1].input[1]],
+                            outputs=[node_name + "_Output"],
+                            name=node_name,
+                        )
+
+                        indices_1 = helper.make_tensor(
+                            name="Constant_Index_1",
+                            data_type=TensorProto.INT64,
+                            dims=[1],  # Shape of the tensor
+                            vals=[1],  # Tensor values
+                        )
+                        self.add_initializer(indices_1)
+
+                        gather = helper.make_node(
+                            "Gather",
+                            inputs=[node_name + "_Output", "Constant_Index_1"],
+                            outputs=[node_name + "_Output_Gather_1"],
+                            name=self.create_node_name("Gather", name_prefix="Added_Gather_"),
+                            axis=0,
+                        )
+
+                        self.add_node(shape_node)
+                        self.add_node(gather)
+                        node.input[1] = node_name + "_Output_Gather_1"
+                        node.input[2] = node_name + "_Output_Gather_1"
+
+                break
+
+    # Remove get_extended_attention_mask() since it generates all zeros.
+    def remove_extended_mask_decoder_init(self):
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Add":
+                extended_mask_nodes = self.match_parent_path(
+                    node,
+                    [
+                        "Mul",
+                        "Sub",
+                        "Mul",
+                        "Unsqueeze",
+                        "Cast",
+                        "LessOrEqual",
+                        "Tile",
+                        "Concat",
+                        "Unsqueeze",
+                        "Gather",
+                        "Shape",
+                    ],
+                    [1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0],
+                )
+                if extended_mask_nodes is None:
+                    continue
+
+                rpb_nodes = self.match_parent_path(node, ["RelativePositionBias"], [0])
+                if rpb_nodes is None:
+                    continue
+
+                rpb_node = rpb_nodes[0]
+                rpb_node.output[0] = node.output[0]
+
+                nodes_to_remove.extend(extended_mask_nodes)
+                nodes_to_remove.append(node)
+                self.remove_nodes(nodes_to_remove)
+
+    def remove_extended_mask_decoder(self):
+        nodes_to_remove = []
+        for node in self.nodes():
+            if node.op_type == "Add":
+                extended_mask_nodes = self.match_parent_path(
+                    node,
+                    [
+                        "Mul",
+                        "Sub",
+                        "Mul",
+                        "Unsqueeze",
+                        "Concat",
+                        "Cast",
+                        "LessOrEqual",
+                        "Tile",
+                        "Concat",
+                        "Unsqueeze",
+                        "Gather",
+                        "Shape",
+                    ],
+                    [1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0],
+                )
+                if extended_mask_nodes is None:
+                    continue
+
+                rpb_nodes = self.match_parent_path(node, ["Slice", "RelativePositionBias"], [0, 0])
+                if rpb_nodes is None:
+                    continue
+
+                rpb_node = rpb_nodes[0]
+                rpb_node.output[0] = node.output[0]
+
+                nodes_to_remove.extend(extended_mask_nodes)
+                nodes_to_remove.append(node)
+                self.remove_nodes(nodes_to_remove)
+
+    def preprocess(self):
+        self.adjust_reshape_and_expand()
+        self.rpb_fusion.apply()
+
+    def postprocess(self):
+        # remove get_extended_attention_mask() since it generates all zeros.
+        self.remove_extended_mask_decoder_init()
+        self.remove_extended_mask_decoder()
+        self.adjust_rel_pos_bis_length_input()
+
+        self.prune_graph()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_tnlr.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_tnlr.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bf9c5f0db9b40aad21395e0922e98ce9656ae2a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_tnlr.py
@@ -0,0 +1,226 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+import logging
+
+from fusion_attention import AttentionMask, FusionAttention
+from fusion_utils import NumpyHelper
+from onnx import NodeProto, helper
+from onnx_model import OnnxModel
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class FusionTnlrAttention(FusionAttention):
+    """
+    Fuse TNLR Attention subgraph into one Attention node.
+    TNLR Attention has extra addition after qk nodes and adopts [S, B, NH] as I/O shape.
+    """
+
+    def __init__(
+        self,
+        model: OnnxModel,
+        hidden_size: int,
+        num_heads: int,
+        attention_mask: AttentionMask,
+    ):
+        super().__init__(model, hidden_size, num_heads, attention_mask)
+
+    def create_attention_node(
+        self,
+        mask_index: str,
+        matmul: NodeProto,
+        add: NodeProto,
+        num_heads: int,
+        hidden_size: int,
+        input: str,
+        output: str,
+        add_qk_str: str,
+    ) -> NodeProto | None:
+        assert num_heads > 0
+        if hidden_size > 0 and (hidden_size % num_heads) != 0:
+            logger.debug(f"input hidden size {hidden_size} is not a multiple of num of heads {num_heads}")
+            return None
+
+        weight = self.model.get_initializer(matmul.input[1])
+        bias = self.model.get_initializer(add.input[1]) or self.model.get_initializer(add.input[0])
+
+        if weight is None or bias is None:
+            return None
+
+        qkv_weight = NumpyHelper.to_array(weight)
+        qkv_bias = NumpyHelper.to_array(bias)
+
+        attention_node_name = self.model.create_node_name("Attention")
+
+        tensor_dtype = weight.data_type
+        np_type = helper.tensor_dtype_to_np_dtype(tensor_dtype)
+        weight = helper.make_tensor(
+            name=attention_node_name + "_qkv_weight",
+            data_type=tensor_dtype,
+            dims=[hidden_size, 3 * hidden_size],
+            vals=qkv_weight.astype(np_type).tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(weight, self.this_graph_name)
+
+        bias = helper.make_tensor(
+            name=attention_node_name + "_qkv_bias",
+            data_type=tensor_dtype,
+            dims=[3 * hidden_size],
+            vals=qkv_bias.astype(np_type).tobytes(),
+            raw=True,
+        )
+        self.model.add_initializer(bias, self.this_graph_name)
+
+        attention_inputs = [
+            input,
+            attention_node_name + "_qkv_weight",
+            attention_node_name + "_qkv_bias",
+        ]
+        if mask_index is not None:
+            attention_inputs.append(mask_index)
+        else:
+            attention_inputs.append("")
+
+        if add_qk_str is not None:
+            attention_inputs.append("")
+            attention_inputs.append(add_qk_str)
+
+        attention_node = helper.make_node(
+            "Attention",
+            inputs=attention_inputs,
+            outputs=[output],
+            name=attention_node_name,
+        )
+        attention_node.domain = "com.microsoft"
+        attention_node.attribute.extend([helper.make_attribute("num_heads", num_heads)])
+
+        return attention_node
+
+    def fuse(self, normalize_node, input_name_to_nodes, output_name_to_node):
+        # Sometimes we can not fuse skiplayernormalization since the add before layernorm has an output that used by nodes outside skiplayernorm
+        # Conceptually we treat add before layernorm as skiplayernorm node since they share the same pattern
+        start_node = normalize_node
+        if normalize_node.op_type != "SkipLayerNormalization":
+            return
+
+        # SkipLayerNormalization has two inputs, and one of them is the root input for attention.
+        qkv_nodes = self.model.match_parent_path(
+            start_node,
+            ["Where", "Add", "MatMul", "Reshape", "Transpose", "MatMul"],
+            [1, 1, 1, 0, 0, 0],
+        )
+        if qkv_nodes is not None:
+            (_, _, matmul_below, reshape_qkv, transpose_qkv, matmul_qkv) = qkv_nodes
+        else:
+            return
+
+        other_inputs = []
+        for _i, input in enumerate(start_node.input):
+            if input not in output_name_to_node:
+                continue
+
+            if input == qkv_nodes[0].output[0]:
+                continue
+            other_inputs.append(input)
+        if len(other_inputs) != 1:
+            return
+
+        root_input = other_inputs[0]
+
+        v_nodes = self.model.match_parent_path(
+            matmul_qkv,
+            ["Transpose", "Reshape", "Slice", "Add", "MatMul"],
+            [1, 0, 0, 0, 1],
+        )
+        if v_nodes is None:
+            return
+        (_, _, _, add, matmul) = v_nodes
+
+        upper_nodes = self.model.match_parent_path(matmul, ["Transpose"], [0])
+        transpose = upper_nodes[0]
+
+        qk_nodes = self.model.match_parent_path(matmul_qkv, ["Softmax", "Add", "MatMul"], [0, 0, 0])
+        if qk_nodes is None:
+            return
+        (_, add_qk, matmul_qk) = qk_nodes
+
+        q_nodes = self.model.match_parent_path(
+            matmul_qk,
+            ["Mul", "Transpose", "Reshape", "Slice", "Add", "MatMul"],
+            [0, 0, 0, 0, 0, 1],
+        )
+        if q_nodes is None:
+            return
+        add = q_nodes[-2]
+        matmul = q_nodes[-1]
+
+        k_nodes = self.model.match_parent_path(
+            matmul_qk,
+            ["Transpose", "Reshape", "Slice", "Add", "MatMul"],
+            [1, 0, 0, 0, 1],
+        )
+        if k_nodes is None:
+            return
+        add = k_nodes[-2]
+        matmul = k_nodes[-1]
+
+        relative_position_bias_nodes = self.model.match_parent_path(add_qk, ["Reshape", "Where"], [1, 0])
+        if relative_position_bias_nodes is None:
+            return
+
+        if matmul.input[0] == root_input:
+            mask_index = None
+            attention_last_node = reshape_qkv
+            # number of heads are same for all the paths, hence to create attention node, we pass the q_num_heads
+            # the input_hidden_size represents the input hidden size, this is used as needed but hidden sizes for Q, K are extracted appropriately
+            new_node = self.create_attention_node(
+                mask_index,
+                matmul,
+                add,
+                self.num_heads,
+                self.hidden_size,
+                root_input,
+                attention_last_node.output[0],
+                relative_position_bias_nodes[0].input[0],
+            )
+            if new_node is None:
+                return
+
+            self.nodes_to_add.append(new_node)
+            self.node_name_to_graph_name[new_node.name] = self.this_graph_name
+
+            # Add a transpose node after the attention node
+            back_transpose = helper.make_node(
+                "Transpose",
+                ["back_transpose_in_" + new_node.name],
+                [new_node.output[0]],
+                "back_transpose_" + new_node.name,
+                perm=[1, 0, 2],
+            )
+            self.model.add_node(back_transpose, self.this_graph_name)
+            new_node.input[0] = transpose.input[0]
+            new_node.output[0] = "back_transpose_in_" + new_node.name
+
+            self.nodes_to_remove.extend([attention_last_node, transpose_qkv, matmul_qkv])
+            self.nodes_to_remove.extend(qk_nodes)
+            self.nodes_to_remove.extend(q_nodes)
+            self.nodes_to_remove.extend(k_nodes)
+            self.nodes_to_remove.extend(v_nodes)
+
+            # Use prune graph to remove mask nodes since they are shared by all attention nodes.
+            # self.nodes_to_remove.extend(mask_nodes)
+            self.prune_graph = True
+
+
+class TnlrOnnxModel(BertOnnxModel):
+    def __init__(self, model, num_heads, hidden_size):
+        super().__init__(model, num_heads, hidden_size)
+        self.attention_mask = AttentionMask(self)
+        self.attention_fusion = FusionTnlrAttention(self, self.hidden_size, self.num_heads, self.attention_mask)
+
+    def fuse_attention(self):
+        self.attention_fusion.apply()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_unet.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_unet.py
new file mode 100644
index 0000000000000000000000000000000000000000..db390fa8f2bf0e04f5d384387cc54292a49e08c3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_unet.py
@@ -0,0 +1,258 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+
+from fusion_attention_unet import FusionAttentionUnet
+from fusion_bias_add import FusionBiasAdd
+from fusion_biassplitgelu import FusionBiasSplitGelu
+from fusion_group_norm import FusionGroupNorm
+from fusion_nhwc_conv import FusionNhwcConv
+from fusion_options import FusionOptions
+from fusion_skip_group_norm import FusionSkipGroupNorm
+from fusion_transpose import FusionInsertTranspose, FusionTranspose
+from import_utils import is_installed
+from onnx import ModelProto
+from onnx_model import OnnxModel
+from onnx_model_bert import BertOnnxModel
+
+logger = logging.getLogger(__name__)
+
+
+class UnetOnnxModel(BertOnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        """Initialize UNet ONNX Model.
+
+        Args:
+            model (ModelProto): the ONNX model
+            num_heads (int, optional): number of attention heads. Defaults to 0 (detect the parameter automatically).
+            hidden_size (int, optional): hidden dimension. Defaults to 0 (detect the parameter automatically).
+        """
+        assert (num_heads == 0 and hidden_size == 0) or (num_heads > 0 and hidden_size % num_heads == 0)
+
+        super().__init__(model, num_heads=num_heads, hidden_size=hidden_size)
+
+    def preprocess(self):
+        self.remove_useless_div()
+
+    def postprocess(self):
+        self.prune_graph()
+        self.remove_unused_constant()
+
+    def remove_useless_div(self):
+        """Remove Div by 1"""
+        div_nodes = [node for node in self.nodes() if node.op_type == "Div"]
+
+        nodes_to_remove = []
+        for div in div_nodes:
+            if self.find_constant_input(div, 1.0) == 1:
+                nodes_to_remove.append(div)
+
+        for node in nodes_to_remove:
+            self.replace_input_of_all_nodes(node.output[0], node.input[0])
+
+        if nodes_to_remove:
+            self.remove_nodes(nodes_to_remove)
+            logger.info("Removed %d Div nodes", len(nodes_to_remove))
+
+    def convert_conv_to_nhwc(self):
+        # Transpose weights in offline might help since ORT does not apply constant-folding on Transpose nodes.
+        conv_to_nhwc_conv = FusionNhwcConv(self, update_weight=True)
+        conv_to_nhwc_conv.apply()
+
+    def merge_adjacent_transpose(self):
+        fusion_transpose = FusionTranspose(self)
+        fusion_transpose.apply()
+
+        remove_count = 0
+        nodes = self.get_nodes_by_op_type("Transpose")
+        for node in nodes:
+            permutation = OnnxModel.get_node_attribute(node, "perm")
+            assert isinstance(permutation, list)
+            if permutation != list(range(len(permutation))):
+                continue
+            assert not (
+                self.find_graph_output(node.output[0])
+                or self.find_graph_input(node.input[0])
+                or self.find_graph_output(node.input[0])
+            )
+
+            # Let all children nodes skip current Transpose node and link to its parent
+            # Note that we cannot update parent node output since parent node might have more than one children.
+            self.replace_input_of_all_nodes(node.output[0], node.input[0])
+
+            self.remove_node(node)
+            remove_count += 1
+
+        total = len(fusion_transpose.nodes_to_remove) + remove_count
+        if total:
+            logger.info("Removed %d Transpose nodes", total)
+
+    def fuse_multi_head_attention(self, options: FusionOptions | None = None):
+        # Self Attention
+        enable_packed_qkv = (options is None) or options.enable_packed_qkv
+        self_attention_fusion = FusionAttentionUnet(
+            self,
+            self.hidden_size,
+            self.num_heads,
+            is_cross_attention=False,
+            enable_packed_qkv=enable_packed_qkv,
+            enable_packed_kv=False,
+        )
+        self_attention_fusion.apply()
+
+        # Cross Attention
+        enable_packed_kv = (options is None) or options.enable_packed_kv
+        cross_attention_fusion = FusionAttentionUnet(
+            self,
+            self.hidden_size,
+            self.num_heads,
+            is_cross_attention=True,
+            enable_packed_qkv=False,
+            enable_packed_kv=enable_packed_kv,
+        )
+        cross_attention_fusion.apply()
+
+    def fuse_bias_add(self):
+        fusion = FusionBiasAdd(self)
+        fusion.apply()
+
+    def optimize(self, options: FusionOptions | None = None):
+        if is_installed("tqdm"):
+            import tqdm  # noqa: PLC0415
+            from tqdm.contrib.logging import logging_redirect_tqdm  # noqa: PLC0415
+
+            with logging_redirect_tqdm():
+                steps = 18
+                progress_bar = tqdm.tqdm(range(steps), initial=0, desc="fusion")
+                self._optimize(options, progress_bar)
+        else:
+            logger.info("tqdm is not installed. Run optimization without progress bar")
+            self._optimize(options, None)
+
+    def _optimize(self, options: FusionOptions | None = None, progress_bar=None):
+        if (options is not None) and not options.enable_shape_inference:
+            self.disable_shape_inference()
+
+        self.utils.remove_identity_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        # Remove cast nodes that having same data type of input and output based on symbolic shape inference.
+        self.utils.remove_useless_cast_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_layer_norm:
+            self.fuse_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_gelu:
+            self.fuse_gelu()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.preprocess()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.fuse_reshape()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_group_norm:
+            channels_last = (options is None) or options.group_norm_channels_last
+            group_norm_fusion = FusionGroupNorm(self, channels_last)
+            group_norm_fusion.apply()
+
+            insert_transpose_fusion = FusionInsertTranspose(self)
+            insert_transpose_fusion.apply()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_bias_splitgelu:
+            bias_split_gelu_fusion = FusionBiasSplitGelu(self)
+            bias_split_gelu_fusion.apply()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_attention:
+            # self.save_model_to_file("before_mha.onnx")
+            self.fuse_multi_head_attention(options)
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_skip_layer_norm:
+            self.fuse_skip_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.fuse_shape()
+        if progress_bar:
+            progress_bar.update(1)
+
+        # Remove reshape nodes that having same shape of input and output based on symbolic shape inference.
+        self.utils.remove_useless_reshape_nodes()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_skip_group_norm:
+            skip_group_norm_fusion = FusionSkipGroupNorm(self)
+            skip_group_norm_fusion.apply()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if (options is None) or options.enable_bias_skip_layer_norm:
+            # Fuse SkipLayerNormalization and Add Bias before it.
+            self.fuse_add_bias_skip_layer_norm()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if options is not None and options.enable_gelu_approximation:
+            self.gelu_approximation()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if options is None or options.enable_nhwc_conv:
+            self.convert_conv_to_nhwc()
+            self.merge_adjacent_transpose()
+        if progress_bar:
+            progress_bar.update(1)
+
+        if options is not None and options.enable_bias_add:
+            self.fuse_bias_add()
+        if progress_bar:
+            progress_bar.update(1)
+
+        self.postprocess()
+        if progress_bar:
+            progress_bar.update(1)
+
+        logger.info(f"opset version: {self.get_opset_version()}")
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "Attention",
+            "MultiHeadAttention",
+            "LayerNormalization",
+            "SkipLayerNormalization",
+            "BiasSplitGelu",
+            "GroupNorm",
+            "SkipGroupNorm",
+            "NhwcConv",
+            "BiasAdd",
+        ]
+
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators:{op_count}")
+        return op_count
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_vae.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_vae.py
new file mode 100644
index 0000000000000000000000000000000000000000..1ee1e8c55f2ea343974b7c012d5124b445d898e3
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_model_vae.py
@@ -0,0 +1,42 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+from logging import getLogger
+
+from fusion_attention_vae import FusionAttentionVae
+from fusion_options import FusionOptions
+from onnx import ModelProto
+from onnx_model_unet import UnetOnnxModel
+
+logger = getLogger(__name__)
+
+
+class VaeOnnxModel(UnetOnnxModel):
+    def __init__(self, model: ModelProto, num_heads: int = 0, hidden_size: int = 0):
+        assert (num_heads == 0 and hidden_size == 0) or (num_heads > 0 and hidden_size % num_heads == 0)
+        super().__init__(model, num_heads=num_heads, hidden_size=hidden_size)
+
+    def fuse_multi_head_attention(self, options: FusionOptions | None = None):
+        # Self Attention
+        self_attention_fusion = FusionAttentionVae(self, self.hidden_size, self.num_heads)
+        self_attention_fusion.apply()
+
+    def get_fused_operator_statistics(self):
+        """
+        Returns node count of fused operators.
+        """
+        op_count = {}
+        ops = [
+            "Attention",
+            "GroupNorm",
+            "SkipGroupNorm",
+            "NhwcConv",
+        ]
+        for op in ops:
+            nodes = self.get_nodes_by_op_type(op)
+            op_count[op] = len(nodes)
+
+        logger.info(f"Optimized operators:{op_count}")
+        return op_count
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_utils.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..838b8cf3ba3c38b1049094404b9369cbcb28618f
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/onnx_utils.py
@@ -0,0 +1,55 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+from fusion_utils import NumpyHelper
+from onnx import ModelProto, TensorProto
+from onnx.external_data_helper import set_external_data
+from onnx_model import OnnxModel
+
+from onnxruntime import OrtValue
+
+
+def extract_raw_data_from_model(model: ModelProto):
+    """
+    Extract external data from model and return the external data as a list of tuples (name, value).
+    Note this function does not handle external data that is not loaded into the model as raw data.
+
+    Args:
+        model (ModelProto): the model proto to extract external data from.
+    Returns:
+        (external_names, external_values): a tuple of two lists of external data names and values.
+    """
+    external_data = []
+    onnx_model = OnnxModel(model)
+    for graph in onnx_model.graphs():
+        for initializer in graph.initializer:
+            name = initializer.name
+
+            if initializer.HasField("raw_data"):
+                numpy_tensor = NumpyHelper.to_array(initializer)
+                ort_value = OrtValue.ortvalue_from_numpy(numpy_tensor)
+                external_data.append((name, ort_value))
+                # mimic set_external_data
+                set_external_data(initializer, location="foo.bin")
+                initializer.name = name
+                initializer.ClearField("raw_data")
+
+    return zip(*external_data, strict=False)
+
+
+def has_external_data(model: ModelProto):
+    """
+    Check if the model has external data.
+
+    Args:
+        model (ModelProto): the model proto to check for external data.
+    Returns:
+        bool: True if the model has external data, False otherwise.
+    """
+    onnx_model = OnnxModel(model)
+    for graph in onnx_model.graphs():
+        for initializer in graph.initializer:
+            if initializer.HasField("data_location") and initializer.data_location == TensorProto.EXTERNAL:
+                return True
+    return False
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/optimizer.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/optimizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..4a22a32e55b7663f5442e9c22f8545e4f85ece70
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/optimizer.py
@@ -0,0 +1,621 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+# Convert Bert ONNX model converted from TensorFlow or exported from PyTorch to use Attention, Gelu,
+# SkipLayerNormalization and EmbedLayerNormalization ops to optimize
+# performance on NVidia GPU and CPU.
+#
+# For Bert model exported from PyTorch, OnnxRuntime has bert model optimization support internally.
+# You can use the option --use_onnxruntime to check optimizations from OnnxRuntime.
+# For Bert model file like name.onnx, optimized model for GPU or CPU from OnnxRuntime will output as
+# name_ort_gpu.onnx or name_ort_cpu.onnx in the same directory.
+#
+# This script is retained for experiment purpose. Useful scenarios like the following:
+#  (1) Change model from fp32 to fp16 for mixed precision inference in GPU with Tensor Core.
+#  (2) Change input data type from int64 to int32.
+#  (3) Some model cannot be handled by OnnxRuntime, and you can modify this script to get optimized model.
+
+import argparse
+import logging
+import os
+import tempfile
+from pathlib import Path
+
+from fusion_options import FusionOptions
+from onnx import ModelProto, load_model
+from onnx_model import OnnxModel
+from onnx_model_bart import BartOnnxModel
+from onnx_model_bert import BertOnnxModel
+from onnx_model_bert_keras import BertOnnxModelKeras
+from onnx_model_bert_tf import BertOnnxModelTF
+from onnx_model_clip import ClipOnnxModel
+from onnx_model_conformer import ConformerOnnxModel
+from onnx_model_gpt2 import Gpt2OnnxModel
+from onnx_model_mmdit import MmditOnnxModel
+from onnx_model_phi import PhiOnnxModel
+from onnx_model_sam2 import Sam2OnnxModel
+from onnx_model_t5 import T5OnnxModel
+from onnx_model_tnlr import TnlrOnnxModel
+from onnx_model_unet import UnetOnnxModel
+from onnx_model_vae import VaeOnnxModel
+from onnx_utils import extract_raw_data_from_model, has_external_data
+
+import onnxruntime
+
+logger = logging.getLogger(__name__)
+
+# Map model type to tuple: optimizer class, export tools (pytorch, tf2onnx, keras2onnx), and default opt_level
+MODEL_TYPES = {
+    "bart": (BartOnnxModel, "pytorch", 1),
+    "bert": (BertOnnxModel, "pytorch", 1),
+    "bert_tf": (BertOnnxModelTF, "tf2onnx", 0),
+    "bert_keras": (BertOnnxModelKeras, "keras2onnx", 0),
+    "clip": (ClipOnnxModel, "pytorch", 1),  # Clip in Stable Diffusion
+    "conformer": (ConformerOnnxModel, "pytorch", 1),
+    "gpt2": (Gpt2OnnxModel, "pytorch", 1),
+    "gpt2_tf": (Gpt2OnnxModel, "tf2onnx", 0),  # might add a class for GPT2OnnxModel for TF later.
+    "gpt_neox": (BertOnnxModel, "pytorch", 0),  # GPT-NeoX
+    "phi": (PhiOnnxModel, "pytorch", 0),
+    "qwen3": (Gpt2OnnxModel, "pytorch", 0),  # Qwen3 (decoder-only with RoPE, GQA, RMSNorm)
+    "sam2": (Sam2OnnxModel, "pytorch", 1),
+    "swin": (BertOnnxModel, "pytorch", 1),
+    "tnlr": (TnlrOnnxModel, "pytorch", 1),
+    "t5": (T5OnnxModel, "pytorch", 2),
+    "unet": (UnetOnnxModel, "pytorch", 1),  # UNet in Stable Diffusion
+    "vae": (VaeOnnxModel, "pytorch", 1),  # UAE in Stable Diffusion
+    "vit": (BertOnnxModel, "pytorch", 1),
+    "mmdit": (MmditOnnxModel, "pytorch", 1),
+}
+
+
+def optimize_by_onnxruntime(
+    onnx_model: str | ModelProto | None = None,
+    use_gpu: bool = False,
+    optimized_model_path: str | None = None,
+    opt_level: int | None = 99,
+    disabled_optimizers: list[str] = [],  # noqa: B006
+    verbose: bool = False,
+    save_as_external_data: bool = False,
+    external_data_filename: str = "",
+    external_data_file_threshold: int = 1024,
+    *,
+    provider: str | None = None,
+    **deprecated_kwargs,
+) -> str:
+    """
+    Use onnxruntime to optimize model.
+
+    Args:
+        onnx_model (str | ModelProto): the path of input onnx model or ModelProto.
+        use_gpu (bool): whether the optimized model is targeted to run in GPU.
+        optimized_model_path (str or None): the path of optimized model.
+        opt_level (int): graph optimization level.
+        disabled_optimizers (List[str]): a list of names of disabled optimizers
+        save_as_external_data (bool): whether to save external data outside of ONNX model
+        external_data_filename (str): name of external data file. If not provided, name is automatically created from ONNX model.
+        external_data_file_threshold (int): threshold to decide whether to save tensor in ONNX model or in external data file
+        provider (str or None): execution provider to use if use_gpu
+    Returns:
+        optimized_model_path (str): the path of optimized model
+    """
+    assert opt_level in [1, 2, 99]
+    from torch import version as torch_version  # noqa: PLC0415
+
+    if onnx_model is None:
+        onnx_model = deprecated_kwargs.pop("onnx_model_path", None)
+    assert onnx_model is not None
+
+    if (
+        use_gpu
+        and provider is None
+        and set(onnxruntime.get_available_providers()).isdisjoint(
+            ["CUDAExecutionProvider", "MIGraphXExecutionProvider"]
+        )
+    ):
+        logger.error("There is no gpu for onnxruntime to do optimization.")
+        return onnx_model
+
+    model = (
+        OnnxModel(load_model(onnx_model, load_external_data=False))
+        if isinstance(onnx_model, str)
+        else OnnxModel(onnx_model)
+    )
+    if model.use_float16() and not use_gpu:
+        logger.warning(
+            "This model uses float16 in the graph, use_gpu=False might cause extra Cast nodes. "
+            "Most operators have no float16 implementation in CPU, so Cast nodes are added to compute them in float32. "
+            "If the model is intended to use in GPU, please set use_gpu=True. "
+            "Otherwise, consider exporting onnx in float32 and optional int8 quantization for better performance. "
+        )
+
+    sess_options = onnxruntime.SessionOptions()
+    if opt_level == 1:
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_BASIC
+    elif opt_level == 2:
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_EXTENDED
+    elif opt_level == 3:
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_LAYOUT
+    else:
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
+
+    if optimized_model_path is None:
+        if isinstance(onnx_model, str):
+            path_prefix = str(Path(onnx_model).with_suffix(""))  # remove .onnx suffix
+        else:
+            path_prefix = "optimized_model"
+        optimized_model_path = "{}_o{}_{}.onnx".format(path_prefix, opt_level, "gpu" if use_gpu else "cpu")
+
+    sess_options.optimized_model_filepath = optimized_model_path
+    if save_as_external_data:
+        if len(external_data_filename) == 0:
+            # Set external data filename to model_name.onnx.data
+            external_data_filename = os.path.basename(optimized_model_path) + ".data"
+        sess_options.add_session_config_entry(
+            "session.optimized_model_external_initializers_file_name", external_data_filename
+        )
+        sess_options.add_session_config_entry(
+            "session.optimized_model_external_initializers_min_size_in_bytes", str(external_data_file_threshold)
+        )
+
+    if verbose:
+        print("Using onnxruntime to optimize model - Debug level Set to verbose")
+        sess_options.log_severity_level = 0
+
+    kwargs = {}
+    if disabled_optimizers:
+        kwargs["disabled_optimizers"] = disabled_optimizers
+
+    if not use_gpu:
+        providers = ["CPUExecutionProvider"]
+    elif provider is not None:
+        if provider == "dml":
+            providers = ["DmlExecutionProvider"]
+        elif provider == "migraphx":
+            providers = ["MIGraphXExecutionProvider"]
+        elif provider == "cuda":
+            providers = ["CUDAExecutionProvider"]
+        elif provider == "tensorrt":
+            providers = ["TensorrtExecutionProvider", "CUDAExecutionProvider"]
+        else:
+            providers = ["CUDAExecutionProvider"]
+
+        providers.append("CPUExecutionProvider")
+    else:
+        providers = []
+
+        if torch_version.hip:
+            providers.append("MIGraphXExecutionProvider")
+        else:
+            providers.append("CUDAExecutionProvider")
+
+    # For large model, extract external data from model and add to session options
+    if isinstance(onnx_model, ModelProto):
+        if has_external_data(onnx_model):
+            raise ValueError(
+                "ModelProto has external data not loaded into memory, ORT cannot create session. "
+                "Please load external data before calling this function. "
+                "See https://onnx.ai/onnx/repo-docs/ExternalData.html for more information."
+            )
+        external_names, external_values = extract_raw_data_from_model(onnx_model)
+        sess_options.add_external_initializers(list(external_names), list(external_values))
+
+    # Inference session is only used to optimize the model.
+    onnx_model = onnx_model.SerializeToString() if isinstance(onnx_model, ModelProto) else onnx_model
+    onnxruntime.InferenceSession(onnx_model, sess_options, providers=providers, **kwargs)
+
+    assert os.path.exists(optimized_model_path) and os.path.isfile(optimized_model_path)
+    logger.debug("Save optimized model by onnxruntime to %s", optimized_model_path)
+    return optimized_model_path
+
+
+def optimize_by_fusion(
+    model: ModelProto,
+    model_type: str = "bert",
+    num_heads: int = 0,
+    hidden_size: int = 0,
+    optimization_options: FusionOptions | None = None,
+) -> OnnxModel:
+    """Optimize Model by graph fusion logic.
+
+    Note that ONNXRuntime graph optimizations (like constant folding) will not be applied. So it is better to enable
+    constant folding during exporting ONNX model, or run optimize_by_onnxruntime on the model first like optimize_model.
+
+    For BERT model, num_heads and hidden_size are optional. For other model types, you need to specify these parameters.
+
+    Args:
+        model (ModelProto): model object
+        model_type (str, optional): model type - like bert, bert_tf, bert_keras or gpt2. Defaults to 'bert'.
+        num_heads (int, optional): number of attention heads. Defaults to 0.
+                                   0 allows detect the parameter from graph automatically.
+        hidden_size (int, optional): hidden size. Defaults to 0.
+                                     0 allows detect the parameter from graph automatically.
+        optimization_options (FusionOptions, optional): optimization options that turn on/off some fusions.
+                                                        Defaults to None.
+
+     Returns:
+        object of an optimizer class.
+    """
+    if model_type not in ["bert", "t5", "swin", "unet", "vae", "clip", "sam2", "mmdit"] and (
+        num_heads == 0 or hidden_size == 0
+    ):
+        logger.warning(f"Please specify parameters of num_heads and hidden_size for model_type {model_type}")
+
+    if model_type not in MODEL_TYPES:
+        logger.warning(f"Unsupported model type: {model_type} for graph fusion, directly return model.")
+        return OnnxModel(model)
+
+    (optimizer_class, producer, _) = MODEL_TYPES[model_type]
+
+    if model.producer_name and producer != model.producer_name:
+        logger.warning(
+            f'Model producer not matched: Expected "{producer}", Got "{model.producer_name}".'
+            "Please specify correct --model_type parameter."
+        )
+
+    if optimization_options is None:
+        optimization_options = FusionOptions(model_type)
+
+    optimizer = optimizer_class(model, num_heads, hidden_size)
+
+    optimizer.optimize(optimization_options)
+
+    optimizer.topological_sort()
+
+    optimizer.model.producer_name = "onnxruntime.transformers"
+    from onnxruntime import __version__ as onnxruntime_version  # noqa: PLC0415
+
+    optimizer.model.producer_version = onnxruntime_version
+
+    return optimizer
+
+
+def optimize_model(
+    input: str | ModelProto,
+    model_type: str = "bert",
+    num_heads: int = 0,
+    hidden_size: int = 0,
+    optimization_options: FusionOptions | None = None,
+    opt_level: int | None = None,
+    use_gpu: bool = False,
+    only_onnxruntime: bool = False,
+    verbose: bool = False,
+    *,
+    provider: str | None = None,
+) -> OnnxModel:
+    """Optimize Model by OnnxRuntime and/or python fusion logic.
+
+    ONNX Runtime has graph optimizations (https://onnxruntime.ai/docs/performance/model-optimizations/graph-optimizations.html).
+    However, the coverage is limited. We also have graph fusions that implemented in Python to improve the coverage.
+    They can combined: ONNX Runtime will run first when opt_level > 0, then graph fusions in Python will be applied.
+
+    To use ONNX Runtime only and no Python fusion logic, use only_onnxruntime flag and a positive opt_level like
+        optimize_model(input, opt_level=1, use_gpu=False, only_onnxruntime=True)
+
+    When opt_level is None, we will choose default optimization level according to model type.
+
+    When opt_level is 0 and only_onnxruntime is False, only python fusion logic is used and onnxruntime is disabled.
+
+    When opt_level > 1, use_gpu shall set properly
+    since the optimized graph might contain operators for GPU or CPU only.
+
+    If your model is intended for GPU inference only (especially float16 or mixed precision model), it is recommended to
+    set use_gpu to be True, otherwise the model is not optimized for GPU inference.
+
+    For BERT model, num_heads and hidden_size are optional. For other model types, you need specify these parameters.
+
+    Args:
+        input (str | ModelProto): input model path or ModelProto.
+        model_type (str, optional): model type - like bert, bert_tf, bert_keras or gpt2. Defaults to 'bert'.
+        num_heads (int, optional): number of attention heads. Defaults to 0.
+            0 allows detect the parameter from graph automatically.
+        hidden_size (int, optional): hidden size. Defaults to 0.
+            0 allows detect the parameter from graph automatically.
+        optimization_options (FusionOptions, optional): optimization options that turn on/off some fusions.
+            Defaults to None.
+        opt_level (int, optional): onnxruntime graph optimization level (0, 1, 2 or 99) or None. Defaults to None.
+            When the value is None, default value (1 for bert and gpt2, 0 for other model types) will be used.
+            When the level > 0, onnxruntime will be used to optimize model first.
+        use_gpu (bool, optional): use gpu or not for onnxruntime. Defaults to False.
+        only_onnxruntime (bool, optional): only use onnxruntime to optimize model, and no python fusion.
+            Defaults to False.
+        provider (str, optional): execution provider to use if use_gpu. Defaults to None.
+
+     Returns:
+        object of an optimizer class.
+    """
+    assert opt_level is None or opt_level in [0, 1, 2, 99]
+
+    if model_type not in MODEL_TYPES:
+        logger.warning(f"Unsupported model type: {model_type} for optimization, directly return model.")
+        return OnnxModel(load_model(input)) if isinstance(input, str) else OnnxModel(input)
+
+    (optimizer_class, _, default_opt_level) = MODEL_TYPES[model_type]
+
+    if opt_level is None:
+        opt_level = default_opt_level
+
+    # Disable constant sharing to avoid model proto str mismatch in test. Ideally the optimizer should not
+    # affect other fusions. We can update the expected model proto once the ConstantSharing optimizer logic becomes
+    # stable.
+    disabled_optimizers = ["ConstantSharing"]
+    temp_model_path = None
+    temp_dir = tempfile.TemporaryDirectory()
+    optimized_model_name = "model_o{}_{}.onnx".format(opt_level, "gpu" if use_gpu else "cpu")
+    optimized_model_path = os.path.join(temp_dir.name, optimized_model_name)
+
+    # Auto detect if input model has external data
+    has_external_data_file = False
+    original_model = load_model(input, load_external_data=False) if isinstance(input, str) else input
+    if has_external_data(original_model):
+        has_external_data_file = True
+    del original_model
+
+    if opt_level > 1:
+        # Disable some optimizers that might cause failure in symbolic shape inference or attention fusion.
+        disabled_optimizers += (
+            []
+            if only_onnxruntime
+            else [
+                "MatMulScaleFusion",
+                "MatMulAddFusion",
+                "MatmulTransposeFusion",
+                "GemmActivationFusion",
+                "BiasSoftmaxFusion",
+            ]
+        )
+        temp_model_path = optimize_by_onnxruntime(
+            input,
+            use_gpu=use_gpu,
+            provider=provider,
+            optimized_model_path=optimized_model_path,
+            opt_level=opt_level,
+            disabled_optimizers=disabled_optimizers,
+            verbose=verbose,
+            save_as_external_data=has_external_data_file,
+        )
+    elif opt_level == 1:
+        # basic optimizations (like constant folding and cast elimination) are not specified to execution provider.
+        # Note that use_gpu=False might cause extra Cast nodes for float16 model since most operators does not support float16 in CPU.
+        # Sometime, use_gpu=True might cause extra memory copy nodes when some operators are supported only in CPU.
+        # We might need remove GPU memory copy nodes as preprocess of optimize_by_fusion if they cause no matching in fusion.
+        temp_model_path = optimize_by_onnxruntime(
+            input,
+            use_gpu=use_gpu,
+            provider=provider,
+            optimized_model_path=optimized_model_path,
+            opt_level=1,
+            disabled_optimizers=disabled_optimizers,
+            verbose=verbose,
+            save_as_external_data=has_external_data_file,
+        )
+
+    if only_onnxruntime and not temp_model_path:
+        logger.warning("Please specify a positive value for opt_level when only_onnxruntime is True")
+
+    if temp_model_path is not None:
+        model = load_model(temp_model_path)
+    elif isinstance(input, str):
+        model = load_model(input)
+    else:
+        model = input
+
+    if only_onnxruntime:
+        optimizer = optimizer_class(model, num_heads, hidden_size)
+    else:
+        optimizer = optimize_by_fusion(model, model_type, num_heads, hidden_size, optimization_options)
+
+    # remove the temporary directory
+    temp_dir.cleanup()
+
+    return optimizer
+
+
+def get_fusion_statistics(optimized_model_path: str) -> dict[str, int]:
+    """
+    Get counter of fused operators in optimized model.
+
+    Args:
+        optimized_model_path (str): the path of onnx model.
+
+    Returns:
+        A dictionary with operator type as key, and count as value
+    """
+    model = load_model(optimized_model_path, format=None, load_external_data=True)
+    optimizer = BertOnnxModel(model)
+    return optimizer.get_fused_operator_statistics()
+
+
+def _parse_arguments():
+    parser = argparse.ArgumentParser(
+        description="Graph optimization tool for ONNX Runtime."
+        "It transforms ONNX graph to use optimized operators for Transformer models."
+    )
+    parser.add_argument("--input", required=True, type=str, help="input onnx model path")
+
+    parser.add_argument("--output", required=True, type=str, help="optimized onnx model path")
+
+    parser.add_argument(
+        "--model_type",
+        required=False,
+        type=str.lower,
+        default="bert",
+        choices=list(MODEL_TYPES.keys()),
+        help="Model type selected in the list: " + ", ".join(MODEL_TYPES.keys()),
+    )
+
+    parser.add_argument(
+        "--num_heads",
+        required=False,
+        type=int,
+        default=0,
+        help="number of attention heads like 12 for bert-base and 16 for bert-large. "
+        "Default is 0 to detect automatically for BERT."
+        "For other model type, this parameter need specify correctly.",
+    )
+
+    parser.add_argument(
+        "--hidden_size",
+        required=False,
+        type=int,
+        default=0,
+        help="hidden size like 768 for bert-base and 1024 for bert-large. "
+        "Default is 0 to detect automatically for BERT. "
+        "For other model type, this parameter need specify correctly.",
+    )
+
+    parser.add_argument(
+        "--input_int32",
+        required=False,
+        action="store_true",
+        help="Use int32 (instead of int64) inputs. "
+        "It could avoid unnecessary data cast when EmbedLayerNormalization is fused for BERT.",
+    )
+    parser.set_defaults(input_int32=False)
+
+    parser.add_argument(
+        "--float16",
+        required=False,
+        action="store_true",
+        help="Convert all weights and nodes in float32 to float16. "
+        "It has potential loss in precision compared to mixed precision conversion.",
+    )
+    parser.set_defaults(float16=False)
+
+    FusionOptions.add_arguments(parser)
+
+    parser.add_argument("--verbose", required=False, action="store_true", help="show debug information.")
+    parser.set_defaults(verbose=False)
+
+    parser.add_argument(
+        "--use_gpu",
+        required=False,
+        action="store_true",
+        help="Use GPU for inference. Set this flag if your model is intended for GPU when opt_level > 1.",
+    )
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        type=str,
+        default=None,
+        help="Execution provider to use if use_gpu",
+    )
+
+    parser.add_argument(
+        "--only_onnxruntime",
+        required=False,
+        action="store_true",
+        help="optimized by onnxruntime only, and no graph fusion in Python",
+    )
+    parser.set_defaults(only_onnxruntime=False)
+
+    parser.add_argument(
+        "--opt_level",
+        required=False,
+        type=int,
+        choices=[0, 1, 2, 3, 99],
+        default=None,
+        help="onnxruntime optimization level. 0 will disable onnxruntime graph optimization. "
+        "The recommended value is 1. When opt_level > 1 is used, optimized model for GPU might not run in CPU. "
+        "Level 2, Level 3 and 99 are intended for --only_onnxruntime.",
+    )
+
+    parser.add_argument(
+        "--use_external_data_format",
+        required=False,
+        action="store_true",
+        help="use external data format to store large model (>2GB)",
+    )
+    parser.set_defaults(use_external_data_format=False)
+
+    parser.add_argument(
+        "--disable_symbolic_shape_infer",
+        required=False,
+        action="store_true",
+        help="disable symbolic shape inference",
+    )
+    parser.set_defaults(disable_symbolic_shape_infer=False)
+
+    parser.add_argument(
+        "--convert_to_packing_mode",
+        required=False,
+        action="store_true",
+        help="convert the model to packing mode. Only available for BERT like model",
+    )
+    parser.set_defaults(convert_to_packing_mode=False)
+
+    parser.add_argument(
+        "--convert_attribute",
+        required=False,
+        action="store_true",
+        help="convert attributes when using a rewritten ONNX model (e.g. Dynamo-exported model from ONNX Script)",
+    )
+    parser.set_defaults(convert_attribute=False)
+
+    args = parser.parse_args()
+
+    return args
+
+
+def _setup_logger(verbose):
+    if verbose:
+        logging.basicConfig(
+            format="[%(filename)s:%(lineno)s - %(funcName)20s()] %(message)s", level=logging.DEBUG, force=True
+        )
+    else:
+        logging.basicConfig(format="%(funcName)20s: %(message)s", level=logging.INFO, force=True)
+
+
+def main():
+    args = _parse_arguments()
+
+    _setup_logger(args.verbose)
+
+    logger.debug(f"arguments:{args}")
+
+    if os.path.realpath(args.input) == os.path.realpath(args.output):
+        logger.warning("Specified the same input and output path. Note that this may overwrite the original model")
+
+    optimization_options = FusionOptions.parse(args)
+
+    optimizer = optimize_model(
+        args.input,
+        args.model_type,
+        args.num_heads,
+        args.hidden_size,
+        opt_level=args.opt_level,
+        optimization_options=optimization_options,
+        use_gpu=args.use_gpu,
+        provider=args.provider,
+        only_onnxruntime=args.only_onnxruntime,
+    )
+
+    if args.float16:
+        optimizer.convert_float_to_float16(keep_io_types=True)
+
+    if args.input_int32:
+        optimizer.change_graph_inputs_to_int32()
+
+    # Print the operator statistics might help end user.
+    optimizer.get_operator_statistics()
+
+    fused_op_count = optimizer.get_fused_operator_statistics()
+    if "bert" in args.model_type and optimizer.is_fully_optimized(fused_op_count):
+        logger.info("The model has been fully optimized.")
+    else:
+        logger.info("The model has been optimized.")
+
+    if args.convert_to_packing_mode:
+        if args.model_type == "bert":
+            optimizer.convert_to_packing_mode(not args.disable_symbolic_shape_infer)
+        else:
+            logger.warning("Packing mode only supports BERT like models")
+
+    optimizer.save_model_to_file(args.output, args.use_external_data_format, convert_attribute=args.convert_attribute)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/past_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/past_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..61d2f5db63a46dbffc2383abbb530c6060f974b6
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/past_helper.py
@@ -0,0 +1,149 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+
+import torch
+
+logger = logging.getLogger(__name__)
+
+
+class PastKeyValuesHelper:
+    """Helper functions to process past key values for encoder-decoder model"""
+
+    @staticmethod
+    def get_past_names(num_layers, present: bool = False):
+        past_self_names = []
+        past_cross_names = []
+        for i in range(num_layers):
+            past_self_names.extend(
+                [f"present_key_self_{i}", f"present_value_self_{i}"]
+                if present
+                else [f"past_key_self_{i}", f"past_value_self_{i}"]
+            )
+            past_cross_names.extend(
+                [f"present_key_cross_{i}", f"present_value_cross_{i}"]
+                if present
+                else [f"past_key_cross_{i}", f"past_value_cross_{i}"]
+            )
+        return past_self_names + past_cross_names
+
+    @staticmethod
+    def group_by_self_or_cross(present_key_values):
+        """Split present state from grouped by layer to grouped by self/cross attention.
+        Before: (past_key_self_0, past_value_self_0, past_key_cross_0, past_value_cross_0), (past_key_self_1, past_value_self_1, past_key_cross_1, past_value_cross_1), ...
+        After: (past_key_self_0, past_value_self_0, past_key_self_1, past_value_self_1, ...), (past_key_cross_0, past_value_cross_0, past_key_cross_1, past_value_cross_1, ...)
+
+        """
+        present_self = []
+        present_cross = []
+        for _i, present_layer_i in enumerate(present_key_values):
+            assert len(present_layer_i) == 4, f"Expected to have four items. Got {len(present_layer_i)}"
+            (
+                present_key_self,
+                present_value_self,
+                present_key_cross,
+                present_value_cross,
+            ) = present_layer_i
+            present_self.extend([present_key_self, present_value_self])
+            present_cross.extend([present_key_cross, present_value_cross])
+        return present_self, present_cross
+
+    @staticmethod
+    def group_by_layer(past, num_layers):
+        """Reorder past state from grouped by self/cross attention to grouped by layer.
+        Before: past_key_self_0, past_value_self_0, past_key_self_1, past_value_self_1, ..., past_key_cross_0, past_value_cross_0, past_key_cross_1, past_value_cross_1, ...
+        After: (past_key_self_0, past_value_self_0, past_key_cross_0, past_value_cross_0), (past_key_self_1, past_value_self_1, past_key_cross_1, past_value_cross_1),
+        """
+        assert len(past) == 4 * num_layers
+        return tuple(
+            [
+                past[2 * i],
+                past[2 * i + 1],
+                past[2 * num_layers + 2 * i],
+                past[2 * num_layers + 2 * i + 1],
+            ]
+            for i in range(num_layers)
+        )
+
+    @staticmethod
+    def back_group_by_layer(past_key_values: tuple[tuple[torch.Tensor]]):
+        """Categorize present_key_values from self and cross attention to layer by layer.
+
+        Reorder past state from grouped by self/cross attention to grouped by layer.
+        Before: past_key_self_0, past_value_self_0, past_key_self_1, past_value_self_1, ...,
+                past_key_cross_0, past_value_cross_0, past_key_cross_1, past_value_cross_1, ...
+        After: (past_key_self_0, past_value_self_0, past_key_cross_0, past_value_cross_0),
+                (past_key_self_1, past_value_self_1, past_key_cross_1, past_value_cross_1),
+
+        Args:
+            present_key_values: From past_key_values of a model (group by self and cross attention)
+
+        Returns:
+            past_tuples: present key and values grouped by layer.
+        """
+        past_tuples = ()
+        half_idx = len(past_key_values) // 2
+        for i in range(len(past_key_values) // 4):
+            idx = 2 * i
+            past_tuples += (
+                (
+                    past_key_values[idx],
+                    past_key_values[idx + 1],
+                    past_key_values[half_idx + idx],
+                    past_key_values[half_idx + idx + 1],
+                ),
+            )
+        return past_tuples
+
+    @staticmethod
+    def group_by_self_and_cross(present_key_values: tuple[torch.Tensor], concat: bool = False):
+        """Categorize present_key_values into self and cross attention.
+
+        Split present state from grouped by layer to grouped by self/cross attention.
+        Before: (past_key_self_0, past_value_self_0, past_key_cross_0, past_value_cross_0),
+                (past_key_self_1, past_value_self_1, past_key_cross_1, past_value_cross_1), ...
+        After: (past_key_self_0, past_value_self_0, past_key_self_1, past_value_self_1, ...),
+                (past_key_cross_0, past_value_cross_0, past_key_cross_1, past_value_cross_1, ...)
+
+        Args:
+            present_key_values: From past_key_values of a model (group by layer)
+            concat: If concat self attention with cross attention key/value to return
+
+        Returns:
+            present_self (Tuple[torch.Tensor]): present key and values from self attention
+            present_cross (Tuple[torch.Tensor]): present key and values from cross attention
+        """
+        present_self: list[torch.Tensor] = []
+        present_cross: list[torch.Tensor] = []
+        for _, present_layer_i in enumerate(present_key_values):
+            assert len(present_layer_i) == 4, f"Expected to have four items. Got {len(present_layer_i)}"
+            present_key_self, present_value_self, present_key_cross, present_value_cross = present_layer_i
+            present_self.extend([present_key_self, present_value_self])
+            present_cross.extend([present_key_cross, present_value_cross])
+        if concat:
+            return present_self + present_cross
+        else:
+            return present_self, present_cross
+
+    @staticmethod
+    def get_input_names(past_key_values: tuple[tuple[torch.Tensor]], encoder=True):
+        """Process input names of model wrapper.
+
+        Args:
+            past_key_values: Consider `self` and `cross` past_key_values
+
+        Returns:
+            names (List[string]): input names
+        """
+        names = []
+        num_layers = len(past_key_values) // 4 if encoder else len(past_key_values)
+        prefix = "past_" if not encoder else "present_"
+        for i in range(num_layers):
+            names.extend([prefix + s for s in [f"key_self_{i}", f"value_self_{i}"]])
+        for i in range(num_layers):
+            names.extend([prefix + s for s in [f"key_cross_{i}", f"value_cross_{i}"]])
+        return names
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/profile_result_processor.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/profile_result_processor.py
new file mode 100644
index 0000000000000000000000000000000000000000..d52f069f8fa7c34629c93cc347a1339d4c9fc611
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/profile_result_processor.py
@@ -0,0 +1,358 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+"""This profiler result processor print out the kernel time spent on each Node of the model.
+Example of importing profile result file from onnxruntime_perf_test:
+    python profile_result_processor.py --input profile_2021-10-25_12-02-41.json
+"""
+
+import argparse
+import json
+
+_NODES_TYPE_CONTAINING_SUBGRAPH = frozenset(("Scan", "Loop", "If"))
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-i",
+        "--input",
+        required=False,
+        type=str,
+        help="Set the input file for reading the profile results",
+    )
+
+    parser.add_argument(
+        "--threshold",
+        required=False,
+        type=float,
+        default=0.01,
+        help="Threshold of run time ratio among all nodes. Nodes with larger ratio will show in top expensive nodes.",
+    )
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        type=str,
+        default="cuda",
+        help="Execution provider to use",
+    )
+
+    parser.add_argument(
+        "--kernel_time_only",
+        required=False,
+        action="store_true",
+        help="Only include the kernel time and no fence time",
+    )
+
+    parser.set_defaults(kernel_time_only=False)
+
+    parser.add_argument("-v", "--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    return parser.parse_args(argv)
+
+
+def load_profile_json(profile_file):
+    print(f"loading profile output {profile_file} ...")
+
+    with open(profile_file) as opened_file:
+        sess_time = json.load(opened_file)
+
+    assert isinstance(sess_time, list)
+    return sess_time
+
+
+def parse_kernel_results(sess_time, threshold=0):
+    """Parse profile data and output nodes in two sections - nodes in the original order, and top expensive nodes.
+
+    Args:
+        sess_time (List[Dict]): profile data
+        threshold (int, optional): Minimum ratio of duration among all. Defaults to 0.
+
+    Returns:
+        List[str]: lines of string for output.
+    """
+    kernel_name_to_op_name = {}
+    kernel_time = {}
+    kernel_freq = {}
+    total = 0
+    session_init = False
+    for item in sess_time:
+        # Skip all MemcpyHostToDevice before session_initialization
+        if item["cat"] == "Session" and item["name"] == "session_initialization":
+            session_init = True
+        if not session_init:
+            continue
+
+        if item["cat"] == "Kernel" and "dur" in item and "args" in item and "op_name" in item["args"]:
+            kernel_name = item["name"]
+
+            op_name = item["args"]["op_name"]
+            if op_name in _NODES_TYPE_CONTAINING_SUBGRAPH:
+                continue
+
+            # Handle MemcpyHostToDevice and MemcpyDeviceToHost here
+            if not op_name:
+                op_name = f"({kernel_name})"
+
+            if kernel_name in kernel_time:
+                kernel_time[kernel_name] += item["dur"]
+                kernel_freq[kernel_name] += 1
+            else:
+                kernel_time[kernel_name] = item["dur"]
+                kernel_freq[kernel_name] = 1
+                kernel_name_to_op_name[kernel_name] = op_name
+
+            total += item["dur"]
+
+    if not kernel_time:
+        return ["No kernel record found!"]
+
+    # Output items with run time ratio > thresholds, and sorted by duration in the descending order.
+    lines = []
+    lines.append(f"\nTop expensive kernels with Time% >= {threshold * 100:.2f}:")
+    lines.append("-" * 64)
+    lines.append("Total(μs)\tTime%\tCalls\tAvg(μs)\tKernel")
+    for kernel_name, duration in sorted(kernel_time.items(), key=lambda x: x[1], reverse=True):
+        ratio = duration / total
+        if ratio < threshold:
+            continue
+
+        calls = kernel_freq[kernel_name]
+        avg_time = duration / float(calls)
+        lines.append(f"{duration:10d}\t{ratio * 100.0:5.2f}\t{calls:5d}\t{avg_time:8.1f}\t{kernel_name}")
+
+    # Group by operator
+    op_time = {}
+    for kernel_name, op_name in kernel_name_to_op_name.items():
+        duration = kernel_time[kernel_name]
+        if op_name in op_time:
+            op_time[op_name] += duration
+        else:
+            op_time[op_name] = duration
+
+    lines.append("\nGroup kernel time by operator:")
+    lines.append("-" * 64)
+    lines.append("Total(μs)\tTime%\tOperator")
+    for op_name, duration in sorted(op_time.items(), key=lambda x: x[1], reverse=True):
+        ratio = duration / total
+        lines.append(f"{duration:10d}\t{ratio * 100.0:5.2f}\t{op_name}")
+
+    return lines
+
+
+def parse_node_results(sess_time, kernel_time_only=False, threshold=0):
+    """Parse profile data and output nodes in two sections - nodes in the original order, and top expensive nodes.
+
+    Args:
+        sess_time (List[Dict]): profile data
+        kernel_time_only (bool, optional): Only include items for kernel time. Defaults to False.
+        threshold (int, optional): Minimum ratio of duration among all. Defaults to 0.
+
+    Returns:
+        List[str]: lines of string for output.
+    """
+    node_name_list = []
+    node_time = {}
+    node_freq = {}
+    node_provider = {}
+    total = 0
+    for item in sess_time:
+        if item["cat"] == "Node" and "dur" in item and "args" in item and "op_name" in item["args"]:
+            node_name = (
+                item["name"].replace("_kernel_time", "").replace("_fence_before", "").replace("_fence_after", "")
+            )
+
+            if "provider" in item["args"]:
+                if item["args"]["provider"] == "CPUExecutionProvider":
+                    device = "CPU"
+                elif item["args"]["provider"] == "CUDAExecutionProvider":
+                    device = "CUDA"
+                elif item["args"]["provider"] == "DmlExecutionProvider":
+                    device = "DML"
+
+                if node_name not in node_provider:
+                    node_provider[node_name] = device
+                else:
+                    assert node_provider[node_name] == device
+            elif kernel_time_only:
+                continue
+
+            op_name = item["args"]["op_name"]
+            if op_name in _NODES_TYPE_CONTAINING_SUBGRAPH:
+                continue
+
+            if node_name in node_time:
+                node_time[node_name] += item["dur"]
+                node_freq[node_name] += 1
+            else:
+                node_time[node_name] = item["dur"]
+                node_freq[node_name] = 1
+                node_name_list.append(node_name)
+
+            total += item["dur"]
+
+    # Output items in the original order.
+    lines = [
+        "\nNodes in the original order:",
+        "-" * 64,
+        "Total(μs)\tTime%\tAcc %\tAvg(μs)\tCalls\tProvider\tNode",
+    ]
+    before_percentage = 0.0
+    for node_name in node_name_list:
+        duration = node_time[node_name]
+        calls = node_freq[node_name]
+        avg_time = duration / float(calls)
+        percentage = (duration / total) * 100.0
+        provider = node_provider.get(node_name, "")
+        before_percentage += percentage
+        lines.append(
+            f"{duration:10d}\t{percentage:5.2f}\t{before_percentage:5.2f}\t{avg_time:8.1f}\t{calls:5d}\t{provider:8s}\t{node_name}"
+        )
+
+    # Output items with run time ratio > thresholds, and sorted by duration in the descending order.
+    lines.append(f"\nTop expensive nodes with Time% >= {threshold * 100:.2f}:")
+    lines.append("-" * 64)
+    lines.append("Total(μs)\tTime%\tAvg(μs)\tCalls\tProvider\tNode")
+    for node_name, duration in sorted(node_time.items(), key=lambda x: x[1], reverse=True):
+        ratio = duration / total
+        if ratio < threshold:
+            continue
+
+        calls = node_freq[node_name]
+        avg_time = duration / float(calls)
+        percentage = (duration / total) * 100.0
+        provider = node_provider.get(node_name, "")
+        lines.append(f"{duration:10d}\t{percentage:5.2f}\t{avg_time:8.1f}\t{calls:5d}\t{provider:8s}\t{node_name}")
+
+    return lines
+
+
+def group_node_results(sess_time):
+    """Group results by operator name.
+
+    Args:
+        sess_time (List[Dict]): profile data
+
+    Returns:
+        List[str]: lines of string for output.
+    """
+    op_kernel_time = {}
+    op_kernel_records = {}
+    total_kernel_time = 0
+
+    provider_op_kernel_time = {}
+    provider_op_kernel_records = {}
+    provider_kernel_time = {}
+
+    op_fence_time = {}
+    total_fence_time = 0
+
+    provider_counter = {}
+    for item in sess_time:
+        if item["cat"] == "Node" and "dur" in item and "args" in item and "op_name" in item["args"]:
+            op_name = item["args"]["op_name"]
+
+            # TODO: shall we have a separated group for nodes with subgraph?
+            if op_name in _NODES_TYPE_CONTAINING_SUBGRAPH:
+                continue
+
+            if "provider" not in item["args"]:
+                if "fence" in item["name"]:
+                    if op_name in op_fence_time:
+                        op_fence_time[op_name] += item["dur"]
+                    else:
+                        op_fence_time[op_name] = item["dur"]
+                    total_fence_time += item["dur"]
+                continue
+
+            provider = item["args"].get("provider", "")
+            if provider in provider_counter:
+                provider_counter[provider] += 1
+            else:
+                provider_counter[provider] = 1
+
+            key = f"{provider}:{op_name}"
+            if key in provider_op_kernel_time:
+                provider_op_kernel_time[key] += item["dur"]
+                provider_op_kernel_records[key] += 1
+            else:
+                provider_op_kernel_time[key] = item["dur"]
+                provider_op_kernel_records[key] = 1
+
+            if provider in provider_kernel_time:
+                provider_kernel_time[provider] += item["dur"]
+            else:
+                provider_kernel_time[provider] = item["dur"]
+
+            if op_name in op_kernel_time:
+                op_kernel_time[op_name] += item["dur"]
+                op_kernel_records[op_name] += 1
+            else:
+                op_kernel_time[op_name] = item["dur"]
+                op_kernel_records[op_name] = 1
+
+            total_kernel_time += item["dur"]
+
+    lines = ["", "Grouped by operator"]
+    lines.append("-" * 64)
+    lines.append("Total(μs)\tTime%\tKernel(μs)\tKernel%\tCalls\tAvgKernel(μs)\tFence(μs)\tOperator")
+    for op_name, kernel_time in sorted(op_kernel_time.items(), key=lambda x: x[1], reverse=True):
+        fence_time = op_fence_time.get(op_name, 0)
+        kernel_time_ratio = kernel_time / total_kernel_time
+        total_time = kernel_time + fence_time
+        time_ratio = total_time / (total_kernel_time + total_fence_time)
+        kernel_calls = op_kernel_records[op_name]
+        avg_kernel_time = kernel_time / kernel_calls
+        lines.append(
+            f"{total_time:10d}\t{time_ratio * 100.0:5.2f}\t{kernel_time:11d}\t{kernel_time_ratio * 100.0:5.2f}\t{kernel_calls:5d}\t{avg_kernel_time:14.1f}\t{fence_time:10d}\t{op_name}"
+        )
+
+    lines += ["", "Grouped by provider + operator"]
+    lines.append("-" * 64)
+    lines.append("Kernel(μs)\tProvider%\tCalls\tAvgKernel(μs)\tProvider\tOperator")
+    for key, kernel_time in sorted(provider_op_kernel_time.items(), key=lambda x: x[1], reverse=True):
+        parts = key.split(":")
+        provider = parts[0]
+        op_name = parts[1]
+        short_ep = provider.replace("ExecutionProvider", "")
+        calls = provider_op_kernel_records[key]
+        avg_kernel_time = kernel_time / calls
+        provider_time_ratio = kernel_time / provider_kernel_time[provider]
+        lines.append(
+            f"{kernel_time:10d}\t{provider_time_ratio * 100.0:9.2f}\t{calls:5d}\t{avg_kernel_time:14.1f}\t{short_ep:8s}\t{op_name}"
+        )
+
+    return lines
+
+
+def process_results(profile_file, args):
+    profile_records = load_profile_json(profile_file)
+
+    lines = parse_kernel_results(profile_records, args.threshold)
+
+    lines += parse_node_results(profile_records, args.kernel_time_only, args.threshold)
+
+    lines += group_node_results(profile_records)
+
+    return lines
+
+
+if __name__ == "__main__":
+    arguments = parse_arguments()
+    print("Arguments", arguments)
+
+    from benchmark_helper import setup_logger
+
+    setup_logger(arguments.verbose)
+
+    profile_file = arguments.input
+
+    results = process_results(profile_file, arguments)
+
+    for line in results:
+        print(line)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/profiler.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/profiler.py
new file mode 100644
index 0000000000000000000000000000000000000000..7079f0b004ba844fab30ae13b410e481479a8d46
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/profiler.py
@@ -0,0 +1,434 @@
+import argparse
+import os
+
+import numpy
+import psutil
+from onnx import TensorProto
+
+"""
+This profiler tool could run a transformer model and print out the kernel time spent on each Node of the model.
+Example of profiling of longformer model:
+    python profiler.py --model longformer-base-4096_fp32.onnx --batch_size 1 --sequence_length 4096 --global_length 8 --samples 1000 --thread_num 8 --dummy_inputs longformer --use_gpu
+Example of importing profile result file from onnxruntime_perf_test:
+    python profiler.py --input profile_2021-10-25_12-02-41.json
+"""
+
+
+def parse_arguments(argv=None):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "-i",
+        "--input",
+        required=False,
+        type=str,
+        help="Set the input file for reading the profile results",
+    )
+
+    parser.add_argument(
+        "-m",
+        "--model",
+        required=False,
+        type=str,
+        help="onnx model path to run profiling. Required when --input is not specified.",
+    )
+
+    parser.add_argument(
+        "-b",
+        "--batch_size",
+        required=False,
+        type=int,
+        default=1,
+        help="batch size of input",
+    )
+
+    parser.add_argument(
+        "-s",
+        "--sequence_length",
+        required=False,
+        type=int,
+        default=32,
+        help="sequence length of input",
+    )
+
+    parser.add_argument(
+        "--past_sequence_length",
+        required=False,
+        type=int,
+        default=1,
+        help="past sequence length for gpt2",
+    )
+
+    parser.add_argument(
+        "--global_length",
+        required=False,
+        type=int,
+        default=1,
+        help="number of global tokens for longformer",
+    )
+
+    parser.add_argument(
+        "--samples",
+        required=False,
+        type=int,
+        default=1000,
+        help="number of samples to test. Set it large enough to reduce the variance of performance result.",
+    )
+
+    parser.add_argument(
+        "--threshold",
+        required=False,
+        type=float,
+        default=0.01,
+        help="Threshold of run time ratio among all nodes. Nodes with larger ratio will show in top expensive nodes.",
+    )
+
+    parser.add_argument(
+        "--thread_num",
+        required=False,
+        type=int,
+        default=-1,
+        help="number of threads to use",
+    )
+
+    parser.add_argument(
+        "--input_ids_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for input IDs, for bert",
+    )
+    parser.add_argument(
+        "--segment_ids_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for segment IDs, for bert",
+    )
+    parser.add_argument(
+        "--input_mask_name",
+        required=False,
+        type=str,
+        default=None,
+        help="input name for attention mask, for bert",
+    )
+
+    parser.add_argument(
+        "--dummy_inputs",
+        required=False,
+        default="default",
+        choices=["bert", "gpt2", "longformer", "default"],
+        help="Type of model inputs. The default will create dummy inputs with ones.",
+    )
+
+    parser.add_argument("-g", "--use_gpu", required=False, action="store_true", help="use GPU")
+    parser.set_defaults(use_gpu=False)
+
+    parser.add_argument(
+        "--provider",
+        required=False,
+        type=str,
+        default="cuda",
+        help="Execution provider to use",
+    )
+
+    parser.add_argument(
+        "--basic_optimization",
+        required=False,
+        action="store_true",
+        help="Enable only basic graph optimizations. By default, all optimizations are enabled in OnnxRuntime",
+    )
+    parser.set_defaults(basic_optimization=False)
+
+    parser.add_argument(
+        "--kernel_time_only",
+        required=False,
+        action="store_true",
+        help="Only include the kernel time and no fence time",
+    )
+    parser.set_defaults(kernel_time_only=False)
+
+    parser.add_argument("-v", "--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+
+    return parser.parse_args(argv)
+
+
+def run_profile(onnx_model_path, use_gpu, provider, basic_optimization, thread_num, all_inputs):
+    from benchmark_helper import create_onnxruntime_session  # noqa: PLC0415
+
+    session = create_onnxruntime_session(
+        onnx_model_path,
+        use_gpu,
+        provider,
+        enable_all_optimization=not basic_optimization,
+        num_threads=thread_num,
+        enable_profiling=True,
+    )
+
+    for inputs in all_inputs:
+        _ = session.run(None, inputs)
+
+    profile_file = session.end_profiling()
+    return profile_file
+
+
+def get_dim_from_type_proto(dim):
+    return getattr(dim, dim.WhichOneof("value")) if type(dim.WhichOneof("value")) == str else None  # noqa: E721
+
+
+def get_shape_from_type_proto(type_proto):
+    return [get_dim_from_type_proto(d) for d in type_proto.tensor_type.shape.dim]
+
+
+def create_dummy_inputs(onnx_model, batch_size, sequence_length, samples):
+    """Create dummy inputs for ONNX model.
+
+    Args:
+        onnx_model (OnnxModel): ONNX model
+        batch_size (int): batch size
+        sequence_length (int): sequence length
+        samples (int): number of samples
+
+    Returns:
+        List[Dict]: list of inputs
+    """
+    dummy_inputs = {}
+    for graph_input in onnx_model.get_graph_inputs_excluding_initializers():
+        shape = get_shape_from_type_proto(graph_input.type)
+        symbol_dims = []
+        for i, dim in enumerate(shape):
+            if isinstance(dim, str):
+                symbol_dims.append(i)
+
+        # allowed symbolic dimensions: batch_size and sequence_length
+        if len(symbol_dims) > 2:
+            return None
+        if len(symbol_dims) > 0:
+            shape[symbol_dims[0]] = batch_size
+        if len(symbol_dims) > 1:
+            shape[symbol_dims[1]] = sequence_length
+
+        elem_type = graph_input.type.tensor_type.elem_type
+        assert elem_type in [TensorProto.FLOAT, TensorProto.INT32, TensorProto.INT64]
+        data_type = (
+            numpy.float32
+            if elem_type == TensorProto.FLOAT
+            else (numpy.int64 if elem_type == TensorProto.INT64 else numpy.int32)
+        )
+        data = numpy.ones(shape, dtype=data_type)
+        dummy_inputs[graph_input.name] = data
+
+    all_inputs = [dummy_inputs for _ in range(samples)]
+    return all_inputs
+
+
+def create_bert_inputs(
+    onnx_model,
+    batch_size,
+    sequence_length,
+    samples,
+    input_ids_name=None,
+    segment_ids_name=None,
+    input_mask_name=None,
+):
+    """Create dummy inputs for BERT model.
+
+    Args:
+        onnx_model (OnnxModel): ONNX model
+        batch_size (int): batch size
+        sequence_length (int): sequence length
+        samples (int): number of samples
+        input_ids_name (str, optional): Name of graph input for input IDs. Defaults to None.
+        segment_ids_name (str, optional): Name of graph input for segment IDs. Defaults to None.
+        input_mask_name (str, optional): Name of graph input for attention mask. Defaults to None.
+
+    Returns:
+        List[Dict]: list of inputs
+    """
+    from bert_test_data import find_bert_inputs, generate_test_data  # noqa: PLC0415
+
+    input_ids, segment_ids, input_mask = find_bert_inputs(onnx_model, input_ids_name, segment_ids_name, input_mask_name)
+    all_inputs = generate_test_data(
+        batch_size,
+        sequence_length,
+        test_cases=samples,
+        seed=123,
+        verbose=False,
+        input_ids=input_ids,
+        segment_ids=segment_ids,
+        input_mask=input_mask,
+        random_mask_length=False,
+    )
+
+    return all_inputs
+
+
+def create_gpt2_inputs(onnx_model, batch_size, sequence_length, past_sequence_length, samples):
+    """Create dummy inputs for GPT-2 model.
+
+    Args:
+        onnx_model (OnnxModel): ONNX model
+        batch_size (int): batch size
+        sequence_length (int): sequence length
+        past_sequence_length (int): past sequence length
+        samples (int): number of samples
+
+    Raises:
+        RuntimeError: symbolic is not supported. Use the tool convert_to_onnx.py to export ONNX model instead.
+
+    Returns:
+        List[Dict]: list of inputs
+    """
+    # The symbolic names shall be same as those used in Gpt2Helper.export_onnx(...) function.
+    symbols = {
+        "batch_size": batch_size,
+        "seq_len": sequence_length,
+        "past_seq_len": past_sequence_length,
+        "total_seq_len": sequence_length + past_sequence_length,
+    }
+
+    dummy_inputs = {}
+    for graph_input in onnx_model.get_graph_inputs_excluding_initializers():
+        shape = get_shape_from_type_proto(graph_input.type)
+        for i, dim in enumerate(shape):
+            if isinstance(dim, str):
+                if dim not in symbols:
+                    raise RuntimeError(f"symbol is not supported: {dim}")
+                else:
+                    shape[i] = symbols[dim]
+
+        elem_type = graph_input.type.tensor_type.elem_type
+        assert elem_type in [TensorProto.FLOAT, TensorProto.INT32, TensorProto.INT64]
+        data_type = (
+            numpy.float32
+            if elem_type == TensorProto.FLOAT
+            else (numpy.int64 if elem_type == TensorProto.INT64 else numpy.int32)
+        )
+        data = numpy.ones(shape, dtype=data_type)
+        dummy_inputs[graph_input.name] = data
+
+    all_inputs = [dummy_inputs for _ in range(samples)]
+    return all_inputs
+
+
+def create_longformer_inputs(onnx_model, batch_size, sequence_length, global_length, samples):
+    """Create dummy inputs for Longformer model.
+
+    Args:
+        onnx_model (OnnxModel): ONNX model
+        batch_size (int): batch size
+        sequence_length (int): sequence length
+        global_length (int): number of global tokens
+        samples (int): number of samples
+
+    Raises:
+        RuntimeError: symbolic is not supported. Use the tool convert_longformer_to_onnx.py to export ONNX model instead.
+
+    Returns:
+        List[Dict]: list of inputs
+    """
+    symbols = {"batch_size": batch_size, "sequence_length": sequence_length}
+
+    dummy_inputs = {}
+    for graph_input in onnx_model.get_graph_inputs_excluding_initializers():
+        shape = get_shape_from_type_proto(graph_input.type)
+        for i, dim in enumerate(shape):
+            if isinstance(dim, str):
+                if dim not in symbols:
+                    raise RuntimeError(f"symbol is not supported: {dim}")
+                else:
+                    shape[i] = symbols[dim]
+
+        elem_type = graph_input.type.tensor_type.elem_type
+        assert elem_type in [TensorProto.FLOAT, TensorProto.INT32, TensorProto.INT64]
+        data_type = (
+            numpy.float32
+            if elem_type == TensorProto.FLOAT
+            else (numpy.int64 if elem_type == TensorProto.INT64 else numpy.int32)
+        )
+
+        if "global" in graph_input.name:
+            data = numpy.zeros(shape, dtype=data_type)
+            data[:, :global_length] = 1
+        else:
+            data = numpy.ones(shape, dtype=data_type)
+        dummy_inputs[graph_input.name] = data
+
+    all_inputs = [dummy_inputs for _ in range(samples)]
+    return all_inputs
+
+
+def run(args):
+    num_threads = args.thread_num if args.thread_num > 0 else psutil.cpu_count(logical=False)
+
+    # Set OMP environment variable before importing onnxruntime. Needed for cpu only, and no impact for onnxruntime-gpu package.
+    if "OMP_NUM_THREADS" not in os.environ:
+        os.environ["OMP_NUM_THREADS"] = str(num_threads)
+
+    from onnx import load  # noqa: PLC0415
+    from onnx_model import OnnxModel  # noqa: PLC0415
+
+    onnx_model = OnnxModel(load(args.model))
+
+    all_inputs = None
+    if args.dummy_inputs == "bert":
+        all_inputs = create_bert_inputs(
+            onnx_model,
+            args.batch_size,
+            args.sequence_length,
+            args.samples,
+            args.input_ids_name,
+            args.segment_ids_name,
+            args.input_mask_name,
+        )
+    elif args.dummy_inputs == "gpt2":
+        all_inputs = create_gpt2_inputs(
+            onnx_model,
+            args.batch_size,
+            args.sequence_length,
+            args.past_sequence_length,
+            args.samples,
+        )
+    elif args.dummy_inputs == "longformer":
+        all_inputs = create_longformer_inputs(
+            onnx_model,
+            args.batch_size,
+            args.sequence_length,
+            args.global_length,
+            args.samples,
+        )
+    else:  # default
+        all_inputs = create_dummy_inputs(onnx_model, args.batch_size, args.sequence_length, args.samples)
+
+    profile_file = run_profile(
+        args.model,
+        args.use_gpu,
+        args.provider,
+        args.basic_optimization,
+        args.thread_num,
+        all_inputs,
+    )
+
+    return profile_file
+
+
+if __name__ == "__main__":
+    arguments = parse_arguments()
+    print("Arguments", arguments)
+
+    from benchmark_helper import setup_logger
+
+    setup_logger(arguments.verbose)
+
+    if not arguments.input:
+        assert arguments.model, "requires either --model to run profiling or --input to read profiling results"
+        profile_file = run(arguments)
+    else:
+        profile_file = arguments.input
+    from profile_result_processor import process_results
+
+    results = process_results(profile_file, arguments)
+
+    for line in results:
+        print(line)
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/quantize_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/quantize_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..a77018acec8922964e7ecf32615a5db7bfac7990
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/quantize_helper.py
@@ -0,0 +1,76 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.  See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+
+import onnx
+import torch
+from transformers.modeling_utils import Conv1D
+
+logger = logging.getLogger(__name__)
+
+
+def _conv1d_to_linear(module):
+    in_size, out_size = module.weight.shape
+    linear = torch.nn.Linear(in_size, out_size)
+    linear.weight.data = module.weight.data.T.contiguous()
+    linear.bias.data = module.bias.data
+    return linear
+
+
+def conv1d_to_linear(model):
+    """in-place
+    This is for Dynamic Quantization, as Conv1D is not recognized by PyTorch, convert it to nn.Linear
+    """
+    logger.debug("replace Conv1D with Linear")
+    for name in list(model._modules):
+        module = model._modules[name]
+        if isinstance(module, Conv1D):
+            linear = _conv1d_to_linear(module)
+            model._modules[name] = linear
+        else:
+            conv1d_to_linear(module)
+
+
+def _get_size_of_pytorch_model(model):
+    torch.save(model.state_dict(), "temp.p")
+    size = os.path.getsize("temp.p") / (1024 * 1024)
+    os.remove("temp.p")
+    return size
+
+
+class QuantizeHelper:
+    @staticmethod
+    def quantize_torch_model(model, dtype=torch.qint8):
+        """
+        Usage: model = quantize_model(model)
+
+        TODO: mix of in-place and return, but results are different
+        """
+        conv1d_to_linear(model)
+        quantized_model = torch.quantization.quantize_dynamic(model, {torch.nn.Linear}, dtype=dtype)
+        logger.info(f"Size of full precision Torch model(MB):{_get_size_of_pytorch_model(model)}")
+        logger.info(f"Size of quantized Torch model(MB):{_get_size_of_pytorch_model(quantized_model)}")
+        return quantized_model
+
+    @staticmethod
+    def quantize_onnx_model(onnx_model_path, quantized_model_path, use_external_data_format=False):
+        from pathlib import Path  # noqa: PLC0415
+
+        from onnxruntime.quantization import quantize_dynamic  # noqa: PLC0415
+
+        Path(quantized_model_path).parent.mkdir(parents=True, exist_ok=True)
+        logger.info(f"Size of full precision ONNX model(MB):{os.path.getsize(onnx_model_path) / (1024 * 1024)}")
+        quantize_dynamic(
+            onnx_model_path,
+            quantized_model_path,
+            use_external_data_format=use_external_data_format,
+            extra_options={"DefaultTensorType": onnx.TensorProto.FLOAT},
+        )
+        logger.info(f"quantized model saved to:{quantized_model_path}")
+        # TODO: inlcude external data in total model size.
+        logger.info(f"Size of quantized ONNX model(MB):{os.path.getsize(quantized_model_path) / (1024 * 1024)}")
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_infer_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_infer_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..6643d8b26dab40bd6dd0fec80a113df10ed7e303
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_infer_helper.py
@@ -0,0 +1,121 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import logging
+import os
+import sys
+
+# In ORT Package the symbolic_shape_infer.py is in ../tools
+file_path = os.path.dirname(__file__)
+if os.path.exists(os.path.join(file_path, "../tools/symbolic_shape_infer.py")):
+    sys.path.append(os.path.join(file_path, "../tools"))
+else:
+    sys.path.append(os.path.join(file_path, ".."))
+
+from symbolic_shape_infer import SymbolicShapeInference, get_shape_from_type_proto, sympy  # noqa: E402
+
+logger = logging.getLogger(__name__)
+
+
+class SymbolicShapeInferenceHelper(SymbolicShapeInference):
+    def __init__(self, model, verbose=0, int_max=2**31 - 1, auto_merge=True, guess_output_rank=False):
+        super().__init__(int_max, auto_merge, guess_output_rank, verbose)
+        self.model_ = model
+        self.all_shapes_inferred_: bool = False
+        self.is_inferred_: bool = False
+        self.dynamic_axis_mapping_: dict[str, int] = {}
+
+    def infer(self, dynamic_axis_mapping: dict[str, int], max_runs: int = 200):
+        """Run shape inference, and try replace dynamic axis from string to integer when mapping is provided.
+
+        Args:
+            dynamic_axis_mapping (_type_): a dictionary with name of dynamic axis as key, like {"batch_size" : 4}
+            max_runs (int, optional): limit maximum number of runs to avoid infinite loop. Defaults to 200.
+
+        Returns:
+            bool: whether all shapes has been inferred or not.
+        """
+        assert dynamic_axis_mapping is not None
+
+        if self.is_inferred_ and self.dynamic_axis_mapping_ == dynamic_axis_mapping:
+            return self.all_shapes_inferred_
+
+        self.dynamic_axis_mapping_ = dynamic_axis_mapping
+
+        self._preprocess(self.model_)
+
+        count = 0
+        while self.run_:
+            logger.debug(f"shape infer run {count}")
+            self.all_shapes_inferred_ = self._infer_impl()
+            count += 1
+            if max_runs > 0 and count >= max_runs:
+                break
+
+        self.is_inferred_ = True
+        return self.all_shapes_inferred_
+
+    def _get_sympy_shape(self, node, idx):
+        """Override it to ensure shape inference by giving the actual value of dynamic axis."""
+        sympy_shape = []
+
+        shape = self._get_shape(node, idx)
+        if shape:
+            for dim in shape:
+                if isinstance(dim, str):
+                    if dim in self.dynamic_axis_mapping_:
+                        sympy_shape.append(self.dynamic_axis_mapping_[dim])
+                    elif dim in self.symbolic_dims_:
+                        sympy_shape.append(self.symbolic_dims_[dim])
+                    else:
+                        sympy_shape.append(sympy.Symbol(dim, integer=True))
+                else:
+                    assert dim is not None
+                    sympy_shape.append(dim)
+        return sympy_shape
+
+    def get_edge_shape(self, edge):
+        """Get shape of an edge.
+
+        Args:
+            edge (str): name of edge
+
+        Returns:
+            Optional[List[int]]: the shape, or None if shape is unknown
+        """
+        assert self.all_shapes_inferred_
+        if edge not in self.known_vi_:
+            print("Cannot retrieve the shape of " + str(edge))
+            return None
+
+        type_proto = self.known_vi_[edge].type
+        shape = get_shape_from_type_proto(type_proto)
+
+        if shape is not None:
+            for i, dim in enumerate(shape):
+                if isinstance(dim, str) and dim in self.dynamic_axis_mapping_:
+                    shape[i] = self.dynamic_axis_mapping_[dim]
+
+        return shape
+
+    def compare_shape(self, edge, edge_other):
+        """Compare shape of two edges.
+
+        Args:
+            edge (str): name of edge
+            edge_other (str): name of another edge
+
+        Raises:
+            Exception: At least one shape is missed for edges to compare
+
+        Returns:
+            bool: whether the shape is same or not
+        """
+        assert self.all_shapes_inferred_
+        shape = self.get_edge_shape(edge)
+        shape_other = self.get_edge_shape(edge_other)
+        if shape is None or shape_other is None:
+            raise Exception("At least one shape is missed for edges to compare")
+        return shape == shape_other
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_optimizer.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_optimizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3c4db68d31c874861a3422b04140d9d7e1b9cd5
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/shape_optimizer.py
@@ -0,0 +1,400 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+# This tool is not used directly in bert optimization. It could assist developing the optimization script on the following scenarios:
+# (1) It could simplify graph by removing many sub-graphs related to reshape.
+# (2) It could reduce extra inputs and outputs to fit other tools. The script compare_bert_results.py or bert_perf_test.py requires 3 inputs.
+
+import argparse
+import logging
+import os
+import re  # noqa: F401
+import sys
+import tempfile
+from collections import deque  # noqa: F401
+from datetime import datetime
+from pathlib import Path  # noqa: F401
+
+import numpy as np
+import onnx
+from onnx import ModelProto, TensorProto, numpy_helper
+from onnx_model import OnnxModel
+
+import onnxruntime
+
+logger = logging.getLogger(__name__)
+
+CONSTANT_SHAPE_NAME_PREFIX = "constant_shape_opt__"
+RESHAPE_INPUT_SHAPE_PREFIX = "reshape_input_shape__"
+
+
+class BertOnnxModelShapeOptimizer(OnnxModel):
+    """
+    This optimizer will replace Shape output or the shape input of Reshape node by initializer. Currently, it requires
+    model inputs to have static shape.
+    """
+
+    def __init__(self, onnx_model):
+        super().__init__(onnx_model.model)
+
+    def add_shape_initializer(self, shape):
+        """
+        Add an initializer for constant shape.
+        """
+        shape_value = np.asarray(shape, dtype=np.int64)
+        constant_shape_name = self.create_node_name("Constant", CONSTANT_SHAPE_NAME_PREFIX)
+        tensor = onnx.helper.make_tensor(
+            name=constant_shape_name,
+            data_type=TensorProto.INT64,
+            dims=shape_value.shape,
+            vals=shape_value,
+        )
+        self.add_initializer(tensor)
+        return tensor
+
+    def get_shape_outputs(self):
+        """
+        Returns a list of output names of all Shape nodes.
+        """
+        input_name_to_nodes = self.input_name_to_nodes()
+
+        outputs = []
+        for node in self.model.graph.node:
+            if node.op_type == "Shape":
+                if node.output[0] in input_name_to_nodes:
+                    outputs.append(node.output[0])
+
+        return outputs
+
+    def get_reshape_shape_inputs(self):
+        """
+        Returns a list of shape input names of Reshape nodes.
+        """
+        self.output_name_to_node()
+
+        shape_inputs = []
+        for node in self.model.graph.node:
+            if node.op_type == "Reshape":
+                shape_inputs.append(node.input[1])
+
+        return shape_inputs
+
+    def add_shape_for_reshape_input(self):
+        """
+        For each Reshape node, create a Shape node for its first input.
+        Returns the output names of these Shape nodes.
+        """
+        output_names = []
+        nodes_to_add = []
+        for node in self.model.graph.node:
+            if node.op_type == "Reshape":
+                input = node.input[0]
+                output_name = self.create_node_name("Reshape_Input", RESHAPE_INPUT_SHAPE_PREFIX)
+                shape_node = onnx.helper.make_node("Shape", inputs=[input], outputs=[output_name])
+                nodes_to_add.append(shape_node)
+                output_names.append(output_name)
+
+        self.add_nodes(nodes_to_add)
+        return output_names
+
+    def add_extra_graph_output(self, extra_outputs):
+        """
+        Add a list of output names to graph output.
+        """
+        names_to_evaluate = []
+        output_names = [output.name for output in self.model.graph.output]
+        for name in extra_outputs:
+            if self.get_initializer(name) is not None:  # already a constant
+                continue
+            names_to_evaluate.append(name)
+
+            if name not in output_names:
+                output_info = onnx.helper.ValueInfoProto()
+                output_info.name = name
+                self.model.graph.output.extend([output_info])
+                output_names.append(name)
+
+        return names_to_evaluate
+
+    # Update input and output shape to be static
+    def use_static_input(self, inputs, batch_size=1, max_seq_len=128):
+        """
+        Update the model to use static axes instead of dynamic axes for graph inputs.
+        """
+        for input in self.model.graph.input:
+            if input.name in inputs:
+                dim_proto = input.type.tensor_type.shape.dim[0]
+                dim_proto.dim_value = batch_size
+                dim_proto = input.type.tensor_type.shape.dim[1]
+                if dim_proto.HasField("dim_param"):
+                    dim_proto.dim_value = max_seq_len
+                elif dim_proto.HasField("dim_value") and dim_proto.dim_value != max_seq_len:
+                    raise ValueError(
+                        f"Unable to set dimension value to {max_seq_len} for axis {1} of {input.name}. Contradicts existing dimension value {dim_proto.dim_value}."
+                    )
+
+    def create_dummy_inputs(
+        self,
+        input_ids,
+        segment_ids,
+        input_mask,
+        batch_size,
+        sequence_length,
+        elem_type,
+        dictionary_size=8,
+    ):
+        """
+        Create dummy data for model inputs. If the model has more than 3 inputs, please update this function accordingly before running the tool.
+        """
+        assert elem_type in [1, 6, 7]  # only int32, int64 and float32 are supported.
+
+        # Create dummy inputs
+        input_1 = np.random.randint(dictionary_size, size=(batch_size, sequence_length), dtype=np.int32)
+        input_2 = np.ones((batch_size, sequence_length), dtype=np.int32)
+        input_3 = np.zeros((batch_size, sequence_length), dtype=np.int32)
+
+        # Here we assume that 3 inputs have same data type
+        if elem_type == 1:  # float32
+            input_1 = np.float32(input_1)
+            input_2 = np.float32(input_2)
+            input_3 = np.float32(input_3)
+        elif elem_type == 7:  # int64
+            input_1 = np.int64(input_1)
+            input_2 = np.int64(input_2)
+            input_3 = np.int64(input_3)
+
+        inputs = {input_ids: input_1, input_mask: input_2, segment_ids: input_3}
+        return inputs
+
+    def shape_optimization(
+        self,
+        temp_model_path,
+        input_ids,
+        segment_ids,
+        input_mask,
+        output_names,
+        batch_size,
+        sequence_length,
+        enable_shape_opt,
+        enable_reshape_opt,
+        verbose,
+    ):
+        self.bert_inputs = [input_ids, segment_ids, input_mask]
+
+        extra_outputs = []
+        if enable_shape_opt:
+            extra_outputs.extend(self.get_shape_outputs())
+
+        if enable_reshape_opt:
+            reshape_shape_inputs = self.get_reshape_shape_inputs()
+            reshape_input_shapes = self.add_shape_for_reshape_input()
+            extra_outputs.extend(reshape_shape_inputs)
+            extra_outputs.extend(reshape_input_shapes)
+
+        if len(extra_outputs) == 0:
+            return
+
+        names_to_evaluate = self.add_extra_graph_output(extra_outputs)
+
+        # This tool does not support dynamic axes right now.
+        self.use_static_input(self.bert_inputs, batch_size, sequence_length)
+
+        with open(temp_model_path, "wb") as out:
+            out.write(self.model.SerializeToString())
+        sess_options = onnxruntime.SessionOptions()
+        sess_options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_DISABLE_ALL
+        session = onnxruntime.InferenceSession(
+            temp_model_path,
+            sess_options,
+            providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
+        )
+
+        elem_type = 7
+        for input in self.model.graph.input:
+            if input.name == input_ids:
+                elem_type = input.type.tensor_type.elem_type
+        inputs = self.create_dummy_inputs(input_ids, segment_ids, input_mask, batch_size, sequence_length, elem_type)
+
+        outputs = session.run(names_to_evaluate, inputs)
+        shapes = {}
+        for i, name in enumerate(names_to_evaluate):
+            shapes[name] = outputs[i]
+
+        logger.debug(f"shapes={shapes}")
+
+        if enable_reshape_opt:
+            for i, shape_input in enumerate(reshape_shape_inputs):
+                input_shape = reshape_input_shapes[i]
+                self.update_target_shape(shapes, shape_input, input_shape, verbose)
+
+        for name, shape in shapes.items():
+            tensor = self.add_shape_initializer(shape)
+            self.replace_input_of_all_nodes(name, tensor.name)
+
+        # Remove extra outputs, and prune all nodes not linked to output.
+        self.prune_graph(output_names)
+
+    def update_target_shape(self, shapes, shape_input, input_shape, verbose):
+        """
+        Update the target shape to use 0 to represent that dimension value does not change.
+        For example, shape of source data is (2, 5, 8) and target shape is (2, 5, 4, 2), the target shape will be updated to (0, 0, 4, 2).
+        """
+        if shape_input in shapes:
+            target_shape = shapes[shape_input]
+        else:
+            initializer = self.get_initializer(shape_input)
+            assert initializer is not None
+            target_shape = numpy_helper.to_array(initializer)
+
+        if input_shape in shapes:
+            source_shape = shapes[input_shape]
+        else:
+            initializer = self.get_initializer(input_shape)
+            assert initializer is not None
+            source_shape = numpy_helper.to_array(initializer)
+
+        new_target_shape = []
+        for i, dim_value in enumerate(target_shape):
+            if i < len(source_shape) and source_shape[i] == dim_value:
+                new_target_shape.append(0)
+            else:
+                new_target_shape.append(dim_value)
+        shapes[shape_input] = new_target_shape
+
+        logger.debug(f"source_shape={source_shape}, target_shape={target_shape}, new_target_shape={new_target_shape}")
+
+    def validate_input(self, input: str):
+        if not self.find_graph_input(input):
+            valid_names = [input.name for input in self.model.graph.input]
+            raise Exception(f"Input {input} does not exist in the graph inputs: {valid_names}")
+
+    def validate_outputs(self, output_names: list[str]):
+        valid_names = [output.name for output in self.model.graph.output]
+        for name in output_names:
+            if name not in valid_names:
+                raise Exception(f"Output {name} does not exist in the graph outputs: {valid_names}")
+
+    def optimize(
+        self,
+        output_path: str,
+        input_ids: str,
+        segment_ids: str,
+        input_mask: str,
+        enable_shape_opt: bool,
+        enable_reshape_opt: bool,
+        output_names: list[str] | None = None,
+        batch_size=1,
+        sequence_length=128,
+        verbose=False,
+    ):
+        # Skip if shape optimization has been done before.
+        for tensor in self.model.graph.initializer:
+            if tensor.name.startswith(CONSTANT_SHAPE_NAME_PREFIX):
+                logger.info("Skip shape optimization since it has been done before")
+                return
+
+        self.validate_input(input_ids)
+        self.validate_input(segment_ids)
+        self.validate_input(input_mask)
+
+        if output_names is not None:
+            self.validate_outputs(output_names)
+            self.prune_graph(output_names)
+
+        remaining_outputs = [output.name for output in self.model.graph.output]
+
+        if enable_shape_opt or enable_reshape_opt:
+            if len(self.get_graph_inputs_excluding_initializers()) != 3:
+                logger.info("Skip shape optimization since graph input number is not 3")
+                return
+
+            with tempfile.TemporaryDirectory() as temp_dir:
+                temp_file_name = "temp_{}.onnx".format(datetime.now().strftime("%m_%d-%H_%M_%S"))
+                dir = "." if verbose else temp_dir
+                temp_file = os.path.join(dir, temp_file_name)
+                self.shape_optimization(
+                    temp_file,
+                    input_ids,
+                    segment_ids,
+                    input_mask,
+                    remaining_outputs,
+                    batch_size,
+                    sequence_length,
+                    enable_shape_opt,
+                    enable_reshape_opt,
+                    verbose,
+                )
+            logger.debug(f"Temp model with additional outputs: {temp_file}")
+            logger.warning(
+                f"Shape optimization is done. The optimized model might only work for input with batch_size={batch_size} sequence_length={sequence_length}"
+            )
+
+        if output_path is not None:
+            with open(output_path, "wb") as out:
+                out.write(self.model.SerializeToString())
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--input", required=True, type=str)
+    parser.add_argument("--output", required=True, type=str)
+    parser.add_argument("--input_ids", required=True, type=str)
+    parser.add_argument("--segment_ids", required=True, type=str)
+    parser.add_argument("--input_mask", required=True, type=str)
+    parser.add_argument("--output_names", required=False, type=str, default=None)
+    parser.add_argument("--batch_size", required=False, type=int, default=1)
+    parser.add_argument("--sequence_length", required=False, type=int, default=128)
+    parser.add_argument("--enable_shape_opt", required=False, action="store_true")
+    parser.set_defaults(enable_shape_opt=False)
+    parser.add_argument("--enable_reshape_opt", required=False, action="store_true")
+    parser.set_defaults(enable_reshape_opt=False)
+    parser.add_argument("--verbose", required=False, action="store_true")
+    parser.set_defaults(verbose=False)
+    args = parser.parse_args()
+    return args
+
+
+def setup_logging(verbose):
+    log_handler = logging.StreamHandler(sys.stdout)
+    if verbose:
+        log_handler.setFormatter(logging.Formatter("[%(filename)s:%(lineno)s - %(funcName)20s()] %(message)s"))
+        logging_level = logging.DEBUG
+    else:
+        log_handler.setFormatter(logging.Formatter("%(filename)20s: %(message)s"))
+        logging_level = logging.INFO
+    log_handler.setLevel(logging_level)
+    logger.addHandler(log_handler)
+    logger.setLevel(logging_level)
+
+
+def main():
+    args = parse_arguments()
+    setup_logging(args.verbose)
+
+    output_names = None if args.output_names is None else args.output_names.split(";")
+
+    model = ModelProto()
+    with open(args.input, "rb") as input_file:
+        model.ParseFromString(input_file.read())
+    onnx_model = OnnxModel(model)
+
+    optimizer = BertOnnxModelShapeOptimizer(onnx_model)
+
+    optimizer.optimize(
+        args.output,
+        args.input_ids,
+        args.segment_ids,
+        args.input_mask,
+        args.enable_shape_opt,
+        args.enable_reshape_opt,
+        output_names,
+        args.batch_size,
+        args.sequence_length,
+        args.verbose,
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/python/user_packages/Python313/site-packages/onnxruntime/transformers/torch_onnx_export_helper.py b/python/user_packages/Python313/site-packages/onnxruntime/transformers/torch_onnx_export_helper.py
new file mode 100644
index 0000000000000000000000000000000000000000..f79bab72bfbf98e2fe081f7ca295aa8db70b345a
--- /dev/null
+++ b/python/user_packages/Python313/site-packages/onnxruntime/transformers/torch_onnx_export_helper.py
@@ -0,0 +1,75 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation.  All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------------------
+
+import torch
+from torch._C._onnx import OperatorExportTypes
+
+TrainingMode = torch.onnx.TrainingMode
+from packaging.version import Version  # noqa: E402
+
+
+def torch_onnx_export(
+    model,
+    args,
+    f,
+    export_params=True,
+    verbose=False,
+    training=TrainingMode.EVAL,
+    input_names=None,
+    output_names=None,
+    operator_export_type=OperatorExportTypes.ONNX,
+    opset_version=None,
+    _retain_param_name=None,
+    do_constant_folding=True,
+    example_outputs=None,
+    strip_doc_string=None,
+    dynamic_axes=None,
+    keep_initializers_as_inputs=None,
+    custom_opsets=None,
+    enable_onnx_checker=None,
+    use_external_data_format=None,
+    export_modules_as_functions=False,
+):
+    if Version(torch.__version__) >= Version("1.11.0"):
+        torch.onnx.export(
+            model=model,
+            args=args,
+            f=f,
+            export_params=export_params,
+            verbose=verbose,
+            training=training,
+            input_names=input_names,
+            output_names=output_names,
+            operator_export_type=operator_export_type,
+            opset_version=opset_version,
+            do_constant_folding=do_constant_folding,
+            dynamic_axes=dynamic_axes,
+            keep_initializers_as_inputs=keep_initializers_as_inputs,
+            custom_opsets=custom_opsets,
+            export_modules_as_functions=export_modules_as_functions,
+            dynamo=False,
+        )
+    else:
+        torch.onnx.export(
+            model=model,
+            args=args,
+            f=f,
+            export_params=export_params,
+            verbose=verbose,
+            training=training,
+            input_names=input_names,
+            output_names=output_names,
+            operator_export_type=operator_export_type,
+            opset_version=opset_version,
+            _retain_param_name=_retain_param_name,
+            do_constant_folding=do_constant_folding,
+            example_outputs=example_outputs,
+            strip_doc_string=strip_doc_string,
+            dynamic_axes=dynamic_axes,
+            keep_initializers_as_inputs=keep_initializers_as_inputs,
+            custom_opsets=custom_opsets,
+            enable_onnx_checker=enable_onnx_checker,
+            use_external_data_format=use_external_data_format,
+        )
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgets.lib b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgets.lib
new file mode 100644
index 0000000000000000000000000000000000000000..37c1dbd9958f378394d907824370fa17ed53e83a
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diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgets.prl b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgets.prl
new file mode 100644
index 0000000000000000000000000000000000000000..9f01d3c1d76bc760774167d66fe243be48a72bcb
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgets.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6SvgWidgets.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgetsd.lib b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgetsd.lib
new file mode 100644
index 0000000000000000000000000000000000000000..4c96f2eb53876d495c465ac2e0d42fd55a9d6011
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diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgetsd.prl b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgetsd.prl
new file mode 100644
index 0000000000000000000000000000000000000000..530199db13b3dbb7ba5742b19455214c07710c8c
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6SvgWidgetsd.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6SvgWidgetsd.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Test.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Test.prl
new file mode 100644
index 0000000000000000000000000000000000000000..3ab00c855ad0369561980af0219e96b6731e5331
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Test.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Test.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Testd.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Testd.prl
new file mode 100644
index 0000000000000000000000000000000000000000..21af849277970d5825dc952c5d870dd0b93d081e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Testd.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Testd.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6UiTools.lib b/qt/6.8.1/msvc2022_64/lib/Qt6UiTools.lib
new file mode 100644
index 0000000000000000000000000000000000000000..85abcfb918bd910d54361af9c6c287a25864e227
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diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6UiTools.prl b/qt/6.8.1/msvc2022_64/lib/Qt6UiTools.prl
new file mode 100644
index 0000000000000000000000000000000000000000..8c0caca33fee5bcf8448f1dfcb79c74a6bbe83e4
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6UiTools.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6UiTools.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.lib b/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.lib
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index 0000000000000000000000000000000000000000..d1cf9ccb9876b694864650e46e6c2abe69883d6d
Binary files /dev/null and b/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.lib differ
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.prl b/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.prl
new file mode 100644
index 0000000000000000000000000000000000000000..51875300c831a10636d514d78d4149e6225ea796
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6UiToolsd.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6UiToolsd.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Widgets.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Widgets.prl
new file mode 100644
index 0000000000000000000000000000000000000000..59483e6e67b041260e4c28762366a9de7875fcc5
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Widgets.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Widgets.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Widgetsd.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Widgetsd.prl
new file mode 100644
index 0000000000000000000000000000000000000000..f0a18a08460ab4a825ccb8bff4c22bf30212ec4b
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Widgetsd.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Widgetsd.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Xml.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Xml.prl
new file mode 100644
index 0000000000000000000000000000000000000000..2eea82ff6f18784a1745137079d912bfca88566e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Xml.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Xml.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/lib/Qt6Xmld.prl b/qt/6.8.1/msvc2022_64/lib/Qt6Xmld.prl
new file mode 100644
index 0000000000000000000000000000000000000000..43c7e5c1c29a8b3e6f926c5fb0cf8bd3f5d86d95
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/lib/Qt6Xmld.prl
@@ -0,0 +1,3 @@
+QMAKE_PRL_TARGET = Qt6Xmld.lib
+QMAKE_PRL_CONFIG = shared
+QMAKE_PRL_VERSION = 6.8.1
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6concurrent_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6concurrent_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6concurrent_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6core_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6core_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..fe50f5e9329ef68f9aeb91325f253811a7f70a50
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6core_metatypes.json
@@ -0,0 +1,9418 @@
+[
+    {
+        "classes": [
+            {
+                "className": "Qt",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "GlobalColor",
+                        "values": [
+                            "color0",
+                            "color1",
+                            "black",
+                            "white",
+                            "darkGray",
+                            "gray",
+                            "lightGray",
+                            "red",
+                            "green",
+                            "blue",
+                            "cyan",
+                            "magenta",
+                            "yellow",
+                            "darkRed",
+                            "darkGreen",
+                            "darkBlue",
+                            "darkCyan",
+                            "darkMagenta",
+                            "darkYellow",
+                            "transparent"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ColorScheme",
+                        "values": [
+                            "Unknown",
+                            "Light",
+                            "Dark"
+                        ]
+                    },
+                    {
+                        "alias": "MouseButton",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "MouseButtons",
+                        "values": [
+                            "NoButton",
+                            "LeftButton",
+                            "RightButton",
+                            "MiddleButton",
+                            "BackButton",
+                            "XButton1",
+                            "ExtraButton1",
+                            "ForwardButton",
+                            "XButton2",
+                            "ExtraButton2",
+                            "TaskButton",
+                            "ExtraButton3",
+                            "ExtraButton4",
+                            "ExtraButton5",
+                            "ExtraButton6",
+                            "ExtraButton7",
+                            "ExtraButton8",
+                            "ExtraButton9",
+                            "ExtraButton10",
+                            "ExtraButton11",
+                            "ExtraButton12",
+                            "ExtraButton13",
+                            "ExtraButton14",
+                            "ExtraButton15",
+                            "ExtraButton16",
+                            "ExtraButton17",
+                            "ExtraButton18",
+                            "ExtraButton19",
+                            "ExtraButton20",
+                            "ExtraButton21",
+                            "ExtraButton22",
+                            "ExtraButton23",
+                            "ExtraButton24",
+                            "AllButtons",
+                            "MaxMouseButton",
+                            "MouseButtonMask"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Orientation",
+                        "values": [
+                            "Horizontal",
+                            "Vertical"
+                        ]
+                    },
+                    {
+                        "alias": "Orientation",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Orientations",
+                        "values": [
+                            "Horizontal",
+                            "Vertical"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FocusPolicy",
+                        "values": [
+                            "NoFocus",
+                            "TabFocus",
+                            "ClickFocus",
+                            "StrongFocus",
+                            "WheelFocus"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TabFocusBehavior",
+                        "values": [
+                            "NoTabFocus",
+                            "TabFocusTextControls",
+                            "TabFocusListControls",
+                            "TabFocusAllControls"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SortOrder",
+                        "values": [
+                            "AscendingOrder",
+                            "DescendingOrder"
+                        ]
+                    },
+                    {
+                        "alias": "SplitBehaviorFlags",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "SplitBehavior",
+                        "values": [
+                            "KeepEmptyParts",
+                            "SkipEmptyParts"
+                        ]
+                    },
+                    {
+                        "alias": "AlignmentFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Alignment",
+                        "values": [
+                            "AlignLeft",
+                            "AlignLeading",
+                            "AlignRight",
+                            "AlignTrailing",
+                            "AlignHCenter",
+                            "AlignJustify",
+                            "AlignAbsolute",
+                            "AlignHorizontal_Mask",
+                            "AlignTop",
+                            "AlignBottom",
+                            "AlignVCenter",
+                            "AlignBaseline",
+                            "AlignVertical_Mask",
+                            "AlignCenter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextFlag",
+                        "values": [
+                            "TextSingleLine",
+                            "TextDontClip",
+                            "TextExpandTabs",
+                            "TextShowMnemonic",
+                            "TextWordWrap",
+                            "TextWrapAnywhere",
+                            "TextDontPrint",
+                            "TextIncludeTrailingSpaces",
+                            "TextHideMnemonic",
+                            "TextJustificationForced",
+                            "TextForceLeftToRight",
+                            "TextForceRightToLeft",
+                            "TextLongestVariant"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextElideMode",
+                        "values": [
+                            "ElideLeft",
+                            "ElideRight",
+                            "ElideMiddle",
+                            "ElideNone"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WindowType",
+                        "values": [
+                            "Widget",
+                            "Window",
+                            "Dialog",
+                            "Sheet",
+                            "Drawer",
+                            "Popup",
+                            "Tool",
+                            "ToolTip",
+                            "SplashScreen",
+                            "Desktop",
+                            "SubWindow",
+                            "ForeignWindow",
+                            "CoverWindow",
+                            "WindowType_Mask",
+                            "MSWindowsFixedSizeDialogHint",
+                            "MSWindowsOwnDC",
+                            "BypassWindowManagerHint",
+                            "X11BypassWindowManagerHint",
+                            "FramelessWindowHint",
+                            "WindowTitleHint",
+                            "WindowSystemMenuHint",
+                            "WindowMinimizeButtonHint",
+                            "WindowMaximizeButtonHint",
+                            "WindowMinMaxButtonsHint",
+                            "WindowContextHelpButtonHint",
+                            "WindowShadeButtonHint",
+                            "WindowStaysOnTopHint",
+                            "WindowTransparentForInput",
+                            "WindowOverridesSystemGestures",
+                            "WindowDoesNotAcceptFocus",
+                            "MaximizeUsingFullscreenGeometryHint",
+                            "CustomizeWindowHint",
+                            "WindowStaysOnBottomHint",
+                            "WindowCloseButtonHint",
+                            "MacWindowToolBarButtonHint",
+                            "BypassGraphicsProxyWidget",
+                            "NoDropShadowWindowHint",
+                            "WindowFullscreenButtonHint"
+                        ]
+                    },
+                    {
+                        "alias": "WindowType",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "WindowFlags",
+                        "values": [
+                            "Widget",
+                            "Window",
+                            "Dialog",
+                            "Sheet",
+                            "Drawer",
+                            "Popup",
+                            "Tool",
+                            "ToolTip",
+                            "SplashScreen",
+                            "Desktop",
+                            "SubWindow",
+                            "ForeignWindow",
+                            "CoverWindow",
+                            "WindowType_Mask",
+                            "MSWindowsFixedSizeDialogHint",
+                            "MSWindowsOwnDC",
+                            "BypassWindowManagerHint",
+                            "X11BypassWindowManagerHint",
+                            "FramelessWindowHint",
+                            "WindowTitleHint",
+                            "WindowSystemMenuHint",
+                            "WindowMinimizeButtonHint",
+                            "WindowMaximizeButtonHint",
+                            "WindowMinMaxButtonsHint",
+                            "WindowContextHelpButtonHint",
+                            "WindowShadeButtonHint",
+                            "WindowStaysOnTopHint",
+                            "WindowTransparentForInput",
+                            "WindowOverridesSystemGestures",
+                            "WindowDoesNotAcceptFocus",
+                            "MaximizeUsingFullscreenGeometryHint",
+                            "CustomizeWindowHint",
+                            "WindowStaysOnBottomHint",
+                            "WindowCloseButtonHint",
+                            "MacWindowToolBarButtonHint",
+                            "BypassGraphicsProxyWidget",
+                            "NoDropShadowWindowHint",
+                            "WindowFullscreenButtonHint"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WindowState",
+                        "values": [
+                            "WindowNoState",
+                            "WindowMinimized",
+                            "WindowMaximized",
+                            "WindowFullScreen",
+                            "WindowActive"
+                        ]
+                    },
+                    {
+                        "alias": "WindowState",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "WindowStates",
+                        "values": [
+                            "WindowNoState",
+                            "WindowMinimized",
+                            "WindowMaximized",
+                            "WindowFullScreen",
+                            "WindowActive"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ApplicationState",
+                        "values": [
+                            "ApplicationSuspended",
+                            "ApplicationHidden",
+                            "ApplicationInactive",
+                            "ApplicationActive"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ScreenOrientation",
+                        "values": [
+                            "PrimaryOrientation",
+                            "PortraitOrientation",
+                            "LandscapeOrientation",
+                            "InvertedPortraitOrientation",
+                            "InvertedLandscapeOrientation"
+                        ]
+                    },
+                    {
+                        "alias": "ScreenOrientation",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ScreenOrientations",
+                        "values": [
+                            "PrimaryOrientation",
+                            "PortraitOrientation",
+                            "LandscapeOrientation",
+                            "InvertedPortraitOrientation",
+                            "InvertedLandscapeOrientation"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WidgetAttribute",
+                        "values": [
+                            "WA_Disabled",
+                            "WA_UnderMouse",
+                            "WA_MouseTracking",
+                            "WA_OpaquePaintEvent",
+                            "WA_StaticContents",
+                            "WA_LaidOut",
+                            "WA_PaintOnScreen",
+                            "WA_NoSystemBackground",
+                            "WA_UpdatesDisabled",
+                            "WA_Mapped",
+                            "WA_InputMethodEnabled",
+                            "WA_WState_Visible",
+                            "WA_WState_Hidden",
+                            "WA_ForceDisabled",
+                            "WA_KeyCompression",
+                            "WA_PendingMoveEvent",
+                            "WA_PendingResizeEvent",
+                            "WA_SetPalette",
+                            "WA_SetFont",
+                            "WA_SetCursor",
+                            "WA_NoChildEventsFromChildren",
+                            "WA_WindowModified",
+                            "WA_Resized",
+                            "WA_Moved",
+                            "WA_PendingUpdate",
+                            "WA_InvalidSize",
+                            "WA_CustomWhatsThis",
+                            "WA_LayoutOnEntireRect",
+                            "WA_OutsideWSRange",
+                            "WA_GrabbedShortcut",
+                            "WA_TransparentForMouseEvents",
+                            "WA_PaintUnclipped",
+                            "WA_SetWindowIcon",
+                            "WA_NoMouseReplay",
+                            "WA_DeleteOnClose",
+                            "WA_RightToLeft",
+                            "WA_SetLayoutDirection",
+                            "WA_NoChildEventsForParent",
+                            "WA_ForceUpdatesDisabled",
+                            "WA_WState_Created",
+                            "WA_WState_CompressKeys",
+                            "WA_WState_InPaintEvent",
+                            "WA_WState_Reparented",
+                            "WA_WState_ConfigPending",
+                            "WA_WState_Polished",
+                            "WA_WState_OwnSizePolicy",
+                            "WA_WState_ExplicitShowHide",
+                            "WA_ShowModal",
+                            "WA_MouseNoMask",
+                            "WA_NoMousePropagation",
+                            "WA_Hover",
+                            "WA_InputMethodTransparent",
+                            "WA_QuitOnClose",
+                            "WA_KeyboardFocusChange",
+                            "WA_AcceptDrops",
+                            "WA_DropSiteRegistered",
+                            "WA_WindowPropagation",
+                            "WA_NoX11EventCompression",
+                            "WA_TintedBackground",
+                            "WA_X11OpenGLOverlay",
+                            "WA_AlwaysShowToolTips",
+                            "WA_MacOpaqueSizeGrip",
+                            "WA_SetStyle",
+                            "WA_SetLocale",
+                            "WA_MacShowFocusRect",
+                            "WA_MacNormalSize",
+                            "WA_MacSmallSize",
+                            "WA_MacMiniSize",
+                            "WA_LayoutUsesWidgetRect",
+                            "WA_StyledBackground",
+                            "WA_CanHostQMdiSubWindowTitleBar",
+                            "WA_MacAlwaysShowToolWindow",
+                            "WA_StyleSheet",
+                            "WA_ShowWithoutActivating",
+                            "WA_X11BypassTransientForHint",
+                            "WA_NativeWindow",
+                            "WA_DontCreateNativeAncestors",
+                            "WA_DontShowOnScreen",
+                            "WA_X11NetWmWindowTypeDesktop",
+                            "WA_X11NetWmWindowTypeDock",
+                            "WA_X11NetWmWindowTypeToolBar",
+                            "WA_X11NetWmWindowTypeMenu",
+                            "WA_X11NetWmWindowTypeUtility",
+                            "WA_X11NetWmWindowTypeSplash",
+                            "WA_X11NetWmWindowTypeDialog",
+                            "WA_X11NetWmWindowTypeDropDownMenu",
+                            "WA_X11NetWmWindowTypePopupMenu",
+                            "WA_X11NetWmWindowTypeToolTip",
+                            "WA_X11NetWmWindowTypeNotification",
+                            "WA_X11NetWmWindowTypeCombo",
+                            "WA_X11NetWmWindowTypeDND",
+                            "WA_SetWindowModality",
+                            "WA_WState_WindowOpacitySet",
+                            "WA_TranslucentBackground",
+                            "WA_AcceptTouchEvents",
+                            "WA_WState_AcceptedTouchBeginEvent",
+                            "WA_TouchPadAcceptSingleTouchEvents",
+                            "WA_X11DoNotAcceptFocus",
+                            "WA_AlwaysStackOnTop",
+                            "WA_TabletTracking",
+                            "WA_ContentsMarginsRespectsSafeArea",
+                            "WA_StyleSheetTarget",
+                            "WA_AttributeCount"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ApplicationAttribute",
+                        "values": [
+                            "AA_QtQuickUseDefaultSizePolicy",
+                            "AA_DontShowIconsInMenus",
+                            "AA_NativeWindows",
+                            "AA_DontCreateNativeWidgetSiblings",
+                            "AA_PluginApplication",
+                            "AA_DontUseNativeMenuBar",
+                            "AA_MacDontSwapCtrlAndMeta",
+                            "AA_Use96Dpi",
+                            "AA_DisableNativeVirtualKeyboard",
+                            "AA_DontUseNativeMenuWindows",
+                            "AA_SynthesizeTouchForUnhandledMouseEvents",
+                            "AA_SynthesizeMouseForUnhandledTouchEvents",
+                            "AA_UseHighDpiPixmaps",
+                            "AA_ForceRasterWidgets",
+                            "AA_UseDesktopOpenGL",
+                            "AA_UseOpenGLES",
+                            "AA_UseSoftwareOpenGL",
+                            "AA_ShareOpenGLContexts",
+                            "AA_SetPalette",
+                            "AA_EnableHighDpiScaling",
+                            "AA_DisableHighDpiScaling",
+                            "AA_UseStyleSheetPropagationInWidgetStyles",
+                            "AA_DontUseNativeDialogs",
+                            "AA_SynthesizeMouseForUnhandledTabletEvents",
+                            "AA_CompressHighFrequencyEvents",
+                            "AA_DontCheckOpenGLContextThreadAffinity",
+                            "AA_DisableShaderDiskCache",
+                            "AA_DontShowShortcutsInContextMenus",
+                            "AA_CompressTabletEvents",
+                            "AA_DisableSessionManager",
+                            "AA_AttributeCount"
+                        ]
+                    },
+                    {
+                        "alias": "ImageConversionFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ImageConversionFlags",
+                        "values": [
+                            "ColorMode_Mask",
+                            "AutoColor",
+                            "ColorOnly",
+                            "MonoOnly",
+                            "AlphaDither_Mask",
+                            "ThresholdAlphaDither",
+                            "OrderedAlphaDither",
+                            "DiffuseAlphaDither",
+                            "NoAlpha",
+                            "Dither_Mask",
+                            "DiffuseDither",
+                            "OrderedDither",
+                            "ThresholdDither",
+                            "DitherMode_Mask",
+                            "AutoDither",
+                            "PreferDither",
+                            "AvoidDither",
+                            "NoOpaqueDetection",
+                            "NoFormatConversion"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BGMode",
+                        "values": [
+                            "TransparentMode",
+                            "OpaqueMode"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Key",
+                        "values": [
+                            "Key_Space",
+                            "Key_Any",
+                            "Key_Exclam",
+                            "Key_QuoteDbl",
+                            "Key_NumberSign",
+                            "Key_Dollar",
+                            "Key_Percent",
+                            "Key_Ampersand",
+                            "Key_Apostrophe",
+                            "Key_ParenLeft",
+                            "Key_ParenRight",
+                            "Key_Asterisk",
+                            "Key_Plus",
+                            "Key_Comma",
+                            "Key_Minus",
+                            "Key_Period",
+                            "Key_Slash",
+                            "Key_0",
+                            "Key_1",
+                            "Key_2",
+                            "Key_3",
+                            "Key_4",
+                            "Key_5",
+                            "Key_6",
+                            "Key_7",
+                            "Key_8",
+                            "Key_9",
+                            "Key_Colon",
+                            "Key_Semicolon",
+                            "Key_Less",
+                            "Key_Equal",
+                            "Key_Greater",
+                            "Key_Question",
+                            "Key_At",
+                            "Key_A",
+                            "Key_B",
+                            "Key_C",
+                            "Key_D",
+                            "Key_E",
+                            "Key_F",
+                            "Key_G",
+                            "Key_H",
+                            "Key_I",
+                            "Key_J",
+                            "Key_K",
+                            "Key_L",
+                            "Key_M",
+                            "Key_N",
+                            "Key_O",
+                            "Key_P",
+                            "Key_Q",
+                            "Key_R",
+                            "Key_S",
+                            "Key_T",
+                            "Key_U",
+                            "Key_V",
+                            "Key_W",
+                            "Key_X",
+                            "Key_Y",
+                            "Key_Z",
+                            "Key_BracketLeft",
+                            "Key_Backslash",
+                            "Key_BracketRight",
+                            "Key_AsciiCircum",
+                            "Key_Underscore",
+                            "Key_QuoteLeft",
+                            "Key_BraceLeft",
+                            "Key_Bar",
+                            "Key_BraceRight",
+                            "Key_AsciiTilde",
+                            "Key_nobreakspace",
+                            "Key_exclamdown",
+                            "Key_cent",
+                            "Key_sterling",
+                            "Key_currency",
+                            "Key_yen",
+                            "Key_brokenbar",
+                            "Key_section",
+                            "Key_diaeresis",
+                            "Key_copyright",
+                            "Key_ordfeminine",
+                            "Key_guillemotleft",
+                            "Key_notsign",
+                            "Key_hyphen",
+                            "Key_registered",
+                            "Key_macron",
+                            "Key_degree",
+                            "Key_plusminus",
+                            "Key_twosuperior",
+                            "Key_threesuperior",
+                            "Key_acute",
+                            "Key_micro",
+                            "Key_mu",
+                            "Key_paragraph",
+                            "Key_periodcentered",
+                            "Key_cedilla",
+                            "Key_onesuperior",
+                            "Key_masculine",
+                            "Key_guillemotright",
+                            "Key_onequarter",
+                            "Key_onehalf",
+                            "Key_threequarters",
+                            "Key_questiondown",
+                            "Key_Agrave",
+                            "Key_Aacute",
+                            "Key_Acircumflex",
+                            "Key_Atilde",
+                            "Key_Adiaeresis",
+                            "Key_Aring",
+                            "Key_AE",
+                            "Key_Ccedilla",
+                            "Key_Egrave",
+                            "Key_Eacute",
+                            "Key_Ecircumflex",
+                            "Key_Ediaeresis",
+                            "Key_Igrave",
+                            "Key_Iacute",
+                            "Key_Icircumflex",
+                            "Key_Idiaeresis",
+                            "Key_ETH",
+                            "Key_Ntilde",
+                            "Key_Ograve",
+                            "Key_Oacute",
+                            "Key_Ocircumflex",
+                            "Key_Otilde",
+                            "Key_Odiaeresis",
+                            "Key_multiply",
+                            "Key_Ooblique",
+                            "Key_Ugrave",
+                            "Key_Uacute",
+                            "Key_Ucircumflex",
+                            "Key_Udiaeresis",
+                            "Key_Yacute",
+                            "Key_THORN",
+                            "Key_ssharp",
+                            "Key_division",
+                            "Key_ydiaeresis",
+                            "Key_Escape",
+                            "Key_Tab",
+                            "Key_Backtab",
+                            "Key_Backspace",
+                            "Key_Return",
+                            "Key_Enter",
+                            "Key_Insert",
+                            "Key_Delete",
+                            "Key_Pause",
+                            "Key_Print",
+                            "Key_SysReq",
+                            "Key_Clear",
+                            "Key_Home",
+                            "Key_End",
+                            "Key_Left",
+                            "Key_Up",
+                            "Key_Right",
+                            "Key_Down",
+                            "Key_PageUp",
+                            "Key_PageDown",
+                            "Key_Shift",
+                            "Key_Control",
+                            "Key_Meta",
+                            "Key_Alt",
+                            "Key_CapsLock",
+                            "Key_NumLock",
+                            "Key_ScrollLock",
+                            "Key_F1",
+                            "Key_F2",
+                            "Key_F3",
+                            "Key_F4",
+                            "Key_F5",
+                            "Key_F6",
+                            "Key_F7",
+                            "Key_F8",
+                            "Key_F9",
+                            "Key_F10",
+                            "Key_F11",
+                            "Key_F12",
+                            "Key_F13",
+                            "Key_F14",
+                            "Key_F15",
+                            "Key_F16",
+                            "Key_F17",
+                            "Key_F18",
+                            "Key_F19",
+                            "Key_F20",
+                            "Key_F21",
+                            "Key_F22",
+                            "Key_F23",
+                            "Key_F24",
+                            "Key_F25",
+                            "Key_F26",
+                            "Key_F27",
+                            "Key_F28",
+                            "Key_F29",
+                            "Key_F30",
+                            "Key_F31",
+                            "Key_F32",
+                            "Key_F33",
+                            "Key_F34",
+                            "Key_F35",
+                            "Key_Super_L",
+                            "Key_Super_R",
+                            "Key_Menu",
+                            "Key_Hyper_L",
+                            "Key_Hyper_R",
+                            "Key_Help",
+                            "Key_Direction_L",
+                            "Key_Direction_R",
+                            "Key_AltGr",
+                            "Key_Multi_key",
+                            "Key_Codeinput",
+                            "Key_SingleCandidate",
+                            "Key_MultipleCandidate",
+                            "Key_PreviousCandidate",
+                            "Key_Mode_switch",
+                            "Key_Kanji",
+                            "Key_Muhenkan",
+                            "Key_Henkan",
+                            "Key_Romaji",
+                            "Key_Hiragana",
+                            "Key_Katakana",
+                            "Key_Hiragana_Katakana",
+                            "Key_Zenkaku",
+                            "Key_Hankaku",
+                            "Key_Zenkaku_Hankaku",
+                            "Key_Touroku",
+                            "Key_Massyo",
+                            "Key_Kana_Lock",
+                            "Key_Kana_Shift",
+                            "Key_Eisu_Shift",
+                            "Key_Eisu_toggle",
+                            "Key_Hangul",
+                            "Key_Hangul_Start",
+                            "Key_Hangul_End",
+                            "Key_Hangul_Hanja",
+                            "Key_Hangul_Jamo",
+                            "Key_Hangul_Romaja",
+                            "Key_Hangul_Jeonja",
+                            "Key_Hangul_Banja",
+                            "Key_Hangul_PreHanja",
+                            "Key_Hangul_PostHanja",
+                            "Key_Hangul_Special",
+                            "Key_Dead_Grave",
+                            "Key_Dead_Acute",
+                            "Key_Dead_Circumflex",
+                            "Key_Dead_Tilde",
+                            "Key_Dead_Macron",
+                            "Key_Dead_Breve",
+                            "Key_Dead_Abovedot",
+                            "Key_Dead_Diaeresis",
+                            "Key_Dead_Abovering",
+                            "Key_Dead_Doubleacute",
+                            "Key_Dead_Caron",
+                            "Key_Dead_Cedilla",
+                            "Key_Dead_Ogonek",
+                            "Key_Dead_Iota",
+                            "Key_Dead_Voiced_Sound",
+                            "Key_Dead_Semivoiced_Sound",
+                            "Key_Dead_Belowdot",
+                            "Key_Dead_Hook",
+                            "Key_Dead_Horn",
+                            "Key_Dead_Stroke",
+                            "Key_Dead_Abovecomma",
+                            "Key_Dead_Abovereversedcomma",
+                            "Key_Dead_Doublegrave",
+                            "Key_Dead_Belowring",
+                            "Key_Dead_Belowmacron",
+                            "Key_Dead_Belowcircumflex",
+                            "Key_Dead_Belowtilde",
+                            "Key_Dead_Belowbreve",
+                            "Key_Dead_Belowdiaeresis",
+                            "Key_Dead_Invertedbreve",
+                            "Key_Dead_Belowcomma",
+                            "Key_Dead_Currency",
+                            "Key_Dead_a",
+                            "Key_Dead_A",
+                            "Key_Dead_e",
+                            "Key_Dead_E",
+                            "Key_Dead_i",
+                            "Key_Dead_I",
+                            "Key_Dead_o",
+                            "Key_Dead_O",
+                            "Key_Dead_u",
+                            "Key_Dead_U",
+                            "Key_Dead_Small_Schwa",
+                            "Key_Dead_Capital_Schwa",
+                            "Key_Dead_Greek",
+                            "Key_Dead_Lowline",
+                            "Key_Dead_Aboveverticalline",
+                            "Key_Dead_Belowverticalline",
+                            "Key_Dead_Longsolidusoverlay",
+                            "Key_Back",
+                            "Key_Forward",
+                            "Key_Stop",
+                            "Key_Refresh",
+                            "Key_VolumeDown",
+                            "Key_VolumeMute",
+                            "Key_VolumeUp",
+                            "Key_BassBoost",
+                            "Key_BassUp",
+                            "Key_BassDown",
+                            "Key_TrebleUp",
+                            "Key_TrebleDown",
+                            "Key_MediaPlay",
+                            "Key_MediaStop",
+                            "Key_MediaPrevious",
+                            "Key_MediaNext",
+                            "Key_MediaRecord",
+                            "Key_MediaPause",
+                            "Key_MediaTogglePlayPause",
+                            "Key_HomePage",
+                            "Key_Favorites",
+                            "Key_Search",
+                            "Key_Standby",
+                            "Key_OpenUrl",
+                            "Key_LaunchMail",
+                            "Key_LaunchMedia",
+                            "Key_Launch0",
+                            "Key_Launch1",
+                            "Key_Launch2",
+                            "Key_Launch3",
+                            "Key_Launch4",
+                            "Key_Launch5",
+                            "Key_Launch6",
+                            "Key_Launch7",
+                            "Key_Launch8",
+                            "Key_Launch9",
+                            "Key_LaunchA",
+                            "Key_LaunchB",
+                            "Key_LaunchC",
+                            "Key_LaunchD",
+                            "Key_LaunchE",
+                            "Key_LaunchF",
+                            "Key_MonBrightnessUp",
+                            "Key_MonBrightnessDown",
+                            "Key_KeyboardLightOnOff",
+                            "Key_KeyboardBrightnessUp",
+                            "Key_KeyboardBrightnessDown",
+                            "Key_PowerOff",
+                            "Key_WakeUp",
+                            "Key_Eject",
+                            "Key_ScreenSaver",
+                            "Key_WWW",
+                            "Key_Memo",
+                            "Key_LightBulb",
+                            "Key_Shop",
+                            "Key_History",
+                            "Key_AddFavorite",
+                            "Key_HotLinks",
+                            "Key_BrightnessAdjust",
+                            "Key_Finance",
+                            "Key_Community",
+                            "Key_AudioRewind",
+                            "Key_BackForward",
+                            "Key_ApplicationLeft",
+                            "Key_ApplicationRight",
+                            "Key_Book",
+                            "Key_CD",
+                            "Key_Calculator",
+                            "Key_ToDoList",
+                            "Key_ClearGrab",
+                            "Key_Close",
+                            "Key_Copy",
+                            "Key_Cut",
+                            "Key_Display",
+                            "Key_DOS",
+                            "Key_Documents",
+                            "Key_Excel",
+                            "Key_Explorer",
+                            "Key_Game",
+                            "Key_Go",
+                            "Key_iTouch",
+                            "Key_LogOff",
+                            "Key_Market",
+                            "Key_Meeting",
+                            "Key_MenuKB",
+                            "Key_MenuPB",
+                            "Key_MySites",
+                            "Key_News",
+                            "Key_OfficeHome",
+                            "Key_Option",
+                            "Key_Paste",
+                            "Key_Phone",
+                            "Key_Calendar",
+                            "Key_Reply",
+                            "Key_Reload",
+                            "Key_RotateWindows",
+                            "Key_RotationPB",
+                            "Key_RotationKB",
+                            "Key_Save",
+                            "Key_Send",
+                            "Key_Spell",
+                            "Key_SplitScreen",
+                            "Key_Support",
+                            "Key_TaskPane",
+                            "Key_Terminal",
+                            "Key_Tools",
+                            "Key_Travel",
+                            "Key_Video",
+                            "Key_Word",
+                            "Key_Xfer",
+                            "Key_ZoomIn",
+                            "Key_ZoomOut",
+                            "Key_Away",
+                            "Key_Messenger",
+                            "Key_WebCam",
+                            "Key_MailForward",
+                            "Key_Pictures",
+                            "Key_Music",
+                            "Key_Battery",
+                            "Key_Bluetooth",
+                            "Key_WLAN",
+                            "Key_UWB",
+                            "Key_AudioForward",
+                            "Key_AudioRepeat",
+                            "Key_AudioRandomPlay",
+                            "Key_Subtitle",
+                            "Key_AudioCycleTrack",
+                            "Key_Time",
+                            "Key_Hibernate",
+                            "Key_View",
+                            "Key_TopMenu",
+                            "Key_PowerDown",
+                            "Key_Suspend",
+                            "Key_ContrastAdjust",
+                            "Key_LaunchG",
+                            "Key_LaunchH",
+                            "Key_TouchpadToggle",
+                            "Key_TouchpadOn",
+                            "Key_TouchpadOff",
+                            "Key_MicMute",
+                            "Key_Red",
+                            "Key_Green",
+                            "Key_Yellow",
+                            "Key_Blue",
+                            "Key_ChannelUp",
+                            "Key_ChannelDown",
+                            "Key_Guide",
+                            "Key_Info",
+                            "Key_Settings",
+                            "Key_MicVolumeUp",
+                            "Key_MicVolumeDown",
+                            "Key_New",
+                            "Key_Open",
+                            "Key_Find",
+                            "Key_Undo",
+                            "Key_Redo",
+                            "Key_MediaLast",
+                            "Key_Select",
+                            "Key_Yes",
+                            "Key_No",
+                            "Key_Cancel",
+                            "Key_Printer",
+                            "Key_Execute",
+                            "Key_Sleep",
+                            "Key_Play",
+                            "Key_Zoom",
+                            "Key_Exit",
+                            "Key_Context1",
+                            "Key_Context2",
+                            "Key_Context3",
+                            "Key_Context4",
+                            "Key_Call",
+                            "Key_Hangup",
+                            "Key_Flip",
+                            "Key_ToggleCallHangup",
+                            "Key_VoiceDial",
+                            "Key_LastNumberRedial",
+                            "Key_Camera",
+                            "Key_CameraFocus",
+                            "Key_unknown"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "KeyboardModifier",
+                        "values": [
+                            "NoModifier",
+                            "ShiftModifier",
+                            "ControlModifier",
+                            "AltModifier",
+                            "MetaModifier",
+                            "KeypadModifier",
+                            "GroupSwitchModifier",
+                            "KeyboardModifierMask"
+                        ]
+                    },
+                    {
+                        "alias": "KeyboardModifier",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "KeyboardModifiers",
+                        "values": [
+                            "NoModifier",
+                            "ShiftModifier",
+                            "ControlModifier",
+                            "AltModifier",
+                            "MetaModifier",
+                            "KeypadModifier",
+                            "GroupSwitchModifier",
+                            "KeyboardModifierMask"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Modifier",
+                        "values": [
+                            "META",
+                            "SHIFT",
+                            "CTRL",
+                            "ALT",
+                            "MODIFIER_MASK"
+                        ]
+                    },
+                    {
+                        "alias": "Modifier",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Modifiers",
+                        "values": [
+                            "META",
+                            "SHIFT",
+                            "CTRL",
+                            "ALT",
+                            "MODIFIER_MASK"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ArrowType",
+                        "values": [
+                            "NoArrow",
+                            "UpArrow",
+                            "DownArrow",
+                            "LeftArrow",
+                            "RightArrow"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PenStyle",
+                        "values": [
+                            "NoPen",
+                            "SolidLine",
+                            "DashLine",
+                            "DotLine",
+                            "DashDotLine",
+                            "DashDotDotLine",
+                            "CustomDashLine"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PenCapStyle",
+                        "values": [
+                            "FlatCap",
+                            "SquareCap",
+                            "RoundCap",
+                            "MPenCapStyle"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PenJoinStyle",
+                        "values": [
+                            "MiterJoin",
+                            "BevelJoin",
+                            "RoundJoin",
+                            "SvgMiterJoin",
+                            "MPenJoinStyle"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BrushStyle",
+                        "values": [
+                            "NoBrush",
+                            "SolidPattern",
+                            "Dense1Pattern",
+                            "Dense2Pattern",
+                            "Dense3Pattern",
+                            "Dense4Pattern",
+                            "Dense5Pattern",
+                            "Dense6Pattern",
+                            "Dense7Pattern",
+                            "HorPattern",
+                            "VerPattern",
+                            "CrossPattern",
+                            "BDiagPattern",
+                            "FDiagPattern",
+                            "DiagCrossPattern",
+                            "LinearGradientPattern",
+                            "RadialGradientPattern",
+                            "ConicalGradientPattern",
+                            "TexturePattern"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizeMode",
+                        "values": [
+                            "AbsoluteSize",
+                            "RelativeSize"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CursorShape",
+                        "values": [
+                            "ArrowCursor",
+                            "UpArrowCursor",
+                            "CrossCursor",
+                            "WaitCursor",
+                            "IBeamCursor",
+                            "SizeVerCursor",
+                            "SizeHorCursor",
+                            "SizeBDiagCursor",
+                            "SizeFDiagCursor",
+                            "SizeAllCursor",
+                            "BlankCursor",
+                            "SplitVCursor",
+                            "SplitHCursor",
+                            "PointingHandCursor",
+                            "ForbiddenCursor",
+                            "WhatsThisCursor",
+                            "BusyCursor",
+                            "OpenHandCursor",
+                            "ClosedHandCursor",
+                            "DragCopyCursor",
+                            "DragMoveCursor",
+                            "DragLinkCursor",
+                            "LastCursor",
+                            "BitmapCursor",
+                            "CustomCursor"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextFormat",
+                        "values": [
+                            "PlainText",
+                            "RichText",
+                            "AutoText",
+                            "MarkdownText"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "AspectRatioMode",
+                        "values": [
+                            "IgnoreAspectRatio",
+                            "KeepAspectRatio",
+                            "KeepAspectRatioByExpanding"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DockWidgetArea",
+                        "values": [
+                            "LeftDockWidgetArea",
+                            "RightDockWidgetArea",
+                            "TopDockWidgetArea",
+                            "BottomDockWidgetArea",
+                            "DockWidgetArea_Mask",
+                            "AllDockWidgetAreas",
+                            "NoDockWidgetArea"
+                        ]
+                    },
+                    {
+                        "alias": "DockWidgetArea",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DockWidgetAreas",
+                        "values": [
+                            "LeftDockWidgetArea",
+                            "RightDockWidgetArea",
+                            "TopDockWidgetArea",
+                            "BottomDockWidgetArea",
+                            "DockWidgetArea_Mask",
+                            "AllDockWidgetAreas",
+                            "NoDockWidgetArea"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ToolBarArea",
+                        "values": [
+                            "LeftToolBarArea",
+                            "RightToolBarArea",
+                            "TopToolBarArea",
+                            "BottomToolBarArea",
+                            "ToolBarArea_Mask",
+                            "AllToolBarAreas",
+                            "NoToolBarArea"
+                        ]
+                    },
+                    {
+                        "alias": "ToolBarArea",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ToolBarAreas",
+                        "values": [
+                            "LeftToolBarArea",
+                            "RightToolBarArea",
+                            "TopToolBarArea",
+                            "BottomToolBarArea",
+                            "ToolBarArea_Mask",
+                            "AllToolBarAreas",
+                            "NoToolBarArea"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DateFormat",
+                        "values": [
+                            "TextDate",
+                            "ISODate",
+                            "RFC2822Date",
+                            "ISODateWithMs"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TimeSpec",
+                        "values": [
+                            "LocalTime",
+                            "UTC",
+                            "OffsetFromUTC",
+                            "TimeZone"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DayOfWeek",
+                        "values": [
+                            "Monday",
+                            "Tuesday",
+                            "Wednesday",
+                            "Thursday",
+                            "Friday",
+                            "Saturday",
+                            "Sunday"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ScrollBarPolicy",
+                        "values": [
+                            "ScrollBarAsNeeded",
+                            "ScrollBarAlwaysOff",
+                            "ScrollBarAlwaysOn"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CaseSensitivity",
+                        "values": [
+                            "CaseInsensitive",
+                            "CaseSensitive"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Corner",
+                        "values": [
+                            "TopLeftCorner",
+                            "TopRightCorner",
+                            "BottomLeftCorner",
+                            "BottomRightCorner"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Edge",
+                        "values": [
+                            "TopEdge",
+                            "LeftEdge",
+                            "RightEdge",
+                            "BottomEdge"
+                        ]
+                    },
+                    {
+                        "alias": "Edge",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Edges",
+                        "values": [
+                            "TopEdge",
+                            "LeftEdge",
+                            "RightEdge",
+                            "BottomEdge"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ConnectionType",
+                        "values": [
+                            "AutoConnection",
+                            "DirectConnection",
+                            "QueuedConnection",
+                            "BlockingQueuedConnection",
+                            "UniqueConnection",
+                            "SingleShotConnection"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ShortcutContext",
+                        "values": [
+                            "WidgetShortcut",
+                            "WindowShortcut",
+                            "ApplicationShortcut",
+                            "WidgetWithChildrenShortcut"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FillRule",
+                        "values": [
+                            "OddEvenFill",
+                            "WindingFill"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MaskMode",
+                        "values": [
+                            "MaskInColor",
+                            "MaskOutColor"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ClipOperation",
+                        "values": [
+                            "NoClip",
+                            "ReplaceClip",
+                            "IntersectClip"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ItemSelectionMode",
+                        "values": [
+                            "ContainsItemShape",
+                            "IntersectsItemShape",
+                            "ContainsItemBoundingRect",
+                            "IntersectsItemBoundingRect"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ItemSelectionOperation",
+                        "values": [
+                            "ReplaceSelection",
+                            "AddToSelection"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TransformationMode",
+                        "values": [
+                            "FastTransformation",
+                            "SmoothTransformation"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Axis",
+                        "values": [
+                            "XAxis",
+                            "YAxis",
+                            "ZAxis"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FocusReason",
+                        "values": [
+                            "MouseFocusReason",
+                            "TabFocusReason",
+                            "BacktabFocusReason",
+                            "ActiveWindowFocusReason",
+                            "PopupFocusReason",
+                            "ShortcutFocusReason",
+                            "MenuBarFocusReason",
+                            "OtherFocusReason",
+                            "NoFocusReason"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ContextMenuPolicy",
+                        "values": [
+                            "NoContextMenu",
+                            "DefaultContextMenu",
+                            "ActionsContextMenu",
+                            "CustomContextMenu",
+                            "PreventContextMenu"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ContextMenuTrigger",
+                        "values": [
+                            "Press",
+                            "Release"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "InputMethodQuery",
+                        "values": [
+                            "ImEnabled",
+                            "ImCursorRectangle",
+                            "ImFont",
+                            "ImCursorPosition",
+                            "ImSurroundingText",
+                            "ImCurrentSelection",
+                            "ImMaximumTextLength",
+                            "ImAnchorPosition",
+                            "ImHints",
+                            "ImPreferredLanguage",
+                            "ImAbsolutePosition",
+                            "ImTextBeforeCursor",
+                            "ImTextAfterCursor",
+                            "ImEnterKeyType",
+                            "ImAnchorRectangle",
+                            "ImInputItemClipRectangle",
+                            "ImReadOnly",
+                            "ImPlatformData",
+                            "ImQueryInput",
+                            "ImQueryAll"
+                        ]
+                    },
+                    {
+                        "alias": "InputMethodQuery",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "InputMethodQueries",
+                        "values": [
+                            "ImEnabled",
+                            "ImCursorRectangle",
+                            "ImFont",
+                            "ImCursorPosition",
+                            "ImSurroundingText",
+                            "ImCurrentSelection",
+                            "ImMaximumTextLength",
+                            "ImAnchorPosition",
+                            "ImHints",
+                            "ImPreferredLanguage",
+                            "ImAbsolutePosition",
+                            "ImTextBeforeCursor",
+                            "ImTextAfterCursor",
+                            "ImEnterKeyType",
+                            "ImAnchorRectangle",
+                            "ImInputItemClipRectangle",
+                            "ImReadOnly",
+                            "ImPlatformData",
+                            "ImQueryInput",
+                            "ImQueryAll"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "InputMethodHint",
+                        "values": [
+                            "ImhNone",
+                            "ImhHiddenText",
+                            "ImhSensitiveData",
+                            "ImhNoAutoUppercase",
+                            "ImhPreferNumbers",
+                            "ImhPreferUppercase",
+                            "ImhPreferLowercase",
+                            "ImhNoPredictiveText",
+                            "ImhDate",
+                            "ImhTime",
+                            "ImhPreferLatin",
+                            "ImhMultiLine",
+                            "ImhNoEditMenu",
+                            "ImhNoTextHandles",
+                            "ImhDigitsOnly",
+                            "ImhFormattedNumbersOnly",
+                            "ImhUppercaseOnly",
+                            "ImhLowercaseOnly",
+                            "ImhDialableCharactersOnly",
+                            "ImhEmailCharactersOnly",
+                            "ImhUrlCharactersOnly",
+                            "ImhLatinOnly",
+                            "ImhExclusiveInputMask"
+                        ]
+                    },
+                    {
+                        "alias": "InputMethodHint",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "InputMethodHints",
+                        "values": [
+                            "ImhNone",
+                            "ImhHiddenText",
+                            "ImhSensitiveData",
+                            "ImhNoAutoUppercase",
+                            "ImhPreferNumbers",
+                            "ImhPreferUppercase",
+                            "ImhPreferLowercase",
+                            "ImhNoPredictiveText",
+                            "ImhDate",
+                            "ImhTime",
+                            "ImhPreferLatin",
+                            "ImhMultiLine",
+                            "ImhNoEditMenu",
+                            "ImhNoTextHandles",
+                            "ImhDigitsOnly",
+                            "ImhFormattedNumbersOnly",
+                            "ImhUppercaseOnly",
+                            "ImhLowercaseOnly",
+                            "ImhDialableCharactersOnly",
+                            "ImhEmailCharactersOnly",
+                            "ImhUrlCharactersOnly",
+                            "ImhLatinOnly",
+                            "ImhExclusiveInputMask"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "EnterKeyType",
+                        "values": [
+                            "EnterKeyDefault",
+                            "EnterKeyReturn",
+                            "EnterKeyDone",
+                            "EnterKeyGo",
+                            "EnterKeySend",
+                            "EnterKeySearch",
+                            "EnterKeyNext",
+                            "EnterKeyPrevious"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ToolButtonStyle",
+                        "values": [
+                            "ToolButtonIconOnly",
+                            "ToolButtonTextOnly",
+                            "ToolButtonTextBesideIcon",
+                            "ToolButtonTextUnderIcon",
+                            "ToolButtonFollowStyle"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LayoutDirection",
+                        "values": [
+                            "LeftToRight",
+                            "RightToLeft",
+                            "LayoutDirectionAuto"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DropAction",
+                        "values": [
+                            "CopyAction",
+                            "MoveAction",
+                            "LinkAction",
+                            "ActionMask",
+                            "TargetMoveAction",
+                            "IgnoreAction"
+                        ]
+                    },
+                    {
+                        "alias": "DropAction",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DropActions",
+                        "values": [
+                            "CopyAction",
+                            "MoveAction",
+                            "LinkAction",
+                            "ActionMask",
+                            "TargetMoveAction",
+                            "IgnoreAction"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CheckState",
+                        "values": [
+                            "Unchecked",
+                            "PartiallyChecked",
+                            "Checked"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ItemDataRole",
+                        "values": [
+                            "DisplayRole",
+                            "DecorationRole",
+                            "EditRole",
+                            "ToolTipRole",
+                            "StatusTipRole",
+                            "WhatsThisRole",
+                            "FontRole",
+                            "TextAlignmentRole",
+                            "BackgroundRole",
+                            "ForegroundRole",
+                            "CheckStateRole",
+                            "AccessibleTextRole",
+                            "AccessibleDescriptionRole",
+                            "SizeHintRole",
+                            "InitialSortOrderRole",
+                            "DisplayPropertyRole",
+                            "DecorationPropertyRole",
+                            "ToolTipPropertyRole",
+                            "StatusTipPropertyRole",
+                            "WhatsThisPropertyRole",
+                            "UserRole"
+                        ]
+                    },
+                    {
+                        "alias": "ItemFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ItemFlags",
+                        "values": [
+                            "NoItemFlags",
+                            "ItemIsSelectable",
+                            "ItemIsEditable",
+                            "ItemIsDragEnabled",
+                            "ItemIsDropEnabled",
+                            "ItemIsUserCheckable",
+                            "ItemIsEnabled",
+                            "ItemIsAutoTristate",
+                            "ItemNeverHasChildren",
+                            "ItemIsUserTristate"
+                        ]
+                    },
+                    {
+                        "alias": "MatchFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "MatchFlags",
+                        "values": [
+                            "MatchExactly",
+                            "MatchContains",
+                            "MatchStartsWith",
+                            "MatchEndsWith",
+                            "MatchRegularExpression",
+                            "MatchWildcard",
+                            "MatchFixedString",
+                            "MatchTypeMask",
+                            "MatchCaseSensitive",
+                            "MatchWrap",
+                            "MatchRecursive"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WindowModality",
+                        "values": [
+                            "NonModal",
+                            "WindowModal",
+                            "ApplicationModal"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextInteractionFlag",
+                        "values": [
+                            "NoTextInteraction",
+                            "TextSelectableByMouse",
+                            "TextSelectableByKeyboard",
+                            "LinksAccessibleByMouse",
+                            "LinksAccessibleByKeyboard",
+                            "TextEditable",
+                            "TextEditorInteraction",
+                            "TextBrowserInteraction"
+                        ]
+                    },
+                    {
+                        "alias": "TextInteractionFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "TextInteractionFlags",
+                        "values": [
+                            "NoTextInteraction",
+                            "TextSelectableByMouse",
+                            "TextSelectableByKeyboard",
+                            "LinksAccessibleByMouse",
+                            "LinksAccessibleByKeyboard",
+                            "TextEditable",
+                            "TextEditorInteraction",
+                            "TextBrowserInteraction"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizeHint",
+                        "values": [
+                            "MinimumSize",
+                            "PreferredSize",
+                            "MaximumSize",
+                            "MinimumDescent",
+                            "NSizeHints"
+                        ]
+                    },
+                    {
+                        "alias": "TouchPointState",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "TouchPointStates",
+                        "values": [
+                            "TouchPointUnknownState",
+                            "TouchPointPressed",
+                            "TouchPointMoved",
+                            "TouchPointStationary",
+                            "TouchPointReleased"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "GestureState",
+                        "values": [
+                            "NoGesture",
+                            "GestureStarted",
+                            "GestureUpdated",
+                            "GestureFinished",
+                            "GestureCanceled"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "GestureType",
+                        "values": [
+                            "TapGesture",
+                            "TapAndHoldGesture",
+                            "PanGesture",
+                            "PinchGesture",
+                            "SwipeGesture",
+                            "CustomGesture",
+                            "LastGestureType"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "NativeGestureType",
+                        "values": [
+                            "BeginNativeGesture",
+                            "EndNativeGesture",
+                            "PanNativeGesture",
+                            "ZoomNativeGesture",
+                            "SmartZoomNativeGesture",
+                            "RotateNativeGesture",
+                            "SwipeNativeGesture"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CursorMoveStyle",
+                        "values": [
+                            "LogicalMoveStyle",
+                            "VisualMoveStyle"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TimerType",
+                        "values": [
+                            "PreciseTimer",
+                            "CoarseTimer",
+                            "VeryCoarseTimer"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TimerId",
+                        "values": [
+                            "Invalid"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ScrollPhase",
+                        "values": [
+                            "NoScrollPhase",
+                            "ScrollBegin",
+                            "ScrollUpdate",
+                            "ScrollEnd",
+                            "ScrollMomentum"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MouseEventSource",
+                        "values": [
+                            "MouseEventNotSynthesized",
+                            "MouseEventSynthesizedBySystem",
+                            "MouseEventSynthesizedByQt",
+                            "MouseEventSynthesizedByApplication"
+                        ]
+                    },
+                    {
+                        "alias": "MouseEventFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "MouseEventFlags",
+                        "values": [
+                            "NoMouseEventFlag",
+                            "MouseEventCreatedDoubleClick",
+                            "MouseEventFlagMask"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ChecksumType",
+                        "values": [
+                            "ChecksumIso3309",
+                            "ChecksumItuV41"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "HighDpiScaleFactorRoundingPolicy",
+                        "values": [
+                            "Unset",
+                            "Round",
+                            "Ceil",
+                            "Floor",
+                            "RoundPreferFloor",
+                            "PassThrough"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "PermissionStatus",
+                        "values": [
+                            "Undetermined",
+                            "Granted",
+                            "Denied"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "namespace": true,
+                "qualifiedClassName": "Qt"
+            }
+        ],
+        "inputFile": "qnamespace.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractAnimation",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Direction",
+                        "values": [
+                            "Forward",
+                            "Backward"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "State",
+                        "values": [
+                            "Stopped",
+                            "Paused",
+                            "Running"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableState",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "state",
+                        "notify": "stateChanged",
+                        "read": "state",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "State",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableLoopCount",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "loopCount",
+                        "read": "loopCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLoopCount"
+                    },
+                    {
+                        "bindable": "bindableCurrentTime",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentTime",
+                        "read": "currentTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentTime"
+                    },
+                    {
+                        "bindable": "bindableCurrentLoop",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "currentLoop",
+                        "notify": "currentLoopChanged",
+                        "read": "currentLoop",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableDirection",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "direction",
+                        "notify": "directionChanged",
+                        "read": "direction",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Direction",
+                        "user": false,
+                        "write": "setDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "duration",
+                        "read": "duration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QAbstractAnimation",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newState",
+                                "type": "QAbstractAnimation::State"
+                            },
+                            {
+                                "name": "oldState",
+                                "type": "QAbstractAnimation::State"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "currentLoop",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "currentLoopChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractAnimation::Direction"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "directionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "policy",
+                                "type": "QAbstractAnimation::DeletionPolicy"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "isCloned": true,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "pause",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resume",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setPaused",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "stop",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msecs",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setCurrentTime",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QAnimationDriver",
+                "lineNumber": 106,
+                "object": true,
+                "qualifiedClassName": "QAnimationDriver",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "stopped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractanimation.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDefaultAnimationDriver",
+                "lineNumber": 81,
+                "object": true,
+                "qualifiedClassName": "QDefaultAnimationDriver",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "startTimer",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "stopTimer",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAnimationDriver"
+                    }
+                ]
+            },
+            {
+                "className": "QAbstractAnimationTimer",
+                "lineNumber": 110,
+                "object": true,
+                "qualifiedClassName": "QAbstractAnimationTimer",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QUnifiedTimer",
+                "lineNumber": 126,
+                "object": true,
+                "qualifiedClassName": "QUnifiedTimer",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "startTimers",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "stopTimer",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QAnimationTimer",
+                "lineNumber": 219,
+                "object": true,
+                "qualifiedClassName": "QAnimationTimer",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "startAnimations",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "stopTimer",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractAnimationTimer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractanimation_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractEventDispatcher",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QAbstractEventDispatcher",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToBlock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "awake",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QAbstractEventDispatcherV2",
+                "lineNumber": 96,
+                "object": true,
+                "qualifiedClassName": "QAbstractEventDispatcherV2",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractEventDispatcher"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstracteventdispatcher.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractItemModel",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LayoutChangeHint",
+                        "values": [
+                            "NoLayoutChangeHint",
+                            "VerticalSortHint",
+                            "HorizontalSortHint"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "CheckIndexOption",
+                        "values": [
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+                        ],
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+                        "name": "rowsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "rowsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "rowsAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "rowsRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "columnsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "columnsAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnsRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "modelAboutToBeReset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "modelReset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
+                            },
+                            {
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+                                "type": "int"
+                            },
+                            {
+                                "name": "sourceEnd",
+                                "type": "int"
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+                            {
+                                "name": "destinationParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "destinationRow",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowsAboutToBeMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
+                            },
+                            {
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+                                "type": "int"
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+                            {
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+                                "type": "int"
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+                            {
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+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "destinationRow",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowsMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
+                            },
+                            {
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+                            {
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+                                "type": "int"
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+                            {
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+                                "type": "QModelIndex"
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+                            {
+                                "name": "destinationColumn",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnsAboutToBeMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
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+                            {
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+                            },
+                            {
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+                                "type": "int"
+                            },
+                            {
+                                "name": "destinationParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "destinationColumn",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnsMoved",
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+                    }
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+                        "name": "submit",
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+                        "name": "revert",
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+                    {
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+                        "name": "resetInternalData",
+                        "returnType": "void"
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+                    }
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+                                "name": "proxyIndex",
+                                "type": "QModelIndex"
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+                        ],
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+                        "name": "mapToSource",
+                        "returnType": "QModelIndex"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceIndex",
+                                "type": "QModelIndex"
+                            }
+                        ],
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+                        "name": "mapFromSource",
+                        "returnType": "QModelIndex"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selection",
+                                "type": "QItemSelection"
+                            }
+                        ],
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+                        "name": "mapSelectionToSource",
+                        "returnType": "QItemSelection"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selection",
+                                "type": "QItemSelection"
+                            }
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+                        "name": "mapSelectionFromSource",
+                        "returnType": "QItemSelection"
+                    }
+                ],
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "sourceModel",
+                        "notify": "sourceModelChanged",
+                        "read": "sourceModel",
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+                        "stored": true,
+                        "type": "QAbstractItemModel*",
+                        "user": false,
+                        "write": "setSourceModel"
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+                ],
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+                        "index": 0,
+                        "name": "sourceModelChanged",
+                        "returnType": "void"
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+                        "index": 1,
+                        "name": "_q_sourceModelDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
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+                            {
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "_q_sourceModelRowsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
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+                        ],
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+                        "name": "_q_sourceModelRowsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_sourceModelRowsRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
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+                            {
+                                "type": "int"
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+                        ],
+                        "index": 5,
+                        "name": "_q_sourceModelColumnsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
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+                            {
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "_q_sourceModelColumnsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "_q_sourceModelColumnsRemoved",
+                        "returnType": "void"
+                    }
+                ],
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+                        "name": "QAbstractItemModel"
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+                ]
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+                        "access": "public",
+                        "name": "QAbstractAnimation"
+                    }
+                ]
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+                        "name": "_q_emitSignals",
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+                        "name": "QIODevice"
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+                        "name": "System",
+                        "values": [
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+                            "Julian",
+                            "Milankovic",
+                            "Jalali",
+                            "IslamicCivil",
+                            "Last",
+                            "User"
+                        ]
+                    }
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+                "qualifiedClassName": "QCalendar"
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setOrganizationDomain"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "quitLockEnabled",
+                        "read": "isQuitLockEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setQuitLockEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QCoreApplication",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToQuit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "organizationNameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "organizationDomainChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "applicationNameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "applicationVersionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "quit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "retcode",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "isCloned": true,
+                        "name": "exit",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcoreapplication.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEvent",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Type",
+                        "values": [
+                            "None",
+                            "Timer",
+                            "MouseButtonPress",
+                            "MouseButtonRelease",
+                            "MouseButtonDblClick",
+                            "MouseMove",
+                            "KeyPress",
+                            "KeyRelease",
+                            "FocusIn",
+                            "FocusOut",
+                            "FocusAboutToChange",
+                            "Enter",
+                            "Leave",
+                            "Paint",
+                            "Move",
+                            "Resize",
+                            "Create",
+                            "Destroy",
+                            "Show",
+                            "Hide",
+                            "Close",
+                            "Quit",
+                            "ParentChange",
+                            "ParentAboutToChange",
+                            "ThreadChange",
+                            "WindowActivate",
+                            "WindowDeactivate",
+                            "ShowToParent",
+                            "HideToParent",
+                            "Wheel",
+                            "WindowTitleChange",
+                            "WindowIconChange",
+                            "ApplicationWindowIconChange",
+                            "ApplicationFontChange",
+                            "ApplicationLayoutDirectionChange",
+                            "ApplicationPaletteChange",
+                            "PaletteChange",
+                            "Clipboard",
+                            "Speech",
+                            "MetaCall",
+                            "SockAct",
+                            "WinEventAct",
+                            "DeferredDelete",
+                            "DragEnter",
+                            "DragMove",
+                            "DragLeave",
+                            "Drop",
+                            "DragResponse",
+                            "ChildAdded",
+                            "ChildPolished",
+                            "ChildRemoved",
+                            "ShowWindowRequest",
+                            "PolishRequest",
+                            "Polish",
+                            "LayoutRequest",
+                            "UpdateRequest",
+                            "UpdateLater",
+                            "EmbeddingControl",
+                            "ActivateControl",
+                            "DeactivateControl",
+                            "ContextMenu",
+                            "InputMethod",
+                            "TabletMove",
+                            "LocaleChange",
+                            "LanguageChange",
+                            "LayoutDirectionChange",
+                            "Style",
+                            "TabletPress",
+                            "TabletRelease",
+                            "OkRequest",
+                            "HelpRequest",
+                            "IconDrag",
+                            "FontChange",
+                            "EnabledChange",
+                            "ActivationChange",
+                            "StyleChange",
+                            "IconTextChange",
+                            "ModifiedChange",
+                            "MouseTrackingChange",
+                            "WindowBlocked",
+                            "WindowUnblocked",
+                            "WindowStateChange",
+                            "ReadOnlyChange",
+                            "ToolTip",
+                            "WhatsThis",
+                            "StatusTip",
+                            "ActionChanged",
+                            "ActionAdded",
+                            "ActionRemoved",
+                            "FileOpen",
+                            "Shortcut",
+                            "ShortcutOverride",
+                            "WhatsThisClicked",
+                            "ToolBarChange",
+                            "ApplicationActivate",
+                            "ApplicationActivated",
+                            "ApplicationDeactivate",
+                            "ApplicationDeactivated",
+                            "QueryWhatsThis",
+                            "EnterWhatsThisMode",
+                            "LeaveWhatsThisMode",
+                            "ZOrderChange",
+                            "HoverEnter",
+                            "HoverLeave",
+                            "HoverMove",
+                            "AcceptDropsChange",
+                            "ZeroTimerEvent",
+                            "GraphicsSceneMouseMove",
+                            "GraphicsSceneMousePress",
+                            "GraphicsSceneMouseRelease",
+                            "GraphicsSceneMouseDoubleClick",
+                            "GraphicsSceneContextMenu",
+                            "GraphicsSceneHoverEnter",
+                            "GraphicsSceneHoverMove",
+                            "GraphicsSceneHoverLeave",
+                            "GraphicsSceneHelp",
+                            "GraphicsSceneDragEnter",
+                            "GraphicsSceneDragMove",
+                            "GraphicsSceneDragLeave",
+                            "GraphicsSceneDrop",
+                            "GraphicsSceneWheel",
+                            "GraphicsSceneLeave",
+                            "KeyboardLayoutChange",
+                            "DynamicPropertyChange",
+                            "TabletEnterProximity",
+                            "TabletLeaveProximity",
+                            "NonClientAreaMouseMove",
+                            "NonClientAreaMouseButtonPress",
+                            "NonClientAreaMouseButtonRelease",
+                            "NonClientAreaMouseButtonDblClick",
+                            "MacSizeChange",
+                            "ContentsRectChange",
+                            "MacGLWindowChange",
+                            "FutureCallOut",
+                            "GraphicsSceneResize",
+                            "GraphicsSceneMove",
+                            "CursorChange",
+                            "ToolTipChange",
+                            "NetworkReplyUpdated",
+                            "GrabMouse",
+                            "UngrabMouse",
+                            "GrabKeyboard",
+                            "UngrabKeyboard",
+                            "StateMachineSignal",
+                            "StateMachineWrapped",
+                            "TouchBegin",
+                            "TouchUpdate",
+                            "TouchEnd",
+                            "NativeGesture",
+                            "RequestSoftwareInputPanel",
+                            "CloseSoftwareInputPanel",
+                            "WinIdChange",
+                            "Gesture",
+                            "GestureOverride",
+                            "ScrollPrepare",
+                            "Scroll",
+                            "Expose",
+                            "InputMethodQuery",
+                            "OrientationChange",
+                            "TouchCancel",
+                            "ThemeChange",
+                            "SockClose",
+                            "PlatformPanel",
+                            "StyleAnimationUpdate",
+                            "ApplicationStateChange",
+                            "WindowChangeInternal",
+                            "ScreenChangeInternal",
+                            "PlatformSurface",
+                            "Pointer",
+                            "TabletTrackingChange",
+                            "WindowAboutToChangeInternal",
+                            "DevicePixelRatioChange",
+                            "ChildWindowAdded",
+                            "ChildWindowRemoved",
+                            "ParentWindowAboutToChange",
+                            "ParentWindowChange",
+                            "User",
+                            "MaxUser"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 44,
+                "qualifiedClassName": "QEvent"
+            }
+        ],
+        "inputFile": "qcoreevent.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCryptographicHash",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Algorithm",
+                        "values": [
+                            "Md4",
+                            "Md5",
+                            "Sha1",
+                            "Sha224",
+                            "Sha256",
+                            "Sha384",
+                            "Sha512",
+                            "Keccak_224",
+                            "Keccak_256",
+                            "Keccak_384",
+                            "Keccak_512",
+                            "RealSha3_224",
+                            "RealSha3_256",
+                            "RealSha3_384",
+                            "RealSha3_512",
+                            "Sha3_224",
+                            "Sha3_256",
+                            "Sha3_384",
+                            "Sha3_512",
+                            "Blake2b_160",
+                            "Blake2b_256",
+                            "Blake2b_384",
+                            "Blake2b_512",
+                            "Blake2s_128",
+                            "Blake2s_160",
+                            "Blake2s_224",
+                            "Blake2s_256",
+                            "NumAlgorithms"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 19,
+                "qualifiedClassName": "QCryptographicHash"
+            }
+        ],
+        "inputFile": "qcryptographichash.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEasingCurve",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Type",
+                        "values": [
+                            "Linear",
+                            "InQuad",
+                            "OutQuad",
+                            "InOutQuad",
+                            "OutInQuad",
+                            "InCubic",
+                            "OutCubic",
+                            "InOutCubic",
+                            "OutInCubic",
+                            "InQuart",
+                            "OutQuart",
+                            "InOutQuart",
+                            "OutInQuart",
+                            "InQuint",
+                            "OutQuint",
+                            "InOutQuint",
+                            "OutInQuint",
+                            "InSine",
+                            "OutSine",
+                            "InOutSine",
+                            "OutInSine",
+                            "InExpo",
+                            "OutExpo",
+                            "InOutExpo",
+                            "OutInExpo",
+                            "InCirc",
+                            "OutCirc",
+                            "InOutCirc",
+                            "OutInCirc",
+                            "InElastic",
+                            "OutElastic",
+                            "InOutElastic",
+                            "OutInElastic",
+                            "InBack",
+                            "OutBack",
+                            "InOutBack",
+                            "OutInBack",
+                            "InBounce",
+                            "OutBounce",
+                            "InOutBounce",
+                            "OutInBounce",
+                            "InCurve",
+                            "OutCurve",
+                            "SineCurve",
+                            "CosineCurve",
+                            "BezierSpline",
+                            "TCBSpline",
+                            "Custom",
+                            "NCurveTypes"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 19,
+                "qualifiedClassName": "QEasingCurve"
+            }
+        ],
+        "inputFile": "qeasingcurve.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEventDispatcherWin32",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QEventDispatcherWin32",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractEventDispatcher"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qeventdispatcher_win_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEventLoop",
+                "enums": [
+                    {
+                        "alias": "ProcessEventsFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ProcessEventsFlags",
+                        "values": [
+                            "AllEvents",
+                            "ExcludeUserInputEvents",
+                            "ExcludeSocketNotifiers",
+                            "WaitForMoreEvents",
+                            "X11ExcludeTimers",
+                            "EventLoopExec",
+                            "DialogExec",
+                            "ApplicationExec"
+                        ]
+                    }
+                ],
+                "lineNumber": 15,
+                "object": true,
+                "qualifiedClassName": "QEventLoop",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "returnCode",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "quit",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qeventloop.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFactoryLoader",
+                "lineNumber": 61,
+                "object": true,
+                "qualifiedClassName": "QFactoryLoader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfactoryloader_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFile",
+                "lineNumber": 92,
+                "object": true,
+                "qualifiedClassName": "QFile",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFileDevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfile.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileDevice",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QFileDevice",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QIODevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfiledevice.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileSelector",
+                "lineNumber": 13,
+                "object": true,
+                "qualifiedClassName": "QFileSelector",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfileselector.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileSystemWatcher",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QFileSystemWatcher",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "directoryChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemwatcher.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileSystemWatcherEngine",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QFileSystemWatcherEngine",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "removed",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "removed",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "directoryChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemwatcher_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPollingFileSystemWatcherEngine",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QPollingFileSystemWatcherEngine",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFileSystemWatcherEngine"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemwatcher_polling_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsFileSystemWatcherEngine",
+                "lineNumber": 37,
+                "object": true,
+                "qualifiedClassName": "QWindowsFileSystemWatcherEngine",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "driveLockForRemoval",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "driveLockForRemovalFailed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "driveRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFileSystemWatcherEngine"
+                    }
+                ]
+            },
+            {
+                "className": "QWindowsFileSystemWatcherEngineThread",
+                "lineNumber": 112,
+                "object": true,
+                "qualifiedClassName": "QWindowsFileSystemWatcherEngineThread",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "removed",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "removed",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "directoryChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemwatcher_win_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFutureWatcherBase",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QFutureWatcherBase",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "canceled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "paused",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "suspending",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "suspended",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "resumed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "resultIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "resultReadyAt",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "beginIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "endIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "resultsReadyAt",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "minimum",
+                                "type": "int"
+                            },
+                            {
+                                "name": "maximum",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "progressRangeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "progressValue",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "progressValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "progressText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "progressTextChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "cancel",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "suspend",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setSuspended",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "suspend",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "resume",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "toggleSuspended",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "paused",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "setPaused",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "pause",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "togglePaused",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfuturewatcher.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QIdentityProxyModel",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QIdentityProxyModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractProxyModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qidentityproxymodel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QIODevice",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QIODevice",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "channel",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "channelReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "bytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "channel",
+                                "type": "int"
+                            },
+                            {
+                                "name": "bytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "channelBytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "aboutToClose",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "readChannelFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QIODeviceBase"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qiodevice.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QItemSelectionModel",
+                "enums": [
+                    {
+                        "alias": "SelectionFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "SelectionFlags",
+                        "values": [
+                            "NoUpdate",
+                            "Clear",
+                            "Select",
+                            "Deselect",
+                            "Toggle",
+                            "Current",
+                            "Rows",
+                            "Columns",
+                            "SelectCurrent",
+                            "ToggleCurrent",
+                            "ClearAndSelect"
+                        ]
+                    }
+                ],
+                "lineNumber": 90,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "isSelected",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "isRowSelected",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "isCloned": true,
+                        "name": "isRowSelected",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "isColumnSelected",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 16,
+                        "isCloned": true,
+                        "name": "isColumnSelected",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "rowIntersectsSelection",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "isCloned": true,
+                        "name": "rowIntersectsSelection",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "columnIntersectsSelection",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 20,
+                        "isCloned": true,
+                        "name": "columnIntersectsSelection",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "selectedRows",
+                        "returnType": "QModelIndexList"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "isCloned": true,
+                        "name": "selectedRows",
+                        "returnType": "QModelIndexList"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "selectedColumns",
+                        "returnType": "QModelIndexList"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "isCloned": true,
+                        "name": "selectedColumns",
+                        "returnType": "QModelIndexList"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableModel",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "model",
+                        "notify": "modelChanged",
+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QAbstractItemModel*",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 1,
+                        "name": "hasSelection",
+                        "notify": "selectionChanged",
+                        "read": "hasSelection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QModelIndex",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 3,
+                        "name": "selection",
+                        "notify": "selectionChanged",
+                        "read": "selection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QItemSelection",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 4,
+                        "name": "selectedIndexes",
+                        "notify": "selectionChanged",
+                        "read": "selectedIndexes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QModelIndexList",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QItemSelectionModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selected",
+                                "type": "QItemSelection"
+                            },
+                            {
+                                "name": "deselected",
+                                "type": "QItemSelection"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "currentRowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "currentColumnChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "model",
+                                "type": "QAbstractItemModel*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "command",
+                                "type": "QItemSelectionModel::SelectionFlags"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "command",
+                                "type": "QItemSelectionModel::SelectionFlags"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "select",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selection",
+                                "type": "QItemSelection"
+                            },
+                            {
+                                "name": "command",
+                                "type": "QItemSelectionModel::SelectionFlags"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "select",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "reset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "clearSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "clearCurrentIndex",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qitemselectionmodel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLibrary",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LoadHint",
+                        "values": [
+                            "ResolveAllSymbolsHint",
+                            "ExportExternalSymbolsHint",
+                            "LoadArchiveMemberHint",
+                            "PreventUnloadHint",
+                            "DeepBindHint"
+                        ]
+                    },
+                    {
+                        "alias": "LoadHint",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "LoadHints",
+                        "values": [
+                            "ResolveAllSymbolsHint",
+                            "ExportExternalSymbolsHint",
+                            "LoadArchiveMemberHint",
+                            "PreventUnloadHint",
+                            "DeepBindHint"
+                        ]
+                    }
+                ],
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "fileName",
+                        "read": "fileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setFileName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "loadHints",
+                        "read": "loadHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LoadHints",
+                        "user": false,
+                        "write": "setLoadHints"
+                    }
+                ],
+                "qualifiedClassName": "QLibrary",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlibrary.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLocale",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Language",
+                        "type": "ushort",
+                        "values": [
+                            "AnyLanguage",
+                            "C",
+                            "Abkhazian",
+                            "Afar",
+                            "Afrikaans",
+                            "Aghem",
+                            "Akan",
+                            "Akkadian",
+                            "Akoose",
+                            "Albanian",
+                            "AmericanSignLanguage",
+                            "Amharic",
+                            "AncientEgyptian",
+                            "AncientGreek",
+                            "Arabic",
+                            "Aragonese",
+                            "Aramaic",
+                            "Armenian",
+                            "Assamese",
+                            "Asturian",
+                            "Asu",
+                            "Atsam",
+                            "Avaric",
+                            "Avestan",
+                            "Aymara",
+                            "Azerbaijani",
+                            "Bafia",
+                            "Balinese",
+                            "Bambara",
+                            "Bamun",
+                            "Bangla",
+                            "Basaa",
+                            "Bashkir",
+                            "Basque",
+                            "BatakToba",
+                            "Belarusian",
+                            "Bemba",
+                            "Bena",
+                            "Bhojpuri",
+                            "Bislama",
+                            "Blin",
+                            "Bodo",
+                            "Bosnian",
+                            "Breton",
+                            "Buginese",
+                            "Bulgarian",
+                            "Burmese",
+                            "Cantonese",
+                            "Catalan",
+                            "Cebuano",
+                            "CentralAtlasTamazight",
+                            "CentralKurdish",
+                            "Chakma",
+                            "Chamorro",
+                            "Chechen",
+                            "Cherokee",
+                            "Chickasaw",
+                            "Chiga",
+                            "Chinese",
+                            "Church",
+                            "Chuvash",
+                            "Colognian",
+                            "Coptic",
+                            "Cornish",
+                            "Corsican",
+                            "Cree",
+                            "Croatian",
+                            "Czech",
+                            "Danish",
+                            "Divehi",
+                            "Dogri",
+                            "Duala",
+                            "Dutch",
+                            "Dzongkha",
+                            "Embu",
+                            "English",
+                            "Erzya",
+                            "Esperanto",
+                            "Estonian",
+                            "Ewe",
+                            "Ewondo",
+                            "Faroese",
+                            "Fijian",
+                            "Filipino",
+                            "Finnish",
+                            "French",
+                            "Friulian",
+                            "Fulah",
+                            "Gaelic",
+                            "Ga",
+                            "Galician",
+                            "Ganda",
+                            "Geez",
+                            "Georgian",
+                            "German",
+                            "Gothic",
+                            "Greek",
+                            "Guarani",
+                            "Gujarati",
+                            "Gusii",
+                            "Haitian",
+                            "Hausa",
+                            "Hawaiian",
+                            "Hebrew",
+                            "Herero",
+                            "Hindi",
+                            "HiriMotu",
+                            "Hungarian",
+                            "Icelandic",
+                            "Ido",
+                            "Igbo",
+                            "InariSami",
+                            "Indonesian",
+                            "Ingush",
+                            "Interlingua",
+                            "Interlingue",
+                            "Inuktitut",
+                            "Inupiaq",
+                            "Irish",
+                            "Italian",
+                            "Japanese",
+                            "Javanese",
+                            "Jju",
+                            "JolaFonyi",
+                            "Kabuverdianu",
+                            "Kabyle",
+                            "Kako",
+                            "Kalaallisut",
+                            "Kalenjin",
+                            "Kamba",
+                            "Kannada",
+                            "Kanuri",
+                            "Kashmiri",
+                            "Kazakh",
+                            "Kenyang",
+                            "Khmer",
+                            "Kiche",
+                            "Kikuyu",
+                            "Kinyarwanda",
+                            "Komi",
+                            "Kongo",
+                            "Konkani",
+                            "Korean",
+                            "Koro",
+                            "KoyraboroSenni",
+                            "KoyraChiini",
+                            "Kpelle",
+                            "Kuanyama",
+                            "Kurdish",
+                            "Kwasio",
+                            "Kyrgyz",
+                            "Lakota",
+                            "Langi",
+                            "Lao",
+                            "Latin",
+                            "Latvian",
+                            "Lezghian",
+                            "Limburgish",
+                            "Lingala",
+                            "LiteraryChinese",
+                            "Lithuanian",
+                            "Lojban",
+                            "LowerSorbian",
+                            "LowGerman",
+                            "LubaKatanga",
+                            "LuleSami",
+                            "Luo",
+                            "Luxembourgish",
+                            "Luyia",
+                            "Macedonian",
+                            "Machame",
+                            "Maithili",
+                            "MakhuwaMeetto",
+                            "Makonde",
+                            "Malagasy",
+                            "Malayalam",
+                            "Malay",
+                            "Maltese",
+                            "Mandingo",
+                            "Manipuri",
+                            "Manx",
+                            "Maori",
+                            "Mapuche",
+                            "Marathi",
+                            "Marshallese",
+                            "Masai",
+                            "Mazanderani",
+                            "Mende",
+                            "Meru",
+                            "Meta",
+                            "Mohawk",
+                            "Mongolian",
+                            "Morisyen",
+                            "Mundang",
+                            "Muscogee",
+                            "Nama",
+                            "NauruLanguage",
+                            "Navajo",
+                            "Ndonga",
+                            "Nepali",
+                            "Newari",
+                            "Ngiemboon",
+                            "Ngomba",
+                            "NigerianPidgin",
+                            "Nko",
+                            "NorthernLuri",
+                            "NorthernSami",
+                            "NorthernSotho",
+                            "NorthNdebele",
+                            "NorwegianBokmal",
+                            "NorwegianNynorsk",
+                            "Nuer",
+                            "Nyanja",
+                            "Nyankole",
+                            "Occitan",
+                            "Odia",
+                            "Ojibwa",
+                            "OldIrish",
+                            "OldNorse",
+                            "OldPersian",
+                            "Oromo",
+                            "Osage",
+                            "Ossetic",
+                            "Pahlavi",
+                            "Palauan",
+                            "Pali",
+                            "Papiamento",
+                            "Pashto",
+                            "Persian",
+                            "Phoenician",
+                            "Polish",
+                            "Portuguese",
+                            "Prussian",
+                            "Punjabi",
+                            "Quechua",
+                            "Romanian",
+                            "Romansh",
+                            "Rombo",
+                            "Rundi",
+                            "Russian",
+                            "Rwa",
+                            "Saho",
+                            "Sakha",
+                            "Samburu",
+                            "Samoan",
+                            "Sango",
+                            "Sangu",
+                            "Sanskrit",
+                            "Santali",
+                            "Sardinian",
+                            "Saurashtra",
+                            "Sena",
+                            "Serbian",
+                            "Shambala",
+                            "Shona",
+                            "SichuanYi",
+                            "Sicilian",
+                            "Sidamo",
+                            "Silesian",
+                            "Sindhi",
+                            "Sinhala",
+                            "SkoltSami",
+                            "Slovak",
+                            "Slovenian",
+                            "Soga",
+                            "Somali",
+                            "SouthernKurdish",
+                            "SouthernSami",
+                            "SouthernSotho",
+                            "SouthNdebele",
+                            "Spanish",
+                            "StandardMoroccanTamazight",
+                            "Sundanese",
+                            "Swahili",
+                            "Swati",
+                            "Swedish",
+                            "SwissGerman",
+                            "Syriac",
+                            "Tachelhit",
+                            "Tahitian",
+                            "TaiDam",
+                            "Taita",
+                            "Tajik",
+                            "Tamil",
+                            "Taroko",
+                            "Tasawaq",
+                            "Tatar",
+                            "Telugu",
+                            "Teso",
+                            "Thai",
+                            "Tibetan",
+                            "Tigre",
+                            "Tigrinya",
+                            "TokelauLanguage",
+                            "TokPisin",
+                            "Tongan",
+                            "Tsonga",
+                            "Tswana",
+                            "Turkish",
+                            "Turkmen",
+                            "TuvaluLanguage",
+                            "Tyap",
+                            "Ugaritic",
+                            "Ukrainian",
+                            "UpperSorbian",
+                            "Urdu",
+                            "Uyghur",
+                            "Uzbek",
+                            "Vai",
+                            "Venda",
+                            "Vietnamese",
+                            "Volapuk",
+                            "Vunjo",
+                            "Walloon",
+                            "Walser",
+                            "Warlpiri",
+                            "Welsh",
+                            "WesternBalochi",
+                            "WesternFrisian",
+                            "Wolaytta",
+                            "Wolof",
+                            "Xhosa",
+                            "Yangben",
+                            "Yiddish",
+                            "Yoruba",
+                            "Zarma",
+                            "Zhuang",
+                            "Zulu",
+                            "Kaingang",
+                            "Nheengatu",
+                            "Haryanvi",
+                            "NorthernFrisian",
+                            "Rajasthani",
+                            "Moksha",
+                            "TokiPona",
+                            "Pijin",
+                            "Obolo",
+                            "Baluchi",
+                            "Ligurian",
+                            "Rohingya",
+                            "Torwali",
+                            "Anii",
+                            "Kangri",
+                            "Venetian",
+                            "Kuvi",
+                            "Afan",
+                            "Bengali",
+                            "Bhutani",
+                            "Byelorussian",
+                            "Cambodian",
+                            "CentralMoroccoTamazight",
+                            "Chewa",
+                            "Frisian",
+                            "Greenlandic",
+                            "Inupiak",
+                            "Kirghiz",
+                            "Kurundi",
+                            "Kwanyama",
+                            "Navaho",
+                            "Oriya",
+                            "RhaetoRomance",
+                            "Uighur",
+                            "Uigur",
+                            "Walamo",
+                            "LastLanguage"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Script",
+                        "type": "ushort",
+                        "values": [
+                            "AnyScript",
+                            "AdlamScript",
+                            "AhomScript",
+                            "AnatolianHieroglyphsScript",
+                            "ArabicScript",
+                            "ArmenianScript",
+                            "AvestanScript",
+                            "BalineseScript",
+                            "BamumScript",
+                            "BanglaScript",
+                            "BassaVahScript",
+                            "BatakScript",
+                            "BhaiksukiScript",
+                            "BopomofoScript",
+                            "BrahmiScript",
+                            "BrailleScript",
+                            "BugineseScript",
+                            "BuhidScript",
+                            "CanadianAboriginalScript",
+                            "CarianScript",
+                            "CaucasianAlbanianScript",
+                            "ChakmaScript",
+                            "ChamScript",
+                            "CherokeeScript",
+                            "CopticScript",
+                            "CuneiformScript",
+                            "CypriotScript",
+                            "CyrillicScript",
+                            "DeseretScript",
+                            "DevanagariScript",
+                            "DuployanScript",
+                            "EgyptianHieroglyphsScript",
+                            "ElbasanScript",
+                            "EthiopicScript",
+                            "FraserScript",
+                            "GeorgianScript",
+                            "GlagoliticScript",
+                            "GothicScript",
+                            "GranthaScript",
+                            "GreekScript",
+                            "GujaratiScript",
+                            "GurmukhiScript",
+                            "HangulScript",
+                            "HanScript",
+                            "HanunooScript",
+                            "HanWithBopomofoScript",
+                            "HatranScript",
+                            "HebrewScript",
+                            "HiraganaScript",
+                            "ImperialAramaicScript",
+                            "InscriptionalPahlaviScript",
+                            "InscriptionalParthianScript",
+                            "JamoScript",
+                            "JapaneseScript",
+                            "JavaneseScript",
+                            "KaithiScript",
+                            "KannadaScript",
+                            "KatakanaScript",
+                            "KayahLiScript",
+                            "KharoshthiScript",
+                            "KhmerScript",
+                            "KhojkiScript",
+                            "KhudawadiScript",
+                            "KoreanScript",
+                            "LannaScript",
+                            "LaoScript",
+                            "LatinScript",
+                            "LepchaScript",
+                            "LimbuScript",
+                            "LinearAScript",
+                            "LinearBScript",
+                            "LycianScript",
+                            "LydianScript",
+                            "MahajaniScript",
+                            "MalayalamScript",
+                            "MandaeanScript",
+                            "ManichaeanScript",
+                            "MarchenScript",
+                            "MeiteiMayekScript",
+                            "MendeScript",
+                            "MeroiticCursiveScript",
+                            "MeroiticScript",
+                            "ModiScript",
+                            "MongolianScript",
+                            "MroScript",
+                            "MultaniScript",
+                            "MyanmarScript",
+                            "NabataeanScript",
+                            "NewaScript",
+                            "NewTaiLueScript",
+                            "NkoScript",
+                            "OdiaScript",
+                            "OghamScript",
+                            "OlChikiScript",
+                            "OldHungarianScript",
+                            "OldItalicScript",
+                            "OldNorthArabianScript",
+                            "OldPermicScript",
+                            "OldPersianScript",
+                            "OldSouthArabianScript",
+                            "OrkhonScript",
+                            "OsageScript",
+                            "OsmanyaScript",
+                            "PahawhHmongScript",
+                            "PalmyreneScript",
+                            "PauCinHauScript",
+                            "PhagsPaScript",
+                            "PhoenicianScript",
+                            "PollardPhoneticScript",
+                            "PsalterPahlaviScript",
+                            "RejangScript",
+                            "RunicScript",
+                            "SamaritanScript",
+                            "SaurashtraScript",
+                            "SharadaScript",
+                            "ShavianScript",
+                            "SiddhamScript",
+                            "SignWritingScript",
+                            "SimplifiedHanScript",
+                            "SinhalaScript",
+                            "SoraSompengScript",
+                            "SundaneseScript",
+                            "SylotiNagriScript",
+                            "SyriacScript",
+                            "TagalogScript",
+                            "TagbanwaScript",
+                            "TaiLeScript",
+                            "TaiVietScript",
+                            "TakriScript",
+                            "TamilScript",
+                            "TangutScript",
+                            "TeluguScript",
+                            "ThaanaScript",
+                            "ThaiScript",
+                            "TibetanScript",
+                            "TifinaghScript",
+                            "TirhutaScript",
+                            "TraditionalHanScript",
+                            "UgariticScript",
+                            "VaiScript",
+                            "VarangKshitiScript",
+                            "YiScript",
+                            "HanifiScript",
+                            "BengaliScript",
+                            "MendeKikakuiScript",
+                            "OriyaScript",
+                            "SimplifiedChineseScript",
+                            "TraditionalChineseScript",
+                            "LastScript"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Country",
+                        "type": "ushort",
+                        "values": [
+                            "AnyTerritory",
+                            "Afghanistan",
+                            "AlandIslands",
+                            "Albania",
+                            "Algeria",
+                            "AmericanSamoa",
+                            "Andorra",
+                            "Angola",
+                            "Anguilla",
+                            "Antarctica",
+                            "AntiguaAndBarbuda",
+                            "Argentina",
+                            "Armenia",
+                            "Aruba",
+                            "AscensionIsland",
+                            "Australia",
+                            "Austria",
+                            "Azerbaijan",
+                            "Bahamas",
+                            "Bahrain",
+                            "Bangladesh",
+                            "Barbados",
+                            "Belarus",
+                            "Belgium",
+                            "Belize",
+                            "Benin",
+                            "Bermuda",
+                            "Bhutan",
+                            "Bolivia",
+                            "BosniaAndHerzegovina",
+                            "Botswana",
+                            "BouvetIsland",
+                            "Brazil",
+                            "BritishIndianOceanTerritory",
+                            "BritishVirginIslands",
+                            "Brunei",
+                            "Bulgaria",
+                            "BurkinaFaso",
+                            "Burundi",
+                            "Cambodia",
+                            "Cameroon",
+                            "Canada",
+                            "CanaryIslands",
+                            "CapeVerde",
+                            "CaribbeanNetherlands",
+                            "CaymanIslands",
+                            "CentralAfricanRepublic",
+                            "CeutaAndMelilla",
+                            "Chad",
+                            "Chile",
+                            "China",
+                            "ChristmasIsland",
+                            "ClippertonIsland",
+                            "CocosIslands",
+                            "Colombia",
+                            "Comoros",
+                            "CongoBrazzaville",
+                            "CongoKinshasa",
+                            "CookIslands",
+                            "CostaRica",
+                            "Croatia",
+                            "Cuba",
+                            "Curacao",
+                            "Cyprus",
+                            "Czechia",
+                            "Denmark",
+                            "DiegoGarcia",
+                            "Djibouti",
+                            "Dominica",
+                            "DominicanRepublic",
+                            "Ecuador",
+                            "Egypt",
+                            "ElSalvador",
+                            "EquatorialGuinea",
+                            "Eritrea",
+                            "Estonia",
+                            "Eswatini",
+                            "Ethiopia",
+                            "Europe",
+                            "EuropeanUnion",
+                            "FalklandIslands",
+                            "FaroeIslands",
+                            "Fiji",
+                            "Finland",
+                            "France",
+                            "FrenchGuiana",
+                            "FrenchPolynesia",
+                            "FrenchSouthernTerritories",
+                            "Gabon",
+                            "Gambia",
+                            "Georgia",
+                            "Germany",
+                            "Ghana",
+                            "Gibraltar",
+                            "Greece",
+                            "Greenland",
+                            "Grenada",
+                            "Guadeloupe",
+                            "Guam",
+                            "Guatemala",
+                            "Guernsey",
+                            "GuineaBissau",
+                            "Guinea",
+                            "Guyana",
+                            "Haiti",
+                            "HeardAndMcDonaldIslands",
+                            "Honduras",
+                            "HongKong",
+                            "Hungary",
+                            "Iceland",
+                            "India",
+                            "Indonesia",
+                            "Iran",
+                            "Iraq",
+                            "Ireland",
+                            "IsleOfMan",
+                            "Israel",
+                            "Italy",
+                            "IvoryCoast",
+                            "Jamaica",
+                            "Japan",
+                            "Jersey",
+                            "Jordan",
+                            "Kazakhstan",
+                            "Kenya",
+                            "Kiribati",
+                            "Kosovo",
+                            "Kuwait",
+                            "Kyrgyzstan",
+                            "Laos",
+                            "LatinAmerica",
+                            "Latvia",
+                            "Lebanon",
+                            "Lesotho",
+                            "Liberia",
+                            "Libya",
+                            "Liechtenstein",
+                            "Lithuania",
+                            "Luxembourg",
+                            "Macao",
+                            "Macedonia",
+                            "Madagascar",
+                            "Malawi",
+                            "Malaysia",
+                            "Maldives",
+                            "Mali",
+                            "Malta",
+                            "MarshallIslands",
+                            "Martinique",
+                            "Mauritania",
+                            "Mauritius",
+                            "Mayotte",
+                            "Mexico",
+                            "Micronesia",
+                            "Moldova",
+                            "Monaco",
+                            "Mongolia",
+                            "Montenegro",
+                            "Montserrat",
+                            "Morocco",
+                            "Mozambique",
+                            "Myanmar",
+                            "Namibia",
+                            "NauruTerritory",
+                            "Nepal",
+                            "Netherlands",
+                            "NewCaledonia",
+                            "NewZealand",
+                            "Nicaragua",
+                            "Nigeria",
+                            "Niger",
+                            "Niue",
+                            "NorfolkIsland",
+                            "NorthernMarianaIslands",
+                            "NorthKorea",
+                            "Norway",
+                            "Oman",
+                            "OutlyingOceania",
+                            "Pakistan",
+                            "Palau",
+                            "PalestinianTerritories",
+                            "Panama",
+                            "PapuaNewGuinea",
+                            "Paraguay",
+                            "Peru",
+                            "Philippines",
+                            "Pitcairn",
+                            "Poland",
+                            "Portugal",
+                            "PuertoRico",
+                            "Qatar",
+                            "Reunion",
+                            "Romania",
+                            "Russia",
+                            "Rwanda",
+                            "SaintBarthelemy",
+                            "SaintHelena",
+                            "SaintKittsAndNevis",
+                            "SaintLucia",
+                            "SaintMartin",
+                            "SaintPierreAndMiquelon",
+                            "SaintVincentAndGrenadines",
+                            "Samoa",
+                            "SanMarino",
+                            "SaoTomeAndPrincipe",
+                            "SaudiArabia",
+                            "Senegal",
+                            "Serbia",
+                            "Seychelles",
+                            "SierraLeone",
+                            "Singapore",
+                            "SintMaarten",
+                            "Slovakia",
+                            "Slovenia",
+                            "SolomonIslands",
+                            "Somalia",
+                            "SouthAfrica",
+                            "SouthGeorgiaAndSouthSandwichIslands",
+                            "SouthKorea",
+                            "SouthSudan",
+                            "Spain",
+                            "SriLanka",
+                            "Sudan",
+                            "Suriname",
+                            "SvalbardAndJanMayen",
+                            "Sweden",
+                            "Switzerland",
+                            "Syria",
+                            "Taiwan",
+                            "Tajikistan",
+                            "Tanzania",
+                            "Thailand",
+                            "TimorLeste",
+                            "Togo",
+                            "TokelauTerritory",
+                            "Tonga",
+                            "TrinidadAndTobago",
+                            "TristanDaCunha",
+                            "Tunisia",
+                            "Turkey",
+                            "Turkmenistan",
+                            "TurksAndCaicosIslands",
+                            "TuvaluTerritory",
+                            "Uganda",
+                            "Ukraine",
+                            "UnitedArabEmirates",
+                            "UnitedKingdom",
+                            "UnitedStatesOutlyingIslands",
+                            "UnitedStates",
+                            "UnitedStatesVirginIslands",
+                            "Uruguay",
+                            "Uzbekistan",
+                            "Vanuatu",
+                            "VaticanCity",
+                            "Venezuela",
+                            "Vietnam",
+                            "WallisAndFutuna",
+                            "WesternSahara",
+                            "World",
+                            "Yemen",
+                            "Zambia",
+                            "Zimbabwe",
+                            "AnyCountry",
+                            "Bonaire",
+                            "BosniaAndHerzegowina",
+                            "CuraSao",
+                            "CzechRepublic",
+                            "DemocraticRepublicOfCongo",
+                            "DemocraticRepublicOfKorea",
+                            "EastTimor",
+                            "LatinAmericaAndTheCaribbean",
+                            "Macau",
+                            "NauruCountry",
+                            "PeoplesRepublicOfCongo",
+                            "RepublicOfKorea",
+                            "RussianFederation",
+                            "SaintVincentAndTheGrenadines",
+                            "SouthGeorgiaAndTheSouthSandwichIslands",
+                            "SvalbardAndJanMayenIslands",
+                            "Swaziland",
+                            "SyrianArabRepublic",
+                            "TokelauCountry",
+                            "TuvaluCountry",
+                            "UnitedStatesMinorOutlyingIslands",
+                            "VaticanCityState",
+                            "WallisAndFutunaIslands",
+                            "LastTerritory",
+                            "LastCountry"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MeasurementSystem",
+                        "values": [
+                            "MetricSystem",
+                            "ImperialUSSystem",
+                            "ImperialUKSystem",
+                            "ImperialSystem"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FormatType",
+                        "values": [
+                            "LongFormat",
+                            "ShortFormat",
+                            "NarrowFormat"
+                        ]
+                    },
+                    {
+                        "alias": "NumberOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "NumberOptions",
+                        "values": [
+                            "DefaultNumberOptions",
+                            "OmitGroupSeparator",
+                            "RejectGroupSeparator",
+                            "OmitLeadingZeroInExponent",
+                            "RejectLeadingZeroInExponent",
+                            "IncludeTrailingZeroesAfterDot",
+                            "RejectTrailingZeroesAfterDot"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TagSeparator",
+                        "type": "char",
+                        "values": [
+                            "Dash",
+                            "Underscore"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CurrencySymbolFormat",
+                        "values": [
+                            "CurrencyIsoCode",
+                            "CurrencySymbol",
+                            "CurrencyDisplayName"
+                        ]
+                    },
+                    {
+                        "alias": "DataSizeFormat",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DataSizeFormats",
+                        "values": [
+                            "DataSizeBase1000",
+                            "DataSizeSIQuantifiers",
+                            "DataSizeIecFormat",
+                            "DataSizeTraditionalFormat",
+                            "DataSizeSIFormat"
+                        ]
+                    },
+                    {
+                        "alias": "LanguageCodeType",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "LanguageCodeTypes",
+                        "values": [
+                            "ISO639Part1",
+                            "ISO639Part2B",
+                            "ISO639Part2T",
+                            "ISO639Part3",
+                            "LegacyLanguageCode",
+                            "ISO639Part2",
+                            "ISO639Alpha2",
+                            "ISO639Alpha3",
+                            "ISO639",
+                            "AnyLanguageCode"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "QuotationStyle",
+                        "values": [
+                            "StandardQuotation",
+                            "AlternateQuotation"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 28,
+                "qualifiedClassName": "QLocale"
+            }
+        ],
+        "inputFile": "qlocale.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMimeData",
+                "lineNumber": 15,
+                "object": true,
+                "qualifiedClassName": "QMimeData",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmimedata.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMimeType",
+                "gadget": true,
+                "lineNumber": 24,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mimeTypeName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "inherits",
+                        "returnType": "bool"
+                    }
+                ],
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "valid",
+                        "read": "isValid",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "isDefault",
+                        "read": "isDefault",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "comment",
+                        "read": "comment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "genericIconName",
+                        "read": "genericIconName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "iconName",
+                        "read": "iconName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "globPatterns",
+                        "read": "globPatterns",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
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+                "object": true,
+                "qualifiedClassName": "QSocketNotifier",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSocketDescriptor"
+                            },
+                            {
+                                "name": "activationEvent",
+                                "type": "QSocketNotifier::Type"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSocketDescriptor"
+                            }
+                        ],
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "activated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsocketnotifier.h",
+        "outputRevision": 68
+    },
+    {
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+                "object": true,
+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "filterRegularExpression",
+                        "read": "filterRegularExpression",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRegularExpression",
+                        "user": false,
+                        "write": "setFilterRegularExpression"
+                    },
+                    {
+                        "bindable": "bindableFilterKeyColumn",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "filterKeyColumn",
+                        "read": "filterKeyColumn",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFilterKeyColumn"
+                    },
+                    {
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "dynamicSortFilter",
+                        "read": "dynamicSortFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDynamicSortFilter"
+                    },
+                    {
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "filterCaseSensitivity",
+                        "notify": "filterCaseSensitivityChanged",
+                        "read": "filterCaseSensitivity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CaseSensitivity",
+                        "user": false,
+                        "write": "setFilterCaseSensitivity"
+                    },
+                    {
+                        "bindable": "bindableSortCaseSensitivity",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "sortCaseSensitivity",
+                        "notify": "sortCaseSensitivityChanged",
+                        "read": "sortCaseSensitivity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CaseSensitivity",
+                        "user": false,
+                        "write": "setSortCaseSensitivity"
+                    },
+                    {
+                        "bindable": "bindableIsSortLocaleAware",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "isSortLocaleAware",
+                        "notify": "sortLocaleAwareChanged",
+                        "read": "isSortLocaleAware",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortLocaleAware"
+                    },
+                    {
+                        "bindable": "bindableSortRole",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "sortRole",
+                        "notify": "sortRoleChanged",
+                        "read": "sortRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSortRole"
+                    },
+                    {
+                        "bindable": "bindableFilterRole",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "filterRole",
+                        "notify": "filterRoleChanged",
+                        "read": "filterRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFilterRole"
+                    },
+                    {
+                        "bindable": "bindableRecursiveFilteringEnabled",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "recursiveFilteringEnabled",
+                        "notify": "recursiveFilteringEnabledChanged",
+                        "read": "isRecursiveFilteringEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRecursiveFilteringEnabled"
+                    },
+                    {
+                        "bindable": "bindableAutoAcceptChildRows",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "autoAcceptChildRows",
+                        "notify": "autoAcceptChildRowsChanged",
+                        "read": "autoAcceptChildRows",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoAcceptChildRows"
+                    }
+                ],
+                "qualifiedClassName": "QSortFilterProxyModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "dynamicSortFilter",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "dynamicSortFilterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filterCaseSensitivity",
+                                "type": "Qt::CaseSensitivity"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "filterCaseSensitivityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sortCaseSensitivity",
+                                "type": "Qt::CaseSensitivity"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sortCaseSensitivityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sortLocaleAware",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sortLocaleAwareChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sortRole",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "sortRoleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filterRole",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "filterRoleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "recursiveFilteringEnabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "recursiveFilteringEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "autoAcceptChildRows",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "autoAcceptChildRowsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pattern",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setFilterRegularExpression",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "regularExpression",
+                                "type": "QRegularExpression"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setFilterRegularExpression",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pattern",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setFilterWildcard",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pattern",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setFilterFixedString",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "invalidate",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QAbstractProxyModel"
+                    }
+                ]
+            }
+        ],
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+                        "isFlag": false,
+                        "name": "StandardLocation",
+                        "values": [
+                            "DesktopLocation",
+                            "DocumentsLocation",
+                            "FontsLocation",
+                            "ApplicationsLocation",
+                            "MusicLocation",
+                            "MoviesLocation",
+                            "PicturesLocation",
+                            "TempLocation",
+                            "HomeLocation",
+                            "AppLocalDataLocation",
+                            "CacheLocation",
+                            "GenericDataLocation",
+                            "RuntimeLocation",
+                            "ConfigLocation",
+                            "DownloadLocation",
+                            "GenericCacheLocation",
+                            "GenericConfigLocation",
+                            "AppDataLocation",
+                            "AppConfigLocation",
+                            "PublicShareLocation",
+                            "TemplatesLocation",
+                            "StateLocation",
+                            "GenericStateLocation"
+                        ]
+                    },
+                    {
+                        "alias": "LocateOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "LocateOptions",
+                        "values": [
+                            "LocateFile",
+                            "LocateDirectory"
+                        ]
+                    }
+                ],
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+                "lineNumber": 15,
+                "qualifiedClassName": "QStandardPaths"
+            }
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "object": true,
+                "qualifiedClassName": "QStringListModel",
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+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstringlistmodel.h",
+        "outputRevision": 68
+    },
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+                "className": "QSystemSemaphore",
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+                        "isFlag": false,
+                        "name": "AccessMode",
+                        "values": [
+                            "Open",
+                            "Create"
+                        ]
+                    }
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+                "qualifiedClassName": "QSystemSemaphore"
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+    },
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+        "classes": [
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+                "className": "QTemporaryFile",
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+                "object": true,
+                "qualifiedClassName": "QTemporaryFile",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFile"
+                    }
+                ]
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+    },
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+                "className": "QDeviceClosedNotifier",
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+                "object": true,
+                "qualifiedClassName": "QDeviceClosedNotifier",
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+                        "index": 0,
+                        "name": "flushStream",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+    },
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+                "object": true,
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+                        "name": "started",
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+                                "type": "Priority"
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+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "retcode",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
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+                        "isCloned": true,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "quit",
+                        "returnType": "void"
+                    }
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+                        "access": "public",
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+                        "name": "expiryTimeout",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setExpiryTimeout"
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+                        "name": "maxThreadCount",
+                        "read": "maxThreadCount",
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+                        "user": false,
+                        "write": "setMaxThreadCount"
+                    },
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+                        "final": false,
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+                        "type": "int",
+                        "user": false
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+                        "final": false,
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+                        "name": "stackSize",
+                        "read": "stackSize",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "uint",
+                        "user": false,
+                        "write": "setStackSize"
+                    },
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+                        "user": false,
+                        "write": "setThreadPriority"
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+                "object": true,
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "duration",
+                        "read": "duration",
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+                        "scriptable": true,
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+                        "type": "int",
+                        "user": false,
+                        "write": "setDuration"
+                    },
+                    {
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "read": "updateInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setUpdateInterval"
+                    },
+                    {
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+                        "constant": false,
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentTime"
+                    },
+                    {
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "read": "direction",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Direction",
+                        "user": false,
+                        "write": "setDirection"
+                    },
+                    {
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "read": "loopCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLoopCount"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "read": "easingCurve",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QEasingCurve",
+                        "user": false,
+                        "write": "setEasingCurve"
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+                ],
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+                "signals": [
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+                        "arguments": [
+                            {
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+                                "type": "int"
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newState",
+                                "type": "QTimeLine::State"
+                            }
+                        ],
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+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "finished",
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+                    {
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+                    {
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "paused",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "setPaused",
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+                    },
+                    {
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+                        "arguments": [
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+                                "name": "msec",
+                                "type": "int"
+                            }
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+                        "name": "setCurrentTime",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "toggleDirection",
+                        "returnType": "void"
+                    }
+                ],
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+                ]
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+                "object": true,
+                "properties": [
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "singleShot",
+                        "read": "isSingleShot",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSingleShot"
+                    },
+                    {
+                        "bindable": "bindableInterval",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "interval",
+                        "read": "interval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "remainingTime",
+                        "read": "remainingTime",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableTimerType",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "timerType",
+                        "read": "timerType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TimerType",
+                        "user": false,
+                        "write": "setTimerType"
+                    },
+                    {
+                        "bindable": "bindableActive",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "active",
+                        "read": "isActive",
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+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QTimer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "timeout",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msec",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "stop",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtimer.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNativeIpcKey",
+                "enums": [
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+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Type",
+                        "type": "quint16",
+                        "values": [
+                            "SystemV",
+                            "PosixRealtime",
+                            "Windows"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 17,
+                "qualifiedClassName": "QNativeIpcKey"
+            }
+        ],
+        "inputFile": "qtipccommon.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTranslator",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QTranslator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtranslator.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTransposeProxyModel",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QTransposeProxyModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractProxyModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtransposeproxymodel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QVariantAnimation",
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "startValue",
+                        "read": "startValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setStartValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "endValue",
+                        "read": "endValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setEndValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentValue",
+                        "notify": "valueChanged",
+                        "read": "currentValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableDuration",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "duration",
+                        "read": "duration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDuration"
+                    },
+                    {
+                        "bindable": "bindableEasingCurve",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "easingCurve",
+                        "read": "easingCurve",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QEasingCurve",
+                        "user": false,
+                        "write": "setEasingCurve"
+                    }
+                ],
+                "qualifiedClassName": "QVariantAnimation",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractAnimation"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qvariantanimation.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsPipeReader",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QWindowsPipeReader",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "ulong"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "winError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "pipeClosed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowspipereader_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsPipeWriter",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QWindowsPipeWriter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "bytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "writeFailed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowspipewriter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWinEventNotifier",
+                "lineNumber": 14,
+                "object": true,
+                "qualifiedClassName": "QWinEventNotifier",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "hEvent",
+                                "type": "HANDLE"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwineventnotifier.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEmptyItemModel",
+                "lineNumber": 693,
+                "object": true,
+                "qualifiedClassName": "QEmptyItemModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractitemmodel.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsRemovableDriveListener",
+                "lineNumber": 57,
+                "object": true,
+                "qualifiedClassName": "QWindowsRemovableDriveListener",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "driveAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "driveRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "driveRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "driveLockForRemoval",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "driveLockForRemovalFailed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QAbstractNativeEventFilter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemwatcher_win.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QObjectContinuationWrapper",
+                "lineNumber": 43,
+                "object": true,
+                "qualifiedClassName": "QObjectContinuationWrapper",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "run",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfutureinterface.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QThreadPoolThread",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QThreadPoolThread",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qthreadpool.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QObject",
+                "constructors": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "QObject",
+                        "returnType": ""
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "QObject",
+                        "returnType": ""
+                    }
+                ],
+                "lineNumber": 102,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableObjectName",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "objectName",
+                        "notify": "objectNameChanged",
+                        "read": "objectName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setObjectName"
+                    }
+                ],
+                "qualifiedClassName": "QObject",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "destroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "destroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "objectName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "objectNameChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "deleteLater",
+                        "returnType": "void"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qobject.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6dbus_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6dbus_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..37c164b91e6044b2f2c93f6a86103c6bfd36a54c
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6dbus_metatypes.json
@@ -0,0 +1,1069 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QDBusAbstractAdaptor",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QDBusAbstractAdaptor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusabstractadaptor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusAdaptorConnector",
+                "lineNumber": 56,
+                "object": true,
+                "qualifiedClassName": "QDBusAdaptorConnector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "obj",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "metaObject",
+                                "type": "const QMetaObject*"
+                            },
+                            {
+                                "name": "sid",
+                                "type": "int"
+                            },
+                            {
+                                "name": "args",
+                                "type": "QVariantList"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "relaySignal",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "relaySlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "polish",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusabstractadaptor_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusAbstractInterface",
+                "lineNumber": 42,
+                "object": true,
+                "qualifiedClassName": "QDBusAbstractInterface",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "_q_serviceOwnerChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDBusAbstractInterfaceBase"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusabstractinterface.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusConnection",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BusType",
+                        "values": [
+                            "SessionBus",
+                            "SystemBus",
+                            "ActivationBus"
+                        ]
+                    },
+                    {
+                        "alias": "RegisterOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "RegisterOptions",
+                        "values": [
+                            "ExportAdaptors",
+                            "ExportScriptableSlots",
+                            "ExportScriptableSignals",
+                            "ExportScriptableProperties",
+                            "ExportScriptableInvokables",
+                            "ExportScriptableContents",
+                            "ExportNonScriptableSlots",
+                            "ExportNonScriptableSignals",
+                            "ExportNonScriptableProperties",
+                            "ExportNonScriptableInvokables",
+                            "ExportNonScriptableContents",
+                            "ExportAllSlots",
+                            "ExportAllSignals",
+                            "ExportAllProperties",
+                            "ExportAllInvokables",
+                            "ExportAllContents",
+                            "ExportAllSignal",
+                            "ExportChildObjects"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "UnregisterMode",
+                        "values": [
+                            "UnregisterNode",
+                            "UnregisterTree"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 41,
+                "qualifiedClassName": "QDBusConnection"
+            }
+        ],
+        "inputFile": "qdbusconnection.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusConnectionPrivate",
+                "lineNumber": 74,
+                "object": true,
+                "qualifiedClassName": "QDBusConnectionPrivate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "dispatchStatusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msg",
+                                "type": "QDBusMessage"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "spyHooksFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pcall",
+                                "type": "QDBusPendingCallPrivate*"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "void*"
+                            },
+                            {
+                                "name": "timeout",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "messageNeedsSending",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pcall",
+                                "type": "QDBusPendingCallPrivate*"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "void*"
+                            }
+                        ],
+                        "index": 3,
+                        "isCloned": true,
+                        "name": "messageNeedsSending",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldOwner",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newOwner",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "serviceOwnerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QDBusError"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QDBusMessage"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "callWithCallbackFailed",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setDispatchEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "doDispatch",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qintptr"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "socketRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qintptr"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "socketWrite",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "o",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "objectDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "obj",
+                                "type": "QObject*"
+                            },
+                            {
+                                "type": "const QMetaObject*"
+                            },
+                            {
+                                "name": "signalId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "args",
+                                "type": "QVariantList"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "relaySignal",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldOwner",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newOwner",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "serviceOwnerChangedNoLock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "registerServiceNoLock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "unregisterServiceNoLock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "handleDBusDisconnection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusconnection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusConnectionInterface",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ServiceQueueOptions",
+                        "values": [
+                            "DontQueueService",
+                            "QueueService",
+                            "ReplaceExistingService"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ServiceReplacementOptions",
+                        "values": [
+                            "DontAllowReplacement",
+                            "AllowReplacement"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RegisterServiceReply",
+                        "values": [
+                            "ServiceNotRegistered",
+                            "ServiceRegistered",
+                            "ServiceQueued"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "registeredServiceNames",
+                        "read": "registeredServiceNames",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDBusReply<QStringList>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "activatableServiceNames",
+                        "read": "activatableServiceNames",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDBusReply<QStringList>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QDBusConnectionInterface",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "service",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "serviceRegistered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "service",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "serviceUnregistered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldOwner",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newOwner",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "serviceOwnerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QDBusError"
+                            },
+                            {
+                                "name": "call",
+                                "type": "QDBusMessage"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "callWithCallbackFailed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "NameAcquired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "NameLost",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "NameOwnerChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "registeredServiceNames",
+                        "returnType": "QDBusReply<QStringList>"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "activatableServiceNames",
+                        "returnType": "QDBusReply<QStringList>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "isServiceRegistered",
+                        "returnType": "QDBusReply<bool>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "serviceOwner",
+                        "returnType": "QDBusReply<QString>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "unregisterService",
+                        "returnType": "QDBusReply<bool>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "qoption",
+                                "type": "ServiceQueueOptions"
+                            },
+                            {
+                                "name": "roption",
+                                "type": "ServiceReplacementOptions"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "registerService",
+                        "returnType": "QDBusReply<QDBusConnectionInterface::RegisterServiceReply>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "qoption",
+                                "type": "ServiceQueueOptions"
+                            }
+                        ],
+                        "index": 13,
+                        "isCloned": true,
+                        "name": "registerService",
+                        "returnType": "QDBusReply<QDBusConnectionInterface::RegisterServiceReply>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 14,
+                        "isCloned": true,
+                        "name": "registerService",
+                        "returnType": "QDBusReply<QDBusConnectionInterface::RegisterServiceReply>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "servicePid",
+                        "returnType": "QDBusReply<uint>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "serviceName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "serviceUid",
+                        "returnType": "QDBusReply<uint>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "startService",
+                        "returnType": "QDBusReply<void>"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDBusAbstractInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusconnectioninterface.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusConnectionManager",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QDBusConnectionManager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDaemonThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusconnectionmanager_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusError",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ErrorType",
+                        "values": [
+                            "NoError",
+                            "Other",
+                            "Failed",
+                            "NoMemory",
+                            "ServiceUnknown",
+                            "NoReply",
+                            "BadAddress",
+                            "NotSupported",
+                            "LimitsExceeded",
+                            "AccessDenied",
+                            "NoServer",
+                            "Timeout",
+                            "NoNetwork",
+                            "AddressInUse",
+                            "Disconnected",
+                            "InvalidArgs",
+                            "UnknownMethod",
+                            "TimedOut",
+                            "InvalidSignature",
+                            "UnknownInterface",
+                            "UnknownObject",
+                            "UnknownProperty",
+                            "PropertyReadOnly",
+                            "InternalError",
+                            "InvalidService",
+                            "InvalidObjectPath",
+                            "InvalidInterface",
+                            "InvalidMember",
+                            "LastErrorType"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 20,
+                "qualifiedClassName": "QDBusError"
+            }
+        ],
+        "inputFile": "qdbuserror.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusPendingCallWatcher",
+                "lineNumber": 60,
+                "object": true,
+                "qualifiedClassName": "QDBusPendingCallWatcher",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "self",
+                                "type": "QDBusPendingCallWatcher*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "finished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDBusPendingCall"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbuspendingcall.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusPendingCallWatcherHelper",
+                "lineNumber": 76,
+                "object": true,
+                "qualifiedClassName": "QDBusPendingCallWatcherHelper",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msg",
+                                "type": "QDBusMessage"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "reply",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QDBusError"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QDBusMessage"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "error",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbuspendingcall_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusServer",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QDBusServer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "connection",
+                                "type": "QDBusConnection"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "newConnection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusserver.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusServiceWatcher",
+                "enums": [
+                    {
+                        "alias": "WatchModeFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "WatchMode",
+                        "values": [
+                            "WatchForRegistration",
+                            "WatchForUnregistration",
+                            "WatchForOwnerChange"
+                        ]
+                    }
+                ],
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableWatchedServices",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "watchedServices",
+                        "read": "watchedServices",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setWatchedServices"
+                    },
+                    {
+                        "bindable": "bindableWatchMode",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "watchMode",
+                        "read": "watchMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WatchMode",
+                        "user": false,
+                        "write": "setWatchMode"
+                    }
+                ],
+                "qualifiedClassName": "QDBusServiceWatcher",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "service",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "serviceRegistered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "service",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "serviceUnregistered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "service",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldOwner",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newOwner",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "serviceOwnerChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "_q_serviceOwnerChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusservicewatcher.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDBusVirtualObject",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QDBusVirtualObject",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdbusvirtualobject.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6designer_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6designer_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..328d4e1e0355bece3b4eddc743b0eee0de5c6028
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6designer_metatypes.json
@@ -0,0 +1,7772 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QtColorButton",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    }
+                ],
+                "qualifiedClassName": "QtColorButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setColor",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QToolButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcolorbutton_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtColorLine",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ColorComponent",
+                        "values": [
+                            "Red",
+                            "Green",
+                            "Blue",
+                            "Hue",
+                            "Saturation",
+                            "Value",
+                            "Alpha"
+                        ]
+                    }
+                ],
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "indicatorSpace",
+                        "read": "indicatorSpace",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndicatorSpace"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "indicatorSize",
+                        "read": "indicatorSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndicatorSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "flip",
+                        "read": "flip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFlip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "colorComponent",
+                        "read": "colorComponent",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ColorComponent",
+                        "user": false,
+                        "write": "setColorComponent"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "orientation",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    }
+                ],
+                "qualifiedClassName": "QtColorLine",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setColor",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcolorline_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientDialog",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "gradient",
+                        "read": "gradient",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGradient",
+                        "user": false,
+                        "write": "setGradient"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "detailsVisible",
+                        "read": "detailsVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDetailsVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "detailsButtonVisible",
+                        "read": "isDetailsButtonVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDetailsButtonVisible"
+                    }
+                ],
+                "qualifiedClassName": "QtGradientDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientEditor",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "gradient",
+                        "read": "gradient",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGradient",
+                        "user": false,
+                        "write": "setGradient"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "detailsVisible",
+                        "read": "detailsVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDetailsVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "detailsButtonVisible",
+                        "read": "isDetailsButtonVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDetailsButtonVisible"
+                    }
+                ],
+                "qualifiedClassName": "QtGradientEditor",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "gradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "gradientChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "details",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "extenstionWidthHint",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "aboutToShowDetails",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradienteditor_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientManager",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QtGradientManager",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "gradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "gradientAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newId",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "gradientRenamed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newGradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "gradientChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "gradientRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "gradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "addGradient",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newId",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "renameGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newGradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "changeGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "removeGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientmanager_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientStopsController",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QtGradientStopsController",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stops",
+                                "type": "QGradientStops"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "gradientStopsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientstopscontroller_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientStopsModel",
+                "lineNumber": 43,
+                "object": true,
+                "qualifiedClassName": "QtGradientStopsModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "stopAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "stopRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            },
+                            {
+                                "name": "newPos",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "stopMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop1",
+                                "type": "QtGradientStop*"
+                            },
+                            {
+                                "name": "stop2",
+                                "type": "QtGradientStop*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "stopsSwapped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            },
+                            {
+                                "name": "newColor",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "stopChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            },
+                            {
+                                "name": "selected",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "stopSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stop",
+                                "type": "QtGradientStop*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "currentStopChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientstopsmodel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientStopsWidget",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    }
+                ],
+                "qualifiedClassName": "QtGradientStopsWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "zoom",
+                                "type": "double"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "zoomChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientstopswidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientView",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QtGradientView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentGradientChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "gradientActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "gradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "slotGradientAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newId",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "slotGradientRenamed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newGradient",
+                                "type": "QGradient"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "slotGradientChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "slotGradientRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "slotNewGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "slotEditGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "slotRemoveGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "slotRenameGradient",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "slotRenameGradientItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "slotCurrentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "slotGradientActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientview_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientViewDialog",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QtGradientViewDialog",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "slotGradientSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "slotGradientActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtgradientviewdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtGradientWidget",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    }
+                ],
+                "qualifiedClassName": "QtGradientWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "startLinearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "endLinearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "centralRadialChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "focalRadialChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "radius",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "radiusRadialChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "centralConicalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "angle",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "angleConicalChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stops",
+                                "type": "QGradientStops"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setGradientStops",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
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+                                "type": "int"
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+                                "type": "bool"
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "code",
+                                "type": "int"
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+                                "name": "text",
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+                                "type": "bool"
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+                                "name": "item",
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+                                "name": "menu",
+                                "type": "QMenu*"
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+                                "name": "filter",
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+                        "name": "mainContainerChanged",
+                        "returnType": "void"
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+            {
+                "className": "WizardPageChangeWatcher",
+                "lineNumber": 169,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::WizardPageChangeWatcher",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pageChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "widgetfactory.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6designercomponentsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6designercomponentsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..92711ec7f2a9a1dfc93794ca4c95d7658bc54b02
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6designercomponentsprivate_metatypes.json
@@ -0,0 +1,7978 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QtColorButton",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "backgroundCheckered",
+                        "read": "isBackgroundCheckered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundCheckered"
+                    }
+                ],
+                "qualifiedClassName": "QtColorButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setColor",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QToolButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcolorbutton_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "BuddyEditor",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::BuddyEditor",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "updateBackground",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "widgetRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "autoBuddy",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::ConnectionEdit",
+                        "name": "ConnectionEdit"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "buddyeditor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "BuddyEditorPlugin",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerFormEditorPluginInterface",
+                            "id": "\"org.qt-project.Qt.Designer.QDesignerFormEditorPluginInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::BuddyEditorPlugin",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activeFormWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "addFormWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "removeFormWindow",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerFormEditorPluginInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "buddyeditor_plugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "BuddyEditorTool",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::BuddyEditorTool",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDesignerFormWindowToolInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "buddyeditor_tool.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ButtonGroupMenu",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ButtonGroupMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "selectGroup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "breakGroup",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "ButtonGroupTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
+                    ]
+                ],
+                "lineNumber": 53,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ButtonGroupTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            },
+            {
+                "className": "ButtonTaskMenu",
+                "lineNumber": 71,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ButtonTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "createGroup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "a",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "addToGroup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "removeFromGroup",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            },
+            {
+                "className": "CommandLinkButtonTaskMenu",
+                "lineNumber": 117,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::CommandLinkButtonTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::ButtonTaskMenu",
+                        "name": "ButtonTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "button_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ComboBoxTaskMenu",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ComboBoxTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "editItems",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "combobox_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ContainerWidgetTaskMenu",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ContainerWidgetTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "removeCurrentPage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "addPage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "addPageAfter",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            },
+            {
+                "className": "WizardContainerWidgetTaskMenu",
+                "lineNumber": 72,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::WizardContainerWidgetTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::ContainerWidgetTaskMenu",
+                        "name": "ContainerWidgetTaskMenu"
+                    }
+                ]
+            },
+            {
+                "className": "MdiContainerWidgetTaskMenu",
+                "lineNumber": 87,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::MdiContainerWidgetTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::ContainerWidgetTaskMenu",
+                        "name": "ContainerWidgetTaskMenu"
+                    }
+                ]
+            },
+            {
+                "className": "ContainerWidgetTaskMenuFactory",
+                "lineNumber": 102,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ContainerWidgetTaskMenuFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QExtensionFactory"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "containerwidget_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "GroupBoxTaskMenu",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::GroupBoxTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "groupbox_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "InPlaceEditor",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::InPlaceEditor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::TextPropertyEditor",
+                        "name": "TextPropertyEditor"
+                    }
+                ]
+            },
+            {
+                "className": "TaskMenuInlineEditor",
+                "lineNumber": 40,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TaskMenuInlineEditor",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "editText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "updateText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "inplace_editor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "InPlaceWidgetHelper",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::InPlaceWidgetHelper",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "inplace_widget_helper.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "AbstractItemEditor",
+                "lineNumber": 40,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::AbstractItemEditor",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "cacheReloaded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "property",
+                                "type": "QtProperty*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "propertyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "property",
+                                "type": "QtProperty*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "resetProperty",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "ItemListEditor",
+                "lineNumber": 87,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ItemListEditor",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            },
+                            {
+                                "name": "role",
+                                "type": "int"
+                            },
+                            {
+                                "name": "v",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "itemInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "itemDeleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "itemMovedUp",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "itemMovedDown",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "newListItemButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "deleteListItemButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "moveListItemUpButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "moveListItemDownButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "listWidgetCurrentRowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "listWidgetItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 12,
+                        "name": "togglePropertyBrowser",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 13,
+                        "name": "cacheReloaded",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::AbstractItemEditor",
+                        "name": "AbstractItemEditor"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "itemlisteditor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LabelTaskMenu",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::LabelTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "editRichText",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "label_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LayoutWidgetTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
+                    ]
+                ],
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "LayoutWidgetTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            },
+            {
+                "className": "SpacerTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
+                    ]
+                ],
+                "lineNumber": 38,
+                "object": true,
+                "qualifiedClassName": "SpacerTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "layouttaskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LineEditTaskMenu",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::LineEditTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "lineedit_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ListWidgetTaskMenu",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ListWidgetTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "editItems",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "listwidget_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ListWidgetEditor",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::ListWidgetEditor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "listwidgeteditor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "MenuTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
+                    ]
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::MenuTaskMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "removeMenu",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            },
+            {
+                "className": "MenuBarTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::MenuBarTaskMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "menutaskmenu.h",
+        "outputRevision": 68
+    },
+    {
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+                "className": "TableWidgetTaskMenu",
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TableWidgetTaskMenu",
+                "slots": [
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+                        "index": 0,
+                        "name": "editItems",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "tablewidget_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "TableWidgetEditor",
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TableWidgetEditor",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "currentRow",
+                                "type": "int"
+                            },
+                            {
+                                "name": "currentCol",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "tableWidgetCurrentCellChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "tableWidgetItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            },
+                            {
+                                "name": "role",
+                                "type": "int"
+                            },
+                            {
+                                "name": "v",
+                                "type": "QVariant"
+                            }
+                        ],
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+                        "name": "columnEditorItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemDeleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemMovedUp",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemMovedDown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowEditorIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            },
+                            {
+                                "name": "role",
+                                "type": "int"
+                            },
+                            {
+                                "name": "v",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "rowEditorItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowEditorItemInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowEditorItemDeleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "rowEditorItemMovedUp",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "rowEditorItemMovedDown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 14,
+                        "name": "togglePropertyBrowser",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "cacheReloaded",
+                        "returnType": "void"
+                    }
+                ],
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+                        "fullyQualifiedName": "qdesigner_internal::AbstractItemEditor",
+                        "name": "AbstractItemEditor"
+                    }
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+            },
+            {
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TableWidgetEditorDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "tablewidgeteditor.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "TaskMenuComponent",
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TaskMenuComponent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "taskmenu_component.h",
+        "outputRevision": 68
+    },
+    {
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TextEditTaskMenu",
+                "slots": [
+                    {
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+                        "index": 0,
+                        "name": "editText",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "textedit_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
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+                "className": "ToolBarTaskMenu",
+                "interfaces": [
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+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
+                        }
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+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
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+            {
+                "className": "StatusBarTaskMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerTaskMenuExtension",
+                            "id": "\"org.qt-project.Qt.Designer.TaskMenu\""
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::StatusBarTaskMenu",
+                "slots": [
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+                        "access": "private",
+                        "index": 0,
+                        "name": "removeStatusBar",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerTaskMenuExtension"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "toolbar_taskmenu.h",
+        "outputRevision": 68
+    },
+    {
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TreeWidgetTaskMenu",
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+                        "index": 0,
+                        "name": "editItems",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "qdesigner_internal::QDesignerTaskMenu",
+                        "name": "QDesignerTaskMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "treewidget_taskmenu.h",
+        "outputRevision": 68
+    },
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+                "qualifiedClassName": "qdesigner_internal::TreeWidgetEditor",
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+                        "name": "newItemButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "newSubItemButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "deleteItemButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
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+                        "name": "moveItemUpButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
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+                        "name": "moveItemDownButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "moveItemRightButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "moveItemLeftButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "treeWidgetCurrentItemChanged",
+                        "returnType": "void"
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+                    {
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+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "treeWidgetItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
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+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorIndexChanged",
+                        "returnType": "void"
+                    },
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+                        "arguments": [
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+                                "name": "idx",
+                                "type": "int"
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+                            {
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+                                "type": "int"
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+                            {
+                                "name": "v",
+                                "type": "QVariant"
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+                        ],
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+                        "name": "columnEditorItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemInserted",
+                        "returnType": "void"
+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemDeleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemMovedUp",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "columnEditorItemMovedDown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
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+                        "name": "togglePropertyBrowser",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 16,
+                        "name": "cacheReloaded",
+                        "returnType": "void"
+                    }
+                ],
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+                        "name": "AbstractItemEditor"
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+            {
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+                "superClasses": [
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+                    }
+                ]
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+        ],
+        "inputFile": "treewidgeteditor.h",
+        "outputRevision": 68
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+                        "arguments": [
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+                                "type": "QString"
+                            },
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+                                "name": "xml",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "global_mouse_pos",
+                                "type": "QPoint"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "handleMousePress",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
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+                    },
+                    {
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+                                "type": "QString"
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+                                "type": "QString"
+                            },
+                            {
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+                                "type": "QPoint"
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+                        ],
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+                        "name": "widgetBoxPressed",
+                        "returnType": "void"
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+                    {
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+                        "name": "itemRemoved",
+                        "returnType": "void"
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+                        "name": "lastItemRemoved",
+                        "returnType": "void"
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+                        "arguments": [
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+                                "type": "QString"
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+                                "type": "Qt::CaseSensitivity"
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+                        "returnType": "void"
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+                    {
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+                        "name": "editCurrentItem",
+                        "returnType": "void"
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+                    {
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+                                "type": "QModelIndex"
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+                        "name": "slotPressed",
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+                        "name": "QListView"
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+                                "type": "QString"
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+                                "type": "QString"
+                            },
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+                                "type": "QPoint"
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+                    },
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+                        "name": "slotLastScratchPadItemDeleted",
+                        "returnType": "void"
+                    },
+                    {
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+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
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+                        "name": "handleMousePress",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "deleteScratchpad",
+                        "returnType": "void"
+                    },
+                    {
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+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "slotIconMode",
+                        "returnType": "void"
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+                ],
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+                        "name": "QTreeWidget"
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+                        "name": "load",
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+                    }
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QPalette"
+                            }
+                        ],
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+                        "name": "paletteChanged",
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+                                "name": "widget",
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+                                "name": "widget",
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+                                "name": "palette",
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+                                "name": "palette",
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+                                "name": "path",
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+                                "name": "pixmap",
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+                                "name": "icon",
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+                        "name": "updateDialogSelection",
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+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
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+                        "name": "updateEditorSelection",
+                        "returnType": "void"
+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            },
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "newName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldName",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "objectNameChanged",
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+                    },
+                    {
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+                        "name": "addConnection",
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+                    },
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+                        "name": "removeConnection",
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+                    },
+                    {
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+                        "name": "updateUi",
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+                    },
+                    {
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+                        "index": 7,
+                        "name": "resizeColumns",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
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+        ],
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+    },
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+                        "name": "activate",
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+                    },
+                    {
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+                        "index": 1,
+                        "name": "deactivate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "findNext",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "findPrevious",
+                        "returnType": "void"
+                    },
+                    {
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+                        "index": 4,
+                        "name": "findCurrentText",
+                        "returnType": "void"
+                    },
+                    {
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+                        "index": 5,
+                        "name": "updateButtons",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
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+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "ItemViewFindWidget",
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+                "object": true,
+                "qualifiedClassName": "ItemViewFindWidget",
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+                    {
+                        "access": "public",
+                        "name": "AbstractFindWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "itemviewfindwidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "TextEditFindWidget",
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+                "qualifiedClassName": "TextEditFindWidget",
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+                    {
+                        "access": "public",
+                        "name": "AbstractFindWidget"
+                    }
+                ]
+            }
+        ],
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+    },
+    {
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+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TextEditor",
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+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "textChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
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+                        "name": "setText",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "resourceActionActivated",
+                        "returnType": "void"
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+                        "name": "fileActionActivated",
+                        "returnType": "void"
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+                    }
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+                                "name": "property",
+                                "type": "QtProperty*"
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+                        "name": "slotClicked",
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+                    }
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+                        "name": "populateLists",
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+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
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+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
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+                        "name": "selectSignal",
+                        "returnType": "void"
+                    },
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+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
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+                    },
+                    {
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+                        "name": "populateSignalList",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "signal",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "populateSlotList",
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+                    },
+                    {
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+                        "name": "populateSlotList",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "editSignals",
+                        "returnType": "void"
+                    },
+                    {
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+                        "index": 7,
+                        "name": "editSlots",
+                        "returnType": "void"
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+                ],
+                "superClasses": [
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+                        "name": "QDialog"
+                    }
+                ]
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+        "outputRevision": 68
+    },
+    {
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+                "object": true,
+                "qualifiedClassName": "QtButtonPropertyBrowser",
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QtBrowserItem*"
+                            }
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+                        "name": "collapsed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                            {
+                                "name": "item",
+                                "type": "QtBrowserItem*"
+                            }
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+                        "name": "expanded",
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+                    }
+                ]
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+                        "access": "public",
+                        "name": "QtAbstractEditorFactory<QtIntPropertyManager>"
+                    }
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+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "addFormWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "removeFormWindow",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerFormEditorPluginInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "signalsloteditor_plugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TabOrderEditorPlugin",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QDesignerFormEditorPluginInterface",
+                            "id": "\"org.qt-project.Qt.Designer.QDesignerFormEditorPluginInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "qdesigner_internal::TabOrderEditorPlugin",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activeFormWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "addFormWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "formWindow",
+                                "type": "QDesignerFormWindowInterface*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "removeFormWindow",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QDesignerFormEditorPluginInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "tabordereditor_plugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtColorButtonPrivate",
+                "lineNumber": 14,
+                "object": true,
+                "qualifiedClassName": "QtColorButtonPrivate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcolorbutton.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtCharEdit",
+                "lineNumber": 1461,
+                "object": true,
+                "qualifiedClassName": "QtCharEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QChar"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QChar"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "slotClearChar",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QtColorEditWidget",
+                "lineNumber": 2078,
+                "object": true,
+                "qualifiedClassName": "QtColorEditWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QtFontEditWidget",
+                "lineNumber": 2277,
+                "object": true,
+                "qualifiedClassName": "QtFontEditWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qteditorfactory.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtMetaEnumWrapper",
+                "lineNumber": 359,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "policy",
+                        "read": "policy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizePolicy::Policy",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QtMetaEnumWrapper",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtpropertymanager.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QtPropertyEditorView",
+                "lineNumber": 91,
+                "object": true,
+                "qualifiedClassName": "QtPropertyEditorView",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTreeWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QtPropertyEditorDelegate",
+                "lineNumber": 191,
+                "object": true,
+                "qualifiedClassName": "QtPropertyEditorDelegate",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "slotEditorDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qttreepropertybrowser.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "InlineEditorModel",
+                "lineNumber": 379,
+                "object": true,
+                "qualifiedClassName": "InlineEditorModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStandardItemModel"
+                    }
+                ]
+            },
+            {
+                "className": "InlineEditor",
+                "lineNumber": 467,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setText"
+                    }
+                ],
+                "qualifiedClassName": "InlineEditor",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "checkSelection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QComboBox"
+                    }
+                ]
+            },
+            {
+                "className": "ConnectionDelegate",
+                "lineNumber": 540,
+                "object": true,
+                "qualifiedClassName": "ConnectionDelegate",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "emitCommitData",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "signalsloteditorwindow.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6devicediscoverysupportprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6devicediscoverysupportprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..acf46be1c636d182259e735e22ae8bd28faf3043
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6devicediscoverysupportprivate_metatypes.json
@@ -0,0 +1,84 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QDeviceDiscoveryDummy",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QDeviceDiscoveryDummy",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDeviceDiscovery"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdevicediscovery_dummy_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDeviceDiscovery",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "QDeviceType",
+                        "values": [
+                            "Device_Unknown",
+                            "Device_Mouse",
+                            "Device_Touchpad",
+                            "Device_Touchscreen",
+                            "Device_Keyboard",
+                            "Device_DRM",
+                            "Device_DRM_PrimaryGPU",
+                            "Device_Tablet",
+                            "Device_Joystick",
+                            "Device_InputMask",
+                            "Device_VideoMask"
+                        ]
+                    }
+                ],
+                "lineNumber": 33,
+                "object": true,
+                "qualifiedClassName": "QDeviceDiscovery",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "deviceNode",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "deviceDetected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "deviceNode",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "deviceRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdevicediscovery_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6exampleiconsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6exampleiconsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6exampleiconsprivate_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6examplesassetdownloaderprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6examplesassetdownloaderprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..609bb495fa168fd29bf27dfe0fcd2f03932e0491
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6examplesassetdownloaderprivate_metatypes.json
@@ -0,0 +1,566 @@
+[
+    {
+        "classes": [
+            {
+                "className": "Barrier",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "Tasking::Barrier",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "success",
+                                "type": "DoneResult"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "barrier.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "NetworkQuery",
+                "lineNumber": 39,
+                "object": true,
+                "qualifiedClassName": "Tasking::NetworkQuery",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "DoneResult"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "networkquery.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TaskInterface",
+                "lineNumber": 95,
+                "object": true,
+                "qualifiedClassName": "Tasking::TaskInterface",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "DoneResult"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "TaskTree",
+                "lineNumber": 622,
+                "object": true,
+                "qualifiedClassName": "Tasking::TaskTree",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "DoneWith"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "done",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "count",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "asyncCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "progressValueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "Tasking",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "WorkflowPolicy",
+                        "values": [
+                            "StopOnError",
+                            "ContinueOnError",
+                            "StopOnSuccess",
+                            "ContinueOnSuccess",
+                            "StopOnSuccessOrError",
+                            "FinishAllAndSuccess",
+                            "FinishAllAndError"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SetupResult",
+                        "values": [
+                            "Continue",
+                            "StopWithSuccess",
+                            "StopWithError"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "DoneResult",
+                        "values": [
+                            "Success",
+                            "Error"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "DoneWith",
+                        "values": [
+                            "Success",
+                            "Error",
+                            "Cancel"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "CallDoneIf",
+                        "values": [
+                            "SuccessOrError",
+                            "Success",
+                            "Error"
+                        ]
+                    }
+                ],
+                "lineNumber": 30,
+                "namespace": true,
+                "qualifiedClassName": "Tasking"
+            }
+        ],
+        "inputFile": "tasktree.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TaskTreeRunner",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "Tasking::TaskTreeRunner",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "taskTree",
+                                "type": "TaskTree*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "aboutToStart",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "DoneWith"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "tasktreerunner.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TcpSocket",
+                "lineNumber": 35,
+                "object": true,
+                "qualifiedClassName": "Tasking::TcpSocket",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "DoneResult"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "tcpsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "AssetDownloader",
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "downloadBase",
+                        "notify": "downloadBaseChanged",
+                        "read": "downloadBase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setDownloadBase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "preferredLocalDownloadDir",
+                        "notify": "preferredLocalDownloadDirChanged",
+                        "read": "preferredLocalDownloadDir",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setPreferredLocalDownloadDir"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "offlineAssetsFilePath",
+                        "notify": "offlineAssetsFilePathChanged",
+                        "read": "offlineAssetsFilePath",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setOfflineAssetsFilePath"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "jsonFileName",
+                        "notify": "jsonFileNameChanged",
+                        "read": "jsonFileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setJsonFileName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "zipFileName",
+                        "notify": "zipFileNameChanged",
+                        "read": "zipFileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setZipFileName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "localDownloadDir",
+                        "notify": "localDownloadDirChanged",
+                        "read": "localDownloadDir",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "Assets::Downloader::AssetDownloader",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "success",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "progressValue",
+                                "type": "int"
+                            },
+                            {
+                                "name": "progressMaximum",
+                                "type": "int"
+                            },
+                            {
+                                "name": "progressText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "progressChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "localDownloadDirChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "downloadBaseChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "preferredLocalDownloadDirChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "offlineAssetsFilePathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "jsonFileNameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "zipFileNameChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "start",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "assetdownloader.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Reaper",
+                "lineNumber": 52,
+                "object": true,
+                "qualifiedClassName": "Tasking::Reaper",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "ProcessReaperPrivate",
+                "lineNumber": 119,
+                "object": true,
+                "qualifiedClassName": "Tasking::ProcessReaperPrivate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprocesstask.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6fbsupportprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6fbsupportprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..05909d1d0fe1d0fa160a471578ef682e6672b521
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6fbsupportprivate_metatypes.json
@@ -0,0 +1,152 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QFbCursorDeviceListener",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QFbCursorDeviceListener",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QInputDeviceManager::DeviceType"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "onDeviceListChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QFbCursor",
+                "lineNumber": 41,
+                "object": true,
+                "qualifiedClassName": "QFbCursor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformCursor"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfbcursor_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFbScreen",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QFbScreen",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setDirty",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setPhysicalSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setGeometry",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QPlatformScreen"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfbscreen_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFbVtHandler",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QFbVtHandler",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "interrupted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "aboutToSuspend",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "resumed",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "handleSignal",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfbvthandler_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6gui_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6gui_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..f542f1a265f996228fb6d76f20236b1eb6580164
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6gui_metatypes.json
@@ -0,0 +1,9004 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QPlatformScreen",
+                "gadget": true,
+                "lineNumber": 43,
+                "qualifiedClassName": "QPlatformScreen"
+            }
+        ],
+        "inputFile": "qplatformscreen.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractTextDocumentLayout",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QAbstractTextDocumentLayout",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "block",
+                                "type": "QTextBlock"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "updateBlock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newSize",
+                                "type": "QSizeF"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "documentSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newPages",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "pageCountChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_dynamicPageCountSlot",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_dynamicDocumentSizeSlot",
+                        "returnType": "QSizeF"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstracttextdocumentlayout.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAccessible",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Event",
+                        "values": [
+                            "SoundPlayed",
+                            "Alert",
+                            "ForegroundChanged",
+                            "MenuStart",
+                            "MenuEnd",
+                            "PopupMenuStart",
+                            "PopupMenuEnd",
+                            "ContextHelpStart",
+                            "ContextHelpEnd",
+                            "DragDropStart",
+                            "DragDropEnd",
+                            "DialogStart",
+                            "DialogEnd",
+                            "ScrollingStart",
+                            "ScrollingEnd",
+                            "MenuCommand",
+                            "ActionChanged",
+                            "ActiveDescendantChanged",
+                            "AttributeChanged",
+                            "DocumentContentChanged",
+                            "DocumentLoadComplete",
+                            "DocumentLoadStopped",
+                            "DocumentReload",
+                            "HyperlinkEndIndexChanged",
+                            "HyperlinkNumberOfAnchorsChanged",
+                            "HyperlinkSelectedLinkChanged",
+                            "HypertextLinkActivated",
+                            "HypertextLinkSelected",
+                            "HyperlinkStartIndexChanged",
+                            "HypertextChanged",
+                            "HypertextNLinksChanged",
+                            "ObjectAttributeChanged",
+                            "PageChanged",
+                            "SectionChanged",
+                            "TableCaptionChanged",
+                            "TableColumnDescriptionChanged",
+                            "TableColumnHeaderChanged",
+                            "TableModelChanged",
+                            "TableRowDescriptionChanged",
+                            "TableRowHeaderChanged",
+                            "TableSummaryChanged",
+                            "TextAttributeChanged",
+                            "TextCaretMoved",
+                            "TextColumnChanged",
+                            "TextInserted",
+                            "TextRemoved",
+                            "TextUpdated",
+                            "TextSelectionChanged",
+                            "VisibleDataChanged",
+                            "ObjectCreated",
+                            "ObjectDestroyed",
+                            "ObjectShow",
+                            "ObjectHide",
+                            "ObjectReorder",
+                            "Focus",
+                            "Selection",
+                            "SelectionAdd",
+                            "SelectionRemove",
+                            "SelectionWithin",
+                            "StateChanged",
+                            "LocationChanged",
+                            "NameChanged",
+                            "DescriptionChanged",
+                            "ValueChanged",
+                            "ParentChanged",
+                            "HelpChanged",
+                            "DefaultActionChanged",
+                            "AcceleratorChanged",
+                            "Announcement",
+                            "IdentifierChanged",
+                            "InvalidEvent"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Role",
+                        "values": [
+                            "NoRole",
+                            "TitleBar",
+                            "MenuBar",
+                            "ScrollBar",
+                            "Grip",
+                            "Sound",
+                            "Cursor",
+                            "Caret",
+                            "AlertMessage",
+                            "Window",
+                            "Client",
+                            "PopupMenu",
+                            "MenuItem",
+                            "ToolTip",
+                            "Application",
+                            "Document",
+                            "Pane",
+                            "Chart",
+                            "Dialog",
+                            "Border",
+                            "Grouping",
+                            "Separator",
+                            "ToolBar",
+                            "StatusBar",
+                            "Table",
+                            "ColumnHeader",
+                            "RowHeader",
+                            "Column",
+                            "Row",
+                            "Cell",
+                            "Link",
+                            "HelpBalloon",
+                            "Assistant",
+                            "List",
+                            "ListItem",
+                            "Tree",
+                            "TreeItem",
+                            "PageTab",
+                            "PropertyPage",
+                            "Indicator",
+                            "Graphic",
+                            "StaticText",
+                            "EditableText",
+                            "Button",
+                            "PushButton",
+                            "CheckBox",
+                            "RadioButton",
+                            "ComboBox",
+                            "ProgressBar",
+                            "Dial",
+                            "HotkeyField",
+                            "Slider",
+                            "SpinBox",
+                            "Canvas",
+                            "Animation",
+                            "Equation",
+                            "ButtonDropDown",
+                            "ButtonMenu",
+                            "ButtonDropGrid",
+                            "Whitespace",
+                            "PageTabList",
+                            "Clock",
+                            "Splitter",
+                            "LayeredPane",
+                            "Terminal",
+                            "Desktop",
+                            "Paragraph",
+                            "WebDocument",
+                            "Section",
+                            "Notification",
+                            "ColorChooser",
+                            "Footer",
+                            "Form",
+                            "Heading",
+                            "Note",
+                            "ComplementaryContent",
+                            "UserRole"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Attribute",
+                        "values": [
+                            "Custom",
+                            "Level"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AnnouncementPoliteness",
+                        "values": [
+                            "Polite",
+                            "Assertive"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 25,
+                "qualifiedClassName": "QAccessible"
+            }
+        ],
+        "inputFile": "qaccessible_base.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAccessibleBridgePlugin",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QAccessibleBridgePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qaccessiblebridge.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAccessibleCache",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QAccessibleCache",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "obj",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "objectDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qaccessiblecache_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAccessiblePlugin",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QAccessiblePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qaccessibleplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAction",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MenuRole",
+                        "values": [
+                            "NoRole",
+                            "TextHeuristicRole",
+                            "ApplicationSpecificRole",
+                            "AboutQtRole",
+                            "AboutRole",
+                            "PreferencesRole",
+                            "QuitRole"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Priority",
+                        "values": [
+                            "LowPriority",
+                            "NormalPriority",
+                            "HighPriority"
+                        ]
+                    }
+                ],
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "checkable",
+                        "notify": "checkableChanged",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "checked",
+                        "notify": "toggled",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChecked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "reset": "resetEnabled",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "icon",
+                        "notify": "changed",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "text",
+                        "notify": "changed",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "iconText",
+                        "notify": "changed",
+                        "read": "iconText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setIconText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "toolTip",
+                        "notify": "changed",
+                        "read": "toolTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setToolTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "statusTip",
+                        "notify": "changed",
+                        "read": "statusTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setStatusTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "whatsThis",
+                        "notify": "changed",
+                        "read": "whatsThis",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWhatsThis"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "font",
+                        "notify": "changed",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "shortcut",
+                        "notify": "changed",
+                        "read": "shortcut",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QKeySequence",
+                        "user": false,
+                        "write": "setShortcut"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "shortcutContext",
+                        "notify": "changed",
+                        "read": "shortcutContext",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ShortcutContext",
+                        "user": false,
+                        "write": "setShortcutContext"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "autoRepeat",
+                        "notify": "changed",
+                        "read": "autoRepeat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRepeat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "menuRole",
+                        "notify": "changed",
+                        "read": "menuRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "MenuRole",
+                        "user": false,
+                        "write": "setMenuRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "iconVisibleInMenu",
+                        "notify": "changed",
+                        "read": "isIconVisibleInMenu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIconVisibleInMenu"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "shortcutVisibleInContextMenu",
+                        "notify": "changed",
+                        "read": "isShortcutVisibleInContextMenu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShortcutVisibleInContextMenu"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "priority",
+                        "notify": "changed",
+                        "read": "priority",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Priority",
+                        "user": false,
+                        "write": "setPriority"
+                    }
+                ],
+                "qualifiedClassName": "QAction",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "changed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checkable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "checkableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "isCloned": true,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "hovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "toggled",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "trigger",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "hover",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setChecked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "resetEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "setDisabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "setVisible",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qaction.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QActionGroup",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ExclusionPolicy",
+                        "values": [
+                            "None",
+                            "Exclusive",
+                            "ExclusiveOptional"
+                        ]
+                    }
+                ],
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "exclusionPolicy",
+                        "read": "exclusionPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QActionGroup::ExclusionPolicy",
+                        "user": false,
+                        "write": "setExclusionPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "enabled",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "visible",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    }
+                ],
+                "qualifiedClassName": "QActionGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "hovered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setDisabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setExclusive",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "policy",
+                                "type": "ExclusionPolicy"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setExclusionPolicy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_actionTriggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_actionHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_actionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qactiongroup.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QGradient",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Type",
+                        "values": [
+                            "LinearGradient",
+                            "RadialGradient",
+                            "ConicalGradient",
+                            "NoGradient"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Spread",
+                        "values": [
+                            "PadSpread",
+                            "ReflectSpread",
+                            "RepeatSpread"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CoordinateMode",
+                        "values": [
+                            "LogicalMode",
+                            "StretchToDeviceMode",
+                            "ObjectBoundingMode",
+                            "ObjectMode"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Preset",
+                        "values": [
+                            "WarmFlame",
+                            "NightFade",
+                            "SpringWarmth",
+                            "JuicyPeach",
+                            "YoungPassion",
+                            "LadyLips",
+                            "SunnyMorning",
+                            "RainyAshville",
+                            "FrozenDreams",
+                            "WinterNeva",
+                            "DustyGrass",
+                            "TemptingAzure",
+                            "HeavyRain",
+                            "AmyCrisp",
+                            "MeanFruit",
+                            "DeepBlue",
+                            "RipeMalinka",
+                            "CloudyKnoxville",
+                            "MalibuBeach",
+                            "NewLife",
+                            "TrueSunset",
+                            "MorpheusDen",
+                            "RareWind",
+                            "NearMoon",
+                            "WildApple",
+                            "SaintPetersburg",
+                            "PlumPlate",
+                            "EverlastingSky",
+                            "HappyFisher",
+                            "Blessing",
+                            "SharpeyeEagle",
+                            "LadogaBottom",
+                            "LemonGate",
+                            "ItmeoBranding",
+                            "ZeusMiracle",
+                            "OldHat",
+                            "StarWine",
+                            "HappyAcid",
+                            "AwesomePine",
+                            "NewYork",
+                            "ShyRainbow",
+                            "MixedHopes",
+                            "FlyHigh",
+                            "StrongBliss",
+                            "FreshMilk",
+                            "SnowAgain",
+                            "FebruaryInk",
+                            "KindSteel",
+                            "SoftGrass",
+                            "GrownEarly",
+                            "SharpBlues",
+                            "ShadyWater",
+                            "DirtyBeauty",
+                            "GreatWhale",
+                            "TeenNotebook",
+                            "PoliteRumors",
+                            "SweetPeriod",
+                            "WideMatrix",
+                            "SoftCherish",
+                            "RedSalvation",
+                            "BurningSpring",
+                            "NightParty",
+                            "SkyGlider",
+                            "HeavenPeach",
+                            "PurpleDivision",
+                            "AquaSplash",
+                            "SpikyNaga",
+                            "LoveKiss",
+                            "CleanMirror",
+                            "PremiumDark",
+                            "ColdEvening",
+                            "CochitiLake",
+                            "SummerGames",
+                            "PassionateBed",
+                            "MountainRock",
+                            "DesertHump",
+                            "JungleDay",
+                            "PhoenixStart",
+                            "OctoberSilence",
+                            "FarawayRiver",
+                            "AlchemistLab",
+                            "OverSun",
+                            "PremiumWhite",
+                            "MarsParty",
+                            "EternalConstance",
+                            "JapanBlush",
+                            "SmilingRain",
+                            "CloudyApple",
+                            "BigMango",
+                            "HealthyWater",
+                            "AmourAmour",
+                            "RiskyConcrete",
+                            "StrongStick",
+                            "ViciousStance",
+                            "PaloAlto",
+                            "HappyMemories",
+                            "MidnightBloom",
+                            "Crystalline",
+                            "PartyBliss",
+                            "ConfidentCloud",
+                            "LeCocktail",
+                            "RiverCity",
+                            "FrozenBerry",
+                            "ChildCare",
+                            "FlyingLemon",
+                            "NewRetrowave",
+                            "HiddenJaguar",
+                            "AboveTheSky",
+                            "Nega",
+                            "DenseWater",
+                            "Seashore",
+                            "MarbleWall",
+                            "CheerfulCaramel",
+                            "NightSky",
+                            "MagicLake",
+                            "YoungGrass",
+                            "ColorfulPeach",
+                            "GentleCare",
+                            "PlumBath",
+                            "HappyUnicorn",
+                            "AfricanField",
+                            "SolidStone",
+                            "OrangeJuice",
+                            "GlassWater",
+                            "NorthMiracle",
+                            "FruitBlend",
+                            "MillenniumPine",
+                            "HighFlight",
+                            "MoleHall",
+                            "SpaceShift",
+                            "ForestInei",
+                            "RoyalGarden",
+                            "RichMetal",
+                            "JuicyCake",
+                            "SmartIndigo",
+                            "SandStrike",
+                            "NorseBeauty",
+                            "AquaGuidance",
+                            "SunVeggie",
+                            "SeaLord",
+                            "BlackSea",
+                            "GrassShampoo",
+                            "LandingAircraft",
+                            "WitchDance",
+                            "SleeplessNight",
+                            "AngelCare",
+                            "CrystalRiver",
+                            "SoftLipstick",
+                            "SaltMountain",
+                            "PerfectWhite",
+                            "FreshOasis",
+                            "StrictNovember",
+                            "MorningSalad",
+                            "DeepRelief",
+                            "SeaStrike",
+                            "NightCall",
+                            "SupremeSky",
+                            "LightBlue",
+                            "MindCrawl",
+                            "LilyMeadow",
+                            "SugarLollipop",
+                            "SweetDessert",
+                            "MagicRay",
+                            "TeenParty",
+                            "FrozenHeat",
+                            "GagarinView",
+                            "FabledSunset",
+                            "PerfectBlue",
+                            "NumPresets"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 134,
+                "qualifiedClassName": "QGradient"
+            }
+        ],
+        "inputFile": "qbrush.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QClipboard",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QClipboard",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QClipboard::Mode"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "changed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "findBufferChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "dataChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qclipboard.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QColorSpace",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "NamedColorSpace",
+                        "values": [
+                            "SRgb",
+                            "SRgbLinear",
+                            "AdobeRgb",
+                            "DisplayP3",
+                            "ProPhotoRgb",
+                            "Bt2020",
+                            "Bt2100Pq",
+                            "Bt2100Hlg"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Primaries",
+                        "values": [
+                            "Custom",
+                            "SRgb",
+                            "AdobeRgb",
+                            "DciP3D65",
+                            "ProPhotoRgb",
+                            "Bt2020"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TransferFunction",
+                        "values": [
+                            "Custom",
+                            "Linear",
+                            "Gamma",
+                            "SRgb",
+                            "ProPhotoRgb",
+                            "Bt2020",
+                            "St2084",
+                            "Hlg"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TransformModel",
+                        "type": "uint8_t",
+                        "values": [
+                            "ThreeComponentMatrix",
+                            "ElementListProcessing"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ColorModel",
+                        "type": "uint8_t",
+                        "values": [
+                            "Undefined",
+                            "Rgb",
+                            "Gray",
+                            "Cmyk"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 20,
+                "qualifiedClassName": "QColorSpace"
+            }
+        ],
+        "inputFile": "qcolorspace.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDragManager",
+                "lineNumber": 57,
+                "object": true,
+                "qualifiedClassName": "QDragManager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdnd_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDrag",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QDrag",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "Qt::DropAction"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "actionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newTarget",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdrag.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPointerEvent",
+                "gadget": true,
+                "lineNumber": 72,
+                "qualifiedClassName": "QPointerEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QInputEvent"
+                    }
+                ]
+            },
+            {
+                "className": "QSinglePointEvent",
+                "gadget": true,
+                "lineNumber": 108,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "exclusivePointGrabber",
+                        "read": "exclusivePointGrabber",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false,
+                        "write": "setExclusivePointGrabber"
+                    }
+                ],
+                "qualifiedClassName": "QSinglePointEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPointerEvent"
+                    }
+                ]
+            },
+            {
+                "className": "QWheelEvent",
+                "gadget": true,
+                "lineNumber": 280,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "device",
+                        "read": "pointingDevice",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "const QPointingDevice*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "pixelDelta",
+                        "read": "pixelDelta",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPoint",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "angleDelta",
+                        "read": "angleDelta",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPoint",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "phase",
+                        "read": "phase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScrollPhase",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "inverted",
+                        "read": "inverted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QWheelEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSinglePointEvent"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qevent.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QEventPoint",
+                "enums": [
+                    {
+                        "alias": "State",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "States",
+                        "type": "quint8",
+                        "values": [
+                            "Unknown",
+                            "Stationary",
+                            "Pressed",
+                            "Updated",
+                            "Released"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 19,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "accepted",
+                        "read": "isAccepted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccepted"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "device",
+                        "read": "device",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "const QPointingDevice*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "id",
+                        "read": "id",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "uniqueId",
+                        "read": "uniqueId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointingDeviceUniqueId",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "state",
+                        "read": "state",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "State",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "timestamp",
+                        "read": "timestamp",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ulong",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "pressTimestamp",
+                        "read": "pressTimestamp",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ulong",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "lastTimestamp",
+                        "read": "lastTimestamp",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ulong",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "timeHeld",
+                        "read": "timeHeld",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "pressure",
+                        "read": "pressure",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "rotation",
+                        "read": "rotation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "ellipseDiameters",
+                        "read": "ellipseDiameters",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "velocity",
+                        "read": "velocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVector2D",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "position",
+                        "read": "position",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "pressPosition",
+                        "read": "pressPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "grabPosition",
+                        "read": "grabPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "lastPosition",
+                        "read": "lastPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "scenePosition",
+                        "read": "scenePosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "scenePressPosition",
+                        "read": "scenePressPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "sceneGrabPosition",
+                        "read": "sceneGrabPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "sceneLastPosition",
+                        "read": "sceneLastPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "globalPosition",
+                        "read": "globalPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "globalPressPosition",
+                        "read": "globalPressPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "globalGrabPosition",
+                        "read": "globalGrabPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "globalLastPosition",
+                        "read": "globalLastPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QEventPoint"
+            }
+        ],
+        "inputFile": "qeventpoint.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileInfoGatherer",
+                "lineNumber": 125,
+                "object": true,
+                "qualifiedClassName": "QFileInfoGatherer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "updates",
+                                "type": "QList<std::pair<QString,QFileInfo>>"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "updates",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "listOfFiles",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "newListOfFiles",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "resolvedName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "nameResolved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "directoryLoaded",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directoryPath",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "list",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "files",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "fetchExtendedInformation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "updateFile",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setResolveSymlinks",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "provider",
+                                "type": "QAbstractFileIconProvider*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setIconProvider",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "driveAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "driveRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfileinfogatherer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileSystemModel",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Option",
+                        "values": [
+                            "DontWatchForChanges",
+                            "DontResolveSymlinks",
+                            "DontUseCustomDirectoryIcons"
+                        ]
+                    }
+                ],
+                "lineNumber": 21,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "resolveSymlinks",
+                        "read": "resolveSymlinks",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setResolveSymlinks"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "nameFilterDisables",
+                        "read": "nameFilterDisables",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setNameFilterDisables"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Options",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QFileSystemModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newPath",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "rootPathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "oldName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "newName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "fileRenamed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "directoryLoaded",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilesystemmodel.h",
+        "outputRevision": 68
+    },
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+                "className": "QFont",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StyleHint",
+                        "values": [
+                            "Helvetica",
+                            "SansSerif",
+                            "Times",
+                            "Serif",
+                            "Courier",
+                            "TypeWriter",
+                            "OldEnglish",
+                            "Decorative",
+                            "System",
+                            "AnyStyle",
+                            "Cursive",
+                            "Monospace",
+                            "Fantasy"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StyleStrategy",
+                        "values": [
+                            "PreferDefault",
+                            "PreferBitmap",
+                            "PreferDevice",
+                            "PreferOutline",
+                            "ForceOutline",
+                            "PreferMatch",
+                            "PreferQuality",
+                            "PreferAntialias",
+                            "NoAntialias",
+                            "NoSubpixelAntialias",
+                            "PreferNoShaping",
+                            "ContextFontMerging",
+                            "PreferTypoLineMetrics",
+                            "NoFontMerging"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HintingPreference",
+                        "values": [
+                            "PreferDefaultHinting",
+                            "PreferNoHinting",
+                            "PreferVerticalHinting",
+                            "PreferFullHinting"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Weight",
+                        "values": [
+                            "Thin",
+                            "ExtraLight",
+                            "Light",
+                            "Normal",
+                            "Medium",
+                            "DemiBold",
+                            "Bold",
+                            "ExtraBold",
+                            "Black"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Style",
+                        "values": [
+                            "StyleNormal",
+                            "StyleItalic",
+                            "StyleOblique"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Stretch",
+                        "values": [
+                            "AnyStretch",
+                            "UltraCondensed",
+                            "ExtraCondensed",
+                            "Condensed",
+                            "SemiCondensed",
+                            "Unstretched",
+                            "SemiExpanded",
+                            "Expanded",
+                            "ExtraExpanded",
+                            "UltraExpanded"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Capitalization",
+                        "values": [
+                            "MixedCase",
+                            "AllUppercase",
+                            "AllLowercase",
+                            "SmallCaps",
+                            "Capitalize"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SpacingType",
+                        "values": [
+                            "PercentageSpacing",
+                            "AbsoluteSpacing"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ResolveProperties",
+                        "values": [
+                            "NoPropertiesResolved",
+                            "FamilyResolved",
+                            "SizeResolved",
+                            "StyleHintResolved",
+                            "StyleStrategyResolved",
+                            "WeightResolved",
+                            "StyleResolved",
+                            "UnderlineResolved",
+                            "OverlineResolved",
+                            "StrikeOutResolved",
+                            "FixedPitchResolved",
+                            "StretchResolved",
+                            "KerningResolved",
+                            "CapitalizationResolved",
+                            "LetterSpacingResolved",
+                            "WordSpacingResolved",
+                            "HintingPreferenceResolved",
+                            "StyleNameResolved",
+                            "FamiliesResolved",
+                            "FeaturesResolved",
+                            "VariableAxesResolved",
+                            "AllPropertiesResolved"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 21,
+                "qualifiedClassName": "QFont"
+            }
+        ],
+        "inputFile": "qfont.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFontDatabase",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WritingSystem",
+                        "values": [
+                            "Any",
+                            "Latin",
+                            "Greek",
+                            "Cyrillic",
+                            "Armenian",
+                            "Hebrew",
+                            "Arabic",
+                            "Syriac",
+                            "Thaana",
+                            "Devanagari",
+                            "Bengali",
+                            "Gurmukhi",
+                            "Gujarati",
+                            "Oriya",
+                            "Tamil",
+                            "Telugu",
+                            "Kannada",
+                            "Malayalam",
+                            "Sinhala",
+                            "Thai",
+                            "Lao",
+                            "Tibetan",
+                            "Myanmar",
+                            "Georgian",
+                            "Khmer",
+                            "SimplifiedChinese",
+                            "TraditionalChinese",
+                            "Japanese",
+                            "Korean",
+                            "Vietnamese",
+                            "Symbol",
+                            "Other",
+                            "Ogham",
+                            "Runic",
+                            "Nko",
+                            "WritingSystemsCount"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SystemFont",
+                        "values": [
+                            "GeneralFont",
+                            "FixedFont",
+                            "TitleFont",
+                            "SmallestReadableFont"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 18,
+                "qualifiedClassName": "QFontDatabase"
+            }
+        ],
+        "inputFile": "qfontdatabase.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QGenericPlugin",
+                "lineNumber": 15,
+                "object": true,
+                "qualifiedClassName": "QGenericPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgenericplugin.h",
+        "outputRevision": 68
+    },
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+                "object": true,
+                "properties": [
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "windowIcon",
+                        "read": "windowIcon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setWindowIcon"
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "applicationDisplayName",
+                        "notify": "applicationDisplayNameChanged",
+                        "read": "applicationDisplayName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setApplicationDisplayName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "desktopFileName",
+                        "read": "desktopFileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDesktopFileName"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "layoutDirection",
+                        "notify": "layoutDirectionChanged",
+                        "read": "layoutDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false,
+                        "write": "setLayoutDirection"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "platformName",
+                        "read": "platformName",
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+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QString",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "index": 5,
+                        "name": "quitOnLastWindowClosed",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setQuitOnLastWindowClosed"
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+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QScreen*",
+                        "user": false
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+                        "index": 0,
+                        "name": "fontDatabaseChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "screen",
+                                "type": "QScreen*"
+                            }
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+                        "name": "screenAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "screen",
+                                "type": "QScreen*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "screenRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "screen",
+                                "type": "QScreen*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "primaryScreenChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "lastWindowClosed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "focusObject",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "focusObjectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "focusWindow",
+                                "type": "QWindow*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "focusWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "Qt::ApplicationState"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "applicationStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "direction",
+                                "type": "Qt::LayoutDirection"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "layoutDirectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sessionManager",
+                                "type": "QSessionManager&"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "commitDataRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sessionManager",
+                                "type": "QSessionManager&"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "saveStateRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "applicationDisplayNameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pal",
+                                "type": "QPalette"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "paletteChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "font",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "number",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "setBadgeNumber",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "_q_updateFocusObject",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QCoreApplication"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qguiapplication.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHighDpiScaling",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "DpiAdjustmentPolicy",
+                        "values": [
+                            "Unset",
+                            "Enabled",
+                            "Disabled",
+                            "UpOnly"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 38,
+                "qualifiedClassName": "QHighDpiScaling"
+            }
+        ],
+        "inputFile": "qhighdpiscaling_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QIconEnginePlugin",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QIconEnginePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qiconengineplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QImage",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Format",
+                        "values": [
+                            "Format_Invalid",
+                            "Format_Mono",
+                            "Format_MonoLSB",
+                            "Format_Indexed8",
+                            "Format_RGB32",
+                            "Format_ARGB32",
+                            "Format_ARGB32_Premultiplied",
+                            "Format_RGB16",
+                            "Format_ARGB8565_Premultiplied",
+                            "Format_RGB666",
+                            "Format_ARGB6666_Premultiplied",
+                            "Format_RGB555",
+                            "Format_ARGB8555_Premultiplied",
+                            "Format_RGB888",
+                            "Format_RGB444",
+                            "Format_ARGB4444_Premultiplied",
+                            "Format_RGBX8888",
+                            "Format_RGBA8888",
+                            "Format_RGBA8888_Premultiplied",
+                            "Format_BGR30",
+                            "Format_A2BGR30_Premultiplied",
+                            "Format_RGB30",
+                            "Format_A2RGB30_Premultiplied",
+                            "Format_Alpha8",
+                            "Format_Grayscale8",
+                            "Format_RGBX64",
+                            "Format_RGBA64",
+                            "Format_RGBA64_Premultiplied",
+                            "Format_Grayscale16",
+                            "Format_BGR888",
+                            "Format_RGBX16FPx4",
+                            "Format_RGBA16FPx4",
+                            "Format_RGBA16FPx4_Premultiplied",
+                            "Format_RGBX32FPx4",
+                            "Format_RGBA32FPx4",
+                            "Format_RGBA32FPx4_Premultiplied",
+                            "Format_CMYK8888",
+                            "NImageFormats"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 36,
+                "qualifiedClassName": "QImage",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPaintDevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qimage.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QImageIOPlugin",
+                "lineNumber": 101,
+                "object": true,
+                "qualifiedClassName": "QImageIOPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qimageiohandler.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QInputControl",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QInputControl",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qinputcontrol_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QInputDevice",
+                "enums": [
+                    {
+                        "alias": "DeviceType",
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "DeviceTypes",
+                        "values": [
+                            "Unknown",
+                            "Mouse",
+                            "TouchScreen",
+                            "TouchPad",
+                            "Puck",
+                            "Stylus",
+                            "Airbrush",
+                            "Keyboard",
+                            "AllDevices"
+                        ]
+                    },
+                    {
+                        "alias": "Capability",
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "Capabilities",
+                        "values": [
+                            "None",
+                            "Position",
+                            "Area",
+                            "Pressure",
+                            "Velocity",
+                            "NormalizedPosition",
+                            "MouseEmulation",
+                            "PixelScroll",
+                            "Scroll",
+                            "Hover",
+                            "Rotation",
+                            "XTilt",
+                            "YTilt",
+                            "TangentialPressure",
+                            "ZPosition",
+                            "All"
+                        ]
+                    }
+                ],
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
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+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "type",
+                        "read": "type",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DeviceType",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "capabilities",
+                        "read": "capabilities",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Capabilities",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "systemId",
+                        "read": "systemId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qint64",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "seatName",
+                        "read": "seatName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "availableVirtualGeometry",
+                        "notify": "availableVirtualGeometryChanged",
+                        "read": "availableVirtualGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QInputDevice",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "area",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "availableVirtualGeometryChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qinputdevice.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QInputDeviceManager",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QInputDeviceManager",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QInputDeviceManager::DeviceType"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "deviceListChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "QPoint"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "cursorPositionChangeRequested",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qinputdevicemanager_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QInputMethod",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Action",
+                        "values": [
+                            "Click",
+                            "ContextMenu"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "cursorRectangle",
+                        "notify": "cursorRectangleChanged",
+                        "read": "cursorRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "anchorRectangle",
+                        "notify": "anchorRectangleChanged",
+                        "read": "anchorRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "keyboardRectangle",
+                        "notify": "keyboardRectangleChanged",
+                        "read": "keyboardRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "inputItemClipRectangle",
+                        "notify": "inputItemClipRectangleChanged",
+                        "read": "inputItemClipRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "animating",
+                        "notify": "animatingChanged",
+                        "read": "isAnimating",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "inputDirection",
+                        "notify": "inputDirectionChanged",
+                        "read": "inputDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QInputMethod",
+                "signals": [
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+                        "access": "public",
+                        "index": 0,
+                        "name": "cursorRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "anchorRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "keyboardRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "inputItemClipRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "animatingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newDirection",
+                                "type": "Qt::LayoutDirection"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "inputDirectionChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "index": 8,
+                        "name": "show",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "hide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "queries",
+                                "type": "Qt::InputMethodQueries"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "reset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "commit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "a",
+                                "type": "Action"
+                            },
+                            {
+                                "name": "cursorPosition",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "invokeAction",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qinputmethod.h",
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+    },
+    {
+        "classes": [
+            {
+                "className": "QInternalMimeData",
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+                            "ReadOnly",
+                            "HideNameFilterDetails",
+                            "DontUseCustomDirectoryIcons"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 263,
+                "qualifiedClassName": "QFileDialogOptions"
+            },
+            {
+                "className": "QPlatformFileDialogHelper",
+                "lineNumber": 364,
+                "object": true,
+                "qualifiedClassName": "QPlatformFileDialogHelper",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "file",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "files",
+                                "type": "QList<QUrl>"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "filesSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "directoryEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "filterSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformDialogHelper"
+                    }
+                ]
+            },
+            {
+                "className": "QMessageDialogOptions",
+                "enums": [
+                    {
+                        "alias": "Option",
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "Options",
+                        "values": [
+                            "DontUseNativeDialog"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardIcon",
+                        "values": [
+                            "NoIcon",
+                            "Information",
+                            "Warning",
+                            "Critical",
+                            "Question"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 398,
+                "qualifiedClassName": "QMessageDialogOptions"
+            },
+            {
+                "className": "QPlatformMessageDialogHelper",
+                "lineNumber": 482,
+                "object": true,
+                "qualifiedClassName": "QPlatformMessageDialogHelper",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QPlatformDialogHelper::ButtonRole"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "Qt::CheckState"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "checkBoxStateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformdialoghelper.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformGraphicsBuffer",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "AccessType",
+                        "values": [
+                            "None",
+                            "SWReadAccess",
+                            "SWWriteAccess",
+                            "TextureAccess",
+                            "HWCompositor"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Origin",
+                        "values": [
+                            "OriginBottomLeft",
+                            "OriginTopLeft"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QPlatformGraphicsBuffer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "previousAccessTypes",
+                                "type": "AccessTypes"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "unlocked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformgraphicsbuffer.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformInputContext",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QPlatformInputContext",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatforminputcontext.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformInputContextPlugin",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QPlatformInputContextPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatforminputcontextplugin_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformIntegrationPlugin",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QPlatformIntegrationPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformintegrationplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformMenuItem",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MenuRole",
+                        "values": [
+                            "NoRole",
+                            "TextHeuristicRole",
+                            "ApplicationSpecificRole",
+                            "AboutQtRole",
+                            "AboutRole",
+                            "PreferencesRole",
+                            "QuitRole",
+                            "CutRole",
+                            "CopyRole",
+                            "PasteRole",
+                            "SelectAllRole",
+                            "RoleCount"
+                        ]
+                    }
+                ],
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QPlatformMenuItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "hovered",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QPlatformMenu",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MenuType",
+                        "values": [
+                            "DefaultMenu",
+                            "EditMenu"
+                        ]
+                    }
+                ],
+                "lineNumber": 71,
+                "object": true,
+                "qualifiedClassName": "QPlatformMenu",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToShow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "aboutToHide",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QPlatformMenuBar",
+                "lineNumber": 120,
+                "object": true,
+                "qualifiedClassName": "QPlatformMenuBar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformNativeInterface",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QPlatformNativeInterface",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "window",
+                                "type": "QPlatformWindow*"
+                            },
+                            {
+                                "name": "propertyName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "windowPropertyChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformnativeinterface.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformServiceColorPicker",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QPlatformServiceColorPicker",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorPicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformservices.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformSharedGraphicsCache",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QPlatformSharedGraphicsCache",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cacheId",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "itemIds",
+                                "type": "QList<quint32>"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemsMissing",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cacheId",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "bufferId",
+                                "type": "void*"
+                            },
+                            {
+                                "name": "itemIds",
+                                "type": "QList<quint32>"
+                            },
+                            {
+                                "name": "positionsInBuffer",
+                                "type": "QList<QPoint>"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "itemsAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cacheId",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "itemIds",
+                                "type": "QList<quint32>"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "itemsInvalidated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cacheId",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "bufferId",
+                                "type": "void*"
+                            },
+                            {
+                                "name": "itemIds",
+                                "type": "QList<quint32>"
+                            },
+                            {
+                                "name": "positionsInBuffer",
+                                "type": "QList<QPoint>"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "itemsUpdated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformsharedgraphicscache.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformSystemTrayIcon",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ActivationReason",
+                        "values": [
+                            "Unknown",
+                            "Context",
+                            "DoubleClick",
+                            "Trigger",
+                            "MiddleClick"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MessageIcon",
+                        "values": [
+                            "NoIcon",
+                            "Information",
+                            "Warning",
+                            "Critical"
+                        ]
+                    }
+                ],
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QPlatformSystemTrayIcon",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reason",
+                                "type": "QPlatformSystemTrayIcon::ActivationReason"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "globalPos",
+                                "type": "QPoint"
+                            },
+                            {
+                                "name": "screen",
+                                "type": "const QPlatformScreen*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "contextMenuRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "messageClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformsystemtrayicon.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformTheme",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ThemeHint",
+                        "values": [
+                            "CursorFlashTime",
+                            "KeyboardInputInterval",
+                            "MouseDoubleClickInterval",
+                            "StartDragDistance",
+                            "StartDragTime",
+                            "KeyboardAutoRepeatRate",
+                            "PasswordMaskDelay",
+                            "StartDragVelocity",
+                            "TextCursorWidth",
+                            "DropShadow",
+                            "MaximumScrollBarDragDistance",
+                            "ToolButtonStyle",
+                            "ToolBarIconSize",
+                            "ItemViewActivateItemOnSingleClick",
+                            "SystemIconThemeName",
+                            "SystemIconFallbackThemeName",
+                            "IconThemeSearchPaths",
+                            "StyleNames",
+                            "WindowAutoPlacement",
+                            "DialogButtonBoxLayout",
+                            "DialogButtonBoxButtonsHaveIcons",
+                            "UseFullScreenForPopupMenu",
+                            "KeyboardScheme",
+                            "UiEffects",
+                            "SpellCheckUnderlineStyle",
+                            "TabFocusBehavior",
+                            "IconPixmapSizes",
+                            "PasswordMaskCharacter",
+                            "DialogSnapToDefaultButton",
+                            "ContextMenuOnMouseRelease",
+                            "MousePressAndHoldInterval",
+                            "MouseDoubleClickDistance",
+                            "WheelScrollLines",
+                            "TouchDoubleTapDistance",
+                            "ShowShortcutsInContextMenus",
+                            "IconFallbackSearchPaths",
+                            "MouseQuickSelectionThreshold",
+                            "InteractiveResizeAcrossScreens",
+                            "ShowDirectoriesFirst",
+                            "PreselectFirstFileInDirectory",
+                            "ButtonPressKeys",
+                            "SetFocusOnTouchRelease",
+                            "FlickStartDistance",
+                            "FlickMaximumVelocity",
+                            "FlickDeceleration",
+                            "MenuBarFocusOnAltPressRelease",
+                            "MouseCursorTheme",
+                            "MouseCursorSize",
+                            "UnderlineShortcut",
+                            "ShowIconsInMenus",
+                            "PreferFileIconFromTheme"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DialogType",
+                        "values": [
+                            "FileDialog",
+                            "ColorDialog",
+                            "FontDialog",
+                            "MessageDialog"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Palette",
+                        "values": [
+                            "SystemPalette",
+                            "ToolTipPalette",
+                            "ToolButtonPalette",
+                            "ButtonPalette",
+                            "CheckBoxPalette",
+                            "RadioButtonPalette",
+                            "HeaderPalette",
+                            "ComboBoxPalette",
+                            "ItemViewPalette",
+                            "MessageBoxLabelPelette",
+                            "MessageBoxLabelPalette",
+                            "TabBarPalette",
+                            "LabelPalette",
+                            "GroupBoxPalette",
+                            "MenuPalette",
+                            "MenuBarPalette",
+                            "TextEditPalette",
+                            "TextLineEditPalette",
+                            "NPalettes"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Font",
+                        "values": [
+                            "SystemFont",
+                            "MenuFont",
+                            "MenuBarFont",
+                            "MenuItemFont",
+                            "MessageBoxFont",
+                            "LabelFont",
+                            "TipLabelFont",
+                            "StatusBarFont",
+                            "TitleBarFont",
+                            "MdiSubWindowTitleFont",
+                            "DockWidgetTitleFont",
+                            "PushButtonFont",
+                            "CheckBoxFont",
+                            "RadioButtonFont",
+                            "ToolButtonFont",
+                            "ItemViewFont",
+                            "ListViewFont",
+                            "HeaderViewFont",
+                            "ListBoxFont",
+                            "ComboMenuItemFont",
+                            "ComboLineEditFont",
+                            "SmallFont",
+                            "MiniFont",
+                            "FixedFont",
+                            "GroupBoxTitleFont",
+                            "TabButtonFont",
+                            "EditorFont",
+                            "NFonts"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardPixmap",
+                        "values": [
+                            "TitleBarMenuButton",
+                            "TitleBarMinButton",
+                            "TitleBarMaxButton",
+                            "TitleBarCloseButton",
+                            "TitleBarNormalButton",
+                            "TitleBarShadeButton",
+                            "TitleBarUnshadeButton",
+                            "TitleBarContextHelpButton",
+                            "DockWidgetCloseButton",
+                            "MessageBoxInformation",
+                            "MessageBoxWarning",
+                            "MessageBoxCritical",
+                            "MessageBoxQuestion",
+                            "DesktopIcon",
+                            "TrashIcon",
+                            "ComputerIcon",
+                            "DriveFDIcon",
+                            "DriveHDIcon",
+                            "DriveCDIcon",
+                            "DriveDVDIcon",
+                            "DriveNetIcon",
+                            "DirOpenIcon",
+                            "DirClosedIcon",
+                            "DirLinkIcon",
+                            "DirLinkOpenIcon",
+                            "FileIcon",
+                            "FileLinkIcon",
+                            "ToolBarHorizontalExtensionButton",
+                            "ToolBarVerticalExtensionButton",
+                            "FileDialogStart",
+                            "FileDialogEnd",
+                            "FileDialogToParent",
+                            "FileDialogNewFolder",
+                            "FileDialogDetailedView",
+                            "FileDialogInfoView",
+                            "FileDialogContentsView",
+                            "FileDialogListView",
+                            "FileDialogBack",
+                            "DirIcon",
+                            "DialogOkButton",
+                            "DialogCancelButton",
+                            "DialogHelpButton",
+                            "DialogOpenButton",
+                            "DialogSaveButton",
+                            "DialogCloseButton",
+                            "DialogApplyButton",
+                            "DialogResetButton",
+                            "DialogDiscardButton",
+                            "DialogYesButton",
+                            "DialogNoButton",
+                            "ArrowUp",
+                            "ArrowDown",
+                            "ArrowLeft",
+                            "ArrowRight",
+                            "ArrowBack",
+                            "ArrowForward",
+                            "DirHomeIcon",
+                            "CommandLink",
+                            "VistaShield",
+                            "BrowserReload",
+                            "BrowserStop",
+                            "MediaPlay",
+                            "MediaStop",
+                            "MediaPause",
+                            "MediaSkipForward",
+                            "MediaSkipBackward",
+                            "MediaSeekForward",
+                            "MediaSeekBackward",
+                            "MediaVolume",
+                            "MediaVolumeMuted",
+                            "LineEditClearButton",
+                            "DialogYesToAllButton",
+                            "DialogNoToAllButton",
+                            "DialogSaveAllButton",
+                            "DialogAbortButton",
+                            "DialogRetryButton",
+                            "DialogIgnoreButton",
+                            "RestoreDefaultsButton",
+                            "TabCloseButton",
+                            "NStandardPixmap",
+                            "CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "KeyboardSchemes",
+                        "values": [
+                            "WindowsKeyboardScheme",
+                            "MacKeyboardScheme",
+                            "X11KeyboardScheme",
+                            "KdeKeyboardScheme",
+                            "GnomeKeyboardScheme",
+                            "CdeKeyboardScheme"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "UiEffect",
+                        "values": [
+                            "GeneralUiEffect",
+                            "AnimateMenuUiEffect",
+                            "FadeMenuUiEffect",
+                            "AnimateComboUiEffect",
+                            "AnimateTooltipUiEffect",
+                            "FadeTooltipUiEffect",
+                            "AnimateToolBoxUiEffect",
+                            "HoverEffect"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 42,
+                "qualifiedClassName": "QPlatformTheme"
+            }
+        ],
+        "inputFile": "qplatformtheme.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformThemePlugin",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QPlatformThemePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformthemeplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPointingDeviceUniqueId",
+                "gadget": true,
+                "lineNumber": 20,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "numericId",
+                        "read": "numericId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qint64",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QPointingDeviceUniqueId"
+            },
+            {
+                "className": "QPointingDevice",
+                "enums": [
+                    {
+                        "alias": "PointerType",
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "PointerTypes",
+                        "values": [
+                            "Unknown",
+                            "Generic",
+                            "Finger",
+                            "Pen",
+                            "Eraser",
+                            "Cursor",
+                            "AllPointerTypes"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "GrabTransition",
+                        "values": [
+                            "GrabPassive",
+                            "UngrabPassive",
+                            "CancelGrabPassive",
+                            "OverrideGrabPassive",
+                            "GrabExclusive",
+                            "UngrabExclusive",
+                            "CancelGrabExclusive"
+                        ]
+                    }
+                ],
+                "lineNumber": 50,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "pointerType",
+                        "read": "pointerType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "PointerType",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "maximumPoints",
+                        "read": "maximumPoints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "buttonCount",
+                        "read": "buttonCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "uniqueId",
+                        "read": "uniqueId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointingDeviceUniqueId",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QPointingDevice",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "grabber",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "transition",
+                                "type": "GrabTransition"
+                            },
+                            {
+                                "name": "event",
+                                "type": "const QPointerEvent*"
+                            },
+                            {
+                                "name": "point",
+                                "type": "QEventPoint"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "grabChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QInputDevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpointingdevice.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QRasterWindow",
+                "lineNumber": 14,
+                "object": true,
+                "qualifiedClassName": "QRasterWindow",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPaintDeviceWindow"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qrasterwindow.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QScreen",
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "manufacturer",
+                        "read": "manufacturer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "model",
+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "serialNumber",
+                        "read": "serialNumber",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "depth",
+                        "read": "depth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "size",
+                        "notify": "geometryChanged",
+                        "read": "size",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "availableSize",
+                        "notify": "availableGeometryChanged",
+                        "read": "availableSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "virtualSize",
+                        "notify": "virtualGeometryChanged",
+                        "read": "virtualSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "availableVirtualSize",
+                        "notify": "virtualGeometryChanged",
+                        "read": "availableVirtualSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "geometry",
+                        "notify": "geometryChanged",
+                        "read": "geometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "availableGeometry",
+                        "notify": "availableGeometryChanged",
+                        "read": "availableGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "virtualGeometry",
+                        "notify": "virtualGeometryChanged",
+                        "read": "virtualGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "availableVirtualGeometry",
+                        "notify": "virtualGeometryChanged",
+                        "read": "availableVirtualGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "physicalSize",
+                        "notify": "physicalSizeChanged",
+                        "read": "physicalSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "physicalDotsPerInchX",
+                        "notify": "physicalDotsPerInchChanged",
+                        "read": "physicalDotsPerInchX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "physicalDotsPerInchY",
+                        "notify": "physicalDotsPerInchChanged",
+                        "read": "physicalDotsPerInchY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "physicalDotsPerInch",
+                        "notify": "physicalDotsPerInchChanged",
+                        "read": "physicalDotsPerInch",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "logicalDotsPerInchX",
+                        "notify": "logicalDotsPerInchChanged",
+                        "read": "logicalDotsPerInchX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "logicalDotsPerInchY",
+                        "notify": "logicalDotsPerInchChanged",
+                        "read": "logicalDotsPerInchY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "logicalDotsPerInch",
+                        "notify": "logicalDotsPerInchChanged",
+                        "read": "logicalDotsPerInch",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "devicePixelRatio",
+                        "notify": "physicalDotsPerInchChanged",
+                        "read": "devicePixelRatio",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "primaryOrientation",
+                        "notify": "primaryOrientationChanged",
+                        "read": "primaryOrientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScreenOrientation",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "orientation",
+                        "notify": "orientationChanged",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScreenOrientation",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "nativeOrientation",
+                        "read": "nativeOrientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScreenOrientation",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "refreshRate",
+                        "notify": "refreshRateChanged",
+                        "read": "refreshRate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QScreen",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "geometry",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "geometryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "geometry",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "availableGeometryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "QSizeF"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "physicalSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "dpi",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "physicalDotsPerInchChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "dpi",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "logicalDotsPerInchChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "virtualGeometryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "Qt::ScreenOrientation"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "primaryOrientationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "Qt::ScreenOrientation"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "orientationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "refreshRate",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "refreshRateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qscreen.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSessionManager",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QSessionManager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsessionmanager.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QShapedPixmapWindow",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QShapedPixmapWindow",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QRasterWindow"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qshapedpixmapdndwindow_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "key",
+                        "read": "key",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QKeySequence",
+                        "user": false,
+                        "write": "setKey"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "enabled",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "autoRepeat",
+                        "read": "autoRepeat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRepeat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "context",
+                        "read": "context",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ShortcutContext",
+                        "user": false,
+                        "write": "setContext"
+                    }
+                ],
+                "qualifiedClassName": "QShortcut",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "activatedAmbiguously",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qshortcut.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QStandardItemModel",
+                "lineNumber": 278,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableSortRole",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "sortRole",
+                        "read": "sortRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSortRole"
+                    }
+                ],
+                "qualifiedClassName": "QStandardItemModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QStandardItem*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "topLeft",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "bottomRight",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "_q_emitItemChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "object": true,
+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "cursorFlashTime",
+                        "notify": "cursorFlashTimeChanged",
+                        "read": "cursorFlashTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "fontSmoothingGamma",
+                        "read": "fontSmoothingGamma",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "keyboardAutoRepeatRate",
+                        "read": "keyboardAutoRepeatRate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "keyboardAutoRepeatRateF",
+                        "read": "keyboardAutoRepeatRateF",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "keyboardInputInterval",
+                        "notify": "keyboardInputIntervalChanged",
+                        "read": "keyboardInputInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "mouseDoubleClickInterval",
+                        "notify": "mouseDoubleClickIntervalChanged",
+                        "read": "mouseDoubleClickInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "mousePressAndHoldInterval",
+                        "notify": "mousePressAndHoldIntervalChanged",
+                        "read": "mousePressAndHoldInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "passwordMaskCharacter",
+                        "read": "passwordMaskCharacter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QChar",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "passwordMaskDelay",
+                        "read": "passwordMaskDelay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "setFocusOnTouchRelease",
+                        "read": "setFocusOnTouchRelease",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "showIsFullScreen",
+                        "read": "showIsFullScreen",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "showIsMaximized",
+                        "read": "showIsMaximized",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "showShortcutsInContextMenus",
+                        "notify": "showShortcutsInContextMenusChanged",
+                        "read": "showShortcutsInContextMenus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowShortcutsInContextMenus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "contextMenuTrigger",
+                        "notify": "contextMenuTriggerChanged",
+                        "read": "contextMenuTrigger",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ContextMenuTrigger",
+                        "user": false,
+                        "write": "setContextMenuTrigger"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "startDragDistance",
+                        "notify": "startDragDistanceChanged",
+                        "read": "startDragDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "startDragTime",
+                        "notify": "startDragTimeChanged",
+                        "read": "startDragTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "startDragVelocity",
+                        "read": "startDragVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "useRtlExtensions",
+                        "read": "useRtlExtensions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "tabFocusBehavior",
+                        "notify": "tabFocusBehaviorChanged",
+                        "read": "tabFocusBehavior",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TabFocusBehavior",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "singleClickActivation",
+                        "read": "singleClickActivation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "useHoverEffects",
+                        "notify": "useHoverEffectsChanged",
+                        "read": "useHoverEffects",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUseHoverEffects"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "wheelScrollLines",
+                        "notify": "wheelScrollLinesChanged",
+                        "read": "wheelScrollLines",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "mouseQuickSelectionThreshold",
+                        "notify": "mouseQuickSelectionThresholdChanged",
+                        "read": "mouseQuickSelectionThreshold",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMouseQuickSelectionThreshold"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "mouseDoubleClickDistance",
+                        "read": "mouseDoubleClickDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "touchDoubleTapDistance",
+                        "read": "touchDoubleTapDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "colorScheme",
+                        "notify": "colorSchemeChanged",
+                        "read": "colorScheme",
+                        "required": false,
+                        "reset": "unsetColorScheme",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ColorScheme",
+                        "user": false,
+                        "write": "setColorScheme"
+                    }
+                ],
+                "qualifiedClassName": "QStyleHints",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cursorFlashTime",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "cursorFlashTimeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "keyboardInputInterval",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "keyboardInputIntervalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouseDoubleClickInterval",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "mouseDoubleClickIntervalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mousePressAndHoldInterval",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "mousePressAndHoldIntervalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "startDragDistance",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "startDragDistanceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "startDragTime",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "startDragTimeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "tabFocusBehavior",
+                                "type": "Qt::TabFocusBehavior"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "tabFocusBehaviorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "useHoverEffects",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "useHoverEffectsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "showShortcutsInContextMenusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contextMenuTrigger",
+                                "type": "Qt::ContextMenuTrigger"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "contextMenuTriggerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "scrollLines",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "wheelScrollLinesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "threshold",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "mouseQuickSelectionThresholdChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "colorScheme",
+                                "type": "Qt::ColorScheme"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "colorSchemeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstylehints.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSurface",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SurfaceClass",
+                        "values": [
+                            "Window",
+                            "Offscreen"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SurfaceType",
+                        "values": [
+                            "RasterSurface",
+                            "OpenGLSurface",
+                            "RasterGLSurface",
+                            "OpenVGSurface",
+                            "VulkanSurface",
+                            "MetalSurface",
+                            "Direct3DSurface"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 20,
+                "qualifiedClassName": "QSurface"
+            }
+        ],
+        "inputFile": "qsurface.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSurfaceFormat",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FormatOption",
+                        "values": [
+                            "StereoBuffers",
+                            "DebugContext",
+                            "DeprecatedFunctions",
+                            "ResetNotification",
+                            "ProtectedContent"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SwapBehavior",
+                        "values": [
+                            "DefaultSwapBehavior",
+                            "SingleBuffer",
+                            "DoubleBuffer",
+                            "TripleBuffer"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderableType",
+                        "values": [
+                            "DefaultRenderableType",
+                            "OpenGL",
+                            "OpenGLES",
+                            "OpenVG"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "OpenGLContextProfile",
+                        "values": [
+                            "NoProfile",
+                            "CoreProfile",
+                            "CompatibilityProfile"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ColorSpace",
+                        "values": [
+                            "DefaultColorSpace",
+                            "sRGBColorSpace"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 16,
+                "qualifiedClassName": "QSurfaceFormat"
+            }
+        ],
+        "inputFile": "qsurfaceformat.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSyntaxHighlighter",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QSyntaxHighlighter",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "rehighlight",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "block",
+                                "type": "QTextBlock"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "rehighlightBlock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsRemoved",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsAdded",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "_q_reformatBlocks",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_delayedRehighlight",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsyntaxhighlighter.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextDocument",
+                "enums": [
+                    {
+                        "alias": "MarkdownFeature",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "MarkdownFeatures",
+                        "values": [
+                            "MarkdownNoHTML",
+                            "MarkdownDialectCommonMark",
+                            "MarkdownDialectGitHub"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ResourceType",
+                        "values": [
+                            "UnknownResource",
+                            "HtmlResource",
+                            "ImageResource",
+                            "StyleSheetResource",
+                            "MarkdownResource",
+                            "UserResource"
+                        ]
+                    }
+                ],
+                "lineNumber": 55,
+                "methods": [
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "loadResource",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "undoRedoEnabled",
+                        "read": "isUndoRedoEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUndoRedoEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 1,
+                        "name": "modified",
+                        "read": "isModified",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setModified"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "pageSize",
+                        "read": "pageSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setPageSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "defaultFont",
+                        "read": "defaultFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setDefaultFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "useDesignMetrics",
+                        "read": "useDesignMetrics",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUseDesignMetrics"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "layoutEnabled",
+                        "read": "isLayoutEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setLayoutEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "size",
+                        "read": "size",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "textWidth",
+                        "read": "textWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTextWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "blockCount",
+                        "read": "blockCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "indentWidth",
+                        "read": "indentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setIndentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "defaultStyleSheet",
+                        "read": "defaultStyleSheet",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDefaultStyleSheet"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "maximumBlockCount",
+                        "read": "maximumBlockCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumBlockCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "documentMargin",
+                        "read": "documentMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setDocumentMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "baseUrl",
+                        "notify": "baseUrlChanged",
+                        "read": "baseUrl",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setBaseUrl"
+                    }
+                ],
+                "qualifiedClassName": "QTextDocument",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsRemoved",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsAdded",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "contentsChange",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "undoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "redoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "undoCommandAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "m",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "modificationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cursor",
+                                "type": "QTextCursor"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newBlockCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "blockCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "baseUrlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "documentLayoutChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractUndoItem*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "appendUndoItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "m",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setModified",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "isCloned": true,
+                        "name": "setModified",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextdocument.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextDocumentLayout",
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "cursorWidth",
+                        "read": "cursorWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "idealWidth",
+                        "read": "idealWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "contentHasAlignment",
+                        "read": "contentHasAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QTextDocumentLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractTextDocumentLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextdocumentlayout_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextFormat",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FormatType",
+                        "values": [
+                            "InvalidFormat",
+                            "BlockFormat",
+                            "CharFormat",
+                            "ListFormat",
+                            "FrameFormat",
+                            "UserFormat"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Property",
+                        "values": [
+                            "ObjectIndex",
+                            "CssFloat",
+                            "LayoutDirection",
+                            "OutlinePen",
+                            "BackgroundBrush",
+                            "ForegroundBrush",
+                            "BackgroundImageUrl",
+                            "BlockAlignment",
+                            "BlockTopMargin",
+                            "BlockBottomMargin",
+                            "BlockLeftMargin",
+                            "BlockRightMargin",
+                            "TextIndent",
+                            "TabPositions",
+                            "BlockIndent",
+                            "LineHeight",
+                            "LineHeightType",
+                            "BlockNonBreakableLines",
+                            "BlockTrailingHorizontalRulerWidth",
+                            "HeadingLevel",
+                            "BlockQuoteLevel",
+                            "BlockCodeLanguage",
+                            "BlockCodeFence",
+                            "BlockMarker",
+                            "FirstFontProperty",
+                            "FontCapitalization",
+                            "FontLetterSpacing",
+                            "FontWordSpacing",
+                            "FontStyleHint",
+                            "FontStyleStrategy",
+                            "FontKerning",
+                            "FontHintingPreference",
+                            "FontFamilies",
+                            "FontStyleName",
+                            "FontLetterSpacingType",
+                            "FontStretch",
+                            "FontFamily",
+                            "FontPointSize",
+                            "FontSizeAdjustment",
+                            "FontSizeIncrement",
+                            "FontWeight",
+                            "FontItalic",
+                            "FontUnderline",
+                            "FontOverline",
+                            "FontStrikeOut",
+                            "FontFixedPitch",
+                            "FontPixelSize",
+                            "LastFontProperty",
+                            "TextUnderlineColor",
+                            "TextVerticalAlignment",
+                            "TextOutline",
+                            "TextUnderlineStyle",
+                            "TextToolTip",
+                            "TextSuperScriptBaseline",
+                            "TextSubScriptBaseline",
+                            "TextBaselineOffset",
+                            "IsAnchor",
+                            "AnchorHref",
+                            "AnchorName",
+                            "OldFontLetterSpacingType",
+                            "OldFontStretch",
+                            "OldTextUnderlineColor",
+                            "OldFontFamily",
+                            "ObjectType",
+                            "ListStyle",
+                            "ListIndent",
+                            "ListNumberPrefix",
+                            "ListNumberSuffix",
+                            "ListStart",
+                            "FrameBorder",
+                            "FrameMargin",
+                            "FramePadding",
+                            "FrameWidth",
+                            "FrameHeight",
+                            "FrameTopMargin",
+                            "FrameBottomMargin",
+                            "FrameLeftMargin",
+                            "FrameRightMargin",
+                            "FrameBorderBrush",
+                            "FrameBorderStyle",
+                            "TableColumns",
+                            "TableColumnWidthConstraints",
+                            "TableCellSpacing",
+                            "TableCellPadding",
+                            "TableHeaderRowCount",
+                            "TableBorderCollapse",
+                            "TableCellRowSpan",
+                            "TableCellColumnSpan",
+                            "TableCellTopPadding",
+                            "TableCellBottomPadding",
+                            "TableCellLeftPadding",
+                            "TableCellRightPadding",
+                            "TableCellTopBorder",
+                            "TableCellBottomBorder",
+                            "TableCellLeftBorder",
+                            "TableCellRightBorder",
+                            "TableCellTopBorderStyle",
+                            "TableCellBottomBorderStyle",
+                            "TableCellLeftBorderStyle",
+                            "TableCellRightBorderStyle",
+                            "TableCellTopBorderBrush",
+                            "TableCellBottomBorderBrush",
+                            "TableCellLeftBorderBrush",
+                            "TableCellRightBorderBrush",
+                            "ImageName",
+                            "ImageTitle",
+                            "ImageAltText",
+                            "ImageWidth",
+                            "ImageHeight",
+                            "ImageQuality",
+                            "ImageMaxWidth",
+                            "FullWidthSelection",
+                            "PageBreakPolicy",
+                            "UserProperty"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ObjectTypes",
+                        "values": [
+                            "NoObject",
+                            "ImageObject",
+                            "TableObject",
+                            "TableCellObject",
+                            "UserObject"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 89,
+                "qualifiedClassName": "QTextFormat"
+            }
+        ],
+        "inputFile": "qtextformat.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextImageHandler",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QTextObjectInterface",
+                            "id": "\"org.qt-project.Qt.QTextObjectInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QTextImageHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QTextObjectInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextimagehandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextList",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QTextList",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextBlockGroup"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextlist.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextObject",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QTextObject",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QTextBlockGroup",
+                "lineNumber": 52,
+                "object": true,
+                "qualifiedClassName": "QTextBlockGroup",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextObject"
+                    }
+                ]
+            },
+            {
+                "className": "QTextFrame",
+                "lineNumber": 80,
+                "object": true,
+                "qualifiedClassName": "QTextFrame",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextobject.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextTable",
+                "lineNumber": 62,
+                "object": true,
+                "qualifiedClassName": "QTextTable",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtexttable.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUndoGroup",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QUndoGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stack",
+                                "type": "QUndoStack*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activeStackChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "clean",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "cleanChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "canUndo",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "canUndoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "canRedo",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "canRedoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "undoText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "undoTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "redoText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "redoTextChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stack",
+                                "type": "QUndoStack*"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setActiveStack",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qundogroup.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUndoStack",
+                "lineNumber": 51,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "active",
+                        "read": "isActive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setActive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "undoLimit",
+                        "read": "undoLimit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setUndoLimit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "canUndo",
+                        "notify": "canUndoChanged",
+                        "read": "canUndo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "canRedo",
+                        "notify": "canRedoChanged",
+                        "read": "canRedo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "undoText",
+                        "notify": "undoTextChanged",
+                        "read": "undoText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "redoText",
+                        "notify": "redoTextChanged",
+                        "read": "redoText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "clean",
+                        "notify": "cleanChanged",
+                        "read": "isClean",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QUndoStack",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "clean",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "cleanChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "canUndo",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "canUndoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "canRedo",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "canRedoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "undoText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "undoTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "redoText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "redoTextChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "setClean",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resetClean",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "active",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setActive",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "isCloned": true,
+                        "name": "setActive",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qundostack.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QValidator",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "State",
+                        "values": [
+                            "Invalid",
+                            "Intermediate",
+                            "Acceptable"
+                        ]
+                    }
+                ],
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QValidator",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "changed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QIntValidator",
+                "lineNumber": 55,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "bottom",
+                        "notify": "bottomChanged",
+                        "read": "bottom",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setBottom"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "top",
+                        "notify": "topChanged",
+                        "read": "top",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setTop"
+                    }
+                ],
+                "qualifiedClassName": "QIntValidator",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bottom",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "bottomChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "top",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "topChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QValidator"
+                    }
+                ]
+            },
+            {
+                "className": "QDoubleValidator",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Notation",
+                        "values": [
+                            "StandardNotation",
+                            "ScientificNotation"
+                        ]
+                    }
+                ],
+                "lineNumber": 88,
+                "object": true,
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+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 41,
+                        "name": "setMaximumWidth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "h",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 42,
+                        "name": "setMaximumHeight",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msec",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 43,
+                        "name": "alert",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 44,
+                        "name": "requestUpdate",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "private",
+                        "index": 45,
+                        "name": "_q_clearAlert",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSurface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindow.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsGuiEventDispatcher",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QWindowsGuiEventDispatcher",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QEventDispatcherWin32"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowsguieventdispatcher_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPMCache",
+                "lineNumber": 176,
+                "object": true,
+                "qualifiedClassName": "QPMCache",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QCache<QPixmapCache::Key,QPixmapCacheEntry>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpixmapcache.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6help_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6help_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..3dbaf2a41586762c5deb18710751dd988f98021c
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6help_metatypes.json
@@ -0,0 +1,933 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QFilterNameDialog",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QFilterNameDialog",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateOkButton",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfilternamedialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpCollectionHandler",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QHelpCollectionHandler",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "error",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpcollectionhandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpContentModel",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QHelpContentModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "contentsCreationStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentsCreated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "insertContents",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            },
+            {
+                "className": "QHelpContentWidget",
+                "lineNumber": 50,
+                "object": true,
+                "qualifiedClassName": "QHelpContentWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "showLink",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTreeView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpcontentwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpDBReader",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QHelpDBReader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpdbreader_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpEngine",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QHelpEngine",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QHelpEngineCore"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpengine.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpEngineCore",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "autoSaveFilter",
+                        "read": "autoSaveFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoSaveFilter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "collectionFile",
+                        "read": "collectionFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCollectionFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "currentFilter",
+                        "read": "currentFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCurrentFilter"
+                    }
+                ],
+                "qualifiedClassName": "QHelpEngineCore",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "setupStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "setupFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "warning",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newFilter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "currentFilterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "readersAboutToBeInvalidated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpenginecore.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpFilterEngine",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QHelpFilterEngine",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newFilter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "filterActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpfilterengine.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpFilterSettingsWidget",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QHelpFilterSettingsWidget",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpfiltersettingswidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpIndexModel",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QHelpIndexModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexCreationStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "indexCreated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "insertIndices",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStringListModel"
+                    }
+                ]
+            },
+            {
+                "className": "QHelpIndexWidget",
+                "lineNumber": 48,
+                "object": true,
+                "qualifiedClassName": "QHelpIndexWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "keyword",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "links",
+                                "type": "QMultiMap<QString,QUrl>"
+                            },
+                            {
+                                "name": "keyword",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "linksActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "document",
+                                "type": "QHelpLink"
+                            },
+                            {
+                                "name": "keyword",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "documentActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "documents",
+                                "type": "QList<QHelpLink>"
+                            },
+                            {
+                                "name": "keyword",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "documentsActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "wildcard",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "filterIndices",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "isCloned": true,
+                        "name": "filterIndices",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "activateCurrentItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "showLink",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QListView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpindexwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchEngine",
+                "lineNumber": 39,
+                "object": true,
+                "qualifiedClassName": "QHelpSearchEngine",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "indexingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "searchingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "searchResultCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "searchingFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "reindexDocumentation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "cancelIndexing",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "queryList",
+                                "type": "QList<QHelpSearchQuery>"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "search",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "searchInput",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "search",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "cancelSearching",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "scheduleIndexDocumentation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "indexDocumentation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchengine.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchEngineCore",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QHelpSearchEngineCore",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "indexingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "searchingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "searchingFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "reindexDocumentation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "cancelIndexing",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "searchInput",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "search",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "cancelSearching",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "scheduleIndexDocumentation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchenginecore.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchIndexReader",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "fulltextsearch::QHelpSearchIndexReader",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "searchingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "searchingFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchindexreader_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchIndexWriter",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "fulltextsearch::QHelpSearchIndexWriter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexingStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "indexingFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchindexwriter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchQueryWidget",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QHelpSearchQueryWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "search",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "on",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setCompactMode",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchquerywidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHelpSearchResultWidget",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QHelpSearchResultWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "requestShowLink",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchresultwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOptionsWidget",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QOptionsWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "options",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "optionSelectionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qoptionswidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QResultWidget",
+                "lineNumber": 20,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "linkColor",
+                        "read": "linkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setLinkColor"
+                    }
+                ],
+                "qualifiedClassName": "QResultWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "requestShowLink",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            },
+                            {
+                                "type": "QTextDocument::ResourceType"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "doSetSource",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextBrowser"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhelpsearchresultwidget.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labsanimation_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labsanimation_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c9e0cf85a1fa2e4edbffdb7fb16b231a5dab32d
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labsanimation_metatypes.json
@@ -0,0 +1,310 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BoundaryRule"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickBoundaryRule",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "OvershootFilter",
+                        "values": [
+                            "None",
+                            "Peak"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ],
+                    [
+                        {
+                            "className": "QQmlPropertyValueInterceptor",
+                            "id": "\"org.qt-project.Qt.QQmlPropertyValueInterceptor\""
+                        }
+                    ]
+                ],
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "returnToBounds",
+                        "returnType": "bool"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "minimum",
+                        "notify": "minimumChanged",
+                        "read": "minimum",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMinimum"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "minimumOvershoot",
+                        "notify": "minimumOvershootChanged",
+                        "read": "minimumOvershoot",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMinimumOvershoot"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "maximum",
+                        "notify": "maximumChanged",
+                        "read": "maximum",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaximum"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "maximumOvershoot",
+                        "notify": "maximumOvershootChanged",
+                        "read": "maximumOvershoot",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaximumOvershoot"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "overshootScale",
+                        "notify": "overshootScaleChanged",
+                        "read": "overshootScale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOvershootScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "currentOvershoot",
+                        "notify": "currentOvershootChanged",
+                        "read": "currentOvershoot",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "peakOvershoot",
+                        "notify": "peakOvershootChanged",
+                        "read": "peakOvershoot",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "overshootFilter",
+                        "notify": "overshootFilterChanged",
+                        "read": "overshootFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "OvershootFilter",
+                        "user": false,
+                        "write": "setOvershootFilter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "easing",
+                        "notify": "easingChanged",
+                        "read": "easing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QEasingCurve",
+                        "user": false,
+                        "write": "setEasing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "returnDuration",
+                        "notify": "returnDurationChanged",
+                        "read": "returnDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setReturnDuration"
+                    }
+                ],
+                "qualifiedClassName": "QQuickBoundaryRule",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "minimumChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "minimumOvershootChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "maximumChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "maximumOvershootChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "overshootScaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "currentOvershootChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "peakOvershootChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "overshootFilterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "easingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "returnDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "returnedToBounds",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlPropertyValueInterceptor"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickboundaryrule_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labsfolderlistmodel_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labsfolderlistmodel_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0a26de35db243b97a175446aba55aef417294d81
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labsfolderlistmodel_metatypes.json
@@ -0,0 +1,562 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "FileProperty",
+                "gadget": true,
+                "lineNumber": 26,
+                "qualifiedClassName": "FileProperty"
+            }
+        ],
+        "inputFile": "fileproperty_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "FileInfoThread",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "FileInfoThread",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "directoryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            },
+                            {
+                                "name": "fromIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "toIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "directoryUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sortFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "status",
+                                "type": "QQuickFolderListModel::Status"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directoryPath",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "dirChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "updateFile",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "fileinfothread_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FolderListModel"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickFolderListModel",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SortField",
+                        "values": [
+                            "Unsorted",
+                            "Name",
+                            "Time",
+                            "Size",
+                            "Type"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 34,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "isFolder",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            },
+                            {
+                                "name": "property",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "get",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "file",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "indexOf",
+                        "returnType": "int"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "folder",
+                        "notify": "folderChanged",
+                        "read": "folder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "rootFolder",
+                        "read": "rootFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setRootFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "parentFolder",
+                        "notify": "folderChanged",
+                        "read": "parentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "nameFilters",
+                        "read": "nameFilters",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setNameFilters"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "sortField",
+                        "read": "sortField",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SortField",
+                        "user": false,
+                        "write": "setSortField"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "sortReversed",
+                        "read": "sortReversed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortReversed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "showFiles",
+                        "read": "showFiles",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowFiles"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "showDirs",
+                        "read": "showDirs",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowDirs"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "showDirsFirst",
+                        "read": "showDirsFirst",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowDirsFirst"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "showDotAndDotDot",
+                        "read": "showDotAndDotDot",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowDotAndDotDot"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "showHidden",
+                        "read": "showHidden",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowHidden"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "showOnlyReadable",
+                        "read": "showOnlyReadable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowOnlyReadable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "caseSensitive",
+                        "read": "caseSensitive",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCaseSensitive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "revision": 523,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Status",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "sortCaseSensitive",
+                        "read": "sortCaseSensitive",
+                        "required": false,
+                        "revision": 524,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortCaseSensitive"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFolderListModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "folderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rowCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "countChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "statusChanged",
+                        "returnType": "void",
+                        "revision": 523
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_directoryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            },
+                            {
+                                "name": "fromIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "toIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "_q_directoryUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "list",
+                                "type": "QList<FileProperty>"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "_q_sortFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "s",
+                                "type": "QQuickFolderListModel::Status"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "_q_statusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfolderlistmodel_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labsplatform_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labsplatform_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..96ac12fd90123a771f456f0ae1b31afcedc73e6f
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labsplatform_metatypes.json
@@ -0,0 +1,3051 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorDialog"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QColorDialogOptions"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformColorDialog",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "currentColor",
+                        "notify": "currentColorChanged",
+                        "read": "currentColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setCurrentColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColorDialogOptions::ColorDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformColorDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformcolordialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Dialog"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Dialog is an abstract base class"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    }
+                ],
+                "className": "QQuickLabsPlatformDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardCode",
+                        "values": [
+                            "Rejected",
+                            "Accepted"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "data",
+                        "read": "data",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "parentWindow",
+                        "notify": "parentWindowChanged",
+                        "read": "parentWindow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QWindow*",
+                        "user": false,
+                        "write": "setParentWindow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "flags",
+                        "notify": "flagsChanged",
+                        "read": "flags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowFlags",
+                        "user": false,
+                        "write": "setFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "modality",
+                        "notify": "modalityChanged",
+                        "read": "modality",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowModality",
+                        "user": false,
+                        "write": "setModality"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "result",
+                        "notify": "resultChanged",
+                        "read": "result",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setResult"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rejected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "parentWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "flagsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "modalityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resultChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "open",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "close",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "accept",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "reject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FileDialog"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QFileDialogOptions"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformFileDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FileMode",
+                        "values": [
+                            "OpenFile",
+                            "OpenFiles",
+                            "SaveFile"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "fileMode",
+                        "notify": "fileModeChanged",
+                        "read": "fileMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FileMode",
+                        "user": false,
+                        "write": "setFileMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "file",
+                        "notify": "fileChanged",
+                        "read": "file",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "files",
+                        "notify": "filesChanged",
+                        "read": "files",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QUrl>",
+                        "user": false,
+                        "write": "setFiles"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "currentFile",
+                        "notify": "currentFileChanged",
+                        "read": "currentFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "currentFiles",
+                        "notify": "currentFilesChanged",
+                        "read": "currentFiles",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QUrl>",
+                        "user": false,
+                        "write": "setCurrentFiles"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "folder",
+                        "notify": "folderChanged",
+                        "read": "folder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFileDialogOptions::FileDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "nameFilters",
+                        "notify": "nameFiltersChanged",
+                        "read": "nameFilters",
+                        "required": false,
+                        "reset": "resetNameFilters",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setNameFilters"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "selectedNameFilter",
+                        "read": "selectedNameFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformFileNameFilter*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "defaultSuffix",
+                        "notify": "defaultSuffixChanged",
+                        "read": "defaultSuffix",
+                        "required": false,
+                        "reset": "resetDefaultSuffix",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDefaultSuffix"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "acceptLabel",
+                        "notify": "acceptLabelChanged",
+                        "read": "acceptLabel",
+                        "required": false,
+                        "reset": "resetAcceptLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAcceptLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "rejectLabel",
+                        "notify": "rejectLabelChanged",
+                        "read": "rejectLabel",
+                        "required": false,
+                        "reset": "resetRejectLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setRejectLabel"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformFileDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fileModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "fileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "filesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "currentFileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "currentFilesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "folderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "nameFiltersChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "defaultSuffixChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "acceptLabelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "rejectLabelChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformDialog"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQuickLabsPlatformFileNameFilter",
+                "lineNumber": 125,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "index",
+                        "notify": "indexChanged",
+                        "read": "index",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "name",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "extensions",
+                        "notify": "extensionsChanged",
+                        "read": "extensions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformFileNameFilter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "extensions",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "extensionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformfiledialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FolderDialog"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QFileDialogOptions"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformFolderDialog",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "folder",
+                        "notify": "folderChanged",
+                        "read": "folder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "currentFolder",
+                        "notify": "currentFolderChanged",
+                        "read": "currentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFileDialogOptions::FileDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "acceptLabel",
+                        "notify": "acceptLabelChanged",
+                        "read": "acceptLabel",
+                        "required": false,
+                        "reset": "resetAcceptLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAcceptLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "rejectLabel",
+                        "notify": "rejectLabelChanged",
+                        "read": "rejectLabel",
+                        "required": false,
+                        "reset": "resetRejectLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setRejectLabel"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformFolderDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "folderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "acceptLabelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "rejectLabelChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformfolderdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FontDialog"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QFontDialogOptions"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformFontDialog",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "currentFont",
+                        "notify": "currentFontChanged",
+                        "read": "currentFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setCurrentFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFontDialogOptions::FontDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformFontDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentFontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformfontdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQuickLabsPlatformIcon",
+                "gadget": true,
+                "lineNumber": 28,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "mask",
+                        "read": "isMask",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMask"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformIcon"
+            }
+        ],
+        "inputFile": "qquicklabsplatformicon_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Menu"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformMenu"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMenu",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "addItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "insertItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "removeItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "addMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "insertMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "removeMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
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+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "data",
+                        "read": "data",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "items",
+                        "notify": "itemsChanged",
+                        "read": "items",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickLabsPlatformMenuItem>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "menuBar",
+                        "notify": "menuBarChanged",
+                        "read": "menuBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenuBar*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "parentMenu",
+                        "notify": "parentMenuChanged",
+                        "read": "parentMenu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenu*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "systemTrayIcon",
+                        "notify": "systemTrayIconChanged",
+                        "read": "systemTrayIcon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformSystemTrayIcon*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "menuItem",
+                        "read": "menuItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenuItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "minimumWidth",
+                        "notify": "minimumWidthChanged",
+                        "read": "minimumWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "type",
+                        "notify": "typeChanged",
+                        "read": "type",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPlatformMenu::MenuType",
+                        "user": false,
+                        "write": "setType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
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+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "revision": 257,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformMenu",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToShow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "aboutToHide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "itemsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "menuBarChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "parentMenuChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "systemTrayIconChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "minimumWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "typeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "iconChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "open",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "close",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "updateIcon",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmenu_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuBar"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMenuBar",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "addMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "insertMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickLabsPlatformMenu*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "removeMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
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+                        "name": "data",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "menus",
+                        "notify": "menusChanged",
+                        "read": "menus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickLabsPlatformMenu>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "window",
+                        "notify": "windowChanged",
+                        "read": "window",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QWindow*",
+                        "user": false,
+                        "write": "setWindow"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformMenuBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "menusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "windowChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmenubar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuItem"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformMenuItem"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMenuItem",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 34,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "menu",
+                        "notify": "menuChanged",
+                        "read": "menu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenu*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "subMenu",
+                        "notify": "subMenuChanged",
+                        "read": "subMenu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenu*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "group",
+                        "notify": "groupChanged",
+                        "read": "group",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenuItemGroup*",
+                        "user": false,
+                        "write": "setGroup"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "separator",
+                        "notify": "separatorChanged",
+                        "read": "isSeparator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSeparator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "checkable",
+                        "notify": "checkableChanged",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "checked",
+                        "notify": "checkedChanged",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChecked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "role",
+                        "notify": "roleChanged",
+                        "read": "role",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPlatformMenuItem::MenuRole",
+                        "user": false,
+                        "write": "setRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "shortcut",
+                        "notify": "shortcutChanged",
+                        "read": "shortcut",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setShortcut"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "revision": 257,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformMenuItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "hovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "menuChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "subMenuChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "groupChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "separatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "checkableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "checkedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "roleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "shortcutChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "iconChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 16,
+                        "name": "activate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 17,
+                        "name": "updateIcon",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmenuitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuItemGroup"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMenuItemGroup",
+                "lineNumber": 28,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "addItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "removeItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "exclusive",
+                        "notify": "exclusiveChanged",
+                        "read": "isExclusive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExclusive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "checkedItem",
+                        "notify": "checkedItemChanged",
+                        "read": "checkedItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenuItem*",
+                        "user": false,
+                        "write": "setCheckedItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "items",
+                        "notify": "itemsChanged",
+                        "read": "items",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickLabsPlatformMenuItem>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformMenuItemGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickLabsPlatformMenuItem*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "hovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "exclusiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "checkedItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "itemsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmenuitemgroup_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuSeparator"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMenuSeparator",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QQuickLabsPlatformMenuSeparator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformMenuItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmenuseparator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MessageDialog"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformDialogHelper"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformMessageDialog",
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "informativeText",
+                        "notify": "informativeTextChanged",
+                        "read": "informativeText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setInformativeText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "detailedText",
+                        "notify": "detailedTextChanged",
+                        "read": "detailedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDetailedText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "buttons",
+                        "notify": "buttonsChanged",
+                        "read": "buttons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPlatformDialogHelper::StandardButtons",
+                        "user": false,
+                        "write": "setButtons"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformMessageDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "informativeTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "detailedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "buttonsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "okClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "saveClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "saveAllClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "openClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "yesClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "yesToAllClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "noClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "noToAllClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "abortClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "retryClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "ignoreClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "closeClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "cancelClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "discardClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "helpClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "applyClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "resetClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "restoreDefaultsClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "handleClick",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickLabsPlatformDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformmessagedialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "StandardPaths"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QStandardPaths"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformStandardPaths",
+                "lineNumber": 31,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "displayName",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "executableName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "paths",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "findExecutable",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "executableName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "isCloned": true,
+                        "name": "findExecutable",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "options",
+                                "type": "QStandardPaths::LocateOptions"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "locate",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "isCloned": true,
+                        "name": "locate",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "options",
+                                "type": "QStandardPaths::LocateOptions"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "locateAll",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "locateAll",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "testMode",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setTestModeEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "standardLocations",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "writableLocation",
+                        "returnType": "QUrl"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickLabsPlatformStandardPaths",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformstandardpaths_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "SystemTrayIcon"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformSystemTrayIcon"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickLabsPlatformSystemTrayIcon",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 33,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "available",
+                        "read": "isAvailable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "supportsMessages",
+                        "read": "supportsMessages",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "tooltip",
+                        "notify": "tooltipChanged",
+                        "read": "tooltip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTooltip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "menu",
+                        "notify": "menuChanged",
+                        "read": "menu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformMenu*",
+                        "user": false,
+                        "write": "setMenu"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "geometry",
+                        "notify": "geometryChanged",
+                        "read": "geometry",
+                        "required": false,
+                        "revision": 257,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "revision": 257,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabsPlatformIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabsPlatformSystemTrayIcon",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reason",
+                                "type": "QPlatformSystemTrayIcon::ActivationReason"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "messageClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "tooltipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "menuChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "geometryChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "iconChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "show",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "hide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "iconType",
+                                "type": "QPlatformSystemTrayIcon::MessageIcon"
+                            },
+                            {
+                                "name": "msecs",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "iconType",
+                                "type": "QPlatformSystemTrayIcon::MessageIcon"
+                            }
+                        ],
+                        "index": 10,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 12,
+                        "name": "updateIcon",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabsplatformsystemtrayicon_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformColorDialog",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformColorDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformColorDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformcolordialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformFileDialog",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformFileDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformFileDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformfiledialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformFontDialog",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformFontDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformFontDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformfontdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformMenu",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformMenu",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformmenu_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformMenuItem",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformMenuItem",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformMenuItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformmenuitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformMessageDialog",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformMessageDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformMessageDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformmessagedialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPlatformSystemTrayIcon",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QWidgetPlatformSystemTrayIcon",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformSystemTrayIcon"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetplatformsystemtrayicon_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labsqmlmodels_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labsqmlmodels_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..01e9d84b7a1c0e5b2153bb23f87b50cb429b3acb
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labsqmlmodels_metatypes.json
@@ -0,0 +1,1127 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "delegate"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "DelegateChoice"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQmlDelegateChoice",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "roleValue",
+                        "notify": "roleValueChanged",
+                        "read": "roleValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setRoleValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "row",
+                        "notify": "rowChanged",
+                        "read": "row",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "index",
+                        "notify": "indexChanged",
+                        "read": "row",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "column",
+                        "notify": "columnChanged",
+                        "read": "column",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setColumn"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQmlDelegateChoice",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "roleValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "columnChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "changed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "choices"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "DelegateChooser"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQmlDelegateChooser",
+                "lineNumber": 70,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "role",
+                        "notify": "roleChanged",
+                        "read": "role",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setRole"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "choices",
+                        "read": "choices",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQmlDelegateChoice>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlDelegateChooser",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "roleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlAbstractDelegateComponent"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldelegatecomponent_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "columns"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "TableModel"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQmlTableModel",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 33,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "appendRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rowIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "getRow",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "row",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "insertRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fromRowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "toRowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "rows",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "moveRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fromRowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "toRowIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "isCloned": true,
+                        "name": "moveRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "rows",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "removeRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rowIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "isCloned": true,
+                        "name": "removeRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rowIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "row",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "data",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "value",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setData",
+                        "returnType": "bool"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "columnCount",
+                        "notify": "columnCountChanged",
+                        "read": "columnCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "rowCount",
+                        "notify": "rowCountChanged",
+                        "read": "rowCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "rows",
+                        "notify": "rowsChanged",
+                        "read": "rows",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setRows"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "columns",
+                        "read": "columns",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQmlTableModelColumn>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlTableModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "columnCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rowCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "rowsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractTableModel"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmltablemodel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TableModelColumn"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQmlTableModelColumn",
+                "lineNumber": 30,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "display",
+                        "notify": "displayChanged",
+                        "read": "display",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setDisplay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "setDisplay",
+                        "notify": "setDisplayChanged",
+                        "read": "getSetDisplay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetDisplay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "decoration",
+                        "notify": "decorationChanged",
+                        "read": "decoration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setDecoration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "setDecoration",
+                        "notify": "setDecorationChanged",
+                        "read": "getSetDecoration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetDecoration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "edit",
+                        "notify": "editChanged",
+                        "read": "edit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "setEdit",
+                        "notify": "setEditChanged",
+                        "read": "getSetEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "toolTip",
+                        "notify": "toolTipChanged",
+                        "read": "toolTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setToolTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "setToolTip",
+                        "notify": "setToolTipChanged",
+                        "read": "getSetToolTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetToolTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "statusTip",
+                        "notify": "statusTipChanged",
+                        "read": "statusTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setStatusTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "setStatusTip",
+                        "notify": "setStatusTipChanged",
+                        "read": "getSetStatusTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetStatusTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "whatsThis",
+                        "notify": "whatsThisChanged",
+                        "read": "whatsThis",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setWhatsThis"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "setWhatsThis",
+                        "notify": "setWhatsThisChanged",
+                        "read": "getSetWhatsThis",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetWhatsThis"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "setFont",
+                        "notify": "setFontChanged",
+                        "read": "getSetFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "textAlignment",
+                        "notify": "textAlignmentChanged",
+                        "read": "textAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setTextAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "setTextAlignment",
+                        "notify": "setTextAlignmentChanged",
+                        "read": "getSetTextAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetTextAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "setBackground",
+                        "notify": "setBackgroundChanged",
+                        "read": "getSetBackground",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "foreground",
+                        "notify": "foregroundChanged",
+                        "read": "foreground",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setForeground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "setForeground",
+                        "notify": "setForegroundChanged",
+                        "read": "getSetForeground",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetForeground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "checkState",
+                        "notify": "checkStateChanged",
+                        "read": "checkState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setCheckState"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "setCheckState",
+                        "notify": "setCheckStateChanged",
+                        "read": "getSetCheckState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetCheckState"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "accessibleText",
+                        "notify": "accessibleTextChanged",
+                        "read": "accessibleText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setAccessibleText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "setAccessibleText",
+                        "notify": "setAccessibleTextChanged",
+                        "read": "getSetAccessibleText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetAccessibleText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "accessibleDescription",
+                        "notify": "accessibleDescriptionChanged",
+                        "read": "accessibleDescription",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setAccessibleDescription"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "setAccessibleDescription",
+                        "notify": "setAccessibleDescriptionChanged",
+                        "read": "getSetAccessibleDescription",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetAccessibleDescription"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "sizeHint",
+                        "notify": "sizeHintChanged",
+                        "read": "sizeHint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSizeHint"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "setSizeHint",
+                        "notify": "setSizeHintChanged",
+                        "read": "getSetSizeHint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setSetSizeHint"
+                    }
+                ],
+                "qualifiedClassName": "QQmlTableModelColumn",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "displayChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "setDisplayChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "decorationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "setDecorationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "editChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "setEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "toolTipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "setToolTipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "statusTipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "setStatusTipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "whatsThisChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "setWhatsThisChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "setFontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "textAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "setTextAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "backgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "setBackgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "foregroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "setForegroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "checkStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "setCheckStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "accessibleTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "setAccessibleTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "accessibleDescriptionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "setAccessibleDescriptionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "sizeHintChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "setSizeHintChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmltablemodelcolumn_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labssettings_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labssettings_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..7a6bc9be0b09fbee9dee53088034097db2f96527
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labssettings_metatypes.json
@@ -0,0 +1,133 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Settings"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQmlSettings",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "defaultValue",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "value",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "isCloned": true,
+                        "name": "value",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "value",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "sync",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "category",
+                        "read": "category",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCategory"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "fileName",
+                        "read": "fileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setFileName"
+                    }
+                ],
+                "qualifiedClassName": "QQmlSettings",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_propertyChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlsettings_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labssharedimage_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labssharedimage_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..9873fb03fd41ad4920c35f9f2dbe669891c1c881
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labssharedimage_metatypes.json
@@ -0,0 +1,48 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QSharedImageLoader",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QSharedImageLoader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsharedimageloader_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QuickSharedImageLoader",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QuickSharedImageLoader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSharedImageLoader"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsharedimageprovider_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6labswavefrontmesh_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6labswavefrontmesh_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..82bf101389c1ffcabe556993d85e5421f2164ce4
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6labswavefrontmesh_metatypes.json
@@ -0,0 +1,145 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "WavefrontMesh"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QWavefrontMesh",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Error",
+                        "values": [
+                            "NoError",
+                            "InvalidSourceError",
+                            "UnsupportedFaceShapeError",
+                            "UnsupportedIndexSizeError",
+                            "FileNotFoundError",
+                            "NoAttributesError",
+                            "MissingPositionAttributeError",
+                            "MissingTextureCoordinateAttributeError",
+                            "MissingPositionAndTextureCoordinateAttributesError",
+                            "TooManyAttributesError",
+                            "InvalidPlaneDefinitionError"
+                        ]
+                    }
+                ],
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "lastError",
+                        "notify": "lastErrorChanged",
+                        "read": "lastError",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Error",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "projectionPlaneV",
+                        "notify": "projectionPlaneVChanged",
+                        "read": "projectionPlaneV",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVector3D",
+                        "user": false,
+                        "write": "setProjectionPlaneV"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "projectionPlaneW",
+                        "notify": "projectionPlaneWChanged",
+                        "read": "projectionPlaneW",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVector3D",
+                        "user": false,
+                        "write": "setProjectionPlaneW"
+                    }
+                ],
+                "qualifiedClassName": "QWavefrontMesh",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "lastErrorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "projectionPlaneVChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "projectionPlaneWChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 4,
+                        "name": "readData",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickShaderEffectMesh"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwavefrontmesh_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6network_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6network_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c599046345c71fb64b82b1a9e7485fc78528f708
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6network_metatypes.json
@@ -0,0 +1,5197 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QNetworkConnectionMonitor",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QNetworkConnectionMonitor",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isOnline",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "reachabilityChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetconmonitor_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpHeaders",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "WellKnownHeader",
+                        "values": [
+                            "AIM",
+                            "Accept",
+                            "AcceptAdditions",
+                            "AcceptCH",
+                            "AcceptDatetime",
+                            "AcceptEncoding",
+                            "AcceptFeatures",
+                            "AcceptLanguage",
+                            "AcceptPatch",
+                            "AcceptPost",
+                            "AcceptRanges",
+                            "AcceptSignature",
+                            "AccessControlAllowCredentials",
+                            "AccessControlAllowHeaders",
+                            "AccessControlAllowMethods",
+                            "AccessControlAllowOrigin",
+                            "AccessControlExposeHeaders",
+                            "AccessControlMaxAge",
+                            "AccessControlRequestHeaders",
+                            "AccessControlRequestMethod",
+                            "Age",
+                            "Allow",
+                            "ALPN",
+                            "AltSvc",
+                            "AltUsed",
+                            "Alternates",
+                            "ApplyToRedirectRef",
+                            "AuthenticationControl",
+                            "AuthenticationInfo",
+                            "Authorization",
+                            "CacheControl",
+                            "CacheStatus",
+                            "CalManagedID",
+                            "CalDAVTimezones",
+                            "CapsuleProtocol",
+                            "CDNCacheControl",
+                            "CDNLoop",
+                            "CertNotAfter",
+                            "CertNotBefore",
+                            "ClearSiteData",
+                            "ClientCert",
+                            "ClientCertChain",
+                            "Close",
+                            "Connection",
+                            "ContentDigest",
+                            "ContentDisposition",
+                            "ContentEncoding",
+                            "ContentID",
+                            "ContentLanguage",
+                            "ContentLength",
+                            "ContentLocation",
+                            "ContentRange",
+                            "ContentSecurityPolicy",
+                            "ContentSecurityPolicyReportOnly",
+                            "ContentType",
+                            "Cookie",
+                            "CrossOriginEmbedderPolicy",
+                            "CrossOriginEmbedderPolicyReportOnly",
+                            "CrossOriginOpenerPolicy",
+                            "CrossOriginOpenerPolicyReportOnly",
+                            "CrossOriginResourcePolicy",
+                            "DASL",
+                            "Date",
+                            "DAV",
+                            "DeltaBase",
+                            "Depth",
+                            "Destination",
+                            "DifferentialID",
+                            "DPoP",
+                            "DPoPNonce",
+                            "EarlyData",
+                            "ETag",
+                            "Expect",
+                            "ExpectCT",
+                            "Expires",
+                            "Forwarded",
+                            "From",
+                            "Hobareg",
+                            "Host",
+                            "If",
+                            "IfMatch",
+                            "IfModifiedSince",
+                            "IfNoneMatch",
+                            "IfRange",
+                            "IfScheduleTagMatch",
+                            "IfUnmodifiedSince",
+                            "IM",
+                            "IncludeReferredTokenBindingID",
+                            "KeepAlive",
+                            "Label",
+                            "LastEventID",
+                            "LastModified",
+                            "Link",
+                            "Location",
+                            "LockToken",
+                            "MaxForwards",
+                            "MementoDatetime",
+                            "Meter",
+                            "MIMEVersion",
+                            "Negotiate",
+                            "NEL",
+                            "ODataEntityId",
+                            "ODataIsolation",
+                            "ODataMaxVersion",
+                            "ODataVersion",
+                            "OptionalWWWAuthenticate",
+                            "OrderingType",
+                            "Origin",
+                            "OriginAgentCluster",
+                            "OSCORE",
+                            "OSLCCoreVersion",
+                            "Overwrite",
+                            "PingFrom",
+                            "PingTo",
+                            "Position",
+                            "Prefer",
+                            "PreferenceApplied",
+                            "Priority",
+                            "ProxyAuthenticate",
+                            "ProxyAuthenticationInfo",
+                            "ProxyAuthorization",
+                            "ProxyStatus",
+                            "PublicKeyPins",
+                            "PublicKeyPinsReportOnly",
+                            "Range",
+                            "RedirectRef",
+                            "Referer",
+                            "Refresh",
+                            "ReplayNonce",
+                            "ReprDigest",
+                            "RetryAfter",
+                            "ScheduleReply",
+                            "ScheduleTag",
+                            "SecPurpose",
+                            "SecTokenBinding",
+                            "SecWebSocketAccept",
+                            "SecWebSocketExtensions",
+                            "SecWebSocketKey",
+                            "SecWebSocketProtocol",
+                            "SecWebSocketVersion",
+                            "Server",
+                            "ServerTiming",
+                            "SetCookie",
+                            "Signature",
+                            "SignatureInput",
+                            "SLUG",
+                            "SoapAction",
+                            "StatusURI",
+                            "StrictTransportSecurity",
+                            "Sunset",
+                            "SurrogateCapability",
+                            "SurrogateControl",
+                            "TCN",
+                            "TE",
+                            "Timeout",
+                            "Topic",
+                            "Traceparent",
+                            "Tracestate",
+                            "Trailer",
+                            "TransferEncoding",
+                            "TTL",
+                            "Upgrade",
+                            "Urgency",
+                            "UserAgent",
+                            "VariantVary",
+                            "Vary",
+                            "Via",
+                            "WantContentDigest",
+                            "WantReprDigest",
+                            "WWWAuthenticate",
+                            "XContentTypeOptions",
+                            "XFrameOptions",
+                            "AcceptCharset",
+                            "CPEPInfo",
+                            "Pragma",
+                            "ProtocolInfo",
+                            "ProtocolQuery"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 19,
+                "qualifiedClassName": "QHttpHeaders"
+            }
+        ],
+        "inputFile": "qhttpheaders.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSslPreSharedKeyAuthenticator",
+                "gadget": true,
+                "lineNumber": 17,
+                "qualifiedClassName": "QSslPreSharedKeyAuthenticator"
+            }
+        ],
+        "inputFile": "qsslpresharedkeyauthenticator.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractNetworkCache",
+                "lineNumber": 78,
+                "object": true,
+                "qualifiedClassName": "QAbstractNetworkCache",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractnetworkcache.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractSocket",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SocketType",
+                        "values": [
+                            "TcpSocket",
+                            "UdpSocket",
+                            "SctpSocket",
+                            "UnknownSocketType"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "NetworkLayerProtocol",
+                        "values": [
+                            "IPv4Protocol",
+                            "IPv6Protocol",
+                            "AnyIPProtocol",
+                            "UnknownNetworkLayerProtocol"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SocketError",
+                        "values": [
+                            "ConnectionRefusedError",
+                            "RemoteHostClosedError",
+                            "HostNotFoundError",
+                            "SocketAccessError",
+                            "SocketResourceError",
+                            "SocketTimeoutError",
+                            "DatagramTooLargeError",
+                            "NetworkError",
+                            "AddressInUseError",
+                            "SocketAddressNotAvailableError",
+                            "UnsupportedSocketOperationError",
+                            "UnfinishedSocketOperationError",
+                            "ProxyAuthenticationRequiredError",
+                            "SslHandshakeFailedError",
+                            "ProxyConnectionRefusedError",
+                            "ProxyConnectionClosedError",
+                            "ProxyConnectionTimeoutError",
+                            "ProxyNotFoundError",
+                            "ProxyProtocolError",
+                            "OperationError",
+                            "SslInternalError",
+                            "SslInvalidUserDataError",
+                            "TemporaryError",
+                            "UnknownSocketError"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SocketState",
+                        "values": [
+                            "UnconnectedState",
+                            "HostLookupState",
+                            "ConnectingState",
+                            "ConnectedState",
+                            "BoundState",
+                            "ListeningState",
+                            "ClosingState"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SocketOption",
+                        "values": [
+                            "LowDelayOption",
+                            "KeepAliveOption",
+                            "MulticastTtlOption",
+                            "MulticastLoopbackOption",
+                            "TypeOfServiceOption",
+                            "SendBufferSizeSocketOption",
+                            "ReceiveBufferSizeSocketOption",
+                            "PathMtuSocketOption"
+                        ]
+                    }
+                ],
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QAbstractSocket",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "hostFound",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "connected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "disconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_connectToNextAddress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QHostInfo"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "_q_startConnecting",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_abortConnectionAttempt",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_testConnection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QIODevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractSocketEngine",
+                "lineNumber": 50,
+                "object": true,
+                "qualifiedClassName": "QAbstractSocketEngine",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "readNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "writeNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "closeNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "exceptionNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "connectionNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractsocketengine_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAuthenticator",
+                "gadget": true,
+                "lineNumber": 17,
+                "qualifiedClassName": "QAuthenticator"
+            }
+        ],
+        "inputFile": "qauthenticator.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "RegisterEnumClassesUnscoped",
+                        "value": "false"
+                    }
+                ],
+                "className": "QDnsTlsAssociationRecord",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "CertificateUsage",
+                        "type": "quint8",
+                        "values": [
+                            "CertificateAuthorityConstrait",
+                            "ServiceCertificateConstraint",
+                            "TrustAnchorAssertion",
+                            "DomainIssuedCertificate",
+                            "PrivateUse",
+                            "PKIX_TA",
+                            "PKIX_EE",
+                            "DANE_TA",
+                            "DANE_EE",
+                            "PrivCert"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Selector",
+                        "type": "quint8",
+                        "values": [
+                            "FullCertificate",
+                            "SubjectPublicKeyInfo",
+                            "PrivateUse",
+                            "Cert",
+                            "SPKI",
+                            "PrivSel"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "MatchingType",
+                        "type": "quint8",
+                        "values": [
+                            "Exact",
+                            "Sha256",
+                            "Sha512",
+                            "PrivateUse",
+                            "PrivMatch"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 144,
+                "qualifiedClassName": "QDnsTlsAssociationRecord"
+            },
+            {
+                "className": "QDnsLookup",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Error",
+                        "values": [
+                            "NoError",
+                            "ResolverError",
+                            "OperationCancelledError",
+                            "InvalidRequestError",
+                            "InvalidReplyError",
+                            "ServerFailureError",
+                            "ServerRefusedError",
+                            "NotFoundError",
+                            "TimeoutError"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Type",
+                        "values": [
+                            "A",
+                            "AAAA",
+                            "ANY",
+                            "CNAME",
+                            "MX",
+                            "NS",
+                            "PTR",
+                            "SRV",
+                            "TLSA",
+                            "TXT"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Protocol",
+                        "type": "quint8",
+                        "values": [
+                            "Standard",
+                            "DnsOverTls"
+                        ]
+                    }
+                ],
+                "lineNumber": 215,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "error",
+                        "notify": "finished",
+                        "read": "error",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Error",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "authenticData",
+                        "notify": "finished",
+                        "read": "isAuthenticData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "errorString",
+                        "notify": "finished",
+                        "read": "errorString",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableName",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "name",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "bindable": "bindableType",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "type",
+                        "notify": "typeChanged",
+                        "read": "type",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Type",
+                        "user": false,
+                        "write": "setType"
+                    },
+                    {
+                        "bindable": "bindableNameserver",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "nameserver",
+                        "notify": "nameserverChanged",
+                        "read": "nameserver",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QHostAddress",
+                        "user": false,
+                        "write": "setNameserver"
+                    },
+                    {
+                        "bindable": "bindableNameserverPort",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "nameserverPort",
+                        "notify": "nameserverPortChanged",
+                        "read": "nameserverPort",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "quint16",
+                        "user": false,
+                        "write": "setNameserverPort"
+                    },
+                    {
+                        "bindable": "bindableNameserverProtocol",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "nameserverProtocol",
+                        "notify": "nameserverProtocolChanged",
+                        "read": "nameserverProtocol",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Protocol",
+                        "user": false,
+                        "write": "setNameserverProtocol"
+                    }
+                ],
+                "qualifiedClassName": "QDnsLookup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QDnsLookup::Type"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "typeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "nameserver",
+                                "type": "QHostAddress"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "nameserverChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "port",
+                                "type": "quint16"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "nameserverPortChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "protocol",
+                                "type": "QDnsLookup::Protocol"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "nameserverProtocolChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "abort",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "lookup",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdnslookup.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDnsLookupRunnable",
+                "lineNumber": 197,
+                "object": true,
+                "qualifiedClassName": "QDnsLookupRunnable",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QDnsLookupReply"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QRunnable"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdnslookup_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDtlsClientVerifier",
+                "lineNumber": 43,
+                "object": true,
+                "qualifiedClassName": "QDtlsClientVerifier",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QDtls",
+                "lineNumber": 82,
+                "object": true,
+                "qualifiedClassName": "QDtls",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "pskRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "handshakeTimeout",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdtls.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHostAddress",
+                "gadget": true,
+                "lineNumber": 38,
+                "qualifiedClassName": "QHostAddress"
+            }
+        ],
+        "inputFile": "qhostaddress.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHostInfo",
+                "gadget": true,
+                "lineNumber": 18,
+                "qualifiedClassName": "QHostInfo"
+            }
+        ],
+        "inputFile": "qhostinfo.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHostInfoResult",
+                "lineNumber": 42,
+                "object": true,
+                "qualifiedClassName": "QHostInfoResult",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "info",
+                                "type": "QHostInfo"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "resultsReady",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "info",
+                                "type": "QHostInfo"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "finalizePostResultsReady",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhostinfo_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttp2Stream",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "State",
+                        "values": [
+                            "Idle",
+                            "ReservedRemote",
+                            "Open",
+                            "HalfClosedLocal",
+                            "HalfClosedRemote",
+                            "Closed"
+                        ]
+                    }
+                ],
+                "lineNumber": 93,
+                "object": true,
+                "qualifiedClassName": "QHttp2Stream",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "headers",
+                                "type": "HPack::HttpHeader"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "headersReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "headersUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "Http2::Http2Error"
+                            },
+                            {
+                                "name": "errorString",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newState",
+                                "type": "QHttp2Stream::State"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newStreamID",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "promisedStreamReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "uploadBlocked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "dataReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "rstFrameRecived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytesWritten",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "bytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorString",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "uploadDeviceError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "uploadFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "Http2::Http2Error"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "sendRST_STREAM",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "headers",
+                                "type": "HPack::HttpHeader"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "priority",
+                                "type": "quint8"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "sendHEADERS",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "headers",
+                                "type": "HPack::HttpHeader"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 13,
+                        "isCloned": true,
+                        "name": "sendHEADERS",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "device",
+                                "type": "QIODevice*"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "sendDATA",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "device",
+                                "type": "QNonContiguousByteDevice*"
+                            },
+                            {
+                                "name": "endStream",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "sendDATA",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "delta",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "sendWINDOW_UPDATE",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 17,
+                        "name": "maybeResumeUpload",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 18,
+                        "name": "uploadDeviceReadChannelFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 19,
+                        "name": "uploadDeviceDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QHttp2Connection",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "CreateStreamError",
+                        "values": [
+                            "MaxConcurrentStreamsReached",
+                            "StreamIdsExhausted",
+                            "ReceivedGOAWAY",
+                            "UnknownError"
+                        ]
+                    }
+                ],
+                "lineNumber": 205,
+                "object": true,
+                "qualifiedClassName": "QHttp2Connection",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stream",
+                                "type": "QHttp2Stream*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "newIncomingStream",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stream",
+                                "type": "QHttp2Stream*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "newPromisedStream",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "errorReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "connectionClosed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "settingsFrameReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "QHttp2Connection::PingState"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "pingFrameRecived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "Http2::Http2Error"
+                            },
+                            {
+                                "name": "errorString",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "Http2::Http2Error"
+                            },
+                            {
+                                "name": "lastStreamID",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "receivedGOAWAY",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "streamID",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "receivedEND_STREAM",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "sendPing",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QByteArrayView"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "sendPing",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "handleReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "handleConnectionClosure",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttp2connection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttp2ProtocolHandler",
+                "lineNumber": 46,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "handleConnectionClosure",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "ensureClientPrefaceSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_receiveReply",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "sendRequest",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "streamID",
+                                "type": "quint32"
+                            },
+                            {
+                                "name": "delta",
+                                "type": "quint32"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "sendWINDOW_UPDATE",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "resumeSuspendedStreams",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QHttp2ProtocolHandler",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_uploadDataReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "_q_replyDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "uploadData",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "_q_uploadDataDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QAbstractProtocolHandler"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttp2protocolhandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpMultiPart",
+                "lineNumber": 58,
+                "object": true,
+                "qualifiedClassName": "QHttpMultiPart",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpmultipart.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpNetworkConnection",
+                "lineNumber": 55,
+                "object": true,
+                "qualifiedClassName": "QHttpNetworkConnection",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isOnline",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "onlineStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "_q_startNextRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QHostInfo"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "_q_hostLookupFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_connectDelayedChannel",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpnetworkconnection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpNetworkConnectionChannel",
+                "lineNumber": 64,
+                "object": true,
+                "qualifiedClassName": "QHttpNetworkConnectionChannel",
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 0,
+                        "name": "_q_receiveReply",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "bytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "_q_bytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 2,
+                        "name": "_q_readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 3,
+                        "name": "_q_disconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QAbstractSocket*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_connected_abstract_socket",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QLocalSocket*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "_q_connected_local_socket",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 6,
+                        "name": "_q_connected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "_q_error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "auth",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "_q_proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 9,
+                        "name": "_q_uploadDataReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 10,
+                        "name": "_q_encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "_q_sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "_q_preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "bytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "_q_encryptedBytesWritten",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpnetworkconnectionchannel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpNetworkReply",
+                "lineNumber": 57,
+                "object": true,
+                "qualifiedClassName": "QHttpNetworkReply",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "socketStartedConnecting",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "requestSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "name": "detail",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "finishedWithError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            }
+                        ],
+                        "index": 8,
+                        "isCloned": true,
+                        "name": "finishedWithError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "headerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "done",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "total",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "dataReadProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "done",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "total",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "dataSendProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "request",
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "cacheCredentials",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "request",
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "authenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "httpStatus",
+                                "type": "int"
+                            },
+                            {
+                                "name": "maxRedirectsRemaining",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "redirected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QHttpNetworkHeader"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpnetworkreply_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpSocketEngine",
+                "lineNumber": 36,
+                "object": true,
+                "qualifiedClassName": "QHttpSocketEngine",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "slotSocketConnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "slotSocketDisconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "slotSocketReadNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "slotSocketBytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "slotSocketError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "slotSocketStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "emitPendingReadNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "emitPendingWriteNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "emitPendingConnectionNotification",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSocketEngine"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpsocketengine_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHttpThreadDelegate",
+                "lineNumber": 48,
+                "object": true,
+                "qualifiedClassName": "QHttpThreadDelegate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "request",
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "authenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QList<QSslError>"
+                            },
+                            {
+                                "type": "bool*"
+                            },
+                            {
+                                "type": "QList<QSslError>*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QSslConfiguration"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "sslConfigurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "socketStartedConnecting",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "requestSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QHttpHeaders"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "bool"
+                            },
+                            {
+                                "type": "QSharedPointer<char>"
+                            },
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "bool"
+                            },
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "downloadMetaData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "downloadProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "downloadData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "downloadFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "httpStatus",
+                                "type": "int"
+                            },
+                            {
+                                "name": "maxRedirectsRemainig",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "redirected",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "startRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "abortRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "readBufferSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "readBufferFreed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "startRequestSynchronously",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 19,
+                        "name": "readyReadSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 20,
+                        "name": "finishedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "name": "detail",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "finishedWithErrorSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            }
+                        ],
+                        "index": 22,
+                        "isCloned": true,
+                        "name": "finishedWithErrorSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 23,
+                        "name": "synchronousFinishedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "name": "detail",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "synchronousFinishedWithErrorSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errorCode",
+                                "type": "QNetworkReply::NetworkError"
+                            }
+                        ],
+                        "index": 25,
+                        "isCloned": true,
+                        "name": "synchronousFinishedWithErrorSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 26,
+                        "name": "headerChangedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 27,
+                        "name": "synchronousHeaderChangedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "done",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "total",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "dataReadProgressSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "request",
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "cacheCredentialsSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 30,
+                        "name": "encryptedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "sslErrorsSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "preSharedKeyAuthenticationRequiredSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "request",
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "synchronousAuthenticationRequiredSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "synchronousProxyAuthenticationRequiredSlot",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QNonContiguousByteDeviceThreadForwardImpl",
+                "lineNumber": 163,
+                "object": true,
+                "qualifiedClassName": "QNonContiguousByteDeviceThreadForwardImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "wantData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "amount",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "processedData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "resetData",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "dataArray",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "dataAtEnd",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "dataSize",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "haveDataSlot",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNonContiguousByteDevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qhttpthreaddelegate_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLocalServer",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SocketOption",
+                        "values": [
+                            "NoOptions",
+                            "UserAccessOption",
+                            "GroupAccessOption",
+                            "OtherAccessOption",
+                            "WorldAccessOption",
+                            "AbstractNamespaceOption"
+                        ]
+                    },
+                    {
+                        "alias": "SocketOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "SocketOptions",
+                        "values": [
+                            "NoOptions",
+                            "UserAccessOption",
+                            "GroupAccessOption",
+                            "OtherAccessOption",
+                            "WorldAccessOption",
+                            "AbstractNamespaceOption"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableSocketOptions",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "socketOptions",
+                        "read": "socketOptions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SocketOptions",
+                        "user": false,
+                        "write": "setSocketOptions"
+                    }
+                ],
+                "qualifiedClassName": "QLocalServer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "newConnection",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "_q_onNewConnection",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlocalserver.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLocalSocket",
+                "enums": [
+                    {
+                        "alias": "SocketOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "SocketOptions",
+                        "values": [
+                            "NoOptions",
+                            "AbstractNamespaceOption"
+                        ]
+                    }
+                ],
+                "lineNumber": 21,
+                "object": true,
+                "properties": [
+                    {
+                        "bindable": "bindableSocketOptions",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "socketOptions",
+                        "read": "socketOptions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SocketOptions",
+                        "user": false,
+                        "write": "setSocketOptions"
+                    }
+                ],
+                "qualifiedClassName": "QLocalSocket",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "connected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "disconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socketError",
+                                "type": "QLocalSocket::LocalSocketError"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socketState",
+                                "type": "QLocalSocket::LocalSocketState"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "_q_pipeClosed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "ulong"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "_q_winError",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QIODevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlocalsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNativeSocketEngine",
+                "lineNumber": 101,
+                "object": true,
+                "qualifiedClassName": "QNativeSocketEngine",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "connectionNotification",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSocketEngine"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnativesocketengine_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkAccessBackend",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TargetType",
+                        "values": [
+                            "Networked",
+                            "Local"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SecurityFeature",
+                        "values": [
+                            "None",
+                            "TLS"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "IOFeature",
+                        "values": [
+                            "None",
+                            "ZeroCopy",
+                            "NeedResetableUpload",
+                            "SupportsSynchronousMode"
+                        ]
+                    }
+                ],
+                "lineNumber": 38,
+                "object": true,
+                "qualifiedClassName": "QNetworkAccessBackend",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 1,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "code",
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "name": "errorString",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "auth",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "auth",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "authenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 5,
+                        "name": "metaDataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "destination",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "redirectionRequested",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QNetworkAccessBackendFactory",
+                "lineNumber": 145,
+                "object": true,
+                "qualifiedClassName": "QNetworkAccessBackendFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkaccessbackend_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkAccessCache",
+                "lineNumber": 34,
+                "object": true,
+                "qualifiedClassName": "QNetworkAccessCache",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkAccessCache::CacheableObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "entryReady",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkaccesscache_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkAccessFileBackend",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QNetworkAccessFileBackend",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "uploadReadyReadSlot",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkAccessBackend"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkaccessfilebackend_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkAccessManager",
+                "lineNumber": 35,
+                "object": true,
+                "qualifiedClassName": "QNetworkAccessManager",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QNetworkReply*"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "authenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QNetworkReply*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QNetworkReply*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QNetworkReply*"
+                            },
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reply",
+                                "type": "QNetworkReply*"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 6,
+                        "name": "supportedSchemesImplementation",
+                        "returnType": "QStringList"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "_q_replySslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "_q_replyPreSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkaccessmanager.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkCookie",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SameSite",
+                        "values": [
+                            "Default",
+                            "None",
+                            "Lax",
+                            "Strict"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 22,
+                "qualifiedClassName": "QNetworkCookie"
+            }
+        ],
+        "inputFile": "qnetworkcookie.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkCookieJar",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QNetworkCookieJar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkcookiejar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkDiskCache",
+                "lineNumber": 15,
+                "object": true,
+                "qualifiedClassName": "QNetworkDiskCache",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractNetworkCache"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkdiskcache.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkFile",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QNetworkFile",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "ok",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QHttpHeaders::WellKnownHeader"
+                            },
+                            {
+                                "name": "value",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "headerRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "networkError",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "open",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "close",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFile"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkfile_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "RegisterEnumClassesUnscoped",
+                        "value": "false"
+                    }
+                ],
+                "className": "QNetworkInformation",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Reachability",
+                        "values": [
+                            "Unknown",
+                            "Disconnected",
+                            "Local",
+                            "Site",
+                            "Online"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TransportMedium",
+                        "values": [
+                            "Unknown",
+                            "Ethernet",
+                            "Cellular",
+                            "WiFi",
+                            "Bluetooth"
+                        ]
+                    },
+                    {
+                        "alias": "Feature",
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "Features",
+                        "values": [
+                            "Reachability",
+                            "CaptivePortal",
+                            "TransportMedium",
+                            "Metered"
+                        ]
+                    }
+                ],
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "reachability",
+                        "notify": "reachabilityChanged",
+                        "read": "reachability",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Reachability",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "isBehindCaptivePortal",
+                        "notify": "isBehindCaptivePortalChanged",
+                        "read": "isBehindCaptivePortal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "transportMedium",
+                        "notify": "transportMediumChanged",
+                        "read": "transportMedium",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TransportMedium",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "isMetered",
+                        "notify": "isMeteredChanged",
+                        "read": "isMetered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QNetworkInformation",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newReachability",
+                                "type": "QNetworkInformation::Reachability"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "reachabilityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "isBehindCaptivePortalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QNetworkInformation::TransportMedium"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "transportMediumChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isMetered",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "isMeteredChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkinformation.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkInformationBackend",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QNetworkInformationBackend",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reachability",
+                                "type": "QNetworkInformation::Reachability"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "reachabilityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "behindPortal",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "behindCaptivePortalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "medium",
+                                "type": "QNetworkInformation::TransportMedium"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "transportMediumChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isMetered",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "isMeteredChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QNetworkInformationBackendFactory",
+                "lineNumber": 135,
+                "object": true,
+                "qualifiedClassName": "QNetworkInformationBackendFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkinformation_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkInterface",
+                "enums": [
+                    {
+                        "alias": "InterfaceFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "InterfaceFlags",
+                        "values": [
+                            "IsUp",
+                            "IsRunning",
+                            "CanBroadcast",
+                            "IsLoopBack",
+                            "IsPointToPoint",
+                            "CanMulticast"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "InterfaceType",
+                        "values": [
+                            "Loopback",
+                            "Virtual",
+                            "Ethernet",
+                            "Slip",
+                            "CanBus",
+                            "Ppp",
+                            "Fddi",
+                            "Wifi",
+                            "Ieee80211",
+                            "Phonet",
+                            "Ieee802154",
+                            "SixLoWPAN",
+                            "Ieee80216",
+                            "Ieee1394",
+                            "Unknown"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 72,
+                "qualifiedClassName": "QNetworkInterface"
+            }
+        ],
+        "inputFile": "qnetworkinterface.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkProxyQuery",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "QueryType",
+                        "values": [
+                            "TcpSocket",
+                            "UdpSocket",
+                            "SctpSocket",
+                            "TcpServer",
+                            "UrlRequest",
+                            "SctpServer"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 20,
+                "qualifiedClassName": "QNetworkProxyQuery"
+            },
+            {
+                "className": "QNetworkProxy",
+                "gadget": true,
+                "lineNumber": 78,
+                "qualifiedClassName": "QNetworkProxy"
+            }
+        ],
+        "inputFile": "qnetworkproxy.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkReply",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "NetworkError",
+                        "values": [
+                            "NoError",
+                            "ConnectionRefusedError",
+                            "RemoteHostClosedError",
+                            "HostNotFoundError",
+                            "TimeoutError",
+                            "OperationCanceledError",
+                            "SslHandshakeFailedError",
+                            "TemporaryNetworkFailureError",
+                            "NetworkSessionFailedError",
+                            "BackgroundRequestNotAllowedError",
+                            "TooManyRedirectsError",
+                            "InsecureRedirectError",
+                            "UnknownNetworkError",
+                            "ProxyConnectionRefusedError",
+                            "ProxyConnectionClosedError",
+                            "ProxyNotFoundError",
+                            "ProxyTimeoutError",
+                            "ProxyAuthenticationRequiredError",
+                            "UnknownProxyError",
+                            "ContentAccessDenied",
+                            "ContentOperationNotPermittedError",
+                            "ContentNotFoundError",
+                            "AuthenticationRequiredError",
+                            "ContentReSendError",
+                            "ContentConflictError",
+                            "ContentGoneError",
+                            "UnknownContentError",
+                            "ProtocolUnknownError",
+                            "ProtocolInvalidOperationError",
+                            "ProtocolFailure",
+                            "InternalServerError",
+                            "OperationNotImplementedError",
+                            "ServiceUnavailableError",
+                            "UnknownServerError"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QNetworkReply",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "socketStartedConnecting",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "requestSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "metaDataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkReply::NetworkError"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "redirected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "redirectAllowed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytesSent",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "bytesTotal",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "uploadProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytesReceived",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "bytesTotal",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "downloadProgress",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "abort",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "ignoreSslErrors",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QIODevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkreply.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkReplyDataImpl",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QNetworkReplyDataImpl",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkReply"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkreplydataimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkReplyFileImpl",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QNetworkReplyFileImpl",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "isOpen",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileOpenFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkReply"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkreplyfileimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkReplyHttpImpl",
+                "lineNumber": 51,
+                "object": true,
+                "qualifiedClassName": "QNetworkReplyHttpImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "startHttpRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "abortHttpRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "readBufferSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "readBufferFreed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "startHttpRequestSynchronously",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "dataArray",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "dataAtEnd",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "dataSize",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "haveUploadData",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "_q_startOperation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "_q_cacheLoadReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "_q_bufferOutgoingData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "_q_bufferOutgoingDataFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "_q_transferTimedOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "_q_finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "_q_error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "replyDownloadData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "replyFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "replyDownloadProgressSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QHttpNetworkRequest"
+                            },
+                            {
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "httpAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QNetworkReply::NetworkError"
+                            },
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "httpError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "replyEncrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QList<QSslError>"
+                            },
+                            {
+                                "type": "bool*"
+                            },
+                            {
+                                "type": "QList<QSslError>*"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "replySslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QSslConfiguration"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "replySslConfigurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "replyPreSharedKeyAuthenticationRequiredSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "proxy",
+                                "type": "QNetworkProxy"
+                            },
+                            {
+                                "name": "auth",
+                                "type": "QAuthenticator*"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "proxyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "r",
+                                "type": "bool*"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "resetUploadDataSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "wantUploadDataSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "sentUploadDataSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "uploadByteDeviceReadyReadSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "emitReplyUploadProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "_q_cacheSaveDeviceAboutToClose",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "_q_metaDataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "onRedirected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "followRedirect",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkReply"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkreplyhttpimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkReplyImpl",
+                "lineNumber": 38,
+                "object": true,
+                "qualifiedClassName": "QNetworkReplyImpl",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "_q_startOperation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "_q_copyReadyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "_q_copyReadChannelFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "_q_bufferOutgoingData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "_q_bufferOutgoingDataFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkReply"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkreplyimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkRequest",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "KnownHeaders",
+                        "values": [
+                            "ContentTypeHeader",
+                            "ContentLengthHeader",
+                            "LocationHeader",
+                            "LastModifiedHeader",
+                            "CookieHeader",
+                            "SetCookieHeader",
+                            "ContentDispositionHeader",
+                            "UserAgentHeader",
+                            "ServerHeader",
+                            "IfModifiedSinceHeader",
+                            "ETagHeader",
+                            "IfMatchHeader",
+                            "IfNoneMatchHeader",
+                            "NumKnownHeaders"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 23,
+                "qualifiedClassName": "QNetworkRequest"
+            }
+        ],
+        "inputFile": "qnetworkrequest.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QRestAccessManager",
+                "lineNumber": 77,
+                "object": true,
+                "qualifiedClassName": "QRestAccessManager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qrestaccessmanager.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSocks5SocketEngine",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QSocks5SocketEngine",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_controlSocketConnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "_q_controlSocketReadNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "_q_controlSocketErrorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_udpSocketReadNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "_q_controlSocketBytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_emitPendingReadNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_emitPendingWriteNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_emitPendingConnectionNotification",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_controlSocketDisconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "_q_controlSocketStateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSocketEngine"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsocks5socketengine_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSsl",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "KeyType",
+                        "values": [
+                            "PrivateKey",
+                            "PublicKey"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "EncodingFormat",
+                        "values": [
+                            "Pem",
+                            "Der"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "KeyAlgorithm",
+                        "values": [
+                            "Opaque",
+                            "Rsa",
+                            "Dsa",
+                            "Ec",
+                            "Dh"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "AlternativeNameEntryType",
+                        "values": [
+                            "EmailEntry",
+                            "DnsEntry",
+                            "IpAddressEntry"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SslProtocol",
+                        "values": [
+                            "TlsV1_0",
+                            "TlsV1_1",
+                            "TlsV1_2",
+                            "AnyProtocol",
+                            "SecureProtocols",
+                            "TlsV1_0OrLater",
+                            "TlsV1_1OrLater",
+                            "TlsV1_2OrLater",
+                            "DtlsV1_0",
+                            "DtlsV1_0OrLater",
+                            "DtlsV1_2",
+                            "DtlsV1_2OrLater",
+                            "TlsV1_3",
+                            "TlsV1_3OrLater",
+                            "UnknownProtocol"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SslOption",
+                        "values": [
+                            "SslOptionDisableEmptyFragments",
+                            "SslOptionDisableSessionTickets",
+                            "SslOptionDisableCompression",
+                            "SslOptionDisableServerNameIndication",
+                            "SslOptionDisableLegacyRenegotiation",
+                            "SslOptionDisableSessionSharing",
+                            "SslOptionDisableSessionPersistence",
+                            "SslOptionDisableServerCipherPreference"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AlertLevel",
+                        "values": [
+                            "Warning",
+                            "Fatal",
+                            "Unknown"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AlertType",
+                        "values": [
+                            "CloseNotify",
+                            "UnexpectedMessage",
+                            "BadRecordMac",
+                            "RecordOverflow",
+                            "DecompressionFailure",
+                            "HandshakeFailure",
+                            "NoCertificate",
+                            "BadCertificate",
+                            "UnsupportedCertificate",
+                            "CertificateRevoked",
+                            "CertificateExpired",
+                            "CertificateUnknown",
+                            "IllegalParameter",
+                            "UnknownCa",
+                            "AccessDenied",
+                            "DecodeError",
+                            "DecryptError",
+                            "ExportRestriction",
+                            "ProtocolVersion",
+                            "InsufficientSecurity",
+                            "InternalError",
+                            "InappropriateFallback",
+                            "UserCancelled",
+                            "NoRenegotiation",
+                            "MissingExtension",
+                            "UnsupportedExtension",
+                            "CertificateUnobtainable",
+                            "UnrecognizedName",
+                            "BadCertificateStatusResponse",
+                            "BadCertificateHashValue",
+                            "UnknownPskIdentity",
+                            "CertificateRequired",
+                            "NoApplicationProtocol",
+                            "UnknownAlertMessage"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ImplementedClass",
+                        "values": [
+                            "Key",
+                            "Certificate",
+                            "Socket",
+                            "DiffieHellman",
+                            "EllipticCurve",
+                            "Dtls",
+                            "DtlsCookie"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SupportedFeature",
+                        "values": [
+                            "CertificateVerification",
+                            "ClientSideAlpn",
+                            "ServerSideAlpn",
+                            "Ocsp",
+                            "Psk",
+                            "SessionTicket",
+                            "Alerts"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "namespace": true,
+                "qualifiedClassName": "QSsl"
+            }
+        ],
+        "inputFile": "qssl.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSslError",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SslError",
+                        "values": [
+                            "NoError",
+                            "UnableToGetIssuerCertificate",
+                            "UnableToDecryptCertificateSignature",
+                            "UnableToDecodeIssuerPublicKey",
+                            "CertificateSignatureFailed",
+                            "CertificateNotYetValid",
+                            "CertificateExpired",
+                            "InvalidNotBeforeField",
+                            "InvalidNotAfterField",
+                            "SelfSignedCertificate",
+                            "SelfSignedCertificateInChain",
+                            "UnableToGetLocalIssuerCertificate",
+                            "UnableToVerifyFirstCertificate",
+                            "CertificateRevoked",
+                            "InvalidCaCertificate",
+                            "PathLengthExceeded",
+                            "InvalidPurpose",
+                            "CertificateUntrusted",
+                            "CertificateRejected",
+                            "SubjectIssuerMismatch",
+                            "AuthorityIssuerSerialNumberMismatch",
+                            "NoPeerCertificate",
+                            "HostNameMismatch",
+                            "NoSslSupport",
+                            "CertificateBlacklisted",
+                            "CertificateStatusUnknown",
+                            "OcspNoResponseFound",
+                            "OcspMalformedRequest",
+                            "OcspMalformedResponse",
+                            "OcspInternalError",
+                            "OcspTryLater",
+                            "OcspSigRequred",
+                            "OcspUnauthorized",
+                            "OcspResponseCannotBeTrusted",
+                            "OcspResponseCertIdUnknown",
+                            "OcspResponseExpired",
+                            "OcspStatusUnknown",
+                            "UnspecifiedError"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 24,
+                "qualifiedClassName": "QSslError"
+            }
+        ],
+        "inputFile": "qsslerror.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSslServer",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QSslServer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "error",
+                                "type": "QSslError"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "peerVerifyError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "error",
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "errorOccurred",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "level",
+                                "type": "QSsl::AlertLevel"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QSsl::AlertType"
+                            },
+                            {
+                                "name": "description",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "alertSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "level",
+                                "type": "QSsl::AlertLevel"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QSsl::AlertType"
+                            },
+                            {
+                                "name": "description",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "alertReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            },
+                            {
+                                "name": "error",
+                                "type": "QSslError"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "handshakeInterruptedOnError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socket",
+                                "type": "QSslSocket*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "startedEncryptionHandshake",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTcpServer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsslserver.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSslSocket",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SslMode",
+                        "values": [
+                            "UnencryptedMode",
+                            "SslClientMode",
+                            "SslServerMode"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PeerVerifyMode",
+                        "values": [
+                            "VerifyNone",
+                            "QueryPeer",
+                            "VerifyPeer",
+                            "AutoVerifyPeer"
+                        ]
+                    }
+                ],
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QSslSocket",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "encrypted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QSslError"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "peerVerifyError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "errors",
+                                "type": "QList<QSslError>"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newMode",
+                                "type": "QSslSocket::SslMode"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "modeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "totalBytes",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "encryptedBytesWritten",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "authenticator",
+                                "type": "QSslPreSharedKeyAuthenticator*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "preSharedKeyAuthenticationRequired",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "newSessionTicketReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "level",
+                                "type": "QSsl::AlertLevel"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QSsl::AlertType"
+                            },
+                            {
+                                "name": "description",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "alertSent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "level",
+                                "type": "QSsl::AlertLevel"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QSsl::AlertType"
+                            },
+                            {
+                                "name": "description",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "alertReceived",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QSslError"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "handshakeInterruptedOnError",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "startClientEncryption",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "startServerEncryption",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "ignoreSslErrors",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 13,
+                        "name": "_q_connectedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 14,
+                        "name": "_q_hostFoundSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "_q_disconnectedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "_q_stateChangedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "_q_errorSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 18,
+                        "name": "_q_readyReadSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "_q_channelReadyReadSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "_q_bytesWrittenSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "_q_channelBytesWrittenSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 22,
+                        "name": "_q_readChannelFinishedSlot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 23,
+                        "name": "_q_flushWriteBuffer",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 24,
+                        "name": "_q_flushReadBuffer",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 25,
+                        "name": "_q_resumeImplementation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTcpSocket"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsslsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTcpServer",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QTcpServer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "newConnection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "pendingConnectionAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socketError",
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "acceptError",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcpserver.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTcpSocket",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QTcpSocket",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSocket"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtcpsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTlsBackend",
+                "lineNumber": 268,
+                "object": true,
+                "qualifiedClassName": "QTlsBackend",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtlsbackend_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUdpSocket",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QUdpSocket",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSocket"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qudpsocket.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QNetworkInformationDummyBackend",
+                "lineNumber": 55,
+                "object": true,
+                "qualifiedClassName": "QNetworkInformationDummyBackend",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNetworkInformationBackend"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qnetworkinformation.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6opengl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6opengl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..d5269c26d875d85a700328461aadf34ecaeb83fc
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6opengl_metatypes.json
@@ -0,0 +1,629 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QOpenGLDebugLogger",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LoggingMode",
+                        "values": [
+                            "AsynchronousLogging",
+                            "SynchronousLogging"
+                        ]
+                    }
+                ],
+                "lineNumber": 119,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "loggingMode",
+                        "read": "loggingMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LoggingMode",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QOpenGLDebugLogger",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "debugMessage",
+                                "type": "QOpenGLDebugMessage"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "messageLogged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "debugMessage",
+                                "type": "QOpenGLDebugMessage"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "logMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "loggingMode",
+                                "type": "LoggingMode"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "startLogging",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "isCloned": true,
+                        "name": "startLogging",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "stopLogging",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_contextAboutToBeDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopengldebug.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLEngineSharedShaders",
+                "gadget": true,
+                "lineNumber": 221,
+                "qualifiedClassName": "QOpenGLEngineSharedShaders"
+            },
+            {
+                "className": "QOpenGLEngineShaderManager",
+                "lineNumber": 372,
+                "object": true,
+                "qualifiedClassName": "QOpenGLEngineShaderManager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopenglengineshadermanager_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLShader",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QOpenGLShader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QOpenGLShaderProgram",
+                "lineNumber": 69,
+                "object": true,
+                "qualifiedClassName": "QOpenGLShaderProgram",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "shaderDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopenglshaderprogram.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLTexture",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Target",
+                        "values": [
+                            "Target1D",
+                            "Target1DArray",
+                            "Target2D",
+                            "Target2DArray",
+                            "Target3D",
+                            "TargetCubeMap",
+                            "TargetCubeMapArray",
+                            "Target2DMultisample",
+                            "Target2DMultisampleArray",
+                            "TargetRectangle",
+                            "TargetBuffer"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BindingTarget",
+                        "values": [
+                            "BindingTarget1D",
+                            "BindingTarget1DArray",
+                            "BindingTarget2D",
+                            "BindingTarget2DArray",
+                            "BindingTarget3D",
+                            "BindingTargetCubeMap",
+                            "BindingTargetCubeMapArray",
+                            "BindingTarget2DMultisample",
+                            "BindingTarget2DMultisampleArray",
+                            "BindingTargetRectangle",
+                            "BindingTargetBuffer"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MipMapGeneration",
+                        "values": [
+                            "GenerateMipMaps",
+                            "DontGenerateMipMaps"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextureUnitReset",
+                        "values": [
+                            "ResetTextureUnit",
+                            "DontResetTextureUnit"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextureFormat",
+                        "values": [
+                            "NoFormat",
+                            "R8_UNorm",
+                            "RG8_UNorm",
+                            "RGB8_UNorm",
+                            "RGBA8_UNorm",
+                            "R16_UNorm",
+                            "RG16_UNorm",
+                            "RGB16_UNorm",
+                            "RGBA16_UNorm",
+                            "R8_SNorm",
+                            "RG8_SNorm",
+                            "RGB8_SNorm",
+                            "RGBA8_SNorm",
+                            "R16_SNorm",
+                            "RG16_SNorm",
+                            "RGB16_SNorm",
+                            "RGBA16_SNorm",
+                            "R8U",
+                            "RG8U",
+                            "RGB8U",
+                            "RGBA8U",
+                            "R16U",
+                            "RG16U",
+                            "RGB16U",
+                            "RGBA16U",
+                            "R32U",
+                            "RG32U",
+                            "RGB32U",
+                            "RGBA32U",
+                            "R8I",
+                            "RG8I",
+                            "RGB8I",
+                            "RGBA8I",
+                            "R16I",
+                            "RG16I",
+                            "RGB16I",
+                            "RGBA16I",
+                            "R32I",
+                            "RG32I",
+                            "RGB32I",
+                            "RGBA32I",
+                            "R16F",
+                            "RG16F",
+                            "RGB16F",
+                            "RGBA16F",
+                            "R32F",
+                            "RG32F",
+                            "RGB32F",
+                            "RGBA32F",
+                            "RGB9E5",
+                            "RG11B10F",
+                            "RG3B2",
+                            "R5G6B5",
+                            "RGB5A1",
+                            "RGBA4",
+                            "RGB10A2",
+                            "D16",
+                            "D24",
+                            "D24S8",
+                            "D32",
+                            "D32F",
+                            "D32FS8X24",
+                            "S8",
+                            "RGB_DXT1",
+                            "RGBA_DXT1",
+                            "RGBA_DXT3",
+                            "RGBA_DXT5",
+                            "R_ATI1N_UNorm",
+                            "R_ATI1N_SNorm",
+                            "RG_ATI2N_UNorm",
+                            "RG_ATI2N_SNorm",
+                            "RGB_BP_UNSIGNED_FLOAT",
+                            "RGB_BP_SIGNED_FLOAT",
+                            "RGB_BP_UNorm",
+                            "R11_EAC_UNorm",
+                            "R11_EAC_SNorm",
+                            "RG11_EAC_UNorm",
+                            "RG11_EAC_SNorm",
+                            "RGB8_ETC2",
+                            "SRGB8_ETC2",
+                            "RGB8_PunchThrough_Alpha1_ETC2",
+                            "SRGB8_PunchThrough_Alpha1_ETC2",
+                            "RGBA8_ETC2_EAC",
+                            "SRGB8_Alpha8_ETC2_EAC",
+                            "RGB8_ETC1",
+                            "RGBA_ASTC_4x4",
+                            "RGBA_ASTC_5x4",
+                            "RGBA_ASTC_5x5",
+                            "RGBA_ASTC_6x5",
+                            "RGBA_ASTC_6x6",
+                            "RGBA_ASTC_8x5",
+                            "RGBA_ASTC_8x6",
+                            "RGBA_ASTC_8x8",
+                            "RGBA_ASTC_10x5",
+                            "RGBA_ASTC_10x6",
+                            "RGBA_ASTC_10x8",
+                            "RGBA_ASTC_10x10",
+                            "RGBA_ASTC_12x10",
+                            "RGBA_ASTC_12x12",
+                            "SRGB8_Alpha8_ASTC_4x4",
+                            "SRGB8_Alpha8_ASTC_5x4",
+                            "SRGB8_Alpha8_ASTC_5x5",
+                            "SRGB8_Alpha8_ASTC_6x5",
+                            "SRGB8_Alpha8_ASTC_6x6",
+                            "SRGB8_Alpha8_ASTC_8x5",
+                            "SRGB8_Alpha8_ASTC_8x6",
+                            "SRGB8_Alpha8_ASTC_8x8",
+                            "SRGB8_Alpha8_ASTC_10x5",
+                            "SRGB8_Alpha8_ASTC_10x6",
+                            "SRGB8_Alpha8_ASTC_10x8",
+                            "SRGB8_Alpha8_ASTC_10x10",
+                            "SRGB8_Alpha8_ASTC_12x10",
+                            "SRGB8_Alpha8_ASTC_12x12",
+                            "SRGB8",
+                            "SRGB8_Alpha8",
+                            "SRGB_DXT1",
+                            "SRGB_Alpha_DXT1",
+                            "SRGB_Alpha_DXT3",
+                            "SRGB_Alpha_DXT5",
+                            "SRGB_BP_UNorm",
+                            "DepthFormat",
+                            "AlphaFormat",
+                            "RGBFormat",
+                            "RGBAFormat",
+                            "LuminanceFormat",
+                            "LuminanceAlphaFormat"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CubeMapFace",
+                        "values": [
+                            "CubeMapPositiveX",
+                            "CubeMapNegativeX",
+                            "CubeMapPositiveY",
+                            "CubeMapNegativeY",
+                            "CubeMapPositiveZ",
+                            "CubeMapNegativeZ"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PixelFormat",
+                        "values": [
+                            "NoSourceFormat",
+                            "Red",
+                            "RG",
+                            "RGB",
+                            "BGR",
+                            "RGBA",
+                            "BGRA",
+                            "Red_Integer",
+                            "RG_Integer",
+                            "RGB_Integer",
+                            "BGR_Integer",
+                            "RGBA_Integer",
+                            "BGRA_Integer",
+                            "Stencil",
+                            "Depth",
+                            "DepthStencil",
+                            "Alpha",
+                            "Luminance",
+                            "LuminanceAlpha"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PixelType",
+                        "values": [
+                            "NoPixelType",
+                            "Int8",
+                            "UInt8",
+                            "Int16",
+                            "UInt16",
+                            "Int32",
+                            "UInt32",
+                            "Float16",
+                            "Float16OES",
+                            "Float32",
+                            "UInt32_RGB9_E5",
+                            "UInt32_RG11B10F",
+                            "UInt8_RG3B2",
+                            "UInt8_RG3B2_Rev",
+                            "UInt16_RGB5A1",
+                            "UInt16_RGB5A1_Rev",
+                            "UInt16_R5G6B5",
+                            "UInt16_R5G6B5_Rev",
+                            "UInt16_RGBA4",
+                            "UInt16_RGBA4_Rev",
+                            "UInt32_RGBA8",
+                            "UInt32_RGBA8_Rev",
+                            "UInt32_RGB10A2",
+                            "UInt32_RGB10A2_Rev",
+                            "UInt32_D24S8",
+                            "Float32_D32_UInt32_S8_X24"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SwizzleComponent",
+                        "values": [
+                            "SwizzleRed",
+                            "SwizzleGreen",
+                            "SwizzleBlue",
+                            "SwizzleAlpha"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SwizzleValue",
+                        "values": [
+                            "RedValue",
+                            "GreenValue",
+                            "BlueValue",
+                            "AlphaValue",
+                            "ZeroValue",
+                            "OneValue"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WrapMode",
+                        "values": [
+                            "Repeat",
+                            "MirroredRepeat",
+                            "ClampToEdge",
+                            "ClampToBorder"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CoordinateDirection",
+                        "values": [
+                            "DirectionS",
+                            "DirectionT",
+                            "DirectionR"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Feature",
+                        "values": [
+                            "ImmutableStorage",
+                            "ImmutableMultisampleStorage",
+                            "TextureRectangle",
+                            "TextureArrays",
+                            "Texture3D",
+                            "TextureMultisample",
+                            "TextureBuffer",
+                            "TextureCubeMapArrays",
+                            "Swizzle",
+                            "StencilTexturing",
+                            "AnisotropicFiltering",
+                            "NPOTTextures",
+                            "NPOTTextureRepeat",
+                            "Texture1D",
+                            "TextureComparisonOperators",
+                            "TextureMipMapLevel",
+                            "MaxFeatureFlag"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DepthStencilMode",
+                        "values": [
+                            "DepthMode",
+                            "StencilMode"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ComparisonFunction",
+                        "values": [
+                            "CompareLessEqual",
+                            "CompareGreaterEqual",
+                            "CompareLess",
+                            "CompareGreater",
+                            "CompareEqual",
+                            "CompareNotEqual",
+                            "CompareAlways",
+                            "CompareNever",
+                            "CommpareNotEqual"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Filter",
+                        "values": [
+                            "Nearest",
+                            "Linear",
+                            "NearestMipMapNearest",
+                            "NearestMipMapLinear",
+                            "LinearMipMapNearest",
+                            "LinearMipMapLinear"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 21,
+                "qualifiedClassName": "QOpenGLTexture"
+            }
+        ],
+        "inputFile": "qopengltexture.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLTimerQuery",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QOpenGLTimerQuery",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QOpenGLTimeMonitor",
+                "lineNumber": 46,
+                "object": true,
+                "qualifiedClassName": "QOpenGLTimeMonitor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopengltimerquery.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLVertexArrayObject",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QOpenGLVertexArrayObject",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_contextAboutToBeDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopenglvertexarrayobject.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QOpenGLWindow",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QOpenGLWindow",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "frameSwapped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPaintDeviceWindow"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopenglwindow.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6openglwidgets_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6openglwidgets_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..bce283cb8908f3c94d049b4e56505f26125f6750
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6openglwidgets_metatypes.json
@@ -0,0 +1,67 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QOpenGLWidget",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "UpdateBehavior",
+                        "values": [
+                            "NoPartialUpdate",
+                            "PartialUpdate"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TargetBuffer",
+                        "type": "uint8_t",
+                        "values": [
+                            "LeftBuffer",
+                            "RightBuffer"
+                        ]
+                    }
+                ],
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QOpenGLWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToCompose",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "frameSwapped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "aboutToResize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "resized",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qopenglwidget.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6packetprotocolprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6packetprotocolprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c944343188a5d5104e4bad4c72ba5da7c2f2e0e1
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6packetprotocolprivate_metatypes.json
@@ -0,0 +1,34 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QPacketProtocol",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QPacketProtocol",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "error",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpacketprotocol_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6printsupport_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6printsupport_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e267296065540b481583aeba5095767943bc67e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6printsupport_metatypes.json
@@ -0,0 +1,519 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QPageSetupDialog",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QPageSetupDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpagesetupdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractPrintDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PrintDialogOption",
+                        "values": [
+                            "PrintToFile",
+                            "PrintSelection",
+                            "PrintPageRange",
+                            "PrintShowPageSize",
+                            "PrintCollateCopies",
+                            "PrintCurrentPage"
+                        ]
+                    },
+                    {
+                        "alias": "PrintDialogOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "PrintDialogOptions",
+                        "values": [
+                            "PrintToFile",
+                            "PrintSelection",
+                            "PrintPageRange",
+                            "PrintShowPageSize",
+                            "PrintCollateCopies",
+                            "PrintCurrentPage"
+                        ]
+                    }
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QAbstractPrintDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractprintdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformPrinterSupportPlugin",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QPlatformPrinterSupportPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplatformprintplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPrintDialog",
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "PrintDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QPrintDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "printer",
+                                "type": "QPrinter*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "accepted",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractPrintDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprintdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPrintPreviewDialog",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QPrintPreviewDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "printer",
+                                "type": "QPrinter*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "paintRequested",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "_q_fit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "_q_zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_zoomOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_navigate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "_q_setMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_pageNumEdited",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_print",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_pageSetup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_previewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "_q_zoomFactorChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprintpreviewdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPrintPreviewWidget",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QPrintPreviewWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "printer",
+                                "type": "QPrinter*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "paintRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "previewChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "print",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "zoom",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "isCloned": true,
+                        "name": "zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "zoom",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "zoomOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "zoomOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "zoomFactor",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setZoomFactor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "QPageLayout::Orientation"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setOrientation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "viewMode",
+                                "type": "ViewMode"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setViewMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "zoomMode",
+                                "type": "ZoomMode"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setZoomMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pageNumber",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setCurrentPage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "fitToWidth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "fitInView",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "setLandscapeOrientation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "setPortraitOrientation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "setSinglePageViewMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "setFacingPagesViewMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "setAllPagesViewMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "updatePreview",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 20,
+                        "name": "_q_fit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 21,
+                        "name": "_q_updateCurrentPage",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprintpreviewwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LineEdit",
+                "lineNumber": 83,
+                "object": true,
+                "qualifiedClassName": "LineEdit",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "handleReturnPressed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLineEdit"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprintpreviewdialog.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "GraphicsView",
+                "lineNumber": 107,
+                "object": true,
+                "qualifiedClassName": "QtPrivate::GraphicsView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "resized",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QGraphicsView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qprintpreviewwidget.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsPrinterSupportPlugin",
+                "lineNumber": 56,
+                "object": true,
+                "qualifiedClassName": "QWindowsPrinterSupportPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformPrinterSupportPlugin"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowsprintersupport.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qml_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qml_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..204b8d985b24daab5d6a63a50cefa3d4f998ee28
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qml_metatypes.json
@@ -0,0 +1,6712 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TypeNotAvailable"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "527"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Type not available."
+                    }
+                ],
+                "className": "QQmlTypeNotAvailable",
+                "lineNumber": 136,
+                "object": true,
+                "qualifiedClassName": "QQmlTypeNotAvailable",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqml.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQmlLoggingCategoryBase",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QQmlLoggingCategoryBase",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlloggingcategorybase_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "void"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "undefined"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "void"
+                    }
+                ],
+                "className": "QQmlVoidForeign",
+                "gadget": true,
+                "lineNumber": 88,
+                "qualifiedClassName": "QQmlVoidForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "var"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "variant"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QVariant"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QQmlVarForeign"
+                    }
+                ],
+                "className": "QQmlVarForeign",
+                "gadget": true,
+                "lineNumber": 99,
+                "qualifiedClassName": "QQmlVarForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "QtObject"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Object"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QObject"
+                    },
+                    {
+                        "name": "QML.Root",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlQtObjectForeign",
+                "gadget": true,
+                "lineNumber": 108,
+                "qualifiedClassName": "QQmlQtObjectForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "int"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "int"
+                    }
+                ],
+                "className": "QQmlIntForeign",
+                "gadget": true,
+                "lineNumber": 117,
+                "qualifiedClassName": "QQmlIntForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "qint32"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "int"
+                    }
+                ],
+                "className": "QQmlQint32Foreign",
+                "gadget": true,
+                "lineNumber": 129,
+                "qualifiedClassName": "QQmlQint32Foreign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "int32_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "int"
+                    }
+                ],
+                "className": "QQmlInt32TForeign",
+                "gadget": true,
+                "lineNumber": 136,
+                "qualifiedClassName": "QQmlInt32TForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "real"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "double"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "double"
+                    }
+                ],
+                "className": "QQmlDoubleForeign",
+                "gadget": true,
+                "lineNumber": 143,
+                "qualifiedClassName": "QQmlDoubleForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "string"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "String"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QString"
+                    }
+                ],
+                "className": "QQmlStringForeign",
+                "gadget": true,
+                "lineNumber": 152,
+                "qualifiedClassName": "QQmlStringForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "String"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QAnyStringView"
+                    }
+                ],
+                "className": "QQmlAnyStringViewForeign",
+                "gadget": true,
+                "lineNumber": 160,
+                "qualifiedClassName": "QQmlAnyStringViewForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "bool"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Boolean"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "bool"
+                    }
+                ],
+                "className": "QQmlBoolForeign",
+                "gadget": true,
+                "lineNumber": 168,
+                "qualifiedClassName": "QQmlBoolForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "date"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Date"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QDateTime"
+                    }
+                ],
+                "className": "QQmlDateForeign",
+                "gadget": true,
+                "lineNumber": 176,
+                "qualifiedClassName": "QQmlDateForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "url"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "URL"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QUrl"
+                    }
+                ],
+                "className": "QQmlUrlForeign",
+                "gadget": true,
+                "lineNumber": 184,
+                "qualifiedClassName": "QQmlUrlForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "regexp"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "RegExp"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QRegularExpression"
+                    }
+                ],
+                "className": "QQmlRegexpForeign",
+                "gadget": true,
+                "lineNumber": 193,
+                "qualifiedClassName": "QQmlRegexpForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::nullptr_t"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QQmlNullForeign"
+                    }
+                ],
+                "className": "QQmlNullForeign",
+                "gadget": true,
+                "lineNumber": 202,
+                "qualifiedClassName": "QQmlNullForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QVariantMap"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Object"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlQVariantMapForeign",
+                "gadget": true,
+                "lineNumber": 210,
+                "qualifiedClassName": "QQmlQVariantMapForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "qint8"
+                    }
+                ],
+                "className": "QQmlQint8Foreign",
+                "gadget": true,
+                "lineNumber": 218,
+                "qualifiedClassName": "QQmlQint8Foreign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "int8_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "qint8"
+                    }
+                ],
+                "className": "QQmlInt8TForeign",
+                "gadget": true,
+                "lineNumber": 226,
+                "qualifiedClassName": "QQmlInt8TForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "quint8"
+                    }
+                ],
+                "className": "QQmlQuint8Foreign",
+                "gadget": true,
+                "lineNumber": 233,
+                "qualifiedClassName": "QQmlQuint8Foreign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "uint8_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "quint8"
+                    }
+                ],
+                "className": "QQmlUint8TForeign",
+                "gadget": true,
+                "lineNumber": 241,
+                "qualifiedClassName": "QQmlUint8TForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "uchar"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "quint8"
+                    }
+                ],
+                "className": "QQmlUcharForeign",
+                "gadget": true,
+                "lineNumber": 248,
+                "qualifiedClassName": "QQmlUcharForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "char"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "quint8"
+                    }
+                ],
+                "className": "QQmlCharForeign",
+                "gadget": true,
+                "lineNumber": 255,
+                "qualifiedClassName": "QQmlCharForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "short"
+                    }
+                ],
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+                "gadget": true,
+                "lineNumber": 268,
+                "qualifiedClassName": "QQmlShortForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "qint16"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "short"
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+                "qualifiedClassName": "QQmlQint16Foreign"
+            },
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+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "int16_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "short"
+                    }
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+                "gadget": true,
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+                "qualifiedClassName": "QQmlInt16TForeign"
+            },
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+                    {
+                        "name": "QML.Element",
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+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "ushort"
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+                "gadget": true,
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+                "qualifiedClassName": "QQmlUshortForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "quint16"
+                    },
+                    {
+                        "name": "QML.Using",
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+                "qualifiedClassName": "QQmlQuint16Foreign"
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+                    {
+                        "name": "QML.Foreign",
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+                    },
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+                        "name": "QML.Using",
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+                ],
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+                "qualifiedClassName": "QQmlUint16TForeign"
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+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
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+                        "value": "uint"
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+                "qualifiedClassName": "QQmlUintForeign"
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+                "classInfos": [
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+                        "name": "QML.Foreign",
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+                    },
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+                        "name": "QML.Using",
+                        "value": "uint"
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+                "qualifiedClassName": "QQmlQuint32Foreign"
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+                        "name": "QML.Foreign",
+                        "value": "uint32_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "uint"
+                    }
+                ],
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+                "gadget": true,
+                "lineNumber": 327,
+                "qualifiedClassName": "QQmlUint32TForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "Number"
+                    },
+                    {
+                        "name": "QML.ExtensionIsJavaScript",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "qlonglong"
+                    },
+                    {
+                        "name": "QML.PrimitiveAlias",
+                        "value": "qsizetype"
+                    }
+                ],
+                "className": "QQmlQlonglongForeign",
+                "gadget": true,
+                "lineNumber": 334,
+                "qualifiedClassName": "QQmlQlonglongForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "qint64"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "qlonglong"
+                    }
+                ],
+                "className": "QQmlQint64Foreign",
+                "gadget": true,
+                "lineNumber": 346,
+                "qualifiedClassName": "QQmlQint64Foreign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "int64_t"
+                    },
+                    {
+                        "name": "QML.Using",
+                        "value": "qlonglong"
+                    }
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+                        "name": "formatTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "time",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 60,
+                        "isCloned": true,
+                        "name": "formatTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDateTime"
+                            },
+                            {
+                                "name": "locale",
+                                "type": "QLocale"
+                            },
+                            {
+                                "name": "formatType",
+                                "type": "QLocale::FormatType"
+                            }
+                        ],
+                        "index": 61,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDateTime"
+                            },
+                            {
+                                "name": "locale",
+                                "type": "QLocale"
+                            }
+                        ],
+                        "index": 62,
+                        "isCloned": true,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDateTime"
+                            }
+                        ],
+                        "index": 63,
+                        "isCloned": true,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "string",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "locale",
+                                "type": "QLocale"
+                            },
+                            {
+                                "name": "formatType",
+                                "type": "QLocale::FormatType"
+                            }
+                        ],
+                        "index": 64,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "string",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "locale",
+                                "type": "QLocale"
+                            }
+                        ],
+                        "index": 65,
+                        "isCloned": true,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "string",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 66,
+                        "isCloned": true,
+                        "name": "formatDateTime",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "index": 67,
+                        "name": "locale",
+                        "returnType": "QLocale"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 68,
+                        "name": "locale",
+                        "returnType": "QLocale"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 69,
+                        "name": "url",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 70,
+                        "name": "resolvedUrl",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "context",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 71,
+                        "name": "resolvedUrl",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 72,
+                        "name": "openUrlExternally",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fontSpecifier",
+                                "type": "QJSValue"
+                            }
+                        ],
+                        "index": 73,
+                        "name": "font",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "index": 74,
+                        "name": "fontFamilies",
+                        "returnType": "QStringList"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 75,
+                        "name": "md5",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 76,
+                        "name": "btoa",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 77,
+                        "name": "atob",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "index": 78,
+                        "name": "quit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "retCode",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 79,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "qml",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 80,
+                        "name": "createQmlObject",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "qml",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 81,
+                        "isCloned": true,
+                        "name": "createQmlObject",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 82,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "QQmlComponent::CompilationMode"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 83,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "QQmlComponent::CompilationMode"
+                            }
+                        ],
+                        "index": 84,
+                        "isCloned": true,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 85,
+                        "isCloned": true,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "moduleUri",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 86,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "moduleUri",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "QQmlComponent::CompilationMode"
+                            },
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 87,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "moduleUri",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "QQmlComponent::CompilationMode"
+                            }
+                        ],
+                        "index": 88,
+                        "isCloned": true,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "moduleUri",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 89,
+                        "isCloned": true,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "function",
+                                "type": "QJSValue"
+                            }
+                        ],
+                        "index": 90,
+                        "name": "binding",
+                        "returnType": "QJSValue"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 91,
+                        "name": "callLater",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "application",
+                        "read": "application",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlApplication*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "platform",
+                        "read": "platform",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlPlatform*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "inputMethod",
+                        "read": "inputMethod",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "styleHints",
+                        "read": "styleHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    },
+                    {
+                        "bindable": "uiLanguageBindable",
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "uiLanguage",
+                        "read": "uiLanguage",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setUiLanguage"
+                    }
+                ],
+                "qualifiedClassName": "QtObject",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlbuiltinfunctions_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlComponent",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CompilationMode",
+                        "values": [
+                            "PreferSynchronous",
+                            "Asynchronous"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading",
+                            "Error"
+                        ]
+                    }
+                ],
+                "lineNumber": 31,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "errorString",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "createObject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "createObject",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 10,
+                        "isCloned": true,
+                        "name": "createObject",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "createObject",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "incubateObject",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "progress",
+                        "notify": "progressChanged",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Status",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "url",
+                        "read": "url",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlComponent",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQmlComponent::Status"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "progressChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "loadUrl",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "CompilationMode"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "loadUrl",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "uri",
+                                "type": "QAnyStringView"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QAnyStringView"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "QQmlComponent::CompilationMode"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "loadFromModule",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "uri",
+                                "type": "QAnyStringView"
+                            },
+                            {
+                                "name": "typeName",
+                                "type": "QAnyStringView"
+                            }
+                        ],
+                        "index": 5,
+                        "isCloned": true,
+                        "name": "loadFromModule",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "baseUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setData",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlcomponent.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlComponentAttached",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QQmlComponentAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "completed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "destruction",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlcomponentattached_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlContext",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QQmlContext",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlcontext.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugConnector",
+                "lineNumber": 53,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugConnector",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QQmlDebugConnectorFactory",
+                "lineNumber": 90,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugConnectorFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugconnector_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugServer",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugServer",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugConnector"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugserver_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugServerConnection",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugServerConnection",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QQmlDebugServerConnectionFactory",
+                "lineNumber": 40,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugServerConnectionFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugserverconnection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugService",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugService",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QJSEngine*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "attachedToEngine",
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QJSEngine*"
+                            }
+                        ],
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "name",
+                                "type": "QString"
+                            },
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+                                "name": "message",
+                                "type": "QByteArray"
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+                        "name": "messageToClient",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
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+                                "name": "messages",
+                                "type": "QList<QByteArray>"
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+                        "name": "ticked",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setOfflineStoragePath"
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+                        "index": 0,
+                        "name": "offlineStoragePathChanged",
+                        "returnType": "void"
+                    },
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+                        "access": "public",
+                        "index": 1,
+                        "name": "quit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "retCode",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "warnings",
+                                "type": "QList<QQmlError>"
+                            }
+                        ],
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+                        "name": "warnings",
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+                        "name": "retranslate",
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+                        "isFlag": false,
+                        "name": "DayOfWeek",
+                        "values": [
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+                            "Monday",
+                            "Tuesday",
+                            "Wednesday",
+                            "Thursday",
+                            "Friday",
+                            "Saturday"
+                        ]
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+                    },
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+                        "name": "QML.Sequence",
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+                ],
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+                        "arguments": [
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+                                "name": "name",
+                                "type": "QString"
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+                        "arguments": [
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+                                "name": "format",
+                                "type": "QLocale::CurrencySymbolFormat"
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+                        "name": "currencySymbol",
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+                                "name": "format",
+                                "type": "QLocale::FormatType"
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+                        "name": "dateTimeFormat",
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+                                "name": "format",
+                                "type": "QLocale::FormatType"
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+                                "type": "QLocale::FormatType"
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+                                "type": "int"
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+                                "type": "QLocale::FormatType"
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+                        "name": "monthName",
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+                    {
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+                                "type": "int"
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+                        "name": "monthName",
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+                    {
+                        "access": "public",
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+                                "name": "index",
+                                "type": "int"
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+                            {
+                                "name": "format",
+                                "type": "QLocale::FormatType"
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+                        ],
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+                        "name": "standaloneMonthName",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
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+                                "name": "index",
+                                "type": "int"
+                            }
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+                        "isCloned": true,
+                        "name": "standaloneMonthName",
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "index",
+                                "type": "int"
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+                            {
+                                "name": "format",
+                                "type": "QLocale::FormatType"
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+                        "name": "dayName",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "index",
+                                "type": "int"
+                            }
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+                        "isCloned": true,
+                        "name": "dayName",
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+                                "name": "index",
+                                "type": "int"
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+                            {
+                                "name": "format",
+                                "type": "QLocale::FormatType"
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+                        "name": "standaloneDayName",
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+                    {
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+                                "name": "index",
+                                "type": "int"
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+                        "name": "standaloneDayName",
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+                                "type": "QQmlV4FunctionPtr"
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+                        "name": "formattedDataSize",
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+                    {
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+                                "name": "bytes",
+                                "type": "double"
+                            },
+                            {
+                                "name": "precision",
+                                "type": "int"
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+                            {
+                                "name": "format",
+                                "type": "QLocale::DataSizeFormats"
+                            }
+                        ],
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+                        "name": "formattedDataSize",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "bytes",
+                                "type": "double"
+                            },
+                            {
+                                "name": "precision",
+                                "type": "int"
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+                        ],
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+                        "isCloned": true,
+                        "name": "formattedDataSize",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
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+                            {
+                                "name": "bytes",
+                                "type": "double"
+                            }
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+                        "isCloned": true,
+                        "name": "formattedDataSize",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
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+                        "name": "toString",
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+                    },
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+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "private",
+                        "name": "QHash<QObjectBiPointer,QV4::WeakValue>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qv4qobjectwrapper_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "double"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<qreal>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QRealStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 140,
+                "qualifiedClassName": "QRealStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "double"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QList<qreal>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QRealListForeign",
+                "gadget": true,
+                "lineNumber": 141,
+                "qualifiedClassName": "QRealListForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "double"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<double>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QDoubleStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 144,
+                "qualifiedClassName": "QDoubleStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "float"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<float>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QFloatStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 145,
+                "qualifiedClassName": "QFloatStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "int"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<int>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QIntStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 146,
+                "qualifiedClassName": "QIntStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "bool"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<bool>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QBoolStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 147,
+                "qualifiedClassName": "QBoolStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "QString"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<QString>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QStringStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 148,
+                "qualifiedClassName": "QStringStdVectorForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Sequence",
+                        "value": "QUrl"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "std::vector<QUrl>"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QUrlStdVectorForeign",
+                "gadget": true,
+                "lineNumber": 149,
+                "qualifiedClassName": "QUrlStdVectorForeign"
+            }
+        ],
+        "inputFile": "qv4sequenceobject_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ObjectReferenceHash",
+                "lineNumber": 88,
+                "object": true,
+                "qualifiedClassName": "ObjectReferenceHash",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugservice.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlFileNetworkReply",
+                "lineNumber": 49,
+                "object": true,
+                "qualifiedClassName": "QQmlFileNetworkReply",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "downloadProgress",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "networkFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "networkDownloadProgress",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlfile.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlXMLHttpRequest",
+                "lineNumber": 967,
+                "object": true,
+                "qualifiedClassName": "QQmlXMLHttpRequest",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QNetworkReply::NetworkError"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "finished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlxmlhttprequest.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlassetdownloader_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlassetdownloader_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..2d9dca392bcf83a5844dd51198f8c59ff9da0802
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlassetdownloader_metatypes.json
@@ -0,0 +1,41 @@
+[
+    {
+        "classes": [
+            {
+                "className": "AssetDownloaderHelper",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "Assets::Downloader::AssetDownloaderHelper",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "Assets::Downloader::AssetDownloader",
+                        "name": "AssetDownloader"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "AssetDownloaderHelper"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "AssetDownloader"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1544"
+                    }
+                ],
+                "className": "QQmlAssetDownloader",
+                "gadget": true,
+                "lineNumber": 36,
+                "qualifiedClassName": "Assets::Downloader::QQmlAssetDownloader"
+            }
+        ],
+        "inputFile": "qqmlassetdownloader_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcompiler_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcompiler_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcompiler_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcore_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcore_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..b01b4e53d65d128fd3c193c37ba9024ffc6c3f2d
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlcore_metatypes.json
@@ -0,0 +1,1023 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LocationPermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QLocationPermission"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlQLocationPermission",
+                "lineNumber": 68,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "availability",
+                        "notify": "availabilityChanged",
+                        "read": "availability",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocationPermission::Availability",
+                        "user": false,
+                        "write": "setAvailability"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "accuracy",
+                        "notify": "accuracyChanged",
+                        "read": "accuracy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocationPermission::Accuracy",
+                        "user": false,
+                        "write": "setAccuracy"
+                    }
+                ],
+                "qualifiedClassName": "QQmlQLocationPermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "availabilityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "accuracyChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CalendarPermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QCalendarPermission"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlCalendarPermission",
+                "lineNumber": 77,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "accessMode",
+                        "notify": "accessModeChanged",
+                        "read": "accessMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QCalendarPermission::AccessMode",
+                        "user": false,
+                        "write": "setAccessMode"
+                    }
+                ],
+                "qualifiedClassName": "QQmlCalendarPermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "accessModeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ContactsPermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QContactsPermission"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlContactsPermission",
+                "lineNumber": 85,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "accessMode",
+                        "notify": "accessModeChanged",
+                        "read": "accessMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QContactsPermission::AccessMode",
+                        "user": false,
+                        "write": "setAccessMode"
+                    }
+                ],
+                "qualifiedClassName": "QQmlContactsPermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "accessModeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BluetoothPermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QBluetoothPermission"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlBluetoothPermission",
+                "lineNumber": 93,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "communicationModes",
+                        "notify": "communicationModesChanged",
+                        "read": "communicationModes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QBluetoothPermission::CommunicationModes",
+                        "user": false,
+                        "write": "setCommunicationModes"
+                    }
+                ],
+                "qualifiedClassName": "QQmlBluetoothPermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "communicationModesChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CameraPermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    }
+                ],
+                "className": "QQmlCameraPermission",
+                "lineNumber": 101,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlCameraPermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MicrophonePermission"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    }
+                ],
+                "className": "QQmlMicrophonePermission",
+                "lineNumber": 107,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "request",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PermissionStatus",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlMicrophonePermission",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlpermissions_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Settings"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1541"
+                    }
+                ],
+                "className": "QQmlSettings",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "defaultValue",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "value",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "isCloned": true,
+                        "name": "value",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "value",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "sync",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "category",
+                        "notify": "categoryChanged",
+                        "read": "category",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCategory"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "location",
+                        "notify": "locationChanged",
+                        "read": "location",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setLocation"
+                    }
+                ],
+                "qualifiedClassName": "QQmlSettings",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "categoryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "locationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "_q_propertyChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlsettings_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "StandardPaths"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QStandardPaths"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlStandardPaths",
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "displayName",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "executableName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "paths",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "findExecutable",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "executableName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "isCloned": true,
+                        "name": "findExecutable",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "options",
+                                "type": "QStandardPaths::LocateOptions"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "locate",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "isCloned": true,
+                        "name": "locate",
+                        "returnType": "QUrl"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "options",
+                                "type": "QStandardPaths::LocateOptions"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "locateAll",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            },
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "locateAll",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "standardLocations",
+                        "returnType": "QList<QUrl>"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QStandardPaths::StandardLocation"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "writableLocation",
+                        "returnType": "QUrl"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQmlStandardPaths",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlstandardpaths_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "SystemInformation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1540"
+                    }
+                ],
+                "className": "QQmlSystemInformation",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Endian",
+                        "values": [
+                            "Big",
+                            "Little"
+                        ]
+                    }
+                ],
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "wordSize",
+                        "read": "wordSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "byteOrder",
+                        "read": "byteOrder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlSystemInformation::Endian",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "buildCpuArchitecture",
+                        "read": "buildCpuArchitecture",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "currentCpuArchitecture",
+                        "read": "currentCpuArchitecture",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "buildAbi",
+                        "read": "buildAbi",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "kernelType",
+                        "read": "kernelType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "kernelVersion",
+                        "read": "kernelVersion",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "productType",
+                        "read": "productType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "productVersion",
+                        "read": "productVersion",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "prettyProductName",
+                        "read": "prettyProductName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "machineHostName",
+                        "read": "machineHostName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "machineUniqueId",
+                        "read": "machineUniqueId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QByteArray",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "bootUniqueId",
+                        "read": "bootUniqueId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QByteArray",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlSystemInformation",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlsysteminformation_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmldebugprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmldebugprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..eca53820c1332d726dc317fc22328b0320f9b4fd
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmldebugprivate_metatypes.json
@@ -0,0 +1,594 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugClient",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "state",
+                                "type": "State"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugConnection",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugConnection",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "connected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "disconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socketError",
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "socketError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "socketState",
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "socketStateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugconnection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugMessageClient",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugMessageClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QtMsgType"
+                            },
+                            {
+                                "type": "QString"
+                            },
+                            {
+                                "type": "QQmlDebugContextInfo"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "message",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugmessageclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDebugTranslationClient",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QQmlDebugTranslationClient",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugtranslationclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlEngineControlClient",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQmlEngineControlClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "engineId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "engineAboutToBeAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "engineId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "engineAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "engineId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "engineAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "engineId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "engineRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlenginecontrolclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlEngineDebugClient",
+                "lineNumber": 70,
+                "object": true,
+                "qualifiedClassName": "QQmlEngineDebugClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "objectId",
+                                "type": "qint32"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "newObject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QByteArray"
+                            },
+                            {
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "result",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlenginedebugclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlInspectorClient",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQmlInspectorClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "requestId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "result",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "responseReceived",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlinspectorclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlPreviewClient",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQmlPreviewClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "request",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "error",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "info",
+                                "type": "FpsInfo"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "fps",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlpreviewclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlProfilerClient",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "recording",
+                        "notify": "recordingChanged",
+                        "read": "isRecording",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRecording"
+                    }
+                ],
+                "qualifiedClassName": "QQmlProfilerClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "maximumTime",
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "complete",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "timestamp",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "engineIds",
+                                "type": "QList<int>"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "traceFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "timestamp",
+                                "type": "qint64"
+                            },
+                            {
+                                "name": "engineIds",
+                                "type": "QList<int>"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "traceStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "recordingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "features",
+                                "type": "quint64"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "recordedFeaturesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "cleared",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlprofilerclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlProfilerEventReceiver",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQmlProfilerEventReceiver",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlprofilereventreceiver_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QV4DebugClient",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QV4DebugClient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "connected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "interrupted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "result",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "failure",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "stopped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDebugClient"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qv4debugclient_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LocalSocketSignalTranslator",
+                "lineNumber": 376,
+                "object": true,
+                "qualifiedClassName": "LocalSocketSignalTranslator",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketError"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "socketError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractSocket::SocketState"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "socketStateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldebugconnection.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmldomprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmldomprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..3b5c2dadfdf678080fa548c3c4469f44f0bf7760
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmldomprivate_metatypes.json
@@ -0,0 +1,874 @@
+[
+    {
+        "classes": [
+            {
+                "className": "FormatTextStatus",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "StateType",
+                        "type": "quint8",
+                        "values": [
+                            "Invalid",
+                            "TopmostIntro",
+                            "TopQml",
+                            "TopJs",
+                            "ObjectdefinitionOrJs",
+                            "MultilineCommentStart",
+                            "MultilineCommentCont",
+                            "ImportStart",
+                            "ImportMaybeDotOrVersionOrAs",
+                            "ImportDot",
+                            "ImportMaybeAs",
+                            "ImportAs",
+                            "PropertyStart",
+                            "PropertyModifiers",
+                            "RequiredProperty",
+                            "PropertyListOpen",
+                            "PropertyName",
+                            "PropertyMaybeInitializer",
+                            "ComponentStart",
+                            "ComponentName",
+                            "TypeAnnotation",
+                            "TypeParameter",
+                            "EnumStart",
+                            "SignalStart",
+                            "SignalMaybeArglist",
+                            "SignalArglistOpen",
+                            "FunctionStart",
+                            "FunctionArglistOpen",
+                            "FunctionArglistClosed",
+                            "BindingOrObjectdefinition",
+                            "BindingAssignment",
+                            "ObjectdefinitionOpen",
+                            "Expression",
+                            "ExpressionContinuation",
+                            "ExpressionMaybeContinuation",
+                            "ExpressionOrObjectdefinition",
+                            "ExpressionOrLabel",
+                            "ParenOpen",
+                            "BracketOpen",
+                            "ObjectliteralOpen",
+                            "ObjectliteralAssignment",
+                            "BracketElementStart",
+                            "BracketElementMaybeObjectdefinition",
+                            "TernaryOp",
+                            "TernaryOpAfterColon",
+                            "JsblockOpen",
+                            "EmptyStatement",
+                            "BreakcontinueStatement",
+                            "IfStatement",
+                            "MaybeElse",
+                            "ElseClause",
+                            "ConditionOpen",
+                            "Substatement",
+                            "SubstatementOpen",
+                            "LabelledStatement",
+                            "ReturnStatement",
+                            "ThrowStatement",
+                            "StatementWithCondition",
+                            "StatementWithConditionParenOpen",
+                            "TryStatement",
+                            "CatchStatement",
+                            "FinallyStatement",
+                            "MaybeCatchOrFinally",
+                            "DoStatement",
+                            "DoStatementWhileParenOpen",
+                            "SwitchStatement",
+                            "CaseStart",
+                            "CaseCont"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 34,
+                "qualifiedClassName": "QQmlJS::Dom::FormatTextStatus"
+            },
+            {
+                "className": "FormatPartialStatus",
+                "gadget": true,
+                "lineNumber": 203,
+                "qualifiedClassName": "QQmlJS::Dom::FormatPartialStatus"
+            }
+        ],
+        "inputFile": "qqmldomcodeformatter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "IndentingLineWriter",
+                "gadget": true,
+                "lineNumber": 30,
+                "qualifiedClassName": "QQmlJS::Dom::IndentingLineWriter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "QQmlJS::Dom::LineWriter",
+                        "name": "LineWriter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldomindentinglinewriter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Token",
+                "gadget": true,
+                "lineNumber": 31,
+                "qualifiedClassName": "QQmlJS::Dom::Token"
+            }
+        ],
+        "inputFile": "qqmldomscanner_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "AttachedInfo",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "PathType",
+                        "values": [
+                            "Relative",
+                            "Canonical"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 51,
+                "qualifiedClassName": "QQmlJS::Dom::AttachedInfo",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "OwningItem"
+                    }
+                ]
+            },
+            {
+                "className": "UpdatedScriptExpression",
+                "gadget": true,
+                "lineNumber": 280,
+                "qualifiedClassName": "QQmlJS::Dom::UpdatedScriptExpression"
+            }
+        ],
+        "inputFile": "qqmldomattachedinfo_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Dom",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "PathRoot",
+                        "values": [
+                            "Other",
+                            "Modules",
+                            "Cpp",
+                            "Libs",
+                            "Top",
+                            "Env",
+                            "Universe"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "PathCurrent",
+                        "values": [
+                            "Other",
+                            "Obj",
+                            "ObjChain",
+                            "ScopeChain",
+                            "Component",
+                            "Module",
+                            "Ids",
+                            "Types",
+                            "LookupStrict",
+                            "LookupDynamic",
+                            "Lookup"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Language",
+                        "values": [
+                            "QmlQuick1",
+                            "QmlQuick2",
+                            "QmlQuick3",
+                            "QmlCompiled",
+                            "QmlAnnotation",
+                            "Qbs"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ResolveOption",
+                        "values": [
+                            "None",
+                            "TraceVisit"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "VisitOption",
+                        "values": [
+                            "None",
+                            "VisitSelf",
+                            "VisitAdopted",
+                            "Recurse",
+                            "NoPath",
+                            "Default"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "LookupOption",
+                        "values": [
+                            "Normal",
+                            "Strict",
+                            "VisitTopClassType",
+                            "SkipFirstScope"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "LookupType",
+                        "values": [
+                            "PropertyDef",
+                            "Binding",
+                            "Property",
+                            "Method",
+                            "Type",
+                            "CppType",
+                            "Symbol"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "VisitPrototypesOption",
+                        "values": [
+                            "Normal",
+                            "SkipFirst",
+                            "RevisitWarn",
+                            "ManualProceedToScope"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "DomKind",
+                        "values": [
+                            "Empty",
+                            "Object",
+                            "List",
+                            "Map",
+                            "Value",
+                            "ScriptElement"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "DomType",
+                        "values": [
+                            "Empty",
+                            "ExternalItemInfo",
+                            "ExternalItemPair",
+                            "QmlDirectory",
+                            "QmldirFile",
+                            "JsFile",
+                            "QmlFile",
+                            "QmltypesFile",
+                            "GlobalScope",
+                            "EnumItem",
+                            "EnumDecl",
+                            "JsResource",
+                            "QmltypesComponent",
+                            "QmlComponent",
+                            "GlobalComponent",
+                            "ModuleAutoExport",
+                            "ModuleIndex",
+                            "ModuleScope",
+                            "ImportScope",
+                            "Export",
+                            "Import",
+                            "Pragma",
+                            "Id",
+                            "QmlObject",
+                            "ConstantData",
+                            "SimpleObjectWrap",
+                            "ScriptExpression",
+                            "Reference",
+                            "PropertyDefinition",
+                            "Binding",
+                            "MethodParameter",
+                            "MethodInfo",
+                            "Version",
+                            "Comment",
+                            "CommentedElement",
+                            "RegionComments",
+                            "AstComments",
+                            "FileLocations",
+                            "UpdatedScriptExpression",
+                            "PropertyInfo",
+                            "MockObject",
+                            "MockOwner",
+                            "Map",
+                            "List",
+                            "ListP",
+                            "LoadInfo",
+                            "ErrorMessage",
+                            "AttachedInfo",
+                            "DomEnvironment",
+                            "DomUniverse",
+                            "ScriptElementWrap",
+                            "ScriptElementStart",
+                            "ScriptBlockStatement",
+                            "ScriptIdentifierExpression",
+                            "ScriptLiteral",
+                            "ScriptRegExpLiteral",
+                            "ScriptForStatement",
+                            "ScriptIfStatement",
+                            "ScriptPostExpression",
+                            "ScriptUnaryExpression",
+                            "ScriptBinaryExpression",
+                            "ScriptVariableDeclaration",
+                            "ScriptVariableDeclarationEntry",
+                            "ScriptReturnStatement",
+                            "ScriptGenericElement",
+                            "ScriptCallExpression",
+                            "ScriptFormalParameter",
+                            "ScriptArray",
+                            "ScriptObject",
+                            "ScriptProperty",
+                            "ScriptType",
+                            "ScriptElision",
+                            "ScriptArrayEntry",
+                            "ScriptPattern",
+                            "ScriptSwitchStatement",
+                            "ScriptCaseBlock",
+                            "ScriptCaseClause",
+                            "ScriptDefaultClause",
+                            "ScriptWhileStatement",
+                            "ScriptDoWhileStatement",
+                            "ScriptForEachStatement",
+                            "ScriptTemplateLiteral",
+                            "ScriptTemplateStringPart",
+                            "ScriptTaggedTemplate",
+                            "ScriptTryCatchStatement",
+                            "ScriptThrowStatement",
+                            "ScriptLabelledStatement",
+                            "ScriptBreakStatement",
+                            "ScriptContinueStatement",
+                            "ScriptConditionalExpression",
+                            "ScriptEmptyStatement",
+                            "ScriptParenthesizedExpression",
+                            "ScriptFunctionExpression",
+                            "ScriptYieldExpression",
+                            "ScriptNewExpression",
+                            "ScriptNewMemberExpression",
+                            "ScriptThisExpression",
+                            "ScriptSuperLiteral",
+                            "ScriptElementStop"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SimpleWrapOption",
+                        "values": [
+                            "None",
+                            "ValueType"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "BindingValueKind",
+                        "values": [
+                            "Object",
+                            "ScriptExpression",
+                            "Array",
+                            "Empty"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "BindingType",
+                        "values": [
+                            "Normal",
+                            "OnBinding"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ListOptions",
+                        "values": [
+                            "Normal",
+                            "Reverse"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "EscapeOptions",
+                        "values": [
+                            "OuterQuotes",
+                            "NoOuterQuotes"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ErrorLevel",
+                        "values": [
+                            "Debug",
+                            "Info",
+                            "Warning",
+                            "Error",
+                            "Fatal"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AstDumperOption",
+                        "values": [
+                            "None",
+                            "NoLocations",
+                            "NoAnnotations",
+                            "DumpNode",
+                            "SloppyCompare"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "GoTo",
+                        "values": [
+                            "Strict",
+                            "MostLikely"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AddOption",
+                        "values": [
+                            "KeepExisting",
+                            "Overwrite"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "FilterUpOptions",
+                        "values": [
+                            "ReturnOuter",
+                            "ReturnOuterNoSelf",
+                            "ReturnInner"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "WriteOutCheck",
+                        "values": [
+                            "None",
+                            "UpdatedDomCompare",
+                            "UpdatedDomStable",
+                            "Reparse",
+                            "ReparseCompare",
+                            "ReparseStable",
+                            "DumpOnFailure",
+                            "All",
+                            "Default"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "LocalSymbolsType",
+                        "values": [
+                            "None",
+                            "ObjectType",
+                            "ValueType",
+                            "Signal",
+                            "Method",
+                            "Attribute",
+                            "Id",
+                            "Namespace",
+                            "Global",
+                            "MethodParameter",
+                            "Singleton",
+                            "AttachedType"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FileLocationRegion",
+                        "type": "int",
+                        "values": [
+                            "AsTokenRegion",
+                            "BreakKeywordRegion",
+                            "DoKeywordRegion",
+                            "CaseKeywordRegion",
+                            "CatchKeywordRegion",
+                            "ColonTokenRegion",
+                            "CommaTokenRegion",
+                            "ComponentKeywordRegion",
+                            "ContinueKeywordRegion",
+                            "DefaultKeywordRegion",
+                            "EllipsisTokenRegion",
+                            "ElseKeywordRegion",
+                            "EnumKeywordRegion",
+                            "EnumValueRegion",
+                            "EqualTokenRegion",
+                            "ForKeywordRegion",
+                            "FinallyKeywordRegion",
+                            "FirstSemicolonTokenRegion",
+                            "FunctionKeywordRegion",
+                            "IdColonTokenRegion",
+                            "IdNameRegion",
+                            "IdTokenRegion",
+                            "IdentifierRegion",
+                            "IfKeywordRegion",
+                            "ImportTokenRegion",
+                            "ImportUriRegion",
+                            "InOfTokenRegion",
+                            "LeftBraceRegion",
+                            "LeftBracketRegion",
+                            "LeftParenthesisRegion",
+                            "MainRegion",
+                            "NewKeywordRegion",
+                            "OperatorTokenRegion",
+                            "OnTargetRegion",
+                            "OnTokenRegion",
+                            "PragmaKeywordRegion",
+                            "PragmaValuesRegion",
+                            "PropertyKeywordRegion",
+                            "QuestionMarkTokenRegion",
+                            "ReadonlyKeywordRegion",
+                            "RequiredKeywordRegion",
+                            "ReturnKeywordRegion",
+                            "RightBraceRegion",
+                            "RightBracketRegion",
+                            "RightParenthesisRegion",
+                            "SecondSemicolonRegion",
+                            "SemicolonTokenRegion",
+                            "SignalKeywordRegion",
+                            "SuperKeywordRegion",
+                            "StarTokenRegion",
+                            "SwitchKeywordRegion",
+                            "ThisKeywordRegion",
+                            "ThrowKeywordRegion",
+                            "TryKeywordRegion",
+                            "TypeIdentifierRegion",
+                            "TypeModifierRegion",
+                            "VersionRegion",
+                            "WhileKeywordRegion",
+                            "YieldKeywordRegion"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "namespace": true,
+                "qualifiedClassName": "QQmlJS::Dom"
+            }
+        ],
+        "inputFile": "qqmldomconstants_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ScriptExpression",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ExpressionType",
+                        "values": [
+                            "BindingExpression",
+                            "FunctionBody",
+                            "ArgInitializer",
+                            "ArgumentStructure",
+                            "ReturnType",
+                            "JSCode",
+                            "ESMCode"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 388,
+                "qualifiedClassName": "QQmlJS::Dom::ScriptExpression",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "OwningItem"
+                    }
+                ]
+            },
+            {
+                "className": "MethodInfo",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MethodType",
+                        "values": [
+                            "Signal",
+                            "Method"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 748,
+                "qualifiedClassName": "QQmlJS::Dom::MethodInfo",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "AttributeInfo"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldomelements_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "ErrorGroup",
+                "gadget": true,
+                "lineNumber": 45,
+                "qualifiedClassName": "QQmlJS::Dom::ErrorGroup"
+            },
+            {
+                "className": "ErrorGroups",
+                "gadget": true,
+                "lineNumber": 63,
+                "qualifiedClassName": "QQmlJS::Dom::ErrorGroups"
+            },
+            {
+                "className": "ErrorMessage",
+                "gadget": true,
+                "lineNumber": 101,
+                "qualifiedClassName": "QQmlJS::Dom::ErrorMessage"
+            }
+        ],
+        "inputFile": "qqmldomerrormessage_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "FieldFilter",
+                "gadget": true,
+                "lineNumber": 32,
+                "qualifiedClassName": "QQmlJS::Dom::FieldFilter"
+            }
+        ],
+        "inputFile": "qqmldomfieldfilter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "FileWriter",
+                "gadget": true,
+                "lineNumber": 29,
+                "qualifiedClassName": "QQmlJS::Dom::FileWriter"
+            }
+        ],
+        "inputFile": "qqmldomfilewriter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Reference",
+                "gadget": true,
+                "lineNumber": 645,
+                "qualifiedClassName": "QQmlJS::Dom::Reference",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "DomElement"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldomitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "LineWriterOptions",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "LineEndings",
+                        "values": [
+                            "Unix",
+                            "Windows",
+                            "OldMacOs"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TrailingSpace",
+                        "values": [
+                            "Preserve",
+                            "Remove"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Update",
+                        "values": [
+                            "None",
+                            "Expressions",
+                            "Locations",
+                            "All",
+                            "Default"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "AttributesSequence",
+                        "values": [
+                            "Normalize",
+                            "Preserve"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 74,
+                "qualifiedClassName": "QQmlJS::Dom::LineWriterOptions"
+            },
+            {
+                "className": "PendingSourceLocation",
+                "gadget": true,
+                "lineNumber": 111,
+                "qualifiedClassName": "QQmlJS::Dom::PendingSourceLocation"
+            },
+            {
+                "className": "LineWriter",
+                "gadget": true,
+                "lineNumber": 126,
+                "qualifiedClassName": "QQmlJS::Dom::LineWriter"
+            }
+        ],
+        "inputFile": "qqmldomlinewriter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Path",
+                "gadget": true,
+                "lineNumber": 596,
+                "qualifiedClassName": "QQmlJS::Dom::Path"
+            }
+        ],
+        "inputFile": "qqmldompath_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "DomUniverse",
+                "gadget": true,
+                "lineNumber": 173,
+                "qualifiedClassName": "QQmlJS::Dom::DomUniverse",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "DomTop"
+                    },
+                    {
+                        "access": "public",
+                        "name": "std::enable_shared_from_this<DomUniverse>"
+                    }
+                ]
+            },
+            {
+                "className": "RefCacheEntry",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Cached",
+                        "values": [
+                            "None",
+                            "First",
+                            "All"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 701,
+                "qualifiedClassName": "QQmlJS::Dom::RefCacheEntry"
+            },
+            {
+                "className": "DomEnvironment",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Option",
+                        "values": [
+                            "Default",
+                            "KeepValid",
+                            "Exported",
+                            "NoReload",
+                            "WeakLoad",
+                            "SingleThreaded",
+                            "NoDependencies"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 716,
+                "qualifiedClassName": "QQmlJS::Dom::DomEnvironment",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "DomTop"
+                    },
+                    {
+                        "access": "public",
+                        "name": "std::enable_shared_from_this<DomEnvironment>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldomtop_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmllocalstorage_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmllocalstorage_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..a00b3d8890cf92fdfaca788a364f9c2e4ba40fed
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmllocalstorage_metatypes.json
@@ -0,0 +1,48 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LocalStorage"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlLocalStorage",
+                "lineNumber": 26,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "openDatabaseSync",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQmlLocalStorage",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmllocalstorage_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmllsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmllsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..291537f40dbd65e5ff3fcceb7e361e65da1991b8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmllsprivate_metatypes.json
@@ -0,0 +1,573 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QLanguageServerModule",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QLanguageServerModule",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QLanguageServer",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "RunStatus",
+                        "values": [
+                            "NotSetup",
+                            "SettingUp",
+                            "DidSetup",
+                            "Initializing",
+                            "DidInitialize",
+                            "WaitPending",
+                            "Stopping",
+                            "Stopped"
+                        ]
+                    }
+                ],
+                "lineNumber": 40,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "runStatus",
+                        "notify": "runStatusChanged",
+                        "read": "runStatus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RunStatus",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "isInitialized",
+                        "read": "isInitialized",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QLanguageServer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "RunStatus"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "runStatusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "server",
+                                "type": "QLanguageServer*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "clientInitialized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "shutdown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "lifecycleError",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "readNextMessage",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "d",
+                                "type": "QByteArray"
+                            },
+                            {
+                                "name": "isEndOfMessage",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "receiveData",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlanguageserver_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlCodeModel",
+                "lineNumber": 80,
+                "object": true,
+                "qualifiedClassName": "QmlLsp::QQmlCodeModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "updatedSnapshot",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "documentationRootPathChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "onCppFileChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlcodemodel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QmlCompletionSupport",
+                "lineNumber": 46,
+                "object": true,
+                "qualifiedClassName": "QmlCompletionSupport",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<CompletionRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlcompletionsupport_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlFindUsagesSupport",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQmlFindUsagesSupport",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<ReferencesRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlfindusagessupport_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDocumentFormatting",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQmlDocumentFormatting",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<DocumentFormattingRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlformatting_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QmlGoToDefinitionSupport",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QmlGoToDefinitionSupport",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<DefinitionRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlgotodefinitionsupport_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QmlGoToTypeDefinitionSupport",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QmlGoToTypeDefinitionSupport",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<TypeDefinitionRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlgototypedefinitionsupport_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlHover",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQmlHover",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<HoverRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlhover_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlLanguageServer",
+                "lineNumber": 39,
+                "object": true,
+                "qualifiedClassName": "QmlLsp::QQmlLanguageServer",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "exit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "errorExit",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLanguageServerModule"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmllanguageserver_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QmlLintSuggestions",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QmlLsp::QmlLintSuggestions",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "uri",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "diagnose",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "server",
+                                "type": "QLanguageServer*"
+                            },
+                            {
+                                "name": "protocol",
+                                "type": "QLanguageServerProtocol*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "registerHandlers",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "clientInfo",
+                                "type": "QLspSpecification::InitializeParams"
+                            },
+                            {
+                                "type": "QLspSpecification::InitializeResult&"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setupCapabilities",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLanguageServerModule"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmllintsuggestions_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlRangeFormatting",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQmlRangeFormatting",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<RangeFormattingRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlrangeformatting_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlRenameSymbolSupport",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQmlRenameSymbolSupport",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlBaseModule<RenameRequest>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlrenamesymbolsupport_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "HighlightingUtils",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "SemanticTokenProtocolTypes",
+                        "values": [
+                            "Namespace",
+                            "Type",
+                            "Enum",
+                            "Parameter",
+                            "Variable",
+                            "Property",
+                            "EnumMember",
+                            "Method",
+                            "Keyword",
+                            "Comment",
+                            "String",
+                            "Number",
+                            "Regexp",
+                            "Operator",
+                            "Decorator",
+                            "QmlLocalId",
+                            "QmlExternalId",
+                            "QmlRootObjectProperty",
+                            "QmlScopeObjectProperty",
+                            "QmlExternalObjectProperty",
+                            "JsScopeVar",
+                            "JsImportVar",
+                            "JsGlobalVar",
+                            "QmlStateName"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "namespace": true,
+                "qualifiedClassName": "HighlightingUtils"
+            }
+        ],
+        "inputFile": "qqmlsemantictokens_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TextSynchronization",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "TextSynchronization",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "params",
+                                "type": "QLspSpecification::DidOpenTextDocumentParams"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "didOpenTextDocument",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "params",
+                                "type": "QLspSpecification::DidChangeTextDocumentParams"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "didDidChangeTextDocument",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "params",
+                                "type": "QLspSpecification::DidCloseTextDocumentParams"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "didCloseTextDocument",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLanguageServerModule"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextsynchronization_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "WorkspaceHandlers",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "WorkspaceHandlers",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QLanguageServer*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "clientInitialized",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLanguageServerModule"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qworkspace_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmeta_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmeta_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..b0ef17f69875dd331b94f18d5c3004d97a6de071
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmeta_metatypes.json
@@ -0,0 +1,584 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQmlLocaleEnums",
+                "gadget": true,
+                "lineNumber": 30,
+                "qualifiedClassName": "QQmlLocaleEnums",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlLocale"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Locale"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "514"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQmlLocaleEnums"
+                    },
+                    {
+                        "name": "QML.ForeignIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlLocaleEnumsForeign",
+                "lineNumber": 37,
+                "namespace": true,
+                "qualifiedClassName": "QQmlLocaleEnumsForeign"
+            }
+        ],
+        "inputFile": "qqmllocaleenums_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Binding"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "ImmediatePropertyNames",
+                        "value": "objectName,target,property,value,when,delayed,restoreMode"
+                    }
+                ],
+                "className": "QQmlBind",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RestorationMode",
+                        "values": [
+                            "RestoreNone",
+                            "RestoreBinding",
+                            "RestoreValue",
+                            "RestoreBindingOrValue"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ],
+                    [
+                        {
+                            "className": "QQmlPropertyValueSource",
+                            "id": "\"org.qt-project.Qt.QQmlPropertyValueSource\""
+                        }
+                    ]
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "target",
+                        "read": "object",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false,
+                        "write": "setObject"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "property",
+                        "read": "property",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setProperty"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "value",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "when",
+                        "read": "when",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWhen"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "delayed",
+                        "read": "delayed",
+                        "required": false,
+                        "revision": 520,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDelayed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "restoreMode",
+                        "notify": "restoreModeChanged",
+                        "read": "restoreMode",
+                        "required": false,
+                        "revision": 526,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RestorationMode",
+                        "user": false,
+                        "write": "setRestoreMode"
+                    }
+                ],
+                "qualifiedClassName": "QQmlBind",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "restoreModeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "targetValueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlPropertyValueSource"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlbind_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Connections"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.HasCustomParser",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlConnections",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "target",
+                        "notify": "targetChanged",
+                        "read": "target",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false,
+                        "write": "setTarget"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "ignoreUnknownSignals",
+                        "read": "ignoreUnknownSignals",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIgnoreUnknownSignals"
+                    }
+                ],
+                "qualifiedClassName": "QQmlConnections",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "enabledChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlconnections_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LoggingCategory"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "520"
+                    }
+                ],
+                "className": "QQmlLoggingCategory",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DefaultLogLevel",
+                        "values": [
+                            "Debug",
+                            "Info",
+                            "Warning",
+                            "Critical",
+                            "Fatal"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 32,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "defaultLogLevel",
+                        "read": "defaultLogLevel",
+                        "required": false,
+                        "revision": 524,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DefaultLogLevel",
+                        "user": false,
+                        "write": "setDefaultLogLevel"
+                    }
+                ],
+                "qualifiedClassName": "QQmlLoggingCategory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlLoggingCategoryBase"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlloggingcategory_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "ParentProperty",
+                        "value": "parent"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Timer"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQmlTimer",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "interval",
+                        "notify": "intervalChanged",
+                        "read": "interval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "running",
+                        "notify": "runningChanged",
+                        "read": "isRunning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "repeat",
+                        "notify": "repeatChanged",
+                        "read": "isRepeating",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRepeating"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "triggeredOnStart",
+                        "notify": "triggeredOnStartChanged",
+                        "read": "triggeredOnStart",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTriggeredOnStart"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "parent",
+                        "read": "parent",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlTimer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "runningChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "intervalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "repeatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "triggeredOnStartChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "stop",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "restart",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "ticked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmltimer_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmodels_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmodels_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..76ed3cd7307f92d913a48738ab8fcb7c24f5068a
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlmodels_metatypes.json
@@ -0,0 +1,3563 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQmlChangeSet",
+                "gadget": true,
+                "lineNumber": 25,
+                "qualifiedClassName": "QQmlChangeSet"
+            }
+        ],
+        "inputFile": "qqmlchangeset_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDMAbstractItemModelData",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "hasModelChildren",
+                        "read": "hasModelChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "modelData",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModelData"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlDMAbstractItemModelData",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modelDataChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDelegateModelItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldmabstractitemmodeldata_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDMListAccessorData",
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "modelData",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModelData"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModelData"
+                    }
+                ],
+                "qualifiedClassName": "QQmlDMListAccessorData",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modelDataChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDelegateModelItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldmlistaccessordata_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQmlDMObjectData",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlAdaptorModelProxyInterface",
+                            "id": "\"org.qt-project.Qt.QQmlAdaptorModelProxyInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "modelData",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "",
+                        "notify": "modelDataChanged",
+                        "read": "modelData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlDMObjectData",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modelDataChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlDelegateModelItem"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlAdaptorModelProxyInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmldmobjectdata_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AbstractDelegateComponent"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Cannot create instance of abstract class AbstractDelegateComponent."
+                    }
+                ],
+                "className": "QQmlAbstractDelegateComponent",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQmlAbstractDelegateComponent",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlComponent"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlabstractdelegatecomponent_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "delegate"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "DelegateModel"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQmlDelegateModelAttached"
+                    }
+                ],
+                "className": "QQmlDelegateModel",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 37,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "modelIndex",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "parentModelIndex",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "model",
+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "filterOnGroup",
+                        "notify": "filterGroupChanged",
+                        "read": "filterGroup",
+                        "required": false,
+                        "reset": "resetFilterGroup",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setFilterGroup"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "items",
+                        "read": "items",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlDelegateModelGroup*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "persistedItems",
+                        "read": "persistedItems",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlDelegateModelGroup*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "groups",
+                        "read": "groups",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQmlDelegateModelGroup>",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "parts",
+                        "read": "parts",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
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+                                "type": "QQmlChangeSet"
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+                        "name": "modelLayoutAboutToBeChanged",
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+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemModel::LayoutChangeHint"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "modelLayoutChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "modelRowsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "sourceStart",
+                                "type": "int"
+                            },
+                            {
+                                "name": "sourceEnd",
+                                "type": "int"
+                            },
+                            {
+                                "name": "destinationParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "destinationRow",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "modelRowsAboutToBeMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "modelRowsAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "modelRowsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "sourceParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "sourceStart",
+                                "type": "int"
+                            },
+                            {
+                                "name": "sourceEnd",
+                                "type": "int"
+                            },
+                            {
+                                "name": "destinationParent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "destinationRow",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "modelRowsMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "modelRowsRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "modelColumnsAboutToBeInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "modelColumnsAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "modelColumnsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "modelColumnsRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmltreemodeltotablemodel_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Package"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickPackageAttached"
+                    }
+                ],
+                "className": "QQuickPackage",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "data",
+                        "read": "data",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickPackage",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickPackageAttached",
+                "lineNumber": 49,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPackageAttached",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpackage_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlnetwork_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlnetwork_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..acf0f4f3b25d391929a4f5290322dea6ea463edc
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlnetwork_metatypes.json
@@ -0,0 +1,354 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQmlSslConfiguration",
+                "gadget": true,
+                "lineNumber": 30,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "certificateFiles",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setCertificateFiles",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "privateKey",
+                                "type": "QQmlSslKey"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setPrivateKey",
+                        "returnType": "void"
+                    }
+                ],
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "ciphers",
+                        "read": "ciphers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCiphers"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "sslOptions",
+                        "read": "sslOptions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QSsl::SslOption>",
+                        "user": false,
+                        "write": "setSslOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "protocol",
+                        "read": "protocol",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSsl::SslProtocol",
+                        "user": false,
+                        "write": "setProtocol"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "peerVerifyMode",
+                        "read": "peerVerifyMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSslSocket::PeerVerifyMode",
+                        "user": false,
+                        "write": "setPeerVerifyMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "peerVerifyDepth",
+                        "read": "peerVerifyDepth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPeerVerifyDepth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "sessionTicket",
+                        "read": "sessionTicket",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QByteArray",
+                        "user": false,
+                        "write": "setSessionTicket"
+                    }
+                ],
+                "qualifiedClassName": "QQmlSslConfiguration"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "sslConfiguration"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QQmlSslDefaultConfiguration",
+                "gadget": true,
+                "lineNumber": 87,
+                "qualifiedClassName": "QQmlSslDefaultConfiguration",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlSslConfiguration"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "sslDtlsConfiguration"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QQmlSslDefaultDtlsConfiguration",
+                "gadget": true,
+                "lineNumber": 97,
+                "qualifiedClassName": "QQmlSslDefaultDtlsConfiguration",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlSslConfiguration"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlsslconfiguration_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "sslKey"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QQmlSslKey",
+                "gadget": true,
+                "lineNumber": 28,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "keyFile",
+                        "read": "keyFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setKeyFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "keyAlgorithm",
+                        "read": "keyAlgorithm",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSsl::KeyAlgorithm",
+                        "user": false,
+                        "write": "setKeyAlgorithm"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "keyFormat",
+                        "read": "keyFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSsl::EncodingFormat",
+                        "user": false,
+                        "write": "setKeyFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "keyPassPhrase",
+                        "read": "keyPassPhrase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QByteArray",
+                        "user": false,
+                        "write": "setKeyPassPhrase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "keyType",
+                        "read": "keyType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSsl::KeyType",
+                        "user": false,
+                        "write": "setKeyType"
+                    }
+                ],
+                "qualifiedClassName": "QQmlSslKey"
+            }
+        ],
+        "inputFile": "qqmlsslkey_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QSsl"
+                    },
+                    {
+                        "name": "QML.ForeignIsNamespace",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Ssl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QSslForeignNamespace",
+                "lineNumber": 26,
+                "namespace": true,
+                "qualifiedClassName": "QSslForeignNamespace"
+            }
+        ],
+        "inputFile": "qqmlsslnamespace_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QSslSocket"
+                    },
+                    {
+                        "name": "QML.ForeignIsNamespace",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "SslSocket"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "SslSocketForeignNamespace",
+                "lineNumber": 26,
+                "namespace": true,
+                "qualifiedClassName": "SslSocketForeignNamespace"
+            }
+        ],
+        "inputFile": "qqmlsslsocketnamespace_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QNetworkInformation"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "NetworkInformation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQmlNetworkInformation",
+                "gadget": true,
+                "lineNumber": 27,
+                "qualifiedClassName": "QQmlNetworkInformation"
+            }
+        ],
+        "inputFile": "qqmlnetworkinformation_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmltoolingsettingsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmltoolingsettingsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmltoolingsettingsprivate_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmltyperegistrarprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmltyperegistrarprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmltyperegistrarprivate_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlworkerscript_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlworkerscript_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c157043d506ebc8ef5371f091b5ec51d8f222abe
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlworkerscript_metatypes.json
@@ -0,0 +1,152 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickWorkerScriptEngine",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QQuickWorkerScriptEngine",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "WorkerScript"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickWorkerScript",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 50,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "ready",
+                        "notify": "readyChanged",
+                        "read": "ready",
+                        "required": false,
+                        "revision": 527,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickWorkerScript",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "readyChanged",
+                        "returnType": "void",
+                        "revision": 527
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "messageObject",
+                                "type": "QJSValue"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "message",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sendMessage",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickworkerscript_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickWorkerScriptEnginePrivate",
+                "lineNumber": 107,
+                "object": true,
+                "qualifiedClassName": "QQuickWorkerScriptEnginePrivate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "stopThread",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickworkerscript.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6qmlxmllistmodel_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlxmllistmodel_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..f0293087fddd20afe22ba299828279859d4cfff8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6qmlxmllistmodel_metatypes.json
@@ -0,0 +1,351 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQmlXmlListModelQueryResult",
+                "gadget": true,
+                "lineNumber": 51,
+                "qualifiedClassName": "QQmlXmlListModelQueryResult"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "XmlListModelRole"
+                    }
+                ],
+                "className": "QQmlXmlListModelRole",
+                "lineNumber": 61,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "name",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "elementName",
+                        "notify": "elementNameChanged",
+                        "read": "elementName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setElementName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "attributeName",
+                        "notify": "attributeNameChanged",
+                        "read": "attributeName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAttributeName"
+                    }
+                ],
+                "qualifiedClassName": "QQmlXmlListModelRole",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "elementNameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "attributeNameChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "XmlListModel"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "roles"
+                    }
+                ],
+                "className": "QQmlXmlListModel",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading",
+                            "Error"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 95,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "errorString",
+                        "returnType": "QString"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Status",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "progress",
+                        "notify": "progressChanged",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "query",
+                        "notify": "queryChanged",
+                        "read": "query",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setQuery"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "roles",
+                        "read": "roleObjects",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQmlXmlListModelRole>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQmlXmlListModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQmlXmlListModel::Status"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "progress",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "progressChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "queryChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "reload",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "requestFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "requestProgress",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "dataCleared",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QQmlXmlListModelQueryResult"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "queryCompleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "object",
+                                "type": "void*"
+                            },
+                            {
+                                "name": "error",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "queryError",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qqmlxmllistmodel_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quick_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quick_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c2e6257a54b128139d0f99b731e3b5cb3c4ac3a0
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quick_metatypes.json
@@ -0,0 +1,40798 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QSGCurveFillNode",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QSGCurveFillNode",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "handleTextureChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "handleTextureProviderDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGCurveAbstractNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgcurvefillnode_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickRhiItem",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TextureFormat",
+                        "values": [
+                            "RGBA8",
+                            "RGBA16F",
+                            "RGBA32F",
+                            "RGB10A2"
+                        ]
+                    }
+                ],
+                "lineNumber": 48,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "sampleCount",
+                        "notify": "sampleCountChanged",
+                        "read": "sampleCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSampleCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "colorBufferFormat",
+                        "notify": "colorBufferFormatChanged",
+                        "read": "colorBufferFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextureFormat",
+                        "user": false,
+                        "write": "setColorBufferFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "mirrorVertically",
+                        "notify": "mirrorVerticallyChanged",
+                        "read": "isMirrorVerticallyEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMirrorVertically"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "alphaBlending",
+                        "notify": "alphaBlendingChanged",
+                        "read": "alphaBlending",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAlphaBlending"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "fixedColorBufferWidth",
+                        "notify": "fixedColorBufferWidthChanged",
+                        "read": "fixedColorBufferWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFixedColorBufferWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "fixedColorBufferHeight",
+                        "notify": "fixedColorBufferHeightChanged",
+                        "read": "fixedColorBufferHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFixedColorBufferHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "effectiveColorBufferSize",
+                        "notify": "effectiveColorBufferSizeChanged",
+                        "read": "effectiveColorBufferSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickRhiItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sampleCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "colorBufferFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "autoRenderTargetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "mirrorVerticallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "alphaBlendingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "fixedColorBufferWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "fixedColorBufferHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "effectiveColorBufferSizeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "invalidateSceneGraph",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickrhiitem.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickRhiItemNode",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QQuickRhiItemNode",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "render",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTextureProvider"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGSimpleTextureNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickrhiitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "WindowContainer"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QQuickWindowContainer",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": true,
+                        "index": 0,
+                        "name": "window",
+                        "notify": "containedWindowChanged",
+                        "read": "containedWindow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QWindow*",
+                        "user": false,
+                        "write": "setContainedWindow"
+                    }
+                ],
+                "qualifiedClassName": "QQuickWindowContainer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "window",
+                                "type": "QWindow*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "containedWindowChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickImplicitSizeItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickwindowcontainer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickDefaultTextureFactory",
+                "lineNumber": 33,
+                "object": true,
+                "qualifiedClassName": "QQuickDefaultTextureFactory",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTextureFactory"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpixmap_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Accessible"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Accessible is only available via attached properties."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickAccessibleAttached"
+                    },
+                    {
+                        "name": "QML.Extended",
+                        "value": "QAccessible"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    }
+                ],
+                "className": "QQuickAccessibleAttached",
+                "lineNumber": 50,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "html",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "stripHtml",
+                        "returnType": "QString",
+                        "revision": 1538
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "politeness",
+                                "type": "QAccessible::AnnouncementPoliteness"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "announce",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 35,
+                        "isCloned": true,
+                        "name": "announce",
+                        "returnType": "void",
+                        "revision": 1544
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "role",
+                        "notify": "roleChanged",
+                        "read": "role",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QAccessible::Role",
+                        "user": false,
+                        "write": "setRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "name",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "description",
+                        "notify": "descriptionChanged",
+                        "read": "description",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDescription"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "id",
+                        "notify": "idChanged",
+                        "read": "id",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setId"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "ignored",
+                        "notify": "ignoredChanged",
+                        "read": "ignored",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIgnored"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "checkable",
+                        "notify": "checkableChanged",
+                        "read": "checkable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_checkable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "checked",
+                        "notify": "checkedChanged",
+                        "read": "checked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_checked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "editable",
+                        "notify": "editableChanged",
+                        "read": "editable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_editable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "focusable",
+                        "notify": "focusableChanged",
+                        "read": "focusable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_focusable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "focused",
+                        "notify": "focusedChanged",
+                        "read": "focused",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_focused"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "multiLine",
+                        "notify": "multiLineChanged",
+                        "read": "multiLine",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_multiLine"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "readOnly",
+                        "notify": "readOnlyChanged",
+                        "read": "readOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_readOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "selected",
+                        "notify": "selectedChanged",
+                        "read": "selected",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_selected"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "selectable",
+                        "notify": "selectableChanged",
+                        "read": "selectable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_selectable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "pressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_pressed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "checkStateMixed",
+                        "notify": "checkStateMixedChanged",
+                        "read": "checkStateMixed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_checkStateMixed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "defaultButton",
+                        "notify": "defaultButtonChanged",
+                        "read": "defaultButton",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_defaultButton"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "passwordEdit",
+                        "notify": "passwordEditChanged",
+                        "read": "passwordEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_passwordEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "selectableText",
+                        "notify": "selectableTextChanged",
+                        "read": "selectableText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_selectableText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "searchEdit",
+                        "notify": "searchEditChanged",
+                        "read": "searchEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_searchEdit"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAccessibleAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "checkableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "checkedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "editableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "focusableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "focusedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "multiLineChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "readOnlyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "selectedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "selectableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "checkStateMixedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "defaultButtonChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "passwordEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "selectableTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "searchEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "roleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "descriptionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "idChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "ignoredChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "pressAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "toggleAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "increaseAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "decreaseAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "scrollUpAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "scrollDownAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "scrollLeftAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "scrollRightAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "previousPageAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "nextPageAction",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "ignored",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "setIgnored",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickaccessibleattached_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAnchors",
+                "enums": [
+                    {
+                        "alias": "Anchor",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Anchors",
+                        "type": "uint",
+                        "values": [
+                            "InvalidAnchor",
+                            "LeftAnchor",
+                            "RightAnchor",
+                            "TopAnchor",
+                            "BottomAnchor",
+                            "HCenterAnchor",
+                            "VCenterAnchor",
+                            "BaselineAnchor",
+                            "Horizontal_Mask",
+                            "Vertical_Mask"
+                        ]
+                    }
+                ],
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "left",
+                        "notify": "leftChanged",
+                        "read": "left",
+                        "required": false,
+                        "reset": "resetLeft",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setLeft"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "right",
+                        "notify": "rightChanged",
+                        "read": "right",
+                        "required": false,
+                        "reset": "resetRight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setRight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "horizontalCenter",
+                        "notify": "horizontalCenterChanged",
+                        "read": "horizontalCenter",
+                        "required": false,
+                        "reset": "resetHorizontalCenter",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setHorizontalCenter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "top",
+                        "notify": "topChanged",
+                        "read": "top",
+                        "required": false,
+                        "reset": "resetTop",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setTop"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "bottom",
+                        "notify": "bottomChanged",
+                        "read": "bottom",
+                        "required": false,
+                        "reset": "resetBottom",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setBottom"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "verticalCenter",
+                        "notify": "verticalCenterChanged",
+                        "read": "verticalCenter",
+                        "required": false,
+                        "reset": "resetVerticalCenter",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setVerticalCenter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "baseline",
+                        "notify": "baselineChanged",
+                        "read": "baseline",
+                        "required": false,
+                        "reset": "resetBaseline",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false,
+                        "write": "setBaseline"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "margins",
+                        "notify": "marginsChanged",
+                        "read": "margins",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMargins"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "leftMargin",
+                        "notify": "leftMarginChanged",
+                        "read": "leftMargin",
+                        "required": false,
+                        "reset": "resetLeftMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "rightMargin",
+                        "notify": "rightMarginChanged",
+                        "read": "rightMargin",
+                        "required": false,
+                        "reset": "resetRightMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "horizontalCenterOffset",
+                        "notify": "horizontalCenterOffsetChanged",
+                        "read": "horizontalCenterOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHorizontalCenterOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "topMargin",
+                        "notify": "topMarginChanged",
+                        "read": "topMargin",
+                        "required": false,
+                        "reset": "resetTopMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "bottomMargin",
+                        "notify": "bottomMarginChanged",
+                        "read": "bottomMargin",
+                        "required": false,
+                        "reset": "resetBottomMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "verticalCenterOffset",
+                        "notify": "verticalCenterOffsetChanged",
+                        "read": "verticalCenterOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setVerticalCenterOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "baselineOffset",
+                        "notify": "baselineOffsetChanged",
+                        "read": "baselineOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBaselineOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "fill",
+                        "notify": "fillChanged",
+                        "read": "fill",
+                        "required": false,
+                        "reset": "resetFill",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setFill"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "centerIn",
+                        "notify": "centerInChanged",
+                        "read": "centerIn",
+                        "required": false,
+                        "reset": "resetCenterIn",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setCenterIn"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "alignWhenCentered",
+                        "notify": "centerAlignedChanged",
+                        "read": "alignWhenCentered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAlignWhenCentered"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAnchors",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "leftChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "topChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "bottomChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "verticalCenterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "horizontalCenterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "baselineChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "fillChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "centerInChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "leftMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "rightMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "topMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "bottomMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "marginsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "verticalCenterOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "horizontalCenterOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "baselineOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "centerAlignedChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickanchors_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAnchorLine",
+                "gadget": true,
+                "lineNumber": 24,
+                "qualifiedClassName": "QQuickAnchorLine"
+            }
+        ],
+        "inputFile": "qquickanchors_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AnimatedImage"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAnimatedImage",
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "playing",
+                        "notify": "playingChanged",
+                        "read": "isPlaying",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPlaying"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "paused",
+                        "notify": "pausedChanged",
+                        "read": "isPaused",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPaused"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentFrame",
+                        "notify": "frameChanged",
+                        "read": "currentFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "frameCount",
+                        "notify": "frameCountChanged",
+                        "read": "frameCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "speed",
+                        "notify": "speedChanged",
+                        "read": "speed",
+                        "required": false,
+                        "revision": 523,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSpeed"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAnimatedImage",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "playingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "pausedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "frameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "currentFrameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "frameCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "speedChanged",
+                        "returnType": "void",
+                        "revision": 523
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "movieUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "movieRequestFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "playingStatusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "onCacheChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickImage"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickanimatedimage_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AnimatedSprite"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAnimatedSprite",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LoopParameters",
+                        "values": [
+                            "Infinite"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FinishBehavior",
+                        "values": [
+                            "FinishAtInitialFrame",
+                            "FinishAtFinalFrame"
+                        ]
+                    }
+                ],
+                "lineNumber": 34,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "running",
+                        "notify": "runningChanged",
+                        "read": "running",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "interpolate",
+                        "notify": "interpolateChanged",
+                        "read": "interpolate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInterpolate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "reverse",
+                        "notify": "reverseChanged",
+                        "read": "reverse",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReverse"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "frameSync",
+                        "notify": "frameSyncChanged",
+                        "read": "frameSync",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFrameSync"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "frameCount",
+                        "notify": "frameCountChanged",
+                        "read": "frameCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "frameHeight",
+                        "notify": "frameHeightChanged",
+                        "read": "frameHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "frameWidth",
+                        "notify": "frameWidthChanged",
+                        "read": "frameWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "frameX",
+                        "notify": "frameXChanged",
+                        "read": "frameX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "frameY",
+                        "notify": "frameYChanged",
+                        "read": "frameY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "frameRate",
+                        "notify": "frameRateChanged",
+                        "read": "frameRate",
+                        "required": false,
+                        "reset": "resetFrameRate",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFrameRate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "frameDuration",
+                        "notify": "frameDurationChanged",
+                        "read": "frameDuration",
+                        "required": false,
+                        "reset": "resetFrameDuration",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "loops",
+                        "notify": "loopsChanged",
+                        "read": "loops",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLoops"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "paused",
+                        "notify": "pausedChanged",
+                        "read": "paused",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPaused"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "currentFrame",
+                        "notify": "currentFrameChanged",
+                        "read": "currentFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "finishBehavior",
+                        "notify": "finishBehaviorChanged",
+                        "read": "finishBehavior",
+                        "required": false,
+                        "revision": 527,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FinishBehavior",
+                        "user": false,
+                        "write": "setFinishBehavior"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAnimatedSprite",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "pausedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "runningChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "interpolateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "reverseChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "frameSyncChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "frameCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "frameHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "frameWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "frameXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "frameYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "frameRateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "frameDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "loopsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "currentFrameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "FinishBehavior"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "finishBehaviorChanged",
+                        "returnType": "void",
+                        "revision": 527
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "finished",
+                        "returnType": "void",
+                        "revision": 524
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "start",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "stop",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "restart",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "frames",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "advance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "isCloned": true,
+                        "name": "advance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "pause",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "resume",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "setRunning",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "setPaused",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "setInterpolate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "setReverse",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "setFrameSync",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "setFrameCount",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "setFrameHeight",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "setFrameWidth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "setFrameX",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "setFrameY",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "setFrameRate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "setFrameDuration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 37,
+                        "name": "resetFrameRate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 38,
+                        "name": "resetFrameDuration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "setLoops",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 40,
+                        "name": "setCurrentFrame",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 41,
+                        "name": "createEngine",
+                        "returnType": "void"
+                    },
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+                        "required": false,
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "stored": true,
+                        "type": "QQmlProperty",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickBehavior",
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+                        "access": "public",
+                        "index": 0,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "targetValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "targetPropertyChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlPropertyValueInterceptor"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlFinalizerHook"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbehavior_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BorderImage"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickBorderImage",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TileMode",
+                        "values": [
+                            "Stretch",
+                            "Repeat",
+                            "Round"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "border",
+                        "read": "border",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickScaleGrid*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "horizontalTileMode",
+                        "notify": "horizontalTileModeChanged",
+                        "read": "horizontalTileMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TileMode",
+                        "user": false,
+                        "write": "setHorizontalTileMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "verticalTileMode",
+                        "notify": "verticalTileModeChanged",
+                        "read": "verticalTileMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TileMode",
+                        "user": false,
+                        "write": "setVerticalTileMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "sourceSize",
+                        "notify": "sourceSizeChanged",
+                        "read": "sourceSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickBorderImage",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "horizontalTileModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "verticalTileModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceSizeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "doUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "requestFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "sciRequestFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickImageBase"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickborderimage_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickCanvasContext",
+                "lineNumber": 34,
+                "object": true,
+                "qualifiedClassName": "QQuickCanvasContext",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textureChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Canvas"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCanvasItem",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderTarget",
+                        "values": [
+                            "Image",
+                            "FramebufferObject"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderStrategy",
+                        "values": [
+                            "Immediate",
+                            "Threaded",
+                            "Cooperative"
+                        ]
+                    }
+                ],
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "getContext",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "requestAnimationFrame",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "cancelRequestAnimationFrame",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "requestPaint",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "dirtyRect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "markDirty",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "isCloned": true,
+                        "name": "markDirty",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filename",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "imageSize",
+                                "type": "QSizeF"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "save",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filename",
+                                "type": "QString"
+                            }
+                        ],
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+                        "isCloned": true,
+                        "name": "save",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "toDataURL",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "isCloned": true,
+                        "name": "toDataURL",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "private",
+                        "index": 31,
+                        "name": "delayedCreate",
+                        "returnType": "void"
+                    }
+                ],
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+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "available",
+                        "notify": "availableChanged",
+                        "read": "isAvailable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "contextType",
+                        "notify": "contextTypeChanged",
+                        "read": "contextType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setContextType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "context",
+                        "notify": "contextChanged",
+                        "read": "context",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "canvasSize",
+                        "notify": "canvasSizeChanged",
+                        "read": "canvasSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setCanvasSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "tileSize",
+                        "notify": "tileSizeChanged",
+                        "read": "tileSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setTileSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "canvasWindow",
+                        "notify": "canvasWindowChanged",
+                        "read": "canvasWindow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setCanvasWindow"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "renderTarget",
+                        "notify": "renderTargetChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RenderTarget",
+                        "user": false,
+                        "write": "setRenderTarget"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "renderStrategy",
+                        "notify": "renderStrategyChanged",
+                        "read": "renderStrategy",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RenderStrategy",
+                        "user": false,
+                        "write": "setRenderStrategy"
+                    }
+                ],
+                "qualifiedClassName": "QQuickCanvasItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "region",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "paint",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "painted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "availableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "contextTypeChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                        "index": 4,
+                        "name": "contextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "canvasSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "tileSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "canvasWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "renderTargetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "renderStrategyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "imageLoaded",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "sourceSize",
+                                "type": "QSizeF"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "loadImage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
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+                        "isCloned": true,
+                        "name": "loadImage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "unloadImage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "isImageLoaded",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "isImageLoading",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "isImageError",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "private",
+                        "index": 17,
+                        "name": "sceneGraphInitialized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 18,
+                        "name": "checkAnimationCallbacks",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 19,
+                        "name": "invalidateSceneGraph",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 20,
+                        "name": "schedulePolish",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            },
+            {
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+                "qualifiedClassName": "QQuickContext2DRenderThread",
+                "superClasses": [
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+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorGroup"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1536"
+                    }
+                ],
+                "className": "QQuickColorGroup",
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+                "object": true,
+                "properties": [
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+                        "constant": false,
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+                        "name": "alternateBase",
+                        "notify": "alternateBaseChanged",
+                        "read": "alternateBase",
+                        "required": false,
+                        "reset": "resetAlternateBase",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setAlternateBase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "base",
+                        "notify": "baseChanged",
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+                        "required": false,
+                        "reset": "resetBase",
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+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setBase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "brightText",
+                        "notify": "brightTextChanged",
+                        "read": "brightText",
+                        "required": false,
+                        "reset": "resetBrightText",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setBrightText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "button",
+                        "notify": "buttonChanged",
+                        "read": "button",
+                        "required": false,
+                        "reset": "resetButton",
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+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setButton"
+                    },
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+                        "designable": true,
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+                        "name": "buttonText",
+                        "notify": "buttonTextChanged",
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+                        "required": false,
+                        "reset": "resetButtonText",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setButtonText"
+                    },
+                    {
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+                        "notify": "darkChanged",
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+                        "required": false,
+                        "reset": "resetDark",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setDark"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
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+                        "name": "highlight",
+                        "notify": "highlightChanged",
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+                        "required": false,
+                        "reset": "resetHighlight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setHighlight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "highlightedText",
+                        "notify": "highlightedTextChanged",
+                        "read": "highlightedText",
+                        "required": false,
+                        "reset": "resetHighlightedText",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setHighlightedText"
+                    },
+                    {
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+                        "final": true,
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+                        "required": false,
+                        "reset": "resetLight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setLight"
+                    },
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+                        "name": "link",
+                        "notify": "linkChanged",
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+                        "required": false,
+                        "reset": "resetLink",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setLink"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "linkVisited",
+                        "notify": "linkVisitedChanged",
+                        "read": "linkVisited",
+                        "required": false,
+                        "reset": "resetLinkVisited",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setLinkVisited"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
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+                        "name": "mid",
+                        "notify": "midChanged",
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+                        "required": false,
+                        "reset": "resetMid",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setMid"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "midlight",
+                        "notify": "midlightChanged",
+                        "read": "midlight",
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+                        "stored": true,
+                        "type": "QColor",
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+                        "write": "setMidlight"
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+                        "final": true,
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+                        "reset": "resetShadow",
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+                        "stored": true,
+                        "type": "QColor",
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+                        "write": "setText"
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+                        "stored": true,
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+                    },
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+                        "reset": "resetWindow",
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+                        "stored": true,
+                        "type": "QColor",
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+                        "write": "setWindow"
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+                        "write": "setWindowText"
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+                        "notify": "placeholderTextChanged",
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+                        "reset": "resetPlaceholderText",
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+                        "reset": "resetAccent",
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+                        "user": false,
+                        "write": "setAccent"
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+                    },
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+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "highlightedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "lightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "linkChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "linkVisitedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "midChanged",
+                        "returnType": "void"
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+                    {
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+                        "name": "midlightChanged",
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+                    {
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+                        "returnType": "void"
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+                    },
+                    {
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+                    },
+                    {
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+                    },
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+                        "arguments": [
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+                                "name": "canvasSize",
+                                "type": "QSize"
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+                                "name": "dirtyRect",
+                                "type": "QRect"
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+                                "name": "antialiasing",
+                                "type": "bool"
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+                                "name": "ccb",
+                                "type": "QQuickContext2DCommandBuffer*"
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+                        "name": "markDirtyTexture",
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+                                "name": "item",
+                                "type": "QQuickCanvasItem*"
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+                        "name": "setItem",
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+                                "name": "region",
+                                "type": "QRectF"
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+                        "name": "grabImage",
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+                        "name": "QObject"
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+                ]
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+    },
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+                        "access": "public",
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+                    {
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+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Drag is only available via attached properties."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickDragAttached"
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+                        "isFlag": false,
+                        "name": "DragType",
+                        "values": [
+                            "None",
+                            "Automatic",
+                            "Internal"
+                        ]
+                    },
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Axis",
+                        "values": [
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+                            "YAxis",
+                            "XAndYAxis",
+                            "XandYAxis"
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+                ],
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+                        "index": 0,
+                        "name": "dragStarted",
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+                                "name": "dropAction",
+                                "type": "Qt::DropAction"
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+                        "name": "dragFinished",
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+                        "name": "hotSpotChanged",
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+                        "name": "imageSourceChanged",
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+                    },
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+                        "name": "dragTypeChanged",
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQmlV4FunctionPtr"
+                            }
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+                        "name": "start",
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+                    },
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+                        "arguments": [
+                            {
+                                "type": "QQmlV4FunctionPtr"
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+                        ],
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+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "drag",
+                                "type": "QQuickDragEvent*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "entered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "exited",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "drag",
+                                "type": "QQuickDragEvent*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "positionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "drop",
+                                "type": "QQuickDragEvent*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "dropped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickdroparea_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "KeyEvent"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Should only be used by signal handlers in the Keys attached property"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickKeyEvent",
+                "lineNumber": 39,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "QKeySequence::StandardKey"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "matches",
+                        "returnType": "bool",
+                        "revision": 514
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "key",
+                        "read": "key",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "text",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "modifiers",
+                        "read": "modifiers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "isAutoRepeat",
+                        "read": "isAutoRepeat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "nativeScanCode",
+                        "read": "nativeScanCode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "quint32",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "accepted",
+                        "read": "isAccepted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccepted"
+                    }
+                ],
+                "qualifiedClassName": "QQuickKeyEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MouseEvent"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Should only be used by mouse event signal handlers, for example in MouseArea"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMouseEvent",
+                "lineNumber": 106,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "x",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "y",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "button",
+                        "read": "button",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "buttons",
+                        "read": "buttons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "modifiers",
+                        "read": "modifiers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "revision": 519,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "isClick",
+                        "read": "isClick",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "wasHeld",
+                        "read": "wasHeld",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "accepted",
+                        "read": "isAccepted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccepted"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "flags",
+                        "read": "flags",
+                        "required": false,
+                        "revision": 523,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMouseEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "WheelEvent"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Should only be used by wheel event signal handlers, for example in MouseArea"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickWheelEvent",
+                "lineNumber": 182,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "device",
+                        "read": "pointingDevice",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "const QPointingDevice*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "x",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "y",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "angleDelta",
+                        "read": "angleDelta",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPoint",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "pixelDelta",
+                        "read": "pixelDelta",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPoint",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "phase",
+                        "read": "phase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScrollPhase",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "buttons",
+                        "read": "buttons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "modifiers",
+                        "read": "modifiers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "inverted",
+                        "read": "inverted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "accepted",
+                        "read": "isAccepted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccepted"
+                    }
+                ],
+                "qualifiedClassName": "QQuickWheelEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CloseEvent"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Should only be used by Window's closing signal"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCloseEvent",
+                "lineNumber": 242,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "accepted",
+                        "read": "isAccepted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccepted"
+                    }
+                ],
+                "qualifiedClassName": "QQuickCloseEvent",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickevents_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "flickableData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Flickable"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickFlickable",
+                "enums": [
+                    {
+                        "alias": "BoundsBehaviorFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "BoundsBehavior",
+                        "values": [
+                            "StopAtBounds",
+                            "DragOverBounds",
+                            "OvershootBounds",
+                            "DragAndOvershootBounds"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BoundsMovement",
+                        "values": [
+                            "FollowBoundsBehavior"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FlickableDirection",
+                        "values": [
+                            "AutoFlickDirection",
+                            "HorizontalFlick",
+                            "VerticalFlick",
+                            "HorizontalAndVerticalFlick",
+                            "AutoFlickIfNeeded"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "h",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "center",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 49,
+                        "name": "resizeContent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 50,
+                        "name": "returnToBounds",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "xVelocity",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "yVelocity",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 51,
+                        "name": "flick",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 52,
+                        "name": "cancelFlick",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "contentX",
+                        "notify": "contentXChanged",
+                        "read": "contentX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "contentY",
+                        "notify": "contentYChanged",
+                        "read": "contentY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentY"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "contentItem",
+                        "read": "contentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "topMargin",
+                        "notify": "topMarginChanged",
+                        "read": "topMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "bottomMargin",
+                        "notify": "bottomMarginChanged",
+                        "read": "bottomMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "originY",
+                        "notify": "originYChanged",
+                        "read": "originY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "leftMargin",
+                        "notify": "leftMarginChanged",
+                        "read": "leftMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "rightMargin",
+                        "notify": "rightMarginChanged",
+                        "read": "rightMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "originX",
+                        "notify": "originXChanged",
+                        "read": "originX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "horizontalVelocity",
+                        "notify": "horizontalVelocityChanged",
+                        "read": "horizontalVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "verticalVelocity",
+                        "notify": "verticalVelocityChanged",
+                        "read": "verticalVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "boundsBehavior",
+                        "notify": "boundsBehaviorChanged",
+                        "read": "boundsBehavior",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "BoundsBehavior",
+                        "user": false,
+                        "write": "setBoundsBehavior"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "boundsMovement",
+                        "notify": "boundsMovementChanged",
+                        "read": "boundsMovement",
+                        "required": false,
+                        "revision": 522,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "BoundsMovement",
+                        "user": false,
+                        "write": "setBoundsMovement"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "rebound",
+                        "notify": "reboundChanged",
+                        "read": "rebound",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setRebound"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "maximumFlickVelocity",
+                        "notify": "maximumFlickVelocityChanged",
+                        "read": "maximumFlickVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaximumFlickVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "flickDeceleration",
+                        "notify": "flickDecelerationChanged",
+                        "read": "flickDeceleration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFlickDeceleration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "moving",
+                        "notify": "movingChanged",
+                        "read": "isMoving",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "movingHorizontally",
+                        "notify": "movingHorizontallyChanged",
+                        "read": "isMovingHorizontally",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "movingVertically",
+                        "notify": "movingVerticallyChanged",
+                        "read": "isMovingVertically",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "flicking",
+                        "notify": "flickingChanged",
+                        "read": "isFlicking",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "flickingHorizontally",
+                        "notify": "flickingHorizontallyChanged",
+                        "read": "isFlickingHorizontally",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "flickingVertically",
+                        "notify": "flickingVerticallyChanged",
+                        "read": "isFlickingVertically",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "dragging",
+                        "notify": "draggingChanged",
+                        "read": "isDragging",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "draggingHorizontally",
+                        "notify": "draggingHorizontallyChanged",
+                        "read": "isDraggingHorizontally",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "draggingVertically",
+                        "notify": "draggingVerticallyChanged",
+                        "read": "isDraggingVertically",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "flickableDirection",
+                        "notify": "flickableDirectionChanged",
+                        "read": "flickableDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FlickableDirection",
+                        "user": false,
+                        "write": "setFlickableDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "interactive",
+                        "notify": "interactiveChanged",
+                        "read": "isInteractive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInteractive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "pressDelay",
+                        "notify": "pressDelayChanged",
+                        "read": "pressDelay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPressDelay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "atXEnd",
+                        "notify": "atXEndChanged",
+                        "read": "isAtXEnd",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "atYEnd",
+                        "notify": "atYEndChanged",
+                        "read": "isAtYEnd",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "atXBeginning",
+                        "notify": "atXBeginningChanged",
+                        "read": "isAtXBeginning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "atYBeginning",
+                        "notify": "atYBeginningChanged",
+                        "read": "isAtYBeginning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "visibleArea",
+                        "read": "visibleArea",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickFlickableVisibleArea*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 35,
+                        "name": "pixelAligned",
+                        "notify": "pixelAlignedChanged",
+                        "read": "pixelAligned",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPixelAligned"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 36,
+                        "name": "synchronousDrag",
+                        "notify": "synchronousDragChanged",
+                        "read": "synchronousDrag",
+                        "required": false,
+                        "revision": 524,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSynchronousDrag"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 37,
+                        "name": "horizontalOvershoot",
+                        "notify": "horizontalOvershootChanged",
+                        "read": "horizontalOvershoot",
+                        "required": false,
+                        "revision": 521,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 38,
+                        "name": "verticalOvershoot",
+                        "notify": "verticalOvershootChanged",
+                        "read": "verticalOvershoot",
+                        "required": false,
+                        "revision": 521,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 39,
+                        "name": "flickableData",
+                        "read": "flickableData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 40,
+                        "name": "flickableChildren",
+                        "read": "flickableChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickFlickable",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "contentWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "contentXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "contentYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "topMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "bottomMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "leftMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "rightMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "originYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "originXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "movingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "movingHorizontallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "movingVerticallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "flickingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "flickingHorizontallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "flickingVerticallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "draggingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "draggingHorizontallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "draggingVerticallyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "horizontalVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "verticalVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "isAtBoundaryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "flickableDirectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "interactiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "boundsBehaviorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "boundsMovementChanged",
+                        "returnType": "void",
+                        "revision": 522
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "reboundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "maximumFlickVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "flickDecelerationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "pressDelayChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "movementStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "movementEnded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "name": "flickStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 33,
+                        "name": "flickEnded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "name": "dragStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 35,
+                        "name": "dragEnded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 36,
+                        "name": "pixelAlignedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 37,
+                        "name": "synchronousDragChanged",
+                        "returnType": "void",
+                        "revision": 524
+                    },
+                    {
+                        "access": "public",
+                        "index": 38,
+                        "name": "horizontalOvershootChanged",
+                        "returnType": "void",
+                        "revision": 521
+                    },
+                    {
+                        "access": "public",
+                        "index": 39,
+                        "name": "verticalOvershootChanged",
+                        "returnType": "void",
+                        "revision": 521
+                    },
+                    {
+                        "access": "public",
+                        "index": 40,
+                        "name": "atXEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 41,
+                        "name": "atYEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 42,
+                        "name": "atXBeginningChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 43,
+                        "name": "atYBeginningChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 44,
+                        "name": "movementStarting",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 45,
+                        "name": "movementEnding",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "hMovementEnding",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "vMovementEnding",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 46,
+                        "name": "movementEnding",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 47,
+                        "name": "velocityTimelineCompleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 48,
+                        "name": "timelineCompleted",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickflickable_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickFlickableVisibleArea",
+                "lineNumber": 250,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "xPosition",
+                        "notify": "xPositionChanged",
+                        "read": "xPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "yPosition",
+                        "notify": "yPositionChanged",
+                        "read": "yPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "widthRatio",
+                        "notify": "widthRatioChanged",
+                        "read": "widthRatio",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "heightRatio",
+                        "notify": "heightRatioChanged",
+                        "read": "heightRatio",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickFlickableVisibleArea",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "xPosition",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "xPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "yPosition",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "yPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "widthRatio",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "widthRatioChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "heightRatio",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "heightRatioChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickflickable_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Flipable"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickFlipable",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Side",
+                        "values": [
+                            "Front",
+                            "Back"
+                        ]
+                    }
+                ],
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "front",
+                        "notify": "frontChanged",
+                        "read": "front",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setFront"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "back",
+                        "notify": "backChanged",
+                        "read": "back",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBack"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
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+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "commit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "hide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "a",
+                                "type": "QInputMethod::Action"
+                            },
+                            {
+                                "name": "cursorPosition",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "invokeAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "reset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "show",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "queries",
+                                "type": "Qt::InputMethodQueries"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "update",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickinputmethod_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickTransform",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QQuickTransform",
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 0,
+                        "name": "update",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    },
+                    {
+                        "name": "ParentProperty",
+                        "value": "parent"
+                    },
+                    {
+                        "name": "qt_QmlJSWrapperFactoryMethod",
+                        "value": "_q_createJSWrapper(QQmlV4ExecutionEnginePtr)"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Item"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickItem",
+                "enums": [
+                    {
+                        "alias": "Flag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Flags",
+                        "values": [
+                            "ItemClipsChildrenToShape",
+                            "ItemAcceptsInputMethod",
+                            "ItemIsFocusScope",
+                            "ItemHasContents",
+                            "ItemAcceptsDrops",
+                            "ItemIsViewport",
+                            "ItemObservesViewport"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ItemChange",
+                        "values": [
+                            "ItemChildAddedChange",
+                            "ItemChildRemovedChange",
+                            "ItemSceneChange",
+                            "ItemVisibleHasChanged",
+                            "ItemParentHasChanged",
+                            "ItemOpacityHasChanged",
+                            "ItemActiveFocusHasChanged",
+                            "ItemRotationHasChanged",
+                            "ItemAntialiasingHasChanged",
+                            "ItemDevicePixelRatioHasChanged",
+                            "ItemEnabledHasChanged"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TransformOrigin",
+                        "values": [
+                            "TopLeft",
+                            "Top",
+                            "TopRight",
+                            "Left",
+                            "Center",
+                            "Right",
+                            "BottomLeft",
+                            "Bottom",
+                            "BottomRight"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 62,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "callback",
+                                "type": "QJSValue"
+                            },
+                            {
+                                "name": "targetSize",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "grabToImage",
+                        "returnType": "bool",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "callback",
+                                "type": "QJSValue"
+                            }
+                        ],
+                        "index": 34,
+                        "isCloned": true,
+                        "name": "grabToImage",
+                        "returnType": "bool",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "contains",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "mapFromItem",
+                        "returnType": "QPointF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 37,
+                        "name": "mapFromItem",
+                        "returnType": "QPointF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "mapFromItem",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "width",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "height",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "mapFromItem",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 40,
+                        "name": "mapToItem",
+                        "returnType": "QPointF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 41,
+                        "name": "mapToItem",
+                        "returnType": "QPointF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 42,
+                        "name": "mapToItem",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QQuickItem*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "width",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "height",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 43,
+                        "name": "mapToItem",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 44,
+                        "name": "mapFromGlobal",
+                        "returnType": "QPointF",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 45,
+                        "name": "mapFromGlobal",
+                        "returnType": "QPointF",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 46,
+                        "name": "mapToGlobal",
+                        "returnType": "QPointF",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 47,
+                        "name": "mapToGlobal",
+                        "returnType": "QPointF",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "index": 48,
+                        "name": "forceActiveFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reason",
+                                "type": "Qt::FocusReason"
+                            }
+                        ],
+                        "index": 49,
+                        "name": "forceActiveFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "forward",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 50,
+                        "name": "nextItemInFocusChain",
+                        "returnType": "QQuickItem*",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 51,
+                        "isCloned": true,
+                        "name": "nextItemInFocusChain",
+                        "returnType": "QQuickItem*",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 52,
+                        "name": "childAt",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "index": 53,
+                        "name": "ensurePolished",
+                        "returnType": "void",
+                        "revision": 1539
+                    },
+                    {
+                        "access": "public",
+                        "index": 54,
+                        "name": "dumpItemTree",
+                        "returnType": "void",
+                        "revision": 1539
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": true,
+                        "index": 0,
+                        "name": "parent",
+                        "notify": "parentChanged",
+                        "read": "parentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setParentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 1,
+                        "name": "data",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "data",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 2,
+                        "name": "resources",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "resources",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 3,
+                        "name": "children",
+                        "notify": "childrenChanged",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "children",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
+                        "bindable": "bindableX",
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "x",
+                        "notify": "xChanged",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setX"
+                    },
+                    {
+                        "bindable": "bindableY",
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "y",
+                        "notify": "yChanged",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "z",
+                        "notify": "zChanged",
+                        "read": "z",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setZ"
+                    },
+                    {
+                        "bindable": "bindableWidth",
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "width",
+                        "notify": "widthChanged",
+                        "read": "width",
+                        "required": false,
+                        "reset": "resetWidth",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setWidth"
+                    },
+                    {
+                        "bindable": "bindableHeight",
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "height",
+                        "notify": "heightChanged",
+                        "read": "height",
+                        "required": false,
+                        "reset": "resetHeight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "opacity",
+                        "notify": "opacityChanged",
+                        "read": "opacity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOpacity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "palette",
+                        "notify": "paletteChanged",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "palette",
+                        "required": false,
+                        "reset": "resetPalette",
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPalette*",
+                        "user": false,
+                        "write": "setPalette"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 13,
+                        "name": "visibleChildren",
+                        "notify": "visibleChildrenChanged",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "visibleChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 14,
+                        "name": "states",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "states",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickState>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 15,
+                        "name": "transitions",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "transitions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickTransition>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "state",
+                        "notify": "stateChanged",
+                        "read": "state",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setState"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": true,
+                        "index": 17,
+                        "name": "childrenRect",
+                        "notify": "childrenRectChanged",
+                        "read": "childrenRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": false,
+                        "final": true,
+                        "index": 18,
+                        "name": "anchors",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "anchors",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchors*",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "left",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "left",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "right",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "right",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "horizontalCenter",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "horizontalCenter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "top",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "top",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "bottom",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "bottom",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "verticalCenter",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "verticalCenter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "baseline",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "baseline",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAnchorLine",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "baselineOffset",
+                        "notify": "baselineOffsetChanged",
+                        "read": "baselineOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBaselineOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "clip",
+                        "notify": "clipChanged",
+                        "read": "clip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setClip"
+                    },
+                    {
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+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "focus",
+                        "notify": "focusChanged",
+                        "read": "hasFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFocus"
+                    },
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+                        "designable": true,
+                        "final": true,
+                        "index": 29,
+                        "name": "activeFocus",
+                        "notify": "activeFocusChanged",
+                        "read": "hasActiveFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": true,
+                        "index": 30,
+                        "name": "activeFocusOnTab",
+                        "notify": "activeFocusOnTabChanged",
+                        "read": "activeFocusOnTab",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setActiveFocusOnTab"
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "focusPolicy",
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+                        "read": "focusPolicy",
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+                        "scriptable": true,
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+                        "user": false,
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+                    },
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+                        "designable": true,
+                        "final": false,
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+                        "notify": "rotationChanged",
+                        "read": "rotation",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRotation"
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "scale",
+                        "notify": "scaleChanged",
+                        "read": "scale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "transformOrigin",
+                        "notify": "transformOriginChanged",
+                        "read": "transformOrigin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TransformOrigin",
+                        "user": false,
+                        "write": "setTransformOrigin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 35,
+                        "name": "transformOriginPoint",
+                        "read": "transformOriginPoint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
+                    {
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+                        "designable": false,
+                        "final": true,
+                        "index": 36,
+                        "name": "transform",
+                        "read": "transform",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickTransform>",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 37,
+                        "name": "smooth",
+                        "notify": "smoothChanged",
+                        "read": "smooth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSmooth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 38,
+                        "name": "antialiasing",
+                        "notify": "antialiasingChanged",
+                        "read": "antialiasing",
+                        "required": false,
+                        "reset": "resetAntialiasing",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAntialiasing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 39,
+                        "name": "implicitWidth",
+                        "notify": "implicitWidthChanged",
+                        "read": "implicitWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setImplicitWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 40,
+                        "name": "implicitHeight",
+                        "notify": "implicitHeightChanged",
+                        "read": "implicitHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setImplicitHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 41,
+                        "name": "containmentMask",
+                        "notify": "containmentMaskChanged",
+                        "read": "containmentMask",
+                        "required": false,
+                        "revision": 523,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false,
+                        "write": "setContainmentMask"
+                    },
+                    {
+                        "constant": true,
+                        "designable": false,
+                        "final": true,
+                        "index": 42,
+                        "name": "layer",
+                        "privateClass": "QQuickItem::d_func()",
+                        "read": "layer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItemLayer*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "childrenRectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "baselineOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "focusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "activeFocusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "Qt::FocusPolicy"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "focusPolicyChanged",
+                        "returnType": "void",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "activeFocusOnTabChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "parentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "TransformOrigin"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "transformOriginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "smoothChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "antialiasingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "clipChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "window",
+                                "type": "QQuickWindow*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "windowChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "childrenChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "opacityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "visibleChildrenChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "rotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "scaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "xChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "yChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "widthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "heightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "zChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "implicitWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "implicitHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "containmentMaskChanged",
+                        "returnType": "void",
+                        "revision": 523
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "paletteChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "paletteCreated",
+                        "returnType": "void",
+                        "revision": 1536
+                    }
+                ],
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+                        "access": "public",
+                        "index": 30,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "_q_resourceObjectDeleted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QQmlV4ExecutionEnginePtr"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "_q_createJSWrapper",
+                        "returnType": "quint64"
+                    }
+                ],
+                "superClasses": [
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+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitem.h",
+        "outputRevision": 68
+    },
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+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
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+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickItemLayer",
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+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "textureSize",
+                        "notify": "sizeChanged",
+                        "read": "size",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "sourceRect",
+                        "notify": "sourceRectChanged",
+                        "read": "sourceRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setSourceRect"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "mipmap",
+                        "notify": "mipmapChanged",
+                        "read": "mipmap",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMipmap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "smooth",
+                        "notify": "smoothChanged",
+                        "read": "smooth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSmooth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "live",
+                        "notify": "liveChanged",
+                        "read": "live",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setLive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "wrapMode",
+                        "notify": "wrapModeChanged",
+                        "read": "wrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickShaderEffectSource::WrapMode",
+                        "user": false,
+                        "write": "setWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "format",
+                        "notify": "formatChanged",
+                        "read": "format",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickShaderEffectSource::Format",
+                        "user": false,
+                        "write": "setFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "samplerName",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QByteArray",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "effect",
+                        "notify": "effectChanged",
+                        "read": "effect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setEffect"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "textureMirroring",
+                        "notify": "textureMirroringChanged",
+                        "read": "textureMirroring",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickShaderEffectSource::TextureMirroring",
+                        "user": false,
+                        "write": "setTextureMirroring"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "samples",
+                        "notify": "samplesChanged",
+                        "read": "samples",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSamples"
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemLayer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "sizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mipmap",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "mipmapChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QQuickShaderEffectSource::WrapMode"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "wrapModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "effectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "smooth",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "smoothChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "live",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "liveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "format",
+                                "type": "QQuickShaderEffectSource::Format"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "formatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sourceRect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "sourceRectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mirroring",
+                                "type": "QQuickShaderEffectSource::TextureMirroring"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "textureMirroringChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "count",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "samplesChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickItemChangeListener"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "KeyNavigation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "KeyNavigation is only available via attached properties."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickKeyNavigationAttached"
+                    }
+                ],
+                "className": "QQuickKeyNavigationAttached",
+                "enums": [
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+                        "isFlag": false,
+                        "name": "Priority",
+                        "values": [
+                            "BeforeItem",
+                            "AfterItem"
+                        ]
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+                "object": true,
+                "properties": [
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+                        "designable": true,
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+                        "name": "left",
+                        "notify": "leftChanged",
+                        "read": "left",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setLeft"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "right",
+                        "notify": "rightChanged",
+                        "read": "right",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setRight"
+                    },
+                    {
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+                        "designable": true,
+                        "final": true,
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+                        "name": "up",
+                        "notify": "upChanged",
+                        "read": "up",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setUp"
+                    },
+                    {
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+                        "designable": true,
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+                        "notify": "downChanged",
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+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setDown"
+                    },
+                    {
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+                        "designable": true,
+                        "final": true,
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+                        "notify": "tabChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTab"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "backtab",
+                        "notify": "backtabChanged",
+                        "read": "backtab",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBacktab"
+                    },
+                    {
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+                        "designable": true,
+                        "final": true,
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+                        "name": "priority",
+                        "notify": "priorityChanged",
+                        "read": "priority",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Priority",
+                        "user": false,
+                        "write": "setPriority"
+                    }
+                ],
+                "qualifiedClassName": "QQuickKeyNavigationAttached",
+                "signals": [
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+                        "access": "public",
+                        "index": 0,
+                        "name": "leftChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "upChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "downChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "tabChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "backtabChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "priorityChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickItemKeyFilter"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LayoutMirroring"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "LayoutMirroring is only available via attached properties."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickLayoutMirroringAttached"
+                    }
+                ],
+                "className": "QQuickLayoutMirroringAttached",
+                "lineNumber": 824,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "reset": "resetEnabled",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "childrenInherit",
+                        "notify": "childrenInheritChanged",
+                        "read": "childrenInherit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChildrenInherit"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLayoutMirroringAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "childrenInheritChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "EnterKey"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "EnterKey is only available via attached properties"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "518"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickEnterKeyAttached"
+                    }
+                ],
+                "className": "QQuickEnterKeyAttached",
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "type",
+                        "notify": "typeChanged",
+                        "read": "type",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::EnterKeyType",
+                        "user": false,
+                        "write": "setType"
+                    }
+                ],
+                "qualifiedClassName": "QQuickEnterKeyAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "typeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Keys"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Keys is only available via attached properties"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickKeysAttached"
+                    }
+                ],
+                "className": "QQuickKeysAttached",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Priority",
+                        "values": [
+                            "BeforeItem",
+                            "AfterItem"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
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+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "forwardTo",
+                        "read": "forwardTo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "priority",
+                        "notify": "priorityChanged",
+                        "read": "priority",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Priority",
+                        "user": false,
+                        "write": "setPriority"
+                    }
+                ],
+                "qualifiedClassName": "QQuickKeysAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "priorityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "released",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "shortcutOverride",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "digit0Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "digit1Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "digit2Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "digit3Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "digit4Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "digit5Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "digit6Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "digit7Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "digit8Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "digit9Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "leftPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "rightPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "upPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
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+                        "name": "downPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "tabPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "backtabPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "asteriskPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "numberSignPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "escapePressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "returnPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "enterPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "deletePressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "spacePressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "backPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "cancelPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "selectPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "yesPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "noPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "context1Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "context2Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "context3Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "context4Pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 37,
+                        "name": "callPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "hangupPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "flipPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 40,
+                        "name": "menuPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 41,
+                        "name": "volumeUpPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "event",
+                                "type": "QQuickKeyEvent*"
+                            }
+                        ],
+                        "index": 42,
+                        "name": "volumeDownPressed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickItemKeyFilter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
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+                    {
+                        "name": "QML.Element",
+                        "value": "ParentAnimation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickParentAnimation",
+                "lineNumber": 25,
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+                        "designable": true,
+                        "final": false,
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+                        "name": "target",
+                        "notify": "targetChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTargetObject"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "newParent",
+                        "notify": "newParentChanged",
+                        "read": "newParent",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setNewParent"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "via",
+                        "notify": "viaChanged",
+                        "read": "via",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setVia"
+                    }
+                ],
+                "qualifiedClassName": "QQuickParentAnimation",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "newParentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "viaChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAnimationGroup"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AnchorAnimation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAnchorAnimation",
+                "lineNumber": 61,
+                "object": true,
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "targets",
+                        "read": "targets",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "duration",
+                        "notify": "durationChanged",
+                        "read": "duration",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDuration"
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "easing",
+                        "notify": "easingChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QEasingCurve",
+                        "user": false,
+                        "write": "setEasing"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAnchorAnimation",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "durationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QEasingCurve"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "easingChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractAnimation"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "PathAnimation"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPathAnimation",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Orientation",
+                        "values": [
+                            "Fixed",
+                            "RightFirst",
+                            "LeftFirst",
+                            "BottomFirst",
+                            "TopFirst"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "duration",
+                        "notify": "durationChanged",
+                        "read": "duration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "easing",
+                        "notify": "easingChanged",
+                        "read": "easing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QEasingCurve",
+                        "user": false,
+                        "write": "setEasing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "path",
+                        "notify": "pathChanged",
+                        "read": "path",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPath*",
+                        "user": false,
+                        "write": "setPath"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "target",
+                        "notify": "targetChanged",
+                        "read": "target",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTargetObject"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "orientation",
+                        "notify": "orientationChanged",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "anchorPoint",
+                        "notify": "anchorPointChanged",
+                        "read": "anchorPoint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false,
+                        "write": "setAnchorPoint"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "orientationEntryDuration",
+                        "notify": "orientationEntryDurationChanged",
+                        "read": "orientationEntryDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setOrientationEntryDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "orientationExitDuration",
+                        "notify": "orientationExitDurationChanged",
+                        "read": "orientationExitDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setOrientationExitDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "endRotation",
+                        "notify": "endRotationChanged",
+                        "read": "endRotation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setEndRotation"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPathAnimation",
+                "signals": [
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "durationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QEasingCurve"
+                            }
+                        ],
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+                        "name": "easingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "pathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "Orientation"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "orientationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "anchorPointChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "orientationEntryDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "orientationExitDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "endRotationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractAnimation"
+                    }
+                ]
+            }
+        ],
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+    },
+    {
+        "classes": [
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+                "classInfos": [
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+                        "value": "anonymous"
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+                        "name": "QML.AddedInVersion",
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+                    }
+                ],
+                "className": "QQuickItemGrabResult",
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fileName",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "saveToFile",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fileName",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "saveToFile",
+                        "returnType": "bool",
+                        "revision": 1538
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "image",
+                        "read": "image",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QImage",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "url",
+                        "read": "url",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemGrabResult",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "ready",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "setup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "render",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitemgrabresult.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QInputDevice"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "InputDevice"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1536"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "InputDevice is only available via read-only properties."
+                    }
+                ],
+                "className": "QInputDeviceForeign",
+                "gadget": true,
+                "lineNumber": 31,
+                "qualifiedClassName": "QInputDeviceForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QPointingDevice"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "PointerDevice"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "524"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "PointerDevice is only available via read-only properties."
+                    }
+                ],
+                "className": "QPointingDeviceForeign",
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+                "qualifiedClassName": "QPointingDeviceForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QPointingDeviceUniqueId"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "pointingDeviceUniqueId"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "521"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "pointingDeviceUniqueId cannot be created in QML."
+                    }
+                ],
+                "className": "QPointingDeviceUniqueIdForeign",
+                "gadget": true,
+                "lineNumber": 49,
+                "qualifiedClassName": "QPointingDeviceUniqueIdForeign"
+            }
+        ],
+        "inputFile": "qquickitemsmodule_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ItemView"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "ItemView is an abstract base class."
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    }
+                ],
+                "className": "QQuickItemView",
+                "enums": [
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LayoutDirection",
+                        "values": [
+                            "LeftToRight",
+                            "RightToLeft",
+                            "VerticalTopToBottom",
+                            "VerticalBottomToTop"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VerticalLayoutDirection",
+                        "values": [
+                            "TopToBottom",
+                            "BottomToTop"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HighlightRangeMode",
+                        "values": [
+                            "NoHighlightRange",
+                            "ApplyRange",
+                            "StrictlyEnforceRange"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PositionMode",
+                        "values": [
+                            "Beginning",
+                            "Center",
+                            "End",
+                            "Visible",
+                            "Contain",
+                            "SnapPosition"
+                        ]
+                    }
+                ],
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 42,
+                        "name": "positionViewAtIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "indexAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 44,
+                        "name": "itemAt",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 45,
+                        "name": "itemAtIndex",
+                        "returnType": "QQuickItem*",
+                        "revision": 525
+                    },
+                    {
+                        "access": "public",
+                        "index": 46,
+                        "name": "positionViewAtBeginning",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 47,
+                        "name": "positionViewAtEnd",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 48,
+                        "name": "forceLayout",
+                        "returnType": "void",
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+                    }
+                ],
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+                        "designable": true,
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+                        "name": "model",
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+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "count",
+                        "notify": "countChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "currentItem",
+                        "notify": "currentItemChanged",
+                        "read": "currentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "keyNavigationWraps",
+                        "notify": "keyNavigationWrapsChanged",
+                        "read": "isWrapEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWrapEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "keyNavigationEnabled",
+                        "notify": "keyNavigationEnabledChanged",
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+                        "required": false,
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setKeyNavigationEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "cacheBuffer",
+                        "notify": "cacheBufferChanged",
+                        "read": "cacheBuffer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCacheBuffer"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "displayMarginBeginning",
+                        "notify": "displayMarginBeginningChanged",
+                        "read": "displayMarginBeginning",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDisplayMarginBeginning"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "displayMarginEnd",
+                        "notify": "displayMarginEndChanged",
+                        "read": "displayMarginEnd",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDisplayMarginEnd"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "layoutDirection",
+                        "notify": "layoutDirectionChanged",
+                        "read": "layoutDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false,
+                        "write": "setLayoutDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "effectiveLayoutDirection",
+                        "notify": "effectiveLayoutDirectionChanged",
+                        "read": "effectiveLayoutDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "verticalLayoutDirection",
+                        "notify": "verticalLayoutDirectionChanged",
+                        "read": "verticalLayoutDirection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VerticalLayoutDirection",
+                        "user": false,
+                        "write": "setVerticalLayoutDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "header",
+                        "notify": "headerChanged",
+                        "read": "header",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setHeader"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "headerItem",
+                        "notify": "headerItemChanged",
+                        "read": "headerItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "footer",
+                        "notify": "footerChanged",
+                        "read": "footer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setFooter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "footerItem",
+                        "notify": "footerItemChanged",
+                        "read": "footerItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "populate",
+                        "notify": "populateTransitionChanged",
+                        "read": "populateTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setPopulateTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "add",
+                        "notify": "addTransitionChanged",
+                        "read": "addTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setAddTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "addDisplaced",
+                        "notify": "addDisplacedTransitionChanged",
+                        "read": "addDisplacedTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setAddDisplacedTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "move",
+                        "notify": "moveTransitionChanged",
+                        "read": "moveTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setMoveTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "moveDisplaced",
+                        "notify": "moveDisplacedTransitionChanged",
+                        "read": "moveDisplacedTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setMoveDisplacedTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "remove",
+                        "notify": "removeTransitionChanged",
+                        "read": "removeTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setRemoveTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "removeDisplaced",
+                        "notify": "removeDisplacedTransitionChanged",
+                        "read": "removeDisplacedTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setRemoveDisplacedTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "displaced",
+                        "notify": "displacedTransitionChanged",
+                        "read": "displacedTransition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setDisplacedTransition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "highlight",
+                        "notify": "highlightChanged",
+                        "read": "highlight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setHighlight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "highlightItem",
+                        "notify": "highlightItemChanged",
+                        "read": "highlightItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "highlightFollowsCurrentItem",
+                        "notify": "highlightFollowsCurrentItemChanged",
+                        "read": "highlightFollowsCurrentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlightFollowsCurrentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "highlightRangeMode",
+                        "notify": "highlightRangeModeChanged",
+                        "read": "highlightRangeMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HighlightRangeMode",
+                        "user": false,
+                        "write": "setHighlightRangeMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "preferredHighlightBegin",
+                        "notify": "preferredHighlightBeginChanged",
+                        "read": "preferredHighlightBegin",
+                        "required": false,
+                        "reset": "resetPreferredHighlightBegin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPreferredHighlightBegin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "preferredHighlightEnd",
+                        "notify": "preferredHighlightEndChanged",
+                        "read": "preferredHighlightEnd",
+                        "required": false,
+                        "reset": "resetPreferredHighlightEnd",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPreferredHighlightEnd"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "highlightMoveDuration",
+                        "notify": "highlightMoveDurationChanged",
+                        "read": "highlightMoveDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHighlightMoveDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "reuseItems",
+                        "notify": "reuseItemsChanged",
+                        "read": "reuseItems",
+                        "required": false,
+                        "revision": 527,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReuseItems"
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "keyNavigationWrapsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "keyNavigationEnabledChanged",
+                        "returnType": "void",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "cacheBufferChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "displayMarginBeginningChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "displayMarginEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "layoutDirectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "effectiveLayoutDirectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "verticalLayoutDirectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "headerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "footerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "headerItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "footerItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "populateTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "addTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "addDisplacedTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "moveTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "moveDisplacedTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "removeTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "removeDisplacedTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "displacedTransitionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "highlightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "highlightItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "highlightFollowsCurrentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "highlightRangeModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "preferredHighlightBeginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "preferredHighlightEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "highlightMoveDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "name": "reuseItemsChanged",
+                        "returnType": "void",
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+                    }
+                ],
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+                        "access": "protected",
+                        "index": 33,
+                        "name": "destroyRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "createdItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "initItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "changeSet",
+                                "type": "QQmlChangeSet"
+                            },
+                            {
+                                "name": "reset",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "modelUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 37,
+                        "name": "destroyingItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "modelIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "onItemPooled",
+                        "returnType": "void",
+                        "revision": 527
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "modelIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "onItemReused",
+                        "returnType": "void",
+                        "revision": 527
+                    },
+                    {
+                        "access": "protected",
+                        "index": 40,
+                        "name": "animStopped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 41,
+                        "name": "trackedPositionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickFlickable"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickItemViewAttached",
+                "lineNumber": 286,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "isCurrentItem",
+                        "notify": "currentItemChanged",
+                        "read": "isCurrentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "delayRemove",
+                        "notify": "delayRemoveChanged",
+                        "read": "delayRemove",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDelayRemove"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "section",
+                        "notify": "sectionChanged",
+                        "read": "section",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "previousSection",
+                        "notify": "prevSectionChanged",
+                        "read": "prevSection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "nextSection",
+                        "notify": "nextSectionChanged",
+                        "read": "nextSection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemViewAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "viewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "delayRemoveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "add",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "remove",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "sectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "prevSectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "nextSectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "pooled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "reused",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitemview_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ViewTransition"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "ViewTransition is only available via attached properties."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickViewTransitionAttached"
+                    }
+                ],
+                "className": "QQuickViewTransitionAttached",
+                "lineNumber": 153,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
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+                        "type": "int",
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+                    },
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+                        "user": false
+                    },
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+                        "designable": true,
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+                        "name": "destination",
+                        "notify": "destinationChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "name": "targetIndexes",
+                        "notify": "targetIndexesChanged",
+                        "read": "targetIndexes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<int>",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": true,
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+                        "name": "targetItems",
+                        "notify": "targetItemsChanged",
+                        "read": "targetItems",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickViewTransitionAttached",
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+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "destinationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "targetIndexesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "targetItemsChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
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+                        "name": "QML.Element",
+                        "value": "ViewSection"
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+                "className": "QQuickViewSection",
+                "enums": [
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SectionCriteria",
+                        "values": [
+                            "FullString",
+                            "FirstCharacter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LabelPositioning",
+                        "values": [
+                            "InlineLabels",
+                            "CurrentLabelAtStart",
+                            "NextLabelAtEnd"
+                        ]
+                    }
+                ],
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+                        "designable": true,
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+                        "notify": "propertyChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setProperty"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "criteria",
+                        "notify": "criteriaChanged",
+                        "read": "criteria",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SectionCriteria",
+                        "user": false,
+                        "write": "setCriteria"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "labelPositioning",
+                        "notify": "labelPositioningChanged",
+                        "read": "labelPositioning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLabelPositioning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickViewSection",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sectionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "propertyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "criteriaChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "labelPositioningChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ListView"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickListViewAttached"
+                    }
+                ],
+                "className": "QQuickListView",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Orientation",
+                        "values": [
+                            "Horizontal",
+                            "Vertical"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SnapMode",
+                        "values": [
+                            "NoSnap",
+                            "SnapToItem",
+                            "SnapOneItem"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HeaderPositioning",
+                        "values": [
+                            "InlineHeader",
+                            "OverlayHeader",
+                            "PullBackHeader"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FooterPositioning",
+                        "values": [
+                            "InlineFooter",
+                            "OverlayFooter",
+                            "PullBackFooter"
+                        ]
+                    }
+                ],
+                "lineNumber": 80,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "highlightMoveVelocity",
+                        "notify": "highlightMoveVelocityChanged",
+                        "read": "highlightMoveVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHighlightMoveVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "highlightResizeVelocity",
+                        "notify": "highlightResizeVelocityChanged",
+                        "read": "highlightResizeVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHighlightResizeVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "highlightResizeDuration",
+                        "notify": "highlightResizeDurationChanged",
+                        "read": "highlightResizeDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHighlightResizeDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "spacing",
+                        "notify": "spacingChanged",
+                        "read": "spacing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSpacing"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "orientation",
+                        "notify": "orientationChanged",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
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+                        "name": "section",
+                        "read": "sectionCriteria",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickViewSection*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "currentSection",
+                        "notify": "currentSectionChanged",
+                        "read": "currentSection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "snapMode",
+                        "notify": "snapModeChanged",
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+                        "required": false,
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+                        "stored": true,
+                        "type": "SnapMode",
+                        "user": false,
+                        "write": "setSnapMode"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "headerPositioning",
+                        "notify": "headerPositioningChanged",
+                        "read": "headerPositioning",
+                        "required": false,
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+                        "scriptable": true,
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+                        "type": "HeaderPositioning",
+                        "user": false,
+                        "write": "setHeaderPositioning"
+                    },
+                    {
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+                        "final": false,
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+                        "name": "footerPositioning",
+                        "notify": "footerPositioningChanged",
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+                        "scriptable": true,
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+                        "write": "setFooterPositioning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickListView",
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+                        "name": "spacingChanged",
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+                        "name": "orientationChanged",
+                        "returnType": "void"
+                    },
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+                        "name": "currentSectionChanged",
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+                    },
+                    {
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+                        "name": "highlightMoveVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "highlightResizeVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "highlightResizeDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "snapModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "headerPositioningChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
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+                        "name": "footerPositioningChanged",
+                        "returnType": "void",
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+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "incrementCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "decrementCurrentIndex",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItemView"
+                    }
+                ]
+            },
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+                "properties": [
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+                        "name": "view",
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+                        "type": "QQuickListView*",
+                        "user": false
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QQuickItemViewAttached"
+                    }
+                ]
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+        "outputRevision": 68
+    },
+    {
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+                    {
+                        "name": "QML.Element",
+                        "value": "Loader"
+                    },
+                    {
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+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading",
+                            "Error"
+                        ]
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+                "methods": [
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "initialProperties",
+                                "type": "QJSValue"
+                            }
+                        ],
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+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QUrl"
+                            }
+                        ],
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+                        "name": "setSource",
+                        "returnType": "void"
+                    }
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setActive"
+                    },
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+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSourceWithoutResolve"
+                    },
+                    {
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+                        "final": false,
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+                        "name": "sourceComponent",
+                        "notify": "sourceComponentChanged",
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+                        "reset": "resetSourceComponent",
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+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setSourceComponent"
+                    },
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+                    },
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+                        "name": "progress",
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+                        "type": "qreal",
+                        "user": false
+                    },
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+                        "name": "asynchronous",
+                        "notify": "asynchronousChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAsynchronous"
+                    }
+                ],
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+                        "name": "itemChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "activeChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "sourceComponentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "progressChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "loaded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "asynchronousChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_sourceLoaded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_updateSize",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickImplicitSizeItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickloader_p.h",
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+    },
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+                        "name": "QML.Element",
+                        "value": "MouseArea"
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+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
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+                ],
+                "className": "QQuickMouseArea",
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+                "object": true,
+                "properties": [
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+                        "designable": true,
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+                        "name": "mouseX",
+                        "notify": "mouseXChanged",
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+                        "stored": true,
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+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "mouseY",
+                        "notify": "mouseYChanged",
+                        "read": "mouseY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "containsMouse",
+                        "notify": "hoveredChanged",
+                        "read": "hovered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
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+                        "stored": true,
+                        "type": "bool",
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+                    },
+                    {
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+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "scrollGestureEnabled",
+                        "notify": "scrollGestureEnabledChanged",
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+                        "required": false,
+                        "scriptable": true,
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+                        "reset": "unsetCursor",
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+                        "stored": true,
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+                        "user": false,
+                        "write": "setCursorShape"
+                    },
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+                        "designable": true,
+                        "final": false,
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+                        "scriptable": true,
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+                    },
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+                        "scriptable": true,
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+                        "type": "int",
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+                ],
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+                        "access": "public",
+                        "index": 0,
+                        "name": "hoveredChanged",
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+                    },
+                    {
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+                    },
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+                        "name": "enabledChanged",
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+                    },
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+                    },
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+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "hoverEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "cursorShapeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "positionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "mouseXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
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+                        "name": "mouseYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "preventStealingChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
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+                        "name": "pressed",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
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+                        "name": "pressAndHold",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
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+                        "name": "released",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
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+                        "name": "clicked",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mouse",
+                                "type": "QQuickMouseEvent*"
+                            }
+                        ],
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+                        "name": "doubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "wheel",
+                                "type": "QQuickWheelEvent*"
+                            }
+                        ],
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+                        "name": "wheel",
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+                    },
+                    {
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+                        "name": "entered",
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+                    {
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+                    {
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+                        "name": "QQuickItem"
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+                    }
+                ],
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+                        "name": "centroidChanged",
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+                ],
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+                        "name": "QQuickPointerDeviceHandler"
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+                ]
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+        ],
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+                    },
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+                    },
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+                    {
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+                    {
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+                    {
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+                        "value": "GestureEvent is only available in the context of handling the gestureStarted signal from MultiPointTouchArea."
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+                ],
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+                ],
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+                    },
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+                    },
+                    {
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+                        "name": "startYChanged",
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+                    },
+                    {
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+                    },
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+                        "name": "scaleChanged",
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+                ],
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+                        "name": "processPath",
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+                    {
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+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            },
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+                        "value": "PathText"
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+                    },
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+                    },
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+                        "read": "text",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
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+                        "notify": "fontChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    }
+                ],
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+                        "name": "xChanged",
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+                    {
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+                        "name": "yChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "name": "invalidate",
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+                    {
+                        "access": "public",
+                        "name": "QQuickPathElement"
+                    }
+                ]
+            }
+        ],
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+    {
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+                "classInfos": [
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+                        "name": "QML.Element",
+                        "value": "PathInterpolator"
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+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
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+                "object": true,
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+                        "designable": true,
+                        "final": false,
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+                        "name": "path",
+                        "notify": "pathChanged",
+                        "read": "path",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPath*",
+                        "user": false,
+                        "write": "setPath"
+                    },
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+                        "name": "x",
+                        "notify": "xChanged",
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+                        "type": "qreal",
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+                    }
+                ],
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+                        "index": 0,
+                        "name": "pathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "progressChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "xChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                    },
+                    {
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+                        "index": 4,
+                        "name": "angleChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "name": "_q_pathUpdated",
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+                ],
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+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+    },
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+                        "name": "QML.Element",
+                        "value": "PathView"
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+                        "name": "QML.AddedInVersion",
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+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickPathViewAttached"
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+                        "name": "HighlightRangeMode",
+                        "values": [
+                            "NoHighlightRange",
+                            "ApplyRange",
+                            "StrictlyEnforceRange"
+                        ]
+                    },
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+                        "name": "SnapMode",
+                        "values": [
+                            "NoSnap",
+                            "SnapToItem",
+                            "SnapOneItem"
+                        ]
+                    },
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "MovementDirection",
+                        "values": [
+                            "Shortest",
+                            "Negative",
+                            "Positive"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PositionMode",
+                        "values": [
+                            "Beginning",
+                            "Center",
+                            "End",
+                            "Contain",
+                            "SnapPosition"
+                        ]
+                    }
+                ],
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+                "methods": [
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "positionViewAtIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
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+                        "name": "indexAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
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+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
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+                            }
+                        ],
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+                        "name": "itemAt",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 44,
+                        "name": "itemAtIndex",
+                        "returnType": "QQuickItem*",
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+                    }
+                ],
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+                "properties": [
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+                        "designable": true,
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+                        "name": "model",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "path",
+                        "notify": "pathChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPath*",
+                        "user": false,
+                        "write": "setPath"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "currentItem",
+                        "notify": "currentItemChanged",
+                        "read": "currentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
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+                        "notify": "offsetChanged",
+                        "read": "offset",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOffset"
+                    },
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+                        "name": "highlight",
+                        "notify": "highlightChanged",
+                        "read": "highlight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setHighlight"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "highlightItem",
+                        "notify": "highlightItemChanged",
+                        "read": "highlightItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "preferredHighlightBegin",
+                        "notify": "preferredHighlightBeginChanged",
+                        "read": "preferredHighlightBegin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPreferredHighlightBegin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "preferredHighlightEnd",
+                        "notify": "preferredHighlightEndChanged",
+                        "read": "preferredHighlightEnd",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPreferredHighlightEnd"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "highlightRangeMode",
+                        "notify": "highlightRangeModeChanged",
+                        "read": "highlightRangeMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HighlightRangeMode",
+                        "user": false,
+                        "write": "setHighlightRangeMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "highlightMoveDuration",
+                        "notify": "highlightMoveDurationChanged",
+                        "read": "highlightMoveDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHighlightMoveDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "dragMargin",
+                        "notify": "dragMarginChanged",
+                        "read": "dragMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setDragMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "maximumFlickVelocity",
+                        "notify": "maximumFlickVelocityChanged",
+                        "read": "maximumFlickVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaximumFlickVelocity"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "flickDeceleration",
+                        "notify": "flickDecelerationChanged",
+                        "read": "flickDeceleration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFlickDeceleration"
+                    },
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+                        "designable": true,
+                        "final": false,
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+                        "notify": "interactiveChanged",
+                        "read": "isInteractive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInteractive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "moving",
+                        "notify": "movingChanged",
+                        "read": "isMoving",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "flicking",
+                        "notify": "flickingChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "dragging",
+                        "notify": "draggingChanged",
+                        "read": "isDragging",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
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+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "pathItemCount",
+                        "notify": "pathItemCountChanged",
+                        "read": "pathItemCount",
+                        "required": false,
+                        "reset": "resetPathItemCount",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPathItemCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "snapMode",
+                        "notify": "snapModeChanged",
+                        "read": "snapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SnapMode",
+                        "user": false,
+                        "write": "setSnapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "movementDirection",
+                        "notify": "movementDirectionChanged",
+                        "read": "movementDirection",
+                        "required": false,
+                        "revision": 519,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "MovementDirection",
+                        "user": false,
+                        "write": "setMovementDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "cacheItemCount",
+                        "notify": "cacheItemCountChanged",
+                        "read": "cacheItemCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCacheItemCount"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPathView",
+                "signals": [
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+                        "access": "public",
+                        "index": 0,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "offsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "pathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "preferredHighlightBeginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "preferredHighlightEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "highlightRangeModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "dragMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "snapPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "pathItemCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "maximumFlickVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "flickDecelerationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "interactiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "movingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "flickingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "draggingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "highlightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "highlightItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "highlightMoveDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "movementStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "movementEnded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "movementDirectionChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "flickStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "flickEnded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "dragStarted",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "dragEnded",
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+                    },
+                    {
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+                        "name": "snapModeChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "cacheItemCountChanged",
+                        "returnType": "void"
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+                ],
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+                        "index": 31,
+                        "name": "incrementCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "name": "decrementCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 33,
+                        "name": "refill",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 34,
+                        "name": "ticked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 35,
+                        "name": "movementEnding",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "changeSet",
+                                "type": "QQmlChangeSet"
+                            },
+                            {
+                                "name": "reset",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "modelUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 37,
+                        "name": "createdItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "initItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "destroyingItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 40,
+                        "name": "pathUpdated",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
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+                "object": true,
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+                        "designable": true,
+                        "final": true,
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+                        "name": "view",
+                        "read": "view",
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+                        "scriptable": true,
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+                        "user": false
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+                        "designable": true,
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+                        "index": 1,
+                        "name": "isCurrentItem",
+                        "notify": "currentItemChanged",
+                        "read": "isCurrentItem",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "onPath",
+                        "notify": "pathChanged",
+                        "read": "isOnPath",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickPathViewAttached",
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+                        "index": 0,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
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+                        "access": "public",
+                        "index": 1,
+                        "name": "pathChanged",
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+                ],
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+                    {
+                        "access": "public",
+                        "name": "QObject"
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+                ]
+            }
+        ],
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+    },
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+                        "name": "QML.Element",
+                        "value": "Pinch"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPinch",
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Axis",
+                        "values": [
+                            "NoDrag",
+                            "XAxis",
+                            "YAxis",
+                            "XAndYAxis",
+                            "XandYAxis"
+                        ]
+                    }
+                ],
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+                "object": true,
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+                        "name": "target",
+                        "notify": "targetChanged",
+                        "read": "target",
+                        "required": false,
+                        "reset": "resetTarget",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTarget"
+                    },
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+                        "designable": true,
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+                        "notify": "minimumScaleChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
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+                        "scriptable": true,
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+                        "type": "bool",
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+                    {
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+                    },
+                    {
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+                        "name": "dragAxisChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "minimumXChanged",
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+                    {
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+                    {
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+                            {
+                                "name": "pinch",
+                                "type": "QQuickPinchEvent*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "pinchUpdated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pinch",
+                                "type": "QQuickPinchEvent*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "pinchFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pinch",
+                                "type": "QQuickPinchEvent*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "smartZoom",
+                        "returnType": "void",
+                        "revision": 517
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpincharea_p.h",
+        "outputRevision": 68
+    },
+    {
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+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "PinchHandler"
+                    },
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+                        "name": "QML.AddedInVersion",
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+                    },
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+                    },
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+                        "name": "xAxis",
+                        "read": "xAxis",
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+                        "scriptable": true,
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+                        "type": "QQuickDragAxis*",
+                        "user": false
+                    },
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDragAxis*",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "index": 14,
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+                        "notify": "updated",
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+                        "stored": true,
+                        "type": "QVector2D",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "activeTranslation",
+                        "notify": "translationChanged",
+                        "read": "activeTranslation",
+                        "required": false,
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+                        "scriptable": true,
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+                        "type": "QPointF",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "persistentTranslation",
+                        "notify": "translationChanged",
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+                        "required": false,
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPointF",
+                        "user": false,
+                        "write": "setPersistentTranslation"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPinchHandler",
+                "signals": [
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+                        "access": "public",
+                        "index": 0,
+                        "name": "minimumScaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "maximumScaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "minimumRotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "maximumRotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "updated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "delta",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "scaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "delta",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "rotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "delta",
+                                "type": "QVector2D"
+                            }
+                        ],
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+                        "name": "translationChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QQuickMultiPointHandler"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpinchhandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPixmapCache",
+                "lineNumber": 44,
+                "object": true,
+                "qualifiedClassName": "QQuickPixmapCache",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
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+                        "stored": true,
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+                        "user": false,
+                        "write": "setAcceptedPointerTypes"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "acceptedButtons",
+                        "notify": "acceptedButtonsChanged",
+                        "read": "acceptedButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::MouseButtons",
+                        "user": false,
+                        "write": "setAcceptedButtons"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "acceptedModifiers",
+                        "notify": "acceptedModifiersChanged",
+                        "read": "acceptedModifiers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::KeyboardModifiers",
+                        "user": false,
+                        "write": "setAcceptedModifiers"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPointerDeviceHandler",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "acceptedDevicesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "acceptedPointerTypesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "acceptedButtonsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "acceptedModifiersChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "acceptedDevices",
+                                "type": "QInputDevice::DeviceTypes"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setAcceptedDevices",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "acceptedPointerTypes",
+                                "type": "QPointingDevice::PointerTypes"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setAcceptedPointerTypes",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "buttons",
+                                "type": "Qt::MouseButtons"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setAcceptedButtons",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "acceptedModifiers",
+                                "type": "Qt::KeyboardModifiers"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setAcceptedModifiers",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QQuickPointerHandler"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "classInfos": [
+                    {
+                        "name": "ParentProperty",
+                        "value": "parent"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "PointerHandler"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "PointerHandler is an abstract base class."
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "524"
+                    }
+                ],
+                "className": "QQuickPointerHandler",
+                "enums": [
+                    {
+                        "alias": "GrabPermission",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "GrabPermissions",
+                        "values": [
+                            "TakeOverForbidden",
+                            "CanTakeOverFromHandlersOfSameType",
+                            "CanTakeOverFromHandlersOfDifferentType",
+                            "CanTakeOverFromItems",
+                            "CanTakeOverFromAnything",
+                            "ApprovesTakeOverByHandlersOfSameType",
+                            "ApprovesTakeOverByHandlersOfDifferentType",
+                            "ApprovesTakeOverByItems",
+                            "ApprovesCancellation",
+                            "ApprovesTakeOverByAnything"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
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+                "object": true,
+                "properties": [
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "enabled",
+                        "notify": "enabledChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "active",
+                        "notify": "activeChanged",
+                        "read": "active",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "target",
+                        "notify": "targetChanged",
+                        "read": "target",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTarget"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "parent",
+                        "notify": "parentChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setParentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "name": "grabPermissions",
+                        "notify": "grabPermissionChanged",
+                        "read": "grabPermissions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "GrabPermissions",
+                        "user": false,
+                        "write": "setGrabPermissions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "margin",
+                        "notify": "marginChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMargin"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "dragThreshold",
+                        "notify": "dragThresholdChanged",
+                        "read": "dragThreshold",
+                        "required": false,
+                        "reset": "resetDragThreshold",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDragThreshold"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "cursorShape",
+                        "notify": "cursorShapeChanged",
+                        "read": "cursorShape",
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+                        "reset": "resetCursorShape",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CursorShape",
+                        "user": false,
+                        "write": "setCursorShape"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPointerHandler",
+                "signals": [
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+                        "access": "public",
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+                        "name": "enabledChanged",
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+                    },
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+                        "name": "activeChanged",
+                        "returnType": "void"
+                    },
+                    {
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+                        "index": 2,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "marginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "dragThresholdChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "transition",
+                                "type": "QPointingDevice::GrabTransition"
+                            },
+                            {
+                                "name": "point",
+                                "type": "QEventPoint"
+                            }
+                        ],
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+                        "name": "grabChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "grabPermissionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "point",
+                                "type": "QEventPoint"
+                            }
+                        ],
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+                        "name": "canceled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "cursorShapeChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "parentChanged",
+                        "returnType": "void",
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+                    }
+                ],
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+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
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+            {
+                "classInfos": [
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+                        "name": "QML.Element",
+                        "value": "PointHandler"
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+                    {
+                        "name": "QML.AddedInVersion",
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+                "className": "QQuickPointHandler",
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+                        "type": "QVector2D",
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+                    }
+                ],
+                "qualifiedClassName": "QQuickPointHandler",
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+                        "index": 0,
+                        "name": "translationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickSinglePointHandler"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpointhandler_p.h",
+        "outputRevision": 68
+    },
+    {
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+                        "write": "setIsExplicit"
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+                ],
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+                ]
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+                    {
+                        "name": "QML.Extended",
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+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
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+                ],
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+                        "name": "Orientation",
+                        "values": [
+                            "Vertical",
+                            "Horizontal"
+                        ]
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+                        "write": "setOrientation"
+                    }
+                ],
+                "qualifiedClassName": "QQuickGradient",
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+                        "name": "updated",
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+                        "name": "orientationChanged",
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+                        "name": "colorChanged",
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+                    {
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+                        "name": "bottomRightRadiusChanged",
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+                        "arguments": [
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+                                "type": "int"
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+                        "name": "itemAt",
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+                        "type": "QVariant",
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+                        "type": "QQmlComponent*",
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+                        "name": "count",
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+                        "scriptable": true,
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+                        "type": "int",
+                        "user": false
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+                ],
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+                        "name": "modelChanged",
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+                        "name": "countChanged",
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+                    {
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+                                "type": "int"
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+                                "name": "index",
+                                "type": "int"
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+                        "name": "createdItem",
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+                            {
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+                        "name": "initItem",
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+                                "name": "changeSet",
+                                "type": "QQmlChangeSet"
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+                                "name": "reset",
+                                "type": "bool"
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+                        "scriptable": true,
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+                        "type": "int",
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+                        "write": "setBottom"
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+                ],
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+                        "name": "borderChanged",
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+                    {
+                        "name": "QML.Creatable",
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+                        "name": "manufacturer",
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+                        "type": "int",
+                        "user": false,
+                        "write": "setFrameDurationVariation"
+                    }
+                ],
+                "qualifiedClassName": "QQuickSprite",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "frameHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "frameWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "reverseChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "frameCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "frameXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "frameYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "frameRateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "frameRateVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "frameDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "frameDurationVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "frameSyncChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "setFrameHeight",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "setFrameWidth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "setReverse",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "setFrames",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "setFrameCount",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "setFrameX",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "setFrameY",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "setFrameRate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "setFrameRateVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "setFrameDuration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "setFrameDurationVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "setFrameSync",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 25,
+                        "name": "startImageLoading",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QQuickStochasticState"
+                    }
+                ]
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+                        "type": "QVariantMap",
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+                                "type": "int"
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+                                "type": "QString"
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+                    {
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+                                "name": "arg",
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+                                "type": "int"
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+                        "name": "entered",
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+                                "type": "bool"
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+                            {
+                                "name": "arg",
+                                "type": "int"
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+                        "arguments": [
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+                                "type": "QString"
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+                        "name": "setName",
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+                    {
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+                        "arguments": [
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+                                "name": "arg",
+                                "type": "QVariantMap"
+                            }
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+                    {
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+                        "arguments": [
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+                                "name": "arg",
+                                "type": "int"
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+                        "name": "setDurationVariation",
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+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                        "type": "QString",
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+                                "name": "arg",
+                                "type": "QString"
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+                    },
+                    {
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+                        "arguments": [
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+                                "name": "idx",
+                                "type": "int"
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+                                "type": "QString"
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+                        "name": "setGlobalGoal",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "time",
+                                "type": "uint"
+                            }
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+                        "name": "updateSprites",
+                        "returnType": "uint"
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+                ],
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+                "properties": [
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+                        "type": "QQmlListProperty<QQuickSprite>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickSpriteEngine",
+                "superClasses": [
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+                ]
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+    },
+    {
+        "classes": [
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+                "classInfos": [
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+                        "value": "sprites"
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+                    {
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+                    },
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+                        "name": "QML.AddedInVersion",
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+                        "final": false,
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+                        "name": "goalSprite",
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+                        "scriptable": true,
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+                        "type": "QString",
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+                        "write": "setGoalSprite"
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+                        "final": false,
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+                        "name": "currentSprite",
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+                        "type": "QQmlListProperty<QQuickSprite>",
+                        "user": false
+                    }
+                ],
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+                        "arguments": [
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+                                "name": "arg",
+                                "type": "bool"
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+                        "name": "runningChanged",
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+                    },
+                    {
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+                                "name": "arg",
+                                "type": "bool"
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+                                "name": "arg",
+                                "type": "QString"
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+                        "name": "goalSpriteChanged",
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+                            {
+                                "name": "arg",
+                                "type": "QString"
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+                        "name": "currentSpriteChanged",
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+                ],
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+                            {
+                                "name": "sprite",
+                                "type": "QString"
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+                        "name": "jumpTo",
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+                            {
+                                "name": "sprite",
+                                "type": "QString"
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+                        "name": "setGoalSprite",
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+                    },
+                    {
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+                                "name": "arg",
+                                "type": "bool"
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+                                "name": "arg",
+                                "type": "bool"
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+                            "id": "\"org.qt-project.Qt.QQmlFinalizerHook\""
+                        }
+                    ]
+                ],
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+                "methods": [
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+                        "access": "public",
+                        "index": 30,
+                        "name": "forceLayout",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cell",
+                                "type": "QPoint"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
+                            },
+                            {
+                                "name": "offset",
+                                "type": "QPointF"
+                            },
+                            {
+                                "name": "subRect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "positionViewAtCell",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cell",
+                                "type": "QPoint"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
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+                            {
+                                "name": "offset",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 32,
+                        "isCloned": true,
+                        "name": "positionViewAtCell",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cell",
+                                "type": "QPoint"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
+                            }
+                        ],
+                        "index": 33,
+                        "isCloned": true,
+                        "name": "positionViewAtCell",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
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+                                "type": "PositionMode"
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+                            {
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+                                "type": "QPointF"
+                            },
+                            {
+                                "name": "subRect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "positionViewAtIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
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+                            {
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+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 35,
+                        "isCloned": true,
+                        "name": "positionViewAtIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
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+                                "type": "PositionMode"
+                            }
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+                        "isCloned": true,
+                        "name": "positionViewAtIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
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+                                "type": "PositionMode"
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+                            {
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+                                "type": "QRectF"
+                            }
+                        ],
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+                        "name": "positionViewAtRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
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+                                "type": "PositionMode"
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+                                "type": "qreal"
+                            }
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+                        "index": 38,
+                        "isCloned": true,
+                        "name": "positionViewAtRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
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+                        "isCloned": true,
+                        "name": "positionViewAtRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
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+                                "type": "PositionMode"
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+                                "type": "qreal"
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+                            {
+                                "name": "subRect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 40,
+                        "name": "positionViewAtColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
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+                            {
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+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 41,
+                        "isCloned": true,
+                        "name": "positionViewAtColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "PositionMode"
+                            }
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+                        "isCloned": true,
+                        "name": "positionViewAtColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cell",
+                                "type": "QPoint"
+                            }
+                        ],
+                        "index": 43,
+                        "name": "itemAtCell",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "position",
+                                "type": "QPointF"
+                            },
+                            {
+                                "name": "includeSpacing",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "cellAtPosition",
+                        "returnType": "QPoint",
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "position",
+                                "type": "QPointF"
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+                        "name": "cellAtPosition",
+                        "returnType": "QPoint",
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+                    },
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+                                "type": "qreal"
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+                            {
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+                                "type": "qreal"
+                            },
+                            {
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+                                "type": "bool"
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+                        "returnType": "QPoint",
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "row",
+                                "type": "int"
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+                            {
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+                                "type": "int"
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+                        "name": "modelIndex",
+                        "returnType": "QModelIndex",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "position",
+                                "type": "QPointF"
+                            },
+                            {
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+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "cellAtPos",
+                        "returnType": "QPoint"
+                    },
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+                        "access": "public",
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+                                "name": "position",
+                                "type": "QPointF"
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+                        "returnType": "QPoint"
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+                                "type": "qreal"
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+                            {
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+                                "type": "qreal"
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+                            {
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+                                "type": "bool"
+                            }
+                        ],
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+                        "returnType": "QPoint"
+                    },
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+                        "access": "public",
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+                                "type": "qreal"
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+                                "name": "column",
+                                "type": "int"
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+                        "returnType": "bool",
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+                                "type": "int"
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+                        "name": "isRowLoaded",
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+                                "name": "column",
+                                "type": "int"
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+                        "name": "columnWidth",
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+                    },
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+                            {
+                                "name": "column",
+                                "type": "int"
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+                        "name": "implicitColumnWidth",
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+                    },
+                    {
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+                                "name": "row",
+                                "type": "int"
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+                    },
+                    {
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+                                "type": "int"
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+                                "type": "int"
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+                        "name": "index",
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+                        "arguments": [
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+                                "name": "cell",
+                                "type": "QPoint"
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+                                "name": "index",
+                                "type": "QModelIndex"
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+                        "name": "cellAtIndex",
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+                    },
+                    {
+                        "access": "public",
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+                                "name": "index",
+                                "type": "QModelIndex"
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+                        "name": "rowAtIndex",
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+                        "arguments": [
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+                                "name": "index",
+                                "type": "QModelIndex"
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+                        "returnType": "int",
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+                    {
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+                                "name": "column",
+                                "type": "int"
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+                            {
+                                "name": "size",
+                                "type": "qreal"
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+                        ],
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+                        "name": "setColumnWidth",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
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+                        "name": "clearColumnWidths",
+                        "returnType": "void",
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+                    },
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+                        "arguments": [
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+                                "name": "column",
+                                "type": "int"
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+                        "name": "explicitColumnWidth",
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+                    },
+                    {
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+                                "type": "int"
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+                                "type": "qreal"
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+                        ],
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+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
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+                        "name": "clearRowHeights",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "row",
+                                "type": "int"
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+                                "name": "index",
+                                "type": "QModelIndex"
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+                    },
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+                        "returnType": "void",
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+                                "type": "int"
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+                                "type": "int"
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+                                "type": "int"
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+                        ],
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+                        "name": "moveRow",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
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+                        "name": "clearColumnReordering",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
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+                        "name": "clearRowReordering",
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+                        "type": "int",
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+                        "type": "qreal",
+                        "user": false,
+                        "write": "setColumnSpacing"
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setRowHeightProvider"
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+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setColumnWidthProvider"
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+                        "stored": true,
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+                        "scriptable": true,
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+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "reuseItems",
+                        "notify": "reuseItemsChanged",
+                        "read": "reuseItems",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReuseItems"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "syncView",
+                        "notify": "syncViewChanged",
+                        "read": "syncView",
+                        "required": false,
+                        "revision": 526,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTableView*",
+                        "user": false,
+                        "write": "setSyncView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "syncDirection",
+                        "notify": "syncDirectionChanged",
+                        "read": "syncDirection",
+                        "required": false,
+                        "revision": 526,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientations",
+                        "user": false,
+                        "write": "setSyncDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "leftColumn",
+                        "notify": "leftColumnChanged",
+                        "read": "leftColumn",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "rightColumn",
+                        "notify": "rightColumnChanged",
+                        "read": "rightColumn",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "topRow",
+                        "notify": "topRowChanged",
+                        "read": "topRow",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "bottomRow",
+                        "notify": "bottomRowChanged",
+                        "read": "bottomRow",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "selectionModel",
+                        "notify": "selectionModelChanged",
+                        "read": "selectionModel",
+                        "required": false,
+                        "revision": 1538,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QItemSelectionModel*",
+                        "user": false,
+                        "write": "setSelectionModel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "animate",
+                        "notify": "animateChanged",
+                        "read": "animate",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAnimate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "keyNavigationEnabled",
+                        "notify": "keyNavigationEnabledChanged",
+                        "read": "keyNavigationEnabled",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setKeyNavigationEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "pointerNavigationEnabled",
+                        "notify": "pointerNavigationEnabledChanged",
+                        "read": "pointerNavigationEnabled",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPointerNavigationEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "currentRow",
+                        "notify": "currentRowChanged",
+                        "read": "currentRow",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "currentColumn",
+                        "notify": "currentColumnChanged",
+                        "read": "currentColumn",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "alternatingRows",
+                        "notify": "alternatingRowsChanged",
+                        "read": "alternatingRows",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAlternatingRows"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "selectionBehavior",
+                        "notify": "selectionBehaviorChanged",
+                        "read": "selectionBehavior",
+                        "required": false,
+                        "revision": 1540,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionBehavior",
+                        "user": false,
+                        "write": "setSelectionBehavior"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "resizableColumns",
+                        "notify": "resizableColumnsChanged",
+                        "read": "resizableColumns",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setResizableColumns"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "resizableRows",
+                        "notify": "resizableRowsChanged",
+                        "read": "resizableRows",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setResizableRows"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "editTriggers",
+                        "notify": "editTriggersChanged",
+                        "read": "editTriggers",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "EditTriggers",
+                        "user": false,
+                        "write": "setEditTriggers"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "selectionMode",
+                        "notify": "selectionModeChanged",
+                        "read": "selectionMode",
+                        "required": false,
+                        "revision": 1542,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionMode",
+                        "user": false,
+                        "write": "setSelectionMode"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTableView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "rowsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "columnsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "rowSpacingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "columnSpacingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "rowHeightProviderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "columnWidthProviderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "reuseItemsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "syncViewChanged",
+                        "returnType": "void",
+                        "revision": 526
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "syncDirectionChanged",
+                        "returnType": "void",
+                        "revision": 526
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "leftColumnChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "rightColumnChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "topRowChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "bottomRowChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "selectionModelChanged",
+                        "returnType": "void",
+                        "revision": 1538
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "animateChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "keyNavigationEnabledChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "pointerNavigationEnabledChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "currentRowChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "currentColumnChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "alternatingRowsChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "selectionBehaviorChanged",
+                        "returnType": "void",
+                        "revision": 1540
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "resizableColumnsChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "resizableRowsChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "editTriggersChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "layoutChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "selectionModeChanged",
+                        "returnType": "void",
+                        "revision": 1542
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldVisualIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newVisualIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "rowMoved",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldVisualIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newVisualIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "columnMoved",
+                        "returnType": "void",
+                        "revision": 1544
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickFlickable"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlFinalizerHook"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickTableViewAttached",
+                "lineNumber": 297,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "view",
+                        "notify": "viewChanged",
+                        "read": "view",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTableView*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "editDelegate",
+                        "notify": "editDelegateChanged",
+                        "read": "editDelegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setEditDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTableViewAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "viewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "pooled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "reused",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "editDelegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "commit",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktableview_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickTableViewHoverHandler",
+                "lineNumber": 56,
+                "object": true,
+                "qualifiedClassName": "QQuickTableViewHoverHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickHoverHandler"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickTableViewPointerHandler",
+                "lineNumber": 73,
+                "object": true,
+                "qualifiedClassName": "QQuickTableViewPointerHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickSinglePointHandler"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickTableViewResizeHandler",
+                "lineNumber": 102,
+                "object": true,
+                "qualifiedClassName": "QQuickTableViewResizeHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTableViewPointerHandler"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickTableViewSectionDragHandler",
+                "lineNumber": 128,
+                "object": true,
+                "qualifiedClassName": "QQuickTableViewSectionDragHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTableViewPointerHandler"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickTableViewTapHandler",
+                "lineNumber": 168,
+                "object": true,
+                "qualifiedClassName": "QQuickTableViewTapHandler",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTapHandler"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktableview_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TapHandler"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "524"
+                    }
+                ],
+                "className": "QQuickTapHandler",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "GesturePolicy",
+                        "values": [
+                            "DragThreshold",
+                            "WithinBounds",
+                            "ReleaseWithinBounds",
+                            "DragWithinBounds"
+                        ]
+                    },
+                    {
+                        "alias": "ExclusiveSignal",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ExclusiveSignals",
+                        "values": [
+                            "NotExclusive",
+                            "SingleTap",
+                            "DoubleTap"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "tapCount",
+                        "notify": "tapCountChanged",
+                        "read": "tapCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "timeHeld",
+                        "notify": "timeHeldChanged",
+                        "read": "timeHeld",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "longPressThreshold",
+                        "notify": "longPressThresholdChanged",
+                        "read": "longPressThreshold",
+                        "required": false,
+                        "reset": "resetLongPressThreshold",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLongPressThreshold"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "gesturePolicy",
+                        "notify": "gesturePolicyChanged",
+                        "read": "gesturePolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "GesturePolicy",
+                        "user": false,
+                        "write": "setGesturePolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "exclusiveSignals",
+                        "notify": "exclusiveSignalsChanged",
+                        "read": "exclusiveSignals",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTapHandler::ExclusiveSignals",
+                        "user": false,
+                        "write": "setExclusiveSignals"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTapHandler",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "tapCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "timeHeldChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "longPressThresholdChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "gesturePolicyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "exclusiveSignalsChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "eventPoint",
+                                "type": "QEventPoint"
+                            },
+                            {
+                                "type": "Qt::MouseButton"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "tapped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "eventPoint",
+                                "type": "QEventPoint"
+                            },
+                            {
+                                "type": "Qt::MouseButton"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "singleTapped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "eventPoint",
+                                "type": "QEventPoint"
+                            },
+                            {
+                                "type": "Qt::MouseButton"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "doubleTapped",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "longPressed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickSinglePointHandler"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktaphandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Text"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickText",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HAlignment",
+                        "values": [
+                            "AlignLeft",
+                            "AlignRight",
+                            "AlignHCenter",
+                            "AlignJustify"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VAlignment",
+                        "values": [
+                            "AlignTop",
+                            "AlignBottom",
+                            "AlignVCenter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextStyle",
+                        "values": [
+                            "Normal",
+                            "Outline",
+                            "Raised",
+                            "Sunken"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextFormat",
+                        "values": [
+                            "PlainText",
+                            "RichText",
+                            "MarkdownText",
+                            "AutoText",
+                            "StyledText"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextElideMode",
+                        "values": [
+                            "ElideLeft",
+                            "ElideRight",
+                            "ElideMiddle",
+                            "ElideNone"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WrapMode",
+                        "values": [
+                            "NoWrap",
+                            "WordWrap",
+                            "WrapAnywhere",
+                            "WrapAtWordBoundaryOrAnywhere",
+                            "Wrap"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderType",
+                        "values": [
+                            "QtRendering",
+                            "NativeRendering",
+                            "CurveRendering"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderTypeQuality",
+                        "values": [
+                            "DefaultRenderTypeQuality",
+                            "LowRenderTypeQuality",
+                            "NormalRenderTypeQuality",
+                            "HighRenderTypeQuality",
+                            "VeryHighRenderTypeQuality"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LineHeightMode",
+                        "values": [
+                            "ProportionalHeight",
+                            "FixedHeight"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FontSizeMode",
+                        "values": [
+                            "FixedSize",
+                            "HorizontalFit",
+                            "VerticalFit",
+                            "Fit"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQuickTextInterface",
+                            "id": "\"org.qt-project.Qt.QQuickTextInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 40,
+                        "name": "forceLayout",
+                        "returnType": "void",
+                        "revision": 521
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 41,
+                        "name": "linkAt",
+                        "returnType": "QString",
+                        "revision": 515
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "linkColor",
+                        "notify": "linkColorChanged",
+                        "read": "linkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setLinkColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "style",
+                        "notify": "styleChanged",
+                        "read": "style",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextStyle",
+                        "user": false,
+                        "write": "setStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "styleColor",
+                        "notify": "styleColorChanged",
+                        "read": "styleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setStyleColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "horizontalAlignment",
+                        "notify": "horizontalAlignmentChanged",
+                        "read": "hAlign",
+                        "required": false,
+                        "reset": "resetHAlign",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false,
+                        "write": "setHAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "effectiveHorizontalAlignment",
+                        "notify": "effectiveHorizontalAlignmentChanged",
+                        "read": "effectiveHAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "verticalAlignment",
+                        "notify": "verticalAlignmentChanged",
+                        "read": "vAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VAlignment",
+                        "user": false,
+                        "write": "setVAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "wrapMode",
+                        "notify": "wrapModeChanged",
+                        "read": "wrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WrapMode",
+                        "user": false,
+                        "write": "setWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "lineCount",
+                        "notify": "lineCountChanged",
+                        "read": "lineCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "truncated",
+                        "notify": "truncatedChanged",
+                        "read": "truncated",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "maximumLineCount",
+                        "notify": "maximumLineCountChanged",
+                        "read": "maximumLineCount",
+                        "required": false,
+                        "reset": "resetMaximumLineCount",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumLineCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "textFormat",
+                        "notify": "textFormatChanged",
+                        "read": "textFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextFormat",
+                        "user": false,
+                        "write": "setTextFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "elide",
+                        "notify": "elideModeChanged",
+                        "read": "elideMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextElideMode",
+                        "user": false,
+                        "write": "setElideMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "paintedWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "paintedHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "lineHeight",
+                        "notify": "lineHeightChanged",
+                        "read": "lineHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLineHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "lineHeightMode",
+                        "notify": "lineHeightModeChanged",
+                        "read": "lineHeightMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LineHeightMode",
+                        "user": false,
+                        "write": "setLineHeightMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "baseUrl",
+                        "notify": "baseUrlChanged",
+                        "read": "baseUrl",
+                        "required": false,
+                        "reset": "resetBaseUrl",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setBaseUrl"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "minimumPixelSize",
+                        "notify": "minimumPixelSizeChanged",
+                        "read": "minimumPixelSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumPixelSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "minimumPointSize",
+                        "notify": "minimumPointSizeChanged",
+                        "read": "minimumPointSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumPointSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "fontSizeMode",
+                        "notify": "fontSizeModeChanged",
+                        "read": "fontSizeMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FontSizeMode",
+                        "user": false,
+                        "write": "setFontSizeMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "renderType",
+                        "notify": "renderTypeChanged",
+                        "read": "renderType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RenderType",
+                        "user": false,
+                        "write": "setRenderType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "hoveredLink",
+                        "notify": "linkHovered",
+                        "read": "hoveredLink",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "renderTypeQuality",
+                        "notify": "renderTypeQualityChanged",
+                        "read": "renderTypeQuality",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRenderTypeQuality"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "padding",
+                        "notify": "paddingChanged",
+                        "read": "padding",
+                        "required": false,
+                        "reset": "resetPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "topPadding",
+                        "notify": "topPaddingChanged",
+                        "read": "topPadding",
+                        "required": false,
+                        "reset": "resetTopPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "leftPadding",
+                        "notify": "leftPaddingChanged",
+                        "read": "leftPadding",
+                        "required": false,
+                        "reset": "resetLeftPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "rightPadding",
+                        "notify": "rightPaddingChanged",
+                        "read": "rightPadding",
+                        "required": false,
+                        "reset": "resetRightPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "bottomPadding",
+                        "notify": "bottomPaddingChanged",
+                        "read": "bottomPadding",
+                        "required": false,
+                        "reset": "resetBottomPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "fontInfo",
+                        "notify": "fontInfoChanged",
+                        "read": "fontInfo",
+                        "required": false,
+                        "revision": 521,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "advance",
+                        "notify": "contentSizeChanged",
+                        "read": "advance",
+                        "required": false,
+                        "revision": 522,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickText",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "linkHovered",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "font",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "linkColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "style",
+                                "type": "QQuickText::TextStyle"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "styleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "styleColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickText::HAlignment"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "horizontalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickText::VAlignment"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "verticalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "wrapModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "lineCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "truncatedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "maximumLineCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "textFormat",
+                                "type": "QQuickText::TextFormat"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "textFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QQuickText::TextElideMode"
+                            }
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+                        "name": "elideModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "contentSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contentWidth",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "contentWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contentHeight",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "contentHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "lineHeight",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "lineHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "LineHeightMode"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "lineHeightModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "fontSizeModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "minimumPixelSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "minimumPointSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "effectiveHorizontalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "line",
+                                "type": "QQuickTextLine*"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "lineLaidOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "baseUrlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "renderTypeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "paddingChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "topPaddingChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "leftPaddingChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "rightPaddingChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "name": "bottomPaddingChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 33,
+                        "name": "fontInfoChanged",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "name": "renderTypeQualityChanged",
+                        "returnType": "void",
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+                    }
+                ],
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+                        "name": "q_updateLayout",
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+                    },
+                    {
+                        "access": "private",
+                        "index": 36,
+                        "name": "triggerPreprocess",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "int"
+                            },
+                            {
+                                "name": "source",
+                                "type": "QUrl"
+                            }
+                        ],
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+                        "name": "loadResource",
+                        "returnType": "QVariant",
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+                    },
+                    {
+                        "access": "private",
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+                        "name": "resourceRequestFinished",
+                        "returnType": "void"
+                    },
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+                        "access": "private",
+                        "index": 39,
+                        "name": "imageDownloadFinished",
+                        "returnType": "void"
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+                        "access": "public",
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+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickTextInterface"
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+                        "type": "int",
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+                        "type": "qreal",
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+                        "type": "qreal",
+                        "user": false,
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+                        "type": "qreal",
+                        "user": false,
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+                        "type": "qreal",
+                        "user": false,
+                        "write": "setY"
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+                        "name": "implicitWidth",
+                        "read": "implicitWidth",
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+                        "scriptable": true,
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+                        "type": "qreal",
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+                        "name": "isLast",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QObject"
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+                ]
+            }
+        ],
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
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+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickTextControl",
+                "signals": [
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+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "preeditTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsRemoved",
+                                "type": "int"
+                            },
+                            {
+                                "name": "charsAdded",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "contentsChange",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "undoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "redoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "format",
+                                "type": "QTextCharFormat"
+                            }
+                        ],
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+                        "name": "currentCharFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "copyAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "overwriteMode",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "overwriteModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "updateCursorRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "updateRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "cursorRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "linkHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "markerClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "marker",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "markerHovered",
+                        "returnType": "void"
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "setPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "setMarkdownText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "setHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QClipboard::Mode"
+                            }
+                        ],
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+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "isCloned": true,
+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 28,
+                        "name": "_q_updateCurrentCharFormatAndSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QTextCursor"
+                            }
+                        ],
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+                        "name": "_q_updateCursorPosChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QInputControl"
+                    }
+                ]
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+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "TextDocument is only available as a property of TextEdit or TextArea."
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickTextDocument",
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+                        "isFlag": false,
+                        "name": "Status",
+                        "type": "quint8",
+                        "values": [
+                            "Null",
+                            "Loading",
+                            "Loaded",
+                            "Saving",
+                            "Saved",
+                            "ReadError",
+                            "WriteError",
+                            "NonLocalFileError"
+                        ]
+                    }
+                ],
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+                        "name": "save",
+                        "returnType": "void",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "saveAs",
+                        "returnType": "void",
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+                    }
+                ],
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+                        "scriptable": true,
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+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
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+                    {
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
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+                        "name": "sourceChanged",
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+                        "name": "modifiedChanged",
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+                    },
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+                        "name": "errorStringChanged",
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+                "className": "QQuickTextImageHandler",
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+                            "className": "QTextObjectInterface",
+                            "id": "\"org.qt-project.Qt.QTextObjectInterface\""
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+                "object": true,
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+                        "access": "public",
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+                    {
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+                "qualifiedClassName": "QQuickTextBlockForeign"
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+                        "value": "TextEdit"
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+                            "AlignRight",
+                            "AlignHCenter",
+                            "AlignJustify"
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VAlignment",
+                        "values": [
+                            "AlignTop",
+                            "AlignBottom",
+                            "AlignVCenter"
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+                    },
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TextFormat",
+                        "values": [
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+                            "RichText",
+                            "AutoText",
+                            "MarkdownText"
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+                    },
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WrapMode",
+                        "values": [
+                            "NoWrap",
+                            "WordWrap",
+                            "WrapAnywhere",
+                            "WrapAtWordBoundaryOrAnywhere",
+                            "Wrap"
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+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SelectionMode",
+                        "values": [
+                            "SelectCharacters",
+                            "SelectWords"
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+                    {
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+                        "isFlag": false,
+                        "name": "RenderType",
+                        "values": [
+                            "QtRendering",
+                            "NativeRendering",
+                            "CurveRendering"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQuickTextInterface",
+                            "id": "\"org.qt-project.Qt.QQuickTextInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 39,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 75,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 76,
+                        "name": "positionToRectangle",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 77,
+                        "name": "positionAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 78,
+                        "name": "moveCursorSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "SelectionMode"
+                            }
+                        ],
+                        "index": 79,
+                        "name": "moveCursorSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 80,
+                        "name": "getText",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 81,
+                        "name": "getFormattedText",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 82,
+                        "name": "linkAt",
+                        "returnType": "QString",
+                        "revision": 515
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "selectionColor",
+                        "notify": "selectionColorChanged",
+                        "read": "selectionColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setSelectionColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "selectedTextColor",
+                        "notify": "selectedTextColorChanged",
+                        "read": "selectedTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setSelectedTextColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "horizontalAlignment",
+                        "notify": "horizontalAlignmentChanged",
+                        "read": "hAlign",
+                        "required": false,
+                        "reset": "resetHAlign",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false,
+                        "write": "setHAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "effectiveHorizontalAlignment",
+                        "notify": "effectiveHorizontalAlignmentChanged",
+                        "read": "effectiveHAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "verticalAlignment",
+                        "notify": "verticalAlignmentChanged",
+                        "read": "vAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VAlignment",
+                        "user": false,
+                        "write": "setVAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "wrapMode",
+                        "notify": "wrapModeChanged",
+                        "read": "wrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WrapMode",
+                        "user": false,
+                        "write": "setWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "lineCount",
+                        "notify": "lineCountChanged",
+                        "read": "lineCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "length",
+                        "notify": "textChanged",
+                        "read": "length",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "contentWidth",
+                        "notify": "contentSizeChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "contentHeight",
+                        "notify": "contentSizeChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "paintedWidth",
+                        "notify": "contentSizeChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "paintedHeight",
+                        "notify": "contentSizeChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "textFormat",
+                        "notify": "textFormatChanged",
+                        "read": "textFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextFormat",
+                        "user": false,
+                        "write": "setTextFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "readOnly",
+                        "notify": "readOnlyChanged",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "cursorVisible",
+                        "notify": "cursorVisibleChanged",
+                        "read": "isCursorVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCursorVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "cursorPosition",
+                        "notify": "cursorPositionChanged",
+                        "read": "cursorPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "cursorRectangle",
+                        "notify": "cursorRectangleChanged",
+                        "read": "cursorRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "cursorDelegate",
+                        "notify": "cursorDelegateChanged",
+                        "read": "cursorDelegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setCursorDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "overwriteMode",
+                        "notify": "overwriteModeChanged",
+                        "read": "overwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "selectionStart",
+                        "notify": "selectionStartChanged",
+                        "read": "selectionStart",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "selectionEnd",
+                        "notify": "selectionEndChanged",
+                        "read": "selectionEnd",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "selectedText",
+                        "notify": "selectedTextChanged",
+                        "read": "selectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "activeFocusOnPress",
+                        "notify": "activeFocusOnPressChanged",
+                        "read": "focusOnPress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFocusOnPress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "persistentSelection",
+                        "notify": "persistentSelectionChanged",
+                        "read": "persistentSelection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPersistentSelection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "textMargin",
+                        "notify": "textMarginChanged",
+                        "read": "textMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTextMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "inputMethodHints",
+                        "notify": "inputMethodHintsChanged",
+                        "read": "inputMethodHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::InputMethodHints",
+                        "user": false,
+                        "write": "setInputMethodHints"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "selectByKeyboard",
+                        "notify": "selectByKeyboardChanged",
+                        "read": "selectByKeyboard",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSelectByKeyboard"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "selectByMouse",
+                        "notify": "selectByMouseChanged",
+                        "read": "selectByMouse",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSelectByMouse"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "mouseSelectionMode",
+                        "notify": "mouseSelectionModeChanged",
+                        "read": "mouseSelectionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionMode",
+                        "user": false,
+                        "write": "setMouseSelectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "canPaste",
+                        "notify": "canPasteChanged",
+                        "read": "canPaste",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "canUndo",
+                        "notify": "canUndoChanged",
+                        "read": "canUndo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "canRedo",
+                        "notify": "canRedoChanged",
+                        "read": "canRedo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 35,
+                        "name": "inputMethodComposing",
+                        "notify": "inputMethodComposingChanged",
+                        "read": "isInputMethodComposing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 36,
+                        "name": "baseUrl",
+                        "notify": "baseUrlChanged",
+                        "read": "baseUrl",
+                        "required": false,
+                        "reset": "resetBaseUrl",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setBaseUrl"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 37,
+                        "name": "renderType",
+                        "notify": "renderTypeChanged",
+                        "read": "renderType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RenderType",
+                        "user": false,
+                        "write": "setRenderType"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 38,
+                        "name": "textDocument",
+                        "read": "textDocument",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextDocument*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 39,
+                        "name": "hoveredLink",
+                        "notify": "linkHovered",
+                        "read": "hoveredLink",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 40,
+                        "name": "padding",
+                        "notify": "paddingChanged",
+                        "read": "padding",
+                        "required": false,
+                        "reset": "resetPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 41,
+                        "name": "topPadding",
+                        "notify": "topPaddingChanged",
+                        "read": "topPadding",
+                        "required": false,
+                        "reset": "resetTopPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 42,
+                        "name": "leftPadding",
+                        "notify": "leftPaddingChanged",
+                        "read": "leftPadding",
+                        "required": false,
+                        "reset": "resetLeftPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 43,
+                        "name": "rightPadding",
+                        "notify": "rightPaddingChanged",
+                        "read": "rightPadding",
+                        "required": false,
+                        "reset": "resetRightPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 44,
+                        "name": "bottomPadding",
+                        "notify": "bottomPaddingChanged",
+                        "read": "bottomPadding",
+                        "required": false,
+                        "reset": "resetBottomPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 45,
+                        "name": "preeditText",
+                        "notify": "preeditTextChanged",
+                        "read": "preeditText",
+                        "required": false,
+                        "revision": 519,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 46,
+                        "name": "tabStopDistance",
+                        "notify": "tabStopDistanceChanged",
+                        "read": "tabStopDistance",
+                        "required": false,
+                        "revision": 522,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTabStopDistance"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 47,
+                        "name": "cursorSelection",
+                        "read": "cursorSelection",
+                        "required": false,
+                        "revision": 1543,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextSelection*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickTextEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "preeditTextChanged",
+                        "returnType": "void",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "contentSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "cursorRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "selectionStartChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "selectionEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "selectedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "selectionColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "selectedTextColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "font",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickTextEdit::HAlignment"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "horizontalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickTextEdit::VAlignment"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "verticalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "wrapModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "lineCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "textFormat",
+                                "type": "QQuickTextEdit::TextFormat"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "textFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isReadOnly",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "readOnlyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isCursorVisible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "cursorVisibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "cursorDelegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "overwriteMode",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "overwriteModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "activeFocusOnPressed",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "activeFocusOnPressChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isPersistentSelection",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "persistentSelectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "textMargin",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "textMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selectByKeyboard",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "selectByKeyboardChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selectByMouse",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "selectByMouseChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QQuickTextEdit::SelectionMode"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "mouseSelectionModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "linkHovered",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "canPasteChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "canUndoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "canRedoChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "name": "inputMethodComposingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 33,
+                        "name": "effectiveHorizontalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "name": "baseUrlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 35,
+                        "name": "inputMethodHintsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 36,
+                        "name": "renderTypeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 37,
+                        "name": "editingFinished",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "index": 38,
+                        "name": "paddingChanged",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "index": 39,
+                        "name": "topPaddingChanged",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "index": 40,
+                        "name": "leftPaddingChanged",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "index": 41,
+                        "name": "rightPaddingChanged",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "index": 42,
+                        "name": "bottomPaddingChanged",
+                        "returnType": "void",
+                        "revision": 518
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "distance",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 43,
+                        "name": "tabStopDistanceChanged",
+                        "returnType": "void",
+                        "revision": 522
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 44,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 45,
+                        "name": "selectWord",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 46,
+                        "name": "select",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 47,
+                        "name": "deselect",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 48,
+                        "name": "isRightToLeft",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 49,
+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 50,
+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 51,
+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 52,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 53,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "position",
+                                "type": "int"
+                            },
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 54,
+                        "name": "insert",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 55,
+                        "name": "remove",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 56,
+                        "name": "append",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 57,
+                        "name": "clear",
+                        "returnType": "void",
+                        "revision": 519
+                    },
+                    {
+                        "access": "private",
+                        "index": 58,
+                        "name": "q_invalidate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 59,
+                        "name": "q_textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 60,
+                        "name": "q_contentsChange",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 61,
+                        "name": "updateSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 62,
+                        "name": "moveCursorDelegate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 63,
+                        "name": "createCursor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 64,
+                        "name": "q_canPasteChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 65,
+                        "name": "updateWholeDocument",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "block",
+                                "type": "QTextBlock"
+                            }
+                        ],
+                        "index": 66,
+                        "name": "invalidateBlock",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 67,
+                        "name": "updateCursor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 68,
+                        "name": "q_linkHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "hovered",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 69,
+                        "name": "q_markerHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 70,
+                        "name": "q_updateAlignment",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 71,
+                        "name": "updateSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 72,
+                        "name": "triggerPreprocess",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "int"
+                            },
+                            {
+                                "name": "source",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 73,
+                        "name": "loadResource",
+                        "returnType": "QVariant",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "private",
+                        "index": 74,
+                        "name": "resourceRequestFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickImplicitSizeItem"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickTextInterface"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TextEdit"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.RemovedInVersion",
+                        "value": "1540"
+                    }
+                ],
+                "className": "QQuickPre64TextEdit",
+                "lineNumber": 422,
+                "object": true,
+                "qualifiedClassName": "QQuickPre64TextEdit",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTextEdit"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktextedit_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TextInput"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1540"
+                    }
+                ],
+                "className": "QQuickTextInput",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "EchoMode",
+                        "values": [
+                            "Normal",
+                            "NoEcho",
+                            "Password",
+                            "PasswordEchoOnEdit"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HAlignment",
+                        "values": [
+                            "AlignLeft",
+                            "AlignRight",
+                            "AlignHCenter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VAlignment",
+                        "values": [
+                            "AlignTop",
+                            "AlignBottom",
+                            "AlignVCenter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WrapMode",
+                        "values": [
+                            "NoWrap",
+                            "WordWrap",
+                            "WrapAnywhere",
+                            "WrapAtWordBoundaryOrAnywhere",
+                            "Wrap"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SelectionMode",
+                        "values": [
+                            "SelectCharacters",
+                            "SelectWords"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CursorPosition",
+                        "values": [
+                            "CursorBetweenCharacters",
+                            "CursorOnCharacter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RenderType",
+                        "values": [
+                            "QtRendering",
+                            "NativeRendering",
+                            "CurveRendering"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQuickTextInterface",
+                            "id": "\"org.qt-project.Qt.QQuickTextInterface\""
+                        }
+                    ]
+                ],
+                "lineNumber": 28,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 69,
+                        "name": "positionAt",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 70,
+                        "name": "positionToRectangle",
+                        "returnType": "QRectF"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 71,
+                        "name": "moveCursorSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            },
+                            {
+                                "name": "mode",
+                                "type": "SelectionMode"
+                            }
+                        ],
+                        "index": 72,
+                        "name": "moveCursorSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 73,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 74,
+                        "name": "getText",
+                        "returnType": "QString"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "length",
+                        "notify": "textChanged",
+                        "read": "length",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "selectionColor",
+                        "notify": "selectionColorChanged",
+                        "read": "selectionColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setSelectionColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "selectedTextColor",
+                        "notify": "selectedTextColorChanged",
+                        "read": "selectedTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setSelectedTextColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "horizontalAlignment",
+                        "notify": "horizontalAlignmentChanged",
+                        "read": "hAlign",
+                        "required": false,
+                        "reset": "resetHAlign",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false,
+                        "write": "setHAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "effectiveHorizontalAlignment",
+                        "notify": "effectiveHorizontalAlignmentChanged",
+                        "read": "effectiveHAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "verticalAlignment",
+                        "notify": "verticalAlignmentChanged",
+                        "read": "vAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VAlignment",
+                        "user": false,
+                        "write": "setVAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "wrapMode",
+                        "notify": "wrapModeChanged",
+                        "read": "wrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WrapMode",
+                        "user": false,
+                        "write": "setWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "readOnly",
+                        "notify": "readOnlyChanged",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "cursorVisible",
+                        "notify": "cursorVisibleChanged",
+                        "read": "isCursorVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCursorVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "cursorPosition",
+                        "notify": "cursorPositionChanged",
+                        "read": "cursorPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "cursorRectangle",
+                        "notify": "cursorRectangleChanged",
+                        "read": "cursorRectangle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "cursorDelegate",
+                        "notify": "cursorDelegateChanged",
+                        "read": "cursorDelegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setCursorDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "overwriteMode",
+                        "notify": "overwriteModeChanged",
+                        "read": "overwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "selectionStart",
+                        "notify": "selectionStartChanged",
+                        "read": "selectionStart",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "selectionEnd",
+                        "notify": "selectionEndChanged",
+                        "read": "selectionEnd",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "selectedText",
+                        "notify": "selectedTextChanged",
+                        "read": "selectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "maximumLength",
+                        "notify": "maximumLengthChanged",
+                        "read": "maxLength",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxLength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "validator",
+                        "notify": "validatorChanged",
+                        "read": "validator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QValidator*",
+                        "user": false,
+                        "write": "setValidator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "inputMask",
+                        "notify": "inputMaskChanged",
+                        "read": "inputMask",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setInputMask"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "inputMethodHints",
+                        "notify": "inputMethodHintsChanged",
+                        "read": "inputMethodHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::InputMethodHints",
+                        "user": false,
+                        "write": "setInputMethodHints"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "acceptableInput",
+                        "notify": "acceptableInputChanged",
+                        "read": "hasAcceptableInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "echoMode",
+                        "notify": "echoModeChanged",
+                        "read": "echoMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "EchoMode",
+                        "user": false,
+                        "write": "setEchoMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "activeFocusOnPress",
+                        "notify": "activeFocusOnPressChanged",
+                        "read": "focusOnPress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFocusOnPress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "passwordCharacter",
+                        "notify": "passwordCharacterChanged",
+                        "read": "passwordCharacter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPasswordCharacter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "passwordMaskDelay",
+                        "notify": "passwordMaskDelayChanged",
+                        "read": "passwordMaskDelay",
+                        "required": false,
+                        "reset": "resetPasswordMaskDelay",
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPasswordMaskDelay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "displayText",
+                        "notify": "displayTextChanged",
+                        "read": "displayText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "preeditText",
+                        "notify": "preeditTextChanged",
+                        "read": "preeditText",
+                        "required": false,
+                        "revision": 519,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "autoScroll",
+                        "notify": "autoScrollChanged",
+                        "read": "autoScroll",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoScroll"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "selectByMouse",
+                        "notify": "selectByMouseChanged",
+                        "read": "selectByMouse",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSelectByMouse"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "mouseSelectionMode",
+                        "notify": "mouseSelectionModeChanged",
+                        "read": "mouseSelectionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionMode",
+                        "user": false,
+                        "write": "setMouseSelectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "persistentSelection",
+                        "notify": "persistentSelectionChanged",
+                        "read": "persistentSelection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPersistentSelection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "canPaste",
+                        "notify": "canPasteChanged",
+                        "read": "canPaste",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 35,
+                        "name": "canUndo",
+                        "notify": "canUndoChanged",
+                        "read": "canUndo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 36,
+                        "name": "canRedo",
+                        "notify": "canRedoChanged",
+                        "read": "canRedo",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 37,
+                        "name": "inputMethodComposing",
+                        "notify": "inputMethodComposingChanged",
+                        "read": "isInputMethodComposing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 38,
+                        "name": "contentWidth",
+                        "notify": "contentSizeChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 39,
+                        "name": "contentHeight",
+                        "notify": "contentSizeChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 40,
+                        "name": "renderType",
+                        "notify": "renderTypeChanged",
+                        "read": "renderType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RenderType",
+                        "user": false,
+                        "write": "setRenderType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 41,
+                        "name": "padding",
+                        "notify": "paddingChanged",
+                        "read": "padding",
+                        "required": false,
+                        "reset": "resetPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 42,
+                        "name": "topPadding",
+                        "notify": "topPaddingChanged",
+                        "read": "topPadding",
+                        "required": false,
+                        "reset": "resetTopPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 43,
+                        "name": "leftPadding",
+                        "notify": "leftPaddingChanged",
+                        "read": "leftPadding",
+                        "required": false,
+                        "reset": "resetLeftPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 44,
+                        "name": "rightPadding",
+                        "notify": "rightPaddingChanged",
+                        "read": "rightPadding",
+                        "required": false,
+                        "reset": "resetRightPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 45,
+                        "name": "bottomPadding",
+                        "notify": "bottomPaddingChanged",
+                        "read": "bottomPadding",
+                        "required": false,
+                        "reset": "resetBottomPadding",
+                        "revision": 518,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomPadding"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTextInput",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "cursorRectangleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "selectionStartChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "selectionEndChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "selectedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "acceptableInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "editingFinished",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "textEdited",
+                        "returnType": "void",
+                        "revision": 521
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "selectionColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "selectedTextColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "font",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickTextInput::HAlignment"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "horizontalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "alignment",
+                                "type": "QQuickTextInput::VAlignment"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "verticalAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "wrapModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isReadOnly",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "readOnlyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "isCursorVisible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "cursorVisibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "cursorDelegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "overwriteMode",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "overwriteModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "maximumLength",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "maximumLengthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "validatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "inputMask",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "inputMaskChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "echoMode",
+                                "type": "QQuickTextInput::EchoMode"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "echoModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "passwordCharacterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "passwordMaskDelayChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "displayTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "preeditTextChanged",
+                        "returnType": "void",
+                        "revision": 519
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "activeFocusOnPress",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "activeFocusOnPressChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "autoScroll",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "autoScrollChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selectByMouse",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "selectByMouseChanged",
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+                            "ProPhotoRgb"
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+                                "type": "QAnyStringView"
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+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGContextFactoryInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgcontextplugin_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGDefaultRenderContext",
+                "lineNumber": 35,
+                "object": true,
+                "qualifiedClassName": "QSGDefaultRenderContext",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderContext"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgdefaultrendercontext_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGPlainTexture",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QSGPlainTexture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTexture"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgplaintexture_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGRenderLoop",
+                "lineNumber": 33,
+                "object": true,
+                "qualifiedClassName": "QSGRenderLoop",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "timeToIncubate",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgrenderloop_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "Manager",
+                "lineNumber": 40,
+                "object": true,
+                "qualifiedClassName": "QSGRhiAtlasTexture::Manager",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "AtlasBase",
+                "lineNumber": 63,
+                "object": true,
+                "qualifiedClassName": "QSGRhiAtlasTexture::AtlasBase",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "TextureBase",
+                "lineNumber": 117,
+                "object": true,
+                "qualifiedClassName": "QSGRhiAtlasTexture::TextureBase",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTexture"
+                    }
+                ]
+            },
+            {
+                "className": "Texture",
+                "lineNumber": 136,
+                "object": true,
+                "qualifiedClassName": "QSGRhiAtlasTexture::Texture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "fullyQualifiedName": "QSGRhiAtlasTexture::TextureBase",
+                        "name": "TextureBase"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgrhiatlastexture_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGRhiLayer",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QSGRhiLayer",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "markDirtyTexture",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "invalidated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGLayer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgrhilayer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGRhiShaderEffectNode",
+                "lineNumber": 91,
+                "object": true,
+                "qualifiedClassName": "QSGRhiShaderEffectNode",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "handleTextureChange",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "object",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "handleTextureProviderDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGShaderEffectNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgrhishadereffectnode_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwareRenderContext",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareRenderContext",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderContext"
+                    }
+                ]
+            },
+            {
+                "className": "QSGSoftwareContext",
+                "lineNumber": 48,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareContext",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGContext"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGRendererInterface"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarecontext_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwareLayer",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareLayer",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "markDirtyTexture",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "invalidated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGLayer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarelayer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwarePixmapTexture",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwarePixmapTexture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTexture"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarepixmaptexture_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwareRenderLoop",
+                "lineNumber": 24,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareRenderLoop",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderLoop"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarerenderloop_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwareThreadedRenderLoop",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareThreadedRenderLoop",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "onAnimationStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "onAnimationStopped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderLoop"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarethreadedrenderloop_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGTexture",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QSGTexture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QSGDynamicTexture",
+                "lineNumber": 99,
+                "object": true,
+                "qualifiedClassName": "QSGDynamicTexture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTexture"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgtexture.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGTextureProvider",
+                "lineNumber": 12,
+                "object": true,
+                "qualifiedClassName": "QSGTextureProvider",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textureChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgtextureprovider.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGThreadedRenderLoop",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QSGThreadedRenderLoop",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "animationStarted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "animationStopped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderLoop"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgthreadedrenderloop_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickLocalTransform",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QQuickLocalTransform",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickTransform"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickflipable.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickFontObject",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QQuickFontObject",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fontDownloaded",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "replyFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfontloader.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGFramebufferObjectNode",
+                "lineNumber": 163,
+                "object": true,
+                "qualifiedClassName": "QSGFramebufferObjectNode",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "render",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "handleScreenChange",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTextureProvider"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGSimpleTextureNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickframebufferobject.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPixmapReply",
+                "lineNumber": 142,
+                "object": true,
+                "qualifiedClassName": "QQuickPixmapReply",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qint64"
+                            },
+                            {
+                                "type": "qint64"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "downloadProgress",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "ReaderThreadExecutionEnforcer",
+                "lineNumber": 192,
+                "object": true,
+                "qualifiedClassName": "ReaderThreadExecutionEnforcer",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "response",
+                                "type": "QQuickImageResponse*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "asyncResponseFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "asyncResponseFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "networkRequestDone",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickPixmapReader",
+                "lineNumber": 220,
+                "object": true,
+                "qualifiedClassName": "QQuickPixmapReader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpixmapcache.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "CallbackRegistrationHelper",
+                "lineNumber": 35,
+                "object": true,
+                "qualifiedClassName": "CallbackRegistrationHelper",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickprofiler.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickShaderEffectSourceTextureProvider",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QQuickShaderEffectSourceTextureProvider",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGTextureProvider"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickShaderSourceAttachedNode",
+                "lineNumber": 629,
+                "object": true,
+                "qualifiedClassName": "QQuickShaderSourceAttachedNode",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "markTextureDirty",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickshadereffectsource.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickWindowIncubationController",
+                "lineNumber": 79,
+                "object": true,
+                "qualifiedClassName": "QQuickWindowIncubationController",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "incubate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "animationStopped",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlIncubationController"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickwindow.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGDefaultAnimationDriver",
+                "lineNumber": 113,
+                "object": true,
+                "qualifiedClassName": "QSGDefaultAnimationDriver",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGAnimationDriver"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgcontext.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGGuiThreadRenderLoop",
+                "lineNumber": 112,
+                "object": true,
+                "qualifiedClassName": "QSGGuiThreadRenderLoop",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSGRenderLoop"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgrenderloop.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGSoftwareRenderThread",
+                "lineNumber": 121,
+                "object": true,
+                "qualifiedClassName": "QSGSoftwareRenderThread",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "onSceneGraphChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgsoftwarethreadedrenderloop.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSGRenderThread",
+                "lineNumber": 220,
+                "object": true,
+                "qualifiedClassName": "QSGRenderThread",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sceneGraphChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsgthreadedrenderloop.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..d981c9d0d9e93fbd1df301d4bcd085b3ede65ddc
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2_metatypes.json
@@ -0,0 +1,38 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickAttachedPropertyPropagator",
+                "lineNumber": 14,
+                "object": true,
+                "qualifiedClassName": "QQuickAttachedPropertyPropagator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickattachedpropertypropagator.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickStylePlugin",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQuickStylePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQmlExtensionPlugin"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickstyleplugin_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basic_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basic_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b98e1eb08a05607ff91e7c0b4cb05e8fe5e1bf6
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basic_metatypes.json
@@ -0,0 +1,618 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Basic"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    }
+                ],
+                "className": "QQuickBasicStyle",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "backgroundColor",
+                        "read": "backgroundColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "overlayModalColor",
+                        "read": "overlayModalColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "overlayDimColor",
+                        "read": "overlayDimColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "textColor",
+                        "read": "textColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "textDarkColor",
+                        "read": "textDarkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "textLightColor",
+                        "read": "textLightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "textLinkColor",
+                        "read": "textLinkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "textSelectionColor",
+                        "read": "textSelectionColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "textDisabledColor",
+                        "read": "textDisabledColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "textDisabledLightColor",
+                        "read": "textDisabledLightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "textPlaceholderColor",
+                        "read": "textPlaceholderColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "focusColor",
+                        "read": "focusColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "focusLightColor",
+                        "read": "focusLightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "focusPressedColor",
+                        "read": "focusPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "buttonColor",
+                        "read": "buttonColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "buttonPressedColor",
+                        "read": "buttonPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "buttonCheckedColor",
+                        "read": "buttonCheckedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "buttonCheckedPressedColor",
+                        "read": "buttonCheckedPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "buttonCheckedFocusColor",
+                        "read": "buttonCheckedFocusColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "toolButtonColor",
+                        "read": "toolButtonColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "tabButtonColor",
+                        "read": "tabButtonColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "tabButtonPressedColor",
+                        "read": "tabButtonPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "tabButtonCheckedPressedColor",
+                        "read": "tabButtonCheckedPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "delegateColor",
+                        "read": "delegateColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "delegatePressedColor",
+                        "read": "delegatePressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "delegateFocusColor",
+                        "read": "delegateFocusColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "indicatorPressedColor",
+                        "read": "indicatorPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "indicatorDisabledColor",
+                        "read": "indicatorDisabledColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "indicatorFrameColor",
+                        "read": "indicatorFrameColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 29,
+                        "name": "indicatorFramePressedColor",
+                        "read": "indicatorFramePressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 30,
+                        "name": "indicatorFrameDisabledColor",
+                        "read": "indicatorFrameDisabledColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 31,
+                        "name": "frameDarkColor",
+                        "read": "frameDarkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 32,
+                        "name": "frameLightColor",
+                        "read": "frameLightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 33,
+                        "name": "scrollBarColor",
+                        "read": "scrollBarColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 34,
+                        "name": "scrollBarPressedColor",
+                        "read": "scrollBarPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 35,
+                        "name": "progressBarColor",
+                        "read": "progressBarColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 36,
+                        "name": "pageIndicatorColor",
+                        "read": "pageIndicatorColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 37,
+                        "name": "separatorColor",
+                        "read": "separatorColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 38,
+                        "name": "disabledDarkColor",
+                        "read": "disabledDarkColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 39,
+                        "name": "disabledLightColor",
+                        "read": "disabledLightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickBasicStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbasicstyle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Overlay"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickOverlay"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickOverlayAttachedForeign",
+                "gadget": true,
+                "lineNumber": 29,
+                "qualifiedClassName": "QQuickOverlayAttachedForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "SplitHandle"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickSplitHandleAttached"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "525"
+                    }
+                ],
+                "className": "QQuickSplitHandleAttachedForeign",
+                "gadget": true,
+                "lineNumber": 39,
+                "qualifiedClassName": "QQuickSplitHandleAttachedForeign"
+            }
+        ],
+        "inputFile": "qtquickcontrols2basicforeign_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basicstyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basicstyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..85650a8406b4fb6a7fc7a656fc8cc04c33bdc2d3
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2basicstyleimpl_metatypes.json
@@ -0,0 +1,232 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BusyIndicatorImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickBasicBusyIndicator",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "pen",
+                        "read": "pen",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setPen"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "fill",
+                        "read": "fill",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setFill"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "running",
+                        "read": "isRunning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickBasicBusyIndicator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbasicbusyindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "DialImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickBasicDial",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "progress",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setProgress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "startAngle",
+                        "read": "startAngle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setStartAngle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "endAngle",
+                        "read": "endAngle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setEndAngle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    }
+                ],
+                "qualifiedClassName": "QQuickBasicDial",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbasicdial_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ProgressBarImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickBasicProgressBar",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "indeterminate",
+                        "read": "isIndeterminate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIndeterminate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "progress",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setProgress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    }
+                ],
+                "qualifiedClassName": "QQuickBasicProgressBar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbasicprogressbar_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fluentwinui3styleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fluentwinui3styleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..e194510f2520388da661e3cb876fd5910c39b8f2
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fluentwinui3styleimpl_metatypes.json
@@ -0,0 +1,60 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FocusStroke"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1544"
+                    }
+                ],
+                "className": "QQuickFluentWinUI3FocusStroke",
+                "lineNumber": 20,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "radius",
+                        "read": "radius",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRadius"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFluentWinUI3FocusStroke",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfluentwinui3focusstroke_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusion_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusion_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea01c22e326138da2b16bb15d11ffd49acb7d773
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusion_metatypes.json
@@ -0,0 +1,348 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Fusion"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickFusionStyle",
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "highlight",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "highlightedText",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "outline",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "highlightedOutline",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "tabFrameColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "down",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "hovered",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "buttonColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "down",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "buttonColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "isCloned": true,
+                        "name": "buttonColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 8,
+                        "isCloned": true,
+                        "name": "buttonColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "buttonOutline",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "isCloned": true,
+                        "name": "buttonOutline",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "buttonOutline",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "baseColor",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "gradientStart",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "baseColor",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "gradientStop",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "colorA",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "colorB",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "factor",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "mergedColors",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "colorA",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "colorB",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 15,
+                        "isCloned": true,
+                        "name": "mergedColors",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "palette",
+                                "type": "QQuickPalette*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "grooveColor",
+                        "returnType": "QColor"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "lightShade",
+                        "read": "lightShade",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "darkShade",
+                        "read": "darkShade",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "topShadow",
+                        "read": "topShadow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "innerContrastLine",
+                        "read": "innerContrastLine",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickFusionStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfusionstyle_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusionstyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusionstyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..6df78dabf36c38a6c8c1f780a047909be261c827
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2fusionstyleimpl_metatypes.json
@@ -0,0 +1,132 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BusyIndicatorImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickFusionBusyIndicator",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "running",
+                        "read": "isRunning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFusionBusyIndicator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfusionbusyindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "DialImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickFusionDial",
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "highlight",
+                        "read": "highlight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlight"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFusionDial",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfusiondial_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "KnobImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickFusionKnob",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQuickFusionKnob",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfusionknob_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imagine_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imagine_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..655a7f7ba665071c847850d170d2914083cb4b4a
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imagine_metatypes.json
@@ -0,0 +1,82 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Imagine"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickImagineStyle"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickImagineStyle",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "path",
+                        "notify": "pathChanged",
+                        "read": "path",
+                        "required": false,
+                        "reset": "resetPath",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPath"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "url",
+                        "notify": "pathChanged",
+                        "read": "url",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickImagineStyle",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pathChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAttachedPropertyPropagator"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickimaginestyle_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imaginestyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imaginestyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2imaginestyleimpl_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2impl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2impl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..b6f8482adefa7f501a6bf758f4bc5af8adbea850
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2impl_metatypes.json
@@ -0,0 +1,1418 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickAnimatedNode",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQuickAnimatedNode",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "started",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "stopped",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "advance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "update",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGTransformNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickanimatednode_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CheckLabel"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickCheckLabel",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQuickCheckLabel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickText"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickText"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickTextForeign",
+                "gadget": true,
+                "lineNumber": 33,
+                "qualifiedClassName": "QQuickTextForeign"
+            }
+        ],
+        "inputFile": "qquickchecklabel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ClippedText"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "514"
+                    }
+                ],
+                "className": "QQuickClippedText",
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "clipX",
+                        "read": "clipX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setClipX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "clipY",
+                        "read": "clipY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setClipY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "clipWidth",
+                        "read": "clipWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setClipWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "clipHeight",
+                        "read": "clipHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setClipHeight"
+                    }
+                ],
+                "qualifiedClassName": "QQuickClippedText",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickText"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickclippedtext_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Color"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickColor",
+                "lineNumber": 25,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "opacity",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "transparent",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "a",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "b",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "factor",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "blend",
+                        "returnType": "QColor"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickColor",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcolor_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorImage"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickColorImage",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "defaultColor",
+                        "notify": "defaultColorChanged",
+                        "read": "defaultColor",
+                        "required": false,
+                        "reset": "resetDefaultColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setDefaultColor"
+                    }
+                ],
+                "qualifiedClassName": "QQuickColorImage",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "defaultColorChanged",
+                        "returnType": "void"
+                    }
+                ],
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+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "PlaceholderText"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "514"
+                    }
+                ],
+                "className": "QQuickPlaceholderText",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQuickPlaceholderText",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateAlignment",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickText"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplaceholdertext_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformTheme"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "PlatformTheme"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickPlatformTheme",
+                "lineNumber": 25,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "themeHint",
+                                "type": "QPlatformTheme::ThemeHint"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "themeHint",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformTheme",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformtheme_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TumblerView"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    }
+                ],
+                "className": "QQuickTumblerView",
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "model",
+                        "notify": "modelChanged",
+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "path",
+                        "notify": "pathChanged",
+                        "read": "path",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPath*",
+                        "user": false,
+                        "write": "setPath"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTumblerView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "pathChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktumblerview_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2material_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2material_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..89ec47b056c0640b71c957554de8d4ef66a60e90
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2material_metatypes.json
@@ -0,0 +1,1274 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Material"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickMaterialStyle"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMaterialStyle",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Theme",
+                        "values": [
+                            "Light",
+                            "Dark",
+                            "System"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Variant",
+                        "values": [
+                            "Normal",
+                            "Dense"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Color",
+                        "values": [
+                            "Red",
+                            "Pink",
+                            "Purple",
+                            "DeepPurple",
+                            "Indigo",
+                            "Blue",
+                            "LightBlue",
+                            "Cyan",
+                            "Teal",
+                            "Green",
+                            "LightGreen",
+                            "Lime",
+                            "Yellow",
+                            "Amber",
+                            "Orange",
+                            "DeepOrange",
+                            "Brown",
+                            "Grey",
+                            "BlueGrey"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Shade",
+                        "values": [
+                            "Shade50",
+                            "Shade100",
+                            "Shade200",
+                            "Shade300",
+                            "Shade400",
+                            "Shade500",
+                            "Shade600",
+                            "Shade700",
+                            "Shade800",
+                            "Shade900",
+                            "ShadeA100",
+                            "ShadeA200",
+                            "ShadeA400",
+                            "ShadeA700"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "RoundedScale",
+                        "values": [
+                            "NotRounded",
+                            "ExtraSmallScale",
+                            "SmallScale",
+                            "MediumScale",
+                            "LargeScale",
+                            "ExtraLargeScale",
+                            "FullScale"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "ContainerStyle",
+                        "values": [
+                            "Filled",
+                            "Outlined"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "theme",
+                                "type": "Theme"
+                            },
+                            {
+                                "name": "background",
+                                "type": "QVariant"
+                            },
+                            {
+                                "name": "accent",
+                                "type": "QVariant"
+                            },
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "flat",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "highlighted",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "buttonColor",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "Color"
+                            },
+                            {
+                                "name": "shade",
+                                "type": "Shade"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "color",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "Color"
+                            }
+                        ],
+                        "index": 16,
+                        "isCloned": true,
+                        "name": "color",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            },
+                            {
+                                "name": "shade",
+                                "type": "Shade"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "shade",
+                        "returnType": "QColor"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "flat",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "hasIcon",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "buttonLeftPadding",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "flat",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "hasIcon",
+                                "type": "bool"
+                            },
+                            {
+                                "name": "hasText",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "buttonRightPadding",
+                        "returnType": "int"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "theme",
+                        "notify": "themeChanged",
+                        "read": "theme",
+                        "required": false,
+                        "reset": "resetTheme",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Theme",
+                        "user": false,
+                        "write": "setTheme"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "primary",
+                        "notify": "primaryChanged",
+                        "read": "primary",
+                        "required": false,
+                        "reset": "resetPrimary",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setPrimary"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "accent",
+                        "notify": "accentChanged",
+                        "read": "accent",
+                        "required": false,
+                        "reset": "resetAccent",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setAccent"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "foreground",
+                        "notify": "foregroundChanged",
+                        "read": "foreground",
+                        "required": false,
+                        "reset": "resetForeground",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setForeground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "reset": "resetBackground",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "elevation",
+                        "notify": "elevationChanged",
+                        "read": "elevation",
+                        "required": false,
+                        "reset": "resetElevation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setElevation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "roundedScale",
+                        "notify": "roundedScaleChanged",
+                        "read": "roundedScale",
+                        "required": false,
+                        "reset": "resetRoundedScale",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RoundedScale",
+                        "user": false,
+                        "write": "setRoundedScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "containerStyle",
+                        "notify": "containerStyleChanged",
+                        "read": "containerStyle",
+                        "required": false,
+                        "reset": "resetContainerStyle",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ContainerStyle",
+                        "user": false,
+                        "write": "setContainerStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "primaryColor",
+                        "notify": "primaryChanged",
+                        "read": "primaryColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "accentColor",
+                        "notify": "accentChanged",
+                        "read": "accentColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "backgroundColor",
+                        "notify": "backgroundChanged",
+                        "read": "backgroundColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "primaryTextColor",
+                        "notify": "themeChanged",
+                        "read": "primaryTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "primaryHighlightedTextColor",
+                        "notify": "primaryHighlightedTextColorChanged",
+                        "read": "primaryHighlightedTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "secondaryTextColor",
+                        "notify": "themeChanged",
+                        "read": "secondaryTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "hintTextColor",
+                        "notify": "themeChanged",
+                        "read": "hintTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "textSelectionColor",
+                        "notify": "themeOrAccentChanged",
+                        "read": "textSelectionColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "dropShadowColor",
+                        "read": "dropShadowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "dividerColor",
+                        "notify": "themeChanged",
+                        "read": "dividerColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "iconColor",
+                        "notify": "themeChanged",
+                        "read": "iconColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "iconDisabledColor",
+                        "notify": "themeChanged",
+                        "read": "iconDisabledColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "frameColor",
+                        "notify": "themeChanged",
+                        "read": "frameColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "rippleColor",
+                        "notify": "themeChanged",
+                        "read": "rippleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "highlightedRippleColor",
+                        "notify": "themeOrAccentChanged",
+                        "read": "highlightedRippleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "switchUncheckedTrackColor",
+                        "notify": "themeChanged",
+                        "read": "switchUncheckedTrackColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "switchCheckedTrackColor",
+                        "notify": "themeOrAccentChanged",
+                        "read": "switchCheckedTrackColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "switchUncheckedHandleColor",
+                        "notify": "themeChanged",
+                        "read": "switchUncheckedHandleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "switchUncheckedHoveredHandleColor",
+                        "notify": "themeChanged",
+                        "read": "switchUncheckedHoveredHandleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "switchDisabledUncheckedTrackColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledUncheckedTrackColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "switchDisabledCheckedTrackColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledCheckedTrackColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 29,
+                        "name": "switchDisabledUncheckedTrackBorderColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledUncheckedTrackBorderColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 30,
+                        "name": "switchCheckedHandleColor",
+                        "notify": "themeOrAccentChanged",
+                        "read": "switchCheckedHandleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 31,
+                        "name": "switchDisabledUncheckedHandleColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledUncheckedHandleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 32,
+                        "name": "switchDisabledCheckedHandleColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledCheckedHandleColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 33,
+                        "name": "switchDisabledCheckedIconColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledCheckedIconColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 34,
+                        "name": "switchDisabledUncheckedIconColor",
+                        "notify": "themeChanged",
+                        "read": "switchDisabledUncheckedIconColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 35,
+                        "name": "scrollBarColor",
+                        "notify": "themeChanged",
+                        "read": "scrollBarColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 36,
+                        "name": "scrollBarHoveredColor",
+                        "notify": "themeChanged",
+                        "read": "scrollBarHoveredColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 37,
+                        "name": "scrollBarPressedColor",
+                        "notify": "themeChanged",
+                        "read": "scrollBarPressedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 38,
+                        "name": "dialogColor",
+                        "notify": "dialogColorChanged",
+                        "read": "dialogColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 39,
+                        "name": "backgroundDimColor",
+                        "notify": "themeChanged",
+                        "read": "backgroundDimColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 40,
+                        "name": "listHighlightColor",
+                        "notify": "themeChanged",
+                        "read": "listHighlightColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 41,
+                        "name": "tooltipColor",
+                        "notify": "tooltipColorChanged",
+                        "read": "tooltipColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 42,
+                        "name": "toolBarColor",
+                        "notify": "toolBarColorChanged",
+                        "read": "toolBarColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 43,
+                        "name": "toolTextColor",
+                        "notify": "toolTextColorChanged",
+                        "read": "toolTextColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 44,
+                        "name": "spinBoxDisabledIconColor",
+                        "notify": "themeChanged",
+                        "read": "spinBoxDisabledIconColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 45,
+                        "name": "sliderDisabledColor",
+                        "notify": "themeChanged",
+                        "read": "sliderDisabledColor",
+                        "required": false,
+                        "revision": 527,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 46,
+                        "name": "textFieldFilledContainerColor",
+                        "notify": "themeChanged",
+                        "read": "textFieldFilledContainerColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 47,
+                        "name": "touchTarget",
+                        "read": "touchTarget",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 48,
+                        "name": "buttonVerticalPadding",
+                        "read": "buttonVerticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 49,
+                        "name": "buttonHeight",
+                        "read": "buttonHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 50,
+                        "name": "delegateHeight",
+                        "read": "delegateHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 51,
+                        "name": "dialogButtonBoxHeight",
+                        "read": "dialogButtonBoxHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 52,
+                        "name": "dialogTitleFontPixelSize",
+                        "read": "dialogTitleFontPixelSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 53,
+                        "name": "dialogRoundedScale",
+                        "read": "dialogRoundedScale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RoundedScale",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 54,
+                        "name": "frameVerticalPadding",
+                        "read": "frameVerticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 55,
+                        "name": "menuItemHeight",
+                        "read": "menuItemHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 56,
+                        "name": "menuItemVerticalPadding",
+                        "read": "menuItemVerticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 57,
+                        "name": "switchIndicatorWidth",
+                        "read": "switchIndicatorWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 58,
+                        "name": "switchIndicatorHeight",
+                        "read": "switchIndicatorHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 59,
+                        "name": "switchNormalHandleHeight",
+                        "read": "switchNormalHandleHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 60,
+                        "name": "switchCheckedHandleHeight",
+                        "read": "switchCheckedHandleHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 61,
+                        "name": "switchLargestHandleHeight",
+                        "read": "switchLargestHandleHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 62,
+                        "name": "switchDelegateVerticalPadding",
+                        "read": "switchDelegateVerticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 63,
+                        "name": "textFieldHeight",
+                        "read": "textFieldHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 64,
+                        "name": "textFieldHorizontalPadding",
+                        "read": "textFieldHorizontalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 65,
+                        "name": "textFieldVerticalPadding",
+                        "read": "textFieldVerticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 66,
+                        "name": "tooltipHeight",
+                        "read": "tooltipHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialStyle",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "themeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "primaryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "accentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "foregroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "backgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "elevationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "themeOrAccentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "primaryHighlightedTextColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "dialogColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "tooltipColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "toolBarColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "toolTextColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "roundedScaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "containerStyleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAttachedPropertyPropagator"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialstyle_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2materialstyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2materialstyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0cbc620e2ef5cb0a79724b3368285e3b7bdaa113
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2materialstyleimpl_metatypes.json
@@ -0,0 +1,687 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FloatingPlaceholderText"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1541"
+                    }
+                ],
+                "className": "QQuickMaterialPlaceholderText",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "filled",
+                        "notify": "filledChanged",
+                        "read": "isFilled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFilled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "controlHasActiveFocus",
+                        "notify": "controlHasActiveFocusChanged",
+                        "read": "controlHasActiveFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setControlHasActiveFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "controlHasText",
+                        "notify": "controlHasTextChanged",
+                        "read": "controlHasText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setControlHasText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "largestHeight",
+                        "notify": "largestHeightChanged",
+                        "read": "largestHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "verticalPadding",
+                        "notify": "verticalPaddingChanged",
+                        "read": "verticalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setVerticalPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "controlImplicitBackgroundHeight",
+                        "notify": "controlImplicitBackgroundHeightChanged",
+                        "read": "controlImplicitBackgroundHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setControlImplicitBackgroundHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "controlHeight",
+                        "read": "controlHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setControlHeight"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialPlaceholderText",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "filledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "largestHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "controlHasActiveFocusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "controlHasTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "controlImplicitBackgroundHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "verticalPaddingChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "adjustTransformOrigin",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPlaceholderText"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialplaceholdertext_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MaterialTextContainer"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1541"
+                    }
+                ],
+                "className": "QQuickMaterialTextContainer",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PlaceHolderHAlignment",
+                        "values": [
+                            "AlignLeft",
+                            "AlignRight",
+                            "AlignHCenter",
+                            "AlignJustify"
+                        ]
+                    }
+                ],
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "filled",
+                        "read": "isFilled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFilled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "controlHasActiveFocus",
+                        "notify": "controlHasActiveFocusChanged",
+                        "read": "controlHasActiveFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setControlHasActiveFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "fillColor",
+                        "read": "fillColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setFillColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "outlineColor",
+                        "read": "outlineColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setOutlineColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "focusedOutlineColor",
+                        "read": "focusedOutlineColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setFocusedOutlineColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "focusAnimationProgress",
+                        "read": "focusAnimationProgress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFocusAnimationProgress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "placeholderTextWidth",
+                        "read": "placeholderTextWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPlaceholderTextWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "placeholderTextHAlign",
+                        "read": "placeholderTextHAlign",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "PlaceHolderHAlignment",
+                        "user": false,
+                        "write": "setPlaceholderTextHAlign"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "controlHasText",
+                        "notify": "controlHasTextChanged",
+                        "read": "controlHasText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setControlHasText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "placeholderHasText",
+                        "notify": "placeholderHasTextChanged",
+                        "read": "placeholderHasText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPlaceholderHasText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "horizontalPadding",
+                        "notify": "horizontalPaddingChanged",
+                        "read": "horizontalPadding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHorizontalPadding"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialTextContainer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "animateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "controlHasActiveFocusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "controlHasTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "placeholderHasTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "horizontalPaddingChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialtextcontainer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BusyIndicatorImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMaterialBusyIndicator",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "running",
+                        "read": "isRunning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialBusyIndicator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialbusyindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ProgressBarImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMaterialProgressBar",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "progress",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setProgress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "indeterminate",
+                        "read": "isIndeterminate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIndeterminate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialProgressBar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialprogressbar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Ripple"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMaterialRipple",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Trigger",
+                        "values": [
+                            "Press",
+                            "Release"
+                        ]
+                    }
+                ],
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "clipRadius",
+                        "read": "clipRadius",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setClipRadius"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "pressed",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPressed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "active",
+                        "read": "isActive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setActive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "anchor",
+                        "read": "anchor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setAnchor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "trigger",
+                        "read": "trigger",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Trigger",
+                        "user": false,
+                        "write": "setTrigger"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaterialRipple",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialripple_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickMaterialRippleBackgroundNode",
+                "lineNumber": 113,
+                "object": true,
+                "qualifiedClassName": "QQuickMaterialRippleBackgroundNode",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAnimatedNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaterialripple.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universal_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universal_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..78e9f2c9a9c848cebd632cd9d1f7038c67420243
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universal_metatypes.json
@@ -0,0 +1,529 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Universal"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickUniversalStyle"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickUniversalStyle",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Theme",
+                        "values": [
+                            "Light",
+                            "Dark",
+                            "System"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Color",
+                        "values": [
+                            "Lime",
+                            "Green",
+                            "Emerald",
+                            "Teal",
+                            "Cyan",
+                            "Cobalt",
+                            "Indigo",
+                            "Violet",
+                            "Pink",
+                            "Magenta",
+                            "Crimson",
+                            "Red",
+                            "Orange",
+                            "Amber",
+                            "Yellow",
+                            "Brown",
+                            "Olive",
+                            "Steel",
+                            "Mauve",
+                            "Taupe"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "Color"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "color",
+                        "returnType": "QColor"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "theme",
+                        "notify": "themeChanged",
+                        "read": "theme",
+                        "required": false,
+                        "reset": "resetTheme",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Theme",
+                        "user": false,
+                        "write": "setTheme"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "accent",
+                        "notify": "accentChanged",
+                        "read": "accent",
+                        "required": false,
+                        "reset": "resetAccent",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setAccent"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "foreground",
+                        "notify": "foregroundChanged",
+                        "read": "foreground",
+                        "required": false,
+                        "reset": "resetForeground",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setForeground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "reset": "resetBackground",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "altHighColor",
+                        "notify": "paletteChanged",
+                        "read": "altHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "altLowColor",
+                        "notify": "paletteChanged",
+                        "read": "altLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "altMediumColor",
+                        "notify": "paletteChanged",
+                        "read": "altMediumColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "altMediumHighColor",
+                        "notify": "paletteChanged",
+                        "read": "altMediumHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "altMediumLowColor",
+                        "notify": "paletteChanged",
+                        "read": "altMediumLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "baseHighColor",
+                        "notify": "paletteChanged",
+                        "read": "baseHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "baseLowColor",
+                        "notify": "paletteChanged",
+                        "read": "baseLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "baseMediumColor",
+                        "notify": "paletteChanged",
+                        "read": "baseMediumColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "baseMediumHighColor",
+                        "notify": "paletteChanged",
+                        "read": "baseMediumHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "baseMediumLowColor",
+                        "notify": "paletteChanged",
+                        "read": "baseMediumLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "chromeAltLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeAltLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "chromeBlackHighColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeBlackHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "chromeBlackLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeBlackLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "chromeBlackMediumLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeBlackMediumLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "chromeBlackMediumColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeBlackMediumColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "chromeDisabledHighColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeDisabledHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "chromeDisabledLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeDisabledLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "chromeHighColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeHighColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "chromeLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "chromeMediumColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeMediumColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "chromeMediumLowColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeMediumLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "chromeWhiteColor",
+                        "notify": "paletteChanged",
+                        "read": "chromeWhiteColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "listLowColor",
+                        "notify": "paletteChanged",
+                        "read": "listLowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "listMediumColor",
+                        "notify": "paletteChanged",
+                        "read": "listMediumColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickUniversalStyle",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "themeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "accentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "foregroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "backgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "paletteChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAttachedPropertyPropagator"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickuniversalstyle_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universalstyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universalstyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..5257860756c81983a9c35f12a36c2f57c28e7364
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2universalstyleimpl_metatypes.json
@@ -0,0 +1,160 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BusyIndicatorImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickUniversalBusyIndicator",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    }
+                ],
+                "qualifiedClassName": "QQuickUniversalBusyIndicator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickuniversalbusyindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FocusRectangle"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickUniversalFocusRectangle",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQuickUniversalFocusRectangle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPaintedItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickuniversalfocusrectangle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ProgressBarImpl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickUniversalProgressBar",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "progress",
+                        "read": "progress",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setProgress"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "indeterminate",
+                        "read": "isIndeterminate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIndeterminate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickUniversalProgressBar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickuniversalprogressbar_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2windowsstyleimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2windowsstyleimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrols2windowsstyleimpl_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrolstestutilsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrolstestutilsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0131ca00a0de8f260014d07817adaef164d16042
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickcontrolstestutilsprivate_metatypes.json
@@ -0,0 +1,81 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "auto"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    }
+                ],
+                "className": "ComponentCreator",
+                "lineNumber": 59,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "data",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "createComponent",
+                        "returnType": "QQmlComponent*"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickControlsTestUtils::ComponentCreator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "auto"
+                    },
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    }
+                ],
+                "className": "StyleInfo",
+                "lineNumber": 70,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "styleName",
+                        "read": "styleName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickControlsTestUtils::StyleInfo",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "controlstestutils_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..9210c6ebb16460796f61d2b86ad0efdf88e7a26e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2_metatypes.json
@@ -0,0 +1,1038 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1540"
+                    }
+                ],
+                "className": "QQuickColorDialog",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "selectedColor",
+                        "notify": "selectedColorChanged",
+                        "read": "selectedColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setSelectedColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColorDialogOptions::ColorDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QQuickColorDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "selectedColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcolordialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickAbstractDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardCode",
+                        "values": [
+                            "Rejected",
+                            "Accepted"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 35,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "data",
+                        "read": "data",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "parentWindow",
+                        "notify": "parentWindowChanged",
+                        "read": "parentWindow",
+                        "required": false,
+                        "reset": "resetParentWindow",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QWindow*",
+                        "user": false,
+                        "write": "setParentWindow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "flags",
+                        "notify": "flagsChanged",
+                        "read": "flags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowFlags",
+                        "user": false,
+                        "write": "setFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "modality",
+                        "notify": "modalityChanged",
+                        "read": "modality",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowModality",
+                        "user": false,
+                        "write": "setModality"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "result",
+                        "notify": "resultChanged",
+                        "read": "result",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setResult"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAbstractDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "rejected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "parentWindowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "flagsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "modalityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resultChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "open",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "close",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "accept",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "reject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickabstractdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FileDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFileDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FileMode",
+                        "values": [
+                            "OpenFile",
+                            "OpenFiles",
+                            "SaveFile"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "fileMode",
+                        "notify": "fileModeChanged",
+                        "read": "fileMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FileMode",
+                        "user": false,
+                        "write": "setFileMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "selectedFile",
+                        "notify": "selectedFileChanged",
+                        "read": "selectedFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSelectedFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "selectedFiles",
+                        "notify": "selectedFilesChanged",
+                        "read": "selectedFiles",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QUrl>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "currentFile",
+                        "notify": "currentFileChanged",
+                        "read": "currentFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "currentFiles",
+                        "notify": "currentFilesChanged",
+                        "read": "currentFiles",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QUrl>",
+                        "user": false,
+                        "write": "setCurrentFiles"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "currentFolder",
+                        "notify": "currentFolderChanged",
+                        "read": "currentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFileDialogOptions::FileDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "nameFilters",
+                        "notify": "nameFiltersChanged",
+                        "read": "nameFilters",
+                        "required": false,
+                        "reset": "resetNameFilters",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setNameFilters"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "selectedNameFilter",
+                        "read": "selectedNameFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickFileNameFilter*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "defaultSuffix",
+                        "notify": "defaultSuffixChanged",
+                        "read": "defaultSuffix",
+                        "required": false,
+                        "reset": "resetDefaultSuffix",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDefaultSuffix"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "acceptLabel",
+                        "notify": "acceptLabelChanged",
+                        "read": "acceptLabel",
+                        "required": false,
+                        "reset": "resetAcceptLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAcceptLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "rejectLabel",
+                        "notify": "rejectLabelChanged",
+                        "read": "rejectLabel",
+                        "required": false,
+                        "reset": "resetRejectLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setRejectLabel"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFileDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fileModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "selectedFileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "selectedFilesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "currentFileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "currentFilesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "currentFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "nameFiltersChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "defaultSuffixChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "acceptLabelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "rejectLabelChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfiledialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FolderDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickFolderDialog",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "currentFolder",
+                        "notify": "currentFolderChanged",
+                        "read": "currentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "selectedFolder",
+                        "notify": "selectedFolderChanged",
+                        "read": "selectedFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSelectedFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFileDialogOptions::FileDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "acceptLabel",
+                        "notify": "acceptLabelChanged",
+                        "read": "acceptLabel",
+                        "required": false,
+                        "reset": "resetAcceptLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAcceptLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "rejectLabel",
+                        "notify": "rejectLabelChanged",
+                        "read": "rejectLabel",
+                        "required": false,
+                        "reset": "resetRejectLabel",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setRejectLabel"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFolderDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "currentFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "selectedFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "acceptLabelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "rejectLabelChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfolderdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FontDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFontDialog",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "selectedFont",
+                        "notify": "selectedFontChanged",
+                        "read": "selectedFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setSelectedFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "currentFont",
+                        "notify": "currentFontChanged",
+                        "read": "currentFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setCurrentFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "options",
+                        "notify": "optionsChanged",
+                        "read": "options",
+                        "required": false,
+                        "reset": "resetOptions",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFontDialogOptions::FontDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFontDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "selectedFontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentFontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfontdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Extended",
+                        "value": "QPlatformDialogHelper"
+                    },
+                    {
+                        "name": "QML.ExtensionIsNamespace",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "MessageDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickMessageDialog",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "informativeText",
+                        "notify": "informativeTextChanged",
+                        "read": "informativeText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setInformativeText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "detailedText",
+                        "notify": "detailedTextChanged",
+                        "read": "detailedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDetailedText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "buttons",
+                        "notify": "buttonsChanged",
+                        "read": "buttons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPlatformDialogHelper::StandardButtons",
+                        "user": false,
+                        "write": "setButtons"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMessageDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "informativeTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "detailedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "buttonsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QPlatformDialogHelper::ButtonRole"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QPlatformDialogHelper::ButtonRole"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "handleClick",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmessagedialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickFileNameFilter"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFileNameFilterQuickDialogs2Foreign",
+                "gadget": true,
+                "lineNumber": 24,
+                "qualifiedClassName": "QQuickFileNameFilterQuickDialogs2Foreign"
+            }
+        ],
+        "inputFile": "qtquickdialogs2foreign_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2quickimpl_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2quickimpl_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b2158dcd01b5f83280e9fc437e478edd8b75ce2
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2quickimpl_metatypes.json
@@ -0,0 +1,2554 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background,contentItem,handle"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "AbstractColorPicker"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1540"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "AbstractColorPicker is abstract."
+                    }
+                ],
+                "className": "QQuickAbstractColorPicker",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "hue",
+                        "notify": "colorChanged",
+                        "read": "hue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "saturation",
+                        "notify": "colorChanged",
+                        "read": "saturation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSaturation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "value",
+                        "notify": "colorChanged",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "lightness",
+                        "notify": "colorChanged",
+                        "read": "lightness",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLightness"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "alpha",
+                        "notify": "colorChanged",
+                        "read": "alpha",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAlpha"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPressed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "handle",
+                        "notify": "handleChanged",
+                        "read": "handle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setHandle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "implicitHandleWidth",
+                        "notify": "implicitHandleWidthChanged",
+                        "read": "implicitHandleWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "implicitHandleHeight",
+                        "notify": "implicitHandleHeightChanged",
+                        "read": "implicitHandleHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickAbstractColorPicker",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "handleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "implicitHandleWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "implicitHandleHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "colorPicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickabstractcolorpicker_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorDialogImpl"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickColorDialogImplAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1540"
+                    }
+                ],
+                "className": "QQuickColorDialogImpl",
+                "lineNumber": 33,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "invokeEyeDropper",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "hue",
+                        "notify": "colorChanged",
+                        "read": "hue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "saturation",
+                        "notify": "colorChanged",
+                        "read": "saturation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSaturation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "value",
+                        "notify": "colorChanged",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "lightness",
+                        "notify": "colorChanged",
+                        "read": "lightness",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLightness"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "alpha",
+                        "notify": "colorChanged",
+                        "read": "alpha",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAlpha"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "red",
+                        "notify": "colorChanged",
+                        "read": "red",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "green",
+                        "notify": "colorChanged",
+                        "read": "green",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setGreen"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "blue",
+                        "notify": "colorChanged",
+                        "read": "blue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setBlue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "isHsl",
+                        "notify": "specChanged",
+                        "read": "isHsl",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHsl"
+                    }
+                ],
+                "qualifiedClassName": "QQuickColorDialogImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "specChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDialog"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickColorDialogImplAttached",
+                "lineNumber": 99,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "buttonBox",
+                        "notify": "buttonBoxChanged",
+                        "read": "buttonBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialogButtonBox*",
+                        "user": false,
+                        "write": "setButtonBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "eyeDropperButton",
+                        "notify": "eyeDropperButtonChanged",
+                        "read": "eyeDropperButton",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAbstractButton*",
+                        "user": false,
+                        "write": "setEyeDropperButton"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "colorPicker",
+                        "notify": "colorPickerChanged",
+                        "read": "colorPicker",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAbstractColorPicker*",
+                        "user": false,
+                        "write": "setColorPicker"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "colorInputs",
+                        "notify": "colorInputsChanged",
+                        "read": "colorInputs",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickColorInputs*",
+                        "user": false,
+                        "write": "setColorInputs"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "alphaSlider",
+                        "notify": "alphaSliderChanged",
+                        "read": "alphaSlider",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickSlider*",
+                        "user": false,
+                        "write": "setAlphaSlider"
+                    }
+                ],
+                "qualifiedClassName": "QQuickColorDialogImplAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "buttonBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "eyeDropperButtonChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "colorPickerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "colorInputsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "alphaSliderChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcolordialogimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ColorInputsImpl"
+                    }
+                ],
+                "className": "QQuickColorInputs",
+                "lineNumber": 30,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "color",
+                        "notify": "colorChanged",
+                        "read": "color",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "red",
+                        "notify": "colorChanged",
+                        "read": "red",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "green",
+                        "notify": "colorChanged",
+                        "read": "green",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "blue",
+                        "notify": "colorChanged",
+                        "read": "blue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "hue",
+                        "notify": "colorChanged",
+                        "read": "hue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "hslSaturation",
+                        "notify": "colorChanged",
+                        "read": "hslSaturation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "hsvSaturation",
+                        "notify": "colorChanged",
+                        "read": "hsvSaturation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "value",
+                        "notify": "colorChanged",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "lightness",
+                        "notify": "colorChanged",
+                        "read": "lightness",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "alpha",
+                        "notify": "colorChanged",
+                        "read": "alpha",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "showAlpha",
+                        "notify": "showAlphaChanged",
+                        "read": "showAlpha",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowAlpha"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "hexInput",
+                        "notify": "hexInputChanged",
+                        "read": "hexInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHexInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "redInput",
+                        "notify": "redInputChanged",
+                        "read": "redInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setRedInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "greenInput",
+                        "notify": "greenInputChanged",
+                        "read": "greenInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setGreenInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "blueInput",
+                        "notify": "blueInputChanged",
+                        "read": "blueInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setBlueInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "hsvHueInput",
+                        "notify": "hsvHueInputChanged",
+                        "read": "hsvHueInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHsvHueInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "hslHueInput",
+                        "notify": "hslHueInputChanged",
+                        "read": "hslHueInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHslHueInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "hsvSaturationInput",
+                        "notify": "hsvSaturationInputChanged",
+                        "read": "hsvSaturationInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHsvSaturationInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "hslSaturationInput",
+                        "notify": "hslSaturationInputChanged",
+                        "read": "hslSaturationInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHslSaturationInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "valueInput",
+                        "notify": "valueInputChanged",
+                        "read": "valueInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setValueInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "lightnessInput",
+                        "notify": "lightnessInputChanged",
+                        "read": "lightnessInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setLightnessInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "rgbAlphaInput",
+                        "notify": "rgbAlphaInputChanged",
+                        "read": "rgbAlphaInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setRgbAlphaInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "hsvAlphaInput",
+                        "notify": "hsvAlphaInputChanged",
+                        "read": "hsvAlphaInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHsvAlphaInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "hslAlphaInput",
+                        "notify": "hslAlphaInputChanged",
+                        "read": "hslAlphaInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextInput*",
+                        "user": false,
+                        "write": "setHslAlphaInput"
+                    }
+                ],
+                "qualifiedClassName": "QQuickColorInputs",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "c",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "c",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "colorModified",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "hslChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "showAlphaChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "hexInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "redInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "greenInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "blueInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "hsvHueInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "hslHueInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "hsvSaturationInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "hslSaturationInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "valueInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "lightnessInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "rgbAlphaInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "hsvAlphaInputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "hslAlphaInputChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcolorinputs_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPlatformColorDialog",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformColorDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformColorDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformcolordialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "SaturationLightnessPickerImpl"
+                    }
+                ],
+                "className": "QQuickSaturationLightnessPicker",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQuickSaturationLightnessPicker",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractColorPicker"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicksaturationlightnesspicker_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FileDialogDelegate"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFileDialogDelegate",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "dialog",
+                        "notify": "dialogChanged",
+                        "read": "dialog",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialog*",
+                        "user": false,
+                        "write": "setDialog"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "file",
+                        "notify": "fileChanged",
+                        "read": "file",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setFile"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFileDialogDelegate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "dialogChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "fileChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfiledialogdelegate_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FileDialogImpl"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickFileDialogImplAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFileDialogImpl",
+                "lineNumber": 36,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "currentFolder",
+                        "notify": "currentFolderChanged",
+                        "read": "currentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "selectedFile",
+                        "notify": "selectedFileChanged",
+                        "read": "selectedFile",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSelectedFile"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "nameFilters",
+                        "notify": "nameFiltersChanged",
+                        "read": "nameFilters",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "selectedNameFilter",
+                        "read": "selectedNameFilter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickFileNameFilter*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "fileName",
+                        "notify": "selectedFileChanged",
+                        "read": "fileName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setFileName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "currentFolderName",
+                        "notify": "selectedFileChanged",
+                        "read": "currentFolderName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickFileDialogImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "folderUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "selectedFileUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "selectedFileChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "nameFiltersChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fileUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "fileSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "filterSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "selectNameFilter",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDialog"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickFileDialogImplAttached",
+                "lineNumber": 104,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "buttonBox",
+                        "notify": "buttonBoxChanged",
+                        "read": "buttonBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialogButtonBox*",
+                        "user": false,
+                        "write": "setButtonBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "nameFiltersComboBox",
+                        "notify": "nameFiltersComboBoxChanged",
+                        "read": "nameFiltersComboBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickComboBox*",
+                        "user": false,
+                        "write": "setNameFiltersComboBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "fileDialogListView",
+                        "notify": "fileDialogListViewChanged",
+                        "read": "fileDialogListView",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickListView*",
+                        "user": false,
+                        "write": "setFileDialogListView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "breadcrumbBar",
+                        "notify": "breadcrumbBarChanged",
+                        "read": "breadcrumbBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickFolderBreadcrumbBar*",
+                        "user": false,
+                        "write": "setBreadcrumbBar"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "fileNameLabel",
+                        "notify": "fileNameLabelChanged",
+                        "read": "fileNameLabel",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLabel*",
+                        "user": false,
+                        "write": "setFileNameLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "fileNameTextField",
+                        "notify": "fileNameTextFieldChanged",
+                        "read": "fileNameTextField",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextField*",
+                        "user": false,
+                        "write": "setFileNameTextField"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "overwriteConfirmationDialog",
+                        "notify": "overwriteConfirmationDialogChanged",
+                        "read": "overwriteConfirmationDialog",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialog*",
+                        "user": false,
+                        "write": "setOverwriteConfirmationDialog"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFileDialogImplAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "buttonBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "nameFiltersComboBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "fileDialogListViewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "breadcrumbBarChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "fileNameLabelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "fileNameTextFieldChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "overwriteConfirmationDialogChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfiledialogimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FolderBreadcrumbBar"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFolderBreadcrumbBar",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "dialog",
+                        "notify": "dialogChanged",
+                        "read": "dialog",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialog*",
+                        "user": false,
+                        "write": "setDialog"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "buttonDelegate",
+                        "notify": "buttonDelegateChanged",
+                        "read": "buttonDelegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setButtonDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "separatorDelegate",
+                        "notify": "separatorDelegateChanged",
+                        "read": "separatorDelegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setSeparatorDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "upButton",
+                        "notify": "upButtonChanged",
+                        "read": "upButton",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAbstractButton*",
+                        "user": false,
+                        "write": "setUpButton"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "textField",
+                        "notify": "textFieldChanged",
+                        "read": "textField",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextField*",
+                        "user": false,
+                        "write": "setTextField"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "upButtonSpacing",
+                        "notify": "upButtonSpacingChanged",
+                        "read": "upButtonSpacing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setUpButtonSpacing"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFolderBreadcrumbBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "dialogChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "buttonDelegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "separatorDelegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "upButtonChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "upButtonSpacingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "textFieldChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickContainer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfolderbreadcrumbbar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FolderDialogImpl"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickFolderDialogImplAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickFolderDialogImpl",
+                "lineNumber": 32,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "currentFolder",
+                        "notify": "currentFolderChanged",
+                        "read": "currentFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setCurrentFolder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "selectedFolder",
+                        "notify": "selectedFolderChanged",
+                        "read": "selectedFolder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSelectedFolder"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFolderDialogImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "folderUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "folderUrl",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "selectedFolderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "nameFiltersChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDialog"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickFolderDialogImplAttached",
+                "lineNumber": 71,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "folderDialogListView",
+                        "notify": "folderDialogListViewChanged",
+                        "read": "folderDialogListView",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickListView*",
+                        "user": false,
+                        "write": "setFolderDialogListView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "breadcrumbBar",
+                        "notify": "breadcrumbBarChanged",
+                        "read": "breadcrumbBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickFolderBreadcrumbBar*",
+                        "user": false,
+                        "write": "setBreadcrumbBar"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFolderDialogImplAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "folderDialogListViewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "breadcrumbBarChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfolderdialogimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "FontDialogImpl"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickFontDialogImplAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFontDialogImpl",
+                "lineNumber": 35,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "currentFont",
+                        "notify": "currentFontChanged",
+                        "read": "currentFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setCurrentFont"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFontDialogImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "font",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "currentFontChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDialog"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickFontDialogImplAttached",
+                "lineNumber": 68,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "familyListView",
+                        "notify": "familyListViewChanged",
+                        "read": "familyListView",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickListView*",
+                        "user": false,
+                        "write": "setFamilyListView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "styleListView",
+                        "notify": "styleListViewChanged",
+                        "read": "styleListView",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickListView*",
+                        "user": false,
+                        "write": "setStyleListView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sizeListView",
+                        "notify": "sizeListViewChanged",
+                        "read": "sizeListView",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickListView*",
+                        "user": false,
+                        "write": "setSizeListView"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "sampleEdit",
+                        "notify": "sampleEditChanged",
+                        "read": "sampleEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextEdit*",
+                        "user": false,
+                        "write": "setSampleEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "buttonBox",
+                        "notify": "buttonBoxChanged",
+                        "read": "buttonBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialogButtonBox*",
+                        "user": false,
+                        "write": "setButtonBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "writingSystemComboBox",
+                        "notify": "writingSystemComboBoxChanged",
+                        "read": "writingSystemComboBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickComboBox*",
+                        "user": false,
+                        "write": "setWritingSystemComboBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "underlineCheckBox",
+                        "notify": "underlineCheckBoxChanged",
+                        "read": "underlineCheckBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickCheckBox*",
+                        "user": false,
+                        "write": "setUnderlineCheckBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "strikeoutCheckBox",
+                        "notify": "strikeoutCheckBoxChanged",
+                        "read": "strikeoutCheckBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickCheckBox*",
+                        "user": false,
+                        "write": "setStrikeoutCheckBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "familyEdit",
+                        "notify": "familyEditChanged",
+                        "read": "familyEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextField*",
+                        "user": false,
+                        "write": "setFamilyEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "styleEdit",
+                        "notify": "styleEditChanged",
+                        "read": "styleEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextField*",
+                        "user": false,
+                        "write": "setStyleEdit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "sizeEdit",
+                        "notify": "sizeEditChanged",
+                        "read": "sizeEdit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTextField*",
+                        "user": false,
+                        "write": "setSizeEdit"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFontDialogImplAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "buttonBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "familyListViewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "styleListViewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "sizeListViewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "sampleEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "writingSystemComboBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "underlineCheckBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "strikeoutCheckBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "familyEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "styleEditChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "sizeEditChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfontdialogimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MessageDialogImpl"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickMessageDialogImplAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickMessageDialogImpl",
+                "lineNumber": 32,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "optionsChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "informativeText",
+                        "notify": "optionsChanged",
+                        "read": "informativeText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "detailedText",
+                        "notify": "optionsChanged",
+                        "read": "detailedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "showDetailedText",
+                        "notify": "showDetailedTextChanged",
+                        "read": "showDetailedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMessageDialogImpl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QPlatformDialogHelper::StandardButton"
+                            },
+                            {
+                                "name": "role",
+                                "type": "QPlatformDialogHelper::ButtonRole"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "showDetailedTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "optionsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "toggleShowDetailedText",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDialog"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickMessageDialogImplAttached",
+                "lineNumber": 69,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "buttonBox",
+                        "notify": "buttonBoxChanged",
+                        "read": "buttonBox",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDialogButtonBox*",
+                        "user": false,
+                        "write": "setButtonBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "detailedTextButton",
+                        "notify": "detailedTextButtonChanged",
+                        "read": "detailedTextButton",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickButton*",
+                        "user": false,
+                        "write": "setDetailedTextButton"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMessageDialogImplAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "buttonBoxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "detailedTextButtonChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmessagedialogimpl_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPlatformFileDialog",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformFileDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformFileDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformfiledialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPlatformFolderDialog",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformFolderDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformFileDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformfolderdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPlatformFontDialog",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformFontDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformFontDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformfontdialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickPlatformMessageDialog",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQuickPlatformMessageDialog",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPlatformMessageDialogHelper"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickplatformmessagedialog_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickFileNameFilter"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickFileNameFilterQuickDialogs2QuickImplForeign",
+                "gadget": true,
+                "lineNumber": 28,
+                "qualifiedClassName": "QQuickFileNameFilterQuickDialogs2QuickImplForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickControl"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickControlForeign",
+                "gadget": true,
+                "lineNumber": 39,
+                "qualifiedClassName": "QQuickControlForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickAbstractButton"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAbstractButtonForeign",
+                "gadget": true,
+                "lineNumber": 47,
+                "qualifiedClassName": "QQuickAbstractButtonForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickIcon"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1538"
+                    }
+                ],
+                "className": "QQuickIconForeign",
+                "gadget": true,
+                "lineNumber": 55,
+                "qualifiedClassName": "QQuickIconForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickPopup"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPopupForeign",
+                "gadget": true,
+                "lineNumber": 64,
+                "qualifiedClassName": "QQuickPopupForeign"
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.Foreign",
+                        "value": "QQuickDialog"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    }
+                ],
+                "className": "QQuickDialogForeign",
+                "gadget": true,
+                "lineNumber": 72,
+                "qualifiedClassName": "QQuickDialogForeign"
+            }
+        ],
+        "inputFile": "qtquickdialogs2quickimplforeign_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2utils_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2utils_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..ef67169b77f0fa5207cc9944f3c0560cb644f5ca
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickdialogs2utils_metatypes.json
@@ -0,0 +1,129 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickFileNameFilter",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "index",
+                        "notify": "indexChanged",
+                        "read": "index",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "name",
+                        "notify": "nameChanged",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "extensions",
+                        "notify": "extensionsChanged",
+                        "read": "extensions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "globs",
+                        "notify": "globsChanged",
+                        "read": "globs",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickFileNameFilter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "nameChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "extensions",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "extensionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "globs",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "globsChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickfilenamefilter_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickeffectsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickeffectsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..6f40ef45638c533319e33ba144cbc421efeff89a
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickeffectsprivate_metatypes.json
@@ -0,0 +1,818 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QGfxSourceProxyME",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Interpolation",
+                        "values": [
+                            "Any",
+                            "Nearest",
+                            "Linear"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "input",
+                        "notify": "inputChanged",
+                        "read": "input",
+                        "required": false,
+                        "reset": "resetInput",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setInput"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "output",
+                        "notify": "outputChanged",
+                        "read": "output",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "sourceRect",
+                        "notify": "sourceRectChanged",
+                        "read": "sourceRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setSourceRect"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "active",
+                        "notify": "activeChanged",
+                        "read": "isActive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "interpolation",
+                        "notify": "interpolationChanged",
+                        "read": "interpolation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Interpolation",
+                        "user": false,
+                        "write": "setInterpolation"
+                    }
+                ],
+                "qualifiedClassName": "QGfxSourceProxyME",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "inputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "outputChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceRectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "activeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "interpolationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "repolish",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgfxsourceproxy_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MultiEffect"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1541"
+                    }
+                ],
+                "className": "QQuickMultiEffect",
+                "lineNumber": 32,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "autoPaddingEnabled",
+                        "notify": "autoPaddingEnabledChanged",
+                        "read": "autoPaddingEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoPaddingEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "paddingRect",
+                        "notify": "paddingRectChanged",
+                        "read": "paddingRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setPaddingRect"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "brightness",
+                        "notify": "brightnessChanged",
+                        "read": "brightness",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBrightness"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "contrast",
+                        "notify": "contrastChanged",
+                        "read": "contrast",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContrast"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "saturation",
+                        "notify": "saturationChanged",
+                        "read": "saturation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSaturation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "colorization",
+                        "notify": "colorizationChanged",
+                        "read": "colorization",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setColorization"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "colorizationColor",
+                        "notify": "colorizationColorChanged",
+                        "read": "colorizationColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColorizationColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "blurEnabled",
+                        "notify": "blurEnabledChanged",
+                        "read": "blurEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBlurEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "blur",
+                        "notify": "blurChanged",
+                        "read": "blur",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBlur"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "blurMax",
+                        "notify": "blurMaxChanged",
+                        "read": "blurMax",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setBlurMax"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "blurMultiplier",
+                        "notify": "blurMultiplierChanged",
+                        "read": "blurMultiplier",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBlurMultiplier"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "shadowEnabled",
+                        "notify": "shadowEnabledChanged",
+                        "read": "shadowEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShadowEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "shadowOpacity",
+                        "notify": "shadowOpacityChanged",
+                        "read": "shadowOpacity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setShadowOpacity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "shadowBlur",
+                        "notify": "shadowBlurChanged",
+                        "read": "shadowBlur",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setShadowBlur"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "shadowHorizontalOffset",
+                        "notify": "shadowHorizontalOffsetChanged",
+                        "read": "shadowHorizontalOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setShadowHorizontalOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "shadowVerticalOffset",
+                        "notify": "shadowVerticalOffsetChanged",
+                        "read": "shadowVerticalOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setShadowVerticalOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "shadowColor",
+                        "notify": "shadowColorChanged",
+                        "read": "shadowColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setShadowColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "shadowScale",
+                        "notify": "shadowScaleChanged",
+                        "read": "shadowScale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setShadowScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "maskEnabled",
+                        "notify": "maskEnabledChanged",
+                        "read": "maskEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMaskEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "maskSource",
+                        "notify": "maskSourceChanged",
+                        "read": "maskSource",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setMaskSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "maskThresholdMin",
+                        "notify": "maskThresholdMinChanged",
+                        "read": "maskThresholdMin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaskThresholdMin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 22,
+                        "name": "maskSpreadAtMin",
+                        "notify": "maskSpreadAtMinChanged",
+                        "read": "maskSpreadAtMin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaskSpreadAtMin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "maskThresholdMax",
+                        "notify": "maskThresholdMaxChanged",
+                        "read": "maskThresholdMax",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaskThresholdMax"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "maskSpreadAtMax",
+                        "notify": "maskSpreadAtMaxChanged",
+                        "read": "maskSpreadAtMax",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMaskSpreadAtMax"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "maskInverted",
+                        "notify": "maskInvertedChanged",
+                        "read": "maskInverted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMaskInverted"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "itemRect",
+                        "notify": "itemRectChanged",
+                        "read": "itemRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "fragmentShader",
+                        "notify": "fragmentShaderChanged",
+                        "read": "fragmentShader",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "vertexShader",
+                        "notify": "vertexShaderChanged",
+                        "read": "vertexShader",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "hasProxySource",
+                        "notify": "hasProxySourceChanged",
+                        "read": "hasProxySource",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMultiEffect",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "shaderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "itemSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "autoPaddingEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "paddingRectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "brightnessChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "contrastChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "saturationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "colorizationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "colorizationColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "blurEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "blurChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "blurMaxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "blurMultiplierChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "shadowEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "shadowOpacityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "shadowBlurChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "shadowHorizontalOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "shadowVerticalOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "shadowColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "shadowScaleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "maskEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "maskSourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "maskThresholdMinChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "maskSpreadAtMinChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "maskThresholdMaxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "maskSpreadAtMaxChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "maskInvertedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "itemRectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "fragmentShaderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "vertexShaderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "hasProxySourceChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmultieffect_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quicklayouts_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quicklayouts_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..e2b153ae29fab6ce6d90bd7b8e2e4f87a2498c47
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quicklayouts_metatypes.json
@@ -0,0 +1,1405 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LayoutItemProxy"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1542"
+                    }
+                ],
+                "className": "QQuickLayoutItemProxy",
+                "lineNumber": 23,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "name": "effectiveTarget",
+                        "returnType": "QQuickItem*"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "target",
+                        "notify": "targetChanged",
+                        "read": "target",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setTarget"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLayoutItemProxy",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "targetChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "updatePos",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "targetMinimumWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "proxyMinimumWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "targetMinimumHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "proxyMinimumHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "targetPreferredWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "proxyPreferredWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "targetPreferredHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "proxyPreferredHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "targetMaximumWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 11,
+                        "name": "proxyMaximumWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 12,
+                        "name": "targetMaximumHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 13,
+                        "name": "proxyMaximumHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 14,
+                        "name": "targetFillWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "proxyFillWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 16,
+                        "name": "targetFillHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 17,
+                        "name": "proxyFillHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 18,
+                        "name": "targetAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 19,
+                        "name": "proxyAlignmentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 20,
+                        "name": "targetHorizontalStretchFactorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 21,
+                        "name": "proxyHorizontalStretchFactorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 22,
+                        "name": "targetVerticalStretchFactorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 23,
+                        "name": "proxyVerticalStretchFactorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 24,
+                        "name": "targetMarginsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 25,
+                        "name": "proxyMarginsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 26,
+                        "name": "targetLeftMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 27,
+                        "name": "proxyLeftMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 28,
+                        "name": "targetTopMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 29,
+                        "name": "proxyTopMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 30,
+                        "name": "targetRightMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 31,
+                        "name": "proxyRightMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 32,
+                        "name": "targetBottomMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 33,
+                        "name": "proxyBottomMarginChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQuickLayoutItemProxyAttachedData",
+                "lineNumber": 114,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "proxyHasControl",
+                        "notify": "controllingProxyChanged",
+                        "read": "proxyHasControl",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "controllingProxy",
+                        "notify": "controllingProxyChanged",
+                        "read": "getControllingProxy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickLayoutItemProxy*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "proxies",
+                        "notify": "proxiesChanged",
+                        "read": "getProxies",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickLayoutItemProxy>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickLayoutItemProxyAttachedData",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "controlTaken",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "controlReleased",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "controllingProxyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "proxiesChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklayoutitemproxy_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Layout"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Do not create objects of type Layout."
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickLayoutAttached"
+                    }
+                ],
+                "className": "QQuickLayout",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizePolicy",
+                        "values": [
+                            "SizePolicyImplicit",
+                            "SizePolicyExplicit"
+                        ]
+                    }
+                ],
+                "lineNumber": 34,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "_q_dumpLayoutTree",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickLayout",
+                "slots": [
+                    {
+                        "access": "protected",
+                        "index": 0,
+                        "name": "invalidateSenderItem",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQuickItemChangeListener"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickLayoutAttached",
+                "lineNumber": 166,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "minimumWidth",
+                        "notify": "minimumWidthChanged",
+                        "read": "minimumWidth",
+                        "required": false,
+                        "scriptable": true,
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "index",
+                        "notify": "indexChanged",
+                        "read": "index",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "isCurrentItem",
+                        "notify": "isCurrentItemChanged",
+                        "read": "isCurrentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "layout",
+                        "notify": "layoutChanged",
+                        "read": "layout",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickStackLayout*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickStackLayoutAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "isCurrentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "layoutChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickstacklayout_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickparticlesprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickparticlesprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..9682eef848629dc6cbf941bdac2ae24caf6e904d
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickparticlesprivate_metatypes.json
@@ -0,0 +1,5839 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "particle"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1543"
+                    }
+                ],
+                "className": "QQuickV4ParticleData",
+                "gadget": true,
+                "lineNumber": 23,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "discard",
+                        "returnType": "void"
+                    }
+                ],
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "initialX",
+                        "read": "initialX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "initialVX",
+                        "read": "initialVX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialVX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "initialAX",
+                        "read": "initialAX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialAX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "initialY",
+                        "read": "initialY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "initialVY",
+                        "read": "initialVY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialVY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "initialAY",
+                        "read": "initialAY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_initialAY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "t",
+                        "read": "t",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_t"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "startSize",
+                        "read": "startSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_startSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "endSize",
+                        "read": "endSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_endSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "lifeSpan",
+                        "read": "lifeSpan",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_lifeSpan"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "rotation",
+                        "read": "rotation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_rotation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "rotationVelocity",
+                        "read": "rotationVelocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_rotationVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "autoRotate",
+                        "read": "autoRotate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_autoRotate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "update",
+                        "read": "update",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "set_update"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "xDeformationVectorX",
+                        "read": "xDeformationVectorX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_xDeformationVectorX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "yDeformationVectorX",
+                        "read": "yDeformationVectorX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_yDeformationVectorX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "xDeformationVectorY",
+                        "read": "xDeformationVectorY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_xDeformationVectorY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "yDeformationVectorY",
+                        "read": "yDeformationVectorY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_yDeformationVectorY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "animationIndex",
+                        "read": "animationIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_animationIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "frameDuration",
+                        "read": "frameDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_frameDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "frameAt",
+                        "read": "frameAt",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_frameAt"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "frameCount",
+                        "read": "frameCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_frameCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "animationT",
+                        "read": "animationT",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_animationT"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "x",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_x"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "vx",
+                        "read": "vx",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_vx"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "ax",
+                        "read": "ax",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_ax"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "y",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_y"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "vy",
+                        "read": "vy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_vy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "ay",
+                        "read": "ay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_ay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "red",
+                        "read": "red",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_red"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "green",
+                        "read": "green",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_green"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "blue",
+                        "read": "blue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_blue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "alpha",
+                        "read": "alpha",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false,
+                        "write": "set_alpha"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "lifeLeft",
+                        "read": "lifeLeft",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 34,
+                        "name": "currentSize",
+                        "read": "currentSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "float",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickV4ParticleData"
+            }
+        ],
+        "inputFile": "qquickv4particledata_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Age"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAgeAffector",
+                "lineNumber": 21,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "lifeLeft",
+                        "notify": "lifeLeftChanged",
+                        "read": "lifeLeft",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLifeLeft"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "advancePosition",
+                        "notify": "advancePositionChanged",
+                        "read": "advancePosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAdvancePosition"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAgeAffector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "lifeLeftChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "advancePositionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setLifeLeft",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setAdvancePosition",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickage_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AngleDirection"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAngleDirection",
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "angle",
+                        "notify": "angleChanged",
+                        "read": "angle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAngle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "magnitude",
+                        "notify": "magnitudeChanged",
+                        "read": "magnitude",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMagnitude"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "angleVariation",
+                        "notify": "angleVariationChanged",
+                        "read": "angleVariation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAngleVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "magnitudeVariation",
+                        "notify": "magnitudeVariationChanged",
+                        "read": "magnitudeVariation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMagnitudeVariation"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAngleDirection",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "angleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "magnitudeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "angleVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "magnitudeVariationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setAngle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setMagnitude",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setAngleVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setMagnitudeVariation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDirection"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickangledirection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "directions"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "CumulativeDirection"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCumulativeDirection",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "directions",
+                        "read": "directions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickDirection>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickCumulativeDirection",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickDirection"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcumulativedirection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Affector"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCustomAffector",
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "relative",
+                        "notify": "relativeChanged",
+                        "read": "relative",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRelative"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "position",
+                        "notify": "positionChanged",
+                        "read": "position",
+                        "required": false,
+                        "reset": "positionReset",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "velocity",
+                        "notify": "velocityChanged",
+                        "read": "velocity",
+                        "required": false,
+                        "reset": "velocityReset",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "acceleration",
+                        "notify": "accelerationChanged",
+                        "read": "acceleration",
+                        "required": false,
+                        "reset": "accelerationReset",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setAcceleration"
+                    }
+                ],
+                "qualifiedClassName": "QQuickCustomAffector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "particles",
+                                "type": "QList<QQuickV4ParticleData>"
+                            },
+                            {
+                                "name": "dt",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "affectParticles",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "positionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "velocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "accelerationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "relativeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setPosition",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setVelocity",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setAcceleration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setRelative",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcustomaffector_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "NullVector"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Abstract type. Use one of the inheriting types instead."
+                    }
+                ],
+                "className": "QQuickDirection",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QQuickDirection",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickdirection_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "EllipseShape"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickEllipseExtruder",
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "fill",
+                        "notify": "fillChanged",
+                        "read": "fill",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFill"
+                    }
+                ],
+                "qualifiedClassName": "QQuickEllipseExtruder",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fillChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setFill",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleExtruder"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickellipseextruder_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Friction"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickFrictionAffector",
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+                "object": true,
+                "properties": [
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "factor",
+                        "notify": "factorChanged",
+                        "read": "factor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFactor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "threshold",
+                        "notify": "thresholdChanged",
+                        "read": "threshold",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
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+                        "write": "setThreshold"
+                    }
+                ],
+                "qualifiedClassName": "QQuickFrictionAffector",
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "factorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "thresholdChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setFactor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setThreshold",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
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+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Gravity"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickGravityAffector",
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+                "object": true,
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "magnitude",
+                        "notify": "magnitudeChanged",
+                        "read": "magnitude",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMagnitude"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "acceleration",
+                        "notify": "magnitudeChanged",
+                        "read": "magnitude",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAcceleration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "angle",
+                        "notify": "angleChanged",
+                        "read": "angle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAngle"
+                    }
+                ],
+                "qualifiedClassName": "QQuickGravityAffector",
+                "signals": [
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
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+                        ],
+                        "index": 0,
+                        "name": "magnitudeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "angleChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setMagnitude",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setAcceleration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setAngle",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
+            }
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+    },
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+                "classInfos": [
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+                        "name": "QML.Element",
+                        "value": "GroupGoal"
+                    },
+                    {
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+                        "value": "512"
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+                ],
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+                "object": true,
+                "properties": [
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+                        "designable": true,
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+                        "name": "goalState",
+                        "notify": "goalStateChanged",
+                        "read": "goalState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setGoalState"
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+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "jump",
+                        "notify": "jumpChanged",
+                        "read": "jump",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setJump"
+                    }
+                ],
+                "qualifiedClassName": "QQuickGroupGoalAffector",
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "goalStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "jumpChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setGoalState",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "setJump",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "name": "QQuickParticleAffector"
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+                ]
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+    },
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+                ],
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+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading",
+                            "Error"
+                        ]
+                    },
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+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "EntryEffect",
+                        "values": [
+                            "None",
+                            "Fade",
+                            "Scale"
+                        ]
+                    }
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+                "object": true,
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+                        "index": 0,
+                        "name": "source",
+                        "notify": "imageChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setImage"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "sprites",
+                        "read": "sprites",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickSprite>",
+                        "user": false
+                    },
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+                        "final": false,
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+                        "name": "status",
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+                        "stored": true,
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+                    },
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+                        "name": "colorTable",
+                        "notify": "colortableChanged",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
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+                    },
+                    {
+                        "constant": false,
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+                        "final": false,
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+                        "name": "sizeTable",
+                        "notify": "sizetableChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSizetable"
+                    },
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+                        "final": false,
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+                        "notify": "opacitytableChanged",
+                        "read": "opacitytable",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setOpacitytable"
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+                        "stored": true,
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+                        "write": "setColor"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "colorVariation",
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+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
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+                        "write": "setColorVariation"
+                    },
+                    {
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+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRedVariation"
+                    },
+                    {
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+                        "final": false,
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+                        "name": "greenVariation",
+                        "notify": "greenVariationChanged",
+                        "read": "greenVariation",
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+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setGreenVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "blueVariation",
+                        "notify": "blueVariationChanged",
+                        "read": "blueVariation",
+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBlueVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "alpha",
+                        "notify": "alphaChanged",
+                        "read": "alpha",
+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAlpha"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "alphaVariation",
+                        "notify": "alphaVariationChanged",
+                        "read": "alphaVariation",
+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAlphaVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "rotation",
+                        "notify": "rotationChanged",
+                        "read": "rotation",
+                        "required": false,
+                        "reset": "resetRotation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRotation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "rotationVariation",
+                        "notify": "rotationVariationChanged",
+                        "read": "rotationVariation",
+                        "required": false,
+                        "reset": "resetRotation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRotationVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "rotationVelocity",
+                        "notify": "rotationVelocityChanged",
+                        "read": "rotationVelocity",
+                        "required": false,
+                        "reset": "resetRotation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRotationVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "rotationVelocityVariation",
+                        "notify": "rotationVelocityVariationChanged",
+                        "read": "rotationVelocityVariation",
+                        "required": false,
+                        "reset": "resetRotation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRotationVelocityVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "autoRotation",
+                        "notify": "autoRotationChanged",
+                        "read": "autoRotation",
+                        "required": false,
+                        "reset": "resetRotation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRotation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "xVector",
+                        "notify": "xVectorChanged",
+                        "read": "xVector",
+                        "required": false,
+                        "reset": "resetDeformation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setXVector"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 19,
+                        "name": "yVector",
+                        "notify": "yVectorChanged",
+                        "read": "yVector",
+                        "required": false,
+                        "reset": "resetDeformation",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setYVector"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 20,
+                        "name": "spritesInterpolate",
+                        "notify": "spritesInterpolateChanged",
+                        "read": "spritesInterpolate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSpritesInterpolate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 21,
+                        "name": "entryEffect",
+                        "notify": "entryEffectChanged",
+                        "read": "entryEffect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "EntryEffect",
+                        "user": false,
+                        "write": "setEntryEffect"
+                    }
+                ],
+                "qualifiedClassName": "QQuickImageParticle",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "imageChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "colortableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sizetableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "opacitytableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "colorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "colorVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "alphaVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "alphaChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "redVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "greenVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "blueVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "rotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "rotationVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "rotationVelocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "rotationVelocityVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "autoRotationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "xVectorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "yVectorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "spritesInterpolateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "bypassOptimizationsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "EntryEffect"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "entryEffectChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "Status"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "setAlphaVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "setAlpha",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "setRedVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "setGreenVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "setBlueVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "setRotation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "setRotationVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "setRotationVelocity",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "setRotationVelocityVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "setAutoRotation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "setXVector",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "setYVector",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "setSpritesInterpolate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "setBypassOptimizations",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "EntryEffect"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "setEntryEffect",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 37,
+                        "name": "createEngine",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "spriteIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "spriteAdvance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "time",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 39,
+                        "name": "spritesUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 40,
+                        "isCloned": true,
+                        "name": "spritesUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 41,
+                        "name": "mainThreadFetchImageData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 42,
+                        "name": "invalidateSceneGraph",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticlePainter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickimageparticle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ItemParticle"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickItemParticleAttached"
+                    }
+                ],
+                "className": "QQuickItemParticle",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "fade",
+                        "notify": "fadeChanged",
+                        "read": "fade",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFade"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemParticle",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fadeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQmlComponent*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "freeze",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "unfreeze",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            },
+                            {
+                                "name": "prioritize",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "take",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 5,
+                        "isCloned": true,
+                        "name": "take",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "give",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setFade",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQmlComponent*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setDelegate",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticlePainter"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickItemParticleAttached",
+                "lineNumber": 98,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "particle",
+                        "read": "particle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItemParticle*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemParticleAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "detached",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "attached",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitemparticle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "LineShape"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickLineExtruder",
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "mirrored",
+                        "notify": "mirroredChanged",
+                        "read": "mirrored",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMirrored"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLineExtruder",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "mirroredChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setMirrored",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleExtruder"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklineextruder_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MaskShape"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMaskExtruder",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMaskExtruder",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "startMaskLoading",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "finishMaskLoading",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleExtruder"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmaskextruder_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ParticleAffector"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Abstract type. Use one of the inheriting types instead."
+                    }
+                ],
+                "className": "QQuickParticleAffector",
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "system",
+                        "notify": "systemChanged",
+                        "read": "system",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickParticleSystem*",
+                        "user": false,
+                        "write": "setSystem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "groups",
+                        "notify": "groupsChanged",
+                        "read": "groups",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setGroups"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "whenCollidingWith",
+                        "notify": "whenCollidingWithChanged",
+                        "read": "whenCollidingWith",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setWhenCollidingWith"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "once",
+                        "notify": "onceChanged",
+                        "read": "onceOff",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOnceOff"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "shape",
+                        "notify": "shapeChanged",
+                        "read": "shape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickParticleExtruder*",
+                        "user": false,
+                        "write": "setShape"
+                    }
+                ],
+                "qualifiedClassName": "QQuickParticleAffector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "systemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "groupsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "onceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleExtruder*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "shapeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "affected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "whenCollidingWithChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setSystem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setGroups",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setOnceOff",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleExtruder*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setShape",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setWhenCollidingWith",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "updateOffsets",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickparticleaffector_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Emitter"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickParticleEmitter",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Lifetime",
+                        "values": [
+                            "InfiniteLife"
+                        ]
+                    }
+                ],
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "system",
+                        "notify": "systemChanged",
+                        "read": "system",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickParticleSystem*",
+                        "user": false,
+                        "write": "setSystem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "group",
+                        "notify": "groupChanged",
+                        "read": "group",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setGroup"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "shape",
+                        "notify": "extruderChanged",
+                        "read": "extruder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickParticleExtruder*",
+                        "user": false,
+                        "write": "setExtruder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "enabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "startTime",
+                        "notify": "startTimeChanged",
+                        "read": "startTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setStartTime"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "emitRate",
+                        "notify": "particlesPerSecondChanged",
+                        "read": "particlesPerSecond",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setParticlesPerSecond"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "lifeSpan",
+                        "notify": "particleDurationChanged",
+                        "read": "particleDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setParticleDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "lifeSpanVariation",
+                        "notify": "particleDurationVariationChanged",
+                        "read": "particleDurationVariation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setParticleDurationVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "maximumEmitted",
+                        "notify": "maximumEmittedChanged",
+                        "read": "maxParticleCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxParticleCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "size",
+                        "notify": "particleSizeChanged",
+                        "read": "particleSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setParticleSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "endSize",
+                        "notify": "particleEndSizeChanged",
+                        "read": "particleEndSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setParticleEndSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "sizeVariation",
+                        "notify": "particleSizeVariationChanged",
+                        "read": "particleSizeVariation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setParticleSizeVariation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "velocity",
+                        "notify": "velocityChanged",
+                        "read": "velocity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setVelocity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "acceleration",
+                        "notify": "accelerationChanged",
+                        "read": "acceleration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickDirection*",
+                        "user": false,
+                        "write": "setAcceleration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "velocityFromMovement",
+                        "notify": "velocityFromMovementChanged",
+                        "read": "velocityFromMovement",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setVelocityFromMovement"
+                    }
+                ],
+                "qualifiedClassName": "QQuickParticleEmitter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "particles",
+                                "type": "QList<QQuickV4ParticleData>"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "emitParticles",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "particlesPerSecondChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "particleDurationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "systemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "groupChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "particleDurationVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleExtruder*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "extruderChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "particleSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "particleEndSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "particleSizeVariationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "velocityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "accelerationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "maximumEmittedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "particleCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "velocityFromMovementChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "startTimeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "milliseconds",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "pulse",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "num",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "burst",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "num",
+                                "type": "int"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "burst",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "setParticlesPerSecond",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "setParticleDuration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "setSystem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 24,
+                        "name": "setGroup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "setParticleDurationVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleExtruder*"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "setExtruder",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "setParticleSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "setParticleEndSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "setParticleSizeVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "setVelocity",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickDirection*"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "setAcceleration",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "setMaxParticleCount",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "setStartTime",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "name": "reset",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
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+                ]
+            }
+        ],
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+    },
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+                        "name": "QML.Element",
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+                    {
+                        "name": "QML.AddedInVersion",
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+                    },
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+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Abstract type. Use one of the inheriting types instead."
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+                "object": true,
+                "qualifiedClassName": "QQuickParticleExtruder",
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+                    {
+                        "access": "public",
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+                ]
+            }
+        ],
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+    },
+    {
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+                    {
+                        "name": "QML.AddedInVersion",
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+                ],
+                "className": "QQuickParticleGroup",
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+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
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+                ],
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+                        "name": "system",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickParticleSystem*",
+                        "user": false,
+                        "write": "setSystem"
+                    },
+                    {
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+                        "name": "particleChildren",
+                        "read": "particleChildren",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickParticleGroup",
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
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+                        "name": "systemChanged",
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+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
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+                        "index": 1,
+                        "name": "setSystem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "obj",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "delayRedirect",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QQuickStochasticState"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
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+                ]
+            }
+        ],
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+                        "name": "QML.AddedInVersion",
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+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
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+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "Abstract type. Use one of the inheriting types instead."
+                    }
+                ],
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+                        "scriptable": true,
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+                    {
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+                        "designable": true,
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+                        "index": 1,
+                        "name": "groups",
+                        "notify": "groupsChanged",
+                        "read": "groups",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setGroups"
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+                ],
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+                        "access": "public",
+                        "index": 0,
+                        "name": "countChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
+                            }
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+                        "index": 1,
+                        "name": "systemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
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+                        "name": "groupsChanged",
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+                ],
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleSystem*"
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+                        ],
+                        "index": 3,
+                        "name": "setSystem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setGroups",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "resetPending",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "calcSystemOffset",
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+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "calcSystemOffset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "sceneGraphInvalidated",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
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+                        "read": "isPaused",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPaused"
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+                    {
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+                        "stored": true,
+                        "type": "bool",
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+                ],
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+                        "access": "public",
+                        "index": 0,
+                        "name": "systemInitialized",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
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+                        "name": "runningChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
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+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "emptyChanged",
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+                ],
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+                        "access": "public",
+                        "index": 4,
+                        "name": "start",
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+                    {
+                        "access": "public",
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+                    {
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+                    {
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+                    {
+                        "access": "public",
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+                                "name": "arg",
+                                "type": "bool"
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+                        "name": "setRunning",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
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+                    },
+                    {
+                        "access": "public",
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+                        "name": "duration",
+                        "returnType": "int"
+                    },
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+                        "name": "emittersChanged",
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+                                "name": "p",
+                                "type": "QQuickParticlePainter*"
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+                        "name": "loadPainter",
+                        "returnType": "void"
+                    },
+                    {
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+                        "name": "createEngine",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "idx",
+                                "type": "int"
+                            }
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+                        "name": "particleStateChange",
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+                        "name": "QQuickItem"
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+                ]
+            },
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+                        "access": "public",
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+                ]
+            }
+        ],
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+    },
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+                            "Quadratic",
+                            "InverseLinear",
+                            "InverseQuadratic"
+                        ]
+                    },
+                    {
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+                        "isFlag": false,
+                        "name": "AffectableParameters",
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+                            "Velocity",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setStrength"
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+                    {
+                        "constant": false,
+                        "designable": true,
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+                        "name": "pointX",
+                        "notify": "pointXChanged",
+                        "read": "pointX",
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+                        "scriptable": true,
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+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPointX"
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+                    {
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+                        "name": "pointY",
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+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPointY"
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+                        "designable": true,
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+                        "required": false,
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+                        "type": "AffectableParameters",
+                        "user": false,
+                        "write": "setAffectedParameter"
+                    },
+                    {
+                        "constant": false,
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+                        "name": "proportionalToDistance",
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+                        "scriptable": true,
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+                ],
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+                        "access": "public",
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+                                "name": "arg",
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+                                "name": "arg",
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+                    {
+                        "access": "public",
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+                        "constant": false,
+                        "designable": true,
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+                        "stored": true,
+                        "type": "qreal",
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+                        "designable": true,
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+                        "name": "xVariation",
+                        "notify": "xVariationChanged",
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+                        "type": "qreal",
+                        "user": false,
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
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+                        "write": "setYVariation"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
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+                    },
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+                            {
+                                "name": "arg",
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+                            {
+                                "name": "arg",
+                                "type": "qreal"
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+                        "access": "public",
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+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
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+                        "name": "yVariationChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setX",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setY",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setXVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
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+                        "name": "setYVariation",
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+                    }
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+                    {
+                        "access": "public",
+                        "name": "QQuickDirection"
+                    }
+                ]
+            }
+        ],
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+    },
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+                        "name": "QML.Element",
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+                        "value": "512"
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+                "object": true,
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
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+                        "notify": "fillChanged",
+                        "read": "fill",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFill"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                        "name": "fillChanged",
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+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
+                            }
+                        ],
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+                        "returnType": "void"
+                    }
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+                        "access": "public",
+                        "name": "QQuickParticleExtruder"
+                    }
+                ]
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+    },
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+                        "name": "QML.Element",
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+                        "value": "512"
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+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setGoalState"
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+                        "type": "bool",
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+                        "read": "systemStates",
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+                        "type": "bool",
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+                        "write": "setSystemStates"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "arg",
+                                "type": "QString"
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+                        "name": "goalStateChanged",
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+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                        "access": "public",
+                        "arguments": [
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+                                "name": "arg",
+                                "type": "QString"
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+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "bool"
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+                        "name": "QQuickParticleAffector"
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+                        "type": "QQuickItem*",
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+                        "name": "proportionalMagnitude",
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+                        "read": "proportionalMagnitude",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setProportionalMagnitude"
+                    },
+                    {
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+                        "final": false,
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+                        "read": "magnitude",
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+                        "scriptable": true,
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+                        "type": "qreal",
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+                        "write": "setMagnitude"
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+                                "type": "bool"
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+                                "type": "bool"
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+                        "name": "setMagnitudeVariation",
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+                    },
+                    {
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+                                "name": "arg",
+                                "type": "QQuickItem*"
+                            }
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+                        "name": "setTargetItem",
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+                        "name": "QQuickDirection"
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+                ]
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+        ],
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+                        "isFlag": false,
+                        "name": "EmitSize",
+                        "values": [
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+                        ]
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+                        "type": "QString",
+                        "user": false,
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+                        "name": "emitRatePerParticle",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setParticlesPerParticlePerSecond"
+                    },
+                    {
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+                        "name": "emitShape",
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+                        "type": "QQuickParticleExtruder*",
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+                    },
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+                        "name": "emitHeight",
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+                        "name": "emitWidth",
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+                        "write": "setEmitterXVariation"
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+                ],
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+                        "arguments": [
+                            {
+                                "name": "particles",
+                                "type": "QList<QQuickV4ParticleData>"
+                            },
+                            {
+                                "name": "followed",
+                                "type": "QQuickV4ParticleData"
+                            }
+                        ],
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+                        "name": "emitFollowParticles",
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+                    },
+                    {
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+                            {
+                                "name": "arg",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "particlesPerParticlePerSecondChanged",
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+                    },
+                    {
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+                        "name": "emitterYVariationChanged",
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+                                "type": "QQuickParticleExtruder*"
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+                        "name": "emissionShapeChanged",
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+                ],
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+                                "name": "arg",
+                                "type": "int"
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+                        "name": "setEmitterXVariation",
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+                    },
+                    {
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+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setEmitterYVariation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setFollow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QQuickParticleExtruder*"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setEmissionShape",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 11,
+                        "name": "recalcParticlesPerSecond",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleEmitter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicktrailemitter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Turbulence"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickTurbulenceAffector",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "strength",
+                        "notify": "strengthChanged",
+                        "read": "strength",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setStrength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "noiseSource",
+                        "notify": "noiseSourceChanged",
+                        "read": "noiseSource",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setNoiseSource"
+                    }
+                ],
+                "qualifiedClassName": "QQuickTurbulenceAffector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "strengthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "noiseSourceChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setStrength",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setNoiseSource",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickturbulence_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Wander"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickWanderAffector",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "AffectableParameters",
+                        "values": [
+                            "Position",
+                            "Velocity",
+                            "Acceleration"
+                        ]
+                    }
+                ],
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "pace",
+                        "notify": "paceChanged",
+                        "read": "pace",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPace"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "xVariance",
+                        "notify": "xVarianceChanged",
+                        "read": "xVariance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setXVariance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "yVariance",
+                        "notify": "yVarianceChanged",
+                        "read": "yVariance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setYVariance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "affectedParameter",
+                        "notify": "affectedParameterChanged",
+                        "read": "affectedParameter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "AffectableParameters",
+                        "user": false,
+                        "write": "setAffectedParameter"
+                    }
+                ],
+                "qualifiedClassName": "QQuickWanderAffector",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "xVarianceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "yVarianceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "paceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "AffectableParameters"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "affectedParameterChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setXVariance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setYVariance",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setPace",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "arg",
+                                "type": "AffectableParameters"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setAffectedParameter",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickParticleAffector"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickwander_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickshapesprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickshapesprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..80c7b008e61f0ac7839f9457630ec374a8daf841
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickshapesprivate_metatypes.json
@@ -0,0 +1,1319 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickShapeCurveRunnable",
+                "lineNumber": 143,
+                "object": true,
+                "qualifiedClassName": "QQuickShapeCurveRunnable",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "self",
+                                "type": "QQuickShapeCurveRunnable*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QRunnable"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickshapecurverenderer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "stops"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ShapeGradient"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": "ShapeGradient is an abstract base class."
+                    }
+                ],
+                "className": "QQuickShapeGradient",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SpreadMode",
+                        "values": [
+                            "PadSpread",
+                            "ReflectSpread",
+                            "RepeatSpread"
+                        ]
+                    }
+                ],
+                "lineNumber": 38,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "spread",
+                        "notify": "spreadChanged",
+                        "read": "spread",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SpreadMode",
+                        "user": false,
+                        "write": "setSpread"
+                    }
+                ],
+                "qualifiedClassName": "QQuickShapeGradient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "spreadChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickGradient"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "stops"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "LinearGradient"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickShapeLinearGradient",
+                "lineNumber": 68,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "x1",
+                        "notify": "x1Changed",
+                        "read": "x1",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setX1"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "y1",
+                        "notify": "y1Changed",
+                        "read": "y1",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setY1"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "x2",
+                        "notify": "x2Changed",
+                        "read": "x2",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setX2"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "y2",
+                        "notify": "y2Changed",
+                        "read": "y2",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setY2"
+                    }
+                ],
+                "qualifiedClassName": "QQuickShapeLinearGradient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "x1Changed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "y1Changed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "x2Changed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "y2Changed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickShapeGradient"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "stops"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "RadialGradient"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickShapeRadialGradient",
+                "lineNumber": 102,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "centerX",
+                        "notify": "centerXChanged",
+                        "read": "centerX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setCenterX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "centerY",
+                        "notify": "centerYChanged",
+                        "read": "centerY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setCenterY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "centerRadius",
+                        "notify": "centerRadiusChanged",
+                        "read": "centerRadius",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setCenterRadius"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "focalX",
+                        "notify": "focalXChanged",
+                        "read": "focalX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFocalX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "focalY",
+                        "notify": "focalYChanged",
+                        "read": "focalY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFocalY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "focalRadius",
+                        "notify": "focalRadiusChanged",
+                        "read": "focalRadius",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setFocalRadius"
+                    }
+                ],
+                "qualifiedClassName": "QQuickShapeRadialGradient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "centerXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "centerYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "focalXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "focalYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "centerRadiusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "focalRadiusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickShapeGradient"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "stops"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ConicalGradient"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickShapeConicalGradient",
+                "lineNumber": 151,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "centerX",
+                        "notify": "centerXChanged",
+                        "read": "centerX",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setCenterX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "centerY",
+                        "notify": "centerYChanged",
+                        "read": "centerY",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setCenterY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "angle",
+                        "notify": "angleChanged",
+                        "read": "angle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setAngle"
+                    }
+                ],
+                "qualifiedClassName": "QQuickShapeConicalGradient",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "centerXChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "centerYChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "angleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickShapeGradient"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ShapePath"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickShapePath",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FillRule",
+                        "values": [
+                            "OddEvenFill",
+                            "WindingFill"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "JoinStyle",
+                        "values": [
+                            "MiterJoin",
+                            "BevelJoin",
+                            "RoundJoin"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CapStyle",
+                        "values": [
+                            "FlatCap",
+                            "SquareCap",
+                            "RoundCap"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StrokeStyle",
+                        "values": [
+                            "SolidLine",
+                            "DashLine"
+                        ]
+                    },
+                    {
+                        "alias": "PathHint",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "PathHints",
+                        "values": [
+                            "PathLinear",
+                            "PathQuadratic",
+                            "PathConvex",
+                            "PathFillOnRight",
+                            "PathSolid",
+                            "PathNonIntersecting",
+                            "PathNonOverlappingControlPointTriangles"
+                        ]
+                    }
+                ],
+                "lineNumber": 183,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "strokeColor",
+                        "notify": "strokeColorChanged",
+                        "read": "strokeColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setStrokeColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "strokeWidth",
+                        "notify": "strokeWidthChanged",
+                        "read": "strokeWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setStrokeWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "fillColor",
+                        "notify": "fillColorChanged",
+                        "read": "fillColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setFillColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "fillRule",
+                        "notify": "fillRuleChanged",
+                        "read": "fillRule",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FillRule",
+                        "user": false,
+                        "write": "setFillRule"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "joinStyle",
+                        "notify": "joinStyleChanged",
+                        "read": "joinStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "JoinStyle",
+                        "user": false,
+                        "write": "setJoinStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "miterLimit",
+                        "notify": "miterLimitChanged",
+                        "read": "miterLimit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMiterLimit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "capStyle",
+                        "notify": "capStyleChanged",
+                        "read": "capStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "CapStyle",
+                        "user": false,
+                        "write": "setCapStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "strokeStyle",
+                        "notify": "strokeStyleChanged",
+                        "read": "strokeStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "StrokeStyle",
+                        "user": false,
+                        "write": "setStrokeStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "dashOffset",
+                        "notify": "dashOffsetChanged",
+                        "read": "dashOffset",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setDashOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "dashPattern",
+                        "notify": "dashPatternChanged",
+                        "read": "dashPattern",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<qreal>",
+                        "user": false,
+                        "write": "setDashPattern"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "fillGradient",
+                        "read": "fillGradient",
+                        "required": false,
+                        "reset": "resetFillGradient",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickShapeGradient*",
+                        "user": false,
+                        "write": "setFillGradient"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "scale",
+                        "notify": "scaleChanged",
+                        "read": "scale",
+                        "required": false,
+                        "revision": 270,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "pathHints",
+                        "notify": "pathHintsChanged",
+                        "read": "pathHints",
+                        "required": false,
+                        "revision": 1543,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "PathHints",
+                        "user": false,
+                        "write": "setPathHints"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "fillTransform",
+                        "notify": "fillTransformChanged",
+                        "read": "fillTransform",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QMatrix4x4",
+                        "user": false,
+                        "write": "setFillTransform"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "fillItem",
+                        "notify": "fillItemChanged",
+                        "read": "fillItem",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setFillItem"
+                    }
+                ],
+                "qualifiedClassName": "QQuickShapePath",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "shapePathChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "strokeColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "strokeWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "fillColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "fillRuleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "joinStyleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "miterLimitChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "capStyleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "strokeStyleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "dashOffsetChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "dashPatternChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "pathHintsChanged",
+                        "returnType": "void",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "fillTransformChanged",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "fillItemChanged",
+                        "returnType": "void",
+                        "revision": 1544
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 14,
+                        "name": "_q_fillGradientChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 15,
+                        "name": "_q_fillItemDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPath"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "data"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Shape"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickShape",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RendererType",
+                        "values": [
+                            "UnknownRenderer",
+                            "GeometryRenderer",
+                            "NvprRenderer",
+                            "SoftwareRenderer",
+                            "CurveRenderer"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Processing"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ContainsMode",
+                        "values": [
+                            "BoundingRectContains",
+                            "FillContains"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FillMode",
+                        "values": [
+                            "NoResize",
+                            "PreserveAspectFit",
+                            "PreserveAspectCrop",
+                            "Stretch"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HAlignment",
+                        "values": [
+                            "AlignLeft",
+                            "AlignRight",
+                            "AlignHCenter"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VAlignment",
+                        "values": [
+                            "AlignTop",
+                            "AlignBottom",
+                            "AlignVCenter"
+                        ]
+                    }
+                ],
+                "lineNumber": 316,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "rendererType",
+                        "notify": "rendererChanged",
+                        "read": "rendererType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RendererType",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "asynchronous",
+                        "notify": "asynchronousChanged",
+                        "read": "asynchronous",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAsynchronous"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "vendorExtensionsEnabled",
+                        "notify": "vendorExtensionsEnabledChanged",
+                        "read": "vendorExtensionsEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVendorExtensionsEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "preferredRendererType",
+                        "notify": "preferredRendererTypeChanged",
+                        "read": "preferredRendererType",
+                        "required": false,
+                        "revision": 1542,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RendererType",
+                        "user": false,
+                        "write": "setPreferredRendererType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Status",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "containsMode",
+                        "notify": "containsModeChanged",
+                        "read": "containsMode",
+                        "required": false,
+                        "revision": 267,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ContainsMode",
+                        "user": false,
+                        "write": "setContainsMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "boundingRect",
+                        "notify": "boundingRectChanged",
+                        "read": "boundingRect",
+                        "required": false,
+                        "revision": 1542,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "fillMode",
+                        "notify": "fillModeChanged",
+                        "read": "fillMode",
+                        "required": false,
+                        "revision": 1543,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FillMode",
+                        "user": false,
+                        "write": "setFillMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "horizontalAlignment",
+                        "notify": "horizontalAlignmentChanged",
+                        "read": "horizontalAlignment",
+                        "required": false,
+                        "revision": 1543,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HAlignment",
+                        "user": false,
+                        "write": "setHorizontalAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "verticalAlignment",
+                        "notify": "verticalAlignmentChanged",
+                        "read": "verticalAlignment",
+                        "required": false,
+                        "revision": 1543,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VAlignment",
+                        "user": false,
+                        "write": "setVerticalAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "data",
+                        "read": "data",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickShape",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "rendererChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "asynchronousChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "vendorExtensionsEnabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "preferredRendererTypeChanged",
+                        "returnType": "void",
+                        "revision": 1542
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "boundingRectChanged",
+                        "returnType": "void",
+                        "revision": 1542
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "containsModeChanged",
+                        "returnType": "void",
+                        "revision": 267
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "fillModeChanged",
+                        "returnType": "void",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "horizontalAlignmentChanged",
+                        "returnType": "void",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "verticalAlignmentChanged",
+                        "returnType": "void",
+                        "revision": 1543
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "_q_shapePathChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickshape_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickShapeFillRunnable",
+                "lineNumber": 139,
+                "object": true,
+                "qualifiedClassName": "QQuickShapeFillRunnable",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "self",
+                                "type": "QQuickShapeFillRunnable*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QRunnable"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickShapeStrokeRunnable",
+                "lineNumber": 163,
+                "object": true,
+                "qualifiedClassName": "QQuickShapeStrokeRunnable",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "self",
+                                "type": "QQuickShapeStrokeRunnable*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "done",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QRunnable"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickShapeGenericStrokeFillNode",
+                "lineNumber": 186,
+                "object": true,
+                "qualifiedClassName": "QQuickShapeGenericStrokeFillNode",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "handleTextureChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "handleTextureProviderDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QSGGeometryNode"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickshapegenericrenderer_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quicktemplates2_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktemplates2_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..e60b7f98bd459c5c2116116a508bbad3c0d55204
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktemplates2_metatypes.json
@@ -0,0 +1,16714 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQuickPopupWindow",
+                "lineNumber": 26,
+                "object": true,
+                "qualifiedClassName": "QQuickPopupWindow",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickWindowQmlImpl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpopupwindow_p_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background,contentItem,indicator"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "AbstractButton"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickAbstractButton",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Display",
+                        "values": [
+                            "IconOnly",
+                            "TextOnly",
+                            "TextBesideIcon",
+                            "TextUnderIcon"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "methods": [
+                    {
+                        "access": "protected",
+                        "index": 27,
+                        "name": "accessiblePressAction",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "reset": "resetText",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "down",
+                        "notify": "downChanged",
+                        "read": "isDown",
+                        "required": false,
+                        "reset": "resetDown",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDown"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "checked",
+                        "notify": "checkedChanged",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChecked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "checkable",
+                        "notify": "checkableChanged",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "autoExclusive",
+                        "notify": "autoExclusiveChanged",
+                        "read": "autoExclusive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoExclusive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "autoRepeat",
+                        "notify": "autoRepeatChanged",
+                        "read": "autoRepeat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRepeat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "indicator",
+                        "notify": "indicatorChanged",
+                        "read": "indicator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setIndicator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "display",
+                        "notify": "displayChanged",
+                        "read": "display",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Display",
+                        "user": false,
+                        "write": "setDisplay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "action",
+                        "notify": "actionChanged",
+                        "read": "action",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAction*",
+                        "user": false,
+                        "write": "setAction"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "autoRepeatDelay",
+                        "notify": "autoRepeatDelayChanged",
+                        "read": "autoRepeatDelay",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoRepeatDelay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "autoRepeatInterval",
+                        "notify": "autoRepeatIntervalChanged",
+                        "read": "autoRepeatInterval",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoRepeatInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "pressX",
+                        "notify": "pressXChanged",
+                        "read": "pressX",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "pressY",
+                        "notify": "pressYChanged",
+                        "read": "pressY",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "implicitIndicatorWidth",
+                        "notify": "implicitIndicatorWidthChanged",
+                        "read": "implicitIndicatorWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "implicitIndicatorHeight",
+                        "notify": "implicitIndicatorHeightChanged",
+                        "read": "implicitIndicatorHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickAbstractButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "released",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "canceled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "pressAndHold",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "doubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "downChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "checkedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "checkableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "autoExclusiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "autoRepeatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "indicatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "toggled",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "iconChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "displayChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "actionChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "autoRepeatDelayChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "autoRepeatIntervalChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "pressXChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "pressYChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "implicitIndicatorWidthChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "implicitIndicatorHeightChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "click",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "animateClick",
+                        "returnType": "void",
+                        "revision": 1544
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickabstractbutton_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Action"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickAction",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "reset": "resetEnabled",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "checked",
+                        "notify": "checkedChanged",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChecked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "checkable",
+                        "notify": "checkableChanged",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "shortcut",
+                        "notify": "shortcutChanged",
+                        "privateClass": "QQuickAction::d_func()",
+                        "read": "shortcut",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setShortcut"
+                    }
+                ],
+                "qualifiedClassName": "QQuickAction",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "icon",
+                                "type": "QQuickIcon"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "iconChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "checkedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checkable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "checkableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "shortcut",
+                                "type": "QKeySequence"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "shortcutChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "toggled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "isCloned": true,
+                        "name": "toggled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "isCloned": true,
+                        "name": "triggered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "source",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "trigger",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "isCloned": true,
+                        "name": "trigger",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickaction_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "actions"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ActionGroup"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickActionGroupAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickActionGroup",
+                "lineNumber": 29,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "checkedAction",
+                        "notify": "checkedActionChanged",
+                        "read": "checkedAction",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAction*",
+                        "user": false,
+                        "write": "setCheckedAction"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "actions",
+                        "notify": "actionsChanged",
+                        "read": "actions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickAction>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "exclusive",
+                        "notify": "exclusiveChanged",
+                        "read": "isExclusive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExclusive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QQuickActionGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "checkedActionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "actionsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "exclusiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "enabledChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "triggered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "addAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "removeAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_updateCurrent",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickActionGroupAttached",
+                "lineNumber": 76,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "group",
+                        "notify": "groupChanged",
+                        "read": "group",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickActionGroup*",
+                        "user": false,
+                        "write": "setGroup"
+                    }
+                ],
+                "qualifiedClassName": "QQuickActionGroupAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "groupChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickactiongroup_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "contentData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ApplicationWindow"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickApplicationWindowAttached"
+                    }
+                ],
+                "className": "QQuickApplicationWindow",
+                "lineNumber": 30,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "contentItem",
+                        "read": "contentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "contentData",
+                        "privateClass": "QQuickApplicationWindow::d_func()",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "activeFocusControl",
+                        "notify": "activeFocusControlChanged",
+                        "read": "activeFocusControl",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "header",
+                        "notify": "headerChanged",
+                        "read": "header",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setHeader"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "footer",
+                        "notify": "footerChanged",
+                        "read": "footer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setFooter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "reset": "resetFont",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "reset": "resetLocale",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "menuBar",
+                        "notify": "menuBarChanged",
+                        "read": "menuBar",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setMenuBar"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "palette",
+                        "notify": "paletteChanged",
+                        "privateClass": "QQuickApplicationWindow::d_func()",
+                        "read": "palette",
+                        "required": false,
+                        "reset": "resetPalette",
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPalette*",
+                        "user": false,
+                        "write": "setPalette"
+                    }
+                ],
+                "qualifiedClassName": "QQuickApplicationWindow",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "backgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "activeFocusControlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "headerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "footerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "menuBarChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_updateActiveFocus",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickWindowQmlImpl"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickApplicationWindowAttached",
+                "lineNumber": 102,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "window",
+                        "notify": "windowChanged",
+                        "read": "window",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickApplicationWindow*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "contentItem",
+                        "notify": "contentItemChanged",
+                        "read": "contentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "activeFocusControl",
+                        "notify": "activeFocusControlChanged",
+                        "read": "activeFocusControl",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "header",
+                        "notify": "headerChanged",
+                        "read": "header",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "footer",
+                        "notify": "footerChanged",
+                        "read": "footer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "menuBar",
+                        "notify": "menuBarChanged",
+                        "read": "menuBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickApplicationWindowAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "windowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "activeFocusControlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "headerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "footerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "menuBarChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickapplicationwindow_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "BusyIndicator"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickBusyIndicator",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "running",
+                        "notify": "runningChanged",
+                        "read": "isRunning",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRunning"
+                    }
+                ],
+                "qualifiedClassName": "QQuickBusyIndicator",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "runningChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbusyindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Button"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickButton",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "highlighted",
+                        "notify": "highlightedChanged",
+                        "read": "isHighlighted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlighted"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "flat",
+                        "notify": "flatChanged",
+                        "read": "isFlat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFlat"
+                    }
+                ],
+                "qualifiedClassName": "QQuickButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "highlightedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "flatChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbutton_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ButtonGroup"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickButtonGroupAttached"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickButtonGroup",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 30,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "checkedButton",
+                        "notify": "checkedButtonChanged",
+                        "read": "checkedButton",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickAbstractButton*",
+                        "user": false,
+                        "write": "setCheckedButton"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "buttons",
+                        "notify": "buttonsChanged",
+                        "read": "buttons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickAbstractButton>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "exclusive",
+                        "notify": "exclusiveChanged",
+                        "read": "isExclusive",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExclusive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "checkState",
+                        "notify": "checkStateChanged",
+                        "read": "checkState",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CheckState",
+                        "user": false,
+                        "write": "setCheckState"
+                    }
+                ],
+                "qualifiedClassName": "QQuickButtonGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "checkedButtonChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "buttonsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QQuickAbstractButton*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "clicked",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "exclusiveChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "checkStateChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QQuickAbstractButton*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "addButton",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QQuickAbstractButton*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "removeButton",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_updateCurrent",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickButtonGroupAttached",
+                "lineNumber": 87,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "group",
+                        "notify": "groupChanged",
+                        "read": "group",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickButtonGroup*",
+                        "user": false,
+                        "write": "setGroup"
+                    }
+                ],
+                "qualifiedClassName": "QQuickButtonGroupAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "groupChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickbuttongroup_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Calendar"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickCalendar",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Month",
+                        "values": [
+                            "January",
+                            "February",
+                            "March",
+                            "April",
+                            "May",
+                            "June",
+                            "July",
+                            "August",
+                            "September",
+                            "October",
+                            "November",
+                            "December"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQuickCalendar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcalendar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CalendarModel"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickCalendarModel",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
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+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "monthAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "yearAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "indexOf",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "year",
+                                "type": "int"
+                            },
+                            {
+                                "name": "month",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "indexOf",
+                        "returnType": "int"
+                    }
+                ],
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+                "properties": [
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+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "from",
+                        "notify": "fromChanged",
+                        "read": "from",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDate",
+                        "user": false,
+                        "write": "setFrom"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "to",
+                        "notify": "toChanged",
+                        "read": "to",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDate",
+                        "user": false,
+                        "write": "setTo"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "rowCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickCalendarModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fromChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "toChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QQmlParserStatus"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcalendarmodel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CheckBox"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCheckBox",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "tristate",
+                        "notify": "tristateChanged",
+                        "read": "isTristate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTristate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "checkState",
+                        "notify": "checkStateChanged",
+                        "read": "checkState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CheckState",
+                        "user": false,
+                        "write": "setCheckState"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "nextCheckState",
+                        "notify": "nextCheckStateChanged",
+                        "read": "getNextCheckState",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setNextCheckState"
+                    }
+                ],
+                "qualifiedClassName": "QQuickCheckBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "tristateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "checkStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "nextCheckStateChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcheckbox_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "CheckDelegate"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickCheckDelegate",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "tristate",
+                        "notify": "tristateChanged",
+                        "read": "isTristate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTristate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "checkState",
+                        "notify": "checkStateChanged",
+                        "read": "checkState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CheckState",
+                        "user": false,
+                        "write": "setCheckState"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "member": "nextCheckState",
+                        "name": "nextCheckState",
+                        "notify": "nextCheckStateChanged",
+                        "privateClass": "QQuickCheckDelegate::d_func()",
+                        "required": false,
+                        "revision": 516,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setNextCheckState"
+                    }
+                ],
+                "qualifiedClassName": "QQuickCheckDelegate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "tristateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "checkStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "nextCheckStateChanged",
+                        "returnType": "void",
+                        "revision": 516
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcheckdelegate_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background,contentItem,indicator,popup"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "ComboBox"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickComboBox",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ImplicitContentWidthPolicy",
+                        "values": [
+                            "ContentItemImplicitWidth",
+                            "WidestText",
+                            "WidestTextWhenCompleted"
+                        ]
+                    }
+                ],
+                "lineNumber": 33,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "textAt",
+                        "returnType": "QString"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "flags",
+                                "type": "Qt::MatchFlags"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "find",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 34,
+                        "isCloned": true,
+                        "name": "find",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "valueAt",
+                        "returnType": "QVariant",
+                        "revision": 526
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "indexOfValue",
+                        "returnType": "int",
+                        "revision": 526
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "model",
+                        "notify": "modelChanged",
+                        "read": "model",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setModel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "delegateModel",
+                        "notify": "delegateModelChanged",
+                        "read": "delegateModel",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlInstanceModel*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "highlightedIndex",
+                        "notify": "highlightedIndexChanged",
+                        "read": "highlightedIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "currentText",
+                        "notify": "currentTextChanged",
+                        "read": "currentText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "displayText",
+                        "notify": "displayTextChanged",
+                        "read": "displayText",
+                        "required": false,
+                        "reset": "resetDisplayText",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDisplayText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "textRole",
+                        "notify": "textRoleChanged",
+                        "read": "textRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTextRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "indicator",
+                        "notify": "indicatorChanged",
+                        "read": "indicator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setIndicator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "popup",
+                        "notify": "popupChanged",
+                        "read": "popup",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPopup*",
+                        "user": false,
+                        "write": "setPopup"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "flat",
+                        "notify": "flatChanged",
+                        "read": "isFlat",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFlat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "down",
+                        "notify": "downChanged",
+                        "read": "isDown",
+                        "required": false,
+                        "reset": "resetDown",
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDown"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "editable",
+                        "notify": "editableChanged",
+                        "read": "isEditable",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEditable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "editText",
+                        "notify": "editTextChanged",
+                        "read": "editText",
+                        "required": false,
+                        "reset": "resetEditText",
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setEditText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "validator",
+                        "notify": "validatorChanged",
+                        "read": "validator",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QValidator*",
+                        "user": false,
+                        "write": "setValidator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "inputMethodHints",
+                        "notify": "inputMethodHintsChanged",
+                        "read": "inputMethodHints",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::InputMethodHints",
+                        "user": false,
+                        "write": "setInputMethodHints"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "inputMethodComposing",
+                        "notify": "inputMethodComposingChanged",
+                        "read": "isInputMethodComposing",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "acceptableInput",
+                        "notify": "acceptableInputChanged",
+                        "read": "hasAcceptableInput",
+                        "required": false,
+                        "revision": 514,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "implicitIndicatorWidth",
+                        "notify": "implicitIndicatorWidthChanged",
+                        "read": "implicitIndicatorWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "implicitIndicatorHeight",
+                        "notify": "implicitIndicatorHeightChanged",
+                        "read": "implicitIndicatorHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "currentValue",
+                        "notify": "currentValueChanged",
+                        "read": "currentValue",
+                        "required": false,
+                        "revision": 526,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "valueRole",
+                        "notify": "valueRoleChanged",
+                        "read": "valueRole",
+                        "required": false,
+                        "revision": 526,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setValueRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "selectTextByMouse",
+                        "notify": "selectTextByMouseChanged",
+                        "read": "selectTextByMouse",
+                        "required": false,
+                        "revision": 527,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSelectTextByMouse"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "implicitContentWidthPolicy",
+                        "notify": "implicitContentWidthPolicyChanged",
+                        "read": "implicitContentWidthPolicy",
+                        "required": false,
+                        "revision": 1536,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ImplicitContentWidthPolicy",
+                        "user": false,
+                        "write": "setImplicitContentWidthPolicy"
+                    }
+                ],
+                "qualifiedClassName": "QQuickComboBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "highlighted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "modelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "delegateModelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "highlightedIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "currentTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "displayTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "textRoleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "indicatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "popupChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "flatChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "accepted",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "downChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "editableChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "editTextChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "validatorChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "inputMethodHintsChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "inputMethodComposingChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "acceptableInputChanged",
+                        "returnType": "void",
+                        "revision": 514
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "implicitIndicatorWidthChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "implicitIndicatorHeightChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "valueRoleChanged",
+                        "returnType": "void",
+                        "revision": 526
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "currentValueChanged",
+                        "returnType": "void",
+                        "revision": 526
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "selectTextByMouseChanged",
+                        "returnType": "void",
+                        "revision": 527
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "name": "implicitContentWidthPolicyChanged",
+                        "returnType": "void",
+                        "revision": 1536
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 29,
+                        "name": "incrementCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 30,
+                        "name": "decrementCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 31,
+                        "name": "selectAll",
+                        "returnType": "void",
+                        "revision": 514
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcombobox_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "contentData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Container"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickContainer",
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "itemAt",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "addItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "insertItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "to",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "moveItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "removeItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "takeItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 515
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "contentModel",
+                        "read": "contentModel",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "contentData",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "contentChildren",
+                        "notify": "contentChildrenChanged",
+                        "read": "contentChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "currentItem",
+                        "notify": "currentItemChanged",
+                        "read": "currentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "reset": "resetContentWidth",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "reset": "resetContentHeight",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentHeight"
+                    }
+                ],
+                "qualifiedClassName": "QQuickContainer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentChildrenChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "contentWidthChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "contentHeightChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "incrementCurrentIndex",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "decrementCurrentIndex",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_currentIndexChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcontainer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickContentItem",
+                "lineNumber": 23,
+                "object": true,
+                "qualifiedClassName": "QQuickContentItem",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickcontentitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background,contentItem"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Control"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickControl",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "reset": "resetFont",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "availableWidth",
+                        "notify": "availableWidthChanged",
+                        "read": "availableWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "availableHeight",
+                        "notify": "availableHeightChanged",
+                        "read": "availableHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "padding",
+                        "notify": "paddingChanged",
+                        "read": "padding",
+                        "required": false,
+                        "reset": "resetPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "topPadding",
+                        "notify": "topPaddingChanged",
+                        "read": "topPadding",
+                        "required": false,
+                        "reset": "resetTopPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "leftPadding",
+                        "notify": "leftPaddingChanged",
+                        "read": "leftPadding",
+                        "required": false,
+                        "reset": "resetLeftPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "rightPadding",
+                        "notify": "rightPaddingChanged",
+                        "read": "rightPadding",
+                        "required": false,
+                        "reset": "resetRightPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "bottomPadding",
+                        "notify": "bottomPaddingChanged",
+                        "read": "bottomPadding",
+                        "required": false,
+                        "reset": "resetBottomPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "spacing",
+                        "notify": "spacingChanged",
+                        "read": "spacing",
+                        "required": false,
+                        "reset": "resetSpacing",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSpacing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "reset": "resetLocale",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "mirrored",
+                        "notify": "mirroredChanged",
+                        "read": "isMirrored",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "focusPolicy",
+                        "notify": "focusPolicyChanged",
+                        "read": "focusPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::FocusPolicy",
+                        "user": false,
+                        "write": "setFocusPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "focusReason",
+                        "notify": "focusReasonChanged",
+                        "read": "focusReason",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::FocusReason",
+                        "user": false,
+                        "write": "setFocusReason"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "visualFocus",
+                        "notify": "visualFocusChanged",
+                        "read": "hasVisualFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "hovered",
+                        "notify": "hoveredChanged",
+                        "read": "isHovered",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "hoverEnabled",
+                        "notify": "hoverEnabledChanged",
+                        "read": "isHoverEnabled",
+                        "required": false,
+                        "reset": "resetHoverEnabled",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHoverEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "wheelEnabled",
+                        "notify": "wheelEnabledChanged",
+                        "read": "isWheelEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWheelEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "contentItem",
+                        "notify": "contentItemChanged",
+                        "read": "contentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setContentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "baselineOffset",
+                        "notify": "baselineOffsetChanged",
+                        "read": "baselineOffset",
+                        "required": false,
+                        "reset": "resetBaselineOffset",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBaselineOffset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "horizontalPadding",
+                        "notify": "horizontalPaddingChanged",
+                        "read": "horizontalPadding",
+                        "required": false,
+                        "reset": "resetHorizontalPadding",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHorizontalPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "verticalPadding",
+                        "notify": "verticalPaddingChanged",
+                        "read": "verticalPadding",
+                        "required": false,
+                        "reset": "resetVerticalPadding",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setVerticalPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "implicitContentWidth",
+                        "notify": "implicitContentWidthChanged",
+                        "read": "implicitContentWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "implicitContentHeight",
+                        "notify": "implicitContentHeightChanged",
+                        "read": "implicitContentHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "implicitBackgroundWidth",
+                        "notify": "implicitBackgroundWidthChanged",
+                        "read": "implicitBackgroundWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "implicitBackgroundHeight",
+                        "notify": "implicitBackgroundHeightChanged",
+                        "read": "implicitBackgroundHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 26,
+                        "name": "topInset",
+                        "notify": "topInsetChanged",
+                        "read": "topInset",
+                        "required": false,
+                        "reset": "resetTopInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "leftInset",
+                        "notify": "leftInsetChanged",
+                        "read": "leftInset",
+                        "required": false,
+                        "reset": "resetLeftInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "rightInset",
+                        "notify": "rightInsetChanged",
+                        "read": "rightInset",
+                        "required": false,
+                        "reset": "resetRightInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 29,
+                        "name": "bottomInset",
+                        "notify": "bottomInsetChanged",
+                        "read": "bottomInset",
+                        "required": false,
+                        "reset": "resetBottomInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomInset"
+                    }
+                ],
+                "qualifiedClassName": "QQuickControl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "availableWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "availableHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "paddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "topPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "leftPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "rightPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "bottomPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "spacingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
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+                "gadget": true,
+                "lineNumber": 30,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "reset": "resetName",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "reset": "resetSource",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "width",
+                        "read": "width",
+                        "required": false,
+                        "reset": "resetWidth",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "height",
+                        "read": "height",
+                        "required": false,
+                        "reset": "resetHeight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "color",
+                        "read": "color",
+                        "required": false,
+                        "reset": "resetColor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "cache",
+                        "read": "cache",
+                        "required": false,
+                        "reset": "resetCache",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCache"
+                    }
+                ],
+                "qualifiedClassName": "QQuickIcon"
+            }
+        ],
+        "inputFile": "qquickicon_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "indicator"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickIndicatorButton",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "pressed",
+                        "notify": "pressedChanged",
+                        "read": "isPressed",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPressed"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "indicator",
+                        "notify": "indicatorChanged",
+                        "read": "indicator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setIndicator"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "hovered",
+                        "notify": "hoveredChanged",
+                        "read": "isHovered",
+                        "required": false,
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHovered"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "implicitIndicatorWidth",
+                        "notify": "implicitIndicatorWidthChanged",
+                        "read": "implicitIndicatorWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "implicitIndicatorHeight",
+                        "notify": "implicitIndicatorHeightChanged",
+                        "read": "implicitIndicatorHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickIndicatorButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pressedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "indicatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "hoveredChanged",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "implicitIndicatorWidthChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "implicitIndicatorHeightChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickindicatorbutton_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "ItemDelegate"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickItemDelegate",
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "highlighted",
+                        "notify": "highlightedChanged",
+                        "read": "isHighlighted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlighted"
+                    }
+                ],
+                "qualifiedClassName": "QQuickItemDelegate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "highlightedChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickitemdelegate_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Label"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickLabel",
+                "lineNumber": 26,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "implicitBackgroundWidth",
+                        "notify": "implicitBackgroundWidthChanged",
+                        "read": "implicitBackgroundWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "implicitBackgroundHeight",
+                        "notify": "implicitBackgroundHeightChanged",
+                        "read": "implicitBackgroundHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "topInset",
+                        "notify": "topInsetChanged",
+                        "read": "topInset",
+                        "required": false,
+                        "reset": "resetTopInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "leftInset",
+                        "notify": "leftInsetChanged",
+                        "read": "leftInset",
+                        "required": false,
+                        "reset": "resetLeftInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "rightInset",
+                        "notify": "rightInsetChanged",
+                        "read": "rightInset",
+                        "required": false,
+                        "reset": "resetRightInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "bottomInset",
+                        "notify": "bottomInsetChanged",
+                        "read": "bottomInset",
+                        "required": false,
+                        "reset": "resetBottomInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomInset"
+                    }
+                ],
+                "qualifiedClassName": "QQuickLabel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "backgroundChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "implicitBackgroundWidthChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "implicitBackgroundHeightChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "topInsetChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "leftInsetChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "rightInsetChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "bottomInsetChanged",
+                        "returnType": "void",
+                        "revision": 517
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickText"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicklabel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "contentData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Menu"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMenu",
+                "lineNumber": 34,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "itemAt",
+                        "returnType": "QQuickItem*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "addItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "insertItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "to",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "moveItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "removeItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "takeItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "menuAt",
+                        "returnType": "QQuickMenu*",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "addMenu",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "insertMenu",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "removeMenu",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "takeMenu",
+                        "returnType": "QQuickMenu*",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "actionAt",
+                        "returnType": "QQuickAction*",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "addAction",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "insertAction",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QQuickAction*"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "removeAction",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "takeAction",
+                        "returnType": "QQuickAction*",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QQmlV4FunctionPtr"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "popup",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "dismiss",
+                        "returnType": "void",
+                        "revision": 515
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "contentModel",
+                        "read": "contentModel",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "contentData",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "cascade",
+                        "notify": "cascadeChanged",
+                        "read": "cascade",
+                        "required": false,
+                        "reset": "resetCascade",
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCascade"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "overlap",
+                        "notify": "overlapChanged",
+                        "read": "overlap",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOverlap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "icon",
+                        "notify": "iconChanged",
+                        "read": "icon",
+                        "required": false,
+                        "revision": 1541,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMenu",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "countChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "cascade",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "cascadeChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "overlapChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "delegateChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "currentIndexChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "icon",
+                                "type": "QQuickIcon"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "iconChanged",
+                        "returnType": "void",
+                        "revision": 1541
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPopup"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmenu_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuBar"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickMenuBar",
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "menuAt",
+                        "returnType": "QQuickMenu*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "addMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "insertMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "menu",
+                                "type": "QQuickMenu*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "removeMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "takeMenu",
+                        "returnType": "QQuickMenu*"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "menus",
+                        "notify": "menusChanged",
+                        "privateClass": "QQuickMenuBar::d_func()",
+                        "read": "menus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickMenu>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "contentData",
+                        "privateClass": "QQuickMenuBar::d_func()",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMenuBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "menusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickContainer"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmenubar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuBarItem"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickMenuBarItem",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "menuBar",
+                        "notify": "menuBarChanged",
+                        "read": "menuBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickMenuBar*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "menu",
+                        "notify": "menuChanged",
+                        "read": "menu",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickMenu*",
+                        "user": false,
+                        "write": "setMenu"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "highlighted",
+                        "notify": "highlightedChanged",
+                        "read": "isHighlighted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlighted"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMenuBarItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "menuBarChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "menuChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "highlightedChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmenubaritem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "arrow,background,contentItem,indicator"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuItem"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickMenuItem",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "highlighted",
+                        "notify": "highlightedChanged",
+                        "read": "isHighlighted",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlighted"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "arrow",
+                        "notify": "arrowChanged",
+                        "read": "arrow",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setArrow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "menu",
+                        "notify": "menuChanged",
+                        "read": "menu",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickMenu*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "subMenu",
+                        "notify": "subMenuChanged",
+                        "read": "subMenu",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickMenu*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "implicitTextPadding",
+                        "notify": "implicitTextPaddingChanged",
+                        "read": "implicitTextPadding",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setImplicitTextPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "textPadding",
+                        "notify": "textPaddingChanged",
+                        "read": "textPadding",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMenuItem",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "highlightedChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "arrowChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "menuChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "subMenuChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "implicitTextPaddingChanged",
+                        "returnType": "void",
+                        "revision": 1544
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "textPaddingChanged",
+                        "returnType": "void",
+                        "revision": 1544
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmenuitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "MenuSeparator"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "513"
+                    }
+                ],
+                "className": "QQuickMenuSeparator",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QQuickMenuSeparator",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmenuseparator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "AbstractMonthGrid"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "1539"
+                    }
+                ],
+                "className": "QQuickMonthGrid",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "month",
+                        "notify": "monthChanged",
+                        "read": "month",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMonth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "year",
+                        "notify": "yearChanged",
+                        "read": "year",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setYear"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickMonthGrid",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "monthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "yearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "released",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "pressAndHold",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmonthgrid_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickMonthModel",
+                "lineNumber": 28,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "dateAt",
+                        "returnType": "QDate"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "indexOf",
+                        "returnType": "int"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "month",
+                        "notify": "monthChanged",
+                        "read": "month",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMonth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "year",
+                        "notify": "yearChanged",
+                        "read": "year",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setYear"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "count",
+                        "read": "rowCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickMonthModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "monthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "yearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickmonthmodel_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    }
+                ],
+                "className": "QQuickNativeIcon",
+                "gadget": true,
+                "lineNumber": 28,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "mask",
+                        "read": "isMask",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMask"
+                    }
+                ],
+                "qualifiedClassName": "QQuickNativeIcon"
+            }
+        ],
+        "inputFile": "qquicknativeicon_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickNativeMenuItem",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQuickNativeMenuItem",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateIcon",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquicknativemenuitem_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Overlay"
+                    },
+                    {
+                        "name": "QML.Attached",
+                        "value": "QQuickOverlayAttached"
+                    },
+                    {
+                        "name": "QML.Creatable",
+                        "value": "false"
+                    },
+                    {
+                        "name": "QML.UncreatableReason",
+                        "value": ""
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "515"
+                    }
+                ],
+                "className": "QQuickOverlay",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "modal",
+                        "notify": "modalChanged",
+                        "read": "modal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setModal"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "modeless",
+                        "notify": "modelessChanged",
+                        "read": "modeless",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setModeless"
+                    }
+                ],
+                "qualifiedClassName": "QQuickOverlay",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "modalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "modelessChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "released",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickOverlayAttached",
+                "lineNumber": 79,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "overlay",
+                        "notify": "overlayChanged",
+                        "read": "overlay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickOverlay*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "modal",
+                        "notify": "modalChanged",
+                        "read": "modal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setModal"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "modeless",
+                        "notify": "modelessChanged",
+                        "read": "modeless",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setModeless"
+                    }
+                ],
+                "qualifiedClassName": "QQuickOverlayAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "overlayChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "modalChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "modelessChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "released",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickoverlay_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "Page"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPage",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "title",
+                        "notify": "titleChanged",
+                        "read": "title",
+                        "required": false,
+                        "reset": "resetTitle",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "header",
+                        "notify": "headerChanged",
+                        "read": "header",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setHeader"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "footer",
+                        "notify": "footerChanged",
+                        "read": "footer",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setFooter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "implicitHeaderWidth",
+                        "notify": "implicitHeaderWidthChanged",
+                        "read": "implicitHeaderWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "implicitHeaderHeight",
+                        "notify": "implicitHeaderHeightChanged",
+                        "read": "implicitHeaderHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "implicitFooterWidth",
+                        "notify": "implicitFooterWidthChanged",
+                        "read": "implicitFooterWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "implicitFooterHeight",
+                        "notify": "implicitFooterHeightChanged",
+                        "read": "implicitFooterHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickPage",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "titleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "headerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "footerChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "implicitHeaderWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "implicitHeaderHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "implicitFooterWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "implicitFooterHeightChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickPane"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpage_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "PageIndicator"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPageIndicator",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "count",
+                        "notify": "countChanged",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "interactive",
+                        "notify": "interactiveChanged",
+                        "read": "isInteractive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInteractive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPageIndicator",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "countChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "interactiveChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpageindicator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DefaultProperty",
+                        "value": "contentData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Pane"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPane",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "reset": "resetContentWidth",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "reset": "resetContentHeight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "contentData",
+                        "privateClass": "QQuickPane::d_func()",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "contentChildren",
+                        "notify": "contentChildrenChanged",
+                        "privateClass": "QQuickPane::d_func()",
+                        "read": "contentChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickPane",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "contentWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "contentHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "contentChildrenChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickpane_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "DeferredPropertyNames",
+                        "value": "background,contentItem"
+                    },
+                    {
+                        "name": "DefaultProperty",
+                        "value": "contentData"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "Popup"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickPopup",
+                "enums": [
+                    {
+                        "alias": "ClosePolicyFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ClosePolicy",
+                        "values": [
+                            "NoAutoClose",
+                            "CloseOnPressOutside",
+                            "CloseOnPressOutsideParent",
+                            "CloseOnReleaseOutside",
+                            "CloseOnReleaseOutsideParent",
+                            "CloseOnEscape"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TransformOrigin",
+                        "values": [
+                            "TopLeft",
+                            "Top",
+                            "TopRight",
+                            "Left",
+                            "Center",
+                            "Right",
+                            "BottomLeft",
+                            "Bottom",
+                            "BottomRight"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PopupType",
+                        "values": [
+                            "Item",
+                            "Window",
+                            "Native"
+                        ]
+                    }
+                ],
+                "interfaces": [
+                    [
+                        {
+                            "className": "QQmlParserStatus",
+                            "id": "\"org.qt-project.Qt.QQmlParserStatus\""
+                        }
+                    ]
+                ],
+                "lineNumber": 41,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reason",
+                                "type": "Qt::FocusReason"
+                            }
+                        ],
+                        "index": 62,
+                        "name": "forceActiveFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 63,
+                        "isCloned": true,
+                        "name": "forceActiveFocus",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "x",
+                        "notify": "xChanged",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setX"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "y",
+                        "notify": "yChanged",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setY"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "z",
+                        "notify": "zChanged",
+                        "read": "z",
+                        "required": false,
+                        "reset": "resetZ",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setZ"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "width",
+                        "notify": "widthChanged",
+                        "read": "width",
+                        "required": false,
+                        "reset": "resetWidth",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "height",
+                        "notify": "heightChanged",
+                        "read": "height",
+                        "required": false,
+                        "reset": "resetHeight",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "implicitWidth",
+                        "notify": "implicitWidthChanged",
+                        "read": "implicitWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setImplicitWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "implicitHeight",
+                        "notify": "implicitHeightChanged",
+                        "read": "implicitHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setImplicitHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "contentWidth",
+                        "notify": "contentWidthChanged",
+                        "read": "contentWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "contentHeight",
+                        "notify": "contentHeightChanged",
+                        "read": "contentHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setContentHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "availableWidth",
+                        "notify": "availableWidthChanged",
+                        "read": "availableWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "availableHeight",
+                        "notify": "availableHeightChanged",
+                        "read": "availableHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 11,
+                        "name": "margins",
+                        "notify": "marginsChanged",
+                        "read": "margins",
+                        "required": false,
+                        "reset": "resetMargins",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setMargins"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 12,
+                        "name": "topMargin",
+                        "notify": "topMarginChanged",
+                        "read": "topMargin",
+                        "required": false,
+                        "reset": "resetTopMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 13,
+                        "name": "leftMargin",
+                        "notify": "leftMarginChanged",
+                        "read": "leftMargin",
+                        "required": false,
+                        "reset": "resetLeftMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 14,
+                        "name": "rightMargin",
+                        "notify": "rightMarginChanged",
+                        "read": "rightMargin",
+                        "required": false,
+                        "reset": "resetRightMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 15,
+                        "name": "bottomMargin",
+                        "notify": "bottomMarginChanged",
+                        "read": "bottomMargin",
+                        "required": false,
+                        "reset": "resetBottomMargin",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 16,
+                        "name": "padding",
+                        "notify": "paddingChanged",
+                        "read": "padding",
+                        "required": false,
+                        "reset": "resetPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 17,
+                        "name": "topPadding",
+                        "notify": "topPaddingChanged",
+                        "read": "topPadding",
+                        "required": false,
+                        "reset": "resetTopPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 18,
+                        "name": "leftPadding",
+                        "notify": "leftPaddingChanged",
+                        "read": "leftPadding",
+                        "required": false,
+                        "reset": "resetLeftPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 19,
+                        "name": "rightPadding",
+                        "notify": "rightPaddingChanged",
+                        "read": "rightPadding",
+                        "required": false,
+                        "reset": "resetRightPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 20,
+                        "name": "bottomPadding",
+                        "notify": "bottomPaddingChanged",
+                        "read": "bottomPadding",
+                        "required": false,
+                        "reset": "resetBottomPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 21,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "reset": "resetLocale",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 22,
+                        "name": "font",
+                        "notify": "fontChanged",
+                        "read": "font",
+                        "required": false,
+                        "reset": "resetFont",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 23,
+                        "name": "parent",
+                        "notify": "parentChanged",
+                        "read": "parentItem",
+                        "required": false,
+                        "reset": "resetParentItem",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setParentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 24,
+                        "name": "background",
+                        "notify": "backgroundChanged",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 25,
+                        "name": "contentItem",
+                        "notify": "contentItemChanged",
+                        "read": "contentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false,
+                        "write": "setContentItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "contentData",
+                        "privateClass": "QQuickPopup::d_func()",
+                        "read": "contentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QObject>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 27,
+                        "name": "contentChildren",
+                        "notify": "contentChildrenChanged",
+                        "privateClass": "QQuickPopup::d_func()",
+                        "read": "contentChildren",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlListProperty<QQuickItem>",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 28,
+                        "name": "clip",
+                        "notify": "clipChanged",
+                        "read": "clip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setClip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 29,
+                        "name": "focus",
+                        "notify": "focusChanged",
+                        "read": "hasFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 30,
+                        "name": "activeFocus",
+                        "notify": "activeFocusChanged",
+                        "read": "hasActiveFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 31,
+                        "name": "modal",
+                        "notify": "modalChanged",
+                        "read": "isModal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setModal"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 32,
+                        "name": "dim",
+                        "notify": "dimChanged",
+                        "read": "dim",
+                        "required": false,
+                        "reset": "resetDim",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDim"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 33,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 34,
+                        "name": "opacity",
+                        "notify": "opacityChanged",
+                        "read": "opacity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOpacity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 35,
+                        "name": "scale",
+                        "notify": "scaleChanged",
+                        "read": "scale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setScale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 36,
+                        "name": "closePolicy",
+                        "notify": "closePolicyChanged",
+                        "read": "closePolicy",
+                        "required": false,
+                        "reset": "resetClosePolicy",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ClosePolicy",
+                        "user": false,
+                        "write": "setClosePolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 37,
+                        "name": "transformOrigin",
+                        "read": "transformOrigin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TransformOrigin",
+                        "user": false,
+                        "write": "setTransformOrigin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 38,
+                        "name": "enter",
+                        "notify": "enterChanged",
+                        "read": "enter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setEnter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 39,
+                        "name": "exit",
+                        "notify": "exitChanged",
+                        "read": "exit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setExit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 40,
+                        "name": "spacing",
+                        "notify": "spacingChanged",
+                        "read": "spacing",
+                        "required": false,
+                        "reset": "resetSpacing",
+                        "revision": 513,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setSpacing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 41,
+                        "name": "opened",
+                        "notify": "openedChanged",
+                        "read": "isOpened",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 42,
+                        "name": "mirrored",
+                        "notify": "mirroredChanged",
+                        "read": "isMirrored",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 43,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 44,
+                        "name": "palette",
+                        "notify": "paletteChanged",
+                        "privateClass": "QQuickPopup::d_func()",
+                        "read": "palette",
+                        "required": false,
+                        "reset": "resetPalette",
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPalette*",
+                        "user": false,
+                        "write": "setPalette"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 45,
+                        "name": "horizontalPadding",
+                        "notify": "horizontalPaddingChanged",
+                        "read": "horizontalPadding",
+                        "required": false,
+                        "reset": "resetHorizontalPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setHorizontalPadding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 46,
+                        "name": "verticalPadding",
+                        "notify": "verticalPaddingChanged",
+                        "read": "verticalPadding",
+                        "required": false,
+                        "reset": "resetVerticalPadding",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setVerticalPadding"
+                    },
+                    {
+                        "constant": true,
+                        "designable": false,
+                        "final": true,
+                        "index": 47,
+                        "name": "anchors",
+                        "privateClass": "QQuickPopup::d_func()",
+                        "read": "getAnchors",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickPopupAnchors*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 48,
+                        "name": "implicitContentWidth",
+                        "notify": "implicitContentWidthChanged",
+                        "read": "implicitContentWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 49,
+                        "name": "implicitContentHeight",
+                        "notify": "implicitContentHeightChanged",
+                        "read": "implicitContentHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 50,
+                        "name": "implicitBackgroundWidth",
+                        "notify": "implicitBackgroundWidthChanged",
+                        "read": "implicitBackgroundWidth",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 51,
+                        "name": "implicitBackgroundHeight",
+                        "notify": "implicitBackgroundHeightChanged",
+                        "read": "implicitBackgroundHeight",
+                        "required": false,
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 52,
+                        "name": "topInset",
+                        "notify": "topInsetChanged",
+                        "read": "topInset",
+                        "required": false,
+                        "reset": "resetTopInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTopInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 53,
+                        "name": "leftInset",
+                        "notify": "leftInsetChanged",
+                        "read": "leftInset",
+                        "required": false,
+                        "reset": "resetLeftInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setLeftInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 54,
+                        "name": "rightInset",
+                        "notify": "rightInsetChanged",
+                        "read": "rightInset",
+                        "required": false,
+                        "reset": "resetRightInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setRightInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 55,
+                        "name": "bottomInset",
+                        "notify": "bottomInsetChanged",
+                        "read": "bottomInset",
+                        "required": false,
+                        "reset": "resetBottomInset",
+                        "revision": 517,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setBottomInset"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 56,
+                        "name": "popupType",
+                        "notify": "popupTypeChanged",
+                        "read": "popupType",
+                        "required": false,
+                        "revision": 1544,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "PopupType",
+                        "user": false,
+                        "write": "setPopupType"
+                    }
+                ],
+                "qualifiedClassName": "QQuickPopup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "opened",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "closed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "aboutToShow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "aboutToHide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "xChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "yChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "zChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "widthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "heightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "implicitWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "implicitHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "contentWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "contentHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "availableWidthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "availableHeightChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "marginsChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "topMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "leftMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "rightMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "bottomMarginChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "paddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "topPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "leftPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "rightPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "bottomPaddingChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "fontChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "parentChanged",
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+                            "Auto"
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+                        "name": "SnapMode",
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+                            "NoSnap",
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+                            "SnapOnRelease"
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+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 25,
+                        "isCloned": true,
+                        "name": "pushItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            }
+                        ],
+                        "index": 26,
+                        "isCloned": true,
+                        "name": "pushItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "pushItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 28,
+                        "isCloned": true,
+                        "name": "pushItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 29,
+                        "isCloned": true,
+                        "name": "pushItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "popToItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 31,
+                        "isCloned": true,
+                        "name": "popToItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "popToIndex",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 33,
+                        "isCloned": true,
+                        "name": "popToIndex",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 34,
+                        "name": "popCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "index": 35,
+                        "isCloned": true,
+                        "name": "popCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QList<QQuickStackViewArg>"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "args",
+                                "type": "QList<QQuickStackViewArg>"
+                            }
+                        ],
+                        "index": 37,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 38,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 39,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QQuickItem*"
+                            }
+                        ],
+                        "index": 40,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 41,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 42,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            }
+                        ],
+                        "index": 43,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            },
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 44,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "properties",
+                                "type": "QVariantMap"
+                            }
+                        ],
+                        "index": 45,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 46,
+                        "isCloned": true,
+                        "name": "replaceCurrentItem",
+                        "returnType": "QQuickItem*",
+                        "revision": 1543
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "busy",
+                        "notify": "busyChanged",
+                        "read": "isBusy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "depth",
+                        "notify": "depthChanged",
+                        "read": "depth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "currentItem",
+                        "notify": "currentItemChanged",
+                        "read": "currentItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "initialItem",
+                        "read": "initialItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QJSValue",
+                        "user": false,
+                        "write": "setInitialItem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "popEnter",
+                        "notify": "popEnterChanged",
+                        "read": "popEnter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setPopEnter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "popExit",
+                        "notify": "popExitChanged",
+                        "read": "popExit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setPopExit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "pushEnter",
+                        "notify": "pushEnterChanged",
+                        "read": "pushEnter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setPushEnter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "pushExit",
+                        "notify": "pushExitChanged",
+                        "read": "pushExit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setPushExit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "replaceEnter",
+                        "notify": "replaceEnterChanged",
+                        "read": "replaceEnter",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setReplaceEnter"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 9,
+                        "name": "replaceExit",
+                        "notify": "replaceExitChanged",
+                        "read": "replaceExit",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickTransition*",
+                        "user": false,
+                        "write": "setReplaceExit"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 10,
+                        "name": "empty",
+                        "notify": "emptyChanged",
+                        "read": "isEmpty",
+                        "required": false,
+                        "revision": 515,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickStackView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "busyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "depthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "popEnterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "popExitChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "pushEnterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "pushExitChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "replaceEnterChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "replaceExitChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "emptyChanged",
+                        "returnType": "void",
+                        "revision": 515
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "operation",
+                                "type": "Operation"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            },
+            {
+                "className": "QQuickStackViewAttached",
+                "lineNumber": 209,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "index",
+                        "notify": "indexChanged",
+                        "read": "index",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "view",
+                        "notify": "viewChanged",
+                        "read": "view",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickStackView*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickStackView::Status",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "visible",
+                        "notify": "visibleChanged",
+                        "read": "isVisible",
+                        "required": false,
+                        "reset": "resetVisible",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    }
+                ],
+                "qualifiedClassName": "QQuickStackViewAttached",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "indexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "viewChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "activating",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "deactivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "deactivating",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "removed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "visibleChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickstackview_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "512"
+                    }
+                ],
+                "className": "QQuickSwipe",
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "close",
+                        "returnType": "void",
+                        "revision": 513
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "side",
+                                "type": "QQuickSwipeDelegate::Side"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "open",
+                        "returnType": "void",
+                        "revision": 514
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "position",
+                        "notify": "positionChanged",
+                        "read": "position",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "complete",
+                        "notify": "completeChanged",
+                        "read": "isComplete",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "left",
+                        "notify": "leftChanged",
+                        "read": "left",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setLeft"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "behind",
+                        "notify": "behindChanged",
+                        "read": "behind",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setBehind"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 4,
+                        "name": "right",
+                        "notify": "rightChanged",
+                        "read": "right",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setRight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 5,
+                        "name": "leftItem",
+                        "notify": "leftItemChanged",
+                        "read": "leftItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 6,
+                        "name": "behindItem",
+                        "notify": "behindItemChanged",
+                        "read": "behindItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 7,
+                        "name": "rightItem",
+                        "notify": "rightItemChanged",
+                        "read": "rightItem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQuickItem*",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 8,
+                        "name": "enabled",
+                        "notify": "enabledChanged",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
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+                        "values": [
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+                            "Center",
+                            "End",
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+                            "SnapPosition"
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+                            {
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+                                "type": "int"
+                            },
+                            {
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+                        "name": "positionViewAtIndex",
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+                    {
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+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "delegate",
+                        "notify": "delegateChanged",
+                        "read": "delegate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QQmlComponent*",
+                        "user": false,
+                        "write": "setDelegate"
+                    }
+                ],
+                "qualifiedClassName": "QQuickWeekNumberColumn",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "monthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "yearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "delegateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickweeknumbercolumn_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickWeekNumberModel",
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "weekNumberAt",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "weekNumber",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "indexOf",
+                        "returnType": "int"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "month",
+                        "notify": "monthChanged",
+                        "read": "month",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMonth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 1,
+                        "name": "year",
+                        "notify": "yearChanged",
+                        "read": "year",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setYear"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 2,
+                        "name": "locale",
+                        "notify": "localeChanged",
+                        "read": "locale",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": true,
+                        "designable": true,
+                        "final": true,
+                        "index": 3,
+                        "name": "count",
+                        "read": "rowCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QQuickWeekNumberModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "monthChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "yearChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "localeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickweeknumbermodel_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quicktest_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktest_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..e34d780a8a5144e8c9801c8c0e93ffbfa95e4cdf
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktest_metatypes.json
@@ -0,0 +1,1659 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Singleton",
+                        "value": "true"
+                    },
+                    {
+                        "name": "QML.Element",
+                        "value": "auto"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QTestRootObject",
+                "lineNumber": 28,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "windowShown",
+                        "notify": "windowShownChanged",
+                        "read": "windowShown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "hasTestCase",
+                        "notify": "hasTestCaseChanged",
+                        "read": "hasTestCase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHasTestCase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "defined",
+                        "read": "defined",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QObject*",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QTestRootObject",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "windowShownChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "hasTestCaseChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "quit",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "quicktest_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "anonymous"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QQuickTouchEventSequence",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QQuickTouchEventSequence",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "touchId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "press",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "touchId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "move",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "touchId",
+                                "type": "int"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "release",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "touchId",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "stationary",
+                        "returnType": "QObject*"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "commit",
+                        "returnType": "QObject*"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TestEvent"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
+                "className": "QuickTestEvent",
+                "lineNumber": 48,
+                "object": true,
+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": true,
+                        "index": 0,
+                        "name": "defaultMouseDelay",
+                        "read": "defaultMouseDelay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QuickTestEvent",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "int"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "keyPress",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "int"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "keyRelease",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "key",
+                                "type": "int"
+                            },
+                            {
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+                                "type": "int"
+                            },
+                            {
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+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "keyClick",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "name": "character",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "keyPressChar",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "character",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "keyReleaseChar",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "character",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "keyClickChar",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "keySequence",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "keySequence",
+                        "returnType": "bool",
+                        "revision": 258
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            },
+                            {
+                                "name": "x",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "y",
+                                "type": "qreal"
+                            },
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+                                "type": "int"
+                            },
+                            {
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+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "mousePress",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "type": "QObject*"
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+                                "type": "int"
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+                                "type": "int"
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+                        "returnType": "bool"
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+                            },
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+                                "type": "int"
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+                        "access": "public",
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+                                "type": "QObject*"
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+                            {
+                                "name": "delay",
+                                "type": "int"
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+                        "access": "public",
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+                                "type": "QObject*"
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+                                "type": "int"
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+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                            {
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+                                "type": "int"
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+                        "name": "mouseMove",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
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+                                "type": "QObject*"
+                            },
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+                                "type": "qreal"
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+                            {
+                                "name": "y",
+                                "type": "qreal"
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+                            {
+                                "name": "buttons",
+                                "type": "int"
+                            },
+                            {
+                                "name": "modifiers",
+                                "type": "int"
+                            },
+                            {
+                                "name": "xDelta",
+                                "type": "int"
+                            },
+                            {
+                                "name": "yDelta",
+                                "type": "int"
+                            },
+                            {
+                                "name": "delay",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "mouseWheel",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "touchEvent",
+                        "returnType": "QQuickTouchEventSequence*"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "isCloned": true,
+                        "name": "touchEvent",
+                        "returnType": "QQuickTouchEventSequence*"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
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+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "TestResult"
+                    },
+                    {
+                        "name": "QML.AddedInVersion",
+                        "value": "256"
+                    }
+                ],
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+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RunMode",
+                        "values": [
+                            "RepeatUntilValidMeasurement",
+                            "RunOnce"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "testCaseName",
+                        "notify": "testCaseNameChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
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+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
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+                        "name": "functionName",
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+                        "user": false,
+                        "write": "setFunctionName"
+                    },
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+                        "read": "dataTag",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDataTag"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "failed",
+                        "read": "isFailed",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "skipped",
+                        "notify": "skippedChanged",
+                        "read": "isSkipped",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSkipped"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "passCount",
+                        "read": "passCount",
+                        "required": false,
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+                                "name": "other",
+                                "type": "QuickTestImageObject*"
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+                        ],
+                        "index": 5,
+                        "name": "equals",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filePath",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "save",
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+                ],
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+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quicktestutilsprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktestutilsprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..b955ab79239a8646bd060a5e6158885bee66dcc8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quicktestutilsprivate_metatypes.json
@@ -0,0 +1,214 @@
+[
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+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QQmlDataTest",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "initTestCase",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "init",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmlutils_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TestHTTPServer",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "TestHTTPServer",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "newConnection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "disconnected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "readyRead",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "sendOne",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "ThreadedTestHTTPServer",
+                "lineNumber": 96,
+                "object": true,
+                "qualifiedClassName": "ThreadedTestHTTPServer",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QThread"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "testhttpserver_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QaimModel",
+                "lineNumber": 57,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "number",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "addItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "removeItem",
+                        "returnType": "void"
+                    }
+                ],
+                "object": true,
+                "qualifiedClassName": "QQuickViewTestUtils::QaimModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            },
+            {
+                "className": "StressTestModel",
+                "lineNumber": 150,
+                "object": true,
+                "qualifiedClassName": "QQuickViewTestUtils::StressTestModel",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "updateModel",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "viewtestutils_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "SignalMultiSpy",
+                "lineNumber": 131,
+                "object": true,
+                "qualifiedClassName": "QQuickVisualTestUtils::SignalMultiSpy",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "receive",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "visualtestutils_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimage_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimage_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..ad26862d918f8395c46667bcb44b1d86e3890247
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimage_metatypes.json
@@ -0,0 +1,123 @@
+[
+    {
+        "classes": [
+            {
+                "classInfos": [
+                    {
+                        "name": "QML.Element",
+                        "value": "VectorImage"
+                    }
+                ],
+                "className": "QQuickVectorImage",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FillMode",
+                        "values": [
+                            "NoResize",
+                            "PreserveAspectFit",
+                            "PreserveAspectCrop",
+                            "Stretch"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RendererType",
+                        "values": [
+                            "GeometryRenderer",
+                            "CurveRenderer"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "source",
+                        "notify": "sourceChanged",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "fillMode",
+                        "notify": "fillModeChanged",
+                        "read": "fillMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FillMode",
+                        "user": false,
+                        "write": "setFillMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "preferredRendererType",
+                        "notify": "preferredRendererTypeChanged",
+                        "read": "preferredRendererType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RendererType",
+                        "user": false,
+                        "write": "setPreferredRendererType"
+                    }
+                ],
+                "qualifiedClassName": "QQuickVectorImage",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "fillModeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "preferredRendererTypeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "updateSvgItemScale",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickvectorimage_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimagegeneratorprivate_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimagegeneratorprivate_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickvectorimagegeneratorprivate_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6quickwidgets_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6quickwidgets_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c46a99b00465e032f5b42c089898dd6ccb7e0e40
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6quickwidgets_metatypes.json
@@ -0,0 +1,202 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QQuickWidget",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ResizeMode",
+                        "values": [
+                            "SizeViewToRootObject",
+                            "SizeRootObjectToView"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Status",
+                        "values": [
+                            "Null",
+                            "Ready",
+                            "Loading",
+                            "Error"
+                        ]
+                    }
+                ],
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "resizeMode",
+                        "read": "resizeMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ResizeMode",
+                        "user": false,
+                        "write": "setResizeMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "status",
+                        "notify": "statusChanged",
+                        "read": "status",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Status",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    }
+                ],
+                "qualifiedClassName": "QQuickWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QQuickWidget::Status"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "statusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "error",
+                                "type": "QQuickWindow::SceneGraphError"
+                            },
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "sceneGraphError",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "component",
+                                "type": "QQmlComponent*"
+                            },
+                            {
+                                "name": "item",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setContent",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "continueExecute",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "createFramebufferObject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "destroyFramebufferObject",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "triggerUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "focusObject",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "propagateFocusObjectChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QQuickWidgetOffscreenWindow",
+                "lineNumber": 116,
+                "object": true,
+                "qualifiedClassName": "QQuickWidgetOffscreenWindow",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QQuickWindow"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qquickwidget_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6shadertools_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6shadertools_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6shadertools_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6sql_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6sql_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..2eb2fde0e9c5d0739ba2c1e7b07ecd745f1fd906
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6sql_metatypes.json
@@ -0,0 +1,554 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QSqlDatabase",
+                "gadget": true,
+                "lineNumber": 37,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "numericalPrecisionPolicy",
+                        "read": "numericalPrecisionPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSql::NumericalPrecisionPolicy",
+                        "user": false,
+                        "write": "setNumericalPrecisionPolicy"
+                    }
+                ],
+                "qualifiedClassName": "QSqlDatabase"
+            }
+        ],
+        "inputFile": "qsqldatabase.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlDriver",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "numericalPrecisionPolicy",
+                        "read": "numericalPrecisionPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSql::NumericalPrecisionPolicy",
+                        "user": false,
+                        "write": "setNumericalPrecisionPolicy"
+                    }
+                ],
+                "qualifiedClassName": "QSqlDriver",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "source",
+                                "type": "QSqlDriver::NotificationSource"
+                            },
+                            {
+                                "name": "payload",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "notification",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "cancelQuery",
+                        "returnType": "bool"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqldriver.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlDriverPlugin",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QSqlDriverPlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqldriverplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlField",
+                "gadget": true,
+                "lineNumber": 18,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "value",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "defaultValue",
+                        "read": "defaultValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false,
+                        "write": "setDefaultValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "tableName",
+                        "read": "tableName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTableName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "metaType",
+                        "read": "metaType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QMetaType",
+                        "user": false,
+                        "write": "setMetaType"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "requiredStatus",
+                        "read": "requiredStatus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "RequiredStatus",
+                        "user": false,
+                        "write": "setRequiredStatus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "generated",
+                        "read": "isGenerated",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setGenerated"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "autoValue",
+                        "read": "isAutoValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "length",
+                        "read": "length",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "precision",
+                        "read": "precision",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPrecision"
+                    }
+                ],
+                "qualifiedClassName": "QSqlField"
+            }
+        ],
+        "inputFile": "qsqlfield.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlIndex",
+                "gadget": true,
+                "lineNumber": 17,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "name",
+                        "read": "name",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "cursorName",
+                        "read": "cursorName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCursorName"
+                    }
+                ],
+                "qualifiedClassName": "QSqlIndex",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSqlRecord"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqlindex.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlQuery",
+                "gadget": true,
+                "lineNumber": 23,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "forwardOnly",
+                        "read": "isForwardOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setForwardOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "positionalBindingEnabled",
+                        "read": "isPositionalBindingEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setPositionalBindingEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "numericalPrecisionPolicy",
+                        "read": "numericalPrecisionPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSql::NumericalPrecisionPolicy",
+                        "user": false,
+                        "write": "setNumericalPrecisionPolicy"
+                    }
+                ],
+                "qualifiedClassName": "QSqlQuery"
+            }
+        ],
+        "inputFile": "qsqlquery.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlQueryModel",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QSqlQueryModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractTableModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqlquerymodel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlRelationalTableModel",
+                "lineNumber": 47,
+                "object": true,
+                "qualifiedClassName": "QSqlRelationalTableModel",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "revertRow",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSqlTableModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqlrelationaltablemodel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSqlTableModel",
+                "lineNumber": 21,
+                "object": true,
+                "qualifiedClassName": "QSqlTableModel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "record",
+                                "type": "QSqlRecord&"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "primeInsert",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "record",
+                                "type": "QSqlRecord&"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "beforeInsert",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "record",
+                                "type": "QSqlRecord&"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "beforeUpdate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "beforeDelete",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "select",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "selectRow",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "submit",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "revert",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "submitAll",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "revertAll",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QSqlQueryModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsqltablemodel.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6svg_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6svg_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..c5225c95c82d64d994b3601af54267f2fdaebae0
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6svg_metatypes.json
@@ -0,0 +1,217 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QSvgRenderer",
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "viewBox",
+                        "read": "viewBoxF",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setViewBox"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "framesPerSecond",
+                        "read": "framesPerSecond",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setFramesPerSecond"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentFrame",
+                        "read": "currentFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "aspectRatioMode",
+                        "read": "aspectRatioMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::AspectRatioMode",
+                        "user": false,
+                        "write": "setAspectRatioMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QtSvg::Options",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "animationEnabled",
+                        "read": "isAnimationEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAnimationEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QSvgRenderer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "repaintNeeded",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filename",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "load",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contents",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "load",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contents",
+                                "type": "QXmlStreamReader*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "load",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "p",
+                                "type": "QPainter*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "render",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "p",
+                                "type": "QPainter*"
+                            },
+                            {
+                                "name": "bounds",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "render",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "p",
+                                "type": "QPainter*"
+                            },
+                            {
+                                "name": "elementId",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "bounds",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "render",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "p",
+                                "type": "QPainter*"
+                            },
+                            {
+                                "name": "elementId",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "isCloned": true,
+                        "name": "render",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsvgrenderer.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6svgwidgets_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6svgwidgets_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..815bfdb3ac0e59f978f6e23a1fa93abdfd8a63ae
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6svgwidgets_metatypes.json
@@ -0,0 +1,110 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QSvgWidget",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QSvgWidget",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "file",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "load",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "contents",
+                                "type": "QByteArray"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "load",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsvgwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QGraphicsSvgItem",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QGraphicsItem",
+                            "id": "\"org.qt-project.Qt.QGraphicsItem\""
+                        }
+                    ]
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "elementId",
+                        "read": "elementId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setElementId"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "maximumCacheSize",
+                        "read": "maximumCacheSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setMaximumCacheSize"
+                    }
+                ],
+                "qualifiedClassName": "QGraphicsSvgItem",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_repaintItem",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QGraphicsObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgraphicssvgitem.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6test_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6test_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..aadb95f408f086028577d8243c3f0f535721bffb
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6test_metatypes.json
@@ -0,0 +1,74 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QTestEventLoop",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QTestEventLoop",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "exitLoop",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtesteventloop.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractItemModelTester",
+                "lineNumber": 33,
+                "object": true,
+                "qualifiedClassName": "QAbstractItemModelTester",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractitemmodeltester.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTestLog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LogMode",
+                        "values": [
+                            "Plain",
+                            "XML",
+                            "LightXML",
+                            "JUnitXML",
+                            "CSV",
+                            "TeamCity",
+                            "TAP"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 33,
+                "qualifiedClassName": "QTestLog"
+            }
+        ],
+        "inputFile": "qtestlog_p.h",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6uitools_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6uitools_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..490ed2ae35e2933614bbedd116581db5903fc9f8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6uitools_metatypes.json
@@ -0,0 +1,292 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QUiLoader",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QUiLoader",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "quiloader.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractFormBuilderGadget",
+                "lineNumber": 47,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "itemFlags",
+                        "read": "fakeItemFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ItemFlags",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "checkState",
+                        "read": "fakeCheckState",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CheckState",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "textAlignment",
+                        "read": "fakeAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "orientation",
+                        "read": "fakeOrientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientation",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "sizeType",
+                        "read": "fakeSizeType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizePolicy::Policy",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "colorRole",
+                        "read": "fakeColorRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPalette::ColorRole",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "colorGroup",
+                        "read": "fakeColorGroup",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPalette::ColorGroup",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "styleStrategy",
+                        "read": "fakeStyleStrategy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont::StyleStrategy",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "hintingPreference",
+                        "read": "fakeHintingPreference",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont::HintingPreference",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "fontWeight",
+                        "read": "fakeFontWeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont::Weight",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "cursorShape",
+                        "read": "fakeCursorShape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CursorShape",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "brushStyle",
+                        "read": "fakeBrushStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::BrushStyle",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "toolBarArea",
+                        "read": "fakeToolBarArea",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ToolBarArea",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "gradientType",
+                        "read": "fakeGradientType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGradient::Type",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "gradientSpread",
+                        "read": "fakeGradientSpread",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGradient::Spread",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "gradientCoordinate",
+                        "read": "fakeGradientCoordinate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGradient::CoordinateMode",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "language",
+                        "read": "fakeLanguage",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale::Language",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "country",
+                        "read": "fakeCountry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale::Country",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QFormInternal::QAbstractFormBuilderGadget",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "properties_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "TranslationWatcher",
+                "lineNumber": 188,
+                "object": true,
+                "qualifiedClassName": "QFormInternal::TranslationWatcher",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "quiloader.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6widgets_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6widgets_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ab236cefb3e5cd69b5e588d9d602d7c6d3fac78
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6widgets_metatypes.json
@@ -0,0 +1,23229 @@
+[
+    {
+        "classes": [
+            {
+                "className": "QRhiWidget",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "Api",
+                        "values": [
+                            "Null",
+                            "OpenGL",
+                            "Metal",
+                            "Vulkan",
+                            "Direct3D11",
+                            "Direct3D12"
+                        ]
+                    },
+                    {
+                        "isClass": true,
+                        "isFlag": false,
+                        "name": "TextureFormat",
+                        "values": [
+                            "RGBA8",
+                            "RGBA16F",
+                            "RGBA32F",
+                            "RGB10A2"
+                        ]
+                    }
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "sampleCount",
+                        "notify": "sampleCountChanged",
+                        "read": "sampleCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSampleCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "colorBufferFormat",
+                        "notify": "colorBufferFormatChanged",
+                        "read": "colorBufferFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TextureFormat",
+                        "user": false,
+                        "write": "setColorBufferFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "fixedColorBufferSize",
+                        "notify": "fixedColorBufferSizeChanged",
+                        "read": "fixedColorBufferSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setFixedColorBufferSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "mirrorVertically",
+                        "notify": "mirrorVerticallyChanged",
+                        "read": "isMirrorVerticallyEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMirrorVertically"
+                    }
+                ],
+                "qualifiedClassName": "QRhiWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "frameSubmitted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "renderFailed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "samples",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sampleCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "format",
+                                "type": "TextureFormat"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "colorBufferFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pixelSize",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "fixedColorBufferSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "mirrorVerticallyChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qrhiwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractButton",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "icon",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "iconSize",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "shortcut",
+                        "read": "shortcut",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QKeySequence",
+                        "user": false,
+                        "write": "setShortcut"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "checkable",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "checked",
+                        "notify": "toggled",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": true,
+                        "write": "setChecked"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "autoRepeat",
+                        "read": "autoRepeat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRepeat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "autoExclusive",
+                        "read": "autoExclusive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoExclusive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "autoRepeatDelay",
+                        "read": "autoRepeatDelay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoRepeatDelay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "autoRepeatInterval",
+                        "read": "autoRepeatInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoRepeatInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 10,
+                        "name": "down",
+                        "read": "isDown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDown"
+                    }
+                ],
+                "qualifiedClassName": "QAbstractButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "released",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "isCloned": true,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "toggled",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setIconSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "animateClick",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "click",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "toggle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setChecked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractbutton.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractItemDelegate",
+                "lineNumber": 22,
+                "object": true,
+                "qualifiedClassName": "QAbstractItemDelegate",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "commitData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QWidget*"
+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemDelegate::EndEditHint"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "closeEditor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 2,
+                        "isCloned": true,
+                        "name": "closeEditor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sizeHintChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_commitDataAndCloseEditor",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractitemdelegate.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractItemView",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SelectionMode",
+                        "values": [
+                            "NoSelection",
+                            "SingleSelection",
+                            "MultiSelection",
+                            "ExtendedSelection",
+                            "ContiguousSelection"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SelectionBehavior",
+                        "values": [
+                            "SelectItems",
+                            "SelectRows",
+                            "SelectColumns"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ScrollHint",
+                        "values": [
+                            "EnsureVisible",
+                            "PositionAtTop",
+                            "PositionAtBottom",
+                            "PositionAtCenter"
+                        ]
+                    },
+                    {
+                        "alias": "EditTrigger",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "EditTriggers",
+                        "values": [
+                            "NoEditTriggers",
+                            "CurrentChanged",
+                            "DoubleClicked",
+                            "SelectedClicked",
+                            "EditKeyPressed",
+                            "AnyKeyPressed",
+                            "AllEditTriggers"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ScrollMode",
+                        "values": [
+                            "ScrollPerItem",
+                            "ScrollPerPixel"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DragDropMode",
+                        "values": [
+                            "NoDragDrop",
+                            "DragOnly",
+                            "DropOnly",
+                            "DragDrop",
+                            "InternalMove"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "autoScroll",
+                        "read": "hasAutoScroll",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoScroll"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "autoScrollMargin",
+                        "read": "autoScrollMargin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoScrollMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "editTriggers",
+                        "read": "editTriggers",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "EditTriggers",
+                        "user": false,
+                        "write": "setEditTriggers"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "tabKeyNavigation",
+                        "read": "tabKeyNavigation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabKeyNavigation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "showDropIndicator",
+                        "read": "showDropIndicator",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDropIndicatorShown"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "dragEnabled",
+                        "read": "dragEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDragEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "dragDropOverwriteMode",
+                        "read": "dragDropOverwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDragDropOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "dragDropMode",
+                        "read": "dragDropMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DragDropMode",
+                        "user": false,
+                        "write": "setDragDropMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "defaultDropAction",
+                        "read": "defaultDropAction",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::DropAction",
+                        "user": false,
+                        "write": "setDefaultDropAction"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "alternatingRowColors",
+                        "read": "alternatingRowColors",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAlternatingRowColors"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "selectionMode",
+                        "read": "selectionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionMode",
+                        "user": false,
+                        "write": "setSelectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "selectionBehavior",
+                        "read": "selectionBehavior",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionBehavior",
+                        "user": false,
+                        "write": "setSelectionBehavior"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "iconSize",
+                        "notify": "iconSizeChanged",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "textElideMode",
+                        "read": "textElideMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextElideMode",
+                        "user": false,
+                        "write": "setTextElideMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "verticalScrollMode",
+                        "read": "verticalScrollMode",
+                        "required": false,
+                        "reset": "resetVerticalScrollMode",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ScrollMode",
+                        "user": false,
+                        "write": "setVerticalScrollMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "horizontalScrollMode",
+                        "read": "horizontalScrollMode",
+                        "required": false,
+                        "reset": "resetHorizontalScrollMode",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ScrollMode",
+                        "user": false,
+                        "write": "setHorizontalScrollMode"
+                    }
+                ],
+                "qualifiedClassName": "QAbstractItemView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "pressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "doubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "entered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "viewportEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "size",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "iconSizeChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "reset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setRootIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "doItemsLayout",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "edit",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "clearSelection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "scrollToTop",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "scrollToBottom",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "topLeft",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "bottomRight",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "roles",
+                                "type": "QList<int>"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "dataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "topLeft",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "bottomRight",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 18,
+                        "isCloned": true,
+                        "name": "dataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "rowsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "start",
+                                "type": "int"
+                            },
+                            {
+                                "name": "end",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "rowsAboutToBeRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "selected",
+                                "type": "QItemSelection"
+                            },
+                            {
+                                "name": "deselected",
+                                "type": "QItemSelection"
+                            }
+                        ],
+                        "index": 21,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 23,
+                        "name": "updateEditorData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 24,
+                        "name": "updateEditorGeometries",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 25,
+                        "name": "updateGeometries",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 26,
+                        "name": "verticalScrollbarAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "horizontalScrollbarAction",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "verticalScrollbarValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "horizontalScrollbarValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QWidget*"
+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemDelegate::EndEditHint"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "closeEditor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "commitData",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "editor",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "editorDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractitemview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractScrollArea",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizeAdjustPolicy",
+                        "values": [
+                            "AdjustIgnored",
+                            "AdjustToContentsOnFirstShow",
+                            "AdjustToContents"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "verticalScrollBarPolicy",
+                        "read": "verticalScrollBarPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScrollBarPolicy",
+                        "user": false,
+                        "write": "setVerticalScrollBarPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "horizontalScrollBarPolicy",
+                        "read": "horizontalScrollBarPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ScrollBarPolicy",
+                        "user": false,
+                        "write": "setHorizontalScrollBarPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sizeAdjustPolicy",
+                        "read": "sizeAdjustPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SizeAdjustPolicy",
+                        "user": false,
+                        "write": "setSizeAdjustPolicy"
+                    }
+                ],
+                "qualifiedClassName": "QAbstractScrollArea",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "_q_hslide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "_q_vslide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 2,
+                        "name": "_q_showOrHideScrollBars",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractscrollarea.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractScrollAreaFilter",
+                "lineNumber": 78,
+                "object": true,
+                "qualifiedClassName": "QAbstractScrollAreaFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractscrollarea_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractSlider",
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "minimum",
+                        "read": "minimum",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimum"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "maximum",
+                        "read": "maximum",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximum"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "singleStep",
+                        "read": "singleStep",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSingleStep"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "pageStep",
+                        "read": "pageStep",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setPageStep"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "value",
+                        "notify": "valueChanged",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": true,
+                        "write": "setValue"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "sliderPosition",
+                        "notify": "sliderMoved",
+                        "read": "sliderPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSliderPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "tracking",
+                        "read": "hasTracking",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTracking"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "orientation",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "invertedAppearance",
+                        "read": "invertedAppearance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInvertedAppearance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "invertedControls",
+                        "read": "invertedControls",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInvertedControls"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 10,
+                        "name": "sliderDown",
+                        "read": "isSliderDown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSliderDown"
+                    }
+                ],
+                "qualifiedClassName": "QAbstractSlider",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "sliderPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "position",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sliderMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "sliderReleased",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "min",
+                                "type": "int"
+                            },
+                            {
+                                "name": "max",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "rangeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "actionTriggered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setValue",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "Qt::Orientation"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setOrientation",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "min",
+                                "type": "int"
+                            },
+                            {
+                                "name": "max",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setRange",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractslider.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QAbstractSpinBox",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ButtonSymbols",
+                        "values": [
+                            "UpDownArrows",
+                            "PlusMinus",
+                            "NoButtons"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CorrectionMode",
+                        "values": [
+                            "CorrectToPreviousValue",
+                            "CorrectToNearestValue"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StepType",
+                        "values": [
+                            "DefaultStepType",
+                            "AdaptiveDecimalStepType"
+                        ]
+                    }
+                ],
+                "lineNumber": 20,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "wrapping",
+                        "read": "wrapping",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWrapping"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "frame",
+                        "read": "hasFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "alignment",
+                        "read": "alignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "buttonSymbols",
+                        "read": "buttonSymbols",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ButtonSymbols",
+                        "user": false,
+                        "write": "setButtonSymbols"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "specialValueText",
+                        "read": "specialValueText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setSpecialValueText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "text",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "accelerated",
+                        "read": "isAccelerated",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAccelerated"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "correctionMode",
+                        "read": "correctionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "CorrectionMode",
+                        "user": false,
+                        "write": "setCorrectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "acceptableInput",
+                        "read": "hasAcceptableInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "keyboardTracking",
+                        "read": "keyboardTracking",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setKeyboardTracking"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "showGroupSeparator",
+                        "read": "isGroupSeparatorShown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setGroupSeparatorShown"
+                    }
+                ],
+                "qualifiedClassName": "QAbstractSpinBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "editingFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "stepUp",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "stepDown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qabstractspinbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QApplication",
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "cursorFlashTime",
+                        "read": "cursorFlashTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorFlashTime"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "doubleClickInterval",
+                        "read": "doubleClickInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDoubleClickInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "keyboardInputInterval",
+                        "read": "keyboardInputInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setKeyboardInputInterval"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "wheelScrollLines",
+                        "read": "wheelScrollLines",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setWheelScrollLines"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "startDragTime",
+                        "read": "startDragTime",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setStartDragTime"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "startDragDistance",
+                        "read": "startDragDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setStartDragDistance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "styleSheet",
+                        "read": "styleSheet",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setStyleSheet"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "autoSipEnabled",
+                        "read": "autoSipEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoSipEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QApplication",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "old",
+                                "type": "QWidget*"
+                            },
+                            {
+                                "name": "now",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "focusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "sheet",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setStyleSheet",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setAutoSipEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "closeAllWindows",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "aboutQt",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QGuiApplication"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qapplication.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QBoxLayout",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QBoxLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    }
+                ]
+            },
+            {
+                "className": "QHBoxLayout",
+                "lineNumber": 77,
+                "object": true,
+                "qualifiedClassName": "QHBoxLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QBoxLayout"
+                    }
+                ]
+            },
+            {
+                "className": "QVBoxLayout",
+                "lineNumber": 90,
+                "object": true,
+                "qualifiedClassName": "QVBoxLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QBoxLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qboxlayout.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QButtonGroup",
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "exclusive",
+                        "read": "exclusive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExclusive"
+                    }
+                ],
+                "qualifiedClassName": "QButtonGroup",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractButton*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractButton*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "buttonPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractButton*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "buttonReleased",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAbstractButton*"
+                            },
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "buttonToggled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "idClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "idPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "idReleased",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "idToggled",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qbuttongroup.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCalendarWidget",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "HorizontalHeaderFormat",
+                        "values": [
+                            "NoHorizontalHeader",
+                            "SingleLetterDayNames",
+                            "ShortDayNames",
+                            "LongDayNames"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "VerticalHeaderFormat",
+                        "values": [
+                            "NoVerticalHeader",
+                            "ISOWeekNumbers"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SelectionMode",
+                        "values": [
+                            "NoSelection",
+                            "SingleSelection"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "selectedDate",
+                        "read": "selectedDate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDate",
+                        "user": false,
+                        "write": "setSelectedDate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "minimumDate",
+                        "read": "minimumDate",
+                        "required": false,
+                        "reset": "clearMinimumDate",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDate",
+                        "user": false,
+                        "write": "setMinimumDate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "maximumDate",
+                        "read": "maximumDate",
+                        "required": false,
+                        "reset": "clearMaximumDate",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QDate",
+                        "user": false,
+                        "write": "setMaximumDate"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "firstDayOfWeek",
+                        "read": "firstDayOfWeek",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::DayOfWeek",
+                        "user": false,
+                        "write": "setFirstDayOfWeek"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "gridVisible",
+                        "read": "isGridVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setGridVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "selectionMode",
+                        "read": "selectionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionMode",
+                        "user": false,
+                        "write": "setSelectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "horizontalHeaderFormat",
+                        "read": "horizontalHeaderFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "HorizontalHeaderFormat",
+                        "user": false,
+                        "write": "setHorizontalHeaderFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "verticalHeaderFormat",
+                        "read": "verticalHeaderFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "VerticalHeaderFormat",
+                        "user": false,
+                        "write": "setVerticalHeaderFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "navigationBarVisible",
+                        "read": "isNavigationBarVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setNavigationBarVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "dateEditEnabled",
+                        "read": "isDateEditEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDateEditEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "dateEditAcceptDelay",
+                        "read": "dateEditAcceptDelay",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDateEditAcceptDelay"
+                    }
+                ],
+                "qualifiedClassName": "QCalendarWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "year",
+                                "type": "int"
+                            },
+                            {
+                                "name": "month",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "currentPageChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setSelectedDate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "min",
+                                "type": "QDate"
+                            },
+                            {
+                                "name": "max",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setDateRange",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "year",
+                                "type": "int"
+                            },
+                            {
+                                "name": "month",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setCurrentPage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "show",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setGridVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setNavigationBarVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "showNextMonth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "showPreviousMonth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "showNextYear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "showPreviousYear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "showSelectedDate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "showToday",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "_q_slotShowDate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "_q_slotChangeDate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "date",
+                                "type": "QDate"
+                            },
+                            {
+                                "name": "changeMonth",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "_q_slotChangeDate",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 18,
+                        "name": "_q_editingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 19,
+                        "name": "_q_prevMonthClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 20,
+                        "name": "_q_nextMonthClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 21,
+                        "name": "_q_yearEditingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 22,
+                        "name": "_q_yearClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "act",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "_q_monthChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcalendarwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCheckBox",
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "tristate",
+                        "read": "isTristate",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTristate"
+                    }
+                ],
+                "qualifiedClassName": "QCheckBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "Qt::CheckState"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "checkStateChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcheckbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QColorDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ColorDialogOption",
+                        "values": [
+                            "ShowAlphaChannel",
+                            "NoButtons",
+                            "DontUseNativeDialog",
+                            "NoEyeDropperButton"
+                        ]
+                    }
+                ],
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "currentColor",
+                        "notify": "currentColorChanged",
+                        "read": "currentColor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QColor",
+                        "user": false,
+                        "write": "setCurrentColor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ColorDialogOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QColorDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentColorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "colorSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcolordialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QColumnView",
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "resizeGripsVisible",
+                        "read": "resizeGripsVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setResizeGripsVisible"
+                    }
+                ],
+                "qualifiedClassName": "QColumnView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "updatePreviewWidget",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcolumnview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QColumnViewGrip",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QColumnViewGrip",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "offset",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "gripMoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcolumnviewgrip_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QComboBox",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "InsertPolicy",
+                        "values": [
+                            "NoInsert",
+                            "InsertAtTop",
+                            "InsertAtCurrent",
+                            "InsertAtBottom",
+                            "InsertAfterCurrent",
+                            "InsertBeforeCurrent",
+                            "InsertAlphabetically"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizeAdjustPolicy",
+                        "values": [
+                            "AdjustToContents",
+                            "AdjustToContentsOnFirstShow",
+                            "AdjustToMinimumContentsLengthWithIcon"
+                        ]
+                    }
+                ],
+                "lineNumber": 23,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "editable",
+                        "read": "isEditable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEditable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentText",
+                        "notify": "currentTextChanged",
+                        "read": "currentText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setCurrentText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "currentIndex",
+                        "notify": "currentIndexChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "currentData",
+                        "read": "currentData",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QVariant",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "maxVisibleItems",
+                        "read": "maxVisibleItems",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxVisibleItems"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "maxCount",
+                        "read": "maxCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "insertPolicy",
+                        "read": "insertPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "InsertPolicy",
+                        "user": false,
+                        "write": "setInsertPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "sizeAdjustPolicy",
+                        "read": "sizeAdjustPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SizeAdjustPolicy",
+                        "user": false,
+                        "write": "setSizeAdjustPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "minimumContentsLength",
+                        "read": "minimumContentsLength",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumContentsLength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "iconSize",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "placeholderText",
+                        "read": "placeholderText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPlaceholderText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "duplicatesEnabled",
+                        "read": "duplicatesEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDuplicatesEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "frame",
+                        "read": "hasFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "modelColumn",
+                        "read": "modelColumn",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setModelColumn"
+                    }
+                ],
+                "qualifiedClassName": "QComboBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "editTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "textActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "highlighted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "textHighlighted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "currentIndexChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "currentTextChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "clearEditText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setEditText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setCurrentText",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcombobox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QComboBoxListView",
+                "lineNumber": 47,
+                "object": true,
+                "qualifiedClassName": "QComboBoxListView",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QListView"
+                    }
+                ]
+            },
+            {
+                "className": "QComboBoxPrivateScroller",
+                "lineNumber": 99,
+                "object": true,
+                "qualifiedClassName": "QComboBoxPrivateScroller",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "doScroll",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QComboBoxPrivateContainer",
+                "lineNumber": 180,
+                "object": true,
+                "qualifiedClassName": "QComboBoxPrivateContainer",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "resetButton",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "scrollItemView",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "hideScrollers",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "updateScrollers",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "viewDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            },
+            {
+                "className": "QComboMenuDelegate",
+                "lineNumber": 233,
+                "object": true,
+                "qualifiedClassName": "QComboMenuDelegate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemDelegate"
+                    }
+                ]
+            },
+            {
+                "className": "QComboBoxDelegate",
+                "lineNumber": 265,
+                "object": true,
+                "qualifiedClassName": "QComboBoxDelegate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStyledItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcombobox_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCommandLinkButton",
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "description",
+                        "read": "description",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDescription"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 1,
+                        "name": "flat",
+                        "read": "isFlat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFlat"
+                    }
+                ],
+                "qualifiedClassName": "QCommandLinkButton",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPushButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcommandlinkbutton.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCommonStyle",
+                "lineNumber": 14,
+                "object": true,
+                "qualifiedClassName": "QCommonStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStyle"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qcommonstyle.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QCompleter",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CompletionMode",
+                        "values": [
+                            "PopupCompletion",
+                            "UnfilteredPopupCompletion",
+                            "InlineCompletion"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ModelSorting",
+                        "values": [
+                            "UnsortedModel",
+                            "CaseSensitivelySortedModel",
+                            "CaseInsensitivelySortedModel"
+                        ]
+                    }
+                ],
+                "lineNumber": 23,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "completionPrefix",
+                        "read": "completionPrefix",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setCompletionPrefix"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "modelSorting",
+                        "read": "modelSorting",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ModelSorting",
+                        "user": false,
+                        "write": "setModelSorting"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "filterMode",
+                        "read": "filterMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::MatchFlags",
+                        "user": false,
+                        "write": "setFilterMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "completionMode",
+                        "read": "completionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "CompletionMode",
+                        "user": false,
+                        "write": "setCompletionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "completionColumn",
+                        "read": "completionColumn",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCompletionColumn"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "completionRole",
+                        "read": "completionRole",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCompletionRole"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "maxVisibleItems",
+                        "read": "maxVisibleItems",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxVisibleItems"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "caseSensitivity",
+                        "read": "caseSensitivity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CaseSensitivity",
+                        "user": false,
+                        "write": "setCaseSensitivity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "wrapAround",
+                        "read": "wrapAround",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setNotchTarget"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "notchesVisible",
+                        "read": "notchesVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setNotchesVisible"
+                    }
+                ],
+                "qualifiedClassName": "QDial",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setNotchesVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "on",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setWrapping",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSlider"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdial.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DialogCode",
+                        "values": [
+                            "Rejected",
+                            "Accepted"
+                        ]
+                    }
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "sizeGripEnabled",
+                        "read": "isSizeGripEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSizeGripEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "modal",
+                        "read": "isModal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setModal"
+                    }
+                ],
+                "qualifiedClassName": "QDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "result",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "finished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "rejected",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "open",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "exec",
+                        "returnType": "int"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "done",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "accept",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "reject",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDialogButtonBox",
+                "enums": [
+                    {
+                        "alias": "StandardButton",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "StandardButtons",
+                        "values": [
+                            "NoButton",
+                            "Ok",
+                            "Save",
+                            "SaveAll",
+                            "Open",
+                            "Yes",
+                            "YesToAll",
+                            "No",
+                            "NoToAll",
+                            "Abort",
+                            "Retry",
+                            "Ignore",
+                            "Close",
+                            "Cancel",
+                            "Discard",
+                            "Help",
+                            "Apply",
+                            "Reset",
+                            "RestoreDefaults"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "orientation",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "standardButtons",
+                        "read": "standardButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "StandardButtons",
+                        "user": false,
+                        "write": "setStandardButtons"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "centerButtons",
+                        "read": "centerButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCenterButtons"
+                    }
+                ],
+                "qualifiedClassName": "QDialogButtonBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QAbstractButton*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "helpRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "rejected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdialogbuttonbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDockWidget",
+                "enums": [
+                    {
+                        "alias": "DockWidgetFeature",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DockWidgetFeatures",
+                        "values": [
+                            "DockWidgetClosable",
+                            "DockWidgetMovable",
+                            "DockWidgetFloatable",
+                            "DockWidgetVerticalTitleBar",
+                            "DockWidgetFeatureMask",
+                            "NoDockWidgetFeatures",
+                            "Reserved"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "floating",
+                        "notify": "topLevelChanged",
+                        "read": "isFloating",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFloating"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "features",
+                        "notify": "featuresChanged",
+                        "read": "features",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DockWidgetFeatures",
+                        "user": false,
+                        "write": "setFeatures"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "allowedAreas",
+                        "notify": "allowedAreasChanged",
+                        "read": "allowedAreas",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::DockWidgetAreas",
+                        "user": false,
+                        "write": "setAllowedAreas"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "windowTitle",
+                        "read": "windowTitle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWindowTitle"
+                    }
+                ],
+                "qualifiedClassName": "QDockWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "features",
+                                "type": "QDockWidget::DockWidgetFeatures"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "featuresChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "topLevel",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "topLevelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "allowedAreas",
+                                "type": "Qt::DockWidgetAreas"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "allowedAreasChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "visibilityChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "area",
+                                "type": "Qt::DockWidgetArea"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "dockLocationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdockwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDockWidgetLayout",
+                "lineNumber": 116,
+                "object": true,
+                "qualifiedClassName": "QDockWidgetLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qdockwidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QErrorMessage",
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+                "object": true,
+                "qualifiedClassName": "QErrorMessage",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qerrormessage.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFileDialog",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ViewMode",
+                        "values": [
+                            "Detail",
+                            "List"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "FileMode",
+                        "values": [
+                            "AnyFile",
+                            "ExistingFile",
+                            "Directory",
+                            "ExistingFiles"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "AcceptMode",
+                        "values": [
+                            "AcceptOpen",
+                            "AcceptSave"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Option",
+                        "values": [
+                            "ShowDirsOnly",
+                            "DontResolveSymlinks",
+                            "DontConfirmOverwrite",
+                            "DontUseNativeDialog",
+                            "ReadOnly",
+                            "HideNameFilterDetails",
+                            "DontUseCustomDirectoryIcons"
+                        ]
+                    },
+                    {
+                        "alias": "Option",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "Options",
+                        "values": [
+                            "ShowDirsOnly",
+                            "DontResolveSymlinks",
+                            "DontConfirmOverwrite",
+                            "DontUseNativeDialog",
+                            "ReadOnly",
+                            "HideNameFilterDetails",
+                            "DontUseCustomDirectoryIcons"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "viewMode",
+                        "read": "viewMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewMode",
+                        "user": false,
+                        "write": "setViewMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "fileMode",
+                        "read": "fileMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FileMode",
+                        "user": false,
+                        "write": "setFileMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "acceptMode",
+                        "read": "acceptMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "AcceptMode",
+                        "user": false,
+                        "write": "setAcceptMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "defaultSuffix",
+                        "read": "defaultSuffix",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDefaultSuffix"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Options",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "supportedSchemes",
+                        "read": "supportedSchemes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setSupportedSchemes"
+                    }
+                ],
+                "qualifiedClassName": "QFileDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "file",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "fileSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "files",
+                                "type": "QStringList"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "filesSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "path",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "directoryEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "urlSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "urls",
+                                "type": "QList<QUrl>"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "urlsSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "currentUrlChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "directory",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "directoryUrlEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "filter",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "filterSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfiledialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFlickGesture",
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+                "object": true,
+                "qualifiedClassName": "QFlickGesture",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QGesture"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qflickgesture_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFocusFrame",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QFocusFrame",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qfocusframe.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QFontComboBox",
+                "enums": [
+                    {
+                        "alias": "FontFilter",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "FontFilters",
+                        "values": [
+                            "AllFonts",
+                            "ScalableFonts",
+                            "NonScalableFonts",
+                            "MonospacedFonts",
+                            "ProportionalFonts"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "writingSystem",
+                        "read": "writingSystem",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFontDatabase::WritingSystem",
+                        "user": false,
+                        "write": "setWritingSystem"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "fontFilters",
+                        "read": "fontFilters",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "FontFilters",
+                        "user": false,
+                        "write": "setFontFilters"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentFont",
+                        "notify": "currentFontChanged",
+                        "read": "currentFont",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setCurrentFont"
+                    }
+                ],
+                "qualifiedClassName": "QFontComboBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "f",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentFontChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "f",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setCurrentFont",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QComboBox"
+                    }
+                ]
+            }
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+                            "MonospacedFonts",
+                            "ProportionalFonts"
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+                        "index": 2,
+                        "name": "interactive",
+                        "read": "isInteractive",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setInteractive"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "sceneRect",
+                        "read": "sceneRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setSceneRect"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "alignment",
+                        "read": "alignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "renderHints",
+                        "read": "renderHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPainter::RenderHints",
+                        "user": false,
+                        "write": "setRenderHints"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "dragMode",
+                        "read": "dragMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DragMode",
+                        "user": false,
+                        "write": "setDragMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "cacheMode",
+                        "read": "cacheMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "CacheMode",
+                        "user": false,
+                        "write": "setCacheMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "transformationAnchor",
+                        "read": "transformationAnchor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewportAnchor",
+                        "user": false,
+                        "write": "setTransformationAnchor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "resizeAnchor",
+                        "read": "resizeAnchor",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewportAnchor",
+                        "user": false,
+                        "write": "setResizeAnchor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "viewportUpdateMode",
+                        "read": "viewportUpdateMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewportUpdateMode",
+                        "user": false,
+                        "write": "setViewportUpdateMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "rubberBandSelectionMode",
+                        "read": "rubberBandSelectionMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ItemSelectionMode",
+                        "user": false,
+                        "write": "setRubberBandSelectionMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "optimizationFlags",
+                        "read": "optimizationFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "OptimizationFlags",
+                        "user": false,
+                        "write": "setOptimizationFlags"
+                    }
+                ],
+                "qualifiedClassName": "QGraphicsView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "viewportRect",
+                                "type": "QRect"
+                            },
+                            {
+                                "name": "fromScenePoint",
+                                "type": "QPointF"
+                            },
+                            {
+                                "name": "toScenePoint",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "rubberBandChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rects",
+                                "type": "QList<QRectF>"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "updateScene",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            },
+                            {
+                                "name": "layers",
+                                "type": "QGraphicsScene::SceneLayers"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "invalidateScene",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 3,
+                        "isCloned": true,
+                        "name": "invalidateScene",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "isCloned": true,
+                        "name": "invalidateScene",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "updateSceneRect",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "widget",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setupViewport",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QCursor"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "_q_setViewportCursor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_unsetViewportCursor",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgraphicsview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QGraphicsWidget",
+                "interfaces": [
+                    [
+                        {
+                            "className": "QGraphicsItem",
+                            "id": "\"org.qt-project.Qt.QGraphicsItem\""
+                        }
+                    ],
+                    [
+                        {
+                            "className": "QGraphicsLayoutItem",
+                            "id": "\"org.qt-project.Qt.QGraphicsLayoutItem\""
+                        }
+                    ]
+                ],
+                "lineNumber": 31,
+                "object": true,
+                "properties": [
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+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "palette",
+                        "read": "palette",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPalette",
+                        "user": false,
+                        "write": "setPalette"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "font",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "layoutDirection",
+                        "read": "layoutDirection",
+                        "required": false,
+                        "reset": "unsetLayoutDirection",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false,
+                        "write": "setLayoutDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "size",
+                        "notify": "geometryChanged",
+                        "read": "size",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "resize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "minimumSize",
+                        "read": "minimumSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setMinimumSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "preferredSize",
+                        "read": "preferredSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setPreferredSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "maximumSize",
+                        "read": "maximumSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizeF",
+                        "user": false,
+                        "write": "setMaximumSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "sizePolicy",
+                        "read": "sizePolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizePolicy",
+                        "user": false,
+                        "write": "setSizePolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "focusPolicy",
+                        "read": "focusPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::FocusPolicy",
+                        "user": false,
+                        "write": "setFocusPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "windowFlags",
+                        "read": "windowFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowFlags",
+                        "user": false,
+                        "write": "setWindowFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "windowTitle",
+                        "read": "windowTitle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWindowTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "geometry",
+                        "notify": "geometryChanged",
+                        "read": "geometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRectF",
+                        "user": false,
+                        "write": "setGeometry"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "autoFillBackground",
+                        "read": "autoFillBackground",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoFillBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "layout",
+                        "notify": "layoutChanged",
+                        "read": "layout",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QGraphicsLayout*",
+                        "user": false,
+                        "write": "setLayout"
+                    }
+                ],
+                "qualifiedClassName": "QGraphicsWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "geometryChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "layoutChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "close",
+                        "returnType": "bool"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QGraphicsObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QGraphicsLayoutItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgraphicswidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QGridLayout",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QGridLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgridlayout.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QGroupBox",
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "title",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "alignment",
+                        "read": "alignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "flat",
+                        "read": "isFlat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFlat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "checkable",
+                        "read": "isCheckable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCheckable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "checked",
+                        "notify": "toggled",
+                        "read": "isChecked",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": true,
+                        "write": "setChecked"
+                    }
+                ],
+                "qualifiedClassName": "QGroupBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "isCloned": true,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "toggled",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "checked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setChecked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_setChildrenEnabled",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qgroupbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QHeaderView",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ResizeMode",
+                        "values": [
+                            "Interactive",
+                            "Stretch",
+                            "Fixed",
+                            "ResizeToContents",
+                            "Custom"
+                        ]
+                    }
+                ],
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "firstSectionMovable",
+                        "read": "isFirstSectionMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFirstSectionMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "showSortIndicator",
+                        "read": "isSortIndicatorShown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortIndicatorShown"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sectionsMovable",
+                        "read": "sectionsMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSectionsMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "sectionsClickable",
+                        "read": "sectionsClickable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSectionsClickable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "highlightSections",
+                        "read": "highlightSections",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHighlightSections"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "stretchLastSection",
+                        "read": "stretchLastSection",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setStretchLastSection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "cascadingSectionResizes",
+                        "read": "cascadingSectionResizes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCascadingSectionResizes"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "defaultSectionSize",
+                        "read": "defaultSectionSize",
+                        "required": false,
+                        "reset": "resetDefaultSectionSize",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDefaultSectionSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "minimumSectionSize",
+                        "read": "minimumSectionSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumSectionSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "maximumSectionSize",
+                        "read": "maximumSectionSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumSectionSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "defaultAlignment",
+                        "read": "defaultAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setDefaultAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "sortIndicatorClearable",
+                        "notify": "sortIndicatorClearableChanged",
+                        "read": "isSortIndicatorClearable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortIndicatorClearable"
+                    }
+                ],
+                "qualifiedClassName": "QHeaderView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldVisualIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newVisualIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "sectionMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldSize",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newSize",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "sectionResized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "sectionPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sectionClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "sectionEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "sectionDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "oldCount",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "sectionCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "sectionHandleDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "geometriesChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "order",
+                                "type": "Qt::SortOrder"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "sortIndicatorChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "clearable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "sortIndicatorClearableChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "offset",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setOffset",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visualIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setOffsetToSectionPosition",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "setOffsetToLastSection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "Qt::Orientation"
+                            },
+                            {
+                                "name": "logicalFirst",
+                                "type": "int"
+                            },
+                            {
+                                "name": "logicalLast",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "headerDataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "logicalIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "updateSection",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 16,
+                        "name": "resizeSections",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "logicalFirst",
+                                "type": "int"
+                            },
+                            {
+                                "name": "logicalLast",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "sectionsInserted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "logicalFirst",
+                                "type": "int"
+                            },
+                            {
+                                "name": "logicalLast",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "sectionsAboutToBeRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qheaderview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QInputDialog",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QInputDialog",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "textValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "textValueSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "intValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "intValueSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "double"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "doubleValueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "double"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "doubleValueSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qinputdialog.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QItemDelegate",
+                "lineNumber": 20,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "clipping",
+                        "read": "hasClipping",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setClipping"
+                    }
+                ],
+                "qualifiedClassName": "QItemDelegate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qitemdelegate.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QExpandingLineEdit",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QExpandingLineEdit",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "resizeToContents",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLineEdit"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qitemeditorfactory_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QKeySequenceEdit",
+                "lineNumber": 16,
+                "object": true,
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "keySequence",
+                        "notify": "keySequenceChanged",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QKeySequence",
+                        "user": true,
+                        "write": "setKeySequence"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "clearButtonEnabled",
+                        "read": "isClearButtonEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setClearButtonEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "maximumSequenceLength",
+                        "read": "maximumSequenceLength",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qsizetype",
+                        "user": false,
+                        "write": "setMaximumSequenceLength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "finishingKeyCombinations",
+                        "read": "finishingKeyCombinations",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QList<QKeyCombination>",
+                        "user": false,
+                        "write": "setFinishingKeyCombinations"
+                    }
+                ],
+                "qualifiedClassName": "QKeySequenceEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "editingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "keySequence",
+                                "type": "QKeySequence"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "keySequenceChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "keySequence",
+                                "type": "QKeySequence"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setKeySequence",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "count",
+                                "type": "qsizetype"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setMaximumSequenceLength",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qkeysequenceedit.h",
+        "outputRevision": 68
+    },
+    {
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+                "object": true,
+                "properties": [
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+                        "index": 0,
+                        "name": "text",
+                        "read": "text",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "textFormat",
+                        "read": "textFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextFormat",
+                        "user": false,
+                        "write": "setTextFormat"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "pixmap",
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+                        "stored": true,
+                        "type": "QPixmap",
+                        "user": false,
+                        "write": "setPixmap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "scaledContents",
+                        "read": "hasScaledContents",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setScaledContents"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "alignment",
+                        "read": "alignment",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "wordWrap",
+                        "read": "wordWrap",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWordWrap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "margin",
+                        "read": "margin",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMargin"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "indent",
+                        "read": "indent",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndent"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "openExternalLinks",
+                        "read": "openExternalLinks",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOpenExternalLinks"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "textInteractionFlags",
+                        "read": "textInteractionFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextInteractionFlags",
+                        "user": false,
+                        "write": "setTextInteractionFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "hasSelectedText",
+                        "read": "hasSelectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "selectedText",
+                        "read": "selectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QLabel",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "linkHovered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QPixmap"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setPixmap",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QPicture"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setPicture",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "movie",
+                                "type": "QMovie*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setMovie",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setNum",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "double"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setNum",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlabel.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLayout",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SizeConstraint",
+                        "values": [
+                            "SetDefaultConstraint",
+                            "SetNoConstraint",
+                            "SetMinimumSize",
+                            "SetFixedSize",
+                            "SetMaximumSize",
+                            "SetMinAndMaxSize"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
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+                        "name": "spacing",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSpacing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "contentsMargins",
+                        "read": "contentsMargins",
+                        "required": false,
+                        "reset": "unsetContentsMargins",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QMargins",
+                        "user": false,
+                        "write": "setContentsMargins"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sizeConstraint",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SizeConstraint",
+                        "user": false,
+                        "write": "setSizeConstraint"
+                    }
+                ],
+                "qualifiedClassName": "QLayout",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QLayoutItem"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlayout.h",
+        "outputRevision": 68
+    },
+    {
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+                        "isFlag": false,
+                        "name": "Mode",
+                        "values": [
+                            "Hex",
+                            "Dec",
+                            "Oct",
+                            "Bin"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SegmentStyle",
+                        "values": [
+                            "Outline",
+                            "Filled",
+                            "Flat"
+                        ]
+                    }
+                ],
+                "lineNumber": 15,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "smallDecimalPoint",
+                        "read": "smallDecimalPoint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSmallDecimalPoint"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "digitCount",
+                        "read": "digitCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDigitCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "mode",
+                        "read": "mode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Mode",
+                        "user": false,
+                        "write": "setMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "segmentStyle",
+                        "read": "segmentStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SegmentStyle",
+                        "user": false,
+                        "write": "setSegmentStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "value",
+                        "read": "value",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "double",
+                        "user": false,
+                        "write": "display"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "intValue",
+                        "read": "intValue",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "display"
+                    }
+                ],
+                "qualifiedClassName": "QLCDNumber",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "overflow",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "str",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "display",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "num",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "display",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "num",
+                                "type": "double"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "display",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "setHexMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "setDecMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "setOctMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "setBinMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setSmallDecimalPoint",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlcdnumber.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLineEdit",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ActionPosition",
+                        "values": [
+                            "LeadingPosition",
+                            "TrailingPosition"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "EchoMode",
+                        "values": [
+                            "Normal",
+                            "NoEcho",
+                            "Password",
+                            "PasswordEchoOnEdit"
+                        ]
+                    }
+                ],
+                "lineNumber": 27,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "property",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "inputMask",
+                        "read": "inputMask",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setInputMask"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "text",
+                        "notify": "textChanged",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "maxLength",
+                        "read": "maxLength",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaxLength"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "frame",
+                        "read": "hasFrame",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFrame"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "echoMode",
+                        "read": "echoMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "EchoMode",
+                        "user": false,
+                        "write": "setEchoMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "displayText",
+                        "read": "displayText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "cursorPosition",
+                        "read": "cursorPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "alignment",
+                        "read": "alignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setAlignment"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 8,
+                        "name": "modified",
+                        "read": "isModified",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setModified"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "hasSelectedText",
+                        "read": "hasSelectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "selectedText",
+                        "read": "selectedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "dragEnabled",
+                        "read": "dragEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDragEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "undoAvailable",
+                        "read": "isUndoAvailable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "redoAvailable",
+                        "read": "isRedoAvailable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "acceptableInput",
+                        "read": "hasAcceptableInput",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "placeholderText",
+                        "read": "placeholderText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPlaceholderText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "cursorMoveStyle",
+                        "read": "cursorMoveStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::CursorMoveStyle",
+                        "user": false,
+                        "write": "setCursorMoveStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "clearButtonEnabled",
+                        "read": "isClearButtonEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setClearButtonEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QLineEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "textEdited",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "returnPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "editingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "inputRejected",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 13,
+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "paste",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlineedit.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QLineEditIconButton",
+                "lineNumber": 48,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "opacity",
+                        "read": "opacity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setOpacity"
+                    }
+                ],
+                "qualifiedClassName": "QLineEditIconButton",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateCursor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "onAnimationFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QToolButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlineedit_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QListView",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Movement",
+                        "values": [
+                            "Static",
+                            "Free",
+                            "Snap"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Flow",
+                        "values": [
+                            "LeftToRight",
+                            "TopToBottom"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ResizeMode",
+                        "values": [
+                            "Fixed",
+                            "Adjust"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LayoutMode",
+                        "values": [
+                            "SinglePass",
+                            "Batched"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ViewMode",
+                        "values": [
+                            "ListMode",
+                            "IconMode"
+                        ]
+                    }
+                ],
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "movement",
+                        "read": "movement",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Movement",
+                        "user": false,
+                        "write": "setMovement"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "flow",
+                        "read": "flow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Flow",
+                        "user": false,
+                        "write": "setFlow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "isWrapping",
+                        "read": "isWrapping",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWrapping"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "resizeMode",
+                        "read": "resizeMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ResizeMode",
+                        "user": false,
+                        "write": "setResizeMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "layoutMode",
+                        "read": "layoutMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LayoutMode",
+                        "user": false,
+                        "write": "setLayoutMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "spacing",
+                        "read": "spacing",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSpacing"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "gridSize",
+                        "read": "gridSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setGridSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "viewMode",
+                        "read": "viewMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewMode",
+                        "user": false,
+                        "write": "setViewMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "modelColumn",
+                        "read": "modelColumn",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setModelColumn"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "uniformItemSizes",
+                        "read": "uniformItemSizes",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUniformItemSizes"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "batchSize",
+                        "read": "batchSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setBatchSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "wordWrap",
+                        "read": "wordWrap",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWordWrap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "selectionRectVisible",
+                        "read": "isSelectionRectVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSelectionRectVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "itemAlignment",
+                        "read": "itemAlignment",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Alignment",
+                        "user": false,
+                        "write": "setItemAlignment"
+                    }
+                ],
+                "qualifiedClassName": "QListView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "indexes",
+                                "type": "QModelIndexList"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "indexesMoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlistview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QListWidget",
+                "lineNumber": 163,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "currentRow",
+                        "notify": "currentRowChanged",
+                        "read": "currentRow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": true,
+                        "write": "setCurrentRow"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sortingEnabled",
+                        "read": "isSortingEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortingEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QListWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "itemClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "itemDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "itemActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "itemEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QListWidgetItem*"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QListWidgetItem*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "currentText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "currentTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "currentRow",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "currentRowChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "itemSelectionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QListWidgetItem*"
+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemView::ScrollHint"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QListWidgetItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QListView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlistwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QListModel",
+                "lineNumber": 44,
+                "object": true,
+                "qualifiedClassName": "QListModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractListModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qlistwidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMainWindow",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "DockOption",
+                        "values": [
+                            "AnimatedDocks",
+                            "AllowNestedDocks",
+                            "AllowTabbedDocks",
+                            "ForceTabbedDocks",
+                            "VerticalTabs",
+                            "GroupedDragging"
+                        ]
+                    },
+                    {
+                        "alias": "DockOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DockOptions",
+                        "values": [
+                            "AnimatedDocks",
+                            "AllowNestedDocks",
+                            "AllowTabbedDocks",
+                            "ForceTabbedDocks",
+                            "VerticalTabs",
+                            "GroupedDragging"
+                        ]
+                    }
+                ],
+                "lineNumber": 24,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "iconSize",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "toolButtonStyle",
+                        "read": "toolButtonStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ToolButtonStyle",
+                        "user": false,
+                        "write": "setToolButtonStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "animated",
+                        "read": "isAnimated",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAnimated"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "documentMode",
+                        "read": "documentMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDocumentMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "tabShape",
+                        "read": "tabShape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QTabWidget::TabShape",
+                        "user": false,
+                        "write": "setTabShape"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "dockNestingEnabled",
+                        "read": "isDockNestingEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDockNestingEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "dockOptions",
+                        "read": "dockOptions",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "DockOptions",
+                        "user": false,
+                        "write": "setDockOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "unifiedTitleAndToolBarOnMac",
+                        "read": "unifiedTitleAndToolBarOnMac",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUnifiedTitleAndToolBarOnMac"
+                    }
+                ],
+                "qualifiedClassName": "QMainWindow",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "iconSize",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "iconSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "toolButtonStyle",
+                                "type": "Qt::ToolButtonStyle"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "toolButtonStyleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "dockWidget",
+                                "type": "QDockWidget*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "tabifiedDockWidgetActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setAnimated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "enabled",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setDockNestingEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "set",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setUnifiedTitleAndToolBarOnMac",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmainwindow.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QDockWidgetGroupWindow",
+                "lineNumber": 343,
+                "object": true,
+                "qualifiedClassName": "QDockWidgetGroupWindow",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "resized",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QMainWindowLayout",
+                "lineNumber": 483,
+                "object": true,
+                "qualifiedClassName": "QMainWindowLayout",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateGapIndicator",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "tabChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "to",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "tabMoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QMainWindowLayoutSeparatorHelper<QMainWindowLayout>"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmainwindowlayout_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMdiArea",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WindowOrder",
+                        "values": [
+                            "CreationOrder",
+                            "StackingOrder",
+                            "ActivationHistoryOrder"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ViewMode",
+                        "values": [
+                            "SubWindowView",
+                            "TabbedView"
+                        ]
+                    }
+                ],
+                "lineNumber": 20,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "background",
+                        "read": "background",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QBrush",
+                        "user": false,
+                        "write": "setBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "activationOrder",
+                        "read": "activationOrder",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WindowOrder",
+                        "user": false,
+                        "write": "setActivationOrder"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "viewMode",
+                        "read": "viewMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ViewMode",
+                        "user": false,
+                        "write": "setViewMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "documentMode",
+                        "read": "documentMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDocumentMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "tabsClosable",
+                        "read": "tabsClosable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabsClosable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "tabsMovable",
+                        "read": "tabsMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabsMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "tabShape",
+                        "read": "tabShape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QTabWidget::TabShape",
+                        "user": false,
+                        "write": "setTabShape"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "tabPosition",
+                        "read": "tabPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QTabWidget::TabPosition",
+                        "user": false,
+                        "write": "setTabPosition"
+                    }
+                ],
+                "qualifiedClassName": "QMdiArea",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QMdiSubWindow*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "subWindowActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "window",
+                                "type": "QMdiSubWindow*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setActiveSubWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "tileSubWindows",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "cascadeSubWindows",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "closeActiveSubWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "closeAllSubWindows",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "activateNextSubWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "activatePreviousSubWindow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "viewport",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setupViewport",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_deactivateAllWindows",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "Qt::WindowStates"
+                            },
+                            {
+                                "type": "Qt::WindowStates"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "_q_processWindowStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "_q_currentTabChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "_q_closeTab",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "_q_moveTab",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmdiarea.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMdiSubWindow",
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "keyboardSingleStep",
+                        "read": "keyboardSingleStep",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setKeyboardSingleStep"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "keyboardPageStep",
+                        "read": "keyboardPageStep",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setKeyboardPageStep"
+                    }
+                ],
+                "qualifiedClassName": "QMdiSubWindow",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "oldState",
+                                "type": "Qt::WindowStates"
+                            },
+                            {
+                                "name": "newState",
+                                "type": "Qt::WindowStates"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "windowStateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "aboutToActivate",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "showSystemMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "showShaded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "_q_updateStaysOnTopHint",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_enterInteractiveMode",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QWidget*"
+                            },
+                            {
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "_q_processFocusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmdisubwindow.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMenu",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "tearOffEnabled",
+                        "read": "isTearOffEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTearOffEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "title",
+                        "read": "title",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "icon",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "separatorsCollapsible",
+                        "read": "separatorsCollapsible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSeparatorsCollapsible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "toolTipsVisible",
+                        "read": "toolTipsVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setToolTipsVisible"
+                    }
+                ],
+                "qualifiedClassName": "QMenu",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "aboutToShow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "aboutToHide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "hovered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "internalDelayedPopup",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 5,
+                        "name": "_q_actionTriggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_actionHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 7,
+                        "name": "_q_overrideMenuActionDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 8,
+                        "name": "_q_platformMenuAboutToShow",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmenu.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMenuBar",
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "defaultUp",
+                        "read": "isDefaultUp",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDefaultUp"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "nativeMenuBar",
+                        "read": "isNativeMenuBar",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setNativeMenuBar"
+                    }
+                ],
+                "qualifiedClassName": "QMenuBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "hovered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_actionTriggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 4,
+                        "name": "_q_actionHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "_q_internalShortcutActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 6,
+                        "name": "_q_updateLayout",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmenubar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QMessageBox",
+                "enums": [
+                    {
+                        "isClass": true,
+                        "isFlag": true,
+                        "name": "Option",
+                        "values": [
+                            "DontUseNativeDialog"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Icon",
+                        "values": [
+                            "NoIcon",
+                            "Information",
+                            "Warning",
+                            "Critical",
+                            "Question"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ButtonRole",
+                        "values": [
+                            "InvalidRole",
+                            "AcceptRole",
+                            "RejectRole",
+                            "DestructiveRole",
+                            "ActionRole",
+                            "HelpRole",
+                            "YesRole",
+                            "NoRole",
+                            "ResetRole",
+                            "ApplyRole",
+                            "NRoles"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardButton",
+                        "values": [
+                            "NoButton",
+                            "Ok",
+                            "Save",
+                            "SaveAll",
+                            "Open",
+                            "Yes",
+                            "YesToAll",
+                            "No",
+                            "NoToAll",
+                            "Abort",
+                            "Retry",
+                            "Ignore",
+                            "Close",
+                            "Cancel",
+                            "Discard",
+                            "Help",
+                            "Apply",
+                            "Reset",
+                            "RestoreDefaults",
+                            "FirstButton",
+                            "LastButton",
+                            "YesAll",
+                            "NoAll",
+                            "Default",
+                            "Escape",
+                            "FlagMask",
+                            "ButtonMask"
+                        ]
+                    },
+                    {
+                        "alias": "StandardButton",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "StandardButtons",
+                        "values": [
+                            "NoButton",
+                            "Ok",
+                            "Save",
+                            "SaveAll",
+                            "Open",
+                            "Yes",
+                            "YesToAll",
+                            "No",
+                            "NoToAll",
+                            "Abort",
+                            "Retry",
+                            "Ignore",
+                            "Close",
+                            "Cancel",
+                            "Discard",
+                            "Help",
+                            "Apply",
+                            "Reset",
+                            "RestoreDefaults",
+                            "FirstButton",
+                            "LastButton",
+                            "YesAll",
+                            "NoAll",
+                            "Default",
+                            "Escape",
+                            "FlagMask",
+                            "ButtonMask"
+                        ]
+                    }
+                ],
+                "lineNumber": 21,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "text",
+                        "read": "text",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "icon",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Icon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "iconPixmap",
+                        "read": "iconPixmap",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPixmap",
+                        "user": false,
+                        "write": "setIconPixmap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "textFormat",
+                        "read": "textFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextFormat",
+                        "user": false,
+                        "write": "setTextFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "standardButtons",
+                        "read": "standardButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "StandardButtons",
+                        "user": false,
+                        "write": "setStandardButtons"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "detailedText",
+                        "read": "detailedText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDetailedText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "informativeText",
+                        "read": "informativeText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setInformativeText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "textInteractionFlags",
+                        "read": "textInteractionFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextInteractionFlags",
+                        "user": false,
+                        "write": "setTextInteractionFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Options",
+                        "user": false,
+                        "write": "setOptions"
+                    }
+                ],
+                "qualifiedClassName": "QMessageBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "button",
+                                "type": "QAbstractButton*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "buttonClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QDialog"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qmessagebox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPixmapFilter",
+                "lineNumber": 32,
+                "object": true,
+                "qualifiedClassName": "QPixmapFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            },
+            {
+                "className": "QPixmapConvolutionFilter",
+                "lineNumber": 61,
+                "object": true,
+                "qualifiedClassName": "QPixmapConvolutionFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPixmapFilter"
+                    }
+                ]
+            },
+            {
+                "className": "QPixmapBlurFilter",
+                "lineNumber": 84,
+                "object": true,
+                "qualifiedClassName": "QPixmapBlurFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPixmapFilter"
+                    }
+                ]
+            },
+            {
+                "className": "QPixmapColorizeFilter",
+                "lineNumber": 105,
+                "object": true,
+                "qualifiedClassName": "QPixmapColorizeFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPixmapFilter"
+                    }
+                ]
+            },
+            {
+                "className": "QPixmapDropShadowFilter",
+                "lineNumber": 125,
+                "object": true,
+                "qualifiedClassName": "QPixmapDropShadowFilter",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QPixmapFilter"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpixmapfilter_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPixmapStyle",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QPixmapStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QCommonStyle"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qpixmapstyle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlainTextEdit",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LineWrapMode",
+                        "values": [
+                            "NoWrap",
+                            "WidgetWidth"
+                        ]
+                    }
+                ],
+                "lineNumber": 29,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 25,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "tabChangesFocus",
+                        "read": "tabChangesFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabChangesFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "documentTitle",
+                        "read": "documentTitle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDocumentTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "undoRedoEnabled",
+                        "read": "isUndoRedoEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUndoRedoEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "lineWrapMode",
+                        "read": "lineWrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LineWrapMode",
+                        "user": false,
+                        "write": "setLineWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "plainText",
+                        "notify": "textChanged",
+                        "read": "toPlainText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setPlainText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "overwriteMode",
+                        "read": "overwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "tabStopDistance",
+                        "read": "tabStopDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTabStopDistance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "cursorWidth",
+                        "read": "cursorWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "textInteractionFlags",
+                        "read": "textInteractionFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextInteractionFlags",
+                        "user": false,
+                        "write": "setTextInteractionFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "blockCount",
+                        "read": "blockCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "maximumBlockCount",
+                        "read": "maximumBlockCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumBlockCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "backgroundVisible",
+                        "read": "backgroundVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setBackgroundVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "centerOnScroll",
+                        "read": "centerOnScroll",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCenterOnScroll"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "placeholderText",
+                        "read": "placeholderText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPlaceholderText"
+                    }
+                ],
+                "qualifiedClassName": "QPlainTextEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "undoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "redoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
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+                        "name": "copyAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRect"
+                            },
+                            {
+                                "name": "dy",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "updateRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newBlockCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "blockCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "modificationChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "setPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
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+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "paste",
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+                    },
+                    {
+                        "access": "public",
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+                        "name": "undo",
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+                    {
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+                        "name": "redo",
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+                    },
+                    {
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+                        "name": "clear",
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+                    },
+                    {
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+                        "index": 16,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "insertPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "appendPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "html",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "appendHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "centerCursor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "range",
+                                "type": "int"
+                            }
+                        ],
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+                        "name": "zoomIn",
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+                    },
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+                        "access": "public",
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+                        "isCloned": true,
+                        "name": "zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "range",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "zoomOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "isCloned": true,
+                        "name": "zoomOut",
+                        "returnType": "void"
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+                "object": true,
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+                        "name": "cursorWidth",
+                        "read": "cursorWidth",
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+                        "scriptable": true,
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+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorWidth"
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+                ],
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+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractTextDocumentLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplaintextedit.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QPlainTextEditControl",
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+                    {
+                        "access": "public",
+                        "name": "QWidgetTextControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qplaintextedit_p.h",
+        "outputRevision": 68
+    },
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+                        "isFlag": false,
+                        "name": "Direction",
+                        "values": [
+                            "TopToBottom",
+                            "BottomToTop"
+                        ]
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+                    },
+                    {
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+                                "type": "int"
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+                                "type": "int"
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+                        "write": "setLabelText"
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+                                "type": "int"
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+                ],
+                "qualifiedClassName": "QScrollArea",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qscrollarea.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QScrollBar",
+                "lineNumber": 19,
+                "object": true,
+                "qualifiedClassName": "QScrollBar",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSlider"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qscrollbar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QScroller",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "State",
+                        "values": [
+                            "Inactive",
+                            "Pressed",
+                            "Dragging",
+                            "Scrolling"
+                        ]
+                    }
+                ],
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "state",
+                        "notify": "stateChanged",
+                        "read": "state",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "State",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "scrollerProperties",
+                        "notify": "scrollerPropertiesChanged",
+                        "read": "scrollerProperties",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QScrollerProperties",
+                        "user": false,
+                        "write": "setScrollerProperties"
+                    }
+                ],
+                "qualifiedClassName": "QScroller",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newstate",
+                                "type": "QScroller::State"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "stateChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QScrollerProperties"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "scrollerPropertiesChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "prop",
+                                "type": "QScrollerProperties"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setScrollerProperties",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "QPointF"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "scrollTo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "QPointF"
+                            },
+                            {
+                                "name": "scrollTime",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "scrollTo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            },
+                            {
+                                "name": "xmargin",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "ymargin",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "ensureVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            },
+                            {
+                                "name": "xmargin",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "ymargin",
+                                "type": "qreal"
+                            },
+                            {
+                                "name": "scrollTime",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "ensureVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resendPrepareEvent",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qscroller.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QScrollerPrivate",
+                "lineNumber": 44,
+                "object": true,
+                "qualifiedClassName": "QScrollerPrivate",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "targetDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qscroller_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUrlModel",
+                "lineNumber": 39,
+                "object": true,
+                "qualifiedClassName": "QUrlModel",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "topLeft",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "bottomRight",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "dataChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "layoutChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStandardItemModel"
+                    }
+                ]
+            },
+            {
+                "className": "QSidebar",
+                "lineNumber": 88,
+                "object": true,
+                "qualifiedClassName": "QSidebar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "url",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "goToUrl",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "clicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "position",
+                                "type": "QPoint"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "showContextMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "removeEntry",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QListView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsidebar_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSizeGrip",
+                "lineNumber": 15,
+                "object": true,
+                "qualifiedClassName": "QSizeGrip",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "_q_showIfNotHidden",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsizegrip.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSizePolicy",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Policy",
+                        "values": [
+                            "Fixed",
+                            "Minimum",
+                            "Maximum",
+                            "Preferred",
+                            "MinimumExpanding",
+                            "Expanding",
+                            "Ignored"
+                        ]
+                    },
+                    {
+                        "alias": "ControlType",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "ControlTypes",
+                        "values": [
+                            "DefaultType",
+                            "ButtonBox",
+                            "CheckBox",
+                            "ComboBox",
+                            "Frame",
+                            "GroupBox",
+                            "Label",
+                            "Line",
+                            "LineEdit",
+                            "PushButton",
+                            "RadioButton",
+                            "Slider",
+                            "SpinBox",
+                            "TabWidget",
+                            "ToolButton"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 17,
+                "qualifiedClassName": "QSizePolicy"
+            }
+        ],
+        "inputFile": "qsizepolicy.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSlider",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TickPosition",
+                        "values": [
+                            "NoTicks",
+                            "TicksAbove",
+                            "TicksLeft",
+                            "TicksBelow",
+                            "TicksRight",
+                            "TicksBothSides"
+                        ]
+                    }
+                ],
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "tickPosition",
+                        "read": "tickPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TickPosition",
+                        "user": false,
+                        "write": "setTickPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "tickInterval",
+                        "read": "tickInterval",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setTickInterval"
+                    }
+                ],
+                "qualifiedClassName": "QSlider",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSlider"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qslider.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QSpinBox",
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+                "object": true,
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+                        "final": false,
+                        "index": 0,
+                        "name": "suffix",
+                        "read": "suffix",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setSuffix"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "prefix",
+                        "read": "prefix",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPrefix"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "cleanText",
+                        "read": "cleanText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false
+                    },
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+                        "designable": true,
+                        "final": false,
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+                        "name": "minimum",
+                        "read": "minimum",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimum"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 4,
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+                        "read": "maximum",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximum"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "singleStep",
+                        "read": "singleStep",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setSingleStep"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "stepType",
+                        "read": "stepType",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "StepType",
+                        "user": false,
+                        "write": "setStepType"
+                    },
+                    {
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+                        "final": false,
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+                        "name": "value",
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+                        "scriptable": true,
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+                        "type": "int",
+                        "user": true,
+                        "write": "setValue"
+                    },
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+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "displayIntegerBase",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setDisplayIntegerBase"
+                    }
+                ],
+                "qualifiedClassName": "QSpinBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "valueChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "textChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "val",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setValue",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractSpinBox"
+                    }
+                ]
+            },
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+                "object": true,
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+                        "scriptable": true,
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+                        "type": "QString",
+                        "user": false,
+                        "write": "setPrefix"
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+                        "designable": true,
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+                        "name": "suffix",
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+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setSuffix"
+                    },
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+                        "designable": true,
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+                        "type": "QString",
+                        "user": false
+                    },
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+                        "designable": true,
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+                        "name": "decimals",
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+                        "scriptable": true,
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+                        "type": "int",
+                        "user": false,
+                        "write": "setDecimals"
+                    },
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+                        "type": "double",
+                        "user": false,
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+                        "type": "double",
+                        "user": false,
+                        "write": "setSingleStep"
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+                    {
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+                        "name": "stepType",
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+                        "type": "StepType",
+                        "user": false,
+                        "write": "setStepType"
+                    },
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+                        "type": "double",
+                        "user": true,
+                        "write": "setValue"
+                    }
+                ],
+                "qualifiedClassName": "QDoubleSpinBox",
+                "signals": [
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+                        "arguments": [
+                            {
+                                "type": "double"
+                            }
+                        ],
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+                        "name": "valueChanged",
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+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
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+                        "name": "textChanged",
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+                    }
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+                        "access": "public",
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+                            {
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+                                "type": "double"
+                            }
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+                        "name": "setValue",
+                        "returnType": "void"
+                    }
+                ],
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+                    {
+                        "access": "public",
+                        "name": "QAbstractSpinBox"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qspinbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QSplashScreen",
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+                "object": true,
+                "qualifiedClassName": "QSplashScreen",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            }
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+                        "index": 0,
+                        "name": "messageChanged",
+                        "returnType": "void"
+                    }
+                ],
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+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "alignment",
+                                "type": "int"
+                            },
+                            {
+                                "name": "color",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "message",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "alignment",
+                                "type": "int"
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+                        ],
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+                        "name": "showMessage",
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+                    {
+                        "access": "public",
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+                                "name": "message",
+                                "type": "QString"
+                            }
+                        ],
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+                        "isCloned": true,
+                        "name": "showMessage",
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+                    {
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+                        "name": "clearMessage",
+                        "returnType": "void"
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+                        "name": "QWidget"
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+        ],
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+    },
+    {
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+                        "type": "Qt::Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "opaqueResize",
+                        "read": "opaqueResize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOpaqueResize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "handleWidth",
+                        "read": "handleWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setHandleWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "childrenCollapsible",
+                        "read": "childrenCollapsible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChildrenCollapsible"
+                    }
+                ],
+                "qualifiedClassName": "QSplitter",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "int"
+                            },
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "splitterMoved",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            },
+            {
+                "className": "QSplitterHandle",
+                "lineNumber": 97,
+                "object": true,
+                "qualifiedClassName": "QSplitterHandle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsplitter.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStackedLayout",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StackingMode",
+                        "values": [
+                            "StackOne",
+                            "StackAll"
+                        ]
+                    }
+                ],
+                "lineNumber": 15,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "stackingMode",
+                        "read": "stackingMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "StackingMode",
+                        "user": false,
+                        "write": "setStackingMode"
+                    }
+                ],
+                "qualifiedClassName": "QStackedLayout",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "widgetRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setCurrentWidget",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstackedlayout.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStackedWidget",
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QStackedWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "widgetRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setCurrentWidget",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstackedwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStatusBar",
+                "lineNumber": 16,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "sizeGripEnabled",
+                        "read": "isSizeGripEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSizeGripEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QStatusBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "messageChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "timeout",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "clearMessage",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstatusbar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStyle",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StateFlag",
+                        "values": [
+                            "State_None",
+                            "State_Enabled",
+                            "State_Raised",
+                            "State_Sunken",
+                            "State_Off",
+                            "State_NoChange",
+                            "State_On",
+                            "State_DownArrow",
+                            "State_Horizontal",
+                            "State_HasFocus",
+                            "State_Top",
+                            "State_Bottom",
+                            "State_FocusAtBorder",
+                            "State_AutoRaise",
+                            "State_MouseOver",
+                            "State_UpArrow",
+                            "State_Selected",
+                            "State_Active",
+                            "State_Window",
+                            "State_Open",
+                            "State_Children",
+                            "State_Item",
+                            "State_Sibling",
+                            "State_Editing",
+                            "State_KeyboardFocusChange",
+                            "State_ReadOnly",
+                            "State_Small",
+                            "State_Mini"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PrimitiveElement",
+                        "values": [
+                            "PE_Frame",
+                            "PE_FrameDefaultButton",
+                            "PE_FrameDockWidget",
+                            "PE_FrameFocusRect",
+                            "PE_FrameGroupBox",
+                            "PE_FrameLineEdit",
+                            "PE_FrameMenu",
+                            "PE_FrameStatusBarItem",
+                            "PE_FrameTabWidget",
+                            "PE_FrameWindow",
+                            "PE_FrameButtonBevel",
+                            "PE_FrameButtonTool",
+                            "PE_FrameTabBarBase",
+                            "PE_PanelButtonCommand",
+                            "PE_PanelButtonBevel",
+                            "PE_PanelButtonTool",
+                            "PE_PanelMenuBar",
+                            "PE_PanelToolBar",
+                            "PE_PanelLineEdit",
+                            "PE_IndicatorArrowDown",
+                            "PE_IndicatorArrowLeft",
+                            "PE_IndicatorArrowRight",
+                            "PE_IndicatorArrowUp",
+                            "PE_IndicatorBranch",
+                            "PE_IndicatorButtonDropDown",
+                            "PE_IndicatorItemViewItemCheck",
+                            "PE_IndicatorCheckBox",
+                            "PE_IndicatorDockWidgetResizeHandle",
+                            "PE_IndicatorHeaderArrow",
+                            "PE_IndicatorMenuCheckMark",
+                            "PE_IndicatorProgressChunk",
+                            "PE_IndicatorRadioButton",
+                            "PE_IndicatorSpinDown",
+                            "PE_IndicatorSpinMinus",
+                            "PE_IndicatorSpinPlus",
+                            "PE_IndicatorSpinUp",
+                            "PE_IndicatorToolBarHandle",
+                            "PE_IndicatorToolBarSeparator",
+                            "PE_PanelTipLabel",
+                            "PE_IndicatorTabTear",
+                            "PE_IndicatorTabTearLeft",
+                            "PE_PanelScrollAreaCorner",
+                            "PE_Widget",
+                            "PE_IndicatorColumnViewArrow",
+                            "PE_IndicatorItemViewItemDrop",
+                            "PE_PanelItemViewItem",
+                            "PE_PanelItemViewRow",
+                            "PE_PanelStatusBar",
+                            "PE_IndicatorTabClose",
+                            "PE_PanelMenu",
+                            "PE_IndicatorTabTearRight",
+                            "PE_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ControlElement",
+                        "values": [
+                            "CE_PushButton",
+                            "CE_PushButtonBevel",
+                            "CE_PushButtonLabel",
+                            "CE_CheckBox",
+                            "CE_CheckBoxLabel",
+                            "CE_RadioButton",
+                            "CE_RadioButtonLabel",
+                            "CE_TabBarTab",
+                            "CE_TabBarTabShape",
+                            "CE_TabBarTabLabel",
+                            "CE_ProgressBar",
+                            "CE_ProgressBarGroove",
+                            "CE_ProgressBarContents",
+                            "CE_ProgressBarLabel",
+                            "CE_MenuItem",
+                            "CE_MenuScroller",
+                            "CE_MenuVMargin",
+                            "CE_MenuHMargin",
+                            "CE_MenuTearoff",
+                            "CE_MenuEmptyArea",
+                            "CE_MenuBarItem",
+                            "CE_MenuBarEmptyArea",
+                            "CE_ToolButtonLabel",
+                            "CE_Header",
+                            "CE_HeaderSection",
+                            "CE_HeaderLabel",
+                            "CE_ToolBoxTab",
+                            "CE_SizeGrip",
+                            "CE_Splitter",
+                            "CE_RubberBand",
+                            "CE_DockWidgetTitle",
+                            "CE_ScrollBarAddLine",
+                            "CE_ScrollBarSubLine",
+                            "CE_ScrollBarAddPage",
+                            "CE_ScrollBarSubPage",
+                            "CE_ScrollBarSlider",
+                            "CE_ScrollBarFirst",
+                            "CE_ScrollBarLast",
+                            "CE_FocusFrame",
+                            "CE_ComboBoxLabel",
+                            "CE_ToolBar",
+                            "CE_ToolBoxTabShape",
+                            "CE_ToolBoxTabLabel",
+                            "CE_HeaderEmptyArea",
+                            "CE_ColumnViewGrip",
+                            "CE_ItemViewItem",
+                            "CE_ShapedFrame",
+                            "CE_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SubElement",
+                        "values": [
+                            "SE_PushButtonContents",
+                            "SE_PushButtonFocusRect",
+                            "SE_CheckBoxIndicator",
+                            "SE_CheckBoxContents",
+                            "SE_CheckBoxFocusRect",
+                            "SE_CheckBoxClickRect",
+                            "SE_RadioButtonIndicator",
+                            "SE_RadioButtonContents",
+                            "SE_RadioButtonFocusRect",
+                            "SE_RadioButtonClickRect",
+                            "SE_ComboBoxFocusRect",
+                            "SE_SliderFocusRect",
+                            "SE_ProgressBarGroove",
+                            "SE_ProgressBarContents",
+                            "SE_ProgressBarLabel",
+                            "SE_ToolBoxTabContents",
+                            "SE_HeaderLabel",
+                            "SE_HeaderArrow",
+                            "SE_TabWidgetTabBar",
+                            "SE_TabWidgetTabPane",
+                            "SE_TabWidgetTabContents",
+                            "SE_TabWidgetLeftCorner",
+                            "SE_TabWidgetRightCorner",
+                            "SE_ItemViewItemCheckIndicator",
+                            "SE_TabBarTearIndicator",
+                            "SE_TabBarTearIndicatorLeft",
+                            "SE_TreeViewDisclosureItem",
+                            "SE_LineEditContents",
+                            "SE_FrameContents",
+                            "SE_DockWidgetCloseButton",
+                            "SE_DockWidgetFloatButton",
+                            "SE_DockWidgetTitleBarText",
+                            "SE_DockWidgetIcon",
+                            "SE_CheckBoxLayoutItem",
+                            "SE_ComboBoxLayoutItem",
+                            "SE_DateTimeEditLayoutItem",
+                            "SE_LabelLayoutItem",
+                            "SE_ProgressBarLayoutItem",
+                            "SE_PushButtonLayoutItem",
+                            "SE_RadioButtonLayoutItem",
+                            "SE_SliderLayoutItem",
+                            "SE_SpinBoxLayoutItem",
+                            "SE_ToolButtonLayoutItem",
+                            "SE_FrameLayoutItem",
+                            "SE_GroupBoxLayoutItem",
+                            "SE_TabWidgetLayoutItem",
+                            "SE_ItemViewItemDecoration",
+                            "SE_ItemViewItemText",
+                            "SE_ItemViewItemFocusRect",
+                            "SE_TabBarTabLeftButton",
+                            "SE_TabBarTabRightButton",
+                            "SE_TabBarTabText",
+                            "SE_ShapedFrameContents",
+                            "SE_ToolBarHandle",
+                            "SE_TabBarScrollLeftButton",
+                            "SE_TabBarScrollRightButton",
+                            "SE_TabBarTearIndicatorRight",
+                            "SE_PushButtonBevel",
+                            "SE_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ComplexControl",
+                        "values": [
+                            "CC_SpinBox",
+                            "CC_ComboBox",
+                            "CC_ScrollBar",
+                            "CC_Slider",
+                            "CC_ToolButton",
+                            "CC_TitleBar",
+                            "CC_Dial",
+                            "CC_GroupBox",
+                            "CC_MdiControls",
+                            "CC_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "SubControl",
+                        "values": [
+                            "SC_None",
+                            "SC_ScrollBarAddLine",
+                            "SC_ScrollBarSubLine",
+                            "SC_ScrollBarAddPage",
+                            "SC_ScrollBarSubPage",
+                            "SC_ScrollBarFirst",
+                            "SC_ScrollBarLast",
+                            "SC_ScrollBarSlider",
+                            "SC_ScrollBarGroove",
+                            "SC_SpinBoxUp",
+                            "SC_SpinBoxDown",
+                            "SC_SpinBoxFrame",
+                            "SC_SpinBoxEditField",
+                            "SC_ComboBoxFrame",
+                            "SC_ComboBoxEditField",
+                            "SC_ComboBoxArrow",
+                            "SC_ComboBoxListBoxPopup",
+                            "SC_SliderGroove",
+                            "SC_SliderHandle",
+                            "SC_SliderTickmarks",
+                            "SC_ToolButton",
+                            "SC_ToolButtonMenu",
+                            "SC_TitleBarSysMenu",
+                            "SC_TitleBarMinButton",
+                            "SC_TitleBarMaxButton",
+                            "SC_TitleBarCloseButton",
+                            "SC_TitleBarNormalButton",
+                            "SC_TitleBarShadeButton",
+                            "SC_TitleBarUnshadeButton",
+                            "SC_TitleBarContextHelpButton",
+                            "SC_TitleBarLabel",
+                            "SC_DialGroove",
+                            "SC_DialHandle",
+                            "SC_DialTickmarks",
+                            "SC_GroupBoxCheckBox",
+                            "SC_GroupBoxLabel",
+                            "SC_GroupBoxContents",
+                            "SC_GroupBoxFrame",
+                            "SC_MdiMinButton",
+                            "SC_MdiNormalButton",
+                            "SC_MdiCloseButton",
+                            "SC_CustomBase",
+                            "SC_All"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "PixelMetric",
+                        "values": [
+                            "PM_ButtonMargin",
+                            "PM_ButtonDefaultIndicator",
+                            "PM_MenuButtonIndicator",
+                            "PM_ButtonShiftHorizontal",
+                            "PM_ButtonShiftVertical",
+                            "PM_DefaultFrameWidth",
+                            "PM_SpinBoxFrameWidth",
+                            "PM_ComboBoxFrameWidth",
+                            "PM_MaximumDragDistance",
+                            "PM_ScrollBarExtent",
+                            "PM_ScrollBarSliderMin",
+                            "PM_SliderThickness",
+                            "PM_SliderControlThickness",
+                            "PM_SliderLength",
+                            "PM_SliderTickmarkOffset",
+                            "PM_SliderSpaceAvailable",
+                            "PM_DockWidgetSeparatorExtent",
+                            "PM_DockWidgetHandleExtent",
+                            "PM_DockWidgetFrameWidth",
+                            "PM_TabBarTabOverlap",
+                            "PM_TabBarTabHSpace",
+                            "PM_TabBarTabVSpace",
+                            "PM_TabBarBaseHeight",
+                            "PM_TabBarBaseOverlap",
+                            "PM_ProgressBarChunkWidth",
+                            "PM_SplitterWidth",
+                            "PM_TitleBarHeight",
+                            "PM_MenuScrollerHeight",
+                            "PM_MenuHMargin",
+                            "PM_MenuVMargin",
+                            "PM_MenuPanelWidth",
+                            "PM_MenuTearoffHeight",
+                            "PM_MenuDesktopFrameWidth",
+                            "PM_MenuBarPanelWidth",
+                            "PM_MenuBarItemSpacing",
+                            "PM_MenuBarVMargin",
+                            "PM_MenuBarHMargin",
+                            "PM_IndicatorWidth",
+                            "PM_IndicatorHeight",
+                            "PM_ExclusiveIndicatorWidth",
+                            "PM_ExclusiveIndicatorHeight",
+                            "PM_DialogButtonsSeparator",
+                            "PM_DialogButtonsButtonWidth",
+                            "PM_DialogButtonsButtonHeight",
+                            "PM_MdiSubWindowFrameWidth",
+                            "PM_MdiSubWindowMinimizedWidth",
+                            "PM_HeaderMargin",
+                            "PM_HeaderMarkSize",
+                            "PM_HeaderGripMargin",
+                            "PM_TabBarTabShiftHorizontal",
+                            "PM_TabBarTabShiftVertical",
+                            "PM_TabBarScrollButtonWidth",
+                            "PM_ToolBarFrameWidth",
+                            "PM_ToolBarHandleExtent",
+                            "PM_ToolBarItemSpacing",
+                            "PM_ToolBarItemMargin",
+                            "PM_ToolBarSeparatorExtent",
+                            "PM_ToolBarExtensionExtent",
+                            "PM_SpinBoxSliderHeight",
+                            "PM_ToolBarIconSize",
+                            "PM_ListViewIconSize",
+                            "PM_IconViewIconSize",
+                            "PM_SmallIconSize",
+                            "PM_LargeIconSize",
+                            "PM_FocusFrameVMargin",
+                            "PM_FocusFrameHMargin",
+                            "PM_ToolTipLabelFrameWidth",
+                            "PM_CheckBoxLabelSpacing",
+                            "PM_TabBarIconSize",
+                            "PM_SizeGripSize",
+                            "PM_DockWidgetTitleMargin",
+                            "PM_MessageBoxIconSize",
+                            "PM_ButtonIconSize",
+                            "PM_DockWidgetTitleBarButtonMargin",
+                            "PM_RadioButtonLabelSpacing",
+                            "PM_LayoutLeftMargin",
+                            "PM_LayoutTopMargin",
+                            "PM_LayoutRightMargin",
+                            "PM_LayoutBottomMargin",
+                            "PM_LayoutHorizontalSpacing",
+                            "PM_LayoutVerticalSpacing",
+                            "PM_TabBar_ScrollButtonOverlap",
+                            "PM_TextCursorWidth",
+                            "PM_TabCloseIndicatorWidth",
+                            "PM_TabCloseIndicatorHeight",
+                            "PM_ScrollView_ScrollBarSpacing",
+                            "PM_ScrollView_ScrollBarOverlap",
+                            "PM_SubMenuOverlap",
+                            "PM_TreeViewIndentation",
+                            "PM_HeaderDefaultSectionSizeHorizontal",
+                            "PM_HeaderDefaultSectionSizeVertical",
+                            "PM_TitleBarButtonIconSize",
+                            "PM_TitleBarButtonSize",
+                            "PM_LineEditIconSize",
+                            "PM_LineEditIconMargin",
+                            "PM_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ContentsType",
+                        "values": [
+                            "CT_PushButton",
+                            "CT_CheckBox",
+                            "CT_RadioButton",
+                            "CT_ToolButton",
+                            "CT_ComboBox",
+                            "CT_Splitter",
+                            "CT_ProgressBar",
+                            "CT_MenuItem",
+                            "CT_MenuBarItem",
+                            "CT_MenuBar",
+                            "CT_Menu",
+                            "CT_TabBarTab",
+                            "CT_Slider",
+                            "CT_ScrollBar",
+                            "CT_LineEdit",
+                            "CT_SpinBox",
+                            "CT_SizeGrip",
+                            "CT_TabWidget",
+                            "CT_DialogButtons",
+                            "CT_HeaderSection",
+                            "CT_GroupBox",
+                            "CT_MdiControls",
+                            "CT_ItemViewItem",
+                            "CT_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "RequestSoftwareInputPanel",
+                        "values": [
+                            "RSIP_OnMouseClickAndAlreadyFocused",
+                            "RSIP_OnMouseClick"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StyleHint",
+                        "values": [
+                            "SH_EtchDisabledText",
+                            "SH_DitherDisabledText",
+                            "SH_ScrollBar_MiddleClickAbsolutePosition",
+                            "SH_ScrollBar_ScrollWhenPointerLeavesControl",
+                            "SH_TabBar_SelectMouseType",
+                            "SH_TabBar_Alignment",
+                            "SH_Header_ArrowAlignment",
+                            "SH_Slider_SnapToValue",
+                            "SH_Slider_SloppyKeyEvents",
+                            "SH_ProgressDialog_CenterCancelButton",
+                            "SH_ProgressDialog_TextLabelAlignment",
+                            "SH_PrintDialog_RightAlignButtons",
+                            "SH_MainWindow_SpaceBelowMenuBar",
+                            "SH_FontDialog_SelectAssociatedText",
+                            "SH_Menu_AllowActiveAndDisabled",
+                            "SH_Menu_SpaceActivatesItem",
+                            "SH_Menu_SubMenuPopupDelay",
+                            "SH_ScrollView_FrameOnlyAroundContents",
+                            "SH_MenuBar_AltKeyNavigation",
+                            "SH_ComboBox_ListMouseTracking",
+                            "SH_Menu_MouseTracking",
+                            "SH_MenuBar_MouseTracking",
+                            "SH_ItemView_ChangeHighlightOnFocus",
+                            "SH_Widget_ShareActivation",
+                            "SH_Workspace_FillSpaceOnMaximize",
+                            "SH_ComboBox_Popup",
+                            "SH_TitleBar_NoBorder",
+                            "SH_Slider_StopMouseOverSlider",
+                            "SH_BlinkCursorWhenTextSelected",
+                            "SH_RichText_FullWidthSelection",
+                            "SH_Menu_Scrollable",
+                            "SH_GroupBox_TextLabelVerticalAlignment",
+                            "SH_GroupBox_TextLabelColor",
+                            "SH_Menu_SloppySubMenus",
+                            "SH_Table_GridLineColor",
+                            "SH_LineEdit_PasswordCharacter",
+                            "SH_DialogButtons_DefaultButton",
+                            "SH_ToolBox_SelectedPageTitleBold",
+                            "SH_TabBar_PreferNoArrows",
+                            "SH_ScrollBar_LeftClickAbsolutePosition",
+                            "SH_ListViewExpand_SelectMouseType",
+                            "SH_UnderlineShortcut",
+                            "SH_SpinBox_AnimateButton",
+                            "SH_SpinBox_KeyPressAutoRepeatRate",
+                            "SH_SpinBox_ClickAutoRepeatRate",
+                            "SH_Menu_FillScreenWithScroll",
+                            "SH_ToolTipLabel_Opacity",
+                            "SH_DrawMenuBarSeparator",
+                            "SH_TitleBar_ModifyNotification",
+                            "SH_Button_FocusPolicy",
+                            "SH_MessageBox_UseBorderForButtonSpacing",
+                            "SH_TitleBar_AutoRaise",
+                            "SH_ToolButton_PopupDelay",
+                            "SH_FocusFrame_Mask",
+                            "SH_RubberBand_Mask",
+                            "SH_WindowFrame_Mask",
+                            "SH_SpinControls_DisableOnBounds",
+                            "SH_Dial_BackgroundRole",
+                            "SH_ComboBox_LayoutDirection",
+                            "SH_ItemView_EllipsisLocation",
+                            "SH_ItemView_ShowDecorationSelected",
+                            "SH_ItemView_ActivateItemOnSingleClick",
+                            "SH_ScrollBar_ContextMenu",
+                            "SH_ScrollBar_RollBetweenButtons",
+                            "SH_Slider_AbsoluteSetButtons",
+                            "SH_Slider_PageSetButtons",
+                            "SH_Menu_KeyboardSearch",
+                            "SH_TabBar_ElideMode",
+                            "SH_DialogButtonLayout",
+                            "SH_ComboBox_PopupFrameStyle",
+                            "SH_MessageBox_TextInteractionFlags",
+                            "SH_DialogButtonBox_ButtonsHaveIcons",
+                            "SH_MessageBox_CenterButtons",
+                            "SH_Menu_SelectionWrap",
+                            "SH_ItemView_MovementWithoutUpdatingSelection",
+                            "SH_ToolTip_Mask",
+                            "SH_FocusFrame_AboveWidget",
+                            "SH_TextControl_FocusIndicatorTextCharFormat",
+                            "SH_WizardStyle",
+                            "SH_ItemView_ArrowKeysNavigateIntoChildren",
+                            "SH_Menu_Mask",
+                            "SH_Menu_FlashTriggeredItem",
+                            "SH_Menu_FadeOutOnHide",
+                            "SH_SpinBox_ClickAutoRepeatThreshold",
+                            "SH_ItemView_PaintAlternatingRowColorsForEmptyArea",
+                            "SH_FormLayoutWrapPolicy",
+                            "SH_TabWidget_DefaultTabPosition",
+                            "SH_ToolBar_Movable",
+                            "SH_FormLayoutFieldGrowthPolicy",
+                            "SH_FormLayoutFormAlignment",
+                            "SH_FormLayoutLabelAlignment",
+                            "SH_ItemView_DrawDelegateFrame",
+                            "SH_TabBar_CloseButtonPosition",
+                            "SH_DockWidget_ButtonsHaveFrame",
+                            "SH_ToolButtonStyle",
+                            "SH_RequestSoftwareInputPanel",
+                            "SH_ScrollBar_Transient",
+                            "SH_Menu_SupportsSections",
+                            "SH_ToolTip_WakeUpDelay",
+                            "SH_ToolTip_FallAsleepDelay",
+                            "SH_Widget_Animate",
+                            "SH_Splitter_OpaqueResize",
+                            "SH_ComboBox_UseNativePopup",
+                            "SH_LineEdit_PasswordMaskDelay",
+                            "SH_TabBar_ChangeCurrentDelay",
+                            "SH_Menu_SubMenuUniDirection",
+                            "SH_Menu_SubMenuUniDirectionFailCount",
+                            "SH_Menu_SubMenuSloppySelectOtherActions",
+                            "SH_Menu_SubMenuSloppyCloseTimeout",
+                            "SH_Menu_SubMenuResetWhenReenteringParent",
+                            "SH_Menu_SubMenuDontStartSloppyOnLeave",
+                            "SH_ItemView_ScrollMode",
+                            "SH_TitleBar_ShowToolTipsOnButtons",
+                            "SH_Widget_Animation_Duration",
+                            "SH_ComboBox_AllowWheelScrolling",
+                            "SH_SpinBox_ButtonsInsideFrame",
+                            "SH_SpinBox_StepModifier",
+                            "SH_TabBar_AllowWheelScrolling",
+                            "SH_Table_AlwaysDrawLeftTopGridLines",
+                            "SH_SpinBox_SelectOnStep",
+                            "SH_CustomBase"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "StandardPixmap",
+                        "values": [
+                            "SP_TitleBarMenuButton",
+                            "SP_TitleBarMinButton",
+                            "SP_TitleBarMaxButton",
+                            "SP_TitleBarCloseButton",
+                            "SP_TitleBarNormalButton",
+                            "SP_TitleBarShadeButton",
+                            "SP_TitleBarUnshadeButton",
+                            "SP_TitleBarContextHelpButton",
+                            "SP_DockWidgetCloseButton",
+                            "SP_MessageBoxInformation",
+                            "SP_MessageBoxWarning",
+                            "SP_MessageBoxCritical",
+                            "SP_MessageBoxQuestion",
+                            "SP_DesktopIcon",
+                            "SP_TrashIcon",
+                            "SP_ComputerIcon",
+                            "SP_DriveFDIcon",
+                            "SP_DriveHDIcon",
+                            "SP_DriveCDIcon",
+                            "SP_DriveDVDIcon",
+                            "SP_DriveNetIcon",
+                            "SP_DirOpenIcon",
+                            "SP_DirClosedIcon",
+                            "SP_DirLinkIcon",
+                            "SP_DirLinkOpenIcon",
+                            "SP_FileIcon",
+                            "SP_FileLinkIcon",
+                            "SP_ToolBarHorizontalExtensionButton",
+                            "SP_ToolBarVerticalExtensionButton",
+                            "SP_FileDialogStart",
+                            "SP_FileDialogEnd",
+                            "SP_FileDialogToParent",
+                            "SP_FileDialogNewFolder",
+                            "SP_FileDialogDetailedView",
+                            "SP_FileDialogInfoView",
+                            "SP_FileDialogContentsView",
+                            "SP_FileDialogListView",
+                            "SP_FileDialogBack",
+                            "SP_DirIcon",
+                            "SP_DialogOkButton",
+                            "SP_DialogCancelButton",
+                            "SP_DialogHelpButton",
+                            "SP_DialogOpenButton",
+                            "SP_DialogSaveButton",
+                            "SP_DialogCloseButton",
+                            "SP_DialogApplyButton",
+                            "SP_DialogResetButton",
+                            "SP_DialogDiscardButton",
+                            "SP_DialogYesButton",
+                            "SP_DialogNoButton",
+                            "SP_ArrowUp",
+                            "SP_ArrowDown",
+                            "SP_ArrowLeft",
+                            "SP_ArrowRight",
+                            "SP_ArrowBack",
+                            "SP_ArrowForward",
+                            "SP_DirHomeIcon",
+                            "SP_CommandLink",
+                            "SP_VistaShield",
+                            "SP_BrowserReload",
+                            "SP_BrowserStop",
+                            "SP_MediaPlay",
+                            "SP_MediaStop",
+                            "SP_MediaPause",
+                            "SP_MediaSkipForward",
+                            "SP_MediaSkipBackward",
+                            "SP_MediaSeekForward",
+                            "SP_MediaSeekBackward",
+                            "SP_MediaVolume",
+                            "SP_MediaVolumeMuted",
+                            "SP_LineEditClearButton",
+                            "SP_DialogYesToAllButton",
+                            "SP_DialogNoToAllButton",
+                            "SP_DialogSaveAllButton",
+                            "SP_DialogAbortButton",
+                            "SP_DialogRetryButton",
+                            "SP_DialogIgnoreButton",
+                            "SP_RestoreDefaultsButton",
+                            "SP_TabCloseButton",
+                            "NStandardPixmap",
+                            "SP_CustomBase"
+                        ]
+                    }
+                ],
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstyle.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStyleAnimation",
+                "lineNumber": 27,
+                "object": true,
+                "qualifiedClassName": "QStyleAnimation",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "start",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractAnimation"
+                    }
+                ]
+            },
+            {
+                "className": "QProgressStyleAnimation",
+                "lineNumber": 74,
+                "object": true,
+                "qualifiedClassName": "QProgressStyleAnimation",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStyleAnimation"
+                    }
+                ]
+            },
+            {
+                "className": "QNumberStyleAnimation",
+                "lineNumber": 95,
+                "object": true,
+                "qualifiedClassName": "QNumberStyleAnimation",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStyleAnimation"
+                    }
+                ]
+            },
+            {
+                "className": "QBlendStyleAnimation",
+                "lineNumber": 119,
+                "object": true,
+                "qualifiedClassName": "QBlendStyleAnimation",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QStyleAnimation"
+                    }
+                ]
+            },
+            {
+                "className": "QScrollbarStyleAnimation",
+                "lineNumber": 146,
+                "object": true,
+                "qualifiedClassName": "QScrollbarStyleAnimation",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "time",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "updateCurrentTime",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QNumberStyleAnimation"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstyleanimation_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStyledItemDelegate",
+                "lineNumber": 20,
+                "object": true,
+                "qualifiedClassName": "QStyledItemDelegate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemDelegate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstyleditemdelegate.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStylePlugin",
+                "lineNumber": 18,
+                "object": true,
+                "qualifiedClassName": "QStylePlugin",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstyleplugin.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QStyleSheetStyle",
+                "lineNumber": 39,
+                "object": true,
+                "qualifiedClassName": "QStyleSheetStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWindowsStyle"
+                    }
+                ]
+            },
+            {
+                "className": "QStyleSheetStyleCaches",
+                "lineNumber": 146,
+                "object": true,
+                "qualifiedClassName": "QStyleSheetStyleCaches",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "objectDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "styleDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qstylesheetstyle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QSystemTrayIcon",
+                "lineNumber": 25,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "toolTip",
+                        "read": "toolTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setToolTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "icon",
+                        "read": "icon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 2,
+                        "name": "visible",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    }
+                ],
+                "qualifiedClassName": "QSystemTrayIcon",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "reason",
+                                "type": "QSystemTrayIcon::ActivationReason"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "activated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "messageClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 3,
+                        "name": "show",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 4,
+                        "name": "hide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "icon",
+                                "type": "QIcon"
+                            },
+                            {
+                                "name": "msecs",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "icon",
+                                "type": "QIcon"
+                            }
+                        ],
+                        "index": 6,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "icon",
+                                "type": "QSystemTrayIcon::MessageIcon"
+                            },
+                            {
+                                "name": "msecs",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "icon",
+                                "type": "QSystemTrayIcon::MessageIcon"
+                            }
+                        ],
+                        "index": 8,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            },
+                            {
+                                "name": "msg",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 9,
+                        "isCloned": true,
+                        "name": "showMessage",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QPlatformSystemTrayIcon::ActivationReason"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "_q_emitActivated",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsystemtrayicon.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QBalloonTip",
+                "lineNumber": 80,
+                "object": true,
+                "qualifiedClassName": "QBalloonTip",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qsystemtrayicon_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTabBar",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Shape",
+                        "values": [
+                            "RoundedNorth",
+                            "RoundedSouth",
+                            "RoundedWest",
+                            "RoundedEast",
+                            "TriangularNorth",
+                            "TriangularSouth",
+                            "TriangularWest",
+                            "TriangularEast"
+                        ]
+                    }
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "shape",
+                        "read": "shape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Shape",
+                        "user": false,
+                        "write": "setShape"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "drawBase",
+                        "read": "drawBase",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDrawBase"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "iconSize",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "elideMode",
+                        "read": "elideMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextElideMode",
+                        "user": false,
+                        "write": "setElideMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "usesScrollButtons",
+                        "read": "usesScrollButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUsesScrollButtons"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "tabsClosable",
+                        "read": "tabsClosable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabsClosable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "selectionBehaviorOnRemove",
+                        "read": "selectionBehaviorOnRemove",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "SelectionBehavior",
+                        "user": false,
+                        "write": "setSelectionBehaviorOnRemove"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "expanding",
+                        "read": "expanding",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExpanding"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "movable",
+                        "read": "isMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "documentMode",
+                        "read": "documentMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDocumentMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "autoHide",
+                        "read": "autoHide",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoHide"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "changeCurrentOnDrag",
+                        "read": "changeCurrentOnDrag",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setChangeCurrentOnDrag"
+                    }
+                ],
+                "qualifiedClassName": "QTabBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "tabCloseRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "from",
+                                "type": "int"
+                            },
+                            {
+                                "name": "to",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "tabMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "tabBarClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "tabBarDoubleClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtabbar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTableView",
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "showGrid",
+                        "read": "showGrid",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setShowGrid"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "gridStyle",
+                        "read": "gridStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::PenStyle",
+                        "user": false,
+                        "write": "setGridStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "sortingEnabled",
+                        "read": "isSortingEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setSortingEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "wordWrap",
+                        "read": "wordWrap",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWordWrap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "cornerButtonEnabled",
+                        "read": "isCornerButtonEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setCornerButtonEnabled"
+                    }
+                ],
+                "qualifiedClassName": "QTableView",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "selectRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "selectColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "hideRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "hideColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "showRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "showColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "resizeRowToContents",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "resizeRowsToContents",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "resizeColumnToContents",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "resizeColumnsToContents",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "order",
+                                "type": "Qt::SortOrder"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "sortByColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "show",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setShowGrid",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "rowMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldIndex",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newIndex",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "columnMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldHeight",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newHeight",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "rowResized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldWidth",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newWidth",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "columnResized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "oldCount",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "rowCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "oldCount",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "columnCountChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtableview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTableWidget",
+                "lineNumber": 192,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "rowCount",
+                        "read": "rowCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setRowCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "columnCount",
+                        "read": "columnCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setColumnCount"
+                    }
+                ],
+                "qualifiedClassName": "QTableWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "itemClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "itemDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "itemActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "itemEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QTableWidgetItem*"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "itemSelectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "cellPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "cellClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "cellDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "cellActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "cellEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "cellChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "currentRow",
+                                "type": "int"
+                            },
+                            {
+                                "name": "currentColumn",
+                                "type": "int"
+                            },
+                            {
+                                "name": "previousRow",
+                                "type": "int"
+                            },
+                            {
+                                "name": "previousColumn",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "currentCellChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTableWidgetItem*"
+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemView::ScrollHint"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTableWidgetItem*"
+                            }
+                        ],
+                        "index": 16,
+                        "isCloned": true,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "insertRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "insertColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "row",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "removeRow",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 20,
+                        "name": "removeColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "clearContents",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTableView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtablewidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTableWidgetMimeData",
+                "lineNumber": 31,
+                "object": true,
+                "qualifiedClassName": "QTableWidgetMimeData",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QMimeData"
+                    }
+                ]
+            },
+            {
+                "className": "QTableModel",
+                "lineNumber": 52,
+                "object": true,
+                "qualifiedClassName": "QTableModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractTableModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtablewidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTabWidget",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TabPosition",
+                        "values": [
+                            "North",
+                            "South",
+                            "West",
+                            "East"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "TabShape",
+                        "values": [
+                            "Rounded",
+                            "Triangular"
+                        ]
+                    }
+                ],
+                "lineNumber": 19,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "tabPosition",
+                        "read": "tabPosition",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TabPosition",
+                        "user": false,
+                        "write": "setTabPosition"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "tabShape",
+                        "read": "tabShape",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "TabShape",
+                        "user": false,
+                        "write": "setTabShape"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "iconSize",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "elideMode",
+                        "read": "elideMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextElideMode",
+                        "user": false,
+                        "write": "setElideMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "usesScrollButtons",
+                        "read": "usesScrollButtons",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUsesScrollButtons"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "documentMode",
+                        "read": "documentMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setDocumentMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "tabsClosable",
+                        "read": "tabsClosable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabsClosable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "movable",
+                        "read": "isMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "tabBarAutoHide",
+                        "read": "tabBarAutoHide",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabBarAutoHide"
+                    }
+                ],
+                "qualifiedClassName": "QTabWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "tabCloseRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "tabBarClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "tabBarDoubleClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "widget",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setCurrentWidget",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtabwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextBrowser",
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "source",
+                        "read": "source",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QUrl",
+                        "user": false,
+                        "write": "setSource"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "sourceType",
+                        "read": "sourceType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QTextDocument::ResourceType",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "searchPaths",
+                        "read": "searchPaths",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QStringList",
+                        "user": false,
+                        "write": "setSearchPaths"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "openExternalLinks",
+                        "read": "openExternalLinks",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOpenExternalLinks"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "openLinks",
+                        "read": "openLinks",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOpenLinks"
+                    }
+                ],
+                "qualifiedClassName": "QTextBrowser",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "backwardAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "forwardAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 2,
+                        "name": "historyChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "sourceChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "highlighted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "anchorClicked",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QUrl"
+                            },
+                            {
+                                "name": "type",
+                                "type": "QTextDocument::ResourceType"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 7,
+                        "isCloned": true,
+                        "name": "setSource",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "backward",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "forward",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "home",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "reload",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTextEdit"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextbrowser.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTextEdit",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "LineWrapMode",
+                        "values": [
+                            "NoWrap",
+                            "WidgetWidth",
+                            "FixedPixelWidth",
+                            "FixedColumnWidth"
+                        ]
+                    },
+                    {
+                        "alias": "AutoFormattingFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "AutoFormatting",
+                        "values": [
+                            "AutoNone",
+                            "AutoBulletList",
+                            "AutoAll"
+                        ]
+                    }
+                ],
+                "lineNumber": 26,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 35,
+                        "name": "loadResource",
+                        "returnType": "QVariant"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            },
+                            {
+                                "name": "argument",
+                                "type": "QVariant"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "inputMethodQuery",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "autoFormatting",
+                        "read": "autoFormatting",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "AutoFormatting",
+                        "user": false,
+                        "write": "setAutoFormatting"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "tabChangesFocus",
+                        "read": "tabChangesFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabChangesFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "documentTitle",
+                        "read": "documentTitle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setDocumentTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "undoRedoEnabled",
+                        "read": "isUndoRedoEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUndoRedoEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "lineWrapMode",
+                        "read": "lineWrapMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "LineWrapMode",
+                        "user": false,
+                        "write": "setLineWrapMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "lineWrapColumnOrWidth",
+                        "read": "lineWrapColumnOrWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setLineWrapColumnOrWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "readOnly",
+                        "read": "isReadOnly",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setReadOnly"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "markdown",
+                        "notify": "textChanged",
+                        "read": "toMarkdown",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setMarkdown"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "html",
+                        "notify": "textChanged",
+                        "read": "toHtml",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setHtml"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 9,
+                        "name": "plainText",
+                        "read": "toPlainText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPlainText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "overwriteMode",
+                        "read": "overwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "tabStopDistance",
+                        "read": "tabStopDistance",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "qreal",
+                        "user": false,
+                        "write": "setTabStopDistance"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "acceptRichText",
+                        "read": "acceptRichText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAcceptRichText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "cursorWidth",
+                        "read": "cursorWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "textInteractionFlags",
+                        "read": "textInteractionFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextInteractionFlags",
+                        "user": false,
+                        "write": "setTextInteractionFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 15,
+                        "name": "document",
+                        "read": "document",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QTextDocument*",
+                        "user": false,
+                        "write": "setDocument"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "placeholderText",
+                        "read": "placeholderText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setPlaceholderText"
+                    }
+                ],
+                "qualifiedClassName": "QTextEdit",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "undoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "redoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "format",
+                                "type": "QTextCharFormat"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "currentCharFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "copyAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "s",
+                                "type": "qreal"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setFontPointSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "fontFamily",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setFontFamily",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "w",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setFontWeight",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "setFontUnderline",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "setFontItalic",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "c",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setTextColor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "c",
+                                "type": "QColor"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setTextBackgroundColor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "f",
+                                "type": "QFont"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "setCurrentFont",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "a",
+                                "type": "Qt::Alignment"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "setAlignment",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "setPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "setHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "markdown",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "setMarkdown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "setText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "insertPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "insertHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "append",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "name",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "scrollToAnchor",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "range",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 32,
+                        "isCloned": true,
+                        "name": "zoomIn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "range",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 33,
+                        "name": "zoomOut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 34,
+                        "isCloned": true,
+                        "name": "zoomOut",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractScrollArea"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtextedit.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolBar",
+                "lineNumber": 22,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "movable",
+                        "notify": "movableChanged",
+                        "read": "isMovable",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMovable"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "allowedAreas",
+                        "notify": "allowedAreasChanged",
+                        "read": "allowedAreas",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ToolBarAreas",
+                        "user": false,
+                        "write": "setAllowedAreas"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "orientation",
+                        "notify": "orientationChanged",
+                        "read": "orientation",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::Orientation",
+                        "user": false,
+                        "write": "setOrientation"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "iconSize",
+                        "notify": "iconSizeChanged",
+                        "read": "iconSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setIconSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "toolButtonStyle",
+                        "notify": "toolButtonStyleChanged",
+                        "read": "toolButtonStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ToolButtonStyle",
+                        "user": false,
+                        "write": "setToolButtonStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "floating",
+                        "read": "isFloating",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "floatable",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setFloatable"
+                    }
+                ],
+                "qualifiedClassName": "QToolBar",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "action",
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "actionTriggered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "movable",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "movableChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "allowedAreas",
+                                "type": "Qt::ToolBarAreas"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "allowedAreasChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "Qt::Orientation"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "orientationChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "iconSize",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "iconSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "toolButtonStyle",
+                                "type": "Qt::ToolButtonStyle"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "toolButtonStyleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "topLevel",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "topLevelChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "visibilityChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "iconSize",
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setIconSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "toolButtonStyle",
+                                "type": "Qt::ToolButtonStyle"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "setToolButtonStyle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "_q_toggleView",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QSize"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "_q_updateIconSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "Qt::ToolButtonStyle"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "_q_updateToolButtonStyle",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbar.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolBarExtension",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QToolBarExtension",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "o",
+                                "type": "Qt::Orientation"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setOrientation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QToolButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbarextension_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolBarLayout",
+                "lineNumber": 41,
+                "object": true,
+                "qualifiedClassName": "QToolBarLayout",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setExpanded",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLayout"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbarlayout_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolBarSeparator",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QToolBarSeparator",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "orientation",
+                                "type": "Qt::Orientation"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setOrientation",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbarseparator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
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+                "className": "QToolBox",
+                "lineNumber": 17,
+                "object": true,
+                "properties": [
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "currentIndex",
+                        "notify": "currentChanged",
+                        "read": "currentIndex",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentIndex"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "count",
+                        "read": "count",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QToolBox",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setCurrentIndex",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "widget",
+                                "type": "QWidget*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setCurrentWidget",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 3,
+                        "name": "_q_buttonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "_q_widgetDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QFrame"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbox.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolButton",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "ToolButtonPopupMode",
+                        "values": [
+                            "DelayedPopup",
+                            "MenuButtonPopup",
+                            "InstantPopup"
+                        ]
+                    }
+                ],
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+                "object": true,
+                "properties": [
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "popupMode",
+                        "read": "popupMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "ToolButtonPopupMode",
+                        "user": false,
+                        "write": "setPopupMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "toolButtonStyle",
+                        "read": "toolButtonStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ToolButtonStyle",
+                        "user": false,
+                        "write": "setToolButtonStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "autoRaise",
+                        "read": "autoRaise",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoRaise"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "arrowType",
+                        "read": "arrowType",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ArrowType",
+                        "user": false,
+                        "write": "setArrowType"
+                    }
+                ],
+                "qualifiedClassName": "QToolButton",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "triggered",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "showMenu",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "style",
+                                "type": "Qt::ToolButtonStyle"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "setToolButtonStyle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QAction*"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setDefaultAction",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbutton.h",
+        "outputRevision": 68
+    },
+    {
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+                "object": true,
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+                        "name": "autoExpandDelay",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setAutoExpandDelay"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "indentation",
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+                        "reset": "resetIndentation",
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+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setIndentation"
+                    },
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+                        "index": 2,
+                        "name": "rootIsDecorated",
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+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setRootIsDecorated"
+                    },
+                    {
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+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "uniformRowHeights",
+                        "read": "uniformRowHeights",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUniformRowHeights"
+                    },
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+                        "name": "itemsExpandable",
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+                        "scriptable": true,
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+                        "type": "bool",
+                        "user": false,
+                        "write": "setItemsExpandable"
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+                        "name": "sortingEnabled",
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+                        "scriptable": true,
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+                        "type": "bool",
+                        "user": false,
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+                        "final": false,
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+                        "name": "animated",
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+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAnimated"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "allColumnsShowFocus",
+                        "read": "allColumnsShowFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAllColumnsShowFocus"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 8,
+                        "name": "wordWrap",
+                        "read": "wordWrap",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWordWrap"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "headerHidden",
+                        "read": "isHeaderHidden",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setHeaderHidden"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 10,
+                        "name": "expandsOnDoubleClick",
+                        "read": "expandsOnDoubleClick",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setExpandsOnDoubleClick"
+                    }
+                ],
+                "qualifiedClassName": "QTreeView",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "expanded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "collapsed",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "hideColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "showColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "expand",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "collapse",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "resizeColumnToContents",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "order",
+                                "type": "Qt::SortOrder"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "sortByColumn",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "expandAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "depth",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "expandRecursively",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 10,
+                        "isCloned": true,
+                        "name": "expandRecursively",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "collapseAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "depth",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "expandToDepth",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "column",
+                                "type": "int"
+                            },
+                            {
+                                "name": "oldSize",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newSize",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "columnResized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "oldCount",
+                                "type": "int"
+                            },
+                            {
+                                "name": "newCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "columnCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 15,
+                        "name": "columnMoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 16,
+                        "name": "reexpand",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "parent",
+                                "type": "QModelIndex"
+                            },
+                            {
+                                "name": "first",
+                                "type": "int"
+                            },
+                            {
+                                "name": "last",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "rowsRemoved",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "value",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "verticalScrollbarValueChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtreeview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTreeWidget",
+                "lineNumber": 225,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "columnCount",
+                        "read": "columnCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setColumnCount"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "topLevelItemCount",
+                        "read": "topLevelItemCount",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    }
+                ],
+                "qualifiedClassName": "QTreeWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "itemPressed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "itemClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "itemDoubleClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "itemActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "itemEntered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "column",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "itemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "itemExpanded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "itemCollapsed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "current",
+                                "type": "QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "previous",
+                                "type": "QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "currentItemChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "itemSelectionChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTreeWidgetItem*"
+                            },
+                            {
+                                "name": "hint",
+                                "type": "QAbstractItemView::ScrollHint"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 11,
+                        "isCloned": true,
+                        "name": "scrollToItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "expandItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "item",
+                                "type": "const QTreeWidgetItem*"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "collapseItem",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "clear",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QTreeView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtreewidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTreeModel",
+                "lineNumber": 36,
+                "object": true,
+                "qualifiedClassName": "QTreeModel",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtreewidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUndoView",
+                "lineNumber": 21,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "emptyLabel",
+                        "read": "emptyLabel",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setEmptyLabel"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "cleanIcon",
+                        "read": "cleanIcon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setCleanIcon"
+                    }
+                ],
+                "qualifiedClassName": "QUndoView",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stack",
+                                "type": "QUndoStack*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setStack",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "group",
+                                "type": "QUndoGroup*"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "setGroup",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QListView"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qundoview.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidget",
+                "lineNumber": 98,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rectangle",
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 27,
+                        "name": "grab",
+                        "returnType": "QPixmap"
+                    },
+                    {
+                        "access": "public",
+                        "index": 28,
+                        "isCloned": true,
+                        "name": "grab",
+                        "returnType": "QPixmap"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "modal",
+                        "read": "isModal",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "windowModality",
+                        "read": "windowModality",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::WindowModality",
+                        "user": false,
+                        "write": "setWindowModality"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "enabled",
+                        "read": "isEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "geometry",
+                        "read": "geometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false,
+                        "write": "setGeometry"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "frameGeometry",
+                        "read": "frameGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "normalGeometry",
+                        "read": "normalGeometry",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "x",
+                        "read": "x",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 7,
+                        "name": "y",
+                        "read": "y",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 8,
+                        "name": "pos",
+                        "read": "pos",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QPoint",
+                        "user": false,
+                        "write": "move"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 9,
+                        "name": "frameSize",
+                        "read": "frameSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 10,
+                        "name": "size",
+                        "read": "size",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "resize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 11,
+                        "name": "width",
+                        "read": "width",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 12,
+                        "name": "height",
+                        "read": "height",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 13,
+                        "name": "rect",
+                        "read": "rect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 14,
+                        "name": "childrenRect",
+                        "read": "childrenRect",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRect",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 15,
+                        "name": "childrenRegion",
+                        "read": "childrenRegion",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QRegion",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 16,
+                        "name": "sizePolicy",
+                        "read": "sizePolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSizePolicy",
+                        "user": false,
+                        "write": "setSizePolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 17,
+                        "name": "minimumSize",
+                        "read": "minimumSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setMinimumSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 18,
+                        "name": "maximumSize",
+                        "read": "maximumSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setMaximumSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 19,
+                        "name": "minimumWidth",
+                        "read": "minimumWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 20,
+                        "name": "minimumHeight",
+                        "read": "minimumHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMinimumHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 21,
+                        "name": "maximumWidth",
+                        "read": "maximumWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 22,
+                        "name": "maximumHeight",
+                        "read": "maximumHeight",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": false,
+                        "type": "int",
+                        "user": false,
+                        "write": "setMaximumHeight"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 23,
+                        "name": "sizeIncrement",
+                        "read": "sizeIncrement",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setSizeIncrement"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 24,
+                        "name": "baseSize",
+                        "read": "baseSize",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false,
+                        "write": "setBaseSize"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 25,
+                        "name": "palette",
+                        "read": "palette",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QPalette",
+                        "user": false,
+                        "write": "setPalette"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 26,
+                        "name": "font",
+                        "read": "font",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QFont",
+                        "user": false,
+                        "write": "setFont"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 27,
+                        "name": "cursor",
+                        "read": "cursor",
+                        "required": false,
+                        "reset": "unsetCursor",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QCursor",
+                        "user": false,
+                        "write": "setCursor"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 28,
+                        "name": "mouseTracking",
+                        "read": "hasMouseTracking",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setMouseTracking"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 29,
+                        "name": "tabletTracking",
+                        "read": "hasTabletTracking",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setTabletTracking"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 30,
+                        "name": "isActiveWindow",
+                        "read": "isActiveWindow",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 31,
+                        "name": "focusPolicy",
+                        "read": "focusPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::FocusPolicy",
+                        "user": false,
+                        "write": "setFocusPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 32,
+                        "name": "focus",
+                        "read": "hasFocus",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 33,
+                        "name": "contextMenuPolicy",
+                        "read": "contextMenuPolicy",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::ContextMenuPolicy",
+                        "user": false,
+                        "write": "setContextMenuPolicy"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 34,
+                        "name": "updatesEnabled",
+                        "read": "updatesEnabled",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setUpdatesEnabled"
+                    },
+                    {
+                        "constant": false,
+                        "designable": false,
+                        "final": false,
+                        "index": 35,
+                        "name": "visible",
+                        "read": "isVisible",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setVisible"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 36,
+                        "name": "minimized",
+                        "read": "isMinimized",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 37,
+                        "name": "maximized",
+                        "read": "isMaximized",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 38,
+                        "name": "fullScreen",
+                        "read": "isFullScreen",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 39,
+                        "name": "sizeHint",
+                        "read": "sizeHint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 40,
+                        "name": "minimumSizeHint",
+                        "read": "minimumSizeHint",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QSize",
+                        "user": false
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 41,
+                        "name": "acceptDrops",
+                        "read": "acceptDrops",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAcceptDrops"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 42,
+                        "name": "windowTitle",
+                        "notify": "windowTitleChanged",
+                        "read": "windowTitle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWindowTitle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 43,
+                        "name": "windowIcon",
+                        "notify": "windowIconChanged",
+                        "read": "windowIcon",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QIcon",
+                        "user": false,
+                        "write": "setWindowIcon"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 44,
+                        "name": "windowIconText",
+                        "notify": "windowIconTextChanged",
+                        "read": "windowIconText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWindowIconText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 45,
+                        "name": "windowOpacity",
+                        "read": "windowOpacity",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "double",
+                        "user": false,
+                        "write": "setWindowOpacity"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 46,
+                        "name": "windowModified",
+                        "read": "isWindowModified",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setWindowModified"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 47,
+                        "name": "toolTip",
+                        "read": "toolTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setToolTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 48,
+                        "name": "toolTipDuration",
+                        "read": "toolTipDuration",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setToolTipDuration"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 49,
+                        "name": "statusTip",
+                        "read": "statusTip",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setStatusTip"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 50,
+                        "name": "whatsThis",
+                        "read": "whatsThis",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWhatsThis"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 51,
+                        "name": "accessibleName",
+                        "read": "accessibleName",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAccessibleName"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 52,
+                        "name": "accessibleDescription",
+                        "read": "accessibleDescription",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setAccessibleDescription"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 53,
+                        "name": "layoutDirection",
+                        "read": "layoutDirection",
+                        "required": false,
+                        "reset": "unsetLayoutDirection",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::LayoutDirection",
+                        "user": false,
+                        "write": "setLayoutDirection"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 54,
+                        "name": "autoFillBackground",
+                        "read": "autoFillBackground",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAutoFillBackground"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 55,
+                        "name": "styleSheet",
+                        "read": "styleSheet",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setStyleSheet"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 56,
+                        "name": "locale",
+                        "read": "locale",
+                        "required": false,
+                        "reset": "unsetLocale",
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QLocale",
+                        "user": false,
+                        "write": "setLocale"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 57,
+                        "name": "windowFilePath",
+                        "read": "windowFilePath",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": false,
+                        "write": "setWindowFilePath"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 58,
+                        "name": "inputMethodHints",
+                        "read": "inputMethodHints",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::InputMethodHints",
+                        "user": false,
+                        "write": "setInputMethodHints"
+                    }
+                ],
+                "qualifiedClassName": "QWidget",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "title",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "windowTitleChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "icon",
+                                "type": "QIcon"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "windowIconChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "iconText",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "windowIconTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "pos",
+                                "type": "QPoint"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "customContextMenuRequested",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "setEnabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 5,
+                        "name": "setDisabled",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 6,
+                        "name": "setWindowModified",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setWindowTitle",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "styleSheet",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 8,
+                        "name": "setStyleSheet",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 9,
+                        "name": "setFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "update",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 11,
+                        "name": "repaint",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "visible",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 12,
+                        "name": "setVisible",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "hidden",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "setHidden",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 14,
+                        "name": "show",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 15,
+                        "name": "hide",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 16,
+                        "name": "showMinimized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 17,
+                        "name": "showMaximized",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 18,
+                        "name": "showFullScreen",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 19,
+                        "name": "showNormal",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "close",
+                        "returnType": "bool"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "raise",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 22,
+                        "name": "lower",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "arguments": [
+                            {
+                                "name": "query",
+                                "type": "Qt::InputMethodQuery"
+                            }
+                        ],
+                        "index": 23,
+                        "name": "updateMicroFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "protected",
+                        "index": 24,
+                        "isCloned": true,
+                        "name": "updateMicroFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 25,
+                        "name": "_q_showIfNotHidden",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 26,
+                        "name": "_q_closestWindowHandle",
+                        "returnType": "QWindow*"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    },
+                    {
+                        "access": "public",
+                        "name": "QPaintDevice"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidget.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetPrivate",
+                "enums": [
+                    {
+                        "alias": "DrawWidgetFlag",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "DrawWidgetFlags",
+                        "values": [
+                            "DrawAsRoot",
+                            "DrawPaintOnScreen",
+                            "DrawRecursive",
+                            "DrawInvisible",
+                            "DontSubtractOpaqueChildren",
+                            "DontDrawOpaqueChildren",
+                            "DontDrawNativeChildren",
+                            "DontSetCompositionMode",
+                            "UseEffectRegionBounds"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "Direction",
+                        "values": [
+                            "DirectionNorth",
+                            "DirectionEast",
+                            "DirectionSouth",
+                            "DirectionWest"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "CloseMode",
+                        "values": [
+                            "CloseNoEvent",
+                            "CloseWithEvent",
+                            "CloseWithSpontaneousEvent"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 179,
+                "qualifiedClassName": "QWidgetPrivate",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObjectPrivate"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidget_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetAction",
+                "lineNumber": 16,
+                "object": true,
+                "qualifiedClassName": "QWidgetAction",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAction"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetaction.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetAnimator",
+                "lineNumber": 30,
+                "object": true,
+                "qualifiedClassName": "QWidgetAnimator",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "animationFinished",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetanimator_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetLineControl",
+                "lineNumber": 50,
+                "object": true,
+                "qualifiedClassName": "QWidgetLineControl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "int"
+                            },
+                            {
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "displayTextChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "textEdited",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "resetInputContext",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "updateMicroFocus",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 7,
+                        "name": "accepted",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "editingFinished",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QRect"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "updateNeeded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 10,
+                        "name": "inputRejected",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 11,
+                        "name": "_q_deleteSelected",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QInputControl"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetlinecontrol_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetRepaintManager",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "UpdateTime",
+                        "values": [
+                            "UpdateNow",
+                            "UpdateLater"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "BufferState",
+                        "values": [
+                            "BufferValid",
+                            "BufferInvalid"
+                        ]
+                    }
+                ],
+                "gadget": true,
+                "lineNumber": 30,
+                "qualifiedClassName": "QWidgetRepaintManager"
+            }
+        ],
+        "inputFile": "qwidgetrepaintmanager_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetResizeHandler",
+                "lineNumber": 29,
+                "object": true,
+                "qualifiedClassName": "QWidgetResizeHandler",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "activate",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetresizehandler_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetTextControl",
+                "lineNumber": 50,
+                "methods": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "type",
+                                "type": "int"
+                            },
+                            {
+                                "name": "name",
+                                "type": "QUrl"
+                            }
+                        ],
+                        "index": 36,
+                        "name": "loadResource",
+                        "returnType": "QVariant"
+                    }
+                ],
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "html",
+                        "notify": "textChanged",
+                        "read": "toHtml",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "QString",
+                        "user": true,
+                        "write": "setHtml"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "overwriteMode",
+                        "read": "overwriteMode",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOverwriteMode"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "acceptRichText",
+                        "read": "acceptRichText",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setAcceptRichText"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "cursorWidth",
+                        "read": "cursorWidth",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCursorWidth"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "textInteractionFlags",
+                        "read": "textInteractionFlags",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextInteractionFlags",
+                        "user": false,
+                        "write": "setTextInteractionFlags"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "openExternalLinks",
+                        "read": "openExternalLinks",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setOpenExternalLinks"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 6,
+                        "name": "ignoreUnusedNavigationEvents",
+                        "read": "ignoreUnusedNavigationEvents",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "bool",
+                        "user": false,
+                        "write": "setIgnoreUnusedNavigationEvents"
+                    }
+                ],
+                "qualifiedClassName": "QWidgetTextControl",
+                "signals": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "textChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 1,
+                        "name": "undoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "redoAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "format",
+                                "type": "QTextCharFormat"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "currentCharFormatChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "b",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "copyAvailable",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "selectionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "cursorPositionChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "updateRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "isCloned": true,
+                        "name": "updateRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QSizeF"
+                            }
+                        ],
+                        "index": 9,
+                        "name": "documentSizeChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "newBlockCount",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 10,
+                        "name": "blockCountChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "rect",
+                                "type": "QRectF"
+                            }
+                        ],
+                        "index": 11,
+                        "name": "visibilityRequest",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 12,
+                        "name": "microFocusChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "link",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 13,
+                        "name": "linkActivated",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 14,
+                        "name": "linkHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "block",
+                                "type": "QTextBlock"
+                            }
+                        ],
+                        "index": 15,
+                        "name": "blockMarkerHovered",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "m",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 16,
+                        "name": "modificationChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 17,
+                        "name": "setPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 18,
+                        "name": "setMarkdown",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 19,
+                        "name": "setHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 20,
+                        "name": "cut",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 21,
+                        "name": "copy",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "mode",
+                                "type": "QClipboard::Mode"
+                            }
+                        ],
+                        "index": 22,
+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 23,
+                        "isCloned": true,
+                        "name": "paste",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 24,
+                        "name": "undo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 25,
+                        "name": "redo",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 26,
+                        "name": "clear",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 27,
+                        "name": "selectAll",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 28,
+                        "name": "insertPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 29,
+                        "name": "insertHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 30,
+                        "name": "append",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "html",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 31,
+                        "name": "appendHtml",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "text",
+                                "type": "QString"
+                            }
+                        ],
+                        "index": 32,
+                        "name": "appendPlainText",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 33,
+                        "name": "adjustSize",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 34,
+                        "name": "_q_deleteSelected",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 35,
+                        "name": "_q_copyLink",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QInputControl"
+                    }
+                ]
+            },
+            {
+                "className": "QUnicodeControlCharacterMenu",
+                "lineNumber": 249,
+                "object": true,
+                "qualifiedClassName": "QUnicodeControlCharacterMenu",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "menuActionTriggered",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QMenu"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgettextcontrol_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWidgetWindow",
+                "lineNumber": 34,
+                "object": true,
+                "qualifiedClassName": "QWidgetWindow",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "updateObjectName",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWindow"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetwindow_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowContainer",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QWindowContainer",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowcontainer_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWindowsStyle",
+                "lineNumber": 28,
+                "object": true,
+                "qualifiedClassName": "QWindowsStyle",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QCommonStyle"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwindowsstyle_p.h",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWizard",
+                "enums": [
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WizardStyle",
+                        "values": [
+                            "ClassicStyle",
+                            "ModernStyle",
+                            "MacStyle",
+                            "AeroStyle",
+                            "NStyles"
+                        ]
+                    },
+                    {
+                        "isClass": false,
+                        "isFlag": false,
+                        "name": "WizardOption",
+                        "values": [
+                            "IndependentPages",
+                            "IgnoreSubTitles",
+                            "ExtendedWatermarkPixmap",
+                            "NoDefaultButton",
+                            "NoBackButtonOnStartPage",
+                            "NoBackButtonOnLastPage",
+                            "DisabledBackButtonOnLastPage",
+                            "HaveNextButtonOnLastPage",
+                            "HaveFinishButtonOnEarlyPages",
+                            "NoCancelButton",
+                            "CancelButtonOnLeft",
+                            "HaveHelpButton",
+                            "HelpButtonOnRight",
+                            "HaveCustomButton1",
+                            "HaveCustomButton2",
+                            "HaveCustomButton3",
+                            "NoCancelButtonOnLastPage"
+                        ]
+                    },
+                    {
+                        "alias": "WizardOption",
+                        "isClass": false,
+                        "isFlag": true,
+                        "name": "WizardOptions",
+                        "values": [
+                            "IndependentPages",
+                            "IgnoreSubTitles",
+                            "ExtendedWatermarkPixmap",
+                            "NoDefaultButton",
+                            "NoBackButtonOnStartPage",
+                            "NoBackButtonOnLastPage",
+                            "DisabledBackButtonOnLastPage",
+                            "HaveNextButtonOnLastPage",
+                            "HaveFinishButtonOnEarlyPages",
+                            "NoCancelButton",
+                            "CancelButtonOnLeft",
+                            "HaveHelpButton",
+                            "HelpButtonOnRight",
+                            "HaveCustomButton1",
+                            "HaveCustomButton2",
+                            "HaveCustomButton3",
+                            "NoCancelButtonOnLastPage"
+                        ]
+                    }
+                ],
+                "lineNumber": 18,
+                "object": true,
+                "properties": [
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 0,
+                        "name": "wizardStyle",
+                        "read": "wizardStyle",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WizardStyle",
+                        "user": false,
+                        "write": "setWizardStyle"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 1,
+                        "name": "options",
+                        "read": "options",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "WizardOptions",
+                        "user": false,
+                        "write": "setOptions"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 2,
+                        "name": "titleFormat",
+                        "read": "titleFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextFormat",
+                        "user": false,
+                        "write": "setTitleFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 3,
+                        "name": "subTitleFormat",
+                        "read": "subTitleFormat",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "Qt::TextFormat",
+                        "user": false,
+                        "write": "setSubTitleFormat"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 4,
+                        "name": "startId",
+                        "read": "startId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setStartId"
+                    },
+                    {
+                        "constant": false,
+                        "designable": true,
+                        "final": false,
+                        "index": 5,
+                        "name": "currentId",
+                        "notify": "currentIdChanged",
+                        "read": "currentId",
+                        "required": false,
+                        "scriptable": true,
+                        "stored": true,
+                        "type": "int",
+                        "user": false,
+                        "write": "setCurrentId"
+                    }
+                ],
+                "qualifiedClassName": "QWizard",
+                "signals": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "currentIdChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 1,
+                        "name": "helpRequested",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "which",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "customButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "pageAdded",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 4,
+                        "name": "pageRemoved",
+                        "returnType": "void"
+                    }
+                ],
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 5,
+                        "name": "back",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 6,
+                        "name": "next",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "id",
+                                "type": "int"
+                            }
+                        ],
+                        "index": 7,
+                        "name": "setCurrentId",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "public",
+                        "index": 8,
+                        "name": "restart",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 9,
+                        "name": "_q_emitCustomButtonClicked",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 10,
+                        "name": "_q_updateButtonStates",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "type": "QObject*"
+                            }
+                        ],
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+                        "name": "QAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtabbar.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTableCornerButton",
+                "lineNumber": 551,
+                "object": true,
+                "qualifiedClassName": "QTableCornerButton",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtableview.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QToolBoxButton",
+                "lineNumber": 25,
+                "object": true,
+                "qualifiedClassName": "QToolBoxButton",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractButton"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtoolbox.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QTipLabel",
+                "lineNumber": 90,
+                "object": true,
+                "qualifiedClassName": "QTipLabel",
+                "slots": [
+                    {
+                        "access": "public",
+                        "index": 0,
+                        "name": "styleSheetParentDestroyed",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QLabel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qtooltip.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QUndoModel",
+                "lineNumber": 17,
+                "object": true,
+                "qualifiedClassName": "QUndoModel",
+                "slots": [
+                    {
+                        "access": "public",
+                        "arguments": [
+                            {
+                                "name": "stack",
+                                "type": "QUndoStack*"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "setStack",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "index": 1,
+                        "name": "stackChanged",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "obj",
+                                "type": "QObject*"
+                            }
+                        ],
+                        "index": 2,
+                        "name": "stackDestroyed",
+                        "returnType": "void"
+                    },
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "index",
+                                "type": "QModelIndex"
+                            }
+                        ],
+                        "index": 3,
+                        "name": "setStackCurrentIndex",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAbstractItemModel"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qundoview.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QWhatsThat",
+                "lineNumber": 100,
+                "object": true,
+                "qualifiedClassName": "QWhatsThat",
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QWidget"
+                    }
+                ]
+            },
+            {
+                "className": "QWhatsThisAction",
+                "lineNumber": 447,
+                "object": true,
+                "qualifiedClassName": "QWhatsThisAction",
+                "slots": [
+                    {
+                        "access": "private",
+                        "index": 0,
+                        "name": "actionTriggered",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QAction"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwhatsthis.cpp",
+        "outputRevision": 68
+    },
+    {
+        "classes": [
+            {
+                "className": "QPlatformTextureListWatcher",
+                "lineNumber": 38,
+                "object": true,
+                "qualifiedClassName": "QPlatformTextureListWatcher",
+                "slots": [
+                    {
+                        "access": "private",
+                        "arguments": [
+                            {
+                                "name": "locked",
+                                "type": "bool"
+                            }
+                        ],
+                        "index": 0,
+                        "name": "onLockStatusChanged",
+                        "returnType": "void"
+                    }
+                ],
+                "superClasses": [
+                    {
+                        "access": "public",
+                        "name": "QObject"
+                    }
+                ]
+            }
+        ],
+        "inputFile": "qwidgetrepaintmanager.cpp",
+        "outputRevision": 68
+    }
+]
diff --git a/qt/6.8.1/msvc2022_64/metatypes/qt6xml_metatypes.json b/qt/6.8.1/msvc2022_64/metatypes/qt6xml_metatypes.json
new file mode 100644
index 0000000000000000000000000000000000000000..0d4f101c7a37a4c875e6999bee1a287fdb733380
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/metatypes/qt6xml_metatypes.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/qt/6.8.1/msvc2022_64/mkspecs/REUSE.toml b/qt/6.8.1/msvc2022_64/mkspecs/REUSE.toml
new file mode 100644
index 0000000000000000000000000000000000000000..6f4d70f3ec773643c82e3ddac37bab098247c80f
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/mkspecs/REUSE.toml
@@ -0,0 +1,20 @@
+version = 1
+
+[[annotations]]
+path = ["**.plist*", "features/data/configure.json", "features/data/testserver/Dockerfile",
+        "features/data/testserver/docker-compose-common.yml", "features/mac/sdk.mk",
+        "features/uikit/xcodebuild.mk", "features/data/dummy.cpp", "features/data/macros.cpp",
+        "macx-ios-clang/LaunchScreen.storyboard", "macx-xcode/WorkspaceSettings.xcsettings",
+        "macx-xcode/default.xcscheme"]
+precedence = "closest"
+comment = "build system"
+SPDX-FileCopyrightText = "Copyright (C) 2024 The Qt Company Ltd."
+SPDX-License-Identifier = "BSD-3-Clause"
+
+[[annotations]]
+path = ["modules/README"]
+comment = "documentation"
+precedence = "closest"
+SPDX-FileCopyrightText = "Copyright (C) 2024 The Qt Company Ltd."
+SPDX-License-Identifier = "LicenseRef-Qt-Commercial OR GFDL-1.3-no-invariants-only"
+
diff --git a/qt/6.8.1/msvc2022_64/mkspecs/qconfig.pri b/qt/6.8.1/msvc2022_64/mkspecs/qconfig.pri
new file mode 100644
index 0000000000000000000000000000000000000000..0af9ca32b0ea99a6c1e44187e6c610f2cf437fe8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/mkspecs/qconfig.pri
@@ -0,0 +1,16 @@
+QT_ARCH = x86_64
+QT_BUILDABI = x86_64-little_endian-lp64
+QT_LIBCPP_ABI_TAG = 
+QT.global.enabled_features = version_tagging shared debug_and_release signaling_nan thread future concurrent dbus opensslv30 shared intelcet shared debug_and_release openssl
+QT.global.disabled_features = static cross_compile pkg-config separate_debug_info appstore-compliant simulator_and_device rpath force_asserts framework c++20 c++2a c++2b reduce_relocations wasm-simd128 wasm-exceptions zstd openssl-linked opensslv11
+QT.global.disabled_features += release build_all
+QT_CONFIG += shared no-pkg-config debug_and_release openssl release debug
+CONFIG +=  shared plugin_manifest intelcet
+QT_VERSION = 6.8.1
+QT_MAJOR_VERSION = 6
+QT_MINOR_VERSION = 8
+QT_PATCH_VERSION = 1
+
+QT_MSVC_MAJOR_VERSION = 19
+QT_MSVC_MINOR_VERSION = 39
+QT_MSVC_PATCH_VERSION = 33520
diff --git a/qt/6.8.1/msvc2022_64/mkspecs/qmodule.pri b/qt/6.8.1/msvc2022_64/mkspecs/qmodule.pri
new file mode 100644
index 0000000000000000000000000000000000000000..f10469a8de0e2dfe97ef68687ca3ed7251ae3867
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/mkspecs/qmodule.pri
@@ -0,0 +1,7 @@
+QT_CPU_FEATURES.x86_64 = 
+QT.global_private.enabled_features = debug x86intrin sse2 sse3 ssse3 sse4_1 sse4_2 avx f16c avx2 avx512f avx512er avx512cd avx512pf avx512dq avx512bw avx512vl avx512ifma avx512vbmi avx512vbmi2 aesni vaes rdrnd rdseed shani localtime_s alloca_malloc_h alloca dbus gui network printsupport sql testlib widgets xml openssl relocatable intelcet msvc_obj_debug_info force_debug_info largefile precompile_header sse2 sse3 ssse3 sse4_1 sse4_2 avx f16c avx2 avx512f avx512er avx512cd avx512pf avx512dq avx512bw avx512vl avx512ifma avx512vbmi avx512vbmi2 aesni vaes rdrnd rdseed shani
+QT.global_private.disabled_features = use_bfd_linker use_gold_linker use_lld_linker use_mold_linker android-style-assets gc_binaries developer-build private_tests elf_private_full_version reduce_exports no_direct_extern_access mips_dsp mips_dspr2 neon arm_crc32 arm_crypto localtime_r posix_fallocate alloca_h system-zlib stdlib-libcpp dbus-linked libudev dlopen glibc_fortify_source trivial_auto_var_init_pattern stack_protector stack_clash_protection libstdcpp_assertions libcpp_hardening relro_now_linker
+CONFIG += msvc_obj_debug_info force_debug_info largefile precompile_header sse2 sse3 ssse3 sse4_1 sse4_2 avx f16c avx2 avx512f avx512er avx512cd avx512pf avx512dq avx512bw avx512vl avx512ifma avx512vbmi avx512vbmi2 aesni vaes rdrnd rdseed shani
+QT_COORD_TYPE = double
+QT_BUILD_PARTS = libs tools
+
diff --git a/qt/6.8.1/msvc2022_64/modules/Concurrent.json b/qt/6.8.1/msvc2022_64/modules/Concurrent.json
new file mode 100644
index 0000000000000000000000000000000000000000..a2e9a0d9bbe7e7a067d6861a3e620eda4eda148b
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Concurrent.json
@@ -0,0 +1,13 @@
+{
+    "name": "Concurrent",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Core.json b/qt/6.8.1/msvc2022_64/modules/Core.json
new file mode 100644
index 0000000000000000000000000000000000000000..59cac42bfe74aff012d49bfbb92c51e4d91b2759
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Core.json
@@ -0,0 +1,13 @@
+{
+    "name": "Core",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/DBus.json b/qt/6.8.1/msvc2022_64/modules/DBus.json
new file mode 100644
index 0000000000000000000000000000000000000000..bfb69ae316d84f6ee1e19ad80248c96d20935c87
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/DBus.json
@@ -0,0 +1,13 @@
+{
+    "name": "DBus",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Designer.json b/qt/6.8.1/msvc2022_64/modules/Designer.json
new file mode 100644
index 0000000000000000000000000000000000000000..7d030d37766a4fb1ea2b1295735db9201a4a8160
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Designer.json
@@ -0,0 +1,14 @@
+{
+    "name": "Designer",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "plugin_types": ["designer"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/DesignerComponentsPrivate.json b/qt/6.8.1/msvc2022_64/modules/DesignerComponentsPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e8addd3d2f14f47d3e22f89c82a7085c353da76
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/DesignerComponentsPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "DesignerComponentsPrivate",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/DeviceDiscoverySupportPrivate.json b/qt/6.8.1/msvc2022_64/modules/DeviceDiscoverySupportPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..6f10728e1ca61d58be7fe95c053f5bdd4feb9c53
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/DeviceDiscoverySupportPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "DeviceDiscoverySupportPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/EntryPointPrivate.json b/qt/6.8.1/msvc2022_64/modules/EntryPointPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..116ada0f29362a25b063c16cea644242b2d26e2f
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/EntryPointPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "EntryPointPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/ExampleIconsPrivate.json b/qt/6.8.1/msvc2022_64/modules/ExampleIconsPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..6119ea7a643f889739d6ec8d13b05741b0ec06c1
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/ExampleIconsPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "ExampleIconsPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/ExamplesAssetDownloaderPrivate.json b/qt/6.8.1/msvc2022_64/modules/ExamplesAssetDownloaderPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..fff1f29e0cce740115a93b37e6d5d2daf85ab541
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/ExamplesAssetDownloaderPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "ExamplesAssetDownloaderPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/FbSupportPrivate.json b/qt/6.8.1/msvc2022_64/modules/FbSupportPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c604cec537a61e2fb11c58dac05ad1a3fc5aa97
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/FbSupportPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "FbSupportPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/FreetypePrivate.json b/qt/6.8.1/msvc2022_64/modules/FreetypePrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..290ed5d131dfe13932a7076baf16d07734883863
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/FreetypePrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "FreetypePrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Gui.json b/qt/6.8.1/msvc2022_64/modules/Gui.json
new file mode 100644
index 0000000000000000000000000000000000000000..1246c7c2df8f95b4c9dd92c2dc53aff398354643
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Gui.json
@@ -0,0 +1,14 @@
+{
+    "name": "Gui",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "plugin_types": ["accessiblebridge", "platforms", "platforms/darwin", "xcbglintegrations", "platformthemes", "platforminputcontexts", "generic", "iconengines", "imageformats", "egldeviceintegrations"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/HarfbuzzPrivate.json b/qt/6.8.1/msvc2022_64/modules/HarfbuzzPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..75906e0372fc7465759d41530d5e687d7427611b
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/HarfbuzzPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "HarfbuzzPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Help.json b/qt/6.8.1/msvc2022_64/modules/Help.json
new file mode 100644
index 0000000000000000000000000000000000000000..6340b5c5eda0638a91f8f07eb56b1e65c032d8c5
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Help.json
@@ -0,0 +1,14 @@
+{
+    "name": "Help",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "plugin_types": ["help"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/JpegPrivate.json b/qt/6.8.1/msvc2022_64/modules/JpegPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..8cd9bff4a5a40261b1742428636f175df88d43bb
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/JpegPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "JpegPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsAnimation.json b/qt/6.8.1/msvc2022_64/modules/LabsAnimation.json
new file mode 100644
index 0000000000000000000000000000000000000000..4610fe931648733f4cd74d3511159301fa6f2549
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsAnimation.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsAnimation",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsFolderListModel.json b/qt/6.8.1/msvc2022_64/modules/LabsFolderListModel.json
new file mode 100644
index 0000000000000000000000000000000000000000..9e0636303f7460887384acbcc7a0d6936af9fb86
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsFolderListModel.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsFolderListModel",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_version": "19.39.33520.0",
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+        "target_system": "Windows",
+        "architecture": "x86_64"
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsPlatform.json b/qt/6.8.1/msvc2022_64/modules/LabsPlatform.json
new file mode 100644
index 0000000000000000000000000000000000000000..6951bfe3420fc7946ec45a8f6ac8d212953fce99
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsPlatform.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsPlatform",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsQmlModels.json b/qt/6.8.1/msvc2022_64/modules/LabsQmlModels.json
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index 0000000000000000000000000000000000000000..9fadb3ef31e5aada8386d175e07bf6af6b58bd1a
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsQmlModels.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsQmlModels",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsSettings.json b/qt/6.8.1/msvc2022_64/modules/LabsSettings.json
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index 0000000000000000000000000000000000000000..02823dd6a4d14e300934b4f00f03bcc3cb886251
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsSettings.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsSettings",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
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index 0000000000000000000000000000000000000000..71e3e9adb8acbe899833826fce1a0bb3eb1e4117
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsSharedImage.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsSharedImage",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/LabsWavefrontMesh.json b/qt/6.8.1/msvc2022_64/modules/LabsWavefrontMesh.json
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index 0000000000000000000000000000000000000000..fdbdcf484ce84b29262a0ce50677e01857f53173
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/LabsWavefrontMesh.json
@@ -0,0 +1,13 @@
+{
+    "name": "LabsWavefrontMesh",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Linguist.json b/qt/6.8.1/msvc2022_64/modules/Linguist.json
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index 0000000000000000000000000000000000000000..32978e557a05feea065e5ab7f2b79fba1bf4b652
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Linguist.json
@@ -0,0 +1,13 @@
+{
+    "name": "Linguist",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Network.json b/qt/6.8.1/msvc2022_64/modules/Network.json
new file mode 100644
index 0000000000000000000000000000000000000000..3caa7ab9e68f4a55314fecd9a78045d36f650600
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Network.json
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+{
+    "name": "Network",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "plugin_types": ["networkaccess", "networkinformation", "tls"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/OpenGL.json b/qt/6.8.1/msvc2022_64/modules/OpenGL.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/OpenGL.json
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+{
+    "name": "OpenGL",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/OpenGLWidgets.json b/qt/6.8.1/msvc2022_64/modules/OpenGLWidgets.json
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index 0000000000000000000000000000000000000000..797d171032d06ed26b6c43614b3b710b51ff65fb
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/OpenGLWidgets.json
@@ -0,0 +1,13 @@
+{
+    "name": "OpenGLWidgets",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/PacketProtocolPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "PacketProtocolPrivate",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/PngPrivate.json b/qt/6.8.1/msvc2022_64/modules/PngPrivate.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/PngPrivate.json
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+{
+    "name": "PngPrivate",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/PrintSupport.json b/qt/6.8.1/msvc2022_64/modules/PrintSupport.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/PrintSupport.json
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+{
+    "name": "PrintSupport",
+    "repository": "qtbase",
+    "version": "6.8.1",
+    "plugin_types": ["printsupport"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QDocCatchConversionsPrivate.json b/qt/6.8.1/msvc2022_64/modules/QDocCatchConversionsPrivate.json
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index 0000000000000000000000000000000000000000..ea3c24284ba00103ac42cf568659be9eef179c91
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QDocCatchConversionsPrivate.json
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+{
+    "name": "QDocCatchConversionsPrivate",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QDocCatchGeneratorsPrivate.json b/qt/6.8.1/msvc2022_64/modules/QDocCatchGeneratorsPrivate.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QDocCatchGeneratorsPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "QDocCatchGeneratorsPrivate",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QDocCatchPrivate.json b/qt/6.8.1/msvc2022_64/modules/QDocCatchPrivate.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QDocCatchPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "QDocCatchPrivate",
+    "repository": "qttools",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Qml.json b/qt/6.8.1/msvc2022_64/modules/Qml.json
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index 0000000000000000000000000000000000000000..cd471e3eeff5e8b4399c62d8e89da3d442f13446
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Qml.json
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+{
+    "name": "Qml",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "plugin_types": ["qmltooling"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlAssetDownloader.json b/qt/6.8.1/msvc2022_64/modules/QmlAssetDownloader.json
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index 0000000000000000000000000000000000000000..c0f425d6c806cfe5e3910d9467de172cc3f5e939
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlAssetDownloader.json
@@ -0,0 +1,13 @@
+{
+    "name": "QmlAssetDownloader",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlCompiler.json b/qt/6.8.1/msvc2022_64/modules/QmlCompiler.json
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index 0000000000000000000000000000000000000000..b7cb122aa91ba39f9eb4c798850f81e4086fe97a
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlCompiler.json
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+{
+    "name": "QmlCompiler",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "plugin_types": ["qmllint"],
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
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+        "target_system": "Windows",
+        "architecture": "x86_64"
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlCore.json b/qt/6.8.1/msvc2022_64/modules/QmlCore.json
new file mode 100644
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlCore.json
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+{
+    "name": "QmlCore",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlDebugPrivate.json b/qt/6.8.1/msvc2022_64/modules/QmlDebugPrivate.json
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@@ -0,0 +1,14 @@
+{
+    "name": "QmlDebugPrivate",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
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+        "compiler_target": "",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlDomPrivate.json b/qt/6.8.1/msvc2022_64/modules/QmlDomPrivate.json
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+++ b/qt/6.8.1/msvc2022_64/modules/QmlDomPrivate.json
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+{
+    "name": "QmlDomPrivate",
+    "repository": "qtdeclarative",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlIntegration.json b/qt/6.8.1/msvc2022_64/modules/QmlIntegration.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlIntegration.json
@@ -0,0 +1,13 @@
+{
+    "name": "QmlIntegration",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlLSPrivate.json b/qt/6.8.1/msvc2022_64/modules/QmlLSPrivate.json
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+{
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+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "plugin_types": ["qmlls"],
+    "internal": true,
+    "built_with": {
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlLocalStorage.json b/qt/6.8.1/msvc2022_64/modules/QmlLocalStorage.json
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index 0000000000000000000000000000000000000000..1d52c55c1f2fcf188a89aed120f124e29586ad85
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlLocalStorage.json
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+{
+    "name": "QmlLocalStorage",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
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+        "compiler_version": "19.39.33520.0",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlMeta.json b/qt/6.8.1/msvc2022_64/modules/QmlMeta.json
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlMeta.json
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+{
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlModels.json b/qt/6.8.1/msvc2022_64/modules/QmlModels.json
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index 0000000000000000000000000000000000000000..e9e490c5badcb57c8253fe769e54f361423f9365
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlModels.json
@@ -0,0 +1,13 @@
+{
+    "name": "QmlModels",
+    "repository": "qtdeclarative",
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+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlNetwork.json b/qt/6.8.1/msvc2022_64/modules/QmlNetwork.json
new file mode 100644
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--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlNetwork.json
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+{
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+    "repository": "qtdeclarative",
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+        "target_system": "Windows",
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+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlToolingSettingsPrivate.json b/qt/6.8.1/msvc2022_64/modules/QmlToolingSettingsPrivate.json
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--- /dev/null
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@@ -0,0 +1,14 @@
+{
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+        "target_system": "Windows",
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+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlTypeRegistrarPrivate.json b/qt/6.8.1/msvc2022_64/modules/QmlTypeRegistrarPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..c2dff50c3c8d228ce4c99e7c070ad308abc13a7b
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlTypeRegistrarPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "QmlTypeRegistrarPrivate",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlWorkerScript.json b/qt/6.8.1/msvc2022_64/modules/QmlWorkerScript.json
new file mode 100644
index 0000000000000000000000000000000000000000..adca19f0b47a1bc8757b716d17a8aeee7a9c589e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlWorkerScript.json
@@ -0,0 +1,13 @@
+{
+    "name": "QmlWorkerScript",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QmlXmlListModel.json b/qt/6.8.1/msvc2022_64/modules/QmlXmlListModel.json
new file mode 100644
index 0000000000000000000000000000000000000000..8690da65ca290b60ce8091b9e8ec5fe5fca204dc
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QmlXmlListModel.json
@@ -0,0 +1,13 @@
+{
+    "name": "QmlXmlListModel",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/Quick.json b/qt/6.8.1/msvc2022_64/modules/Quick.json
new file mode 100644
index 0000000000000000000000000000000000000000..3f8f98c02fcb8ca48e56408d8e1db154c12601b2
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/Quick.json
@@ -0,0 +1,14 @@
+{
+    "name": "Quick",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "plugin_types": ["scenegraph"],
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2.json
new file mode 100644
index 0000000000000000000000000000000000000000..f916a8d0e6ee469a52ff55b0c0349c17c4537f02
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Basic.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Basic.json
new file mode 100644
index 0000000000000000000000000000000000000000..9782cc26fc9ec1e569f9d08a1101bbc1699f3b44
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Basic.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Basic",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2BasicStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2BasicStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..a9fe009f198e4adb43b049167905bba5e62e434e
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2BasicStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2BasicStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2FluentWinUI3StyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2FluentWinUI3StyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..f8227ee72da34179aa6aa300d00aaf0b55fa90e8
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2FluentWinUI3StyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2FluentWinUI3StyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Fusion.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Fusion.json
new file mode 100644
index 0000000000000000000000000000000000000000..047a517034c3eebde7ab691e3313b0c07b7a3e0d
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Fusion.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Fusion",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2FusionStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2FusionStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..d2a731d5b487381f834c6790552b96903c1b0e61
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2FusionStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2FusionStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Imagine.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Imagine.json
new file mode 100644
index 0000000000000000000000000000000000000000..18b79ea96aca7df836b0ea168ba2815af3fc4356
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Imagine.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Imagine",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2ImagineStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2ImagineStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..c26350ac38781e3956810d0d597cc72cbb688290
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2ImagineStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2ImagineStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Impl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Impl.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ac2a6a9be23c35290caaa2eefe15992828f4a2c
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Impl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Impl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Material.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Material.json
new file mode 100644
index 0000000000000000000000000000000000000000..e8cac863aa16464557898f0dacf6e3278227add5
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Material.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Material",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2MaterialStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2MaterialStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..ca8bf58871e26a192522cfec463c9778e05ea1b3
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2MaterialStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2MaterialStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2Universal.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2Universal.json
new file mode 100644
index 0000000000000000000000000000000000000000..2ee2330668ab82976e49184bc79012d6463b37cd
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2Universal.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2Universal",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2UniversalStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2UniversalStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..178c781b874e46193c28738a6971b518cb692345
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2UniversalStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2UniversalStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControls2WindowsStyleImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickControls2WindowsStyleImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..e238c0319ecf4a3cfc77483311d5157ff56cdd2c
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControls2WindowsStyleImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickControls2WindowsStyleImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickControlsTestUtilsPrivate.json b/qt/6.8.1/msvc2022_64/modules/QuickControlsTestUtilsPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..60022f438e834dcc3e1fa0759076e1a2bff7a610
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickControlsTestUtilsPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "QuickControlsTestUtilsPrivate",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickDialogs2.json b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2.json
new file mode 100644
index 0000000000000000000000000000000000000000..956b510ec9b03c26f43473ffb7f9b44bdd81f103
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickDialogs2",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickDialogs2QuickImpl.json b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2QuickImpl.json
new file mode 100644
index 0000000000000000000000000000000000000000..01d6b7f2838de41ded1d739ef4fae0a40c23b817
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2QuickImpl.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickDialogs2QuickImpl",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickDialogs2Utils.json b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2Utils.json
new file mode 100644
index 0000000000000000000000000000000000000000..e0a234c071f6121775e9e41dad764e4dd1b03728
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickDialogs2Utils.json
@@ -0,0 +1,13 @@
+{
+    "name": "QuickDialogs2Utils",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}
diff --git a/qt/6.8.1/msvc2022_64/modules/QuickEffectsPrivate.json b/qt/6.8.1/msvc2022_64/modules/QuickEffectsPrivate.json
new file mode 100644
index 0000000000000000000000000000000000000000..cf22150c923e1361ebe001fce156e5ff13e4e4fe
--- /dev/null
+++ b/qt/6.8.1/msvc2022_64/modules/QuickEffectsPrivate.json
@@ -0,0 +1,14 @@
+{
+    "name": "QuickEffectsPrivate",
+    "repository": "qtdeclarative",
+    "version": "6.8.1",
+    "internal": true,
+    "built_with": {
+        "compiler_id": "MSVC",
+        "compiler_target": "",
+        "compiler_version": "19.39.33520.0",
+        "cross_compiled": false,
+        "target_system": "Windows",
+        "architecture": "x86_64"
+    }
+}